diff --git a/Cora_Preprocessing/cora.py b/Cora_Preprocessing/cora.py
deleted file mode 100644
index cb8520a9592145f63bd5801d8436e15d58058cc1..0000000000000000000000000000000000000000
--- a/Cora_Preprocessing/cora.py
+++ /dev/null
@@ -1,131 +0,0 @@
-"""
-Getting a networkx graph from Cora. Graph can be saved in txt file. CARE: numpy-arrays are converted to lists due to errors (NumPy array is not JSON serializable).
-Initialize Embeddings for n dimensions with initialize-module.
-Arrays are initialized in normal or uniform random format (default = normal).
-
-
-#Usage
-get_graph(path_nodes="/home/utaemon/SP/cora/cora.content", path_edges="/home/utaemon/SP/cora/cora.cites")
--> return graph with nodes and edges
-To write the graph informations in file:
-def write_graph_to_file(path_nodes="/home/utaemon/SP/cora/cora.content", path_edges="/home/utaemon/SP/cora/cora.cites", path_output_graph = "/home/utaemon/SP/")
-To write the dictionary with initalizing Embeddings in file:
-def write_dict_to_file(rand_type="normal_random", dimension = 128, quantity=1433, path_output_emb = "/home/utaemon/SP/")
-"""
-
-import networkx as nx
-import numpy as np
-import initialize
-import pickle as pkl
-
-def list_of_classes():
-    return ["Case_Based", "Genetic_Algorithms", "Neural_Networks", "Probabilistic_Methods", "Reinforcement_Learning", "Rule_Learning", "Theory"]
-
-def read_file_and_get_nodes(graph_name, path="/home/utaemon/SP/cora/cora.content"):
-    class_list = list_of_classes()
-    max_bow_len = 0
-    node_mapping = {}
-    length_array = np.empty((0))
-    with open(path) as file:
-        counter = 0
-        for line in file.readlines():
-            split_line = np.array(line.split())
-            paper_id, split_line = split_line[0], split_line[1:]
-            node_mapping[paper_id] = counter
-            paper_id = counter
-            counter += 1
-            paper_class, all_bow_of_paper = split_line[-1], split_line[:-1]
-            paper_bow = np.where(all_bow_of_paper == "1")               #get indices which words occur
-            length_array = np.append(length_array, len(paper_bow[0]))
-            if len(paper_bow[0]) > max_bow_len:
-                max_bow_len = len(paper_bow[0])
-            paper_class = class_list.index(paper_class)                 #get index of class to numeralize
-            #add infos to Graph
-            graph_name.add_node(int(paper_id))
-            graph_name.node[int(paper_id)]["class"] = paper_class
-            graph_name.node[int(paper_id)]["bow"] = paper_bow[0]
-            graph_name.node[int(paper_id)]["paper_id"] = [paper_id]
-    graph_name.graph["bow"]={"maxlen": max_bow_len, "vocab": 1433, "lengths": length_array}
-    graph_name.graph["paper_id"] = {"maxlen": 1, "vocab": (len(graph_name)), "lengths": np.ones(len(graph_name))}
-    return node_mapping
-
-def read_file_and_get_edges(graph_name, node_mapping, path="/home/utaemon/SP/cora/cora.cites"):
-    with open(path) as file:
-        for line in file.readlines():
-            a, b = line.split()
-            graph_name.add_edge(node_mapping[a],node_mapping[b])
-
-#---------------------create graph--------------
-
-
-def get_graph(path_nodes, path_edges):
-    Cora_graph = nx.Graph()
-    node_mapping = read_file_and_get_nodes(Cora_graph, path_nodes)
-    read_file_and_get_edges(Cora_graph, node_mapping, path_edges)
-    return Cora_graph
-
-#----------for getting maxima--------
-def get_neighbours_dict(path_nodes, path_edges):
-    dict_neighbours = {}
-    for edge in get_graph(path_nodes, path_edges).edges:
-        if edge[0] not in dict_neighbours:
-            dict_neighbours[edge[0]] = {edge[1]}
-        else:
-            dict_neighbours[edge[0]].add(edge[1])
-        if edge[1] not in dict_neighbours:
-            dict_neighbours[edge[1]] = {edge[0]}
-        else:
-            dict_neighbours[edge[1]].add(edge[0])
-    return dict_neighbours
-
-def get_node_bow_len(path_nodes, path_edges):
-    bow_len_dict = {}
-    nodes = get_graph(path_nodes, path_edges).nodes(data=True)
-    for node in nodes:
-        bow_len_dict[node[0]] = len(node[1]["bow"])             #node[0] = paper_id, node[1] contains node information
-    return bow_len_dict
-
-def get_max_neighbours(path_nodes, path_edges):
-    neighbours_dict = get_neighbours_dict(path_nodes, path_edges)
-    max_neighbours = 0
-    for key in neighbours_dict:
-        if len(neighbours_dict[key]) > max_neighbours:
-            max_neighbours = len(neighbours_dict[key])
-    return max_neighbours
-
-def get_max_bow_neighbours(path_nodes, path_edges):
-    node_bow_len_dict = get_node_bow_len(path_nodes, path_edges)
-    neighbours_dict = get_neighbours_dict(path_nodes, path_edges)
-    max_neighbour_bow_len = 0
-    for key in neighbours_dict:
-        temp_bow_max_len = 0
-        for neighbour in neighbours_dict[key]:
-            temp_bow_max_len += node_bow_len_dict[neighbour]
-        if temp_bow_max_len > max_neighbour_bow_len:
-            max_neighbour_bow_len = temp_bow_max_len
-    return max_neighbour_bow_len
-
-def add_max_values_to_graph(path_nodes, path_edges):                    #update Graph with max values
-    Cora_graph = get_graph(path_nodes, path_edges)
-    Cora_graph.graph["bow"]["maxlen_neighbours"] = get_max_bow_neighbours(path_nodes, path_edges)
-    Cora_graph.graph["paper_id"]["maxlen_neighbours"] = get_max_neighbours(path_nodes, path_edges)
-    return Cora_graph
-
-def get_init_emb(rand_type="normal_random", dimension = 128, quantity=1433):
-    return initialize.get_embeddings(rand_type=rand_type, dimension = dimension, quantity=quantity)
-
-def write_pickle_graph_file(path_nodes="/home/utaemon/SP/cora/cora.content", path_edges="/home/utaemon/SP/cora/cora.cites", path_output_graph = "/home/utaemon/SP/"):
-    g = add_max_values_to_graph(path_nodes, path_edges)
-    with open(path_output_graph + "graph.pkl", "wb") as output:
-        pkl.dump(g, output)
-
-def read_pickle_graph(path = "/home/utaemon/SP/graph.pkl"):
-    with open(path, 'rb') as f:
-        graph = pkl.load(f)
-    return graph
-
-
-if __name__ == "__main__":
-    # execute only if run as a script
-    get_graph(path_nodes="/home/utaemon/SP/cora/cora.content", path_edges="/home/utaemon/SP/cora/cora.cites")
-    get_init_emb(rand_type="normal_random", dimension = 128, quantity=1433)
diff --git a/Cora_Preprocessing/cora_statistics.txt b/Cora_Preprocessing/cora_statistics.txt
deleted file mode 100644
index 5b0d8aafa204b0b95a6d7b84a5f645f5c3838861..0000000000000000000000000000000000000000
--- a/Cora_Preprocessing/cora_statistics.txt
+++ /dev/null
@@ -1,16 +0,0 @@
-Nodes per Class
-
-0
-298
-1
-418
-2
-818
-3
-426
-4
-217
-5
-180
-6
-351
diff --git a/Cora_Preprocessing/get_nodes.py b/Cora_Preprocessing/get_nodes.py
deleted file mode 100644
index 711e9f955095259f1036267bd10578660900a7c5..0000000000000000000000000000000000000000
--- a/Cora_Preprocessing/get_nodes.py
+++ /dev/null
@@ -1,67 +0,0 @@
-#!/usr/bin/env python3
-# -*- coding: utf-8 -*-
-
-"""
-@author: Utaemon Toyota
-@project: Software Projekt
-@date: 25.12.2018
-"""
-
-import random
-import cora
-
-def get_graph(path_nodes, path_edges):
-    return cora.get_graph(path_nodes, path_edges)
-
-def dict_of_node_classes(path_nodes, path_edges):
-    cora = get_graph(path_nodes, path_edges)
-    class_dict = {}
-    for node in cora.node:
-        node_class = cora.node[node]["class"]
-        if not node_class in class_dict:
-            class_dict[node_class] = set()
-        class_dict[node_class].add(node)
-    return class_dict
-
-def get_random_num_nodes(set_elm, num):
-    return set(random.sample(set_elm, num))
-
-def get_num_random_nodes_for_all_classes(num = 3, path_nodes="/home/utaemon/SP/cora/cora.content", path_edges="/home/utaemon/SP/cora/cora.cites"):
-    """get specific number of nodes per class, same number for all classes"""
-    cora_dict = dict_of_node_classes(path_nodes, path_edges)
-    sampled_random_id_set = set()
-    for key in cora_dict:
-        for id in get_random_num_nodes(cora_dict[key], num):
-            sampled_random_id_set.add(id)
-    # if you want to return dict of class:random_ids
-    # cora_dict = dict_of_node_classes(path_nodes, path_edges)
-    # sampled_random_dict = {}
-    # for key in cora_dict:
-    #    sampled_random_dict[key] = get_random_num_nodes(cora_dict[key], num)
-    # return sampled_random_dict
-    return sampled_random_id_set
-
-#get random nodes
-def get_num_of_random_nodes(num = 3, path_nodes="/home/utaemon/SP/cora/cora.content", path_edges="/home/utaemon/SP/cora/cora.cites"):
-    """Get random nodes."""
-    cora_nodes = set(get_graph(path_nodes, path_edges).nodes)
-    return set(random.sample(cora_nodes, num))
-
-#get a dictionary with class: ids
-def get_dict_of_nodes(*args):
-    """*args: Tuple of Set_name and number of nodes in it, for example ("a", 10)."""
-    dict_of_sets = {}
-    for arg in args:
-        ids = get_num_of_random_nodes(arg[1])
-        dict_of_sets[arg[0]] = ids
-    return dict_of_sets
-
-#get features from nodes
-def get_features_for_nodes(path_nodes="/home/utaemon/SP/cora/cora.content", path_edges="/home/utaemon/SP/cora/cora.cites"):
-    cora_graph = get_graph(path_nodes, path_edges)
-    set_of_cora_nodes = get_num_of_random_nodes()
-    dict_of_id_and_features = {}
-    for id in set_of_cora_nodes:
-        dict_of_id_and_features[id] = cora_graph.node[id]
-    return dict_of_id_and_features
-
diff --git a/Cora_Preprocessing/get_subgraph.py b/Cora_Preprocessing/get_subgraph.py
deleted file mode 100644
index db6e2efc9bc2263d16d90f06b79a643bd51f0d32..0000000000000000000000000000000000000000
--- a/Cora_Preprocessing/get_subgraph.py
+++ /dev/null
@@ -1,45 +0,0 @@
-#!/usr/bin/env python3
-
-"""
-@author: Utaemon Toyota
-@project: Software Projekt
-@date: 14.01.2018
-"""
-
-import cora
-import networkx as nx
-import pickle as pkl
-
-def get_graph(graph_path):
-    cora_graph = cora.read_pickle_graph(graph_path)
-    return cora_graph
-
-def get_start_node(graph):
-    li_nodes = graph.nodes
-    return list(li_nodes)[0]
-
-def get_neighbours(nb):
-    return list(dict(nb).keys())
-
-def get_subgraph(graph_path):
-    cora_graph = get_graph(graph_path)
-    start = get_start_node(cora_graph)
-    start_nb = get_neighbours(cora_graph[start])
-    temp_node_set = set()
-    temp2 = set()
-    for node in start_nb:
-        temp_node_set.add(node)
-    for node in temp_node_set:
-        for elm in get_neighbours(cora_graph[node]):
-            temp2.add(elm)
-    temp3 = temp_node_set.union(temp2)
-    cora_test = nx.Graph(cora_graph.subgraph(list(temp3)))
-    return cora_test
-
-def write_test_pickle(output = "test_cora.pkl", graph_path = "/home/utaemon/SP/cora_graph.pkl"):
-    with open (output, "wb") as output:
-        pkl.dump(get_subgraph(graph_path), output)
-
-#write_test_pickle()
-#cora_test = cora.read_pickle_graph("test_cora.pkl")
-#print (cora_test.edges)
diff --git a/Cora_Preprocessing/graph.pkl b/Cora_Preprocessing/graph.pkl
deleted file mode 100644
index beb2191a82ee7320c14065afd9dc7ebf138f7d63..0000000000000000000000000000000000000000
Binary files a/Cora_Preprocessing/graph.pkl and /dev/null differ
diff --git a/Cora_Preprocessing/graph.txt b/Cora_Preprocessing/graph.txt
deleted file mode 100644
index 94d751b307189cce86008a2d452c5baf900abcfa..0000000000000000000000000000000000000000
--- a/Cora_Preprocessing/graph.txt
+++ /dev/null
@@ -1 +0,0 @@
-{"directed": false, "multigraph": false, "graph": {}, "nodes": [{"class": 2, "bow": [[118, 125, 176, 252, 351, 456, 507, 521, 619, 648, 698, 702, 734, 845, 902, 1205, 1209, 1236, 1352, 1426]], "id": 31336}, {"class": 5, "bow": [[12, 509, 620, 763, 882, 893, 978, 1131, 1135, 1177, 1207, 1256, 1263, 1266, 1332, 1389, 1425]], "id": 1061127}, {"class": 4, "bow": [[45, 209, 212, 239, 292, 394, 510, 514, 581, 621, 623, 638, 1075, 1132, 1177, 1206, 1263, 1289, 1349, 1389, 1415, 1421]], "id": 1106406}, {"class": 4, "bow": [[41, 93, 99, 149, 594, 617, 624, 648, 874, 915, 942, 988, 1004, 1049, 1071, 1170, 1177, 1194, 1292, 1348, 1349]], "id": 13195}, {"class": 3, "bow": [[44, 122, 135, 153, 364, 396, 402, 474, 507, 619, 661, 699, 701, 828, 1066, 1174, 1175, 1177, 1208, 1209, 1212, 1254, 1381]], "id": 37879}, {"class": 3, "bow": [[93, 168, 211, 507, 526, 551, 874, 972, 1143, 1177, 1198, 1290, 1426]], "id": 1126012}, {"class": 6, "bow": [[187, 266, 317, 324, 367, 509, 619, 701, 916, 937, 1171, 1174, 1177, 1203, 1263, 1290, 1330, 1355, 1397]], "id": 1107140}, {"class": 2, "bow": [[3, 89, 99, 132, 203, 238, 438, 507, 521, 536, 638, 736, 807, 819, 921, 1046, 1177, 1192, 1198]], "id": 1102850}, {"class": 2, "bow": [[456, 648, 902, 1209, 1273]], "id": 31349}, {"class": 6, "bow": [[12, 21, 96, 161, 203, 434, 470, 521, 547, 869, 926, 1196, 1209, 1230, 1263, 1332, 1336, 1369]], "id": 1106418}, {"class": 2, "bow": [[118, 171, 533, 820, 1209, 1241, 1273]], "id": 1123188}, {"class": 1, "bow": [[63, 92, 140, 168, 187, 234, 375, 398, 495, 808, 937, 987, 1079, 1132, 1177, 1262, 1263, 1360, 1390, 1423, 1426]], "id": 1128990}, {"class": 3, "bow": [[2, 77, 102, 129, 135, 250, 262, 466, 474, 540, 548, 591, 760, 893, 1131, 1177, 1209, 1254, 1317, 1339, 1353]], "id": 109323}, {"class": 0, "bow": [[25, 31, 234, 607, 627, 633, 673, 855, 920, 973, 979, 1074, 1131, 1209, 1210, 1263, 1301, 1397]], "id": 217139}, {"class": 2, "bow": [[93, 254, 456, 509, 521, 619, 648, 698, 736, 845, 902, 1151, 1205, 1209, 1273, 1312, 1381, 1389, 1396]], "id": 31353}, {"class": 2, "bow": [[19, 46, 58, 61, 128, 132, 203, 233, 261, 440, 517, 625, 953, 1170, 1177, 1179, 1202, 1263, 1295, 1331, 1353, 1412, 1414]], "id": 32083}, {"class": 4, "bow": [[625, 1253, 1263]], "id": 1126029}, {"class": 2, "bow": [[19, 132, 414, 739, 774, 810, 896, 1051, 1070, 1075, 1144, 1177, 1209, 1231, 1236, 1255, 1262, 1299]], "id": 1118017}, {"class": 2, "bow": [[88, 274, 305, 457, 625, 729, 739, 810, 898, 1019, 1144, 1193, 1209, 1316, 1368]], "id": 49482}, {"class": 2, "bow": [[135, 334, 367, 540, 554, 725, 729, 754, 868, 1011, 1071, 1073, 1159, 1178, 1257, 1366, 1381]], "id": 753265}, {"class": 6, "bow": [[89, 324, 336, 442, 474, 483, 510, 540, 615, 697, 698, 729, 957, 1177, 1209, 1211, 1232, 1233, 1259, 1263, 1332, 1427]], "id": 249858}, {"class": 4, "bow": [[19, 132, 205, 336, 548, 581, 774, 874, 1003, 1263, 1276, 1307, 1320, 1339, 1352]], "id": 1113739}, {"class": 1, "bow": [[19, 140, 351, 368, 464, 756, 774, 834, 860, 986, 1132, 1151, 1171, 1197, 1207, 1267, 1352]], "id": 48766}, {"class": 3, "bow": [[126, 400, 540, 682, 722, 945, 1011, 1205, 1247, 1249, 1389]], "id": 646195}, {"class": 4, "bow": [[3, 831, 836, 1263]], "id": 1126050}, {"class": 6, "bow": [[262, 405, 442, 507, 615, 698, 816, 827, 860, 939, 961, 1022, 1114, 1209, 1211, 1259, 1263, 1328]], "id": 59626}, {"class": 2, "bow": [[19, 114, 203, 211, 411, 619, 701, 715, 727, 749, 754, 774, 923, 1138, 1148, 1169, 1177, 1209, 1229, 1381, 1389, 1390, 1431]], "id": 340299}, {"class": 3, "bow": [[64, 151, 178, 324, 398, 647, 1094, 1170, 1193, 1208, 1230, 1231, 1254, 1301, 1305, 1353, 1395]], "id": 354004}, {"class": 2, "bow": [[19, 52, 507, 667, 723, 755, 774, 865, 876, 1052, 1075, 1209, 1231, 1270, 1345, 1353]], "id": 242637}, {"class": 5, "bow": [[81, 168, 203, 221, 228, 245, 401, 507, 779, 814, 922, 963, 1114, 1118, 1177, 1205, 1235, 1258, 1263, 1336, 1349, 1379]], "id": 1106492}, {"class": 0, "bow": [[4, 173, 349, 411, 414, 475, 659, 670, 728, 750, 819, 995, 1071, 1075, 1143, 1149, 1172, 1230, 1239, 1242, 1290, 1393, 1407]], "id": 74975}, {"class": 2, "bow": [[10, 57, 125, 135, 172, 177, 208, 284, 438, 474, 507, 612, 647, 702, 749, 760, 801, 1072, 1109, 1117, 1175, 1177, 1209, 1328, 1330]], "id": 1152272}, {"class": 0, "bow": [[40, 82, 83, 126, 192, 313, 414, 464, 505, 513, 537, 605, 625, 675, 913, 1149, 1170, 1177, 1290, 1299, 1343, 1397]], "id": 100701}, {"class": 2, "bow": [[19, 47, 136, 138, 176, 300, 456, 507, 538, 612, 711, 755, 774, 808, 979, 1071, 1209, 1263, 1328, 1357]], "id": 66982}, {"class": 4, "bow": [[57, 203, 284, 338, 352, 426, 581, 758, 933, 1071, 1170, 1173, 1177, 1194, 1198, 1263, 1295, 1352, 1359, 1387, 1423]], "id": 13960}, {"class": 4, "bow": [[184, 187, 211, 338, 495, 507, 581, 725, 763, 813, 906, 1075, 1076, 1104, 1142, 1177, 1207, 1263, 1270, 1274, 1295, 1298, 1303, 1343, 1355, 1381]], "id": 13966}, {"class": 2, "bow": [[5, 19, 130, 136, 207, 351, 420, 451, 575, 647, 693, 711, 724, 774, 783, 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372862}, {"source": 178718, "target": 1110546}, {"source": 1108209, "target": 118559}, {"source": 1112665, "target": 6344}, {"source": 1104647, "target": 45603}, {"source": 66563, "target": 1123530}, {"source": 66563, "target": 66564}, {"source": 67292, "target": 1105530}, {"source": 154047, "target": 1112106}, {"source": 154047, "target": 1133846}, {"source": 642930, "target": 1131184}, {"source": 654519, "target": 1131754}, {"source": 178727, "target": 1110546}, {"source": 1135108, "target": 6913}, {"source": 162075, "target": 1109830}, {"source": 162075, "target": 162080}, {"source": 593209, "target": 593210}, {"source": 1132285, "target": 12195}, {"source": 162080, "target": 1109830}, {"source": 162080, "target": 1135345}, {"source": 593210, "target": 195792}, {"source": 118424, "target": 118436}, {"source": 1135122, "target": 733534}, {"source": 634938, "target": 1130847}, {"source": 1131565, "target": 62329}, {"source": 20857, "target": 6923}, {"source": 118435, "target": 118436}, {"source": 643695, "target": 1154068}, {"source": 1111978, "target": 210309}, {"source": 1154012, "target": 626530}, {"source": 49844, "target": 49847}, {"source": 1108267, "target": 20924}, {"source": 1108267, "target": 28230}, {"source": 1050679, "target": 427606}, {"source": 1114838, "target": 270600}, {"source": 577227, "target": 1131752}, {"source": 601561, "target": 252715}, {"source": 24476, "target": 1103499}, {"source": 16461, "target": 1105603}, {"source": 1138027, "target": 7867}, {"source": 1114864, "target": 6311}, {"source": 1114864, "target": 14529}, {"source": 1154068, "target": 444191}, {"source": 449841, "target": 1123093}, {"source": 801170, "target": 289779}, {"source": 251756, "target": 62329}, {"source": 251756, "target": 195792}, {"source": 144679, "target": 1114239}, {"source": 1138043, "target": 66751}, {"source": 86923, "target": 1114184}, {"source": 342802, "target": 2695}, {"source": 342802, "target": 2696}, {"source": 342802, "target": 2698}, {"source": 1152633, "target": 36131}, {"source": 711527, "target": 216878}, {"source": 684372, "target": 684531}, {"source": 101811, "target": 151430}, {"source": 246618, "target": 116545}, {"source": 246618, "target": 116552}, {"source": 1136631, "target": 767763}, {"source": 1152676, "target": 57119}, {"source": 235776, "target": 6311}, {"source": 57119, "target": 606647}, {"source": 119956, "target": 5462}, {"source": 948147, "target": 733534}, {"source": 739816, "target": 1140543}, {"source": 739816, "target": 1140548}, {"source": 3222, "target": 1131137}, {"source": 3222, "target": 964248}, {"source": 36802, "target": 1108389}, {"source": 3232, "target": 1106330}, {"source": 3232, "target": 1123068}, {"source": 3237, "target": 964248}, {"source": 1111265, "target": 24043}, {"source": 695284, "target": 66751}, {"source": 695284, "target": 693143}, {"source": 71736, "target": 1152991}, {"source": 12165, "target": 12195}, {"source": 12165, "target": 12211}, {"source": 1133004, "target": 2696}, {"source": 1133008, "target": 688824}, {"source": 1102567, "target": 4878}, {"source": 644427, "target": 644577}, {"source": 689439, "target": 616336}, {"source": 633585, "target": 40605}, {"source": 633585, "target": 633721}, {"source": 633585, "target": 884094}, {"source": 31083, "target": 1123068}, {"source": 6152, "target": 299195}, {"source": 1119987, "target": 14529}, {"source": 82664, "target": 1106236}, {"source": 82666, "target": 101143}, {"source": 82666, "target": 1106236}, {"source": 672070, "target": 1132443}, {"source": 672070, "target": 1154123}, {"source": 672070, "target": 1154124}, {"source": 672070, "target": 672071}, {"source": 672071, "target": 1132443}, {"source": 672071, "target": 1132461}, {"source": 632874, "target": 40583}, {"source": 632874, "target": 633081}, {"source": 1114192, "target": 2696}, {"source": 1114192, "target": 2698}, {"source": 1114192, "target": 256106}, {"source": 20924, "target": 1115701}, {"source": 20924, "target": 294030}, {"source": 1131634, "target": 427606}, {"source": 180301, "target": 1110628}, {"source": 160705, "target": 2696}, {"source": 160705, "target": 13136}, {"source": 628458, "target": 628459}, {"source": 1130915, "target": 633721}, {"source": 1116336, "target": 6913}, {"source": 57922, "target": 6925}, {"source": 57922, "target": 1118658}, {"source": 57932, "target": 6925}, {"source": 73972, "target": 50980}, {"source": 198443, "target": 190697}, {"source": 60159, "target": 60169}, {"source": 101143, "target": 101145}, {"source": 101145, "target": 89308}, {"source": 259772, "target": 1114336}, {"source": 467383, "target": 1128977}, {"source": 13686, "target": 1385}, {"source": 13686, "target": 27535}, {"source": 118558, "target": 28385}, {"source": 1126503, "target": 50838}, {"source": 40583, "target": 40605}, {"source": 95719, "target": 32698}, {"source": 693143, "target": 66751}, {"source": 6913, "target": 1152917}, {"source": 6913, "target": 431206}, {"source": 256106, "target": 2696}, {"source": 256106, "target": 2698}, {"source": 36140, "target": 350373}, {"source": 36140, "target": 46500}, {"source": 1115670, "target": 151430}, {"source": 1108389, "target": 1919}, {"source": 6923, "target": 308003}, {"source": 6923, "target": 6941}, {"source": 6925, "target": 1118658}, {"source": 6925, "target": 372862}, {"source": 62329, "target": 195792}, {"source": 62329, "target": 427606}, {"source": 36167, "target": 70520}, {"source": 6941, "target": 372862}, {"source": 62333, "target": 62347}, {"source": 167205, "target": 8591}, {"source": 1112026, "target": 27535}, {"source": 1119295, "target": 6318}, {"source": 1152761, "target": 263498}, {"source": 444191, "target": 17363}, {"source": 263482, "target": 263486}, {"source": 675756, "target": 1132505}, {"source": 1125895, "target": 28385}, {"source": 884094, "target": 40605}, {"source": 120817, "target": 1140543}, {"source": 18770, "target": 28964}, {"source": 18781, "target": 18785}, {"source": 578845, "target": 593559}, {"source": 578845, "target": 593560}, {"source": 293271, "target": 293285}, {"source": 63835, "target": 114308}, {"source": 12275, "target": 233106}, {"source": 6215, "target": 6224}, {"source": 385067, "target": 272345}, {"source": 1103394, "target": 22564}, {"source": 1103394, "target": 22566}, {"source": 2663, "target": 7047}, {"source": 28964, "target": 1125944}, {"source": 753070, "target": 767763}, {"source": 563613, "target": 1129572}, {"source": 2695, "target": 1120197}, {"source": 2695, "target": 2698}, {"source": 2695, "target": 2696}, {"source": 2696, "target": 1120858}, {"source": 2696, "target": 2698}, {"source": 1113551, "target": 41417}, {"source": 1138968, "target": 427606}, {"source": 40605, "target": 633721}, {"source": 40605, "target": 633081}, {"source": 1999, "target": 1123068}, {"source": 33325, "target": 429781}, {"source": 1115701, "target": 202520}, {"source": 1136040, "target": 754594}, {"source": 1123756, "target": 28230}, {"source": 1107728, "target": 115188}, {"source": 1125906, "target": 519318}, {"source": 28249, "target": 628668}, {"source": 444240, "target": 254923}, {"source": 27535, "target": 34961}, {"source": 28267, "target": 1152896}, {"source": 263553, "target": 1117219}, {"source": 10174, "target": 10186}, {"source": 675847, "target": 1132505}, {"source": 630890, "target": 233106}, {"source": 561568, "target": 561613}, {"source": 116512, "target": 1107808}, {"source": 74821, "target": 1120252}, {"source": 74821, "target": 1131149}, {"source": 74821, "target": 1131150}, {"source": 1105622, "target": 430574}, {"source": 1140543, "target": 255628}, {"source": 1140543, "target": 523010}, {"source": 42156, "target": 1152179}, {"source": 22564, "target": 22566}, {"source": 195792, "target": 1128974}, {"source": 89308, "target": 103528}, {"source": 628667, "target": 628668}, {"source": 4983, "target": 7867}, {"source": 593559, "target": 593560}, {"source": 70520, "target": 27631}, {"source": 152226, "target": 152227}, {"source": 626530, "target": 1130454}, {"source": 626530, "target": 626531}, {"source": 626531, "target": 1130454}]}
\ No newline at end of file
diff --git a/Cora_Preprocessing/initialize.py b/Cora_Preprocessing/initialize.py
deleted file mode 100644
index 20dd9ae28d8e04465497f2d6cd07e16194a84630..0000000000000000000000000000000000000000
--- a/Cora_Preprocessing/initialize.py
+++ /dev/null
@@ -1,35 +0,0 @@
-"""
-Initialize Embeddings for n dimensions.
-Arrays are initialized in normal or uniform random format.
-The seed has the default value 1.
-
-#Usage
-Embeddings.normal_random(dimension = 128, seed = 1)
-Embeddings.uniform_random(dimension = 128, seed = 1)
-or to get a set of Embeddings:
-get_embeddings(rand_type="normal_random", dimension = 128, quantity=1)
-"""
-
-import numpy as np
-
-class Embeddings:
-
-    def normal_random(dimension = 128, seed = 1):
-        np.random.seed(seed)
-        return np.random.normal(size=dimension)
-
-    def uniform_random(dimension = 128, seed = 1):
-        np.random.seed(seed)
-        return np.random.uniform(size=dimension)
-
-
-def get_embeddings(rand_type="normal_random", dimension = 128, quantity=1):
-
-    emb_dict = {}
-    if rand_type == "normal_random":
-        for i in range(0, quantity):
-            emb_dict[i] = Embeddings.normal_random(dimension = dimension, seed = i)
-    elif rand_type == "uniform_random":
-        for i in range(0, quantity):
-            emb_dict[i] = Embeddings.uniform_random(dimension = dimension, seed = i)
-    return emb_dict
\ No newline at end of file
diff --git a/Cora_Preprocessing/normal_random_init.txt b/Cora_Preprocessing/normal_random_init.txt
deleted file mode 100644
index 7298073f55ed5311535594dde56a730934dcef87..0000000000000000000000000000000000000000
--- a/Cora_Preprocessing/normal_random_init.txt
+++ /dev/null
@@ -1,38040 +0,0 @@
-{0: array([ 1.76405235,  0.40015721,  0.97873798,  2.2408932 ,  1.86755799,
-       -0.97727788,  0.95008842, -0.15135721, -0.10321885,  0.4105985 ,
-        0.14404357,  1.45427351,  0.76103773,  0.12167502,  0.44386323,
-        0.33367433,  1.49407907, -0.20515826,  0.3130677 , -0.85409574,
-       -2.55298982,  0.6536186 ,  0.8644362 , -0.74216502,  2.26975462,
-       -1.45436567,  0.04575852, -0.18718385,  1.53277921,  1.46935877,
-        0.15494743,  0.37816252, -0.88778575, -1.98079647, -0.34791215,
-        0.15634897,  1.23029068,  1.20237985, -0.38732682, -0.30230275,
-       -1.04855297, -1.42001794, -1.70627019,  1.9507754 , -0.50965218,
-       -0.4380743 , -1.25279536,  0.77749036, -1.61389785, -0.21274028,
-       -0.89546656,  0.3869025 , -0.51080514, -1.18063218, -0.02818223,
-        0.42833187,  0.06651722,  0.3024719 , -0.63432209, -0.36274117,
-       -0.67246045, -0.35955316, -0.81314628, -1.7262826 ,  0.17742614,
-       -0.40178094, -1.63019835,  0.46278226, -0.90729836,  0.0519454 ,
-        0.72909056,  0.12898291,  1.13940068, -1.23482582,  0.40234164,
-       -0.68481009, -0.87079715, -0.57884966, -0.31155253,  0.05616534,
-       -1.16514984,  0.90082649,  0.46566244, -1.53624369,  1.48825219,
-        1.89588918,  1.17877957, -0.17992484, -1.07075262,  1.05445173,
-       -0.40317695,  1.22244507,  0.20827498,  0.97663904,  0.3563664 ,
-        0.70657317,  0.01050002,  1.78587049,  0.12691209,  0.40198936,
-        1.8831507 , -1.34775906, -1.270485  ,  0.96939671, -1.17312341,
-        1.94362119, -0.41361898, -0.74745481,  1.92294203,  1.48051479,
-        1.86755896,  0.90604466, -0.86122569,  1.91006495, -0.26800337,
-        0.8024564 ,  0.94725197, -0.15501009,  0.61407937,  0.92220667,
-        0.37642553, -1.09940079,  0.29823817,  1.3263859 , -0.69456786,
-       -0.14963454, -0.43515355,  1.84926373]), 1: array([ 1.62434536, -0.61175641, -0.52817175, -1.07296862,  0.86540763,
-       -2.3015387 ,  1.74481176, -0.7612069 ,  0.3190391 , -0.24937038,
-        1.46210794, -2.06014071, -0.3224172 , -0.38405435,  1.13376944,
-       -1.09989127, -0.17242821, -0.87785842,  0.04221375,  0.58281521,
-       -1.10061918,  1.14472371,  0.90159072,  0.50249434,  0.90085595,
-       -0.68372786, -0.12289023, -0.93576943, -0.26788808,  0.53035547,
-       -0.69166075, -0.39675353, -0.6871727 , -0.84520564, -0.67124613,
-       -0.0126646 , -1.11731035,  0.2344157 ,  1.65980218,  0.74204416,
-       -0.19183555, -0.88762896, -0.74715829,  1.6924546 ,  0.05080775,
-       -0.63699565,  0.19091548,  2.10025514,  0.12015895,  0.61720311,
-        0.30017032, -0.35224985, -1.1425182 , -0.34934272, -0.20889423,
-        0.58662319,  0.83898341,  0.93110208,  0.28558733,  0.88514116,
-       -0.75439794,  1.25286816,  0.51292982, -0.29809284,  0.48851815,
-       -0.07557171,  1.13162939,  1.51981682,  2.18557541, -1.39649634,
-       -1.44411381, -0.50446586,  0.16003707,  0.87616892,  0.31563495,
-       -2.02220122, -0.30620401,  0.82797464,  0.23009474,  0.76201118,
-       -0.22232814, -0.20075807,  0.18656139,  0.41005165,  0.19829972,
-        0.11900865, -0.67066229,  0.37756379,  0.12182127,  1.12948391,
-        1.19891788,  0.18515642, -0.37528495, -0.63873041,  0.42349435,
-        0.07734007, -0.34385368,  0.04359686, -0.62000084,  0.69803203,
-       -0.44712856,  1.2245077 ,  0.40349164,  0.59357852, -1.09491185,
-        0.16938243,  0.74055645, -0.9537006 , -0.26621851,  0.03261455,
-       -1.37311732,  0.31515939,  0.84616065, -0.85951594,  0.35054598,
-       -1.31228341, -0.03869551, -1.61577235,  1.12141771,  0.40890054,
-       -0.02461696, -0.77516162,  1.27375593,  1.96710175, -1.85798186,
-        1.23616403,  1.62765075,  0.3380117 ]), 2: array([-4.16757847e-01, -5.62668272e-02, -2.13619610e+00,  1.64027081e+00,
-       -1.79343559e+00, -8.41747366e-01,  5.02881417e-01, -1.24528809e+00,
-       -1.05795222e+00, -9.09007615e-01,  5.51454045e-01,  2.29220801e+00,
-        4.15393930e-02, -1.11792545e+00,  5.39058321e-01, -5.96159700e-01,
-       -1.91304965e-02,  1.17500122e+00, -7.47870949e-01,  9.02525097e-03,
-       -8.78107893e-01, -1.56434170e-01,  2.56570452e-01, -9.88779049e-01,
-       -3.38821966e-01, -2.36184031e-01, -6.37655012e-01, -1.18761229e+00,
-       -1.42121723e+00, -1.53495196e-01, -2.69056960e-01,  2.23136679e+00,
-       -2.43476758e+00,  1.12726505e-01,  3.70444537e-01,  1.35963386e+00,
-        5.01857207e-01, -8.44213704e-01,  9.76147160e-06,  5.42352572e-01,
-       -3.13508197e-01,  7.71011738e-01, -1.86809065e+00,  1.73118467e+00,
-        1.46767801e+00, -3.35677339e-01,  6.11340780e-01,  4.79705919e-02,
-       -8.29135289e-01,  8.77102184e-02,  1.00036589e+00, -3.81092518e-01,
-       -3.75669423e-01, -7.44707629e-02,  4.33496330e-01,  1.27837923e+00,
-       -6.34679305e-01,  5.08396243e-01,  2.16116006e-01, -1.85861239e+00,
-       -4.19316482e-01, -1.32328898e-01, -3.95702397e-02,  3.26003433e-01,
-       -2.04032305e+00,  4.62555231e-02, -6.77675577e-01, -1.43943903e+00,
-        5.24296430e-01,  7.35279576e-01, -6.53250268e-01,  8.42456282e-01,
-       -3.81516482e-01,  6.64890091e-02, -1.09873895e+00,  1.58448706e+00,
-       -2.65944946e+00, -9.14526229e-02,  6.95119605e-01, -2.03346655e+00,
-       -1.89469265e-01, -7.72186654e-02,  8.24703005e-01,  1.24821292e+00,
-       -4.03892269e-01, -1.38451867e+00,  1.36723542e+00,  1.21788563e+00,
-       -4.62005348e-01,  3.50888494e-01,  3.81866234e-01,  5.66275441e-01,
-        2.04207979e-01,  1.40669624e+00, -1.73795950e+00,  1.04082395e+00,
-        3.80471970e-01, -2.17135269e-01,  1.17353150e+00, -2.34360319e+00,
-        1.16152149e+00,  3.86078048e-01, -1.13313327e+00,  4.33092555e-01,
-       -3.04086439e-01,  2.58529487e+00,  1.83533272e+00,  4.40689872e-01,
-       -7.19253841e-01, -5.83414595e-01, -3.25049628e-01, -5.60234506e-01,
-       -9.02246068e-01, -5.90972275e-01, -2.76179492e-01, -5.16883894e-01,
-       -6.98589950e-01, -9.28891925e-01,  2.55043824e+00, -1.47317325e+00,
-       -1.02141473e+00,  4.32395701e-01, -3.23580070e-01,  4.23824708e-01,
-        7.99179995e-01,  1.26261366e+00,  7.51964849e-01, -9.93760983e-01]), 3: array([ 1.78862847,  0.43650985,  0.09649747, -1.8634927 , -0.2773882 ,
-       -0.35475898, -0.08274148, -0.62700068, -0.04381817, -0.47721803,
-       -1.31386475,  0.88462238,  0.88131804,  1.70957306,  0.05003364,
-       -0.40467741, -0.54535995, -1.54647732,  0.98236743, -1.10106763,
-       -1.18504653, -0.2056499 ,  1.48614836,  0.23671627, -1.02378514,
-       -0.7129932 ,  0.62524497, -0.16051336, -0.76883635, -0.23003072,
-        0.74505627,  1.97611078, -1.24412333, -0.62641691, -0.80376609,
-       -2.41908317, -0.92379202, -1.02387576,  1.12397796, -0.13191423,
-       -1.62328545,  0.64667545, -0.35627076, -1.74314104, -0.59664964,
-       -0.58859438, -0.8738823 ,  0.02971382, -2.24825777, -0.26776186,
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-        9.72705077e-01, -3.01726716e+00, -4.07551163e-01,  4.16485303e-01,
-       -7.98440750e-01,  4.77004015e-01, -1.03563167e+00, -5.25259907e-01,
-       -9.60161920e-01, -7.73549070e-01, -9.07252200e-01, -1.74144652e-01,
-       -9.89971595e-03, -7.44798094e-01,  9.66790460e-01,  1.68659050e+00,
-        1.48932813e+00,  2.65066571e-01,  5.81810253e-01, -5.19259286e-01,
-       -3.00834092e-01, -8.40890557e-01,  7.63623357e-01,  3.87264422e-01]), 1432: array([ 0.46070143,  1.6233909 ,  1.58620697, -1.43065636, -0.52432785,
-       -0.46163515, -1.3499444 , -0.88961407, -1.78859659, -0.8621639 ,
-        1.83470609,  1.58108023,  1.0827928 , -1.87291177,  1.02044512,
-       -0.75351365, -0.0512194 ,  0.12238113,  2.17695019,  0.08573657,
-       -1.31297869,  2.31967208,  2.62781959, -0.60043556, -0.38255282,
-        0.40733831, -0.24213596, -1.70378566,  3.74958064, -0.63881323,
-       -0.50298784, -1.3046381 , -0.83758467,  0.89268113, -0.12759896,
-        0.06308588,  0.35608266, -0.24766893, -1.31776023,  0.34935661,
-        0.72600533,  1.08322324,  0.15066948,  0.38671947, -0.76359213,
-       -0.72132478,  0.43351352, -0.874464  ,  2.16936576, -1.42353862,
-        0.23208466,  1.24496774, -0.07584597, -0.75597156, -0.61715375,
-        0.02512582,  0.07354967,  0.83941237, -0.33973694, -0.4113587 ,
-        0.12358751,  0.10070728,  1.3036303 ,  0.3953138 , -1.20486132,
-        0.53926525,  1.18585277, -0.33163399, -1.79116264,  1.40867218,
-        2.20577169, -1.49667519,  1.55454024,  0.60002574, -1.38078127,
-       -1.99227286, -0.98348261,  1.61645572,  0.87052252,  1.48709287,
-        1.71632084,  1.23073659,  1.34441214,  0.40201085, -0.40133607,
-       -1.00994733,  0.95244079,  0.01220438, -0.9201909 , -0.49483938,
-       -0.95984092,  1.84861552, -0.00438667, -0.53802655,  1.83284417,
-        1.14781999,  2.4090095 ,  1.85415442, -1.17038439,  1.92930675,
-        0.42455421,  0.23247433,  0.03538493,  1.11485803,  0.98869693,
-       -0.21872244, -0.63995148,  0.78726846,  0.70896734, -0.20096695,
-        0.28655299, -1.55204675, -0.91886896,  0.12390089, -1.90885681,
-        1.42838845, -0.53262281, -0.10833793, -1.84487392,  0.895773  ,
-       -0.94511036,  1.26363173, -0.80115999, -0.37172982,  0.67986585,
-       -0.93534054, -0.07947857, -1.17620061])}
\ No newline at end of file
diff --git a/Cora_Preprocessing/test_cora.pkl b/Cora_Preprocessing/test_cora.pkl
deleted file mode 100644
index 1485d18316027ba2b528303ab91da30cef95a47c..0000000000000000000000000000000000000000
Binary files a/Cora_Preprocessing/test_cora.pkl and /dev/null differ
diff --git a/Cora_Preprocessing/uniform_random_init.txt b/Cora_Preprocessing/uniform_random_init.txt
deleted file mode 100644
index cd8dd6cb177dfc86da63c3b171c30431cf1906f6..0000000000000000000000000000000000000000
--- a/Cora_Preprocessing/uniform_random_init.txt
+++ /dev/null
@@ -1,36852 +0,0 @@
-{0: array([0.5488135 , 0.71518937, 0.60276338, 0.54488318, 0.4236548 ,
-       0.64589411, 0.43758721, 0.891773  , 0.96366276, 0.38344152,
-       0.79172504, 0.52889492, 0.56804456, 0.92559664, 0.07103606,
-       0.0871293 , 0.0202184 , 0.83261985, 0.77815675, 0.87001215,
-       0.97861834, 0.79915856, 0.46147936, 0.78052918, 0.11827443,
-       0.63992102, 0.14335329, 0.94466892, 0.52184832, 0.41466194,
-       0.26455561, 0.77423369, 0.45615033, 0.56843395, 0.0187898 ,
-       0.6176355 , 0.61209572, 0.616934  , 0.94374808, 0.6818203 ,
-       0.3595079 , 0.43703195, 0.6976312 , 0.06022547, 0.66676672,
-       0.67063787, 0.21038256, 0.1289263 , 0.31542835, 0.36371077,
-       0.57019677, 0.43860151, 0.98837384, 0.10204481, 0.20887676,
-       0.16130952, 0.65310833, 0.2532916 , 0.46631077, 0.24442559,
-       0.15896958, 0.11037514, 0.65632959, 0.13818295, 0.19658236,
-       0.36872517, 0.82099323, 0.09710128, 0.83794491, 0.09609841,
-       0.97645947, 0.4686512 , 0.97676109, 0.60484552, 0.73926358,
-       0.03918779, 0.28280696, 0.12019656, 0.2961402 , 0.11872772,
-       0.31798318, 0.41426299, 0.0641475 , 0.69247212, 0.56660145,
-       0.26538949, 0.52324805, 0.09394051, 0.5759465 , 0.9292962 ,
-       0.31856895, 0.66741038, 0.13179786, 0.7163272 , 0.28940609,
-       0.18319136, 0.58651293, 0.02010755, 0.82894003, 0.00469548,
-       0.67781654, 0.27000797, 0.73519402, 0.96218855, 0.24875314,
-       0.57615733, 0.59204193, 0.57225191, 0.22308163, 0.95274901,
-       0.44712538, 0.84640867, 0.69947928, 0.29743695, 0.81379782,
-       0.39650574, 0.8811032 , 0.58127287, 0.88173536, 0.69253159,
-       0.72525428, 0.50132438, 0.95608363, 0.6439902 , 0.42385505,
-       0.60639321, 0.0191932 , 0.30157482]), 1: array([4.17022005e-01, 7.20324493e-01, 1.14374817e-04, 3.02332573e-01,
-       1.46755891e-01, 9.23385948e-02, 1.86260211e-01, 3.45560727e-01,
-       3.96767474e-01, 5.38816734e-01, 4.19194514e-01, 6.85219500e-01,
-       2.04452250e-01, 8.78117436e-01, 2.73875932e-02, 6.70467510e-01,
-       4.17304802e-01, 5.58689828e-01, 1.40386939e-01, 1.98101489e-01,
-       8.00744569e-01, 9.68261576e-01, 3.13424178e-01, 6.92322616e-01,
-       8.76389152e-01, 8.94606664e-01, 8.50442114e-02, 3.90547832e-02,
-       1.69830420e-01, 8.78142503e-01, 9.83468338e-02, 4.21107625e-01,
-       9.57889530e-01, 5.33165285e-01, 6.91877114e-01, 3.15515631e-01,
-       6.86500928e-01, 8.34625672e-01, 1.82882773e-02, 7.50144315e-01,
-       9.88861089e-01, 7.48165654e-01, 2.80443992e-01, 7.89279328e-01,
-       1.03226007e-01, 4.47893526e-01, 9.08595503e-01, 2.93614148e-01,
-       2.87775339e-01, 1.30028572e-01, 1.93669579e-02, 6.78835533e-01,
-       2.11628116e-01, 2.65546659e-01, 4.91573159e-01, 5.33625451e-02,
-       5.74117605e-01, 1.46728575e-01, 5.89305537e-01, 6.99758360e-01,
-       1.02334429e-01, 4.14055988e-01, 6.94400158e-01, 4.14179270e-01,
-       4.99534589e-02, 5.35896406e-01, 6.63794645e-01, 5.14889112e-01,
-       9.44594756e-01, 5.86555041e-01, 9.03401915e-01, 1.37474704e-01,
-       1.39276347e-01, 8.07391289e-01, 3.97676837e-01, 1.65354197e-01,
-       9.27508580e-01, 3.47765860e-01, 7.50812103e-01, 7.25997985e-01,
-       8.83306091e-01, 6.23672207e-01, 7.50942434e-01, 3.48898342e-01,
-       2.69927892e-01, 8.95886218e-01, 4.28091190e-01, 9.64840047e-01,
-       6.63441498e-01, 6.21695720e-01, 1.14745973e-01, 9.49489259e-01,
-       4.49912133e-01, 5.78389614e-01, 4.08136803e-01, 2.37026980e-01,
-       9.03379521e-01, 5.73679487e-01, 2.87032703e-03, 6.17144914e-01,
-       3.26644902e-01, 5.27058102e-01, 8.85942099e-01, 3.57269760e-01,
-       9.08535151e-01, 6.23360116e-01, 1.58212428e-02, 9.29437234e-01,
-       6.90896918e-01, 9.97322850e-01, 1.72340508e-01, 1.37135750e-01,
-       9.32595463e-01, 6.96818161e-01, 6.60001727e-02, 7.55463053e-01,
-       7.53876188e-01, 9.23024536e-01, 7.11524759e-01, 1.24270962e-01,
-       1.98801338e-02, 2.62109869e-02, 2.83064880e-02, 2.46211068e-01,
-       8.60027949e-01, 5.38831064e-01, 5.52821979e-01, 8.42030892e-01]), 2: array([0.4359949 , 0.02592623, 0.54966248, 0.43532239, 0.4203678 ,
-       0.33033482, 0.20464863, 0.61927097, 0.29965467, 0.26682728,
-       0.62113383, 0.52914209, 0.13457995, 0.51357812, 0.18443987,
-       0.78533515, 0.85397529, 0.49423684, 0.84656149, 0.07964548,
-       0.50524609, 0.0652865 , 0.42812233, 0.09653092, 0.12715997,
-       0.59674531, 0.226012  , 0.10694568, 0.22030621, 0.34982629,
-       0.46778748, 0.20174323, 0.64040673, 0.48306984, 0.50523672,
-       0.38689265, 0.79363745, 0.58000418, 0.1622986 , 0.70075235,
-       0.96455108, 0.50000836, 0.88952006, 0.34161365, 0.56714413,
-       0.42754596, 0.43674726, 0.77655918, 0.53560417, 0.95374223,
-       0.54420816, 0.08209492, 0.3663424 , 0.8508505 , 0.40627504,
-       0.02720237, 0.24717724, 0.06714437, 0.99385201, 0.97058031,
-       0.80025835, 0.60181712, 0.76495986, 0.16922545, 0.29302323,
-       0.52406688, 0.35662428, 0.04567897, 0.98315345, 0.44135492,
-       0.50400044, 0.32354132, 0.25974475, 0.38688989, 0.8320169 ,
-       0.73674706, 0.37921057, 0.01301734, 0.79740494, 0.2693888 ,
-       0.58268489, 0.02555094, 0.66220202, 0.38752343, 0.4970738 ,
-       0.41490584, 0.3508719 , 0.55097791, 0.97291069, 0.11277622,
-       0.31325853, 0.04179771, 0.73839976, 0.65751239, 0.21463575,
-       0.41675344, 0.64384193, 0.66148133, 0.17047713, 0.88165224,
-       0.77800816, 0.13395421, 0.86891663, 0.74877788, 0.79858565,
-       0.54334523, 0.22083792, 0.91845865, 0.59208458, 0.34623791,
-       0.26377853, 0.91391548, 0.41973546, 0.54019152, 0.60844216,
-       0.82624983, 0.62356318, 0.17671216, 0.59125735, 0.48926617,
-       0.54790778, 0.69952062, 0.24581116, 0.18662715, 0.11058315,
-       0.27405925, 0.01025004, 0.62935972]), 3: array([0.5507979 , 0.70814782, 0.29090474, 0.51082761, 0.89294695,
-       0.89629309, 0.12558531, 0.20724288, 0.0514672 , 0.44080984,
-       0.02987621, 0.45683322, 0.64914405, 0.27848728, 0.6762549 ,
-       0.59086282, 0.02398188, 0.55885409, 0.25925245, 0.4151012 ,
-       0.28352508, 0.69313792, 0.44045372, 0.15686774, 0.54464902,
-       0.78031476, 0.30636353, 0.22195788, 0.38797126, 0.93638365,
-       0.97599542, 0.67238368, 0.90283411, 0.84575087, 0.37799404,
-       0.09221701, 0.6534109 , 0.55784076, 0.36156476, 0.2250545 ,
-       0.40651992, 0.46894025, 0.26923558, 0.29179277, 0.4576864 ,
-       0.86053391, 0.5862529 , 0.28348786, 0.27797751, 0.45462208,
-       0.20541034, 0.20137871, 0.51403506, 0.08722937, 0.48358553,
-       0.36217621, 0.70768662, 0.74674622, 0.69109292, 0.68918041,
-       0.37360012, 0.6681348 , 0.33984866, 0.57279387, 0.32580716,
-       0.44514505, 0.06152893, 0.24267542, 0.97160261, 0.2305842 ,
-       0.69147751, 0.65047686, 0.72393914, 0.47508861, 0.59666377,
-       0.06696942, 0.07256214, 0.19897603, 0.151861  , 0.10010434,
-       0.12929386, 0.55327773, 0.18781482, 0.95210124, 0.68161178,
-       0.54101967, 0.7071806 , 0.26388667, 0.92672568, 0.83919306,
-       0.7263195 , 0.48023996, 0.84210319, 0.74475232, 0.66032591,
-       0.91397527, 0.63366556, 0.36594058, 0.55284457, 0.19638058,
-       0.1920723 , 0.72566962, 0.7849367 , 0.97209836, 0.85097142,
-       0.54359433, 0.08979087, 0.48887324, 0.92793635, 0.7876182 ,
-       0.48509423, 0.45527936, 0.21798577, 0.17721338, 0.07362367,
-       0.89239319, 0.64017662, 0.14333232, 0.41412692, 0.04910892,
-       0.20937335, 0.73070812, 0.65112277, 0.4789783 , 0.27478051,
-       0.65222313, 0.95644951, 0.43552056]), 4: array([0.96702984, 0.54723225, 0.97268436, 0.71481599, 0.69772882,
-       0.2160895 , 0.97627445, 0.00623026, 0.25298236, 0.43479153,
-       0.77938292, 0.19768507, 0.86299324, 0.98340068, 0.16384224,
-       0.59733394, 0.0089861 , 0.38657128, 0.04416006, 0.95665297,
-       0.43614665, 0.94897731, 0.78630599, 0.8662893 , 0.17316542,
-       0.07494859, 0.60074272, 0.16797218, 0.73338017, 0.40844386,
-       0.52790882, 0.93757158, 0.52169612, 0.10819338, 0.15822341,
-       0.54520265, 0.52440408, 0.63761024, 0.40149544, 0.64980511,
-       0.3969    , 0.62391611, 0.76740497, 0.17897391, 0.37557577,
-       0.50253306, 0.68666708, 0.25367965, 0.55474086, 0.62493084,
-       0.89550117, 0.36285359, 0.63755707, 0.1914464 , 0.49779411,
-       0.1824454 , 0.91838304, 0.43182207, 0.8301881 , 0.4167763 ,
-       0.90466759, 0.40482522, 0.3311745 , 0.57213877, 0.84544365,
-       0.86101431, 0.59568812, 0.08466161, 0.59726661, 0.24545371,
-       0.73259345, 0.89465129, 0.51473397, 0.60356351, 0.06506781,
-       0.54007473, 0.12918678, 0.61456285, 0.36365035, 0.76775803,
-       0.04853414, 0.10981812, 0.68402322, 0.5146537 , 0.57164137,
-       0.84370699, 0.48773764, 0.81014442, 0.51024363, 0.92672069,
-       0.66692777, 0.14872684, 0.36455318, 0.86577492, 0.35028521,
-       0.18902576, 0.47262131, 0.39278117, 0.61892993, 0.43676629,
-       0.26092216, 0.41247221, 0.41903403, 0.90242186, 0.97961626,
-       0.62356884, 0.08318412, 0.73299872, 0.6786854 , 0.82602287,
-       0.34745134, 0.05888009, 0.61182182, 0.12401462, 0.75952953,
-       0.79442332, 0.40862679, 0.94379751, 0.17377979, 0.94258585,
-       0.46548967, 0.76299364, 0.7528202 , 0.98120992, 0.97327799,
-       0.04009112, 0.01597128, 0.54329032]), 5: array([0.22199317, 0.87073231, 0.20671916, 0.91861091, 0.48841119,
-       0.61174386, 0.76590786, 0.51841799, 0.2968005 , 0.18772123,
-       0.08074127, 0.7384403 , 0.44130922, 0.15830987, 0.87993703,
-       0.27408646, 0.41423502, 0.29607993, 0.62878791, 0.57983781,
-       0.5999292 , 0.26581912, 0.28468588, 0.25358821, 0.32756395,
-       0.1441643 , 0.16561286, 0.96393053, 0.96022672, 0.18841466,
-       0.02430656, 0.20455555, 0.69984361, 0.77951459, 0.02293309,
-       0.57766286, 0.00164217, 0.51547261, 0.63979518, 0.9856244 ,
-       0.2590976 , 0.80249689, 0.87048309, 0.92274961, 0.00221421,
-       0.46948837, 0.98146874, 0.3989448 , 0.81373248, 0.5464565 ,
-       0.77085409, 0.48493107, 0.02911156, 0.08652569, 0.11145381,
-       0.25124511, 0.96491529, 0.63176605, 0.8166602 , 0.566082  ,
-       0.63535621, 0.81190239, 0.92668262, 0.91262676, 0.82481072,
-       0.09420273, 0.36104842, 0.03550903, 0.54635835, 0.79614272,
-       0.0511428 , 0.18866774, 0.36547777, 0.24429087, 0.79508747,
-       0.35209494, 0.63887768, 0.49341505, 0.58349974, 0.93929935,
-       0.94354008, 0.11169243, 0.84355497, 0.34602815, 0.10082727,
-       0.38340907, 0.5103548 , 0.96110308, 0.37151262, 0.01236941,
-       0.85970689, 0.11111075, 0.47833904, 0.84998003, 0.51473797,
-       0.44660783, 0.80047642, 0.02039138, 0.57261865, 0.41138362,
-       0.9851368 , 0.80140153, 0.0539621 , 0.19047777, 0.45241885,
-       0.70294208, 0.33204815, 0.3599832 , 0.92147057, 0.95363051,
-       0.40768573, 0.89857115, 0.33025325, 0.08273857, 0.52671757,
-       0.66084439, 0.89298429, 0.96515755, 0.76993268, 0.75909912,
-       0.71004905, 0.70155283, 0.76733138, 0.97434948, 0.37371452,
-       0.08305444, 0.23964044, 0.22148276]), 6: array([0.89286015, 0.33197981, 0.82122912, 0.04169663, 0.10765668,
-       0.59505206, 0.52981736, 0.41880743, 0.33540785, 0.62251943,
-       0.43814143, 0.73588211, 0.51803641, 0.5788586 , 0.6453551 ,
-       0.99022427, 0.8198582 , 0.41320093, 0.87626766, 0.82375943,
-       0.05447451, 0.71863724, 0.80217056, 0.73640664, 0.70913175,
-       0.54093685, 0.12482417, 0.9576473 , 0.4032563 , 0.21695116,
-       0.71727585, 0.99420744, 0.25561406, 0.67130943, 0.59900591,
-       0.71733215, 0.93734953, 0.35180977, 0.2536341 , 0.40247251,
-       0.74651072, 0.72407057, 0.4061078 , 0.98937985, 0.45049928,
-       0.37380843, 0.70962861, 0.08245855, 0.39837292, 0.77088097,
-       0.76475098, 0.28385938, 0.18954219, 0.47125096, 0.33480604,
-       0.73473504, 0.18910712, 0.33110407, 0.84422842, 0.61502403,
-       0.88526408, 0.97655302, 0.83690859, 0.18082463, 0.61841051,
-       0.47610887, 0.40415665, 0.74188369, 0.82593329, 0.68322983,
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-       0.23049519, 0.31010682, 0.03413107, 0.71119228, 0.98054956,
-       0.57990428, 0.47342376, 0.69058083, 0.15395495, 0.18751266,
-       0.17125004, 0.13526191, 0.24755432, 0.57615338, 0.9413693 ,
-       0.91912552, 0.02007269, 0.00991136, 0.98032292, 0.1423061 ,
-       0.86485673, 0.22838775, 0.10647924, 0.92525275, 0.11646035,
-       0.35863108, 0.0555888 , 0.38545237, 0.81318936, 0.8139494 ,
-       0.33861538, 0.64199526, 0.87937879, 0.2184527 , 0.10284349,
-       0.03697819, 0.167709  , 0.03898879, 0.92838817, 0.85198156,
-       0.04303383, 0.5779467 , 0.49719524, 0.02151818, 0.48956121,
-       0.5557971 , 0.9675353 , 0.11664639, 0.07198896, 0.14657945,
-       0.58971933, 0.65737486, 0.71103807, 0.31184787, 0.39098131,
-       0.7622165 , 0.07739932, 0.89265743, 0.74660172, 0.49674558,
-       0.63412897, 0.57474217, 0.65380705, 0.50325867, 0.61064717,
-       0.35611533, 0.36859526, 0.01628561, 0.1580631 , 0.2071582 ,
-       0.60636208, 0.38782019, 0.06299522, 0.79224872, 0.30490105,
-       0.23524014, 0.96566389, 0.92031316, 0.93180861, 0.26038429,
-       0.66659816, 0.0059446 , 0.89401698, 0.78159368, 0.25838457,
-       0.23440394, 0.93320316, 0.52960842, 0.85421185, 0.47746859,
-       0.28914877, 0.45058882, 0.02423889, 0.66461373, 0.41632986,
-       0.79152952, 0.77959783, 0.45781069, 0.91273646, 0.96820319,
-       0.47883352, 0.7951077 , 0.06640604, 0.2734389 , 0.13271693,
-       0.19557   , 0.68453134, 0.87595988, 0.07199452, 0.33307419,
-       0.94356141, 0.62385149, 0.79156537, 0.12967996, 0.96993685,
-       0.50766038, 0.8432893 , 0.88141045]), 1429: array([0.042225  , 0.09499545, 0.8550585 , 0.30416361, 0.78542804,
-       0.90075447, 0.69844757, 0.60395438, 0.7149149 , 0.13934965,
-       0.83720408, 0.23432677, 0.69963625, 0.1960665 , 0.12122513,
-       0.3436056 , 0.95923196, 0.09847881, 0.26003771, 0.92544486,
-       0.54707838, 0.72035046, 0.20604331, 0.6127197 , 0.330977  ,
-       0.75867318, 0.50437081, 0.63624276, 0.55370786, 0.53475581,
-       0.78205526, 0.65298539, 0.37807641, 0.12222662, 0.39933118,
-       0.53466048, 0.77624897, 0.17208188, 0.8199735 , 0.09811937,
-       0.90089791, 0.21269873, 0.33383662, 0.88489851, 0.20709388,
-       0.33697815, 0.20168416, 0.23504331, 0.45456654, 0.88227086,
-       0.53300959, 0.12843737, 0.05709549, 0.02226622, 0.99532205,
-       0.16136141, 0.13033201, 0.1907824 , 0.91697681, 0.41762848,
-       0.93662141, 0.31537208, 0.74169032, 0.06451644, 0.16129662,
-       0.98400226, 0.35758865, 0.4246665 , 0.79988282, 0.90055578,
-       0.43237876, 0.40604206, 0.69260491, 0.09901507, 0.29485509,
-       0.5503635 , 0.50815659, 0.36294332, 0.9300925 , 0.20276799,
-       0.68748712, 0.45301021, 0.8875994 , 0.83266735, 0.14061382,
-       0.5565404 , 0.69391672, 0.92074277, 0.24447687, 0.33021245,
-       0.97320725, 0.58231425, 0.65313535, 0.43504382, 0.98952678,
-       0.40410513, 0.79728501, 0.91035642, 0.39477546, 0.46023105,
-       0.33920006, 0.52199368, 0.55410561, 0.43738957, 0.78134956,
-       0.68976669, 0.03791428, 0.24595688, 0.89334913, 0.51669506,
-       0.77595271, 0.44525823, 0.27474722, 0.51162583, 0.27569943,
-       0.13748649, 0.80431562, 0.56465895, 0.80541281, 0.31609878,
-       0.99437626, 0.64326784, 0.68040414, 0.63824278, 0.1836599 ,
-       0.53206684, 0.89680315, 0.13785553]), 1430: array([0.58854604, 0.46438014, 0.06564768, 0.05282183, 0.32179673,
-       0.89652424, 0.04482914, 0.90708984, 0.1216225 , 0.06952697,
-       0.28020228, 0.62007534, 0.20944904, 0.52111192, 0.43847115,
-       0.0448813 , 0.68145877, 0.20673107, 0.57849273, 0.06949415,
-       0.33152365, 0.87941767, 0.04637965, 0.36356471, 0.17074819,
-       0.42923617, 0.36910697, 0.20757462, 0.54266946, 0.11338965,
-       0.46993644, 0.22899255, 0.89400338, 0.00882482, 0.08427634,
-       0.3419995 , 0.1133802 , 0.56204926, 0.18927125, 0.28887656,
-       0.26874215, 0.47003831, 0.43814732, 0.20962007, 0.55987501,
-       0.48112051, 0.33790756, 0.90306359, 0.20752   , 0.59378454,
-       0.32045429, 0.66374429, 0.16142236, 0.78740326, 0.70718374,
-       0.76291132, 0.37597868, 0.89346146, 0.61985663, 0.14387882,
-       0.53622812, 0.84742629, 0.34002953, 0.65668725, 0.22987419,
-       0.17882441, 0.21623237, 0.2282735 , 0.15249453, 0.03960758,
-       0.32211604, 0.65239525, 0.78166396, 0.05093319, 0.60872335,
-       0.36047734, 0.28225109, 0.54934906, 0.97660901, 0.35559244,
-       0.25232922, 0.4017838 , 0.62858905, 0.2880824 , 0.62463582,
-       0.07697871, 0.98674629, 0.87224196, 0.71853464, 0.56153953,
-       0.71644223, 0.28686034, 0.70513298, 0.87494438, 0.80398849,
-       0.34783943, 0.39827422, 0.54034347, 0.20622741, 0.45445764,
-       0.18142843, 0.73111375, 0.38070523, 0.49902265, 0.70928027,
-       0.75540905, 0.13757135, 0.92042497, 0.34241308, 0.17377664,
-       0.76771799, 0.54100533, 0.328922  , 0.56775739, 0.14286868,
-       0.90371967, 0.31091738, 0.08044603, 0.55803682, 0.53604625,
-       0.33778937, 0.45997068, 0.44838298, 0.05281117, 0.50903993,
-       0.06312011, 0.2268193 , 0.71128106]), 1431: array([0.20988224, 0.30477429, 0.86184518, 0.38860829, 0.1413354 ,
-       0.32536603, 0.01099786, 0.82304196, 0.15182569, 0.17587744,
-       0.49627362, 0.99876378, 0.93677396, 0.97799784, 0.19051525,
-       0.38403528, 0.92397282, 0.14623947, 0.1055324 , 0.93033182,
-       0.9576833 , 0.61507469, 0.835207  , 0.01671193, 0.65598974,
-       0.30596126, 0.43427231, 0.81510952, 0.69473857, 0.67267337,
-       0.43760868, 0.89293255, 0.31796773, 0.58634312, 0.93264451,
-       0.36229999, 0.3784869 , 0.41382711, 0.43682724, 0.63007498,
-       0.70635926, 0.69698421, 0.58869855, 0.62052094, 0.28637013,
-       0.49296185, 0.38571135, 0.81907395, 0.6213308 , 0.55446721,
-       0.31159505, 0.09254761, 0.55022973, 0.09737569, 0.97773405,
-       0.58106363, 0.51088939, 0.72680823, 0.28647975, 0.779398  ,
-       0.01106569, 0.89072094, 0.46165515, 0.81306586, 0.65776864,
-       0.17915014, 0.63978809, 0.12393605, 0.39363079, 0.76481873,
-       0.36148099, 0.69116769, 0.30112679, 0.36939246, 0.94874457,
-       0.04829852, 0.24494235, 0.62322045, 0.15547463, 0.87859512,
-       0.89898172, 0.46527482, 0.74192265, 0.44042592, 0.9351298 ,
-       0.2645203 , 0.20660956, 0.91398012, 0.69563711, 0.87617965,
-       0.39509872, 0.33029095, 0.6578189 , 0.50074015, 0.67348759,
-       0.59039276, 0.28253627, 0.81025112, 0.43925539, 0.30098834,
-       0.45850352, 0.62799558, 0.36793786, 0.85858919, 0.62863348,
-       0.00186434, 0.17249229, 0.74187157, 0.57741629, 0.00443782,
-       0.49323637, 0.66997495, 0.27092451, 0.86298615, 0.14151176,
-       0.53803469, 0.31578453, 0.20637966, 0.90737364, 0.5503824 ,
-       0.58831928, 0.67516052, 0.56067851, 0.0530182 , 0.16136557,
-       0.88877874, 0.65013568, 0.92699718]), 1432: array([0.94808625, 0.9394137 , 0.73603221, 0.56698348, 0.39297501,
-       0.61866147, 0.20754419, 0.16782702, 0.00433468, 0.72040907,
-       0.3568627 , 0.28279638, 0.41897144, 0.33190271, 0.94547222,
-       0.8289613 , 0.57531226, 0.58739333, 0.36566077, 0.57766599,
-       0.30136033, 0.76900757, 0.2976799 , 0.99740597, 0.95920877,
-       0.30781027, 0.50600635, 0.65250806, 0.82520135, 0.06701301,
-       0.27036036, 0.00819157, 0.57365937, 0.45830739, 0.48189083,
-       0.57925518, 0.83709702, 0.18341447, 0.26390569, 0.46644712,
-       0.49774386, 0.51324265, 0.21384044, 0.38967455, 0.75070255,
-       0.26477086, 0.72047962, 0.05405285, 0.22761666, 0.89161547,
-       0.58051265, 0.19630925, 0.77150669, 0.68197108, 0.94625201,
-       0.67386391, 0.23942088, 0.22415177, 0.14696134, 0.6750181 ,
-       0.85003981, 0.88661265, 0.44903598, 0.57766533, 0.05352784,
-       0.24852445, 0.82917033, 0.56136335, 0.07726935, 0.06522161,
-       0.01848441, 0.93563285, 0.06935293, 0.45679356, 0.51848908,
-       0.04586136, 0.65545079, 0.01439219, 0.77919292, 0.95305503,
-       0.91708015, 0.53654474, 0.14096168, 0.20347393, 0.8138479 ,
-       0.88515272, 0.59123729, 0.80087414, 0.02605306, 0.15507104,
-       0.63212866, 0.2047896 , 0.95308206, 0.13714705, 0.63252382,
-       0.99277175, 0.4078226 , 0.82960682, 0.93681571, 0.78006139,
-       0.58439272, 0.3926925 , 0.92029348, 0.04826661, 0.86959071,
-       0.88514556, 0.45248451, 0.57002743, 0.5899317 , 0.73299409,
-       0.40541074, 0.43444318, 0.8430509 , 0.09267654, 0.7359408 ,
-       0.97608184, 0.67453015, 0.39381252, 0.99333714, 0.32644838,
-       0.70540057, 0.6202385 , 0.59553345, 0.63322595, 0.99898658,
-       0.13959392, 0.58755704, 0.79280986])}
\ No newline at end of file
diff --git a/EP/Cora_node_classification/README.md b/EP/Cora_node_classification/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..526942e7f3c2f27eca99c640c67becddd632ef99
--- /dev/null
+++ b/EP/Cora_node_classification/README.md
@@ -0,0 +1,45 @@
+# AUTHORS
+Lyuba Dimitrova, Nadia Arslan, Nicolas Weber, Utaemon Toyota
+
+# PROJECT
+Softwareprojekt WS2018/19
+Betreuerin: Prof. Dr. Anette Frank
+Graph Embedding Propagation
+
+# Cora Node Classification
+To evaluate the trained graph and the embeddings the task of node classification will be executed. First, the data of cora will be imported into a networkX graph, which will be saved in a pickle file to use it for the training of the embeddings with our EP-SP algorithm. Afterwards the trained embedding will be evaluated with LibLinear L2-Logistic Regression provided from sklearn.
+
+# Required Data
+- Cora dataset saved in cora_data for building the graph
+- Embeddings for node classification
+
+# Dependencies
+For cora.py
+-networkx	for building the graph
+-numpy		to save one-hot vocabulary vectors
+-pickle		to save data in a pickle file
+
+For node_classification.py
+-cora.py
+-random_nodes_for_node_classification.py	for getting random node sets for test, training and validation sets 
+-pickle
+-numpy
+-sklearn	for evaluation
+-random		for getting random test, trainings and validation sets
+-sys
+-argparse
+-heapq		for getting a heatmap from confusion matrix
+-sklearn	for confusion matrix and f1 score
+
+# Running instructions
+For cora.py
+...
+
+For node_classification.py
+python3 node_classification.py [-g] [-e] [-s] [-i] [-n]
+        -g / --graph        Path to pickled networkX-graph
+        -e / --embeddings   Path to pickled embeddings
+        -s / --seed         Seed for randomization. If this argument is called, only a node classification for this specific seed will be executed
+        -i / --iterations   Number of iterations of node classification. Counter of iteration is equal to random seed
+        -n / --number       Number of instances per class for training
+        -c / --regularization   Inverse of regularization strength
diff --git a/EP/Cora_node_classification/cora.py b/EP/Cora_node_classification/cora.py
index cb8520a9592145f63bd5801d8436e15d58058cc1..95c21dfdba73ffa25f34f8cfa1a83aa79f4478c5 100644
--- a/EP/Cora_node_classification/cora.py
+++ b/EP/Cora_node_classification/cora.py
@@ -1,27 +1,22 @@
 """
+@info
 Getting a networkx graph from Cora. Graph can be saved in txt file. CARE: numpy-arrays are converted to lists due to errors (NumPy array is not JSON serializable).
-Initialize Embeddings for n dimensions with initialize-module.
-Arrays are initialized in normal or uniform random format (default = normal).
 
-
-#Usage
-get_graph(path_nodes="/home/utaemon/SP/cora/cora.content", path_edges="/home/utaemon/SP/cora/cora.cites")
+@usage
+get_graph(path_nodes="/cora_data/cora.content", path_edges="/cora_data/cora.cites")
 -> return graph with nodes and edges
 To write the graph informations in file:
-def write_graph_to_file(path_nodes="/home/utaemon/SP/cora/cora.content", path_edges="/home/utaemon/SP/cora/cora.cites", path_output_graph = "/home/utaemon/SP/")
-To write the dictionary with initalizing Embeddings in file:
-def write_dict_to_file(rand_type="normal_random", dimension = 128, quantity=1433, path_output_emb = "/home/utaemon/SP/")
+def write_graph_to_file(path_nodes="/cora_data/cora.content", path_edges="/cora_data/cora.cites", path_output_graph = "")
 """
 
 import networkx as nx
 import numpy as np
-import initialize
 import pickle as pkl
 
 def list_of_classes():
     return ["Case_Based", "Genetic_Algorithms", "Neural_Networks", "Probabilistic_Methods", "Reinforcement_Learning", "Rule_Learning", "Theory"]
 
-def read_file_and_get_nodes(graph_name, path="/home/utaemon/SP/cora/cora.content"):
+def read_file_and_get_nodes(graph_name, path="/cora_data/cora.content"):
     class_list = list_of_classes()
     max_bow_len = 0
     node_mapping = {}
@@ -49,7 +44,7 @@ def read_file_and_get_nodes(graph_name, path="/home/utaemon/SP/cora/cora.content
     graph_name.graph["paper_id"] = {"maxlen": 1, "vocab": (len(graph_name)), "lengths": np.ones(len(graph_name))}
     return node_mapping
 
-def read_file_and_get_edges(graph_name, node_mapping, path="/home/utaemon/SP/cora/cora.cites"):
+def read_file_and_get_edges(graph_name, node_mapping, path="/cora_data/cora.cites"):
     with open(path) as file:
         for line in file.readlines():
             a, b = line.split()
@@ -111,15 +106,12 @@ def add_max_values_to_graph(path_nodes, path_edges):                    #update
     Cora_graph.graph["paper_id"]["maxlen_neighbours"] = get_max_neighbours(path_nodes, path_edges)
     return Cora_graph
 
-def get_init_emb(rand_type="normal_random", dimension = 128, quantity=1433):
-    return initialize.get_embeddings(rand_type=rand_type, dimension = dimension, quantity=quantity)
-
-def write_pickle_graph_file(path_nodes="/home/utaemon/SP/cora/cora.content", path_edges="/home/utaemon/SP/cora/cora.cites", path_output_graph = "/home/utaemon/SP/"):
+def write_pickle_graph_file(path_nodes="/cora_data/cora.content", path_edges="/cora_data/cora.cites", path_output_graph = ""):
     g = add_max_values_to_graph(path_nodes, path_edges)
     with open(path_output_graph + "graph.pkl", "wb") as output:
         pkl.dump(g, output)
 
-def read_pickle_graph(path = "/home/utaemon/SP/graph.pkl"):
+def read_pickle_graph(path = "graph.pkl"):
     with open(path, 'rb') as f:
         graph = pkl.load(f)
     return graph
@@ -127,5 +119,5 @@ def read_pickle_graph(path = "/home/utaemon/SP/graph.pkl"):
 
 if __name__ == "__main__":
     # execute only if run as a script
-    get_graph(path_nodes="/home/utaemon/SP/cora/cora.content", path_edges="/home/utaemon/SP/cora/cora.cites")
+    get_graph(path_nodes="/cora_data/cora.content", path_edges="/cora_data/cora.cites")
     get_init_emb(rand_type="normal_random", dimension = 128, quantity=1433)
diff --git a/Cora_Preprocessing/cora_data/README b/EP/Cora_node_classification/cora_data/README
similarity index 100%
rename from Cora_Preprocessing/cora_data/README
rename to EP/Cora_node_classification/cora_data/README
diff --git a/Cora_Preprocessing/cora_data/cora.cites b/EP/Cora_node_classification/cora_data/cora.cites
similarity index 100%
rename from Cora_Preprocessing/cora_data/cora.cites
rename to EP/Cora_node_classification/cora_data/cora.cites
diff --git a/Cora_Preprocessing/cora_data/cora.content b/EP/Cora_node_classification/cora_data/cora.content
similarity index 100%
rename from Cora_Preprocessing/cora_data/cora.content
rename to EP/Cora_node_classification/cora_data/cora.content
diff --git a/Cora_Preprocessing/cora_data/cora_small.content b/EP/Cora_node_classification/cora_data/cora_small.content
similarity index 100%
rename from Cora_Preprocessing/cora_data/cora_small.content
rename to EP/Cora_node_classification/cora_data/cora_small.content
diff --git a/EP/Cora_node_classification/initialize.py b/EP/Cora_node_classification/initialize.py
deleted file mode 100644
index 20dd9ae28d8e04465497f2d6cd07e16194a84630..0000000000000000000000000000000000000000
--- a/EP/Cora_node_classification/initialize.py
+++ /dev/null
@@ -1,35 +0,0 @@
-"""
-Initialize Embeddings for n dimensions.
-Arrays are initialized in normal or uniform random format.
-The seed has the default value 1.
-
-#Usage
-Embeddings.normal_random(dimension = 128, seed = 1)
-Embeddings.uniform_random(dimension = 128, seed = 1)
-or to get a set of Embeddings:
-get_embeddings(rand_type="normal_random", dimension = 128, quantity=1)
-"""
-
-import numpy as np
-
-class Embeddings:
-
-    def normal_random(dimension = 128, seed = 1):
-        np.random.seed(seed)
-        return np.random.normal(size=dimension)
-
-    def uniform_random(dimension = 128, seed = 1):
-        np.random.seed(seed)
-        return np.random.uniform(size=dimension)
-
-
-def get_embeddings(rand_type="normal_random", dimension = 128, quantity=1):
-
-    emb_dict = {}
-    if rand_type == "normal_random":
-        for i in range(0, quantity):
-            emb_dict[i] = Embeddings.normal_random(dimension = dimension, seed = i)
-    elif rand_type == "uniform_random":
-        for i in range(0, quantity):
-            emb_dict[i] = Embeddings.uniform_random(dimension = dimension, seed = i)
-    return emb_dict
\ No newline at end of file
diff --git a/EP/Cora_node_classification/nc_100_uniform.txt b/EP/Cora_node_classification/nc_100_uniform.txt
deleted file mode 100644
index 75876b2c0918cf01adb1db994f6bd0f782a6f096..0000000000000000000000000000000000000000
--- a/EP/Cora_node_classification/nc_100_uniform.txt
+++ /dev/null
@@ -1,915 +0,0 @@
-Node Classification on random seed  0 -> 0.561
-Confusion Matrix:
- [[ 57   2   2  15   4  12  14]
- [  6 118  10   1  13   3   0]
- [ 24  24 129  39  25  22  54]
- [ 12   5  23  93   5   6  23]
- [  1   7   5   4  55   1   0]
- [  5   0   1   4   3  51   4]
- [  9   2   7   6  29   7  58]]
-Node Classification on random seed  1 -> 0.611
-Confusion Matrix:
- [[ 88   3   4   5   3   8   9]
- [  6 117   6   3  12   9   0]
- [ 32  17 125  28  43  23  42]
- [  9   3   6 112  11   3  16]
- [  2   7   1   0  59   4   1]
- [  5   4   1   1   2  44   4]
- [ 14   3  11   6  12  10  66]]
-Node Classification on random seed  2 -> 0.586
-Confusion Matrix:
- [[ 84   3   4   5   1  15   9]
- [  5 130   4   2   2   4   7]
- [ 32  42 115  35  35  23  34]
- [  6  14   7 101  11  10  20]
- [  2   7   1   3  53   0   1]
- [  2   2   5   3   0  30   7]
- [  5   3  11  12   6  14  73]]
-Node Classification on random seed  3 -> 0.623
-Confusion Matrix:
- [[ 74   0   0   1   2  23   9]
- [  5 131   3   1  13   2   8]
- [ 18  26 144  33  34  18  40]
- [ 16   6  18  98   3   3  11]
- [  2   2   1   1  57   2   3]
- [  9   1   3   1   0  39   6]
- [ 17   5  12   9   3   7  80]]
-Node Classification on random seed  4 -> 0.613
-Confusion Matrix:
- [[ 88   2   9   7   4   6   5]
- [ 10 132   3   3  11   2   5]
- [ 26  29 127  31  38  21  36]
- [ 15   5  18  97   2   2   6]
- [  0   9   5   3  48   0   1]
- [  8   0   7   0   1  46   3]
- [ 14   1  12   6   6  15  75]]
-Node Classification on random seed  5 -> 0.63
-Confusion Matrix:
- [[ 63   2  15   7   3   6   5]
- [  5 123   6   3   6   4  10]
- [ 32  19 131  38  33  10  42]
- [  9   7   9 122   5   1   7]
- [  2   6   4   4  59   0   4]
- [  3   0   2   2   0  52   4]
- [  6   3  10  14   4  18  80]]
-Node Classification on random seed  6 -> 0.604
-Confusion Matrix:
- [[ 67   3   2   6   3  13  14]
- [  6 116   1   0   4   1   3]
- [ 18  44 122  17  50  20  46]
- [  7   5  15 102   8   5   9]
- [  1   9   5   2  59   2   1]
- [  9   1   2   3   5  45   3]
- [  7   4  11   7   5  19  93]]
-Node Classification on random seed  7 -> 0.576
-Confusion Matrix:
- [[ 73   5   0   8   6  14   8]
- [  4 113   7   0   4   5   3]
- [ 20  13  96  42  70  34  38]
- [  6   7  24  96   4  10   7]
- [  2   5   2   1  73   0   3]
- [  2   2   6   3   0  51   4]
- [ 16   3   7   4  12  13  74]]
-Node Classification on random seed  8 -> 0.573
-Confusion Matrix:
- [[ 78   2   5   2   2   4  10]
- [  5 128   3   5   9   1   4]
- [ 26  15 126  56  34  12  53]
- [ 14   8  30  89   4   1  11]
- [  1   4   7   3  53   0   4]
- [  5   4   3   1   2  31  15]
- [ 15   3  18   6   9  11  68]]
-Node Classification on random seed  9 -> 0.56
-Confusion Matrix:
- [[ 62   4   5   1   2  15  10]
- [  9 133   9   2   6   4   0]
- [ 24  15 104  37  57  20  42]
- [ 19   2  23  85   3   7  21]
- [  3   8   1   3  57   1   1]
- [  5   1   1   1   0  55   3]
- [  8   4  14   5  29  15  64]]
-Node Classification on random seed  10 -> 0.615
-Confusion Matrix:
- [[ 80   4   1   6   2   7  16]
- [  6 118   2   3  13   0   3]
- [ 31  21 130  44  39  17  34]
- [  6   1  19 105   7   4  24]
- [  1   3   4   1  48   0   4]
- [  8   5   1   0   0  51   4]
- [ 18   7   8   2   9   0  83]]
-Node Classification on random seed  11 -> 0.593
-Confusion Matrix:
- [[ 53   3   4   8   6  15  19]
- [  3 132   4   4   4   5   4]
- [ 24  23 124  42  28  26  51]
- [  3   3  11 102   3   7  23]
- [  0   6   2   3  59   1   1]
- [  1   0   5   0   1  45  15]
- [ 11   4   5  10   7  12  78]]
-Node Classification on random seed  12 -> 0.583
-Confusion Matrix:
- [[ 85   2   6   3   4  11  11]
- [  5 120  14   2   8   2   7]
- [ 34  15 106  44  27  18  53]
- [ 11   4  11  91   7   9  20]
- [  2   4   9   2  63   0   4]
- [  5   1   0   2   2  48   5]
- [  8   3  17   6   4  15  70]]
-Node Classification on random seed  13 -> 0.584
-Confusion Matrix:
- [[ 73   7   3  10   6   7   4]
- [  8 132   3   5  18   1   3]
- [ 28  38 132  36  34  25  23]
- [ 12   1  11  92  19   2   4]
- [  0   9   3   3  52   1   4]
- [  7   0   5   3   0  41   6]
- [ 15   5  18  18   3   8  62]]
-Node Classification on random seed  14 -> 0.586
-Confusion Matrix:
- [[ 77   1   4   4   6   9   8]
- [  9 115  10   1   8   8   0]
- [ 23  21 111  45  59  20  27]
- [ 21   2  12  97  10   9  17]
- [  0   5   3   1  61   1   1]
- [  3   2   3   2   3  44   4]
- [  8   2  15   4  11  12  81]]
-Node Classification on random seed  15 -> 0.645
-Confusion Matrix:
- [[ 76   4   2   7   3   8   9]
- [  3 129   9  13   2   2   1]
- [ 19  16 182  26  23  16  30]
- [ 17   3  18  96   7  12  13]
- [  1   6   5   4  50   0   3]
- [  5   3   2   5   2  37  12]
- [  6   4  10   9   2  13  75]]
-Node Classification on random seed  16 -> 0.617
-Confusion Matrix:
- [[ 67   1   0   7   7  15  10]
- [  6 120   4   5   9   6   4]
- [ 15  23 135  41  27  13  60]
- [ 14   7   9 119   2   6  11]
- [  1   6   4   0  64   1   2]
- [  3   3   4   0   2  36  12]
- [ 10   3   6   3   7  14  76]]
-Node Classification on random seed  17 -> 0.625
-Confusion Matrix:
- [[ 65   3   3   7   1   4  19]
- [  6 132   5   3   8   1   2]
- [ 34  21 154  22  28  36  32]
- [  7   2  18  96   4   6  21]
- [  1   8   1   0  59   0   6]
- [  7   1   1   3   1  36   9]
- [ 10   1  15   5   6   7  83]]
-Node Classification on random seed  18 -> 0.605
-Confusion Matrix:
- [[ 58   2   5  12   5   9  22]
- [  9 121   5   2  12   6   7]
- [ 16  24 154  27  34  17  48]
- [  8   2  20 101   3   9  14]
- [  0   3   3   3  55   0   3]
- [  7   0   1   0   3  36   7]
- [ 11   7  11   4   8   6  80]]
-Node Classification on random seed  19 -> 0.626
-Confusion Matrix:
- [[ 59   6   7   6   3   8  11]
- [  6 127   4   3   8   2   3]
- [ 35  17 149  30  37  16  26]
- [ 14   6  15 111   9   6   8]
- [  1   8   0   0  64   1   2]
- [  7   5   1   3   2  37   3]
- [  9   6  16   9   8   7  79]]
-Node Classification on random seed  20 -> 0.629
-Confusion Matrix:
- [[ 80   7   1   4   3  11   7]
- [  7 116   3   9  11   6   3]
- [ 24  22 175  26  19  30  37]
- [ 25   2  12  83   3  13   7]
- [  0   3   3   1  58   2   3]
- [  4   2   1   6   0  48   3]
- [ 15   2  13   2   1  18  69]]
-Node Classification on random seed  21 -> 0.631
-Confusion Matrix:
- [[ 83   1   2   8   1  11   8]
- [  2 134   8   3   6   3   9]
- [ 22  20 129  32  18  30  34]
- [  3   4  22 113   1   6   6]
- [  2   8  11   6  57   0   2]
- [  5   2   6   1   1  48   4]
- [ 11   2  13   7   6  22  67]]
-Node Classification on random seed  22 -> 0.626
-Confusion Matrix:
- [[ 76   3   8   6   6   2  14]
- [  2 128   4   4   2   0   4]
- [ 35  19 118  34  32  24  36]
- [  8  11  25 105   8   4   6]
- [  2   8   2   0  66   1   1]
- [  1   1   4   1   0  53   8]
- [  7   5  14   6   8   8  80]]
-Node Classification on random seed  23 -> 0.64
-Confusion Matrix:
- [[ 87   1   3   4   2   4   7]
- [  6 115   4   2  10   6   2]
- [ 27  15 151  18  26  27  39]
- [ 10   5  14 110   3   8   7]
- [  1  10  12   3  62   0   1]
- [  5   2   3   0   0  50   6]
- [ 13   6  13   6   5  24  65]]
-Node Classification on random seed  24 -> 0.589
-Confusion Matrix:
- [[ 46  10   4   1   5  19  24]
- [  4 121   5   6   7   3   3]
- [ 25  35 137  35  30  44  22]
- [ 15   3  15 102   6   3  12]
- [  2   9   2   5  60   1   0]
- [  0   3   2   1   0  47   6]
- [  6   2   7   6   5  18  76]]
-Node Classification on random seed  25 -> 0.621
-Confusion Matrix:
- [[ 91   0   6   3   2   6  13]
- [  3 135   8   1  12   2   2]
- [ 23  25 154  23  29  18  35]
- [ 10   6  21  93   1   6  15]
- [  2   9   4   3  61   0   4]
- [  6   1   0   2   4  37   1]
- [ 21   5  20   3  14  10  50]]
-Node Classification on random seed  26 -> 0.576
-Confusion Matrix:
- [[ 68   0   1   4   5  13   4]
- [  4 120   5   3  18   9   2]
- [ 44  26 121  33  30  38  25]
- [ 10   4   8  95   3  10  25]
- [  2   6   0   5  64   0   1]
- [  6   0   0   0   1  41   1]
- [ 17   6   5   3  14  33  67]]
-Node Classification on random seed  27 -> 0.626
-Confusion Matrix:
- [[ 84   1   3   5   3  13   2]
- [  5 112   4   0  15   4   9]
- [ 25  19 134  27  32  20  36]
- [  9   4   8 118   9  10  10]
- [  2   3   0   3  64   0   4]
- [  7   1   4   2   2  44   9]
- [ 15   2  12  19  10   6  70]]
-Node Classification on random seed  28 -> 0.603
-Confusion Matrix:
- [[ 56   1   2   5   6  20  10]
- [  3 128   8   0  10   2   3]
- [ 22  16 133  34  34  22  51]
- [ 13   3  24  96   4  10   6]
- [  2   9   8   0  61   0   3]
- [  3   2   2   3   0  48   8]
- [ 10   3   6   9   9  11  81]]
-Node Classification on random seed  29 -> 0.613
-Confusion Matrix:
- [[ 84   3   2  14   1  10   3]
- [  6 118   3   3   5   2   7]
- [ 23  15 143  46  28  21  51]
- [ 11   2  26  86   3   3  15]
- [  1   5   3   1  56   1   5]
- [  4   0   2   0   4  48   8]
- [  7   3   6   8   8  18  78]]
-Node Classification on random seed  30 -> 0.603
-Confusion Matrix:
- [[ 64   3   1   9   1  11  15]
- [  8 115   2  10  11   5   6]
- [ 23  22 138  42  28  28  25]
- [  8   4  19 116   7   4   9]
- [  5   4   1   1  55   0   4]
- [  5   2   2   2   0  47   3]
- [ 15   3   8  16   8  17  68]]
-Node Classification on random seed  31 -> 0.614
-Confusion Matrix:
- [[ 67   3   6   7   2  16   8]
- [  3 124  10   0   3   2   5]
- [ 26  22 125  54  31  38  44]
- [  7   2   9  98   6   2  14]
- [  2   2  12   1  65   0   1]
- [  7   0   2   3   0  45   8]
- [ 10   1   1   2   3  11  90]]
-Node Classification on random seed  32 -> 0.627
-Confusion Matrix:
- [[ 72   3   1   6   7   8  13]
- [  7 135   6   4   2   6   3]
- [ 18  14 141  54  22  11  28]
- [ 22   0  16  92  10   5  17]
- [  0   9   5   4  47   2   1]
- [  2   2   5   4   0  46   4]
- [ 14   4   5   5   8  16  94]]
-Node Classification on random seed  33 -> 0.624
-Confusion Matrix:
- [[ 71   2   1   6   2  14  11]
- [  9 135   5   3   8   0   1]
- [ 21  19 131  31  27  16  45]
- [  9   7  12 107   5   7  16]
- [  2  10   3   1  60   0   1]
- [  9  10   0   1   4  46   2]
- [ 15   4   6  13   7  11  74]]
-Node Classification on random seed  34 -> 0.652
-Confusion Matrix:
- [[ 82   1   3   6   2   7   6]
- [  7 124   5   1  10   1   4]
- [ 18  24 181  38  22  10  33]
- [  7   3  16  91   9  17  12]
- [  2   5   6   1  57   0   1]
- [  6   3   0   3   0  43   4]
- [ 12   6   9   7   8  13  74]]
-Node Classification on random seed  35 -> 0.648
-Confusion Matrix:
- [[ 67   2   1   4   3  21   7]
- [  3 122   4   2   7   1   6]
- [ 21  25 156  25  21  33  40]
- [  6   4  12  98   8   4  10]
- [  0   4   3   2  72   1   2]
- [  7   1   1   3   2  53   3]
- [ 16   3   7  10   5  12  80]]
-Node Classification on random seed  36 -> 0.643
-Confusion Matrix:
- [[ 85   0   6   4   6  11  11]
- [  6 131   4   4   7   2   1]
- [ 33  28 137  32  12  17  40]
- [ 12   9   9 101   2   8  16]
- [  1   5   4   1  55   0   3]
- [  5   3   1   1   2  42  12]
- [ 10   6   4   6   9   4  92]]
-Node Classification on random seed  37 -> 0.626
-Confusion Matrix:
- [[ 67   4   7   2   3  16  16]
- [ 10 120  10   3   4   1   4]
- [ 19  35 161  32  18  13  34]
- [ 15   2  14  98   5   8  17]
- [  4   4   5   6  62   3   2]
- [  6   0   2   2   0  37   6]
- [  9   4   5   5   3  16  81]]
-Node Classification on random seed  38 -> 0.602
-Confusion Matrix:
- [[ 72   2   1   5   3  10  13]
- [  3 124   6   6   8   4   2]
- [ 21  30 154  41  19  21  41]
- [  8   3  12  87   9  10  20]
- [  2   3   6   1  58   0   6]
- [  5   0   0   2   0  43   3]
- [ 23   2   4  16   9  18  64]]
-Node Classification on random seed  39 -> 0.618
-Confusion Matrix:
- [[ 62   4   4   2   3  10  18]
- [  5 142   9   1   7   6   3]
- [ 25  26 121  39  26  27  43]
- [  6   4  13 116   3  10   7]
- [  0   9   2   4  60   4   4]
- [  5   3   1   3   1  50   5]
- [  6   0   7   3   2  22  67]]
-Node Classification on random seed  40 -> 0.624
-Confusion Matrix:
- [[ 52   8   8   3   7  14   6]
- [  9 125   3   3   8   4   3]
- [ 15  16 159  20  20  39  31]
- [ 10   3  20  99   8   7  18]
- [  0   5   6   0  65   0   4]
- [  8   1   1   1   1  45   3]
- [ 20   7   9   2   5  20  79]]
-Node Classification on random seed  41 -> 0.583
-Confusion Matrix:
- [[ 54   0   8   2   3  14  16]
- [  8 121   2   1  11   8   2]
- [ 19  21 139  36  41  28  50]
- [ 21   4   9  91   9  13  11]
- [  1   8   4   3  64   3   3]
- [  0   1   1   0   0  37   5]
- [ 11   7  15   2   7   9  77]]
-Node Classification on random seed  42 -> 0.633
-Confusion Matrix:
- [[ 74   3   6   3   1   9  13]
- [  2 126   5   4   8   1   6]
- [ 37  19 137  29  16  24  42]
- [ 13   4  14 106   6   3  14]
- [  2   3   7   2  63   1   1]
- [  3   1   4   1   3  53   3]
- [  8   4  11   5   6  20  74]]
-Node Classification on random seed  43 -> 0.607
-Confusion Matrix:
- [[ 80   0   4   2   1  14   4]
- [  4 123  15   5   1   3   5]
- [ 23  24 117  39  33  37  40]
- [ 12   0  16 111   2   6  13]
- [  0   5   5   0  61   2   4]
- [  5   0   2   4   2  42   4]
- [ 13   3   5   8   8  20  73]]
-Node Classification on random seed  44 -> 0.613
-Confusion Matrix:
- [[ 59   0   7   6   0  24   7]
- [  3 142   9   4   5   1  15]
- [ 25  38 134  33  10  17  39]
- [ 17   7  16  97   5   3  13]
- [  1  11   5   0  49   1   7]
- [  1   1   3   1   0  50   3]
- [  7   2  11   3   5  21  82]]
-Node Classification on random seed  45 -> 0.585
-Confusion Matrix:
- [[ 73   2   7   7   4  17   5]
- [  4 124   7   6   7   6   1]
- [ 23  23 109  24  49  19  54]
- [ 17   6  17  92   4   6   7]
- [  1   7   0   5  63   0   3]
- [ 12   1   2   1   0  36   8]
- [  8   3  11  10   4  17  88]]
-Node Classification on random seed  46 -> 0.587
-Confusion Matrix:
- [[ 67   1   5  16   1   9   5]
- [  7 102  18   0   4   4   5]
- [ 29   7 138  59  17  30  37]
- [  8   3  13 113   4   4  15]
- [  5   5   6   0  47   1   2]
- [  7   1   1   3   1  46   8]
- [ 19   1  18  12   4  18  74]]
-Node Classification on random seed  47 -> 0.621
-Confusion Matrix:
- [[ 76   3   4   6   3   6  13]
- [  4 145   3   6  10   0   1]
- [ 14  18 136  42  33  25  41]
- [ 11   2  10  99  12   8  25]
- [  4   5   1   1  60   0   0]
- [  6   1   2   3   1  41   3]
- [ 10   7  10   1   5  19  64]]
-Node Classification on random seed  48 -> 0.604
-Confusion Matrix:
- [[ 80   0   3   7   6  12   5]
- [  1 123  13   1  18   6   3]
- [ 20  14 143  28  23  25  62]
- [  8   1  17  95   7   9   8]
- [  1   4   3   0  65   5   2]
- [  5   0   0   5   0  38   4]
- [ 15   4   7  18   9  17  60]]
-Node Classification on random seed  49 -> 0.612
-Confusion Matrix:
- [[ 67   3   5  11   4   9  14]
- [  7 136  10   6   2   3   3]
- [ 23  31 127  32  42  10  44]
- [  7   2  10 101   0   2  18]
- [  2   5   1   0  70   1   1]
- [  5   1   2   6   3  34   7]
- [ 19   2   3  17   7   8  77]]
-Node Classification on random seed  50 -> 0.632
-Confusion Matrix:
- [[ 58   3   3   7   5  17   5]
- [  3 124   7   0   4   4   2]
- [ 23  27 154  25  13  28  46]
- [ 12   3  16 119   7   7  15]
- [  0   6   3   0  64   0   4]
- [  1   2   1   2   3  40   3]
- [  9   2  11  12   5  22  73]]
-Node Classification on random seed  51 -> 0.614
-Confusion Matrix:
- [[ 77   2   8   2   1   7  19]
- [  3 145   4   4   5   3   5]
- [ 18  25 109  24  52  27  38]
- [ 16   4   9  98  10   6  11]
- [  1   9   6   1  60   0   2]
- [  5   2   1   1   2  42   7]
- [  1   3   7  10   9  16  83]]
-Node Classification on random seed  52 -> 0.61
-Confusion Matrix:
- [[ 55   2  14   4   3   5  16]
- [  5 141   2   1   4   0   2]
- [ 18  33 131  44  23  23  49]
- [  7   5  22 100   6   3  16]
- [  3  11   3   3  57   2   2]
- [  5   1   2   1   0  49   4]
- [  8   3  10  11   4  10  77]]
-Node Classification on random seed  53 -> 0.634
-Confusion Matrix:
- [[ 73   1   4   2   3  16  10]
- [  2 127   7   6   7   2   3]
- [ 14  11 133  48  30  30  25]
- [ 14   2  19 109   9   4   4]
- [  1   9   7   2  56   1   1]
- [  5   0   0   1   0  53   6]
- [  5   5  15  11   6  18  83]]
-Node Classification on random seed  54 -> 0.623
-Confusion Matrix:
- [[ 80   0   2   0   4  13   7]
- [  7 160   5   1   4   7   2]
- [ 32  19 115  48  23  25  27]
- [ 13   5  22  80   4   9  12]
- [  4  11   1   4  63   1   1]
- [  9   0   2   2   0  43   5]
- [ 10   2   8   8   8  10  82]]
-Node Classification on random seed  55 -> 0.611
-Confusion Matrix:
- [[ 59   4   4   3   3   8  17]
- [  4 135   2   4   4   0   4]
- [ 18  24 127  40  34  27  37]
- [ 19   4   8 117   8   6  10]
- [  0   8  11   2  60   0   1]
- [  9   1   1   6   1  43   6]
- [ 23   5   7   2   3  11  70]]
-Node Classification on random seed  56 -> 0.623
-Confusion Matrix:
- [[ 61   1   3   8   2  12  17]
- [  4 134   4   6   4   9   3]
- [ 10  25 144  40  23  21  46]
- [  8   4  18 104   0   7  10]
- [  1   6   5   2  60   1   2]
- [  3   2   4   3   1  42   9]
- [ 10   2  13   9   1  18  78]]
-Node Classification on random seed  57 -> 0.599
-Confusion Matrix:
- [[ 61   1   6   6   2  14   4]
- [  4 137   2   1   9   5   2]
- [ 32  11 142  35  28  38  34]
- [  6   4  15  94   4   9  24]
- [  3   8   3   1  51   1   2]
- [  8   3   1   9   2  44   6]
- [ 13   5   6   4  10  20  70]]
-Node Classification on random seed  58 -> 0.586
-Confusion Matrix:
- [[ 69   6  13   1   4   5   5]
- [  3 120   2   0  18   0   5]
- [ 32  25 109  67  25   5  43]
- [ 12   8   4 101   3   2  20]
- [  5   5   3   0  61   0   2]
- [  7   2   1   0   5  45   4]
- [ 15   7  22  11   6  11  81]]
-Node Classification on random seed  59 -> 0.618
-Confusion Matrix:
- [[ 60   3   2   1   3  17   9]
- [  2 127   7   0   9   1   2]
- [ 24  41 161  19  41  21  33]
- [ 24   3  24  90   9   1   7]
- [  1   8   1   1  62   1   0]
- [  7   2   1   0   1  37  12]
- [  7   3   4   8  11  11  81]]
-Node Classification on random seed  60 -> 0.627
-Confusion Matrix:
- [[ 64   2   4   7   2   9   4]
- [  6 135   4   2   3   2   6]
- [ 19  14 153  44  30  34  32]
- [ 10   1  12 105   3   6  21]
- [  0   7   6   2  65   2   2]
- [  3   1   2   1   0  41   2]
- [  7   3  17   6  24  11  64]]
-Node Classification on random seed  61 -> 0.613
-Confusion Matrix:
- [[ 71   4   8   7   7  14   5]
- [  1 136   4   4   2   1   0]
- [ 25  20 135  32  21  24  51]
- [  8   3  26 111   2   6  15]
- [  1   5   3   5  55   0   4]
- [ 18   0   0   1   4  32   2]
- [ 17   5   4   7   6  15  73]]
-Node Classification on random seed  62 -> 0.627
-Confusion Matrix:
- [[ 67   4   1  11   4   7  13]
- [  8 130   3   2   9   3   4]
- [ 22  24 135  40  33  22  36]
- [  8   4  10 110   9  11   7]
- [  8   4   2   1  60   0   1]
- [  4   1   0   1   0  46   6]
- [ 17   2   3  10   5  13  79]]
-Node Classification on random seed  63 -> 0.587
-Confusion Matrix:
- [[ 64   4   0   1  10  12  11]
- [  1 115  10   4  12   3   7]
- [ 32  29 135  37  21  25  36]
- [  8  11  15 100  11   6   7]
- [  0   3   5   0  72   0   2]
- [  9   0   7   1   0  43   5]
- [ 12   5   9  12   5  25  58]]
-Node Classification on random seed  64 -> 0.626
-Confusion Matrix:
- [[ 65   4   4   2   3  17   7]
- [  2 129  17   1   0   5   6]
- [ 24  13 151  29  21  27  44]
- [ 17   4  14  90  11   6  16]
- [  1   7   2   0  63   1   0]
- [  4   0   1   0   0  48   5]
- [ 11   1  15   8   6  18  80]]
-Node Classification on random seed  65 -> 0.605
-Confusion Matrix:
- [[ 64   1   8   2   4   9   8]
- [  6 111   7   1  14   3   7]
- [ 26  26 124  46  25  27  37]
- [  7   3  22 113   7   5  10]
- [  0   4   2   1  70   1   6]
- [  6   1   3   0   4  40   4]
- [  8   5   3   8   8  20  83]]
-Node Classification on random seed  66 -> 0.607
-Confusion Matrix:
- [[ 60   3   1   9   4   8  12]
- [  7 115   3   2  20   6   2]
- [ 27  16 136  38  25  23  53]
- [  8   1  13 113   3  12  10]
- [  1   7   5   0  61   0   5]
- [ 11   1   3   2   3  50   3]
- [ 11   4   5   4   9  13  72]]
-Node Classification on random seed  67 -> 0.607
-Confusion Matrix:
- [[ 67   3   1   5   3  10   9]
- [  4 126   9   3   7   3   3]
- [ 31  20 154  36  28  19  42]
- [  8   2  18  96   2   7  25]
- [  2   6   2   2  64   1   1]
- [  3   1   0   3   0  35   8]
- [ 15   6   6  10  14  15  65]]
-Node Classification on random seed  68 -> 0.65
-Confusion Matrix:
- [[ 78   3   3   5   5   5   7]
- [ 11 119   3   3   7   0   1]
- [ 37  32 161  26  23  21  36]
- [ 13   6  10 117   4   4   8]
- [  1   1   4   5  56   2   5]
- [  6   3   1   0   3  43   4]
- [ 15   1  11   4   2   9  76]]
-Node Classification on random seed  69 -> 0.581
-Confusion Matrix:
- [[ 72   3   1   1   3  19  12]
- [  3 143   4   2   8   3   4]
- [ 35  26 101  31  26  35  40]
- [ 16   6   4 108   9   9  15]
- [  0   4   2   1  68   2   2]
- [  4   1   5   4   2  42   4]
- [ 15   1   7  21   3  26  47]]
-Node Classification on random seed  70 -> 0.593
-Confusion Matrix:
- [[ 76   0   8   4   3   8   7]
- [  5 126  13   3   5   3   7]
- [ 37  25 112  35  30  20  48]
- [  4   5  12  95  15  11   5]
- [  3   4   2   0  66   0   1]
- [  3   0   5   2   1  42   3]
- [ 10   2  26   7   9  16  76]]
-Node Classification on random seed  71 -> 0.635
-Confusion Matrix:
- [[ 63   1   3   6   8  10  19]
- [  8 120   6   2   7  11   1]
- [ 21   9 167  18  19  29  47]
- [  8   3  15 115   3   8  15]
- [  2   8   6   0  49   2   1]
- [  3   2   5   1   3  55   6]
- [  3   5  10   6   1  24  66]]
-Node Classification on random seed  72 -> 0.574
-Confusion Matrix:
- [[ 67   2   8   4   5  12   4]
- [  6 108   4   2  15   5   6]
- [ 22  24 119  51  42  26  22]
- [ 16   0  12 102   6  10  15]
- [  2   3   8   1  61   1   5]
- [  6   4   3   0   1  38  17]
- [ 12   4   9  14   4  13  79]]
-Node Classification on random seed  73 -> 0.634
-Confusion Matrix:
- [[ 75   4   5   5   2  13   7]
- [  3 144   3   7   8   4   3]
- [ 34   9 121  39  28  27  29]
- [  4   3   8 110   5   4  18]
- [  0  10   2   1  74   0   1]
- [  5   0   0   3   7  41   1]
- [ 14   3  18  15   4  10  69]]
-Node Classification on random seed  74 -> 0.591
-Confusion Matrix:
- [[ 78   0   7   7   3   5  20]
- [  7 116   2   1   3   0  12]
- [ 17  25 137  40  20  32  37]
- [ 12  12   7  98   4  14  19]
- [  0   9   9   0  50   1   2]
- [ 11   4   4   1   1  38   6]
- [ 15   4   7   2   7  20  74]]
-Node Classification on random seed  75 -> 0.589
-Confusion Matrix:
- [[ 62   1   8   7   3  13   7]
- [  6 108   3   2   8   7   7]
- [ 16  24 159  34  24  20  42]
- [  7   3  13 107   3   8  11]
- [  0   3   5   2  62   2   3]
- [  5   3   9   3   0  42   5]
- [ 11   4  12  11  29  27  49]]
-Node Classification on random seed  76 -> 0.604
-Confusion Matrix:
- [[ 70   2   2   4   5  11  10]
- [  5 126   3   1   3   2   3]
- [ 23  24 145  50  29  24  42]
- [  9   6  25  74   2  12  16]
- [  0  10   5   1  51   4   2]
- [  9   0   0   2   0  45   8]
- [ 10   3   5   6   7  11  93]]
-Node Classification on random seed  77 -> 0.614
-Confusion Matrix:
- [[ 61   4   6   4   1  10  13]
- [  1 128   7   2   5   5   5]
- [ 26  23 131  46  40  10  51]
- [  9   3  12 125   3   6  10]
- [  0   2   1   6  47   1   2]
- [  7   4   3   1   0  39   8]
- [ 15   7   5   5  10   7  83]]
-Node Classification on random seed  78 -> 0.605
-Confusion Matrix:
- [[ 66   3   0   5   4  12  13]
- [  3 136   4   1   6   1  10]
- [ 28  24 119  20  36  25  43]
- [ 12   0  19  83  12  15  22]
- [  2   6   4   1  63   3   5]
- [  5   1   3   1   0  54   2]
- [ 16   2   2   6  10   8  84]]
-Node Classification on random seed  79 -> 0.644
-Confusion Matrix:
- [[ 94   1   5   6   4   6   9]
- [  5 111  14   6   9   3   2]
- [ 20  14 156  37  25  16  44]
- [  3   3   9 104   4   4  14]
- [  3   4   3   4  70   1   2]
- [  5   1   5   3   3  40   2]
- [ 11  11   7  11   1  16  69]]
-Node Classification on random seed  80 -> 0.653
-Confusion Matrix:
- [[ 70   4   4   2   0  10  10]
- [  4 145   6   6   1   1   0]
- [ 26  29 146  28  29  37  27]
- [  7   3  13 107   9   8  16]
- [  0   8   3   2  51   1   1]
- [  3   0   5   2   0  45   5]
- [ 10   2   8   3   7   7  89]]
-Node Classification on random seed  81 -> 0.606
-Confusion Matrix:
- [[ 56   1  13   5   1  16  14]
- [  5 124   6   0   5   2   1]
- [ 16  23 145  28  11  38  43]
- [ 14   4  25 108   2  10   9]
- [  0   6   5   3  56   0   3]
- [  6   2   1  11   0  42   4]
- [ 17   4   7  12   4  17  75]]
-Node Classification on random seed  82 -> 0.603
-Confusion Matrix:
- [[ 74   3  12   5   5   6  13]
- [  2 135   3   3  12   4   1]
- [ 41  15 120  22  23  14  55]
- [ 12   9  24  86  11   5  12]
- [  2   5   6   0  65   1   1]
- [  7   0   5   0   0  48   1]
- [ 12   4  15  10   6  10  75]]
-Node Classification on random seed  83 -> 0.594
-Confusion Matrix:
- [[ 67   3   4   1   8  13  13]
- [  2 115   7   0   6   1   6]
- [ 23  29 123  24  36  21  52]
- [ 14  10  12 100  10   6  10]
- [  0   2   5   2  58   3   5]
- [  6   4   2   0   6  51   7]
- [  7   4  11   7   4  20  80]]
-Node Classification on random seed  84 -> 0.603
-Confusion Matrix:
- [[ 79   0   7   2   4  10   7]
- [  9 119   9   1   3   2   1]
- [ 23  32 137  48  29  11  38]
- [ 19   5   9  88   9  13  11]
- [  3  10   2   0  67   0   1]
- [  8   0   2   0   0  47   6]
- [ 19   5  14   4   6  15  66]]
-Node Classification on random seed  85 -> 0.607
-Confusion Matrix:
- [[ 76   2   5   2   4   5   8]
- [  5 149   4   2   2   5   2]
- [ 18  24 117  50  22  38  33]
- [ 14  10  15  85   9   7  10]
- [  3   9   6   2  56   2   3]
- [  9   0   2   3   0  32  11]
- [  6   5   8   5  11  12  92]]
-Node Classification on random seed  86 -> 0.606
-Confusion Matrix:
- [[ 67   2   5   6   4  10  14]
- [  4 124   9   4  11   3   1]
- [ 26  20 122  45  22  29  42]
- [  7   1  21 109   6   4  10]
- [  2   4   1   2  74   1   2]
- [ 13   3   4   4   0  35   7]
- [  6   4   4  17   6   8  75]]
-Node Classification on random seed  87 -> 0.597
-Confusion Matrix:
- [[ 66   3   2   8   3  11   8]
- [  4 121   5   2   4   4   5]
- [ 10  25 131  34  23  32  43]
- [ 16   1  20 102   8   6  16]
- [  0   2   6   2  68   1   0]
- [  6   2   0   3   1  46   6]
- [  8  11   4  26  11  21  63]]
-Node Classification on random seed  88 -> 0.622
-Confusion Matrix:
- [[ 69   0   6   7   6   9   6]
- [  5 116   9  13   5   3   4]
- [ 19  11 165  31  42  23  27]
- [ 11   1  15 102  17   7   5]
- [  1   4   4   0  53   0   4]
- [  2   1   1   0   1  51   1]
- [ 15   5   9  25   7  16  66]]
-Node Classification on random seed  89 -> 0.628
-Confusion Matrix:
- [[ 87   6   1  10   3   7   9]
- [  4 124   3   3   7   7   3]
- [ 30  15 145  29  26  14  47]
- [ 10   4  17 102   4   5  12]
- [  3   3   5   3  58   1   7]
- [  6   0   6   3   2  35   9]
- [  3   3   6  18  11   7  77]]
-Node Classification on random seed  90 -> 0.62
-Confusion Matrix:
- [[ 78   0   3   9   4   8  10]
- [  3 121   7   0   4   5  12]
- [ 20  20 132  43  29  25  34]
- [  2   8  22 109   1   5  10]
- [  2   9   7   4  54   0   1]
- [  3   1   2   2   0  48   9]
- [ 10   9  15   5   6  11  78]]
-Node Classification on random seed  91 -> 0.593
-Confusion Matrix:
- [[ 61   0   4   6   5  10  18]
- [  3 118  13   2  13   3   7]
- [ 19  18 137  50  27  17  40]
- [ 20   1   9  97   7   8  19]
- [  2   7   4   1  58   5   1]
- [  6   0   1   2   1  44   6]
- [ 13   2   8  11   6  12  78]]
-Node Classification on random seed  92 -> 0.634
-Confusion Matrix:
- [[ 61   3   6   5   2   3  28]
- [  5 145   3   2   3   1   4]
- [ 10  22 121  44  23  13  48]
- [ 13   6   8 106   6   2   7]
- [  2  11   4   0  65   2   0]
- [  6   0   3   5   1  47   6]
- [ 14   8  12  12   2  11  89]]
-Node Classification on random seed  93 -> 0.605
-Confusion Matrix:
- [[ 72   3   7   3   5   9   9]
- [  2 120  12   2   5   2   2]
- [ 13  28 139  34  32  12  33]
- [ 25   3  28  67   8   4  17]
- [  1   9   8   0  62   0   2]
- [  6   5   4   2   0  47   5]
- [ 21   4   8   2   7  13  98]]
-Node Classification on random seed  94 -> 0.597
-Confusion Matrix:
- [[ 73   1   1   5   7  17   8]
- [  9 139   3   2   6   4   6]
- [ 26  26 123  37  24  18  43]
- [  8   1  21  92   6  12  11]
- [  0   7   6   4  59   3   1]
- [  8   0   0   2   0  42   8]
- [ 14   5  16  11   5  11  69]]
-Node Classification on random seed  95 -> 0.589
-Confusion Matrix:
- [[ 60   0   3   7   1   3  21]
- [ 13 121  19   6   3   5   5]
- [ 17  18 140  53  19   9  58]
- [  9   4  17  95   8   2  21]
- [  4   7   6   1  65   1   0]
- [  7   2   1   4   2  38  11]
- [  6   3  10  11   7   7  70]]
-Node Classification on random seed  96 -> 0.628
-Confusion Matrix:
- [[ 60   6   6   7   2  15  14]
- [  4 132   8   4   2   2   5]
- [ 12  27 141  28  23  18  40]
- [  7   5  18 118   6   4  13]
- [  0   6   6   2  65   1   1]
- [  5   1   0   9   1  42   5]
- [ 10   1   6  18   9  15  70]]
-Node Classification on random seed  97 -> 0.619
-Confusion Matrix:
- [[ 76   2   8   7   9  13   2]
- [  1 122   5   4  13   7   0]
- [ 18  28 159  29  24  26  34]
- [  7   4  24  92   3   9  16]
- [  0  12   4   3  53   0   4]
- [  0   2   9   2   2  38   2]
- [  5   5   2   8  10  18  79]]
-Node Classification on random seed  98 -> 0.615
-Confusion Matrix:
- [[ 56   1  11   5   7  19   1]
- [  6 117   6   5   8   8   0]
- [ 21  12 157  48  24  28  20]
- [ 16   0  14 113   5   6   7]
- [  2  10   8   0  63   1   3]
- [  8   1   3   1   0  46   3]
- [ 13   2   8  11   9  24  63]]
-Node Classification on random seed  99 -> 0.641
-Confusion Matrix:
- [[ 77   0   5   8   0   6  16]
- [  8 131   7   6   3   1   5]
- [ 30  15 145  24  31  17  37]
- [  6   1   9 102   5   9  11]
- [  8   7   3   2  64   1   3]
- [  8   0   0   0   0  44  12]
- [  7   5   9   8   8  18  78]]
-[0.561, 0.611, 0.586, 0.623, 0.613, 0.63, 0.604, 0.576, 0.573, 0.56, 0.615, 0.593, 0.583, 0.584, 0.586, 0.645, 0.617, 0.625, 0.605, 0.626, 0.629, 0.631, 0.626, 0.64, 0.589, 0.621, 0.576, 0.626, 0.603, 0.613, 0.603, 0.614, 0.627, 0.624, 0.652, 0.648, 0.643, 0.626, 0.602, 0.618, 0.624, 0.583, 0.633, 0.607, 0.613, 0.585, 0.587, 0.621, 0.604, 0.612, 0.632, 0.614, 0.61, 0.634, 0.623, 0.611, 0.623, 0.599, 0.586, 0.618, 0.627, 0.613, 0.627, 0.587, 0.626, 0.605, 0.607, 0.607, 0.65, 0.581, 0.593, 0.635, 0.574, 0.634, 0.591, 0.589, 0.604, 0.614, 0.605, 0.644, 0.653, 0.606, 0.603, 0.594, 0.603, 0.607, 0.606, 0.597, 0.622, 0.628, 0.62, 0.593, 0.634, 0.605, 0.597, 0.589, 0.628, 0.619, 0.615, 0.641]
-[80, 34, 68, 35, 15, 79, 36, 99, 23, 71]
-Maximum:  0.653 Seed:  80
-Average:  0.6111899999999997
-10 Higest Scores:
-1 : 0.653 on Seed 80
-2 : 0.652 on Seed 34
-3 : 0.65 on Seed 68
-4 : 0.648 on Seed 35
-5 : 0.645 on Seed 15
-6 : 0.644 on Seed 79
-7 : 0.643 on Seed 36
-8 : 0.641 on Seed 99
-9 : 0.64 on Seed 23
-10 : 0.635 on Seed 71
diff --git a/EP/Cora_node_classification/nc_emb_uniform_m20_10000.txt b/EP/Cora_node_classification/nc_emb_uniform_m20_10000.txt
deleted file mode 100644
index 8ad851ac2c80fa9073f01690be768fd74da00727..0000000000000000000000000000000000000000
--- a/EP/Cora_node_classification/nc_emb_uniform_m20_10000.txt
+++ /dev/null
@@ -1,90015 +0,0 @@
-Node Classification on random seed  0 -> 0.561
-Confusion Matrix:
- [[ 57   2   2  15   4  12  14]
- [  6 118  10   1  13   3   0]
- [ 24  24 129  39  25  22  54]
- [ 12   5  23  93   5   6  23]
- [  1   7   5   4  55   1   0]
- [  5   0   1   4   3  51   4]
- [  9   2   7   6  29   7  58]]
-Node Classification on random seed  1 -> 0.611
-Confusion Matrix:
- [[ 88   3   4   5   3   8   9]
- [  6 117   6   3  12   9   0]
- [ 32  17 125  28  43  23  42]
- [  9   3   6 112  11   3  16]
- [  2   7   1   0  59   4   1]
- [  5   4   1   1   2  44   4]
- [ 14   3  11   6  12  10  66]]
-Node Classification on random seed  2 -> 0.586
-Confusion Matrix:
- [[ 84   3   4   5   1  15   9]
- [  5 130   4   2   2   4   7]
- [ 32  42 115  35  35  23  34]
- [  6  14   7 101  11  10  20]
- [  2   7   1   3  53   0   1]
- [  2   2   5   3   0  30   7]
- [  5   3  11  12   6  14  73]]
-Node Classification on random seed  3 -> 0.623
-Confusion Matrix:
- [[ 74   0   0   1   2  23   9]
- [  5 131   3   1  13   2   8]
- [ 18  26 144  33  34  18  40]
- [ 16   6  18  98   3   3  11]
- [  2   2   1   1  57   2   3]
- [  9   1   3   1   0  39   6]
- [ 17   5  12   9   3   7  80]]
-Node Classification on random seed  4 -> 0.613
-Confusion Matrix:
- [[ 88   2   9   7   4   6   5]
- [ 10 132   3   3  11   2   5]
- [ 26  29 127  31  38  21  36]
- [ 15   5  18  97   2   2   6]
- [  0   9   5   3  48   0   1]
- [  8   0   7   0   1  46   3]
- [ 14   1  12   6   6  15  75]]
-Node Classification on random seed  5 -> 0.63
-Confusion Matrix:
- [[ 63   2  15   7   3   6   5]
- [  5 123   6   3   6   4  10]
- [ 32  19 131  38  33  10  42]
- [  9   7   9 122   5   1   7]
- [  2   6   4   4  59   0   4]
- [  3   0   2   2   0  52   4]
- [  6   3  10  14   4  18  80]]
-Node Classification on random seed  6 -> 0.604
-Confusion Matrix:
- [[ 67   3   2   6   3  13  14]
- [  6 116   1   0   4   1   3]
- [ 18  44 122  17  50  20  46]
- [  7   5  15 102   8   5   9]
- [  1   9   5   2  59   2   1]
- [  9   1   2   3   5  45   3]
- [  7   4  11   7   5  19  93]]
-Node Classification on random seed  7 -> 0.576
-Confusion Matrix:
- [[ 73   5   0   8   6  14   8]
- [  4 113   7   0   4   5   3]
- [ 20  13  96  42  70  34  38]
- [  6   7  24  96   4  10   7]
- [  2   5   2   1  73   0   3]
- [  2   2   6   3   0  51   4]
- [ 16   3   7   4  12  13  74]]
-Node Classification on random seed  8 -> 0.573
-Confusion Matrix:
- [[ 78   2   5   2   2   4  10]
- [  5 128   3   5   9   1   4]
- [ 26  15 126  56  34  12  53]
- [ 14   8  30  89   4   1  11]
- [  1   4   7   3  53   0   4]
- [  5   4   3   1   2  31  15]
- [ 15   3  18   6   9  11  68]]
-Node Classification on random seed  9 -> 0.56
-Confusion Matrix:
- [[ 62   4   5   1   2  15  10]
- [  9 133   9   2   6   4   0]
- [ 24  15 104  37  57  20  42]
- [ 19   2  23  85   3   7  21]
- [  3   8   1   3  57   1   1]
- [  5   1   1   1   0  55   3]
- [  8   4  14   5  29  15  64]]
-Node Classification on random seed  10 -> 0.615
-Confusion Matrix:
- [[ 80   4   1   6   2   7  16]
- [  6 118   2   3  13   0   3]
- [ 31  21 130  44  39  17  34]
- [  6   1  19 105   7   4  24]
- [  1   3   4   1  48   0   4]
- [  8   5   1   0   0  51   4]
- [ 18   7   8   2   9   0  83]]
-Node Classification on random seed  11 -> 0.593
-Confusion Matrix:
- [[ 53   3   4   8   6  15  19]
- [  3 132   4   4   4   5   4]
- [ 24  23 124  42  28  26  51]
- [  3   3  11 102   3   7  23]
- [  0   6   2   3  59   1   1]
- [  1   0   5   0   1  45  15]
- [ 11   4   5  10   7  12  78]]
-Node Classification on random seed  12 -> 0.583
-Confusion Matrix:
- [[ 85   2   6   3   4  11  11]
- [  5 120  14   2   8   2   7]
- [ 34  15 106  44  27  18  53]
- [ 11   4  11  91   7   9  20]
- [  2   4   9   2  63   0   4]
- [  5   1   0   2   2  48   5]
- [  8   3  17   6   4  15  70]]
-Node Classification on random seed  13 -> 0.584
-Confusion Matrix:
- [[ 73   7   3  10   6   7   4]
- [  8 132   3   5  18   1   3]
- [ 28  38 132  36  34  25  23]
- [ 12   1  11  92  19   2   4]
- [  0   9   3   3  52   1   4]
- [  7   0   5   3   0  41   6]
- [ 15   5  18  18   3   8  62]]
-Node Classification on random seed  14 -> 0.586
-Confusion Matrix:
- [[ 77   1   4   4   6   9   8]
- [  9 115  10   1   8   8   0]
- [ 23  21 111  45  59  20  27]
- [ 21   2  12  97  10   9  17]
- [  0   5   3   1  61   1   1]
- [  3   2   3   2   3  44   4]
- [  8   2  15   4  11  12  81]]
-Node Classification on random seed  15 -> 0.645
-Confusion Matrix:
- [[ 76   4   2   7   3   8   9]
- [  3 129   9  13   2   2   1]
- [ 19  16 182  26  23  16  30]
- [ 17   3  18  96   7  12  13]
- [  1   6   5   4  50   0   3]
- [  5   3   2   5   2  37  12]
- [  6   4  10   9   2  13  75]]
-Node Classification on random seed  16 -> 0.617
-Confusion Matrix:
- [[ 67   1   0   7   7  15  10]
- [  6 120   4   5   9   6   4]
- [ 15  23 135  41  27  13  60]
- [ 14   7   9 119   2   6  11]
- [  1   6   4   0  64   1   2]
- [  3   3   4   0   2  36  12]
- [ 10   3   6   3   7  14  76]]
-Node Classification on random seed  17 -> 0.625
-Confusion Matrix:
- [[ 65   3   3   7   1   4  19]
- [  6 132   5   3   8   1   2]
- [ 34  21 154  22  28  36  32]
- [  7   2  18  96   4   6  21]
- [  1   8   1   0  59   0   6]
- [  7   1   1   3   1  36   9]
- [ 10   1  15   5   6   7  83]]
-Node Classification on random seed  18 -> 0.605
-Confusion Matrix:
- [[ 58   2   5  12   5   9  22]
- [  9 121   5   2  12   6   7]
- [ 16  24 154  27  34  17  48]
- [  8   2  20 101   3   9  14]
- [  0   3   3   3  55   0   3]
- [  7   0   1   0   3  36   7]
- [ 11   7  11   4   8   6  80]]
-Node Classification on random seed  19 -> 0.626
-Confusion Matrix:
- [[ 59   6   7   6   3   8  11]
- [  6 127   4   3   8   2   3]
- [ 35  17 149  30  37  16  26]
- [ 14   6  15 111   9   6   8]
- [  1   8   0   0  64   1   2]
- [  7   5   1   3   2  37   3]
- [  9   6  16   9   8   7  79]]
-Node Classification on random seed  20 -> 0.629
-Confusion Matrix:
- [[ 80   7   1   4   3  11   7]
- [  7 116   3   9  11   6   3]
- [ 24  22 175  26  19  30  37]
- [ 25   2  12  83   3  13   7]
- [  0   3   3   1  58   2   3]
- [  4   2   1   6   0  48   3]
- [ 15   2  13   2   1  18  69]]
-Node Classification on random seed  21 -> 0.631
-Confusion Matrix:
- [[ 83   1   2   8   1  11   8]
- [  2 134   8   3   6   3   9]
- [ 22  20 129  32  18  30  34]
- [  3   4  22 113   1   6   6]
- [  2   8  11   6  57   0   2]
- [  5   2   6   1   1  48   4]
- [ 11   2  13   7   6  22  67]]
-Node Classification on random seed  22 -> 0.626
-Confusion Matrix:
- [[ 76   3   8   6   6   2  14]
- [  2 128   4   4   2   0   4]
- [ 35  19 118  34  32  24  36]
- [  8  11  25 105   8   4   6]
- [  2   8   2   0  66   1   1]
- [  1   1   4   1   0  53   8]
- [  7   5  14   6   8   8  80]]
-Node Classification on random seed  23 -> 0.64
-Confusion Matrix:
- [[ 87   1   3   4   2   4   7]
- [  6 115   4   2  10   6   2]
- [ 27  15 151  18  26  27  39]
- [ 10   5  14 110   3   8   7]
- [  1  10  12   3  62   0   1]
- [  5   2   3   0   0  50   6]
- [ 13   6  13   6   5  24  65]]
-Node Classification on random seed  24 -> 0.589
-Confusion Matrix:
- [[ 46  10   4   1   5  19  24]
- [  4 121   5   6   7   3   3]
- [ 25  35 137  35  30  44  22]
- [ 15   3  15 102   6   3  12]
- [  2   9   2   5  60   1   0]
- [  0   3   2   1   0  47   6]
- [  6   2   7   6   5  18  76]]
-Node Classification on random seed  25 -> 0.621
-Confusion Matrix:
- [[ 91   0   6   3   2   6  13]
- [  3 135   8   1  12   2   2]
- [ 23  25 154  23  29  18  35]
- [ 10   6  21  93   1   6  15]
- [  2   9   4   3  61   0   4]
- [  6   1   0   2   4  37   1]
- [ 21   5  20   3  14  10  50]]
-Node Classification on random seed  26 -> 0.576
-Confusion Matrix:
- [[ 68   0   1   4   5  13   4]
- [  4 120   5   3  18   9   2]
- [ 44  26 121  33  30  38  25]
- [ 10   4   8  95   3  10  25]
- [  2   6   0   5  64   0   1]
- [  6   0   0   0   1  41   1]
- [ 17   6   5   3  14  33  67]]
-Node Classification on random seed  27 -> 0.626
-Confusion Matrix:
- [[ 84   1   3   5   3  13   2]
- [  5 112   4   0  15   4   9]
- [ 25  19 134  27  32  20  36]
- [  9   4   8 118   9  10  10]
- [  2   3   0   3  64   0   4]
- [  7   1   4   2   2  44   9]
- [ 15   2  12  19  10   6  70]]
-Node Classification on random seed  28 -> 0.603
-Confusion Matrix:
- [[ 56   1   2   5   6  20  10]
- [  3 128   8   0  10   2   3]
- [ 22  16 133  34  34  22  51]
- [ 13   3  24  96   4  10   6]
- [  2   9   8   0  61   0   3]
- [  3   2   2   3   0  48   8]
- [ 10   3   6   9   9  11  81]]
-Node Classification on random seed  29 -> 0.613
-Confusion Matrix:
- [[ 84   3   2  14   1  10   3]
- [  6 118   3   3   5   2   7]
- [ 23  15 143  46  28  21  51]
- [ 11   2  26  86   3   3  15]
- [  1   5   3   1  56   1   5]
- [  4   0   2   0   4  48   8]
- [  7   3   6   8   8  18  78]]
-Node Classification on random seed  30 -> 0.603
-Confusion Matrix:
- [[ 64   3   1   9   1  11  15]
- [  8 115   2  10  11   5   6]
- [ 23  22 138  42  28  28  25]
- [  8   4  19 116   7   4   9]
- [  5   4   1   1  55   0   4]
- [  5   2   2   2   0  47   3]
- [ 15   3   8  16   8  17  68]]
-Node Classification on random seed  31 -> 0.614
-Confusion Matrix:
- [[ 67   3   6   7   2  16   8]
- [  3 124  10   0   3   2   5]
- [ 26  22 125  54  31  38  44]
- [  7   2   9  98   6   2  14]
- [  2   2  12   1  65   0   1]
- [  7   0   2   3   0  45   8]
- [ 10   1   1   2   3  11  90]]
-Node Classification on random seed  32 -> 0.627
-Confusion Matrix:
- [[ 72   3   1   6   7   8  13]
- [  7 135   6   4   2   6   3]
- [ 18  14 141  54  22  11  28]
- [ 22   0  16  92  10   5  17]
- [  0   9   5   4  47   2   1]
- [  2   2   5   4   0  46   4]
- [ 14   4   5   5   8  16  94]]
-Node Classification on random seed  33 -> 0.624
-Confusion Matrix:
- [[ 71   2   1   6   2  14  11]
- [  9 135   5   3   8   0   1]
- [ 21  19 131  31  27  16  45]
- [  9   7  12 107   5   7  16]
- [  2  10   3   1  60   0   1]
- [  9  10   0   1   4  46   2]
- [ 15   4   6  13   7  11  74]]
-Node Classification on random seed  34 -> 0.652
-Confusion Matrix:
- [[ 82   1   3   6   2   7   6]
- [  7 124   5   1  10   1   4]
- [ 18  24 181  38  22  10  33]
- [  7   3  16  91   9  17  12]
- [  2   5   6   1  57   0   1]
- [  6   3   0   3   0  43   4]
- [ 12   6   9   7   8  13  74]]
-Node Classification on random seed  35 -> 0.648
-Confusion Matrix:
- [[ 67   2   1   4   3  21   7]
- [  3 122   4   2   7   1   6]
- [ 21  25 156  25  21  33  40]
- [  6   4  12  98   8   4  10]
- [  0   4   3   2  72   1   2]
- [  7   1   1   3   2  53   3]
- [ 16   3   7  10   5  12  80]]
-Node Classification on random seed  36 -> 0.643
-Confusion Matrix:
- [[ 85   0   6   4   6  11  11]
- [  6 131   4   4   7   2   1]
- [ 33  28 137  32  12  17  40]
- [ 12   9   9 101   2   8  16]
- [  1   5   4   1  55   0   3]
- [  5   3   1   1   2  42  12]
- [ 10   6   4   6   9   4  92]]
-Node Classification on random seed  37 -> 0.626
-Confusion Matrix:
- [[ 67   4   7   2   3  16  16]
- [ 10 120  10   3   4   1   4]
- [ 19  35 161  32  18  13  34]
- [ 15   2  14  98   5   8  17]
- [  4   4   5   6  62   3   2]
- [  6   0   2   2   0  37   6]
- [  9   4   5   5   3  16  81]]
-Node Classification on random seed  38 -> 0.602
-Confusion Matrix:
- [[ 72   2   1   5   3  10  13]
- [  3 124   6   6   8   4   2]
- [ 21  30 154  41  19  21  41]
- [  8   3  12  87   9  10  20]
- [  2   3   6   1  58   0   6]
- [  5   0   0   2   0  43   3]
- [ 23   2   4  16   9  18  64]]
-Node Classification on random seed  39 -> 0.618
-Confusion Matrix:
- [[ 62   4   4   2   3  10  18]
- [  5 142   9   1   7   6   3]
- [ 25  26 121  39  26  27  43]
- [  6   4  13 116   3  10   7]
- [  0   9   2   4  60   4   4]
- [  5   3   1   3   1  50   5]
- [  6   0   7   3   2  22  67]]
-Node Classification on random seed  40 -> 0.624
-Confusion Matrix:
- [[ 52   8   8   3   7  14   6]
- [  9 125   3   3   8   4   3]
- [ 15  16 159  20  20  39  31]
- [ 10   3  20  99   8   7  18]
- [  0   5   6   0  65   0   4]
- [  8   1   1   1   1  45   3]
- [ 20   7   9   2   5  20  79]]
-Node Classification on random seed  41 -> 0.583
-Confusion Matrix:
- [[ 54   0   8   2   3  14  16]
- [  8 121   2   1  11   8   2]
- [ 19  21 139  36  41  28  50]
- [ 21   4   9  91   9  13  11]
- [  1   8   4   3  64   3   3]
- [  0   1   1   0   0  37   5]
- [ 11   7  15   2   7   9  77]]
-Node Classification on random seed  42 -> 0.633
-Confusion Matrix:
- [[ 74   3   6   3   1   9  13]
- [  2 126   5   4   8   1   6]
- [ 37  19 137  29  16  24  42]
- [ 13   4  14 106   6   3  14]
- [  2   3   7   2  63   1   1]
- [  3   1   4   1   3  53   3]
- [  8   4  11   5   6  20  74]]
-Node Classification on random seed  43 -> 0.607
-Confusion Matrix:
- [[ 80   0   4   2   1  14   4]
- [  4 123  15   5   1   3   5]
- [ 23  24 117  39  33  37  40]
- [ 12   0  16 111   2   6  13]
- [  0   5   5   0  61   2   4]
- [  5   0   2   4   2  42   4]
- [ 13   3   5   8   8  20  73]]
-Node Classification on random seed  44 -> 0.613
-Confusion Matrix:
- [[ 59   0   7   6   0  24   7]
- [  3 142   9   4   5   1  15]
- [ 25  38 134  33  10  17  39]
- [ 17   7  16  97   5   3  13]
- [  1  11   5   0  49   1   7]
- [  1   1   3   1   0  50   3]
- [  7   2  11   3   5  21  82]]
-Node Classification on random seed  45 -> 0.585
-Confusion Matrix:
- [[ 73   2   7   7   4  17   5]
- [  4 124   7   6   7   6   1]
- [ 23  23 109  24  49  19  54]
- [ 17   6  17  92   4   6   7]
- [  1   7   0   5  63   0   3]
- [ 12   1   2   1   0  36   8]
- [  8   3  11  10   4  17  88]]
-Node Classification on random seed  46 -> 0.587
-Confusion Matrix:
- [[ 67   1   5  16   1   9   5]
- [  7 102  18   0   4   4   5]
- [ 29   7 138  59  17  30  37]
- [  8   3  13 113   4   4  15]
- [  5   5   6   0  47   1   2]
- [  7   1   1   3   1  46   8]
- [ 19   1  18  12   4  18  74]]
-Node Classification on random seed  47 -> 0.621
-Confusion Matrix:
- [[ 76   3   4   6   3   6  13]
- [  4 145   3   6  10   0   1]
- [ 14  18 136  42  33  25  41]
- [ 11   2  10  99  12   8  25]
- [  4   5   1   1  60   0   0]
- [  6   1   2   3   1  41   3]
- [ 10   7  10   1   5  19  64]]
-Node Classification on random seed  48 -> 0.604
-Confusion Matrix:
- [[ 80   0   3   7   6  12   5]
- [  1 123  13   1  18   6   3]
- [ 20  14 143  28  23  25  62]
- [  8   1  17  95   7   9   8]
- [  1   4   3   0  65   5   2]
- [  5   0   0   5   0  38   4]
- [ 15   4   7  18   9  17  60]]
-Node Classification on random seed  49 -> 0.612
-Confusion Matrix:
- [[ 67   3   5  11   4   9  14]
- [  7 136  10   6   2   3   3]
- [ 23  31 127  32  42  10  44]
- [  7   2  10 101   0   2  18]
- [  2   5   1   0  70   1   1]
- [  5   1   2   6   3  34   7]
- [ 19   2   3  17   7   8  77]]
-Node Classification on random seed  50 -> 0.632
-Confusion Matrix:
- [[ 58   3   3   7   5  17   5]
- [  3 124   7   0   4   4   2]
- [ 23  27 154  25  13  28  46]
- [ 12   3  16 119   7   7  15]
- [  0   6   3   0  64   0   4]
- [  1   2   1   2   3  40   3]
- [  9   2  11  12   5  22  73]]
-Node Classification on random seed  51 -> 0.614
-Confusion Matrix:
- [[ 77   2   8   2   1   7  19]
- [  3 145   4   4   5   3   5]
- [ 18  25 109  24  52  27  38]
- [ 16   4   9  98  10   6  11]
- [  1   9   6   1  60   0   2]
- [  5   2   1   1   2  42   7]
- [  1   3   7  10   9  16  83]]
-Node Classification on random seed  52 -> 0.61
-Confusion Matrix:
- [[ 55   2  14   4   3   5  16]
- [  5 141   2   1   4   0   2]
- [ 18  33 131  44  23  23  49]
- [  7   5  22 100   6   3  16]
- [  3  11   3   3  57   2   2]
- [  5   1   2   1   0  49   4]
- [  8   3  10  11   4  10  77]]
-Node Classification on random seed  53 -> 0.634
-Confusion Matrix:
- [[ 73   1   4   2   3  16  10]
- [  2 127   7   6   7   2   3]
- [ 14  11 133  48  30  30  25]
- [ 14   2  19 109   9   4   4]
- [  1   9   7   2  56   1   1]
- [  5   0   0   1   0  53   6]
- [  5   5  15  11   6  18  83]]
-Node Classification on random seed  54 -> 0.623
-Confusion Matrix:
- [[ 80   0   2   0   4  13   7]
- [  7 160   5   1   4   7   2]
- [ 32  19 115  48  23  25  27]
- [ 13   5  22  80   4   9  12]
- [  4  11   1   4  63   1   1]
- [  9   0   2   2   0  43   5]
- [ 10   2   8   8   8  10  82]]
-Node Classification on random seed  55 -> 0.611
-Confusion Matrix:
- [[ 59   4   4   3   3   8  17]
- [  4 135   2   4   4   0   4]
- [ 18  24 127  40  34  27  37]
- [ 19   4   8 117   8   6  10]
- [  0   8  11   2  60   0   1]
- [  9   1   1   6   1  43   6]
- [ 23   5   7   2   3  11  70]]
-Node Classification on random seed  56 -> 0.623
-Confusion Matrix:
- [[ 61   1   3   8   2  12  17]
- [  4 134   4   6   4   9   3]
- [ 10  25 144  40  23  21  46]
- [  8   4  18 104   0   7  10]
- [  1   6   5   2  60   1   2]
- [  3   2   4   3   1  42   9]
- [ 10   2  13   9   1  18  78]]
-Node Classification on random seed  57 -> 0.599
-Confusion Matrix:
- [[ 61   1   6   6   2  14   4]
- [  4 137   2   1   9   5   2]
- [ 32  11 142  35  28  38  34]
- [  6   4  15  94   4   9  24]
- [  3   8   3   1  51   1   2]
- [  8   3   1   9   2  44   6]
- [ 13   5   6   4  10  20  70]]
-Node Classification on random seed  58 -> 0.586
-Confusion Matrix:
- [[ 69   6  13   1   4   5   5]
- [  3 120   2   0  18   0   5]
- [ 32  25 109  67  25   5  43]
- [ 12   8   4 101   3   2  20]
- [  5   5   3   0  61   0   2]
- [  7   2   1   0   5  45   4]
- [ 15   7  22  11   6  11  81]]
-Node Classification on random seed  59 -> 0.618
-Confusion Matrix:
- [[ 60   3   2   1   3  17   9]
- [  2 127   7   0   9   1   2]
- [ 24  41 161  19  41  21  33]
- [ 24   3  24  90   9   1   7]
- [  1   8   1   1  62   1   0]
- [  7   2   1   0   1  37  12]
- [  7   3   4   8  11  11  81]]
-Node Classification on random seed  60 -> 0.627
-Confusion Matrix:
- [[ 64   2   4   7   2   9   4]
- [  6 135   4   2   3   2   6]
- [ 19  14 153  44  30  34  32]
- [ 10   1  12 105   3   6  21]
- [  0   7   6   2  65   2   2]
- [  3   1   2   1   0  41   2]
- [  7   3  17   6  24  11  64]]
-Node Classification on random seed  61 -> 0.613
-Confusion Matrix:
- [[ 71   4   8   7   7  14   5]
- [  1 136   4   4   2   1   0]
- [ 25  20 135  32  21  24  51]
- [  8   3  26 111   2   6  15]
- [  1   5   3   5  55   0   4]
- [ 18   0   0   1   4  32   2]
- [ 17   5   4   7   6  15  73]]
-Node Classification on random seed  62 -> 0.627
-Confusion Matrix:
- [[ 67   4   1  11   4   7  13]
- [  8 130   3   2   9   3   4]
- [ 22  24 135  40  33  22  36]
- [  8   4  10 110   9  11   7]
- [  8   4   2   1  60   0   1]
- [  4   1   0   1   0  46   6]
- [ 17   2   3  10   5  13  79]]
-Node Classification on random seed  63 -> 0.587
-Confusion Matrix:
- [[ 64   4   0   1  10  12  11]
- [  1 115  10   4  12   3   7]
- [ 32  29 135  37  21  25  36]
- [  8  11  15 100  11   6   7]
- [  0   3   5   0  72   0   2]
- [  9   0   7   1   0  43   5]
- [ 12   5   9  12   5  25  58]]
-Node Classification on random seed  64 -> 0.626
-Confusion Matrix:
- [[ 65   4   4   2   3  17   7]
- [  2 129  17   1   0   5   6]
- [ 24  13 151  29  21  27  44]
- [ 17   4  14  90  11   6  16]
- [  1   7   2   0  63   1   0]
- [  4   0   1   0   0  48   5]
- [ 11   1  15   8   6  18  80]]
-Node Classification on random seed  65 -> 0.605
-Confusion Matrix:
- [[ 64   1   8   2   4   9   8]
- [  6 111   7   1  14   3   7]
- [ 26  26 124  46  25  27  37]
- [  7   3  22 113   7   5  10]
- [  0   4   2   1  70   1   6]
- [  6   1   3   0   4  40   4]
- [  8   5   3   8   8  20  83]]
-Node Classification on random seed  66 -> 0.607
-Confusion Matrix:
- [[ 60   3   1   9   4   8  12]
- [  7 115   3   2  20   6   2]
- [ 27  16 136  38  25  23  53]
- [  8   1  13 113   3  12  10]
- [  1   7   5   0  61   0   5]
- [ 11   1   3   2   3  50   3]
- [ 11   4   5   4   9  13  72]]
-Node Classification on random seed  67 -> 0.607
-Confusion Matrix:
- [[ 67   3   1   5   3  10   9]
- [  4 126   9   3   7   3   3]
- [ 31  20 154  36  28  19  42]
- [  8   2  18  96   2   7  25]
- [  2   6   2   2  64   1   1]
- [  3   1   0   3   0  35   8]
- [ 15   6   6  10  14  15  65]]
-Node Classification on random seed  68 -> 0.65
-Confusion Matrix:
- [[ 78   3   3   5   5   5   7]
- [ 11 119   3   3   7   0   1]
- [ 37  32 161  26  23  21  36]
- [ 13   6  10 117   4   4   8]
- [  1   1   4   5  56   2   5]
- [  6   3   1   0   3  43   4]
- [ 15   1  11   4   2   9  76]]
-Node Classification on random seed  69 -> 0.581
-Confusion Matrix:
- [[ 72   3   1   1   3  19  12]
- [  3 143   4   2   8   3   4]
- [ 35  26 101  31  26  35  40]
- [ 16   6   4 108   9   9  15]
- [  0   4   2   1  68   2   2]
- [  4   1   5   4   2  42   4]
- [ 15   1   7  21   3  26  47]]
-Node Classification on random seed  70 -> 0.593
-Confusion Matrix:
- [[ 76   0   8   4   3   8   7]
- [  5 126  13   3   5   3   7]
- [ 37  25 112  35  30  20  48]
- [  4   5  12  95  15  11   5]
- [  3   4   2   0  66   0   1]
- [  3   0   5   2   1  42   3]
- [ 10   2  26   7   9  16  76]]
-Node Classification on random seed  71 -> 0.635
-Confusion Matrix:
- [[ 63   1   3   6   8  10  19]
- [  8 120   6   2   7  11   1]
- [ 21   9 167  18  19  29  47]
- [  8   3  15 115   3   8  15]
- [  2   8   6   0  49   2   1]
- [  3   2   5   1   3  55   6]
- [  3   5  10   6   1  24  66]]
-Node Classification on random seed  72 -> 0.574
-Confusion Matrix:
- [[ 67   2   8   4   5  12   4]
- [  6 108   4   2  15   5   6]
- [ 22  24 119  51  42  26  22]
- [ 16   0  12 102   6  10  15]
- [  2   3   8   1  61   1   5]
- [  6   4   3   0   1  38  17]
- [ 12   4   9  14   4  13  79]]
-Node Classification on random seed  73 -> 0.634
-Confusion Matrix:
- [[ 75   4   5   5   2  13   7]
- [  3 144   3   7   8   4   3]
- [ 34   9 121  39  28  27  29]
- [  4   3   8 110   5   4  18]
- [  0  10   2   1  74   0   1]
- [  5   0   0   3   7  41   1]
- [ 14   3  18  15   4  10  69]]
-Node Classification on random seed  74 -> 0.591
-Confusion Matrix:
- [[ 78   0   7   7   3   5  20]
- [  7 116   2   1   3   0  12]
- [ 17  25 137  40  20  32  37]
- [ 12  12   7  98   4  14  19]
- [  0   9   9   0  50   1   2]
- [ 11   4   4   1   1  38   6]
- [ 15   4   7   2   7  20  74]]
-Node Classification on random seed  75 -> 0.589
-Confusion Matrix:
- [[ 62   1   8   7   3  13   7]
- [  6 108   3   2   8   7   7]
- [ 16  24 159  34  24  20  42]
- [  7   3  13 107   3   8  11]
- [  0   3   5   2  62   2   3]
- [  5   3   9   3   0  42   5]
- [ 11   4  12  11  29  27  49]]
-Node Classification on random seed  76 -> 0.604
-Confusion Matrix:
- [[ 70   2   2   4   5  11  10]
- [  5 126   3   1   3   2   3]
- [ 23  24 145  50  29  24  42]
- [  9   6  25  74   2  12  16]
- [  0  10   5   1  51   4   2]
- [  9   0   0   2   0  45   8]
- [ 10   3   5   6   7  11  93]]
-Node Classification on random seed  77 -> 0.614
-Confusion Matrix:
- [[ 61   4   6   4   1  10  13]
- [  1 128   7   2   5   5   5]
- [ 26  23 131  46  40  10  51]
- [  9   3  12 125   3   6  10]
- [  0   2   1   6  47   1   2]
- [  7   4   3   1   0  39   8]
- [ 15   7   5   5  10   7  83]]
-Node Classification on random seed  78 -> 0.605
-Confusion Matrix:
- [[ 66   3   0   5   4  12  13]
- [  3 136   4   1   6   1  10]
- [ 28  24 119  20  36  25  43]
- [ 12   0  19  83  12  15  22]
- [  2   6   4   1  63   3   5]
- [  5   1   3   1   0  54   2]
- [ 16   2   2   6  10   8  84]]
-Node Classification on random seed  79 -> 0.644
-Confusion Matrix:
- [[ 94   1   5   6   4   6   9]
- [  5 111  14   6   9   3   2]
- [ 20  14 156  37  25  16  44]
- [  3   3   9 104   4   4  14]
- [  3   4   3   4  70   1   2]
- [  5   1   5   3   3  40   2]
- [ 11  11   7  11   1  16  69]]
-Node Classification on random seed  80 -> 0.653
-Confusion Matrix:
- [[ 70   4   4   2   0  10  10]
- [  4 145   6   6   1   1   0]
- [ 26  29 146  28  29  37  27]
- [  7   3  13 107   9   8  16]
- [  0   8   3   2  51   1   1]
- [  3   0   5   2   0  45   5]
- [ 10   2   8   3   7   7  89]]
-Node Classification on random seed  81 -> 0.606
-Confusion Matrix:
- [[ 56   1  13   5   1  16  14]
- [  5 124   6   0   5   2   1]
- [ 16  23 145  28  11  38  43]
- [ 14   4  25 108   2  10   9]
- [  0   6   5   3  56   0   3]
- [  6   2   1  11   0  42   4]
- [ 17   4   7  12   4  17  75]]
-Node Classification on random seed  82 -> 0.603
-Confusion Matrix:
- [[ 74   3  12   5   5   6  13]
- [  2 135   3   3  12   4   1]
- [ 41  15 120  22  23  14  55]
- [ 12   9  24  86  11   5  12]
- [  2   5   6   0  65   1   1]
- [  7   0   5   0   0  48   1]
- [ 12   4  15  10   6  10  75]]
-Node Classification on random seed  83 -> 0.594
-Confusion Matrix:
- [[ 67   3   4   1   8  13  13]
- [  2 115   7   0   6   1   6]
- [ 23  29 123  24  36  21  52]
- [ 14  10  12 100  10   6  10]
- [  0   2   5   2  58   3   5]
- [  6   4   2   0   6  51   7]
- [  7   4  11   7   4  20  80]]
-Node Classification on random seed  84 -> 0.603
-Confusion Matrix:
- [[ 79   0   7   2   4  10   7]
- [  9 119   9   1   3   2   1]
- [ 23  32 137  48  29  11  38]
- [ 19   5   9  88   9  13  11]
- [  3  10   2   0  67   0   1]
- [  8   0   2   0   0  47   6]
- [ 19   5  14   4   6  15  66]]
-Node Classification on random seed  85 -> 0.607
-Confusion Matrix:
- [[ 76   2   5   2   4   5   8]
- [  5 149   4   2   2   5   2]
- [ 18  24 117  50  22  38  33]
- [ 14  10  15  85   9   7  10]
- [  3   9   6   2  56   2   3]
- [  9   0   2   3   0  32  11]
- [  6   5   8   5  11  12  92]]
-Node Classification on random seed  86 -> 0.606
-Confusion Matrix:
- [[ 67   2   5   6   4  10  14]
- [  4 124   9   4  11   3   1]
- [ 26  20 122  45  22  29  42]
- [  7   1  21 109   6   4  10]
- [  2   4   1   2  74   1   2]
- [ 13   3   4   4   0  35   7]
- [  6   4   4  17   6   8  75]]
-Node Classification on random seed  87 -> 0.597
-Confusion Matrix:
- [[ 66   3   2   8   3  11   8]
- [  4 121   5   2   4   4   5]
- [ 10  25 131  34  23  32  43]
- [ 16   1  20 102   8   6  16]
- [  0   2   6   2  68   1   0]
- [  6   2   0   3   1  46   6]
- [  8  11   4  26  11  21  63]]
-Node Classification on random seed  88 -> 0.622
-Confusion Matrix:
- [[ 69   0   6   7   6   9   6]
- [  5 116   9  13   5   3   4]
- [ 19  11 165  31  42  23  27]
- [ 11   1  15 102  17   7   5]
- [  1   4   4   0  53   0   4]
- [  2   1   1   0   1  51   1]
- [ 15   5   9  25   7  16  66]]
-Node Classification on random seed  89 -> 0.628
-Confusion Matrix:
- [[ 87   6   1  10   3   7   9]
- [  4 124   3   3   7   7   3]
- [ 30  15 145  29  26  14  47]
- [ 10   4  17 102   4   5  12]
- [  3   3   5   3  58   1   7]
- [  6   0   6   3   2  35   9]
- [  3   3   6  18  11   7  77]]
-Node Classification on random seed  90 -> 0.62
-Confusion Matrix:
- [[ 78   0   3   9   4   8  10]
- [  3 121   7   0   4   5  12]
- [ 20  20 132  43  29  25  34]
- [  2   8  22 109   1   5  10]
- [  2   9   7   4  54   0   1]
- [  3   1   2   2   0  48   9]
- [ 10   9  15   5   6  11  78]]
-Node Classification on random seed  91 -> 0.593
-Confusion Matrix:
- [[ 61   0   4   6   5  10  18]
- [  3 118  13   2  13   3   7]
- [ 19  18 137  50  27  17  40]
- [ 20   1   9  97   7   8  19]
- [  2   7   4   1  58   5   1]
- [  6   0   1   2   1  44   6]
- [ 13   2   8  11   6  12  78]]
-Node Classification on random seed  92 -> 0.634
-Confusion Matrix:
- [[ 61   3   6   5   2   3  28]
- [  5 145   3   2   3   1   4]
- [ 10  22 121  44  23  13  48]
- [ 13   6   8 106   6   2   7]
- [  2  11   4   0  65   2   0]
- [  6   0   3   5   1  47   6]
- [ 14   8  12  12   2  11  89]]
-Node Classification on random seed  93 -> 0.605
-Confusion Matrix:
- [[ 72   3   7   3   5   9   9]
- [  2 120  12   2   5   2   2]
- [ 13  28 139  34  32  12  33]
- [ 25   3  28  67   8   4  17]
- [  1   9   8   0  62   0   2]
- [  6   5   4   2   0  47   5]
- [ 21   4   8   2   7  13  98]]
-Node Classification on random seed  94 -> 0.597
-Confusion Matrix:
- [[ 73   1   1   5   7  17   8]
- [  9 139   3   2   6   4   6]
- [ 26  26 123  37  24  18  43]
- [  8   1  21  92   6  12  11]
- [  0   7   6   4  59   3   1]
- [  8   0   0   2   0  42   8]
- [ 14   5  16  11   5  11  69]]
-Node Classification on random seed  95 -> 0.589
-Confusion Matrix:
- [[ 60   0   3   7   1   3  21]
- [ 13 121  19   6   3   5   5]
- [ 17  18 140  53  19   9  58]
- [  9   4  17  95   8   2  21]
- [  4   7   6   1  65   1   0]
- [  7   2   1   4   2  38  11]
- [  6   3  10  11   7   7  70]]
-Node Classification on random seed  96 -> 0.628
-Confusion Matrix:
- [[ 60   6   6   7   2  15  14]
- [  4 132   8   4   2   2   5]
- [ 12  27 141  28  23  18  40]
- [  7   5  18 118   6   4  13]
- [  0   6   6   2  65   1   1]
- [  5   1   0   9   1  42   5]
- [ 10   1   6  18   9  15  70]]
-Node Classification on random seed  97 -> 0.619
-Confusion Matrix:
- [[ 76   2   8   7   9  13   2]
- [  1 122   5   4  13   7   0]
- [ 18  28 159  29  24  26  34]
- [  7   4  24  92   3   9  16]
- [  0  12   4   3  53   0   4]
- [  0   2   9   2   2  38   2]
- [  5   5   2   8  10  18  79]]
-Node Classification on random seed  98 -> 0.615
-Confusion Matrix:
- [[ 56   1  11   5   7  19   1]
- [  6 117   6   5   8   8   0]
- [ 21  12 157  48  24  28  20]
- [ 16   0  14 113   5   6   7]
- [  2  10   8   0  63   1   3]
- [  8   1   3   1   0  46   3]
- [ 13   2   8  11   9  24  63]]
-Node Classification on random seed  99 -> 0.641
-Confusion Matrix:
- [[ 77   0   5   8   0   6  16]
- [  8 131   7   6   3   1   5]
- [ 30  15 145  24  31  17  37]
- [  6   1   9 102   5   9  11]
- [  8   7   3   2  64   1   3]
- [  8   0   0   0   0  44  12]
- [  7   5   9   8   8  18  78]]
-Node Classification on random seed  100 -> 0.601
-Confusion Matrix:
- [[ 81   2   2   9   3  10   8]
- [  4 121  21   0   8   3  10]
- [ 23  33 152  25  26  16  56]
- [  8   9  19  85   4   2   1]
- [  1   7   8   0  50   2   3]
- [  4   3   2   1   5  38  10]
- [ 11   4   9   5   7  15  74]]
-Node Classification on random seed  101 -> 0.628
-Confusion Matrix:
- [[ 84   2   2   2   3  12   1]
- [  2 116   9   3   7   0   1]
- [ 26  15 146  49  36  14  30]
- [ 11   7  12 123   5   5   5]
- [  1   9   6   1  53   0   0]
- [ 11   2   2   2   0  44   1]
- [ 22   7   9  16  10  14  62]]
-Node Classification on random seed  102 -> 0.627
-Confusion Matrix:
- [[ 73   3   7   9   5   6  10]
- [  6 144   5   4   4   4   2]
- [ 27  13 122  29  20  24  41]
- [ 20   2  23  87   4  12  14]
- [  0   8   4   0  64   1   1]
- [  2   5   3   0   0  52   4]
- [ 19   4   8   2   7  11  85]]
-Node Classification on random seed  103 -> 0.615
-Confusion Matrix:
- [[ 62   5   5   6   7   8  18]
- [  5 122  11   5  10   4   4]
- [ 33  24 141  36  14  13  38]
- [ 12   3  28 102   5   3  10]
- [  1   7   1   0  62   4   1]
- [  6   1   1   2   0  41   4]
- [  5   6   7  16   5  11  85]]
-Node Classification on random seed  104 -> 0.621
-Confusion Matrix:
- [[ 66   3   2   8   7  12   8]
- [  8 128   5   2   9   3   5]
- [ 30  16 147  36  20  27  32]
- [  9   3   9  96   7  10  14]
- [  1  10   2   6  59   1   3]
- [  8   1   5   0   0  55   3]
- [  7   2   9   6  11  19  70]]
-Node Classification on random seed  105 -> 0.592
-Confusion Matrix:
- [[ 62   1   5   1   4  15  15]
- [  4 127   2   9   4   1   2]
- [ 21  12 123  41  24  28  52]
- [ 11   0  12 105   9   8  23]
- [  2  11   3   3  49   0   6]
- [ 13   0   6   0   0  45   6]
- [  8   4  11   0   7  24  81]]
-Node Classification on random seed  106 -> 0.609
-Confusion Matrix:
- [[ 78   7   4   2   4   8   8]
- [  6 115   6   2  22   6   3]
- [ 33  12 148  33  25  11  42]
- [ 13   3  25  82   5   6  25]
- [  2   4   3   1  61   0   4]
- [  9   1   5   0   0  36   5]
- [ 19   2   9   3   3  10  89]]
-Node Classification on random seed  107 -> 0.627
-Confusion Matrix:
- [[ 73   2   6   5   9   9   7]
- [  6 134   2   5  12   1   1]
- [ 27  14 142  39  16  19  50]
- [  6   4  21 101   3   1  20]
- [  2   5   4   1  55   0   1]
- [  7   0   1   3   0  46   4]
- [ 26   2   3  13   5  11  76]]
-Node Classification on random seed  108 -> 0.55
-Confusion Matrix:
- [[ 56   8   7   3   4  14   9]
- [  7 119   9   1  13   0   3]
- [ 34  31 109  34  30  27  43]
- [ 23   4  22  78  13   2  22]
- [  0   6   3   1  65   3   2]
- [  2   1   1   5   3  35   6]
- [  3   6  12   3   8  22  88]]
-Node Classification on random seed  109 -> 0.556
-Confusion Matrix:
- [[ 65   0   9  10   8   8   9]
- [  4 124   6   3   8   3   3]
- [ 39  32 110  54  17  28  36]
- [ 14   2  24 100   5  10   9]
- [  1   8   4   1  58   1   4]
- [  8   6   5   1   2  38   0]
- [ 10   5  21   6   5  15  61]]
-Node Classification on random seed  110 -> 0.67
-Confusion Matrix:
- [[ 64   3   8   8   2   9  13]
- [  3 135   4   1   8   1   5]
- [ 29  18 151  28  25  18  27]
- [ 12   1   7 117   3   5   8]
- [  4   4   5   6  67   2   0]
- [  4   0   0   2   0  52   0]
- [  9   1   7   9  11  20  84]]
-Node Classification on random seed  111 -> 0.638
-Confusion Matrix:
- [[ 81   6   7   4   3   6   4]
- [  5 147   4   1   9   3   3]
- [ 17  21 152  39  38  16  24]
- [ 11   7  11 103   5   7  13]
- [  0   6   2   1  58   2   1]
- [ 12   2   5   1   2  35   7]
- [ 10   3  12  11  10  11  62]]
-Node Classification on random seed  112 -> 0.624
-Confusion Matrix:
- [[ 66   7   0   4   2   5  20]
- [  4 130   5   3   3   2   7]
- [ 22  20 143  30  34  12  51]
- [ 12   8  10 102   3   2  14]
- [  0  10   7   1  61   0   7]
- [ 10   2   2   1   1  38  10]
- [  9   2   7  12   1  14  84]]
-Node Classification on random seed  113 -> 0.62
-Confusion Matrix:
- [[ 71   3   5   4   2   5  10]
- [  5 134   9   0   8   2   2]
- [ 20  23 142  28  25  31  40]
- [  8   2  28  96   8  11  12]
- [  1   8   7   0  61   1   3]
- [  3   1   0   0   1  34  11]
- [ 11   2   8   7   5  20  82]]
-Node Classification on random seed  114 -> 0.589
-Confusion Matrix:
- [[ 57   0  10   2   4   9  32]
- [  5 125  13   1  14   1   5]
- [ 13  23 111  32  48  23  44]
- [  5  11  11 122   5  11  12]
- [  4   1   0   1  59   3   3]
- [  4   0   6   1   0  42   6]
- [  9   4  13   8   6   8  73]]
-Node Classification on random seed  115 -> 0.605
-Confusion Matrix:
- [[ 82   7   1   4   7   7   8]
- [  5 127   4   4   9   1   1]
- [ 35  36 122  38  17  12  46]
- [ 23   4  10  97   2  14  12]
- [  2   6   2   0  60   1   3]
- [  8   0   2   1   1  37   5]
- [ 16   2  13   6   8  12  80]]
-Node Classification on random seed  116 -> 0.651
-Confusion Matrix:
- [[ 68   1   4   3   8  11  10]
- [  1 136   4   5   9   4   2]
- [ 29  24 163  16  35  14  24]
- [ 19   9  20  96   5   2   4]
- [  1   9   3   0  68   2   4]
- [  5   1   1   0   0  49   4]
- [ 14   3   6   6   7  20  71]]
-Node Classification on random seed  117 -> 0.613
-Confusion Matrix:
- [[ 53   3   5   9   4  16   9]
- [  1 137   5   5  10   3  10]
- [ 19  18 147  24  23  24  39]
- [  6   4  24 100   9   7  15]
- [  0   6   4   2  57   5   4]
- [  2   3   0   1   1  46   9]
- [  8   5  10   5   6  24  73]]
-Node Classification on random seed  118 -> 0.633
-Confusion Matrix:
- [[ 81   1   1   5   5   3   6]
- [  4 126   7   3   5   7   4]
- [ 21  20 137  24  33  33  39]
- [  5   3  10 115   8  13  13]
- [  2   3   4   2  69   5   3]
- [ 14   1   3   1   1  37   2]
- [ 24   1   6   1  11  10  68]]
-Node Classification on random seed  119 -> 0.661
-Confusion Matrix:
- [[ 84   3   1   4   4  13   6]
- [  6 134   1   5   1   2   3]
- [ 16  32 155  40  12  15  37]
- [ 13   6  19 109   6   7   9]
- [  3   4   3   1  56   0   1]
- [  3   1   1   2   0  45   8]
- [ 19   1  10  10   5   6  78]]
-Node Classification on random seed  120 -> 0.575
-Confusion Matrix:
- [[ 67   3   7   2   7  13  14]
- [  4 121   2   4  11   4   5]
- [ 28  25  97  34  36  38  66]
- [ 10   1  12 116   6   6  12]
- [  1   7   5   0  66   0   3]
- [  2   2   1   1   0  36   3]
- [  5   3   7  13   3  19  72]]
-Node Classification on random seed  121 -> 0.622
-Confusion Matrix:
- [[ 59   2   3  12   5  14   9]
- [  1 130   3   2   8   4   4]
- [ 30  33 132  19  33  23  36]
- [ 10   6  14 108  10   5   5]
- [  2   5   6   2  65   1   3]
- [  3   1   5   3   1  47   2]
- [ 10   5   9  10   8  11  81]]
-Node Classification on random seed  122 -> 0.636
-Confusion Matrix:
- [[ 65   2  11   2   3  15   5]
- [  6 126   6   1  18   1   1]
- [ 17  24 145  25  34  23  51]
- [  4   5  17 106   1   6  10]
- [  2   7   1   2  64   0   1]
- [  7   0   3   0   0  40   5]
- [  9   7  13   1   4  14  90]]
-Node Classification on random seed  123 -> 0.645
-Confusion Matrix:
- [[ 87   2   1   9   7  19   0]
- [  1 140   8   3  15   2   3]
- [ 18   7 138  29  26  20  56]
- [ 10   2  10 104   6   6  19]
- [  3   5   3   0  62   0   6]
- [  3   2   0   4   0  42   4]
- [  8   3   3   6   8  18  72]]
-Node Classification on random seed  124 -> 0.632
-Confusion Matrix:
- [[ 70   2  11   5   3  13   3]
- [  8 141   3   2   6   3   1]
- [ 25  23 126  46  27  17  38]
- [ 11   1  19  99   5   4  11]
- [  1   5   3   0  72   0   6]
- [  5   3   1   3   0  53   3]
- [ 14   7   9   2   3  16  71]]
-Node Classification on random seed  125 -> 0.621
-Confusion Matrix:
- [[ 65   4   8   7   0  12   9]
- [  4 132   5   1   7   5   3]
- [ 22  28 138  36  38  21  39]
- [ 11   2  18 105   6   8   9]
- [  0   8   4   2  59   3   3]
- [  8   1   0   1   0  44   6]
- [ 15   2   3   6   1  13  78]]
-Node Classification on random seed  126 -> 0.639
-Confusion Matrix:
- [[ 75   4   5  12   3   7  10]
- [  4 131   8   5   4   0   8]
- [ 19  28 152  34  19  14  41]
- [  7   2  11  97   3   4  20]
- [  0   6   3   0  71   3   4]
- [ 10   2   3   3   0  36   5]
- [ 17   4   8  11   3   7  77]]
-Node Classification on random seed  127 -> 0.611
-Confusion Matrix:
- [[ 75   1   4   1   5   9  19]
- [  2 119   4   1   4   1   7]
- [ 35  21 140  31  31  24  35]
- [ 16   1   9 114   7   3  17]
- [  1   5   2   1  58   1   2]
- [  7   2   2   5   0  37   7]
- [ 17   3  14  10   6  16  68]]
-Node Classification on random seed  128 -> 0.603
-Confusion Matrix:
- [[ 63  17   3   6   3   4  17]
- [  5 128   9   2   7   5   6]
- [ 27  24 133  36  14  14  43]
- [ 15   7   9 111   6   4  13]
- [  1   9  10   4  34   0   4]
- [  5   4   4   1   1  42   9]
- [ 13   8   7   5   5  11  92]]
-Node Classification on random seed  129 -> 0.66
-Confusion Matrix:
- [[ 75   3   3  13   4   8   8]
- [  5 134   7   4   2   1   1]
- [ 35  20 145  36  28  21  23]
- [  2   1  20 125   5   3   9]
- [  1   4   7   0  63   0   4]
- [ 11   0   1   1   0  44   3]
- [  7   2   6   9   5  17  74]]
-Node Classification on random seed  130 -> 0.652
-Confusion Matrix:
- [[ 76   0   4   7   5  10  17]
- [  5 128   8   0  19   0   6]
- [ 15  17 138  29  24  15  41]
- [  8   9  14 106   5  14   4]
- [  0   4   4   2  72   0   4]
- [  5   2   2   0   3  43   6]
- [  0   4   8   4   4  20  89]]
-Node Classification on random seed  131 -> 0.616
-Confusion Matrix:
- [[ 53   1   5  15   3  14   6]
- [  6 120   5   2   4   1   4]
- [ 14  18 135  44  19  23  57]
- [  3   5  21 109   8  10  13]
- [  1  11   3   0  57   0   4]
- [ 10   0   1   0   0  48   4]
- [ 15   4   6   7   4  13  94]]
-Node Classification on random seed  132 -> 0.576
-Confusion Matrix:
- [[ 63   5   3  10   2   8  13]
- [  3 122   3   0  20   3   7]
- [ 40  20 115  22  24  22  51]
- [ 12   5  17  95   5   5  13]
- [  2   6   3   0  72   0   1]
- [  1   1   5   5   9  46   7]
- [  6   3  12  13  14  23  63]]
-Node Classification on random seed  133 -> 0.629
-Confusion Matrix:
- [[ 74   0   2   3   1  10   6]
- [  4 110   6   1   4   7   9]
- [ 16  23 138  35  35  32  41]
- [ 11   5  27 107   2   4  10]
- [  1   8   4   3  63   0   2]
- [  5   3   0   2   0  55   0]
- [  7   3  14   4   5  16  82]]
-Node Classification on random seed  134 -> 0.66
-Confusion Matrix:
- [[ 86   2   4   6   4   7   5]
- [  1 153  10   4   6   1   6]
- [ 17  29 155  26  20  14  40]
- [  8   4  17  94  10   3  14]
- [  2  10   1   4  57   0   4]
- [  3   1   2   5   1  38   8]
- [  4   4  18   5   1   9  77]]
-Node Classification on random seed  135 -> 0.62
-Confusion Matrix:
- [[ 64   3  10   8   4  14   5]
- [  3 120   2   4   6   4   7]
- [ 37  27 135  22  31  26  31]
- [  9   3   8 122   3   7  13]
- [  3   5   6   1  50   0   3]
- [  5   3   2   6   0  51   5]
- [ 15   1   9  12   1  16  78]]
-Node Classification on random seed  136 -> 0.613
-Confusion Matrix:
- [[ 72   2   3   8   8  18   8]
- [  7 124   3   8  16   4   2]
- [ 18  37 126  42  18  28  29]
- [  9   1   6 112   6   7  12]
- [  1   4   0   1  65   3   2]
- [  5   1   0   6   3  37   5]
- [ 11   1   4   6   9  25  77]]
-Node Classification on random seed  137 -> 0.656
-Confusion Matrix:
- [[ 83   5   3   4   3  14   7]
- [  5 138   3   1   8   3   3]
- [ 27  19 160  36  24  16  33]
- [ 20   8   2 108   5   4  15]
- [  1   7   2   2  49   1   4]
- [  5   2   1   0   2  43   5]
- [ 12   3   8   6   5  10  75]]
-Node Classification on random seed  138 -> 0.626
-Confusion Matrix:
- [[ 63   3  15   6   6   8  15]
- [  3 118   5   1  11   3   9]
- [  9  15 165  27  20  23  40]
- [  8   3  11 106   4   6  24]
- [  1   2   7   3  68   0   2]
- [  7   0   1   2   0  45   6]
- [ 15   3  11  19   3  17  61]]
-Node Classification on random seed  139 -> 0.618
-Confusion Matrix:
- [[ 88   1   0   3   7   5  12]
- [  2 111   2   3   5   3   3]
- [ 17  32 133  39  23  30  32]
- [ 25   5  10  93   3  10  17]
- [  0   2   3   2  73   3   2]
- [ 11   0   2   1   2  55   5]
- [  6   4  17  11   6  16  65]]
-Node Classification on random seed  140 -> 0.584
-Confusion Matrix:
- [[ 63   5  13   2   4   6  21]
- [  2 121   9   3   5   1  11]
- [ 27  10 153  61  20  18  27]
- [ 32   9  11  85   8   5  13]
- [  0   3   4   3  49   2   6]
- [  2   1   0   6   1  41   7]
- [ 12   2  13   5  10  16  72]]
-Node Classification on random seed  141 -> 0.632
-Confusion Matrix:
- [[ 62   2   6   7   5  10  18]
- [  1 123   1   5   6   0   8]
- [ 21  25 131  32  56  17  31]
- [  9   2   7 121   2   5  18]
- [  1   5   1   0  67   2   0]
- [  3   1   1   0   1  58   6]
- [  9   7  12   9   5  11  70]]
-Node Classification on random seed  142 -> 0.626
-Confusion Matrix:
- [[ 75   4   4   9   3   9   5]
- [  2 140   6   2   8   2   7]
- [ 15  20 142  29  20  26  38]
- [ 14   6  17 111   4  10   8]
- [  1   9   4   2  53   3   2]
- [ 10   0   5   6   2  37   5]
- [ 16   4   4  12   7  14  68]]
-Node Classification on random seed  143 -> 0.663
-Confusion Matrix:
- [[ 74   4   6   8   4   3   2]
- [  6 131   4   4   5   0   5]
- [ 24  21 166  31  17  31  34]
- [  6   1  10 117  10   9  15]
- [  0   9   5   1  56   0   3]
- [  4   3   4   0   1  38   2]
- [ 17   3   7   2   6  10  81]]
-Node Classification on random seed  144 -> 0.64
-Confusion Matrix:
- [[ 80   2   1   3   6   9   9]
- [  5 119  13   2   4   4   2]
- [ 30  21 140  41  19  10  40]
- [  8   3  21 118   2   8   4]
- [  0  11   2   5  65   0   4]
- [  4   1   7   0   1  42   1]
- [ 10   4   5   6   6  26  76]]
-Node Classification on random seed  145 -> 0.623
-Confusion Matrix:
- [[ 56   1   4   8   4  18  22]
- [  4 123   3   2   8   7   3]
- [ 28  12 147  39  31  20  37]
- [ 12   3  11  98   5   3  12]
- [  0   9   0   2  67   1   1]
- [  8   0   1   4   1  48   8]
- [ 20   2   5   3   3  12  84]]
-Node Classification on random seed  146 -> 0.635
-Confusion Matrix:
- [[ 66   2   5   3   2  23   6]
- [  3 117   5   3  20   3  11]
- [ 22  10 171  25  37  23  36]
- [ 10   2  12  90   5   6   7]
- [  0   9   2   0  61   1   0]
- [  2   0   0   4   2  55   9]
- [ 15   7   8   2  12  11  75]]
-Node Classification on random seed  147 -> 0.577
-Confusion Matrix:
- [[ 75   2  14   3   2  11  12]
- [  3 124   6   2  25   0   5]
- [ 23   7 128  43  42  43  33]
- [ 22   1  12  97   6   9   6]
- [  1  10   7   1  47   2   5]
- [  3   0   2   0   0  52   2]
- [  9   3   7  10   9  20  54]]
-Node Classification on random seed  148 -> 0.622
-Confusion Matrix:
- [[ 59   2   6   8   4   6   7]
- [  6 127   6   5   4   5   2]
- [ 31  18 153  42  14  22  45]
- [ 20   4  11  97   5   5   8]
- [  0   5   4   6  60   3   2]
- [  6   1   2   2   4  37   6]
- [ 14   2   5   3  12  15  89]]
-Node Classification on random seed  149 -> 0.565
-Confusion Matrix:
- [[ 65   0   6  16   8  12  15]
- [  3 102  12   5  12   0   4]
- [ 13  16 140  48  29  26  36]
- [  7   5  22 111   2  10  17]
- [  2   6   5   1  45   1   7]
- [  3   3   5   3   4  34  10]
- [ 13   6  13   6  12  11  68]]
-Node Classification on random seed  150 -> 0.624
-Confusion Matrix:
- [[ 77   2   6   4   8  18   6]
- [  1 134   7   2   9   2   4]
- [ 28  19 128  35  32  17  32]
- [  8   1  26  81   6   8  18]
- [  1   4   2   6  67   0   3]
- [  4   1   2   4   1  59   1]
- [  8   1   6   5  11  17  78]]
-Node Classification on random seed  151 -> 0.634
-Confusion Matrix:
- [[ 73   1   3   6   3  13  10]
- [  4 145   8   1  10   0   7]
- [ 13  22 121  60  22   7  45]
- [ 16   1   7 115   3   3  12]
- [  2   8   2   3  63   2   2]
- [  5   0   5   1   2  37   6]
- [ 11   4   7   9  11   9  80]]
-Node Classification on random seed  152 -> 0.6
-Confusion Matrix:
- [[ 61   0   6   3   3  21  16]
- [  7 126   4   6  11   2   2]
- [ 24  19 134  29  33  23  35]
- [  2   6  26  99  14   9  15]
- [  0  10   0   0  66   0   1]
- [  5   0   2   0   1  45   7]
- [  2   5  18   9  12  12  69]]
-Node Classification on random seed  153 -> 0.605
-Confusion Matrix:
- [[ 64   6   7   1   2  10  12]
- [  9 118   7   1   5   2   4]
- [ 37  14 143  49  37  18  44]
- [ 13   4  14  99  10   6  11]
- [  1   1   3   1  61   0   6]
- [  1   5   3   2   0  42   7]
- [  9   4   6   3   6  14  78]]
-Node Classification on random seed  154 -> 0.618
-Confusion Matrix:
- [[ 59   6   7   2   3  10  28]
- [  8 133   3   2   3   4   4]
- [  9  29 136  42  22  22  32]
- [ 24   6   9  99   5   6  15]
- [  2   9   4   1  59   2   2]
- [  8   3   1   0   0  46  13]
- [  3  10   4   5   7   7  86]]
-Node Classification on random seed  155 -> 0.628
-Confusion Matrix:
- [[ 76   4   2   4   2   7   6]
- [  2 136   5   6   4   0   2]
- [ 25  21 157  34  27  21  30]
- [  6   7  17  74   7  16  22]
- [  4   6   7   3  59   0   4]
- [  4   2   3   0   0  50   5]
- [ 15   7  10   4   5  16  76]]
-Node Classification on random seed  156 -> 0.604
-Confusion Matrix:
- [[ 67   1  10   5   2   9   3]
- [  8 135   8   3   5   1   1]
- [ 20  29 123  56  28  31  26]
- [  8   4   9  89   7  11  13]
- [  3   7   7   1  70   0   5]
- [  0   0   1   2   3  52   3]
- [ 14  10   5   2   6  29  68]]
-Node Classification on random seed  157 -> 0.598
-Confusion Matrix:
- [[ 70   2   3   4   2   8  14]
- [  9 126   5   0   3   2   2]
- [ 33  33 126  47  22  29  30]
- [ 18   7  20 101   7   7   9]
- [  2  13   2   1  61   1   4]
- [  7   2   1   1   1  42   2]
- [ 14   2   7   6   5  15  72]]
-Node Classification on random seed  158 -> 0.686
-Confusion Matrix:
- [[ 82   4   4   3   4   6  10]
- [  2 138   6   0   6   3   6]
- [ 23  12 180  28  17   8  33]
- [ 11   1  14 123   4   7   7]
- [  0   6   6   3  49   1   2]
- [  6   0   2   2   2  40   7]
- [ 17   3   5   9  11  13  74]]
-Node Classification on random seed  159 -> 0.639
-Confusion Matrix:
- [[ 74   4   4   5   0  15  15]
- [  2 141  12   0   6   4   4]
- [ 23  21 147  27  17  19  44]
- [ 13   4  15  99   2   2   9]
- [  4   8   2   0  57   2   2]
- [  8   2   5   0   0  39   4]
- [ 20   2   2   9  12  12  82]]
-Node Classification on random seed  160 -> 0.634
-Confusion Matrix:
- [[ 71   1   2   5   7   9   3]
- [  6 127   4   6   3   0   3]
- [ 25  20 170  27  18  19  44]
- [ 15   5  12  97  12  12   4]
- [  2   9   7   2  51   2   2]
- [  7   0   2   5   2  42   7]
- [ 20   3  14   9   3   8  76]]
-Node Classification on random seed  161 -> 0.62
-Confusion Matrix:
- [[ 67   3   5   4   3   7  18]
- [  3 133   6   0   8   3  11]
- [ 25  24 129  33  41  28  22]
- [ 14   6  11 117   6   3  13]
- [  1   4   0   3  59   1   2]
- [  6   1   3   2   0  44   7]
- [ 21   5  11   7   4   5  71]]
-Node Classification on random seed  162 -> 0.597
-Confusion Matrix:
- [[ 62   6   1   7   5  20  11]
- [  1 126   4   1   6   6  10]
- [ 28  20 136  35  31  29  32]
- [ 14   6  10  99   3   8  10]
- [  1   4   2   1  64   0   6]
- [  8   1   4   3   3  48   2]
- [  8   2  19   8   7  20  62]]
-Node Classification on random seed  163 -> 0.579
-Confusion Matrix:
- [[ 63   7   7   2   1  19  18]
- [  4 127   5   1   7   0   4]
- [ 26  31 110  51  39  26  44]
- [ 14   5  11 105   4   5   4]
- [  0   3   4   2  64   0   2]
- [  7   2   1   0   0  48   4]
- [ 17   6   7   9   8  14  62]]
-Node Classification on random seed  164 -> 0.547
-Confusion Matrix:
- [[ 60   0   3  16   4  15   7]
- [  9 119   7   2  13   1  10]
- [ 34  17 120  41  37  38  38]
- [  7   1  17  82   5   7  11]
- [  3  10   2   3  63   2   0]
- [  4   3   1   9   2  44   7]
- [  9   5  13   5  15  20  59]]
-Node Classification on random seed  165 -> 0.623
-Confusion Matrix:
- [[ 86   7   2   1   8   9   4]
- [  4 125   7   6  13   4   4]
- [ 23  21 161  43  23  29  20]
- [ 21   1  15  95   2   7  16]
- [  0   9   1   3  53   1   1]
- [  4   0   5   3   0  31   7]
- [ 14   1  13   2   4  19  72]]
-Node Classification on random seed  166 -> 0.622
-Confusion Matrix:
- [[ 88   1   6   4   3   3  12]
- [  0 140   7   1   5   2   4]
- [ 32  26 125  31  23  24  46]
- [ 10   4  15 100   8   3  21]
- [  0  12   6   0  50   0   1]
- [  6   3   5   0   1  47   4]
- [ 12   5   5  10   5  12  72]]
-Node Classification on random seed  167 -> 0.593
-Confusion Matrix:
- [[ 68   1   1   5   6  22   4]
- [  7 119   5   5  14   2   1]
- [ 23  25 131  43  40  20  39]
- [  9   3  19  99   9   4  14]
- [  1   4   2   3  63   0   2]
- [  2   1   7   3   5  41   3]
- [ 17   2   4   8   5  17  72]]
-Node Classification on random seed  168 -> 0.645
-Confusion Matrix:
- [[ 68   3   4   9   3   8  19]
- [  2 125   3   2   9   1   3]
- [ 12  21 156  46  19  17  41]
- [  6   3  17 100   4   9  13]
- [  3   6   3   3  59   0   8]
- [  1   3   4   1   0  46   5]
- [  6   4  10   9   3  12  91]]
-Node Classification on random seed  169 -> 0.614
-Confusion Matrix:
- [[ 68   2   4   5   2  12   5]
- [  8 130   9   6   2   0   3]
- [ 27  31 134  42  28  19  36]
- [  8   5  11 114   1   6  23]
- [  1   7   3   0  59   0   2]
- [  7   1   5   0   2  33  14]
- [ 11   3   6  10   4  15  76]]
-Node Classification on random seed  170 -> 0.63
-Confusion Matrix:
- [[ 71   1   5   5   4  19   8]
- [  8 138   7   2   5   3   0]
- [ 33  13 141  32  33  41  19]
- [  5   2  24 104   5   6  14]
- [  2   5   5   2  52   1   0]
- [  5   1   2   2   0  48   3]
- [  7   5   9  12   5  10  76]]
-Node Classification on random seed  171 -> 0.654
-Confusion Matrix:
- [[ 73   5   5   4   2  14   8]
- [  9 139   2   2   5   1   2]
- [ 24  30 141  38  11  24  41]
- [ 10   1  12 106   2   8  12]
- [  2  10   3   1  50   0   4]
- [  8   1   0   0   0  49   3]
- [  7   3   6   8   5  13  96]]
-Node Classification on random seed  172 -> 0.637
-Confusion Matrix:
- [[ 70   3   0   0   2  17  13]
- [  2 133   6   2   8   6   6]
- [ 24  23 135  25  28  30  38]
- [ 10  11   7 107   4   5  10]
- [  0   5   1   0  65   3   3]
- [  5   1   1   5   4  38  10]
- [  7   3   6   4   5  20  89]]
-Node Classification on random seed  173 -> 0.642
-Confusion Matrix:
- [[ 59   4   2   4   6  11   2]
- [ 11 139   3   6   1   2   5]
- [ 23  25 153  53  17  14  29]
- [ 11   7  18  99   3   7  11]
- [  0   3   7   1  64   0   1]
- [  3   2   1   1   1  49   3]
- [ 10   8   5   6   5  26  79]]
-Node Classification on random seed  174 -> 0.595
-Confusion Matrix:
- [[ 80   0   0   6   0  19   9]
- [  4 127   3  15   2  11   3]
- [ 21  32 128  45  15  34  38]
- [  7   3   6 105   7  12  12]
- [  1   3   4   2  48   1   6]
- [  5   2   2   2   5  33  16]
- [  6   1   7  11   6  21  74]]
-Node Classification on random seed  175 -> 0.598
-Confusion Matrix:
- [[ 73   1   2   9   2  14  15]
- [  3 132   5   3   4   4   4]
- [ 16  28 129  63  15  36  53]
- [  8   2  15  94   2   9  20]
- [  0   6   5   4  44   0   2]
- [  6   0   2   2   1  46   4]
- [  7   1   7   5   3  14  80]]
-Node Classification on random seed  176 -> 0.608
-Confusion Matrix:
- [[ 71   5   3   7   0  12  12]
- [  5 130   0   2   0   0   5]
- [ 21  20 165  42  19  20  28]
- [  4   2  22  96  16  11  10]
- [  0   7  10   2  52   1   4]
- [ 14   4   2   0   1  37   2]
- [ 13   8   8  20   3  27  57]]
-Node Classification on random seed  177 -> 0.615
-Confusion Matrix:
- [[ 56   2   9   3   5  18   8]
- [  6 123   3   4   4   2   3]
- [ 36  30 112  56  16  13  40]
- [ 11   8  12 125   3   6  10]
- [  0  10   3   3  62   0   2]
- [  4   1   1   1   2  53   4]
- [ 10   3   8   2   9  14  84]]
-Node Classification on random seed  178 -> 0.616
-Confusion Matrix:
- [[ 74   4   1   4   4  16   7]
- [  3 111  15   2   6   5   5]
- [ 23  19 142  31  18  24  58]
- [ 14  10  13  99   2   8  17]
- [  0   7   7   0  62   0   3]
- [  4   0   4   0   0  37   5]
- [ 10   4  14   2   4  11  91]]
-Node Classification on random seed  179 -> 0.637
-Confusion Matrix:
- [[ 67   3   2   1  12  18   3]
- [  4 118   6   0  12   2   6]
- [ 18  20 160  27  24  35  24]
- [ 12   6  21 102   3   6  16]
- [  0   5   3   0  73   0   2]
- [  2   0   2   3   0  50   2]
- [  7   2  15  10   8  21  67]]
-Node Classification on random seed  180 -> 0.584
-Confusion Matrix:
- [[ 76   1   1   5   0  10   4]
- [  1 121  10   5   7   1   4]
- [ 23  24 130  28  43  25  45]
- [  8   0  27  96   7  10  16]
- [  2   7   4   3  54   2   1]
- [  3   0   5   0   0  52   6]
- [ 11   6  20  13  10  18  55]]
-Node Classification on random seed  181 -> 0.633
-Confusion Matrix:
- [[ 59   2   5   5   3   7   8]
- [  2 130   7   7  20   2   3]
- [ 24   6 168  29  31  30  32]
- [ 13   2   9 103   3   9  18]
- [  1   0   8   1  52   0   8]
- [  6   1   5   0   0  53   5]
- [ 11   0  16  12   4  12  68]]
-Node Classification on random seed  182 -> 0.596
-Confusion Matrix:
- [[ 56   3   4   2   5   7  10]
- [  0 130   7   5   9  10   8]
- [ 17  24 132  42  23  38  40]
- [ 24   3  13  99   1   1  25]
- [  0   7   6   0  59   0   1]
- [  4   2   2   3   0  39   5]
- [ 13   3  13   7   3  14  81]]
-Node Classification on random seed  183 -> 0.652
-Confusion Matrix:
- [[ 79   0   6   3   1  13   5]
- [  3 123   3   5  11   1   8]
- [ 17  21 161  33  17  14  43]
- [  7   3  15 102   5   4  16]
- [  3   5   8   2  73   2   1]
- [ 12   1   2   2   1  33   8]
- [  6   1  10   4   8  18  81]]
-Node Classification on random seed  184 -> 0.644
-Confusion Matrix:
- [[ 74   1   8  11   5   9   8]
- [  4 126   3   2   8   6   2]
- [ 38  14 162  27  21  17  27]
- [ 19   0  24 104   3   3   7]
- [  1   8   6   0  57   0   3]
- [  5   1   2   3   0  54   5]
- [  9   0   7  21  10   8  67]]
-Node Classification on random seed  185 -> 0.641
-Confusion Matrix:
- [[ 87   2   5   4   1   8  10]
- [  9 143  11   4   1   0   1]
- [ 15  12 151  48  12  13  35]
- [ 20   4  11  81   8   7  17]
- [  0  10   4   2  51   1   4]
- [  3   4   2   0   0  57   4]
- [ 20   1  21   9   1  15  71]]
-Node Classification on random seed  186 -> 0.626
-Confusion Matrix:
- [[ 60   2   6  11   3  11  15]
- [  4 144   4   2   7   2   4]
- [ 22  19 148  36  19  20  50]
- [  6   6  15 113   6   4  10]
- [  0   7   1   4  49   2   1]
- [  5   0   4   2   0  40   5]
- [  4   8   8   7   8  24  72]]
-Node Classification on random seed  187 -> 0.618
-Confusion Matrix:
- [[ 62   2   6   3   5  11  11]
- [  4 123   4   0  13   4   2]
- [ 22  42 160  30  29  13  33]
- [ 10   3  15 107   6   5  14]
- [  2   8   6   1  58   0   0]
- [  3   1   1   1   1  49   7]
- [ 14   2  11   6  11  20  59]]
-Node Classification on random seed  188 -> 0.614
-Confusion Matrix:
- [[ 80   1   2  10   6  11   4]
- [  6 120  14   1   5   3   7]
- [ 23  11 155  29  32  25  34]
- [ 17   1  16  84   7  14  18]
- [  1   8   3   4  60   2   2]
- [  4   2   0   1   3  54   6]
- [ 16   4  13   1   7  12  61]]
-Node Classification on random seed  189 -> 0.608
-Confusion Matrix:
- [[ 62   4  12   3   4  12   2]
- [  7 139   4   1   4   1   3]
- [ 30  27 127  40  27  21  27]
- [ 17   4  15 101   3   7   9]
- [  3  10   3   4  66   0   1]
- [  6   0   5   5   2  40   1]
- [ 19   4  15   7   6  17  73]]
-Node Classification on random seed  190 -> 0.605
-Confusion Matrix:
- [[ 60   3   4  13   2  10  11]
- [  7 115   7  10   9   8   6]
- [ 25  16 151  43  16  26  35]
- [  7   1  20 103   2   4  14]
- [  3  12   7   4  45   1   5]
- [ 10   2   4   0   0  54   4]
- [ 12   4   7   5   3  13  77]]
-Node Classification on random seed  191 -> 0.608
-Confusion Matrix:
- [[ 73   3   6   5   1  15   6]
- [  8 132   5   8   8   3   2]
- [ 28  23 138  38  17  21  34]
- [ 26   6   6 108   5   4   5]
- [  3   5  12   3  44   1   2]
- [ 11   0   0   0   0  39   9]
- [ 14   5   7  11   4  22  74]]
-Node Classification on random seed  192 -> 0.608
-Confusion Matrix:
- [[ 70   1   5   2   4  20   8]
- [  4 128   3   0  14   4   5]
- [ 27  14 139  30  36  17  44]
- [ 12   6  12  97   6   7   8]
- [  0   6   4   0  61   0   7]
- [  1   2   8   2   3  37   4]
- [ 11   1   7  17   8  22  76]]
-Node Classification on random seed  193 -> 0.663
-Confusion Matrix:
- [[ 76   1   1   2   4  10  16]
- [  7 127   8   1   2   5   2]
- [ 10  27 165  38  16  18  51]
- [ 11   3   8  99   6   7  13]
- [  2   6   5   2  57   0   4]
- [  3   3   1   0   1  50   2]
- [  4   4   9   3   6  15  89]]
-Node Classification on random seed  194 -> 0.6
-Confusion Matrix:
- [[ 62   2   5   5   1  18   7]
- [ 10 132   6   1   8   1   2]
- [ 27  12 162  28  31  32  35]
- [ 15   3  11  86   4  10  18]
- [  3   5   4   5  54   1   2]
- [  1   1  10   5   3  45   4]
- [ 10   0  12   6  11  25  59]]
-Node Classification on random seed  195 -> 0.593
-Confusion Matrix:
- [[ 58   2   4   9   8  17   6]
- [  7 114   7   1  13   5   3]
- [ 17  19 136  37  30  24  50]
- [ 10   5  14 113   5  11   9]
- [  2   5   3   2  64   0   3]
- [  1   2   4   1   0  47   5]
- [  5   4  11  15   9  22  61]]
-Node Classification on random seed  196 -> 0.647
-Confusion Matrix:
- [[ 64   3   1  12   9   5  10]
- [  4 116   4   2   8   5   1]
- [ 18  22 187  16  19  22  57]
- [  7   3  14  94   9   4   9]
- [  2   7   5   0  65   1   1]
- [ 12   1   3   2   0  39   7]
- [ 17   5   9   2   4  11  82]]
-Node Classification on random seed  197 -> 0.589
-Confusion Matrix:
- [[ 59   3   4   9   6  13  14]
- [  4 132   5   2  15   7   3]
- [ 36  17 123  27  35  21  38]
- [  8  10   9 105   4  11  15]
- [  3   7   5   2  58   0   1]
- [  6   2   2   7   1  43   1]
- [ 22   3   8   2  17   6  69]]
-Node Classification on random seed  198 -> 0.611
-Confusion Matrix:
- [[ 59   3   1   4   7   7  26]
- [  4 140   5   2  10   6   7]
- [ 37  33 132  18  20  25  41]
- [ 10   3  15  96   9   2   9]
- [  0   9   5   0  53   2   4]
- [ 10   0   0   0   1  44   7]
- [ 12   4  10   5   6  10  87]]
-Node Classification on random seed  199 -> 0.647
-Confusion Matrix:
- [[ 68   1   7   8   4  10   2]
- [  8 130  11   3   3   5   3]
- [ 17  22 181  27  23  12  24]
- [ 16   4  23  94   4   3  11]
- [  0   5   6   0  58   2   2]
- [  6   1   1   2   3  39   3]
- [ 12   5  14   8   4  28  77]]
-Node Classification on random seed  200 -> 0.617
-Confusion Matrix:
- [[ 69   2   1   4   6  16  12]
- [  1 136   5   3   4   1   0]
- [ 17  24 158  26  25  22  35]
- [ 12   1  25  78   2  10  12]
- [  1   7   6   3  72   0   2]
- [  4   1   5   1   3  41  10]
- [ 15   3  11  18   9  18  63]]
-Node Classification on random seed  201 -> 0.589
-Confusion Matrix:
- [[ 54   5   9   3   6  17  15]
- [  0 133  12   3   6   7   5]
- [ 24  16 120  55  37  30  26]
- [ 17   7  18 108   2   2  11]
- [  2   7   3   3  55   0   2]
- [  3   0   3   4   1  38   7]
- [  8   0  10   4   9  12  81]]
-Node Classification on random seed  202 -> 0.597
-Confusion Matrix:
- [[ 66   4   9  11   3   9   6]
- [  7 127   1   4   9   1   2]
- [ 25  31 107  42  35  11  52]
- [  8  10   5 120   6   5   9]
- [  0   7   4   0  62   0   3]
- [  4   2   4   2   4  38   4]
- [ 10   9  10   9   7  19  77]]
-Node Classification on random seed  203 -> 0.63
-Confusion Matrix:
- [[ 80   4   1   2   2   6  13]
- [  1 107   1   7  12   2   7]
- [ 25  16 148  20  34  12  59]
- [ 10   2   7 116   9   4  19]
- [  0   2   4   0  66   1   3]
- [  8   3   1   0   4  43   3]
- [ 15   7   8   4  20  12  70]]
-Node Classification on random seed  204 -> 0.618
-Confusion Matrix:
- [[ 69   0   1   8   4   5  13]
- [  2 128   3   5  18   4   3]
- [ 17  26 138  35  24  26  44]
- [  6   2  18 108  13   7   7]
- [  1   5   1   0  56   0   2]
- [  2   2   1   7   0  39  14]
- [  9   8  10   6   6  17  80]]
-Node Classification on random seed  205 -> 0.57
-Confusion Matrix:
- [[ 69   1   1   4   7  20   7]
- [  7 132   4   5   1   5   5]
- [ 28  23 123  44  24  38  46]
- [ 11   2  24  91   7   8   8]
- [  2  10   7   0  55   2   1]
- [  9   0   4   0   0  36   8]
- [  7   5   9   6  10  20  64]]
-Node Classification on random seed  206 -> 0.579
-Confusion Matrix:
- [[ 84   2   6   7   2   8  12]
- [  5 128   7   2   8   4   3]
- [ 37  26 104  17  63  12  59]
- [  3   6  19  86   7   8  11]
- [  0  10   3   3  59   1   0]
- [  4   2   0   2   2  46   4]
- [ 19   3   6  11   4  13  72]]
-Node Classification on random seed  207 -> 0.617
-Confusion Matrix:
- [[ 73   6  15   2   3   9   7]
- [  6 140   2   1  10   8   4]
- [ 30  26 136  26  20  31  30]
- [ 24   7   9  88   2   3  16]
- [  0   5   9   0  59   0   2]
- [  8   1   2   3   1  48   7]
- [ 17   3  10   3   5  10  73]]
-Node Classification on random seed  208 -> 0.634
-Confusion Matrix:
- [[ 67   3   3   7   3   4  11]
- [  5 141   4   5   5   3   1]
- [ 16  33 161  58  22  28  32]
- [  7   5  10 101   5  11   5]
- [  2   6   1   1  66   2   2]
- [  9   3   1   1   0  29   6]
- [  7   3   5  15   6  10  69]]
-Node Classification on random seed  209 -> 0.629
-Confusion Matrix:
- [[ 71   2   6   9   5  19   7]
- [  3 127   3   3   2   4   6]
- [ 24  19 156  32  19  16  45]
- [ 15  11  10  86   3   3   9]
- [  1   7   6   3  65   2   2]
- [  2   1   1   2   4  47  11]
- [ 12   4   6  13   5  14  77]]
-Node Classification on random seed  210 -> 0.622
-Confusion Matrix:
- [[ 72   2   6   3   4   9   4]
- [  3 127   6   6  11   1   4]
- [ 22  32 147  49  12  24  24]
- [  7  11  17 103   0   8  20]
- [  0   3   2   2  66   1   5]
- [  9   2   4   2   0  40   1]
- [  5   2   7   8  20  20  67]]
-Node Classification on random seed  211 -> 0.639
-Confusion Matrix:
- [[ 69   1   1  12   5  10  16]
- [  1 133   6   4   5   4   1]
- [ 23  15 143  20  36  19  53]
- [ 12   3  18  98   3   5  12]
- [  0   2   2   1  61   3   1]
- [ 10   2   3   2   0  49   1]
- [ 11   2  10  13   4   9  86]]
-Node Classification on random seed  212 -> 0.589
-Confusion Matrix:
- [[ 75   1   3   8   4  14  13]
- [  4 129   4   5  16   1   3]
- [ 31  30 134  33  26  15  58]
- [ 12   2  14  94   2   2  12]
- [  4   7   1   1  54   3   5]
- [  6   1   1   4   2  46   4]
- [ 12   0   2  13  21  11  57]]
-Node Classification on random seed  213 -> 0.607
-Confusion Matrix:
- [[ 82   1   2   4   4   6  11]
- [  6 109  10   3   7   6   4]
- [ 20  16 123  35  29  46  27]
- [  6   4  26 111   4   9  16]
- [  1   7   4   3  59   2   2]
- [  5   2   2   3   0  48   7]
- [ 14   3   6   7   9  14  75]]
-Node Classification on random seed  214 -> 0.617
-Confusion Matrix:
- [[ 79   6   0   7   3   6  14]
- [  4 132   3   5   2   4   8]
- [ 23  25 145  40  20  16  31]
- [ 20  11  14  85   7   3  18]
- [  0  11   2   5  70   6   1]
- [  5   0   1   2   1  36   8]
- [ 10   2   4  10  18   7  70]]
-Node Classification on random seed  215 -> 0.627
-Confusion Matrix:
- [[ 71   5   4   2   3  14   8]
- [  6 132   3   3   6   0   1]
- [ 24  44 125  23  20  21  39]
- [ 12   3  11 128   3   7   6]
- [  2  11   4   1  64   1   3]
- [  8   4   3   1   1  38   6]
- [ 19   6   5   3  10  17  69]]
-Node Classification on random seed  216 -> 0.624
-Confusion Matrix:
- [[ 75   3   7   6   8   7   8]
- [  1 131  11   5  15   1   1]
- [ 22  14 138  29  24  36  45]
- [ 17   2  10 101   9   9   6]
- [  1   7   8   0  46   0   2]
- [  2   4   2   0   0  55   2]
- [ 10   7   7   3   7  18  78]]
-Node Classification on random seed  217 -> 0.657
-Confusion Matrix:
- [[ 74   2   2   0   1  13   5]
- [  7 121   8   5  10   1   5]
- [ 20  23 149  34  32  13  44]
- [ 10   2  16 105   5   5  13]
- [  3   3   1   0  67   0   3]
- [  7   0   1   0   2  55   5]
- [ 11   2   3   9   4  13  86]]
-Node Classification on random seed  218 -> 0.618
-Confusion Matrix:
- [[ 72   8   2   2   3   7  20]
- [  4 131  13   1   3   1   5]
- [ 24  20 148  23  21  27  37]
- [ 20   2  11  89  15   4  13]
- [  0   6   4   3  52   0   3]
- [  8   1   2   1   0  39  11]
- [ 26   4   8   3   7   9  87]]
-Node Classification on random seed  219 -> 0.627
-Confusion Matrix:
- [[ 63   2   7   5   8   6   5]
- [ 12 122   4   1  11   2   3]
- [ 16  30 125  42  25  21  35]
- [ 13   4  14 144   4   8   8]
- [  2   1   7   0  69   1   1]
- [  4   0   1   5   3  47   6]
- [ 21   4   7   4   8  12  57]]
-Node Classification on random seed  220 -> 0.626
-Confusion Matrix:
- [[ 68   3   0   3   2  10   8]
- [  3 130   6   7   4   1   9]
- [ 17  16 142  39  33  11  46]
- [ 13   7  15 110   4   3  22]
- [  3   8   1   2  53   0   4]
- [  3   4   3   3   0  46   8]
- [ 16   2   5   7  10  13  77]]
-Node Classification on random seed  221 -> 0.568
-Confusion Matrix:
- [[ 63   2  10   7   7  11  19]
- [  5 114   9   4  16   9   4]
- [ 24  27 140  38  31  18  45]
- [ 15   8  14  95   4   3  11]
- [  0   5   3   1  56   0   3]
- [  5   3   4   1   0  42   5]
- [  9   3  10   6  24   9  58]]
-Node Classification on random seed  222 -> 0.597
-Confusion Matrix:
- [[ 61   7   9   2   6  14  12]
- [  2 134  10   2   4   3   3]
- [ 20  26 144  43  27  30  23]
- [ 19   2  25  87   9   4  10]
- [  1   7   4   2  59   0   2]
- [  3   1   2   2   4  47   8]
- [  8   6   9   7   4  21  65]]
-Node Classification on random seed  223 -> 0.617
-Confusion Matrix:
- [[ 69   1   2   3   4  13  11]
- [  2 121   5   0   7   5  10]
- [ 26  14 143  39  20  36  47]
- [ 13   4  11  95   6  10  21]
- [  0   7   1   0  59   1   2]
- [  1   1   2   1   0  45   6]
- [  3   4   9   8   9  18  85]]
-Node Classification on random seed  224 -> 0.631
-Confusion Matrix:
- [[ 59   0   1   3   6  22  13]
- [  3 127   3   1  14   4   3]
- [ 11  15 138  38  25  18  46]
- [  8   2  18 102   7   6  24]
- [  0   7   6   2  63   1   2]
- [  3   1   2   0   1  60   5]
- [ 10   5   6   6   7  14  82]]
-Node Classification on random seed  225 -> 0.618
-Confusion Matrix:
- [[ 65   3   6   8   6  13   3]
- [  3 122   4   2  16   5   3]
- [ 34  16 156  22  15  23  41]
- [ 18  11  24 110   4   6   8]
- [  1   8   3   0  55   0   2]
- [  4   2   2   2   1  52   2]
- [ 10   2   5  17   3  24  58]]
-Node Classification on random seed  226 -> 0.617
-Confusion Matrix:
- [[ 81   3   2   6   2   4  10]
- [  4 126   5   3   9   2   7]
- [ 24  12 147  29  36  24  34]
- [ 10  10  13  99   3  14   9]
- [  0   8   4   3  58   4   1]
- [ 10   0   0   2   0  41   6]
- [ 18   2  10   8   8  24  65]]
-Node Classification on random seed  227 -> 0.599
-Confusion Matrix:
- [[ 67   1   8   0   6   4  20]
- [  4 130   3   3   9   0   3]
- [ 17  24 120  56  35   9  33]
- [  6   3  25  94   4   7  18]
- [  1   3   3   3  64   0   2]
- [  8   3   1   5   5  41  10]
- [  2   8  19   6   9  15  83]]
-Node Classification on random seed  228 -> 0.616
-Confusion Matrix:
- [[ 79   1   3   5   3   8   7]
- [  4 130  10   0  10   6   4]
- [ 19  26 125  33  20  25  39]
- [  9   7  14 107   3  12  11]
- [  0   4   3   1  59   2   3]
- [ 11   2   1   7   2  41   8]
- [ 13   2   7  11   7  21  75]]
-Node Classification on random seed  229 -> 0.623
-Confusion Matrix:
- [[ 69   3  18   4   1   7   9]
- [  9 146   7   2   8   2   3]
- [ 26  35 118  40  17  28  26]
- [  9   6   9 114   4   4   9]
- [  1   9   4   2  53   1   1]
- [  6   0   5   1   2  45   2]
- [ 16   4   9  13   2  13  78]]
-Node Classification on random seed  230 -> 0.593
-Confusion Matrix:
- [[ 61   1  17   4   1  13  13]
- [  4 122   5   1   7   2   6]
- [ 16  17 112  33  51  25  28]
- [  6   7  27 112  14   5  15]
- [  1   5   4   2  62   2   2]
- [ 10   1   3   0   0  44   0]
- [ 10   4   5  11   8  21  80]]
-Node Classification on random seed  231 -> 0.607
-Confusion Matrix:
- [[ 76   2   2   7   3   6  16]
- [  6 113   7   3   6   5   7]
- [ 23  26 142  40  13  25  47]
- [ 12   6  12  88   5   4  20]
- [  3   6   5   3  54   2   4]
- [  6   2   0   5   0  49  15]
- [ 10   4   4   1   6  14  85]]
-Node Classification on random seed  232 -> 0.637
-Confusion Matrix:
- [[ 77   2   3   6   0   6  11]
- [  1 107  12   2  15   2   3]
- [ 21  29 148  18  21  22  44]
- [ 10   2  16 103  15  11  13]
- [  2  13   6   1  64   1   1]
- [  3   2   4   0   0  51   4]
- [  5   2   9  11   5   9  87]]
-Node Classification on random seed  233 -> 0.583
-Confusion Matrix:
- [[ 61  10  11   5   4   3  10]
- [  2 113   7   4   9   4   6]
- [ 19  36 137  28  40  17  46]
- [  9   7  11  89  14   6  26]
- [  1   5   3   0  58   0   1]
- [  3   3   2   4   0  40   7]
- [ 16   8   9   4   7  10  85]]
-Node Classification on random seed  234 -> 0.648
-Confusion Matrix:
- [[ 73   1  14   3   4   4  11]
- [  0 130   6   2   7   2   8]
- [ 25  36 138  29  32  24  17]
- [ 14   4   9 123   5   4  11]
- [  1   6   7   1  54   1   2]
- [  6   2   1   0   1  55   3]
- [ 15   2  12   4   5  11  75]]
-Node Classification on random seed  235 -> 0.602
-Confusion Matrix:
- [[ 75   4   1   2   6  16  15]
- [  8 120   7   4  11   3   8]
- [ 27  30 157  34  20  24  33]
- [  5   5  18  75   6   8  22]
- [  3   4   7   0  54   2   2]
- [  3   1   2   3   0  47   6]
- [ 14   4   8   5   4  13  74]]
-Node Classification on random seed  236 -> 0.609
-Confusion Matrix:
- [[ 64   1   6   7   2  20  11]
- [  3 148   3   0   6   1   3]
- [ 22  35 133  35  20  29  24]
- [ 16   6  13 109   4   9  14]
- [  1   7   7   1  57   4   1]
- [ 11   1   3   3   0  44   1]
- [ 19   2   7   6   6  21  54]]
-Node Classification on random seed  237 -> 0.646
-Confusion Matrix:
- [[ 92   5   6   2   1   4  11]
- [  2 121  12   6   6   5   5]
- [ 20  17 163  30  25  22  28]
- [ 11   4  15  89   4   3  26]
- [  3   3   3   0  61   0   2]
- [  6   3   5   1   0  48   9]
- [ 13   4   6   3   8  15  72]]
-Node Classification on random seed  238 -> 0.581
-Confusion Matrix:
- [[ 62   2   2   5   3  14   7]
- [  2 119   9   3  14   2   2]
- [ 15  36 111  39  18  28  69]
- [ 10   7   5 104   2  15   8]
- [  0   3   2   2  69   2   2]
- [  3   3   2   6   2  48   6]
- [ 20   5   6   6  13  19  68]]
-Node Classification on random seed  239 -> 0.588
-Confusion Matrix:
- [[ 71   3   6   1   1  16  15]
- [  2 115   2   0  18   5   3]
- [ 13  20 146  36  21  32  42]
- [ 20   6  13  89   6   8   7]
- [  0   5   6   0  50   3  11]
- [  6   3   7   4   0  41   5]
- [  8   9   8   1  10  30  76]]
-Node Classification on random seed  240 -> 0.617
-Confusion Matrix:
- [[ 66   2   5   5   7  11   5]
- [  2 122   7   3   9   3   2]
- [ 24  12 140  34  40  20  49]
- [  7   8  12 111   7   4  28]
- [  0   3   4   1  63   0   2]
- [  7   1   1   3   0  38   1]
- [ 11   2   5  14   5  17  77]]
-Node Classification on random seed  241 -> 0.642
-Confusion Matrix:
- [[ 80   2   2   2   3   7  16]
- [  5 135   7   1   4   0   4]
- [ 27  15 156  22  41  14  41]
- [ 15   3  15  81  13   3  14]
- [  1   4   4   2  69   0   2]
- [  8   0   4   0   0  39   2]
- [ 17   1   7  12   6  12  82]]
-Node Classification on random seed  242 -> 0.64
-Confusion Matrix:
- [[ 59   1   3   8   3  14   4]
- [  3 125   7   6   5   4   6]
- [ 29  18 160  35  33  22  27]
- [  7   4  15 105   3   5  10]
- [  1   9   3   0  60   1   2]
- [  9   0   3   0   0  46   3]
- [ 14   0   9   6   9  19  85]]
-Node Classification on random seed  243 -> 0.674
-Confusion Matrix:
- [[ 78   2   4   1   5  11   5]
- [  4 133   1   0   5   4   0]
- [ 15  13 181  32  30  12  30]
- [ 11   8  17 108   2  12   6]
- [  1  11   5   2  58   0   0]
- [  7   1   2   0   3  48   3]
- [ 15   4   4   4  14  20  68]]
-Node Classification on random seed  244 -> 0.592
-Confusion Matrix:
- [[ 67   0   5  11   9  12  11]
- [  5 130   4   5   8   6   4]
- [ 33  29 116  35  26  11  44]
- [ 10   5  14 111   8  10   6]
- [  1   2   2   2  63   1   5]
- [  0   4   2   4   1  41   9]
- [ 13   2   5   2  15  27  64]]
-Node Classification on random seed  245 -> 0.632
-Confusion Matrix:
- [[ 84   1   2   3   5   7   7]
- [  5 130   7   9  12   3   2]
- [ 34  15 122  50  35  20  20]
- [  8   5   9 107  12   3   9]
- [  1   3   6   0  74   0   1]
- [  8   1   4   0   0  53   0]
- [ 15   5  10   7  13  11  62]]
-Node Classification on random seed  246 -> 0.656
-Confusion Matrix:
- [[ 72   1   3  13   3  15   5]
- [  3 142   2   2   4   2   4]
- [ 19  24 167  26  10  24  31]
- [  8   9  24  97  12   8  10]
- [  1   3   6   3  59   1   0]
- [  0   0   2   4   1  42   8]
- [  6   3  15  11   6  12  77]]
-Node Classification on random seed  247 -> 0.632
-Confusion Matrix:
- [[ 73   1   2   3   3  13  19]
- [  4 120   5   1  11   1   3]
- [ 31  18 150  34  30  23  37]
- [ 10   3  10 113   5  12   9]
- [  1   7   1   2  68   1   1]
- [ 12   0   0   0   0  38   7]
- [ 11   1   7   7   7  15  70]]
-Node Classification on random seed  248 -> 0.618
-Confusion Matrix:
- [[ 55   3   5   4   3  15  17]
- [  4 121   5   0  13   5   3]
- [ 20  20 148  37  32  36  29]
- [  9   3   6 114   7   6  17]
- [  0   4   5   1  62   0   4]
- [  8   0   1   1   1  45   6]
- [  9   4  14   5   8  12  73]]
-Node Classification on random seed  249 -> 0.615
-Confusion Matrix:
- [[ 81   2   5   5   3   8   4]
- [  4 139   6   6   3   4   5]
- [ 31  29 149  26  14  22  35]
- [ 24   9  10  83  10  14   8]
- [  3  13   5   1  59   2   0]
- [  8   0   1   0   0  33   8]
- [ 10   3  13  16   2  13  71]]
-Node Classification on random seed  250 -> 0.617
-Confusion Matrix:
- [[ 72   3   3   6   3   8  11]
- [  3 138   6   3   4   5   2]
- [ 31  30 132  35  33  21  42]
- [  8   2  12 109   4   9  13]
- [  2   5   3   3  51   2   0]
- [  1   1   4   1   3  47   7]
- [  6   5  10   1   8  24  68]]
-Node Classification on random seed  251 -> 0.591
-Confusion Matrix:
- [[ 73   2   3   8   1  10  12]
- [  4 135   2   4   6   2   8]
- [ 37  26 116  40  51  27  26]
- [  4   2  16  99   7   2  15]
- [  7   7   4   1  55   1   3]
- [  7   3   0   0   3  42   3]
- [ 16   3  10   3   4  19  71]]
-Node Classification on random seed  252 -> 0.638
-Confusion Matrix:
- [[ 82   2  10   3   4   8   8]
- [  1 131   8   4  12   4   1]
- [ 30  15 137  53  27  19  27]
- [ 13   5  13 113   9   5   5]
- [  0   8   4   3  59   0   4]
- [  4   3   2   1   1  48   1]
- [ 10   5   9   6   7   8  68]]
-Node Classification on random seed  253 -> 0.612
-Confusion Matrix:
- [[ 70   0   5  16   5   8  11]
- [  5 126   3   0  11   3   5]
- [ 20  22 143  32  27  24  34]
- [  4   6  23 110   5   3  10]
- [  3   9   2   1  56   0   2]
- [  6   0   0   3   1  47  10]
- [ 21   6  12  11   9  10  60]]
-Node Classification on random seed  254 -> 0.619
-Confusion Matrix:
- [[ 68   1   2   8   3  16  10]
- [  2 125   5   4   7   1   0]
- [ 19  30 114  48  53  25  25]
- [ 11   1  13 112   3   5  11]
- [  1   5   2   1  67   1   1]
- [  2   0   0   3   2  51   7]
- [  8   2   9  17   3  14  82]]
-Node Classification on random seed  255 -> 0.633
-Confusion Matrix:
- [[ 77   3   1   7   4  20  14]
- [  2 126   5   7   6   1   4]
- [ 21  20 154  34  34  25  23]
- [ 12   5  21  98   3  10   4]
- [  0   8   5   0  58   0   3]
- [  2   4   0   1   1  51   9]
- [  6   3   5   5   5  24  69]]
-Node Classification on random seed  256 -> 0.63
-Confusion Matrix:
- [[ 68   1   0   5   3  20   9]
- [ 12 115  12   0   7   0   9]
- [ 25  15 145  29  17  37  33]
- [  5   3  21 115   8   4  10]
- [  5   3   6   0  56   0   1]
- [  7   1   3   1   2  52   7]
- [ 20   0   6   5   5  13  79]]
-Node Classification on random seed  257 -> 0.598
-Confusion Matrix:
- [[ 78   2   3   4   7  11   8]
- [  1 114   8   5  12   4   6]
- [ 34  24 113  41  44  26  23]
- [  9   7  18 110   6   2   3]
- [  2  13   3   3  58   0   2]
- [  2   0   0   1   5  38   5]
- [ 12   8   9   3   5  21  87]]
-Node Classification on random seed  258 -> 0.621
-Confusion Matrix:
- [[ 74   2   6   6   4   6  10]
- [  4 130   5   3   9   3  10]
- [ 25  12 141  56  18  23  30]
- [  6   2  11 111   3   7  11]
- [  1  10   7   4  53   0   3]
- [  9   2   3   5   2  40   3]
- [ 13   5   9   6   5  20  72]]
-Node Classification on random seed  259 -> 0.603
-Confusion Matrix:
- [[ 64   5   9   1   3  15  18]
- [  4 137   1   0   7   1   3]
- [ 21  23 120  44  31  24  46]
- [ 11   6  21  93   1  10  12]
- [  1   9   3   2  62   1   0]
- [  3   1   2   3   1  40   4]
- [  5   6   8  13  10   8  87]]
-Node Classification on random seed  260 -> 0.636
-Confusion Matrix:
- [[ 74   4   1   5   2   5   8]
- [  7 134   8   2   8   3   4]
- [ 26  16 149  31  29  26  34]
- [ 13   0  13 114   5   4  13]
- [  0   4   3   0  60   2   1]
- [ 10   2   3   4   7  32   6]
- [ 21   0  10   5   6  13  73]]
-Node Classification on random seed  261 -> 0.617
-Confusion Matrix:
- [[ 87   2   4   1   4  13   7]
- [  7 114   2   5  21   1   2]
- [ 27  17 139  26  36  14  41]
- [  7   0  21  94   8   5  12]
- [  2   8   5   1  54   3   5]
- [  9   3   1   4   2  39   7]
- [ 11   2   8   5   7  17  90]]
-Node Classification on random seed  262 -> 0.623
-Confusion Matrix:
- [[ 72   2   5   7   6  15  10]
- [  4 141   5   4   1   2   2]
- [ 16  21 121  40  20  28  31]
- [  5   5  15 113   6   7  24]
- [  1   4   5   2  55   2   1]
- [  8   1   3   3   0  50   2]
- [ 14   3   9   4  14  20  71]]
-Node Classification on random seed  263 -> 0.613
-Confusion Matrix:
- [[ 69   1   3   3   6  11   6]
- [  5 138   5   2   6   4   2]
- [ 16  24 132  43  19  36  42]
- [ 20   1  12  98   6   5  13]
- [  3   5   2   0  56   5   2]
- [  9   0   1   5   0  46   5]
- [ 16   5  11   9   6  12  74]]
-Node Classification on random seed  264 -> 0.65
-Confusion Matrix:
- [[ 89   4   5   3   6   7   4]
- [  2 121  10   2  10   2   2]
- [ 24  16 160  22  31  15  37]
- [  8   5  22 109   8   3   7]
- [  0   8   6   1  59   0   3]
- [ 12   2   2   3   1  45   1]
- [ 17   4  21   2   6   6  67]]
-Node Classification on random seed  265 -> 0.63
-Confusion Matrix:
- [[ 64   9   2   7   3   9  13]
- [  7 138   3   1   3   1   3]
- [ 16  24 128  25  46  11  44]
- [ 11   9   5 122  14   4  10]
- [  0   8   5   0  50   1   3]
- [  9   3   1   5   1  47   3]
- [ 13   4   9   2  10  13  81]]
-Node Classification on random seed  266 -> 0.6
-Confusion Matrix:
- [[ 68   1  14   8  10  10   7]
- [  3 144   0   4   8   4   3]
- [ 22  27 111  62  25  16  45]
- [  5   3  10  95   4   5  13]
- [  0   3   1   0  61   2   1]
- [  3   4   8   4   0  38   3]
- [  8   3  13  12  11  15  83]]
-Node Classification on random seed  267 -> 0.622
-Confusion Matrix:
- [[ 75   2   7   5   5   7  13]
- [  6 119  12   1  10   2   6]
- [ 16  21 140  30  36  20  41]
- [ 19   1  19 101   4   4  15]
- [  1   4   3   2  64   1   1]
- [  0   1   1   6   2  40   4]
- [  6   2  22   6   4  10  83]]
-Node Classification on random seed  268 -> 0.588
-Confusion Matrix:
- [[ 70   2   7   3   5  16   9]
- [ 11 126   6   5   4   2   1]
- [ 33  21 128  46  21  27  40]
- [ 14   2  18 105   2   3  13]
- [  0   6   4   1  56   1   4]
- [  3   2   2   3   3  50   5]
- [  9   4  14   7  14  19  53]]
-Node Classification on random seed  269 -> 0.628
-Confusion Matrix:
- [[ 59   3   8   9   5   9   7]
- [  2 138   2   5  15   2   2]
- [ 21  31 141  51  32  20  17]
- [  7   6  18 115   2   2   9]
- [  3   5   2   2  62   0   2]
- [  2   2   3   3   1  53   1]
- [  8   5   6   8  13  21  60]]
-Node Classification on random seed  270 -> 0.612
-Confusion Matrix:
- [[ 70   3   7  12   1   5   5]
- [  2 115   5   2  14   1  12]
- [ 22  21 132  45  24  13  43]
- [ 23   2  15 106   5   5   6]
- [  4   4   6   1  79   0   2]
- [  6   0   1   0   0  51   6]
- [  7   5   7  15  18  13  59]]
-Node Classification on random seed  271 -> 0.61
-Confusion Matrix:
- [[ 73   1   2   0   3  13   8]
- [  6 128   5   2  10   3   1]
- [ 29  24 124  41  23  20  49]
- [ 11   2  21  97  20   4  12]
- [  1   7   2   1  69   0   3]
- [  4   3   6   3   0  47   5]
- [  7   3  15   6   5   9  72]]
-Node Classification on random seed  272 -> 0.65
-Confusion Matrix:
- [[ 82   5   6   4   3   8   6]
- [  3 123   4   3  11   0   1]
- [ 19  19 173  26  36  19  28]
- [  5   3  23 110   9   6  11]
- [  1   6   7   0  56   0   1]
- [  6   1   2   2   2  52   1]
- [ 13   6  18   5   3  18  54]]
-Node Classification on random seed  273 -> 0.616
-Confusion Matrix:
- [[ 68   1  12   1   2  15   8]
- [  7 110   8   1  12  10   4]
- [ 20  17 147  42  29  19  31]
- [ 17   2  10 106   4   3  18]
- [  2   4   2   2  67   2   2]
- [  3   0   2   1   0  48   5]
- [ 16   4  13  10  15   8  70]]
-Node Classification on random seed  274 -> 0.58
-Confusion Matrix:
- [[ 63   1   4   4   6  13  17]
- [  2 121   7   4  12   4   5]
- [ 30  32 117  42  42  22  44]
- [ 16   6  18 111   9   6   1]
- [  1   5   1   1  60   1   2]
- [  2   3   1   4   1  42   6]
- [  8   8   6   6   9   8  66]]
-Node Classification on random seed  275 -> 0.625
-Confusion Matrix:
- [[ 62   0   1   1   6  15   6]
- [  3 116   5   2  20   2   4]
- [ 27  17 157  39  27  14  39]
- [  3   3  17 106   3   2  22]
- [  0   7   6   1  67   1   4]
- [  7   0   5   1   2  47   7]
- [  6   3  18   9   6  14  70]]
-Node Classification on random seed  276 -> 0.599
-Confusion Matrix:
- [[ 80   1   7   4   2  10   5]
- [ 10 122   3   4   5   3   1]
- [ 30  21 146  46  22  35  28]
- [ 14  13   9 101   2   8   8]
- [  0   6   7   1  55   2   4]
- [ 11   2   1   7   0  30   5]
- [ 15   8  10   9   9  13  65]]
-Node Classification on random seed  277 -> 0.601
-Confusion Matrix:
- [[ 65   3   1   7   3  18  15]
- [  7 122   4   2   9   1   5]
- [ 24  20 140  21  30  36  37]
- [  9   1  22  88   2  13  17]
- [  1   6   4   1  70   0   2]
- [ 11   0   1   3   0  35   7]
- [ 16   3  10   3  19   5  81]]
-Node Classification on random seed  278 -> 0.622
-Confusion Matrix:
- [[ 62   1   3   9   7   3  13]
- [  5 149   2   6   8   2   1]
- [ 21  26 130  54  22  16  39]
- [ 16   4  15  91   3   3  13]
- [  5   5   3   1  64   0   1]
- [  4   0   1   3   2  48   5]
- [ 14   2   9  12   8  11  78]]
-Node Classification on random seed  279 -> 0.632
-Confusion Matrix:
- [[ 74   5   4   6   9  11   8]
- [  5 120  10   5   2   0   4]
- [ 17  15 154  40  37  11  39]
- [ 11   4  23  86   2   2  19]
- [  0   5   2   1  58   2   1]
- [  4   3   1   5   2  46   3]
- [ 16   2   5   7   6  14  94]]
-Node Classification on random seed  280 -> 0.62
-Confusion Matrix:
- [[ 72   3   5   2   2  21  12]
- [  1 119   8   4   4   2   7]
- [ 21  27 144  27  29  19  35]
- [ 13   2  13 102  10  10  16]
- [  2   7   3   0  67   0  10]
- [  5   0   1   2   2  47   3]
- [ 14   6   8   2   8  14  69]]
-Node Classification on random seed  281 -> 0.63
-Confusion Matrix:
- [[ 60   6   6   1   3  10   8]
- [ 10 136  10   0   7   1   8]
- [ 31  17 146  27  28  21  41]
- [  6   1  11  98   4   9  20]
- [  1   1   4   1  55   2   1]
- [  2   0   2   2   0  52  11]
- [  6   6  13   4   8  20  83]]
-Node Classification on random seed  282 -> 0.619
-Confusion Matrix:
- [[ 81   7   3   0   9  12   5]
- [  7 116   6   2   8   6   2]
- [ 25  17 130  38  32  24  32]
- [ 12   3   7 115   3   5   9]
- [  1   9   9   5  49   1   3]
- [  6   0   0   1   1  52   7]
- [ 19   4   7   7  16  11  76]]
-Node Classification on random seed  283 -> 0.603
-Confusion Matrix:
- [[ 83   0   3   3   3   9   2]
- [  8 105  17   2   6   2   8]
- [ 33  17 107  44  35  24  48]
- [  7   6  15 115   3   9  11]
- [  1   5   2   2  64   5   2]
- [  6   4   0   0   0  54   2]
- [ 15   4   6   4  11  13  75]]
-Node Classification on random seed  284 -> 0.574
-Confusion Matrix:
- [[ 81   2   2   4   2   8   6]
- [  4 118   7   4  12   0   6]
- [ 23  22 102  57  13  40  30]
- [ 25   2  24  79  11   6  18]
- [  0   2   7   1  66   1   2]
- [ 17   4   2   1   0  38   7]
- [ 19   3   6   9   7  10  90]]
-Node Classification on random seed  285 -> 0.622
-Confusion Matrix:
- [[ 57   2   5   7   1  12  11]
- [  4 131   4   2   6   6   7]
- [ 28  21 155  38  23  23  45]
- [  9   6  14  97   3   6  11]
- [  4   9   3   1  52   4   5]
- [  2   1   3   1   2  41   5]
- [  3   4  11   8   7  11  89]]
-Node Classification on random seed  286 -> 0.642
-Confusion Matrix:
- [[ 72   1   0   3  12   8   9]
- [  5 123   4   3   6   6   3]
- [ 26  10 178  48  13  15  27]
- [ 16   5  11  96  12   4  19]
- [  0   6   8   0  51   1   1]
- [  9   1   5   3   2  43   5]
- [  9   3   4  12   4  19  79]]
-Node Classification on random seed  287 -> 0.593
-Confusion Matrix:
- [[ 61   1   4   3   0  16   6]
- [  8 146   6   4   4   1   8]
- [ 22  53 138  42  17  25  28]
- [ 16   2  23  89   4   3  14]
- [  1   7   4   4  57   3   4]
- [  3   2   3   1   2  36   6]
- [ 11   9  12   4   8  13  66]]
-Node Classification on random seed  288 -> 0.584
-Confusion Matrix:
- [[ 73   3   7   3   5  13  19]
- [  9 111   6   1   9   1   4]
- [ 19  33 115  38  18  29  62]
- [  6   6  27 104   0   5  16]
- [  2   6   0   3  60   0   2]
- [ 10   0   5   1   4  41   8]
- [  9   2   8   2   3  12  80]]
-Node Classification on random seed  289 -> 0.61
-Confusion Matrix:
- [[ 75   1   8   0   3  13  11]
- [  6 142   1   2  10   3   3]
- [ 21  31 122  35  30  23  40]
- [  7   5   9 111   6   9  14]
- [  1   8   1   1  54   3   5]
- [  5   2   4   0   0  32   5]
- [  8   5  16   4   5  26  74]]
-Node Classification on random seed  290 -> 0.608
-Confusion Matrix:
- [[ 57   3   0   6   3  26   9]
- [  3 125   4   1  11   2   6]
- [ 23  21 143  29  55  20  34]
- [ 13   9  12 116   1   8  13]
- [  0   6   2   1  57   3   5]
- [  3   1   0   8   0  44   3]
- [  2   5   7  14   6  14  66]]
-Node Classification on random seed  291 -> 0.604
-Confusion Matrix:
- [[ 74   2   3   3   5  11  12]
- [  4 112   2   1   5   3   2]
- [ 26  25 158  18  33  33  41]
- [ 17   3  18  82  12  12   6]
- [  2  10   1   0  70   2   6]
- [  7   0   2   1   1  54   1]
- [  9   1  16   5   6  29  54]]
-Node Classification on random seed  292 -> 0.583
-Confusion Matrix:
- [[ 68   3  11   9   9   7  12]
- [  9 125  11   5   4   1   8]
- [ 17  49 127  38  15  15  36]
- [ 11   1  18  84   4  24   5]
- [  1  10   5   1  52   0   4]
- [  5   1   0   3   2  47   7]
- [ 20   3  13   7   8   5  80]]
-Node Classification on random seed  293 -> 0.609
-Confusion Matrix:
- [[ 62   2   3  13   3  16  14]
- [  4 111   9   6   5   0   3]
- [ 26  22 150  31  16  18  36]
- [ 15   3   9 104  10   7  16]
- [  0  10   7   2  60   0   3]
- [  3   1   0   5   0  37  11]
- [ 20   7   5   9   6  15  85]]
-Node Classification on random seed  294 -> 0.614
-Confusion Matrix:
- [[ 75   4   2   5   1  15   5]
- [  7 126   7   3   2   4   1]
- [ 17  24 138  50  31  25  35]
- [ 15   4  10 118   3  11   8]
- [  2  10   5   0  56   0   4]
- [  2   1   2   2   0  46   6]
- [  9   5  19  11   2  17  55]]
-Node Classification on random seed  295 -> 0.619
-Confusion Matrix:
- [[ 84   4   1   2   0   7   8]
- [  4 136   4   4  11   4   0]
- [ 40  26 112  32  20  21  43]
- [ 10  10  13 101   6  12  12]
- [  5   5   5   0  63   0   3]
- [  3   0   0   3   0  39   7]
- [ 17   4   6   4   6  19  84]]
-Node Classification on random seed  296 -> 0.606
-Confusion Matrix:
- [[ 72   6   1   2   2  25   1]
- [  2 141   4   4   7   3   2]
- [ 13  36 126  34  35  35  21]
- [  5   4  15 101  12  11  13]
- [  1  12   0   2  56   2   3]
- [  3   0   3   5   2  41   6]
- [  6   6   8  11   7  24  69]]
-Node Classification on random seed  297 -> 0.639
-Confusion Matrix:
- [[ 79   2   4   2   2  12  10]
- [  3 146   2   4   2   3   7]
- [ 22  24 130  27  25  27  32]
- [ 18   4  14 102   3   4  21]
- [  1   6   3   5  56   1   1]
- [  0   1   6   3   0  44   6]
- [ 14   9   5   1  11  14  82]]
-Node Classification on random seed  298 -> 0.619
-Confusion Matrix:
- [[ 70   9   0  12   6   6  14]
- [ 15 123   2   1   6  12   1]
- [ 27  17 135  26  30  17  26]
- [  6  10  24 118   9  13   6]
- [  3   1   3   2  67   0   1]
- [ 14   0   1   2   0  36   4]
- [ 13   5   8  10   8  11  70]]
-Node Classification on random seed  299 -> 0.656
-Confusion Matrix:
- [[ 64   3   0   3   5   9  21]
- [  7 112   7   0  15   1   5]
- [ 17  12 179  17  45  16  27]
- [  7   6  10 105  10   7  10]
- [  1   3   4   0  70   1   2]
- [  5   0   1   1   2  43   6]
- [ 11   3  13   4  14  13  83]]
-Node Classification on random seed  300 -> 0.612
-Confusion Matrix:
- [[ 76   5   0   4   4  13   5]
- [  9 108  11   4  14   2   5]
- [ 20  33 132  37  25  29  41]
- [ 10   5   9 103   8   3  12]
- [  0   6   3   3  56   4   3]
- [  7   2   5   0   1  50   3]
- [ 11   4   9   5   7   7  87]]
-Node Classification on random seed  301 -> 0.597
-Confusion Matrix:
- [[ 68   4   7  11   6  11  12]
- [  9 117   6   3  12   5   4]
- [ 24  16 114  23  48  26  50]
- [  3   3  20 110  11   5  12]
- [  3   3   3   0  70   0   7]
- [  5   2   2   2   1  38   5]
- [ 10   3   7   2   7  10  80]]
-Node Classification on random seed  302 -> 0.587
-Confusion Matrix:
- [[ 60   2  10  12   6  12   3]
- [  3 136  11   3   4   4   6]
- [ 20  27 127  27  28  25  52]
- [  9   4  31  90   3  12   7]
- [  0   7   4   1  63   0   2]
- [ 13   2   4   0   0  40   4]
- [ 12   6   9  14   5   9  71]]
-Node Classification on random seed  303 -> 0.615
-Confusion Matrix:
- [[ 62   1   7  14   5  14   7]
- [  7 123   4   0   7   1   7]
- [ 27  36 127  36  43  15  25]
- [  6   8  22 113   5   5   6]
- [  3   4   1   0  64   1   2]
- [  2   0   4   1   0  46   2]
- [ 12   2   7  11   7  18  80]]
-Node Classification on random seed  304 -> 0.624
-Confusion Matrix:
- [[ 58   2   4   1   4  15  12]
- [  5 150   4   5   5   2   3]
- [ 21  33 140  41  21  18  30]
- [ 10   5  17  96   3   7  14]
- [  0   5   3   4  67   1   4]
- [  1   2   9   0   2  44   3]
- [ 11   9   5   4   4  27  69]]
-Node Classification on random seed  305 -> 0.62
-Confusion Matrix:
- [[ 70   1   1   1   4  16  11]
- [  6 130  10   3   4   3   4]
- [ 21  21 142  36  42  23  36]
- [ 11   8  23 102   2   7  11]
- [  1   3   5   2  54   1   1]
- [  6   2   5   1   0  36   5]
- [ 13   5   5   6   4  10  86]]
-Node Classification on random seed  306 -> 0.609
-Confusion Matrix:
- [[ 77   0   2   9   5   6  10]
- [  3 141   3   2   9   6   1]
- [ 29  26 132  39  24  22  46]
- [ 21   4   4 106  13   3   9]
- [  4  12   6   5  41   0   2]
- [  7   1   1   1   2  48   5]
- [ 10   3   3  11  15   7  64]]
-Node Classification on random seed  307 -> 0.617
-Confusion Matrix:
- [[ 70   3   4   8   2   5   3]
- [  8 124   6   1   4   1   4]
- [ 45  25 144  39  19  13  47]
- [ 11   2  13  99   4   7  15]
- [  1   5   4   0  57   3   5]
- [  7   5   1   2   1  29   6]
- [ 22   2   6  10   8   6  94]]
-Node Classification on random seed  308 -> 0.619
-Confusion Matrix:
- [[ 69   1   4   6   6  16   4]
- [  2 128  12   2   4   0   5]
- [ 11  20 141  35  34  27  30]
- [ 13   5  23  75   9   7  23]
- [  1   6   2   1  63   5   4]
- [  8   3   2   0   1  46   4]
- [  6   7   4   3  12  13  97]]
-Node Classification on random seed  309 -> 0.58
-Confusion Matrix:
- [[ 58   3   9   6   4   8  12]
- [  5 131   2   4  14   1   6]
- [ 22  38 125  22  15  35  48]
- [ 10   1  24  93   4  13  21]
- [  1   2   5   3  66   1   3]
- [  6   2   2   3   3  39   7]
- [ 10   7   5   9   8  16  68]]
-Node Classification on random seed  310 -> 0.638
-Confusion Matrix:
- [[ 66   2   3   2   2  11  16]
- [  2 130   4   7  12   9   5]
- [ 21  23 131  17  59  30  25]
- [ 14   5  12 108   6   1   8]
- [  2   3   3   1  68   1   0]
- [  0   1   0   1   1  54   4]
- [  7   5   9   3  12  13  81]]
-Node Classification on random seed  311 -> 0.634
-Confusion Matrix:
- [[ 89   1   0   2   0  13   9]
- [  5 125   6   1   8   2   7]
- [ 18  18 161  36  15  18  46]
- [ 26   3  15  93   5   5   8]
- [  3   3   5   0  58   0   3]
- [ 12   1   3   1   3  32   1]
- [ 18   9   6   7   6  18  76]]
-Node Classification on random seed  312 -> 0.597
-Confusion Matrix:
- [[ 73   1   2   1  10  10  11]
- [  9 148   4   0   3   2   2]
- [ 32  23 132  46  27  26  27]
- [ 22   4  30  78   5   7   8]
- [  0   7   6   1  50   0   7]
- [  6   4   5   0   0  51   2]
- [ 17   6  14   3   2  11  65]]
-Node Classification on random seed  313 -> 0.629
-Confusion Matrix:
- [[ 81   1   8   7   5  18   3]
- [  3 131   9   2  14   2   4]
- [ 18  36 127  41  24  17  39]
- [  6   4  17 117   5   3   9]
- [  1   9   2   1  53   0   4]
- [  9   0   1   1   3  36   9]
- [ 10   4   7   2   7   6  84]]
-Node Classification on random seed  314 -> 0.59
-Confusion Matrix:
- [[ 79   1   4   3  10   9   8]
- [  4 113   5   3  12   7   8]
- [ 28  30 129  45  17  20  45]
- [ 22   3  12 110   5   3   9]
- [  0   5   7   3  59   0   3]
- [ 10   3   3   2   5  36   3]
- [ 13   1   6   9   6  18  64]]
-Node Classification on random seed  315 -> 0.604
-Confusion Matrix:
- [[ 74   2   1   1   3  12  12]
- [  7 123   4   1   6   9   4]
- [ 35  25 141  38  33  23  31]
- [ 10   3   7 110   5   6  18]
- [  1   7   4   0  58   2   3]
- [ 11   0   1   9   1  28   3]
- [ 12   4   4  19   5  14  70]]
-Node Classification on random seed  316 -> 0.638
-Confusion Matrix:
- [[ 77   4   0   5   0  19   3]
- [  3 108   8   5  11  10   2]
- [ 30  16 140  23  23  43  22]
- [  6   2  16 128   8  13   9]
- [  1   2   4   0  70   1   5]
- [  3   2   1   1   3  46   3]
- [ 11   4   3   8  10  19  69]]
-Node Classification on random seed  317 -> 0.605
-Confusion Matrix:
- [[ 91   2   7   2   3  10   4]
- [  5 127   5   0  10   2   4]
- [ 25  33 113  25  27  34  64]
- [  2   4  13  97   4   5  25]
- [  2   5   3   5  55   0   3]
- [  3   1   0   2   2  48   1]
- [ 16   4   1  11   9  12  74]]
-Node Classification on random seed  318 -> 0.605
-Confusion Matrix:
- [[ 62   3   4  10   2  16  13]
- [  8 124   9   4   5   3  13]
- [ 24  18 135  36  32  27  23]
- [  9   7  11 107  17   6   8]
- [  2   6   1   0  56   1   4]
- [  6   0   0   4   2  48   1]
- [  6   1   8  11   8  26  73]]
-Node Classification on random seed  319 -> 0.591
-Confusion Matrix:
- [[ 70   1   4   9   4  13   6]
- [  4 125   7   3  10   4  10]
- [ 45  25 133  12  39  22  33]
- [ 13  10  12  99  15   7   5]
- [  0   6   4   0  71   0   4]
- [  3   0   0   5   2  37  10]
- [  5   6  10   6  29   6  56]]
-Node Classification on random seed  320 -> 0.63
-Confusion Matrix:
- [[ 68   1   2   5   1  12  17]
- [  7 126   1   1   8   0   3]
- [ 22  19 145  17  30  25  50]
- [ 18   3  13  91   7   7  12]
- [  1   6   3   3  72   0   4]
- [  6   0   6   1   1  41  10]
- [  8   6   3  10  11  10  87]]
-Node Classification on random seed  321 -> 0.591
-Confusion Matrix:
- [[ 72   2   6   5   8  16   4]
- [  5 101   6   4  22   1   8]
- [ 35  15 125  30  30  28  30]
- [ 22   0  20  96  11   4  10]
- [  2   3   0   0  70   6   5]
- [  2   3   5   0   0  50   3]
- [  4   5   8   6   8  27  77]]
-Node Classification on random seed  322 -> 0.633
-Confusion Matrix:
- [[ 86   4   1   3   3  13   4]
- [  6 108   4   1  13   6   2]
- [ 42  14 155  34  19  25  39]
- [ 11   4  17  88   6   8   7]
- [  3   4   6   0  68   0   4]
- [  5   4   2   2   2  41   3]
- [  7   2   8   5   2  22  87]]
-Node Classification on random seed  323 -> 0.621
-Confusion Matrix:
- [[ 77   4   6   7   4   2  12]
- [  4 116  15   0  10   1   1]
- [ 29  18 121  30  31  30  34]
- [ 15   1   6 127   7   7  11]
- [  0  16   7   1  51   0   1]
- [  9   1   4   4   0  47   2]
- [  6   3  11   9   5  15  82]]
-Node Classification on random seed  324 -> 0.635
-Confusion Matrix:
- [[ 74   1   5   3   8  10  10]
- [  3 138   4   2   5   2   2]
- [ 30  21 143  50  20  21  34]
- [ 13   5   8 104   6   2  16]
- [  0   7   6   3  66   0   2]
- [ 13   1   3   0   1  44   4]
- [ 10   2   3   9   7  13  66]]
-Node Classification on random seed  325 -> 0.65
-Confusion Matrix:
- [[ 75   4   1   8   2  14   4]
- [  4 127   5   2  10   2   4]
- [ 30  13 138  23  36  23  34]
- [  7   5  19 105   6   5   7]
- [  3   6   4   1  71   1   0]
- [  5   1   1   0   2  44   9]
- [ 12   3  13   5   1  15  90]]
-Node Classification on random seed  326 -> 0.629
-Confusion Matrix:
- [[ 76   5   0   6   2  18   5]
- [  2 126  15   0   9   3   1]
- [ 28  13 146  20  10  31  44]
- [ 10   4  15 123   2   3  11]
- [  0   3   3   1  64   1   8]
- [  7   3   1   3   1  34  10]
- [ 13   2   7  16  11  24  60]]
-Node Classification on random seed  327 -> 0.603
-Confusion Matrix:
- [[ 62   3   8   7   4  22   8]
- [  0 119  13   9   5   3   3]
- [ 22  16 155  38  23  26  17]
- [  5   0  14 107   8  15  13]
- [  4   7   6   2  60   2   3]
- [  4   8   1   4   1  41   5]
- [ 13   2   6  13   7  27  59]]
-Node Classification on random seed  328 -> 0.584
-Confusion Matrix:
- [[ 58   3   9   7   2  10  22]
- [  3 124   3   0   2   8   9]
- [ 23  12 128  45  27  29  46]
- [ 15   2  21 117   2  11  12]
- [  2   4   4   1  59   0   5]
- [ 11   0   6   1   0  20   7]
- [  9   5  11  15   7   5  78]]
-Node Classification on random seed  329 -> 0.615
-Confusion Matrix:
- [[ 74   3   5   7   4  19   9]
- [  5 119   6   2   6   1   6]
- [ 29  31 153  37  20  22  24]
- [ 13   5  13  94   4   4   9]
- [  1  10   8   1  63   3   1]
- [  3   2   0   3   0  35   5]
- [  8  10   9   9   7  21  77]]
-Node Classification on random seed  330 -> 0.66
-Confusion Matrix:
- [[ 79   2   1   2   2  11  10]
- [  1 149   4   0   2   4  11]
- [ 31  17 152  51  11  13  27]
- [  9   9  14 108   8   3  12]
- [  1   8   5   0  50   1   3]
- [  4   2   2   0   1  43   5]
- [ 14   8  11   3   3  14  79]]
-Node Classification on random seed  331 -> 0.617
-Confusion Matrix:
- [[ 66   8   2   6   4  10  12]
- [  4 116  14   3   8   0   5]
- [ 11  25 134  32  35  30  39]
- [  2   0  13 106  16  11  16]
- [  1   2   4   0  69   0   1]
- [  4   1   1   2   0  44   4]
- [ 16   4   4   6  10  17  82]]
-Node Classification on random seed  332 -> 0.617
-Confusion Matrix:
- [[ 69   0   6   2   2  11   6]
- [  6 123   6   2   9  10   3]
- [ 25  19 156  20  32  21  51]
- [ 13   5  10  96   3   3  21]
- [  2   4   2   0  54   1   6]
- [  6   2   4   1   2  46  12]
- [ 14   1   4   6  10  20  73]]
-Node Classification on random seed  333 -> 0.617
-Confusion Matrix:
- [[ 74   1  10  10   5  10  12]
- [  2 141   2   1   5   1   6]
- [ 21  24 132  34  21  23  49]
- [ 10   8   9 109  12   5  20]
- [  0  13   2   3  49   1   1]
- [  3   1   1   2   0  43   9]
- [  6   2  11   9   8  10  69]]
-Node Classification on random seed  334 -> 0.605
-Confusion Matrix:
- [[ 64   4   2   5   5   7  10]
- [  3 131   8   1  12   4   9]
- [ 18  23 135  35  30  37  19]
- [ 10   4  18  95  11   8   6]
- [  1   6   5   0  64   3   1]
- [  1   5   0   1   1  58   9]
- [ 20   9   9   4   5  26  58]]
-Node Classification on random seed  335 -> 0.596
-Confusion Matrix:
- [[ 69   0   3   4   2   7  13]
- [  4 118   8   2  10   9   1]
- [ 25  24 130  36  31  37  38]
- [ 25   4   4 108   6  13  21]
- [  2   4   1   2  50   2   0]
- [  8   0   0   2   0  51   3]
- [ 11   3   5  11   4  19  70]]
-Node Classification on random seed  336 -> 0.63
-Confusion Matrix:
- [[ 72   2   4   9   2  13   6]
- [  0 134  10   1   9   0   2]
- [ 13  29 147  42  18  26  42]
- [ 13   4  10  95   5  15  18]
- [  0   8   5   3  59   1   2]
- [  7   1   0   0   0  40   5]
- [  7   5   8   5   6  14  83]]
-Node Classification on random seed  337 -> 0.615
-Confusion Matrix:
- [[ 65   2   1   4   5  16   9]
- [ 11 102   3   0  18   5   6]
- [ 23  28 155  41  19  35  29]
- [  8   1   9 110   5   8  14]
- [  1   3   3   0  57   0   2]
- [  4   4   0   1   2  48   4]
- [ 12   2   7   8   8  24  78]]
-Node Classification on random seed  338 -> 0.587
-Confusion Matrix:
- [[ 66   5   6   7   1  20   8]
- [ 11 100  15   4   7   1   7]
- [ 25  21 134  34  33  37  31]
- [  5   7  14 112   3   5   6]
- [  3   6   3   2  64   0   3]
- [  1   4   2   3   2  45   6]
- [  8   7  11  12   2  25  66]]
-Node Classification on random seed  339 -> 0.583
-Confusion Matrix:
- [[ 70   2   3   4   5   9  14]
- [  3 118   7   4   6   3  12]
- [ 33  24 123  60  18  21  33]
- [ 20   4  11  88   3  14  12]
- [  4   4   4   1  68   0   1]
- [  8   0   1   0   2  39   6]
- [  5   7  11   9   8  21  77]]
-Node Classification on random seed  340 -> 0.581
-Confusion Matrix:
- [[ 53   8   4   6   5  18  15]
- [  9 122  12   4   5   2   2]
- [ 28  17 120  30  21  23  57]
- [ 14   6  21  81   6   5  16]
- [  4   3   2   1  58   4   2]
- [  8   0   0   2   0  53   5]
- [ 11   2  11   7   6  17  94]]
-Node Classification on random seed  341 -> 0.604
-Confusion Matrix:
- [[ 64   0   4   3   4  22   7]
- [  2 112  17   1  11   4   0]
- [ 18  27 130  24  32  30  41]
- [ 12  10  18  98   5   8  12]
- [  0   4   5   2  60   2   2]
- [  4   2   3   4   2  48   2]
- [  9   5   9   1   7  21  92]]
-Node Classification on random seed  342 -> 0.599
-Confusion Matrix:
- [[ 60   3   3   8  10   9   9]
- [  3 120  10   0   3   4   8]
- [ 31  13 151  63  16  11  30]
- [  8   4  22 105  12   3  12]
- [  5   5   2   2  51   1   2]
- [  3   1   0   4   0  35  12]
- [ 21   3  12  11   5  17  77]]
-Node Classification on random seed  343 -> 0.609
-Confusion Matrix:
- [[ 67   4   1   6   1  14  10]
- [  1 121   3   2   7   2   7]
- [ 26  13 145  35  29  28  43]
- [ 12   6  15  92   6   9  24]
- [  1   5   6   1  67   5   2]
- [  0   1   4   1   0  49   4]
- [ 20   1   4  11   6  15  68]]
-Node Classification on random seed  344 -> 0.638
-Confusion Matrix:
- [[ 67   7   4   0   5   9  15]
- [  3 138   8   4  10   2   4]
- [ 31  17 142  41  31  12  27]
- [ 18   4  19 109   8   2  10]
- [  2   4   4   1  65   0   1]
- [  5   1   3   7   0  39   3]
- [ 10   2   5   5   5  13  78]]
-Node Classification on random seed  345 -> 0.592
-Confusion Matrix:
- [[ 54   4   6   5   1  19   4]
- [  5 132   4   2   3   6   4]
- [ 18  39 131  18  30  25  35]
- [ 19   8  16 103   3   7  12]
- [  3   3   2   2  70   1   2]
- [  7   0   4   1   0  35   4]
- [ 25  12   9   3  11  26  67]]
-Node Classification on random seed  346 -> 0.616
-Confusion Matrix:
- [[ 72   4   1   4   6  18   9]
- [  2 138   4   0   9   2   2]
- [ 39  17 135  24  19  23  46]
- [ 13   7  15 102   1  12  17]
- [  0   6   3   4  49   0   4]
- [  9   2   4   1   0  49   0]
- [ 16   7   1  10   7  16  71]]
-Node Classification on random seed  347 -> 0.619
-Confusion Matrix:
- [[ 63   2   8   9   3  20   8]
- [  2 128   6   6   5   6   3]
- [ 10  29 152  26  19  33  30]
- [ 18   2  12  86   9   9  17]
- [  0   2   4   1  63   0   3]
- [  5   2   2   0   1  41  15]
- [ 16   3   7   9   8  11  86]]
-Node Classification on random seed  348 -> 0.577
-Confusion Matrix:
- [[ 62   2   5   3   3   9  19]
- [  8 129   1   3   9   4   1]
- [ 36  28 109  51  23  25  45]
- [ 13   5   5  98   5   6  32]
- [  1   5   3   1  66   2   1]
- [  8   1   0   1   0  37   5]
- [ 11   2  12   5  12  12  76]]
-Node Classification on random seed  349 -> 0.622
-Confusion Matrix:
- [[ 62   2   2   6   5  11  10]
- [  3 121   4   6  10   1   7]
- [ 32  17 139  50  31  23  29]
- [ 14   1   9 104   6   6  10]
- [  1   3   7   1  76   1   1]
- [  4   1   0   6   1  45   3]
- [ 17   1   8  10   8  10  75]]
-Node Classification on random seed  350 -> 0.612
-Confusion Matrix:
- [[ 75   1   6   4   6   3  11]
- [  6 134   9   1   2   2   4]
- [ 19  26 138  20  42   7  51]
- [ 15   4  17  93   3   6  26]
- [  1  11   2   3  51   3   2]
- [  3   7   7   0   0  42   5]
- [ 12   4  12   4  10  11  79]]
-Node Classification on random seed  351 -> 0.604
-Confusion Matrix:
- [[ 70   3   9   4   1   7   7]
- [  6 129   6   6   6   5   1]
- [ 34  29 139  40  24  28  28]
- [ 13   5  13  94   1   6  18]
- [  1   8   2   4  65   0   2]
- [  4   2   1   6   0  44   7]
- [  6   5  12  10   9  17  63]]
-Node Classification on random seed  352 -> 0.628
-Confusion Matrix:
- [[ 64   4   2   4   5   9   6]
- [  4 108   5   3  17   0   2]
- [ 19  19 155  27  37  11  41]
- [ 14   6  15 112   4   5  20]
- [  2   3   3   1  60   1   4]
- [  6   1   2   4   1  38  10]
- [ 16   0   9  10   7  13  91]]
-Node Classification on random seed  353 -> 0.61
-Confusion Matrix:
- [[ 85   1   6   5   4   7   8]
- [  6 111   6   3   6   2   3]
- [ 30  18 139  35  30  30  39]
- [ 19   4  12 106   3   1   7]
- [  0   6   3   2  69   2   2]
- [  6   0   6   2   1  40   9]
- [ 15   3  12  10   7  19  60]]
-Node Classification on random seed  354 -> 0.628
-Confusion Matrix:
- [[ 66   1   7   4   4  15  14]
- [  6 128  11   4   4   2  11]
- [ 12  22 174  29  22  19  42]
- [ 11   4  11  99   4  14  16]
- [  0   7   3   0  63   0   1]
- [  4   1   6   3   0  40   7]
- [  5   5  12   4   5  20  58]]
-Node Classification on random seed  355 -> 0.606
-Confusion Matrix:
- [[ 65   3   0   8   4  25   8]
- [  8 141   2   4   4   1   7]
- [ 30  37 116  34  14  26  46]
- [  9   9  18 107   5   1  12]
- [  2  11   4   0  51   1   2]
- [  6   2   1   0   0  44   3]
- [ 11   3   2  10   5  16  82]]
-Node Classification on random seed  356 -> 0.564
-Confusion Matrix:
- [[ 70   1   2   6   2   6  15]
- [  6 121   3   2  13   4   1]
- [ 30  16 111  45  36  22  45]
- [ 13  10  13  89  12   9  15]
- [  4  11   6   3  59   0   0]
- [  6   2   2   3   2  46   7]
- [ 20   3   9   6  12  13  68]]
-Node Classification on random seed  357 -> 0.645
-Confusion Matrix:
- [[ 74   2   4   3   2  16  10]
- [  2 127   5   4   8   2   0]
- [ 18  28 134  46  28  20  37]
- [  5   7   5 113   5   8  13]
- [  0   6   6   1  65   2   3]
- [  7   3   1   3   0  41   4]
- [  5   1   5   6   7  17  91]]
-Node Classification on random seed  358 -> 0.589
-Confusion Matrix:
- [[ 74   1   8   7   1  13  12]
- [ 12 107   6   8   4   1   5]
- [ 25  16 126  37  41  25  38]
- [  4   5  17  96  11  10  11]
- [  1   2   6   2  63   0   2]
- [  7   1   2   4   1  46   4]
- [  9   5   4  12   9  22  77]]
-Node Classification on random seed  359 -> 0.636
-Confusion Matrix:
- [[ 78   6   2   5   3   8   5]
- [  3 146   4   4   2   0   4]
- [ 21  28 133  47  17  20  26]
- [  9   3  19 103   4  12   9]
- [  1  14   3   0  56   1   1]
- [  4   3   1   1   0  48   3]
- [ 16   8  10   7   7  23  72]]
-Node Classification on random seed  360 -> 0.63
-Confusion Matrix:
- [[ 47   2   7   6   4  13  19]
- [  3 131   7   2  17   1   5]
- [ 25  10 136  27  30  11  62]
- [  6   3  15 114   8   4  13]
- [  0   8   3   3  70   0   2]
- [  5   3   2   0   0  52   2]
- [ 10   7   6   8   4   7  80]]
-Node Classification on random seed  361 -> 0.566
-Confusion Matrix:
- [[ 66   1   9   2   1  11  15]
- [  6 143   4   1   4   2   5]
- [ 27  36 113  44  33  20  40]
- [  9   5  19  82   2   8  12]
- [  2  11   4   3  57   0   3]
- [  8   2   2   0   1  42  18]
- [ 17   4  18   5   6  14  63]]
-Node Classification on random seed  362 -> 0.624
-Confusion Matrix:
- [[ 74   5   4   7   2  13  10]
- [  5 127   2  10   7   2   6]
- [ 14  17 138  62  25  11  37]
- [ 12   2  13 114   7   5  17]
- [  0   4   1   1  60   1   6]
- [  4   2   4   4   0  44   3]
- [  5   4   5  10   8  19  67]]
-Node Classification on random seed  363 -> 0.585
-Confusion Matrix:
- [[ 60   7   4   8   6  14  18]
- [  7 121   8   1   6   0   7]
- [ 11  47 122  32  29  25  48]
- [ 10   7  11  97   6   7  15]
- [  2   8   4   3  52   0   1]
- [  4   0   2   1   2  57   8]
- [  5   4   3  14   7  13  76]]
-Node Classification on random seed  364 -> 0.625
-Confusion Matrix:
- [[ 63   3   2   6  10  11  13]
- [ 11 114  13   1  12   2   4]
- [ 19  16 151  22  36  15  56]
- [ 13   5  16 105   4   8   6]
- [  1   4   2   2  65   1   1]
- [  2   3   3   1   0  50   6]
- [  7   3   6   7   8  14  77]]
-Node Classification on random seed  365 -> 0.62
-Confusion Matrix:
- [[ 63   4  11   5   4  18   3]
- [  4 152   9   1   2   5   5]
- [ 25  23 132  26  34  24  33]
- [ 10   1  12 111  10   9   7]
- [  1   4   2   0  54   1   1]
- [  2   2   2   1   3  49  14]
- [ 13   1  12   8   6  22  59]]
-Node Classification on random seed  366 -> 0.647
-Confusion Matrix:
- [[ 68   2   5   3  10   9  14]
- [  3 130   4   0   1   1   3]
- [ 27  17 132  54  19  19  35]
- [  9   0  14 119   5   8  13]
- [  0  10   3   0  70   1   1]
- [ 11   1   1   1   0  43   3]
- [ 13   4   6   6   2  15  85]]
-Node Classification on random seed  367 -> 0.601
-Confusion Matrix:
- [[ 67   0   1   2   7   6   8]
- [  9 105  12   1   8   6   9]
- [ 39  10 139  38  34  22  28]
- [ 15   4  18  89   5  25   8]
- [  1   1   6   3  71   0   2]
- [  8   0   0   2   2  47   6]
- [ 14   4   9   8   7  11  83]]
-Node Classification on random seed  368 -> 0.597
-Confusion Matrix:
- [[ 61   1   2   2  10  15  19]
- [  7 118   5   0  14   1   0]
- [ 32  22 130  36  26  22  40]
- [  4   3  17  97  11  14  21]
- [  1   8   1   3  53   2   1]
- [  1   1   3   1   2  54   4]
- [  9   4   9   0   9  20  84]]
-Node Classification on random seed  369 -> 0.619
-Confusion Matrix:
- [[ 77   3   1   6   2   9  10]
- [  3 106   3   3  16   3   2]
- [  9  20 166  32  29  16  45]
- [  5   7  19  99  16   5  14]
- [  0   5   7   4  59   3   3]
- [  6   0   0   3   0  54   3]
- [ 17   4  14  11  11  12  58]]
-Node Classification on random seed  370 -> 0.625
-Confusion Matrix:
- [[ 79   4  12   2   3   9   7]
- [ 13 118   4   0   3   3   5]
- [ 33  31 130  18  17  15  45]
- [ 16   4  11 123   4   1  17]
- [  3   8   3   0  57   0   3]
- [  5   3   1   0   1  36   8]
- [ 19   4  20   5   3  12  82]]
-Node Classification on random seed  371 -> 0.648
-Confusion Matrix:
- [[ 73   5  12   2   2  11   4]
- [  1 143   1   3   1   4   3]
- [ 32  25 138  30  26  18  36]
- [ 11   5  18 100   5   4  13]
- [  4   4   2   0  68   7   3]
- [  4   1   3   1   0  55   1]
- [ 12   3  14   2   3  16  71]]
-Node Classification on random seed  372 -> 0.569
-Confusion Matrix:
- [[ 71   2   5   4   3  20   6]
- [  4 126   2   2  10   4   2]
- [ 35  20 124  44  20  36  37]
- [ 26   9  11  80   5  14  20]
- [  2   4   5   2  50   1   2]
- [  7   1   1   0   2  45  13]
- [ 11   4  11   7   3  14  73]]
-Node Classification on random seed  373 -> 0.585
-Confusion Matrix:
- [[ 57   2   3   7   4  24  10]
- [  0 121  14   5  13   1   4]
- [ 37  12 125  38  34  17  40]
- [ 14   4  17 107   0  15  13]
- [  1   2   4   0  56   1   4]
- [  4   2   0   1   0  44   7]
- [ 12   1  10  14   8  16  75]]
-Node Classification on random seed  374 -> 0.6
-Confusion Matrix:
- [[ 62   2   9  13   6  10  10]
- [  1 121   8   4  10   1   4]
- [ 19  12 122  23  66  22  39]
- [ 14  10  15  85   4  13  24]
- [  1   3   3   0  64   1   2]
- [  3   1   2   2   0  43   6]
- [  9   4   6   5   4   9 103]]
-Node Classification on random seed  375 -> 0.611
-Confusion Matrix:
- [[ 74   1   4   1   6  14  15]
- [  0 123   6   1  11   1   1]
- [ 21  27 141  51  16  20  26]
- [ 21   5  14  94  12   6  17]
- [  1   7   3   2  55   1   1]
- [  0   3   3   2   1  51   7]
- [ 14   6  13  11   6  11  73]]
-Node Classification on random seed  376 -> 0.613
-Confusion Matrix:
- [[ 85   2   4   2   8   6   8]
- [  9 118   6   3  11   7   3]
- [ 20  29 122  37  39  12  49]
- [ 12   9  16  94   3   3  12]
- [  1   6   3   2  57   0   3]
- [  3   0   2   4   0  56   6]
- [ 10   3  13   3   9   9  81]]
-Node Classification on random seed  377 -> 0.619
-Confusion Matrix:
- [[ 78   3   6   5   3   7  11]
- [  4 115  12   3  11   0   7]
- [ 29  13 146  19  22  10  47]
- [ 24   3  31  87   3   6  10]
- [  5   7   3   3  68   1   7]
- [  3   1   2   1   2  50   5]
- [ 18   3   5   5   7  14  75]]
-Node Classification on random seed  378 -> 0.633
-Confusion Matrix:
- [[ 52   7   3   5   9   8  14]
- [  4 140   3   2  12   3   6]
- [ 24  26 154  28  21  30  18]
- [ 25   9  15 109   2   3   8]
- [  2   8   4   2  62   2   1]
- [  4   2   0   4   0  42   2]
- [  9   4  10   5   2  21  74]]
-Node Classification on random seed  379 -> 0.625
-Confusion Matrix:
- [[ 69   3   4   5   2   6  10]
- [  9 116  13   1   2   8   9]
- [ 29  25 154  33  18  23  37]
- [  7   3  11 110   5   2  16]
- [  1   8   5   0  56   1   4]
- [ 14   0   0   1   1  45   9]
- [ 15   4   7   5   6  13  75]]
-Node Classification on random seed  380 -> 0.569
-Confusion Matrix:
- [[ 65   4   3   8   8  19   3]
- [  7 125   3   8  12   1   1]
- [ 34  27  99  39  30  29  45]
- [ 16   2  16 106   6  11  12]
- [  3   3   1   0  55   1   2]
- [  3   1   2   4   2  56   4]
- [ 13   2  16   7   2  21  63]]
-Node Classification on random seed  381 -> 0.625
-Confusion Matrix:
- [[ 65   5   6   4   2  11  12]
- [  2 131   6   1   5   7   1]
- [ 22  12 149  31  30  23  52]
- [ 18   4  19 100   2   7   9]
- [  4   7   8   1  55   0   2]
- [  4   0   5   0   0  52   4]
- [ 14   2   7   4   7  15  73]]
-Node Classification on random seed  382 -> 0.608
-Confusion Matrix:
- [[ 68   7   2   5   4   9  13]
- [  7 118   7   3   1   0   1]
- [ 27  15 150  48  23  20  34]
- [ 19   3  23 106   3   6   6]
- [  1   7   5   7  42   2   3]
- [  3   1   4   0   0  45   8]
- [ 20   6  11   8   5  15  79]]
-Node Classification on random seed  383 -> 0.62
-Confusion Matrix:
- [[ 58   4   1   9   3   8  21]
- [  0 130   6   4  10  10   2]
- [ 21  11 156  27  30  24  49]
- [ 18   2  12 112   1   4  14]
- [  1   7   4   1  52   1   2]
- [  7   3   4   1   0  31  12]
- [  7   4   6   7   8  14  81]]
-Node Classification on random seed  384 -> 0.616
-Confusion Matrix:
- [[ 57   2  11   7   4  21   4]
- [  5 121   2   3   9   8   6]
- [ 18  25 129  49  34  22  34]
- [  8   6  16 122   6   5   5]
- [  1  14   0   0  58   0   2]
- [  0   3   2   2   1  46   5]
- [  8   2  11   6   3  14  83]]
-Node Classification on random seed  385 -> 0.643
-Confusion Matrix:
- [[ 72   2   5   3   4   9   2]
- [  2 122   8   2   9   5   3]
- [ 23  24 155  50  24  13  26]
- [ 11   4  19 104  17   5   9]
- [  3   4   2   2  75   2   1]
- [  1   0   3   1   1  52   3]
- [  8   8  12   6   6  15  63]]
-Node Classification on random seed  386 -> 0.627
-Confusion Matrix:
- [[ 75   1   2  10   3  12   6]
- [  3 125   7   4   5   5   6]
- [ 18  12 149  36  52  29  20]
- [  8   2  24 116   2  11   6]
- [  0   4   4   6  50   0   5]
- [  7   4   1   1   0  37   5]
- [  5   2   7   5   9  24  75]]
-Node Classification on random seed  387 -> 0.6
-Confusion Matrix:
- [[ 62   2  12   3   5  14   4]
- [  0 129  12   2  11   2   4]
- [ 34  27 117  59  21   4  43]
- [  9   4   7 129   2   4   8]
- [  0   4   2   1  61   0   1]
- [  6   1   8   1   5  46   1]
- [ 13   4  14  15  13  18  56]]
-Node Classification on random seed  388 -> 0.631
-Confusion Matrix:
- [[ 66   6   3   6  15   5   1]
- [  2 147   8   0   8   8   3]
- [ 30  28 143  28  19  19  42]
- [ 13   5  12  98   9   4  10]
- [  0  11   3   2  57   0   1]
- [  0   2   1   3   2  43   7]
- [ 14   9   3   7   9  11  77]]
-Node Classification on random seed  389 -> 0.625
-Confusion Matrix:
- [[ 70   1  10   7   2   5   8]
- [  9 127   0   5  13   0   5]
- [ 35  16 145  33  25  26  39]
- [  5   2  25 110   4   3  11]
- [  1   5   4   1  54   1   3]
- [  9   1   1   1   0  44   2]
- [ 21   9   2   6   3  16  75]]
-Node Classification on random seed  390 -> 0.634
-Confusion Matrix:
- [[ 80   4   2   3   1   6  13]
- [ 10 120  10   4   7   3   7]
- [ 21  21 166  28  21  22  44]
- [ 17   2  17  93   3   7   8]
- [  2   3   1   3  71   1   3]
- [  9   0   3   1   0  37   5]
- [ 15   3   4  13   8  11  67]]
-Node Classification on random seed  391 -> 0.637
-Confusion Matrix:
- [[ 75   9   5   9   6   8   6]
- [  4 120   7   5   6   1  11]
- [ 22  22 141  24  41  11  47]
- [ 10   1  18 103   4   3  11]
- [  1   2   6   4  66   0   2]
- [  4   2   0   1   1  56   3]
- [ 11   5   6   2   7  15  76]]
-Node Classification on random seed  392 -> 0.625
-Confusion Matrix:
- [[ 73   3   9   1   5  10   9]
- [  4 114   9   2  15   5   1]
- [ 16  32 167  44  15  10  43]
- [  6   9  16  95   4   3  11]
- [  3   4   8   0  64   2   1]
- [  4   2   2   2   2  38   7]
- [  9   6   9   7   6  19  74]]
-Node Classification on random seed  393 -> 0.63
-Confusion Matrix:
- [[ 83   5   2   8   7  12   3]
- [  3 110   8   4  14   5   6]
- [ 21  25 136  49  18  23  29]
- [  3   3  12 116   9   8  24]
- [  1   1   4   2  70   0   4]
- [  7   0   3   1   0  42   4]
- [ 17   2   3   2   2  16  73]]
-Node Classification on random seed  394 -> 0.644
-Confusion Matrix:
- [[ 72   1   9   7   5  14   8]
- [  5 128   5   5   7   0   3]
- [ 24  12 128  43  23  16  34]
- [ 10   3   8 113   3   4  13]
- [  2   7   3   4  71   2   3]
- [  7   0   2   1   2  47   5]
- [ 11   1   7  11  10  16  85]]
-Node Classification on random seed  395 -> 0.626
-Confusion Matrix:
- [[ 62   0  10   5   4  13  13]
- [  1 121   7   2   9   2   6]
- [ 15  14 158  40  23  32  36]
- [  4   1  18 109   4   7  15]
- [  1   8   9   2  58   1   3]
- [  8   3   0   4   2  42   4]
- [  8   7  12   4   5  12  76]]
-Node Classification on random seed  396 -> 0.636
-Confusion Matrix:
- [[ 82   3   4   5   1  12   7]
- [  7 143   8   2   4   1   2]
- [ 20  21 127  33  38  23  41]
- [ 10   0  11 103   6   2  12]
- [  1  11   4   3  64   1   2]
- [  5   1   1   0   1  46   3]
- [ 17   3   8   9  11  10  71]]
-Node Classification on random seed  397 -> 0.576
-Confusion Matrix:
- [[ 66   2  11   7   3  12  10]
- [  3 122   7   3   6   7   7]
- [ 22  33 112  43  42  11  40]
- [  8   2  14 118   5  13  13]
- [  0   8   3   0  70   0   1]
- [  2   3   0   3   1  42   3]
- [  6   3  11   9  16  31  46]]
-Node Classification on random seed  398 -> 0.556
-Confusion Matrix:
- [[ 64   1   0   5   5   8  10]
- [  1 119   5   0  26   0   0]
- [ 29  13 125  50  33  32  44]
- [ 11   4  24  97  13  13   9]
- [  2   0   8   1  60   0   3]
- [  6   1   2   1   4  34  11]
- [ 13   2   9   9  17  19  57]]
-Node Classification on random seed  399 -> 0.622
-Confusion Matrix:
- [[ 75  14   4   0   2  12  20]
- [  2 126   4  15   3   2   6]
- [ 14  26 126  35  30   8  52]
- [ 11   7   9  98  12   5  16]
- [  0   8   1   1  60   1   1]
- [  5   4   2   0   1  37  11]
- [  8   6   3   2  13   2 100]]
-Node Classification on random seed  400 -> 0.609
-Confusion Matrix:
- [[ 65   2   4   3   5   6  25]
- [  3 130  13   0  10   3   1]
- [ 22  20 134  36  61  11  37]
- [  7   6   9 102  13   3  12]
- [  1   7   3   0  59   0   1]
- [  8   0   4   1   1  39   6]
- [  3   5   5   6  17  11  80]]
-Node Classification on random seed  401 -> 0.62
-Confusion Matrix:
- [[ 45   1  14   9  10  20   3]
- [ 14 120   5   2   2   3   5]
- [ 22  29 159  38  25  15  33]
- [ 10   3  14 112   9   3  13]
- [  4   7   2   2  69   0   1]
- [  0   2   1   1   2  48  11]
- [  9   3  12   2   6  13  67]]
-Node Classification on random seed  402 -> 0.623
-Confusion Matrix:
- [[ 65   2   7  11   5   5   3]
- [  2 133   9   7   6   3   3]
- [ 17  22 145  25  31  21  56]
- [  7   3  13 110  10   5  16]
- [  1   6   2   5  52   0   3]
- [  8   0   6   3   0  40   7]
- [  9   1   4  10   9  14  78]]
-Node Classification on random seed  403 -> 0.614
-Confusion Matrix:
- [[ 69   0   3   3   2  18  23]
- [  4 121   4   3   4   3   5]
- [ 17  21 141  25  53  35  31]
- [  5   1  15 103   8   4  14]
- [  2   8   3   3  58   2   0]
- [  6   1   2   4   1  53   2]
- [ 14   5   8   3   5  16  69]]
-Node Classification on random seed  404 -> 0.607
-Confusion Matrix:
- [[ 62   0  15   8   0  11   7]
- [  6 125   5   2   2   0   7]
- [ 31  17 138  49  30  24  34]
- [ 13   7  11  99   7   1   8]
- [  2   5   5   4  54   2   3]
- [  4   0   1   0   0  49   8]
- [  8   4  14  12  11  15  80]]
-Node Classification on random seed  405 -> 0.641
-Confusion Matrix:
- [[ 73   4   3   8   4   9  10]
- [  9 122   4   2   7   4   5]
- [ 28   9 174  39  20  12  40]
- [  6   5  13  92   4   1  19]
- [  2  10   5   2  60   0   3]
- [  8   2   5   0   1  39   8]
- [ 14   3  16   6   4   5  81]]
-Node Classification on random seed  406 -> 0.602
-Confusion Matrix:
- [[ 68   2   5   4   5  12   3]
- [  4 122   8   1   1   0   3]
- [ 33  23 132  36  28  18  55]
- [ 15   1  15  96   5   7  26]
- [  2  13   2   2  62   1   1]
- [  4   1   4   3   4  42   3]
- [  5   2  15   4   8  14  80]]
-Node Classification on random seed  407 -> 0.604
-Confusion Matrix:
- [[ 78   5   6   5   1   8  10]
- [  4 120   9   3  13   4   4]
- [ 37  21 128  41  42  21  30]
- [ 12   6   8 110   5   4   9]
- [  0   9   3   1  52   1   4]
- [  3   1   2   2   2  41   3]
- [ 14   2   5   7  11  18  75]]
-Node Classification on random seed  408 -> 0.619
-Confusion Matrix:
- [[ 72   3   2   1   1  17  11]
- [  6 129  12   0   4   0   0]
- [ 18  29 143  32  27  26  40]
- [  7  10  16  86   4   8  13]
- [  4   9   4   5  59   0   0]
- [  1   0   3   1   1  47  15]
- [  6   4  13  10   4  14  83]]
-Node Classification on random seed  409 -> 0.595
-Confusion Matrix:
- [[ 70   2   5   3   2  16  10]
- [  5 119   6   1  13   0   2]
- [ 16  18 139  33  34  37  44]
- [ 19   4  16  80   4  10  15]
- [  3   6   5   0  63   3   4]
- [ 10   2   0   1   2  41   3]
- [ 18   4   8   3   6  12  83]]
-Node Classification on random seed  410 -> 0.586
-Confusion Matrix:
- [[ 60   2   3   5  11   5   5]
- [  1 125   4   7   4   7   1]
- [ 32  27 140  41  30  24  32]
- [ 19   3  15 105   9   2   6]
- [  1   6   6   4  43   1   3]
- [ 13   2   3   4   0  47  10]
- [ 27   5  15   8   3   8  66]]
-Node Classification on random seed  411 -> 0.657
-Confusion Matrix:
- [[ 66   1   6   5   4  10   7]
- [  8 129   7   2   7   2   6]
- [ 19  17 160  36  23  14  40]
- [  7   2  14  88   3   1  21]
- [  2   6   0   2  68   0   3]
- [  5   3   4   2   1  47   5]
- [ 12   3   5   9   5  14  99]]
-Node Classification on random seed  412 -> 0.613
-Confusion Matrix:
- [[ 72   2   3   2   0  15   6]
- [  4 120   7   5  11   3   1]
- [ 17  27 141  43  20  30  52]
- [ 21   0  13 103   6   3  12]
- [  4   1   3   1  61   1   4]
- [  5   2   2   3   1  36   7]
- [ 19   3   9   4   4  11  80]]
-Node Classification on random seed  413 -> 0.634
-Confusion Matrix:
- [[ 72   2   4   4   3   7  13]
- [  4 123   6   2   2   1   1]
- [ 19  24 156  34  21  26  43]
- [ 15   9  12 102   1  11  14]
- [  1   3   6   2  54   1   2]
- [  6   3   2   2   3  49   8]
- [  9   2   9   5   7  17  78]]
-Node Classification on random seed  414 -> 0.628
-Confusion Matrix:
- [[ 70   6   1   7   2   5   2]
- [  0 114   3   5   9   4   2]
- [ 21  21 157  45  16  20  49]
- [ 18   8  14 106   6   3  10]
- [  1  10   5   0  67   1   0]
- [ 13   6   0   0   3  47   3]
- [ 13   3   9   7   7  14  67]]
-Node Classification on random seed  415 -> 0.625
-Confusion Matrix:
- [[ 67   2   3   1   5  13  12]
- [  3 135   6   2  15   3   3]
- [ 27  19 118  38  19  26  43]
- [ 12   2  19 100   2   7  11]
- [  1   2   2   2  65   1   2]
- [  3   3   1   4   0  53   3]
- [ 13   4  11   4   4  22  87]]
-Node Classification on random seed  416 -> 0.604
-Confusion Matrix:
- [[ 59   6   6   5   2  11  17]
- [  5 144   5   3   6   1   2]
- [ 23  29 134  26  40  24  45]
- [ 10  10  16 104   4   6  10]
- [  0   5   2   2  64   0   5]
- [  5   6   1   0   0  39   6]
- [ 15   2  12   8   9   6  60]]
-Node Classification on random seed  417 -> 0.625
-Confusion Matrix:
- [[ 72   8   4   5   3  13  12]
- [  3 133   8   0   3   2   6]
- [ 26  28 163  23  29  14  31]
- [ 10   4  15  91  15   3  16]
- [  0  13   2   1  62   2   1]
- [  1   3   0   3   0  44   5]
- [ 15   6  12   4   5  21  60]]
-Node Classification on random seed  418 -> 0.566
-Confusion Matrix:
- [[ 65   3   5   3   7  14  12]
- [  8 113   2   5   6   3   5]
- [ 10  26 119  41  31  15  51]
- [ 17   8  17  95   3   8  25]
- [  1  11   0   1  67   0   1]
- [  4   4   2   5   1  49   1]
- [ 12   9  15  15  12  15  58]]
-Node Classification on random seed  419 -> 0.592
-Confusion Matrix:
- [[ 76   0   7   4   9  10  10]
- [  4 100   9   5  18   0   1]
- [ 28  10 126  51  54  33  23]
- [  6   2  14 107   2   3  19]
- [  4   3   2   0  68   1   2]
- [  6   1   1   5   1  37   4]
- [ 15   1  10   7  11  12  78]]
-Node Classification on random seed  420 -> 0.621
-Confusion Matrix:
- [[ 60   2   8  13   6   5  19]
- [  2 130   7   1   6   2   4]
- [ 11  11 138  29  42  20  49]
- [ 12   4  16  93   8  13   8]
- [  0   8   1   2  67   0   1]
- [ 11   2   1   0   0  38   5]
- [ 12   2  15   8   4   9  95]]
-Node Classification on random seed  421 -> 0.624
-Confusion Matrix:
- [[ 85   1   1  18   1   5   4]
- [  5 129   6   1   7   2   5]
- [ 31  38 142  38  22  17  33]
- [  6   4  10 105   5   9  12]
- [  3   4   2   1  56   0   2]
- [  9   1   1   3   0  41   6]
- [ 19   0  16  14   6   8  66]]
-Node Classification on random seed  422 -> 0.6
-Confusion Matrix:
- [[ 81   0   6   8   1   8   6]
- [  4 117   3  11   4   4   3]
- [ 24  19 133  37  25  28  41]
- [ 12   1   8 115   5   6  13]
- [  2   5   6   2  59   2  12]
- [ 13   1   2   7   2  33   7]
- [  6   5   7  16   9  19  62]]
-Node Classification on random seed  423 -> 0.57
-Confusion Matrix:
- [[ 56   1  12   6  10  17  12]
- [  8 112   5   3   3   5   6]
- [ 30  16 130  24  32  17  52]
- [ 20   4  26  71   2  11  19]
- [  1   5   1   1  65   1   2]
- [  3   0   5   0   3  53   4]
- [ 14   6  10   7   5  21  83]]
-Node Classification on random seed  424 -> 0.593
-Confusion Matrix:
- [[ 65   2  11   6   2   9  23]
- [  5 123   3   3  11  10   4]
- [ 20  16 139  28  37  24  46]
- [ 11   3  22  99   4   6  11]
- [  4   4   4   3  51   1   0]
- [  9   1   3   1   0  42   4]
- [ 10   3  13   8   9  13  74]]
-Node Classification on random seed  425 -> 0.602
-Confusion Matrix:
- [[ 73   6   5   1   0  15   3]
- [  3 145   1   2   6   4   0]
- [ 14  28 104  82  22  28  38]
- [ 13   5  10 106  14  11   4]
- [  0   4   4   2  59   2   1]
- [  2   2   2   3   2  35  12]
- [  9   3   3  11   6  15  80]]
-Node Classification on random seed  426 -> 0.622
-Confusion Matrix:
- [[ 66   0   4  12   6   6   6]
- [  2 116   8   5   4   5   4]
- [ 31  14 151  27  42  13  40]
- [  4   2  24 101  12   7  19]
- [  2   4   4   1  62   0   7]
- [  2   1   0   2   3  49   6]
- [  2   2   7   6  16  16  77]]
-Node Classification on random seed  427 -> 0.626
-Confusion Matrix:
- [[ 68   6   7   3   5   8   3]
- [ 10 128   5   4   6   1   2]
- [ 21  12 121  48  55  13  42]
- [  3   4  11 128   6   3   8]
- [  2   5   2   2  72   1   1]
- [ 11   2   2   3   1  36   4]
- [ 22   5   5   4   5  11  73]]
-Node Classification on random seed  428 -> 0.623
-Confusion Matrix:
- [[ 84   5   2   0   1   4  14]
- [  2 120   2   0   7   7   4]
- [ 23  23 142  29  22  32  40]
- [ 12   6  21  93   3   4  17]
- [  1   5   6   3  53   4   3]
- [  9   1   4   5   0  41   4]
- [ 18   7   7   1   6  13  90]]
-Node Classification on random seed  429 -> 0.605
-Confusion Matrix:
- [[ 70   0   2   9   9  12  12]
- [  4 146   4   3   4   1   4]
- [ 29  42 127  38  24  14  25]
- [ 28   8  21  73   8   3  14]
- [  0   4   2   2  68   0   2]
- [  7   0   2   0   2  39   6]
- [ 12   2   9   4   6  17  82]]
-Node Classification on random seed  430 -> 0.637
-Confusion Matrix:
- [[ 69   0   9   3   6  17   6]
- [  5 126   5   1   6   0   3]
- [ 18  11 142  42  36   9  42]
- [ 10   5  13 106   8   5   9]
- [  1   6   2   0  66   2   3]
- [  9   4   0   3   4  40   8]
- [ 14   3   7   9  11   8  88]]
-Node Classification on random seed  431 -> 0.632
-Confusion Matrix:
- [[ 70   8   0   1   4  21   8]
- [  5 123   4   0   6   4   5]
- [ 22  23 159  33  28  18  22]
- [ 17   2  17 103   5   7  19]
- [  2   4   5   0  67   1   2]
- [ 10   1   2   1   0  41   5]
- [ 14   7   9   4   4  18  69]]
-Node Classification on random seed  432 -> 0.6
-Confusion Matrix:
- [[ 68   5   5   7   3   7   7]
- [  8 128   2   5  10   3   8]
- [ 23  34 111  39  37  18  46]
- [ 10   6  11 104   5   5  12]
- [  0   3   2   4  59   0   3]
- [  6   0   4   3   0  54   4]
- [ 15   2   7   5   7  19  76]]
-Node Classification on random seed  433 -> 0.569
-Confusion Matrix:
- [[ 67   4   5   7   3  19   1]
- [  8 134   5   0   6   2   2]
- [ 42  18 128  32  35  19  47]
- [ 21   1  17  84   4   6  24]
- [  4   7   9   3  52   1   0]
- [  5   0   2   3   0  42   0]
- [ 27   3   9   5   8  17  62]]
-Node Classification on random seed  434 -> 0.625
-Confusion Matrix:
- [[ 65   2   2   4   7   3  23]
- [  5 125   6   2   8   2   4]
- [ 33  24 131  31  19  20  52]
- [  5   6   6 118   7   1  12]
- [  3   4   5   3  62   0   4]
- [  6   4   0   5   0  38   5]
- [ 14   1  10   4   9  14  86]]
-Node Classification on random seed  435 -> 0.612
-Confusion Matrix:
- [[ 63   3   3   7   8   4  15]
- [  2 129   4   5   4   2   0]
- [ 16  19 146  55  25  22  37]
- [ 16   3  24 103   3   4  13]
- [  1   9   2   4  53   1   6]
- [  3   1   1   7   6  41   6]
- [  8   5   8  13   2  11  77]]
-Node Classification on random seed  436 -> 0.63
-Confusion Matrix:
- [[ 88   0   4   8   1   9   4]
- [  2 125   4   2   3   4   5]
- [ 29  17 149  36  24  23  38]
- [ 14   3  20  77   7  14  14]
- [  0   8   6   2  68   0   3]
- [  3   1   2   2   2  44   6]
- [  5   8  14   6   4  13  79]]
-Node Classification on random seed  437 -> 0.633
-Confusion Matrix:
- [[ 76   1   2   3   3  14   6]
- [  7 119   5   1  18   3   4]
- [ 31  29 150  29  38  22  17]
- [ 15   0   8  98   7   2  10]
- [  1   0   3   0  71   0   2]
- [ 12   3   1   0   1  49   1]
- [ 14   2   8   7  11  26  70]]
-Node Classification on random seed  438 -> 0.591
-Confusion Matrix:
- [[ 66   1   8   6   4  14   7]
- [  7 130   3   4   0   4   6]
- [ 29  27 142  33   7  20  44]
- [ 19  11  16  83   5  12  10]
- [  0   8   6   5  49   3   3]
- [  7   2   2   9   0  52   4]
- [ 22   3   6  11   3  18  69]]
-Node Classification on random seed  439 -> 0.596
-Confusion Matrix:
- [[ 78   7   2   9   6  14   5]
- [  7 131   3   3   4   8   1]
- [ 22  27 129  30  31  27  53]
- [ 15   6  13  91   8  11  10]
- [  1   8   4   1  54   0   3]
- [ 10   0   5   3   2  41   4]
- [  9   5   6   9   4   8  72]]
-Node Classification on random seed  440 -> 0.62
-Confusion Matrix:
- [[ 70   0   4   7   2   7   9]
- [  2 120   8  11   7   3   4]
- [ 16  23 137  33  26  15  37]
- [ 12   5  34 100   4   7   9]
- [  1   7   2   0  65   2   3]
- [ 12   5   1   2   3  50   1]
- [ 18   4   3   8   5  18  78]]
-Node Classification on random seed  441 -> 0.598
-Confusion Matrix:
- [[ 72   2   4   5   4  10  10]
- [  5 141   3   2   3   2   1]
- [ 33  19 145  38  16  30  45]
- [ 16   2  22  91   3   6   4]
- [  3  13   5   1  50   0   3]
- [  8   0   5   1   0  48   3]
- [ 11   5  21  16   7  15  51]]
-Node Classification on random seed  442 -> 0.614
-Confusion Matrix:
- [[ 76   6   5   3   4   9  14]
- [  8 119   5   0  16   0   5]
- [ 38  20 136  30  36  24  25]
- [ 13   5  19 101   7   7  15]
- [  3   4   1   2  63   1   0]
- [  7   2   2   1   0  47   4]
- [ 14   5   6   2   8  10  72]]
-Node Classification on random seed  443 -> 0.641
-Confusion Matrix:
- [[ 57   2   2   5   9  10  10]
- [  7 133   5   3  11   0   5]
- [ 24  17 156  23  16  27  36]
- [ 15   4  16 106   5   3   7]
- [  2   9  10   4  59   1   2]
- [  9   2   0   3   2  38   4]
- [  8   3  13  10   7   8  92]]
-Node Classification on random seed  444 -> 0.6
-Confusion Matrix:
- [[ 81   2   5   6   4  11   4]
- [  4 121  10   2  16   3   7]
- [ 19  35 115  27  50  27  24]
- [  5   6  21  95   3   4  19]
- [  1   5   2   1  79   0   2]
- [  6   1   8   2   0  38   3]
- [ 11   1  19   5   9  10  71]]
-Node Classification on random seed  445 -> 0.61
-Confusion Matrix:
- [[ 60   5   0   5   2  11   8]
- [  4 135   6   2  12   7   1]
- [ 30  39 132  43  21   7  43]
- [ 11   7  29 102   4  11   5]
- [  4   1   6   0  56   0   3]
- [  7   0   4   2   2  46   4]
- [ 15   0   5   4   4  16  79]]
-Node Classification on random seed  446 -> 0.625
-Confusion Matrix:
- [[ 78   1   7   5   2  12  20]
- [  5 116   7   4   4   4   2]
- [ 36  11 137  36  32  22  43]
- [  6   5  21  96   1   5  13]
- [  2   6   2   2  69   1   5]
- [  6   0   3   2   0  46   3]
- [  6   1  11   9   5   7  83]]
-Node Classification on random seed  447 -> 0.639
-Confusion Matrix:
- [[ 63   0   1   3   9   9   7]
- [  4 127   4   6  12   1   7]
- [ 20  20 154  33  36  13  37]
- [ 10   6  23 108   5   2   5]
- [  2  10   4   1  62   0   0]
- [  4   2   2   0   3  48   5]
- [ 14   8   5   6  10  12  77]]
-Node Classification on random seed  448 -> 0.633
-Confusion Matrix:
- [[ 66   8   3   4   2  12   7]
- [  2 143   5   2   8   4   4]
- [ 21  23 151  25  19  12  47]
- [ 16   9  18  92   3   4  15]
- [  2   3   1   0  57   0   0]
- [ 16   1   4   1   2  50   2]
- [ 18   6   7  13   7  11  74]]
-Node Classification on random seed  449 -> 0.61
-Confusion Matrix:
- [[ 88   2   3   5   4   9   9]
- [  3 111  13   7  13  11   5]
- [ 20  16 130  19  33  26  45]
- [ 18   4   7  93   5  16   6]
- [  0   6   7   3  62   4   1]
- [  2   0   4   0   0  44   9]
- [ 16   3   7   8   6  15  82]]
-Node Classification on random seed  450 -> 0.629
-Confusion Matrix:
- [[ 72   3   2   3   6   7  18]
- [  8 122  12   3   8   3   5]
- [ 27  16 159  18  26  11  48]
- [ 30   3   9  82   8   3  16]
- [  2   1   7   3  62   0   3]
- [  5   1   1   3   0  47   8]
- [ 16   6   4   1   9   8  85]]
-Node Classification on random seed  451 -> 0.606
-Confusion Matrix:
- [[ 80   4   0   4   3   6  10]
- [  3 126   7   4   5   3   3]
- [ 28  24 152  32  18  24  43]
- [ 10   6  16  94  12   2  24]
- [  2   9   8   1  52   1   2]
- [  5   3   2   1   2  35   3]
- [ 16   3  11   8  19   7  67]]
-Node Classification on random seed  452 -> 0.563
-Confusion Matrix:
- [[ 73   1   3  14   7  11  10]
- [  6 118   3   3  12   4   6]
- [ 25  24  99  57  54  10  39]
- [ 14   4  14  93  11   7  13]
- [  0   3   1   0  65   0   2]
- [  9   1   0   2   1  34   5]
- [ 10   3   5  16   6  21  81]]
-Node Classification on random seed  453 -> 0.604
-Confusion Matrix:
- [[ 68  12   2  15   2   5  11]
- [  5 126   9   0   7   8   2]
- [ 21  25 121  43  20  36  46]
- [  9   3   9 111   4   7  15]
- [  3   4   4   1  57   1   2]
- [ 10   1   2   0   1  45   3]
- [ 15   2   8   6   7  10  76]]
-Node Classification on random seed  454 -> 0.631
-Confusion Matrix:
- [[ 78   2   1   3  10   7   8]
- [  7 130   5   3  12   6   3]
- [ 14  29 147  26  28  20  52]
- [ 13   5  29  93   2   6   9]
- [  0   6   5   1  64   2   3]
- [ 11   0   0   2   0  41   5]
- [  4   2   6   6   5  11  78]]
-Node Classification on random seed  455 -> 0.611
-Confusion Matrix:
- [[ 70   1   3   4   4   8   8]
- [  1 141   3   8   6   2   1]
- [ 20  22 128  24  29  30  56]
- [ 17   6  15  89   7  11  15]
- [  1   7   0   2  54   1   4]
- [  5   3   1   1   1  50   6]
- [  8   2   9  10   9  18  79]]
-Node Classification on random seed  456 -> 0.603
-Confusion Matrix:
- [[ 71   1  10   2   7   8   8]
- [  4 146   2   3   4   1   5]
- [ 26  12  99  31  33  27  63]
- [  8   0  24  89   6  12  18]
- [  0   9   1   0  59   2   5]
- [  8   0   3   1   2  51   6]
- [ 15   1   4   7   8  10  88]]
-Node Classification on random seed  457 -> 0.607
-Confusion Matrix:
- [[ 75   0   6   3   6  10   8]
- [  8 124  10   1   6   0   2]
- [ 17  27 138  39  26  22  37]
- [ 10   9   9 112  11   6  11]
- [  4   8   8   0  57   0   2]
- [  7   1   0   2   0  37   6]
- [ 17  12   6   8   8  20  64]]
-Node Classification on random seed  458 -> 0.596
-Confusion Matrix:
- [[ 86   4   1   6   2   4  13]
- [  0 129   6   5   8   1   4]
- [ 35  13  98  69  40  20  35]
- [ 15   8  11 100  13   3   4]
- [  0   2   3   2  57   2   1]
- [ 13   2   1   0   0  51   7]
- [ 17   1   9  12   5   7  75]]
-Node Classification on random seed  459 -> 0.596
-Confusion Matrix:
- [[ 76   1  11   6   2   6  12]
- [  4 131   7   3   3   0  10]
- [ 23  20 143  31  40  19  25]
- [  9   7  39  73  10   8  15]
- [  0   7   2   2  67   0   4]
- [  5   1   3   1   0  47   8]
- [  7   6  16   5   7  19  59]]
-Node Classification on random seed  460 -> 0.623
-Confusion Matrix:
- [[ 67   2   8   5   1  10  14]
- [  3 131   1   7   3   6   5]
- [ 27  21 131  29  35  15  48]
- [ 12   0  14 115  11   6  10]
- [  4   9   0   0  60   1   2]
- [  4   1   2   0   0  50   0]
- [ 15   2  11   5   7  21  69]]
-Node Classification on random seed  461 -> 0.61
-Confusion Matrix:
- [[ 52   5   2   8   5   8  22]
- [  3 129   9   0   9   5   2]
- [ 27  27 138  29  25  12  32]
- [ 13   5  35  94   4   7  10]
- [  1   9   6   4  65   0   1]
- [  5   1   5   1   0  54   5]
- [  8   1  11   7   8  13  78]]
-Node Classification on random seed  462 -> 0.635
-Confusion Matrix:
- [[ 83   4   1   8   2   7   9]
- [  4 132   4   8   4   0   6]
- [ 20  20 151  27  34  14  39]
- [ 24   3  16  85   5   4  16]
- [  2   4   4   2  58   1   3]
- [  3   7   1   3   0  43   4]
- [ 10   3  13   5   3  18  83]]
-Node Classification on random seed  463 -> 0.633
-Confusion Matrix:
- [[ 87   2   1   5   1   9  11]
- [  5 127   2   8   1   4   7]
- [ 27  14 148  41  25  20  34]
- [ 17   2   5  90   9  11  14]
- [  2   4   2   0  60   1   6]
- [  9   5   1   0   2  47   6]
- [ 17   5   9   4   3  16  74]]
-Node Classification on random seed  464 -> 0.645
-Confusion Matrix:
- [[ 73   1   2   3   1   7  12]
- [  2 134   4   2   6   2  11]
- [ 26  24 153  17  32  25  43]
- [ 11   4  17  93   1   4  25]
- [  1   7   3   2  59   1   2]
- [  1   2   1   2   1  50   3]
- [  9   3   3   4  12  16  83]]
-Node Classification on random seed  465 -> 0.59
-Confusion Matrix:
- [[ 78   5   7   3   4   5  11]
- [  6 125  15   0   7   5   5]
- [ 27  21 127  44  21  16  50]
- [ 14   9  13  83   7   5  17]
- [  2   1   7   1  61   1   2]
- [  9   1   1   1   3  33  13]
- [ 16   8   9   3   4  11  83]]
-Node Classification on random seed  466 -> 0.624
-Confusion Matrix:
- [[ 73   1   6   4   5  16   9]
- [  6 124   2   2  14   0   1]
- [ 25  14 138  45  31  21  46]
- [  9   3  14 111   9   7   7]
- [  1   5   5   1  58   2   3]
- [  8   4   2   0   3  46   5]
- [ 14   3   4   4   6   9  74]]
-Node Classification on random seed  467 -> 0.614
-Confusion Matrix:
- [[ 71   0   4   3  10   6  20]
- [  3 112   3   5  18   5   3]
- [ 34  20 135  34  24  17  48]
- [  5   2  13 107   8  11  19]
- [  0   6   4   1  59   0   0]
- [ 11   2   1   0   0  47   3]
- [ 13   3   3   1   6  17  83]]
-Node Classification on random seed  468 -> 0.667
-Confusion Matrix:
- [[ 66   6   2   4   4   3   3]
- [  3 146   2   1   8   6   1]
- [ 33  23 149  31  28  15  39]
- [ 10   5  10 120   3   8   5]
- [  1   5   2   3  62   1   1]
- [  6   0   1   5   0  48   2]
- [ 11   1   4   7   9  21  76]]
-Node Classification on random seed  469 -> 0.629
-Confusion Matrix:
- [[ 61   3   7   3   5  16  14]
- [  5 116   7   5  15   2   0]
- [ 18  17 150  55  19  19  40]
- [  6   2  18 107   3   6  14]
- [  0   9   7   2  60   3   1]
- [  2   1   3   1   0  44   4]
- [  2   6   7   8   2  14  91]]
-Node Classification on random seed  470 -> 0.6
-Confusion Matrix:
- [[ 63   1   5  14   4   9  17]
- [ 10 111   6   0  11   1   2]
- [ 33  30 147  37  32   8  33]
- [ 15   6  16 105   7   2   6]
- [  4   3   3   1  61   0   0]
- [  7   1   2   3   0  47   4]
- [ 18   2  11  14  12  10  66]]
-Node Classification on random seed  471 -> 0.625
-Confusion Matrix:
- [[ 69   2   7   9   4   2   8]
- [ 12 107  10   2   8   0   1]
- [ 28  12 146  41  44  18  34]
- [ 11   4  15 111   3   4   8]
- [  2   5   5   1  65   1   1]
- [  9   0   2   2   0  52   1]
- [ 21   2   6  16   2  12  75]]
-Node Classification on random seed  472 -> 0.594
-Confusion Matrix:
- [[ 59   2   1   2   7  28   7]
- [  3 133  12   3   1   1   7]
- [ 24  39 139  41  18  28  26]
- [ 13   5  11 108   3   4   4]
- [  2  14  11   0  59   0   0]
- [  8   2   3   0   0  41   2]
- [ 24   9   9   9   3  20  55]]
-Node Classification on random seed  473 -> 0.652
-Confusion Matrix:
- [[ 60   2   6   3   5  14  17]
- [  1 125   5   1   5   1   5]
- [ 20  29 186  23  14  11  29]
- [ 17   7  31  95   1   4  10]
- [  0   9   4   1  63   0   1]
- [  4   1   5   1   2  44   4]
- [  8   3  10   3   8  23  79]]
-Node Classification on random seed  474 -> 0.608
-Confusion Matrix:
- [[ 50   3   1   4   4  15  22]
- [  0 121   9   2  13   5   0]
- [ 21  20 160  28  34  27  46]
- [ 15   3  17  82  13   3   7]
- [  3   4   6   1  60   2   0]
- [  4   1   1   0   0  51   8]
- [ 14   3   7   6   5  15  84]]
-Node Classification on random seed  475 -> 0.627
-Confusion Matrix:
- [[ 47   2   3  10   9  25  14]
- [  4 122   0   0  15   4   3]
- [ 26  17 158  28  15  21  28]
- [ 17   4  16 120   3   4  16]
- [  0   2   5   0  61   1   1]
- [  5   2   5   5   4  49   2]
- [ 12   7   6   8  12  12  70]]
-Node Classification on random seed  476 -> 0.62
-Confusion Matrix:
- [[ 67   2   5  11   9  11   8]
- [  5 125  11   5   9   4   2]
- [ 23  16 145  37  23  16  44]
- [ 11   3  17 105   5   5  14]
- [  1   7   5   1  62   0   3]
- [  3   2   1   3   2  46   2]
- [ 10   4  10  10   7  13  70]]
-Node Classification on random seed  477 -> 0.564
-Confusion Matrix:
- [[ 70   5   2   6   6  10  10]
- [  5 120   6   1  13   3   7]
- [ 36  28 115  30  40  32  39]
- [  5   8  18  87   4  10  16]
- [  2   7   1   1  61   2   1]
- [  8   1   7   0   6  43   3]
- [ 11   2   9   7   6  22  68]]
-Node Classification on random seed  478 -> 0.619
-Confusion Matrix:
- [[ 70   1   0   2   4  18  17]
- [  4 110  10   2   6   8   6]
- [ 18  27 159  41  29  11  44]
- [ 16   2   9  91   6   6  20]
- [  1   6   4   4  58   2   4]
- [  3   2   0   1   2  36   6]
- [  3   1   4  10  12   9  95]]
-Node Classification on random seed  479 -> 0.652
-Confusion Matrix:
- [[ 80   6   4   4   8   7   9]
- [  4 127   2   3   2   1   3]
- [ 34  14 143  31  15  12  59]
- [ 14   1  12 114   4   8  11]
- [  2  13   2   1  55   0   1]
- [  2   0   2   2   0  53   5]
- [ 13   6   9   5   4  13  80]]
-Node Classification on random seed  480 -> 0.631
-Confusion Matrix:
- [[ 89   2   1   2   4   5  22]
- [  6 124   8   1   3   1   9]
- [ 33  21 145  16  26  10  52]
- [ 18   6  16  92   7   1  18]
- [  1   8   7   1  67   0   6]
- [  4   1   3   0   2  38   9]
- [  2  11  13   3   4   6  76]]
-Node Classification on random seed  481 -> 0.621
-Confusion Matrix:
- [[ 56   1  10   7   6  15   1]
- [  6 136   4   6  12   1   9]
- [ 19  12 129  37  38  21  48]
- [  6   2  13 117   8   6  12]
- [  2   2   3   0  64   1   8]
- [  2   2   3   1   0  52   5]
- [ 11   0   2  17   2  18  67]]
-Node Classification on random seed  482 -> 0.589
-Confusion Matrix:
- [[ 86   2   4   5   3   9   1]
- [  5 136   6   1   2   2   3]
- [ 39  38 128  36  27  16  30]
- [ 21   7  23  93   7   6  11]
- [  0   8   2   1  50   0   3]
- [  9   4   4   1   0  41   1]
- [ 11   5  18   7   7  26  55]]
-Node Classification on random seed  483 -> 0.62
-Confusion Matrix:
- [[ 81   0   1   4   6  23   9]
- [  7 123   5   2   4   1   1]
- [ 21  20 145  24  27  17  53]
- [  5   2  12 111  11  10   7]
- [  3   9   4   1  59   0   3]
- [  2   0   5   1   2  38   6]
- [  9   3   8  17   9  26  63]]
-Node Classification on random seed  484 -> 0.56
-Confusion Matrix:
- [[ 63   1   5   4   6  19  11]
- [  0 105   7   6   7   8   8]
- [ 22  14 138  62  38  17  39]
- [ 13   2  16  76   8   4  31]
- [  0   8   5   0  71   1   1]
- [  5   2   4   1   0  46   8]
- [  9   6   5   6  19  12  61]]
-Node Classification on random seed  485 -> 0.639
-Confusion Matrix:
- [[ 66   5   4   1   5   5  16]
- [  3 117  15   2   3   2   2]
- [ 26  25 135  41  30   5  29]
- [ 24   5  11 108   6   0  10]
- [  0   8   4   1  68   0   3]
- [  6   1   2   1   0  64   6]
- [ 15   6  14   4   4  11  81]]
-Node Classification on random seed  486 -> 0.6
-Confusion Matrix:
- [[ 51   1   8  12   5   8  18]
- [  6 145   6   4   2   1   3]
- [ 20  42 115  39  30  18  37]
- [ 20   2  15 110   1   4  14]
- [  1   4   5   1  68   0   3]
- [  3   1   1   1   0  46  10]
- [ 15   2   2  18   9   8  65]]
-Node Classification on random seed  487 -> 0.642
-Confusion Matrix:
- [[ 72   2   2   6   3  14  14]
- [  4 127   4   6  10   1   2]
- [ 23  13 157  37  19   9  48]
- [ 14   4  16  99   4   6  14]
- [  2   7   0   0  62   0   0]
- [  4   2   3   2   1  41   7]
- [  9   0  10  10   7  19  84]]
-Node Classification on random seed  488 -> 0.596
-Confusion Matrix:
- [[ 71   2   7   9   2   4   9]
- [ 11 141   5   4   5   0   4]
- [ 33  19 121  41  35  15  49]
- [  9   3  23  89   6   4  10]
- [  2   8   3   1  58   0   1]
- [  9   1   2   1   1  47   7]
- [ 15   5  11   8  11   9  69]]
-Node Classification on random seed  489 -> 0.636
-Confusion Matrix:
- [[ 70   2   3   2   4   8  10]
- [  1 117   2   1  18   2   3]
- [ 29  17 145  46  23  21  41]
- [ 10   7  18 118   5   6   6]
- [  2   4   6   1  62   0   1]
- [  8   0   1   0   3  43   3]
- [ 11   1   7   6   2  23  81]]
-Node Classification on random seed  490 -> 0.591
-Confusion Matrix:
- [[ 56   3  10  12   5  15  11]
- [  2 111   3   7   6   4   6]
- [ 25  35 137  36  23  18  44]
- [ 10   2  16  85  10   3  25]
- [  1   6   8   0  64   3   4]
- [  2   1   3   1   2  46   5]
- [ 16   2   4   4   7   9  92]]
-Node Classification on random seed  491 -> 0.597
-Confusion Matrix:
- [[ 68   1   9   8   4  16   2]
- [  5 126   6   0  13   7   2]
- [ 11  23 111  54  36  32  39]
- [  5   3  24 107  11   6   9]
- [  3   2   3   4  66   1   3]
- [  3   1   1   0   1  51   5]
- [  9   4  10   5   6  16  68]]
-Node Classification on random seed  492 -> 0.589
-Confusion Matrix:
- [[ 57   7   1   6   1  21   6]
- [  9 122   4   1   4   0   5]
- [ 11  14 160  55  19  18  42]
- [ 10   4  31 104   4   9  17]
- [  2   6   8   3  57   0   3]
- [ 14   0   3   7   4  23   3]
- [ 22   0   4  10   5  18  66]]
-Node Classification on random seed  493 -> 0.633
-Confusion Matrix:
- [[ 82   2   3   9   0  11  10]
- [  3 120   0   8   3   1   5]
- [ 18  21 130  50  37  10  37]
- [ 18   4  10 100  10   3  11]
- [  0   6   0   3  66   1   1]
- [  4   3   4   1   2  53   6]
- [  6   5   7  10  14  10  82]]
-Node Classification on random seed  494 -> 0.614
-Confusion Matrix:
- [[ 61   3  10   8   2  21  10]
- [  0 118   9   0   8  10   2]
- [ 17  15 150  28  48  15  39]
- [  6   5  23  87   6   5  13]
- [  0   7   3   0  63   1   3]
- [  8   5   2   2   0  45   4]
- [  8   2   6   8  10  14  90]]
-Node Classification on random seed  495 -> 0.582
-Confusion Matrix:
- [[ 62   5   3   5   6   5  19]
- [  6 115  12   2   9   0   2]
- [ 17  20 140  31  34  15  71]
- [ 15   5  10  90  10   8  17]
- [  1   5   4   2  63   0   8]
- [  9   1   2   2   2  38   2]
- [ 26   2   8   5   9   3  74]]
-Node Classification on random seed  496 -> 0.613
-Confusion Matrix:
- [[ 58   2  13   4   2  13  15]
- [  5 125   4   2   7   7   5]
- [ 30  12 144  27  24  21  54]
- [ 12   2  21 100   3   6  10]
- [  0   7   4   0  72   1   4]
- [  6   0   1   7   1  47   4]
- [ 11   2  10   5   8  15  67]]
-Node Classification on random seed  497 -> 0.591
-Confusion Matrix:
- [[ 67  10  10   3   2   7  18]
- [  4 123  12   2   5   5   5]
- [ 22  20 111  40  24  27  53]
- [  8   9  15 104   8   2  20]
- [  0   5   4   2  66   0   1]
- [ 10   1   1   0   1  35   4]
- [ 10   5   9   0  13  12  85]]
-Node Classification on random seed  498 -> 0.596
-Confusion Matrix:
- [[ 58   7   6   6   2   5   6]
- [  4 133   2   2  18   1   1]
- [ 17  34 126  40  31  22  35]
- [ 15   5  10  99   5   7  20]
- [  2   5   6   4  63   0   3]
- [  9   1   1   3   0  37   6]
- [ 19   5  13  10   3  13  80]]
-Node Classification on random seed  499 -> 0.599
-Confusion Matrix:
- [[ 71   4   8   0   6  14   2]
- [  5 112   3   3   6   3   0]
- [ 36  21 139  26  37  27  30]
- [ 16   7  25 103   8  12   7]
- [  2   6   2   2  62   1   5]
- [ 10   1   0   2   0  39   7]
- [ 17   4  12   5   7  12  73]]
-Node Classification on random seed  500 -> 0.631
-Confusion Matrix:
- [[ 89   0   3   5   5  17   6]
- [  6 117   5   5   2   7   3]
- [ 24  21 140  38  21  30  28]
- [ 11   4  11 111   6   8  14]
- [  0   4   5   1  66   0   0]
- [  7   5   0   1   0  39   2]
- [ 10   3  20  10   2  19  69]]
-Node Classification on random seed  501 -> 0.606
-Confusion Matrix:
- [[ 61   3   2   3   6   6  12]
- [  5 115   7   2  15   3   6]
- [ 14  25 141  44  24  25  43]
- [ 19   2  22 106   4   4  12]
- [  0   7   6   1  57   0   3]
- [  4   0   2   4   0  49   5]
- [ 14   2   7  11   9  11  77]]
-Node Classification on random seed  502 -> 0.582
-Confusion Matrix:
- [[ 77   2   2   6   2  12   7]
- [  6 119   6   1  14   8   1]
- [ 36  15 126  28  20  21  66]
- [ 19   0  11  87   6   9  21]
- [  4   4   3   1  50   6   2]
- [  4   2   1   2   1  47   5]
- [  9   3  10  13   7  22  76]]
-Node Classification on random seed  503 -> 0.674
-Confusion Matrix:
- [[ 87   3   4   2   9   6  11]
- [  4 132  10   3   6   3   2]
- [ 23  10 148  41  17   8  43]
- [  4   3   5 126   4   0  14]
- [  0   6   4   2  63   0   6]
- [  8   4   2   2   1  36   3]
- [ 19   2   4  10  11   7  82]]
-Node Classification on random seed  504 -> 0.635
-Confusion Matrix:
- [[ 78   4   5   2   3  11   9]
- [  6 124   6   4   2   4   3]
- [ 21  22 160  26  34  25  35]
- [  5   0  13 106  17   6  11]
- [  0   4   9   1  52   0   3]
- [  6   3   0   3   1  44   5]
- [ 18   3  17   4   4  10  71]]
-Node Classification on random seed  505 -> 0.589
-Confusion Matrix:
- [[ 57   3   4  17   6  12   5]
- [  1 136   4   2   8   3   5]
- [ 25  27 106  52  18  20  61]
- [  6   6  25 105   7   6  10]
- [  0   6   4   2  61   1   4]
- [  6   2   0   2   1  39   5]
- [ 12   3   8   5   6  11  85]]
-Node Classification on random seed  506 -> 0.591
-Confusion Matrix:
- [[ 60   3   4   1   1  28   4]
- [  1 130  11   7   5   1   4]
- [ 22  27 134  37  20  26  51]
- [ 16   5  15  91   3   4  16]
- [  1   6   5   1  56   1   3]
- [  8   1   3   0   2  42   9]
- [ 18   6   8   7   4  14  78]]
-Node Classification on random seed  507 -> 0.616
-Confusion Matrix:
- [[ 62   3   0   5   4   9  16]
- [  4 116   7   8   6   2   9]
- [ 41  16 109  34  38  19  41]
- [ 11   6  16 124   1   6  14]
- [  2   7   3   3  68   0   2]
- [  1   1   3   0   0  45   3]
- [ 15   4   2   3   6  13  92]]
-Node Classification on random seed  508 -> 0.654
-Confusion Matrix:
- [[ 59   3   6   4   3  19   4]
- [  5 141   5   2   7   4   7]
- [ 22  15 169  23  25  22  30]
- [  9   5  22 109   5   6   6]
- [  1   8   2   0  57   1   1]
- [  4   1   1   0   0  48  13]
- [ 12   3   7   5  11  17  71]]
-Node Classification on random seed  509 -> 0.624
-Confusion Matrix:
- [[ 68   1   8   9   3  15  12]
- [  0 115   6   2   6   7   9]
- [ 22  34 151  36  26  11  39]
- [ 10   1  12 112   8   9  12]
- [  3   6   1   1  57   2   1]
- [  3   1   4   6   0  42   4]
- [ 11   2  14   5   6   8  79]]
-Node Classification on random seed  510 -> 0.619
-Confusion Matrix:
- [[ 70   2   3   4   3   9  14]
- [  4 141   7   3   3   3   3]
- [ 28  26 165  34  17  20  39]
- [ 24   5  14  87  13   2   8]
- [  2  12   3   1  53   3   4]
- [  1   2   0   3   1  42   8]
- [ 12   4   4  11   6  16  61]]
-Node Classification on random seed  511 -> 0.569
-Confusion Matrix:
- [[ 67   0   7   4   8   9  11]
- [  4 107   8   4  19   2   1]
- [ 49  27 109  41  37  13  44]
- [ 18   5  13  97   3   8  15]
- [  4   8   0   3  65   0   1]
- [  4   1   3   1   1  42   4]
- [ 12   4   4   9   4  18  82]]
-Node Classification on random seed  512 -> 0.619
-Confusion Matrix:
- [[ 62   5   2   2  11  17   9]
- [  6 124   9   2   4   6   4]
- [ 34  19 122  21  34  21  40]
- [  8   3  21 103   4  12   8]
- [  2   2   3   2  72   1   1]
- [  7   0   2   1   1  53   4]
- [ 17   2   7   5  10  12  83]]
-Node Classification on random seed  513 -> 0.612
-Confusion Matrix:
- [[ 87   1   1   4   4  13   3]
- [  4 140   6   0   6   7   3]
- [ 22  23 118  16  35  35  44]
- [ 14   7  17 101   4   4  11]
- [  2  10   2   2  61   2   4]
- [  5   4   2   4   2  33  10]
- [  8   5  10   8   6  18  72]]
-Node Classification on random seed  514 -> 0.59
-Confusion Matrix:
- [[ 70   1   5   5   3  13   8]
- [ 15 123   5   2   6   3   3]
- [ 38  20 130  31  28  19  50]
- [ 15   4   5  90  13   5  12]
- [  6   7   3   0  65   1   1]
- [  6   0   0   1   1  41   2]
- [ 14   5   7   7   2  38  71]]
-Node Classification on random seed  515 -> 0.605
-Confusion Matrix:
- [[ 65   2   9   1   1   9   6]
- [  8 116   6   7   7   0   3]
- [ 16  27 135  45  26  36  35]
- [  6   5  12 115   9  10   8]
- [  2  11   6   4  58   0   1]
- [  5   3   3   0   2  51   6]
- [ 13   3  13   5   9  15  65]]
-Node Classification on random seed  516 -> 0.628
-Confusion Matrix:
- [[ 90   4   4   3   3   2  10]
- [ 10 117   6   1   3   0   0]
- [ 29  21 152  43  13  23  30]
- [ 13   7  16  95   4   8  14]
- [  3   9   9   0  48   1   0]
- [ 11   4   4   0   0  52   6]
- [ 11   2  11   3   9  22  74]]
-Node Classification on random seed  517 -> 0.619
-Confusion Matrix:
- [[ 87   3   5   6   4   9   7]
- [  5 135  10   1   6   4   5]
- [ 20  22 138  26  28  17  47]
- [ 10   4  24  93   4   4  13]
- [  3   8   5   2  50   5   1]
- [  7   4   5   4   1  42   4]
- [ 16   3   9   1   8  11  74]]
-Node Classification on random seed  518 -> 0.61
-Confusion Matrix:
- [[ 52   7   2   4   8  12  18]
- [  1 121   5   1  10   3   7]
- [ 20  12 138  41  35  29  30]
- [ 10   2  17 118   7   8  11]
- [  0   3   4   2  72   0   4]
- [  6   2   1   0   2  48   2]
- [  8   3   9  12  13  19  61]]
-Node Classification on random seed  519 -> 0.636
-Confusion Matrix:
- [[ 57   3   3   6   4  14   8]
- [  1 128   5   1   7   8   5]
- [ 30  21 153  33  38  29  25]
- [ 14   1   9 111   5   6   4]
- [  0  10   6   1  66   0   0]
- [  3   2   3   3   0  50   2]
- [ 15   1  11   4   7  16  71]]
-Node Classification on random seed  520 -> 0.65
-Confusion Matrix:
- [[ 82   2   0   6   2   6   9]
- [  6 120   2   1   8   2   9]
- [ 23  23 149  39  17  21  37]
- [ 10  11   7 113   2   8   9]
- [  3   1   4   3  60   1   2]
- [  3   2   1   1   0  49  10]
- [  8   3   2   6   7  33  77]]
-Node Classification on random seed  521 -> 0.646
-Confusion Matrix:
- [[ 80   0   8   5   1   9   7]
- [  7 139   1   2   4   2   1]
- [ 28  37 129  34  37  26  29]
- [  1   6   7 119   4   2  10]
- [  3  11   2   3  60   1   0]
- [  6   0   4   1   2  47   3]
- [ 15   3   7   8   7  10  72]]
-Node Classification on random seed  522 -> 0.609
-Confusion Matrix:
- [[ 61   7   3   2   5  16  13]
- [  1 129   4   2   6   0   8]
- [ 29  18 151  29  33  16  28]
- [ 13   5  18 110   4   2  12]
- [  2  13   4   1  64   1   4]
- [  1   0   9   0   1  42   2]
- [ 16   8  10  12  26   7  52]]
-Node Classification on random seed  523 -> 0.627
-Confusion Matrix:
- [[ 68   5   2   2   1  20   9]
- [  9 130   4   3   2   2   9]
- [ 18  23 147  35  14  23  45]
- [ 18  12  14 104   4   5  14]
- [  5   9   3   3  50   0   1]
- [  2   0   1   4   0  43  16]
- [  7   7   4   4   5   9  85]]
-Node Classification on random seed  524 -> 0.599
-Confusion Matrix:
- [[ 65   0   3   6   4  18   2]
- [ 14 121   5   0  10   3  10]
- [ 54  20 118  25  31  12  35]
- [ 29   0  12 110   2   6  12]
- [  1   4   4   0  66   5   2]
- [  2   0   4   5   1  45   5]
- [ 17   0  10  10   9   9  74]]
-Node Classification on random seed  525 -> 0.61
-Confusion Matrix:
- [[ 73   0   7   3   2  17  14]
- [  3 127   9   3   9   3   3]
- [ 31  26 122  21  21  32  43]
- [  3   3  23 106   6   6  10]
- [  1   6   7   0  59   0   3]
- [  2   0   3   2   2  49   8]
- [  7   2   4   8   6  31  74]]
-Node Classification on random seed  526 -> 0.602
-Confusion Matrix:
- [[ 65   2   5   6   2  14  17]
- [  5 101   7   2  16   7   3]
- [ 28   8 154  31  35  33  29]
- [  8   1  15 113   3   7  13]
- [  3   6   9   1  54   1   3]
- [  8   1   2   4   0  48   3]
- [ 17   9   7   5   8  14  67]]
-Node Classification on random seed  527 -> 0.617
-Confusion Matrix:
- [[ 64   1  14   6   0   8   8]
- [  1 132   7   1   1   2   2]
- [ 11  33 148  26  31  29  52]
- [  9   2  17 102   5   4  11]
- [  2  14   3   3  55   2   0]
- [  6   1   0   1   2  45   3]
- [ 21   9   9   2   6  18  71]]
-Node Classification on random seed  528 -> 0.638
-Confusion Matrix:
- [[ 86   0   3   6   6  14   3]
- [  6 126   4   0  12   3   4]
- [ 27  10 150  23  28  17  42]
- [ 13   5  16 106   5   2  15]
- [  4   6   2   0  52   2   4]
- [  4   1   2   2   7  51   4]
- [ 19   4   7  10   5  15  67]]
-Node Classification on random seed  529 -> 0.613
-Confusion Matrix:
- [[ 58   9   6  10   3  14  11]
- [  9 142   2   4   4   3   4]
- [ 21  23 131  41  14  24  44]
- [  3   3   7 106   5  13  17]
- [  4   6   8   2  60   0   2]
- [  9   0   1   0   0  44   9]
- [  9   3  10  11   8  11  72]]
-Node Classification on random seed  530 -> 0.612
-Confusion Matrix:
- [[ 64   3   3   4   3  17  17]
- [  2 128   6   2   0   4   6]
- [ 27  25 143  23  11  22  51]
- [ 15   6   9  85   4  10  22]
- [  2  11   3   1  63   1   8]
- [  4   0   3   0   0  52   5]
- [ 14   4   3  20   4  13  77]]
-Node Classification on random seed  531 -> 0.633
-Confusion Matrix:
- [[ 69   3   9   4   5  12   7]
- [  3 117   7   1   2   4   8]
- [ 14  25 139  24  34  32  37]
- [ 14   4  17 104   2   4  13]
- [  0   4   3   3  69   2   1]
- [  3   1   0   1   1  51   1]
- [  7   4  11   9   5  26  84]]
-Node Classification on random seed  532 -> 0.627
-Confusion Matrix:
- [[ 69   0   1   2   2  12  16]
- [  1 114  11   1   2   8   5]
- [ 17  21 165  22  17  25  45]
- [ 18   9  18 102   8   1  13]
- [  1   7  13   2  41   2   2]
- [  7   3   2   1   0  48   4]
- [ 14   6  11   6   7  10  88]]
-Node Classification on random seed  533 -> 0.65
-Confusion Matrix:
- [[ 76   4   1   3   2   3   9]
- [  4 144   2   1   7   3   6]
- [ 26  26 134  21  27  20  46]
- [ 12   7   9 118   3   8  13]
- [  1  10   3   1  68   0   2]
- [  8   2   0   3   3  32   3]
- [ 13   1  11   7   7  12  78]]
-Node Classification on random seed  534 -> 0.591
-Confusion Matrix:
- [[ 53   5   2  11   3  14  16]
- [  8  99   9   1  23   3   4]
- [ 30  10 175  24  31  24  37]
- [  9   5  22  89   6   7  18]
- [  0   3   7   0  67   0   4]
- [  4   0   1   1   0  42   5]
- [ 17   3   7  12   7  16  66]]
-Node Classification on random seed  535 -> 0.641
-Confusion Matrix:
- [[ 72   4   9   4   8  15   4]
- [  9 119   2   1   7   2   3]
- [ 36  26 171  24  18  21  27]
- [ 22   3  14  91   4   6  14]
- [  2   7   4   2  57   0   0]
- [  7   0   3   1   1  45   4]
- [ 10   7   7   1   5  15  86]]
-Node Classification on random seed  536 -> 0.614
-Confusion Matrix:
- [[ 83   3   9   5   9  13   1]
- [  2 122   3   9   4   3   2]
- [ 17   7 158  61  18  17  42]
- [ 18   8  21  94  10   7   7]
- [  0   5   7   2  50   4   1]
- [  3   0   2   1   0  38   5]
- [ 15   9   6   4   9  17  69]]
-Node Classification on random seed  537 -> 0.59
-Confusion Matrix:
- [[ 78   1  10   5   3   8   6]
- [  7 118   5   4   9   1   9]
- [ 34  14 157  27  34  13  39]
- [ 20   3  12  72   7   1  31]
- [  0   3   6   6  61   2   3]
- [  4   3   5   1   1  43   3]
- [ 17   0  16   8  15  14  61]]
-Node Classification on random seed  538 -> 0.605
-Confusion Matrix:
- [[ 69   2   5   9   5  12  12]
- [  9 126  11   7   4   2   4]
- [ 23  22 132  35  28  26  42]
- [  9   2  19 108   5   3  11]
- [  1  10   3   1  53   1   0]
- [  8   1   0   3   1  45   5]
- [ 16   6   3  10   5  14  72]]
-Node Classification on random seed  539 -> 0.621
-Confusion Matrix:
- [[ 75   4   6   4   4   9  11]
- [  9 109   6   4  16   4   2]
- [ 28  18 143  29  37  15  33]
- [ 11   3  15 128   0   4   3]
- [  1   6   7   5  63   0   2]
- [  6   1   3   4   6  37   6]
- [ 14   4  10  14   6   9  66]]
-Node Classification on random seed  540 -> 0.607
-Confusion Matrix:
- [[ 69   8   1  14   3  15   8]
- [ 10 117   2   3  10   8   2]
- [ 23  15 150  50  27  27  20]
- [  2   5   5 114   7   4   0]
- [  1   7   8   2  66   0   0]
- [ 12   1   2   7   2  36   2]
- [ 11   2  12  26   9  20  55]]
-Node Classification on random seed  541 -> 0.581
-Confusion Matrix:
- [[ 74   2  19   2   3   7  18]
- [ 24 109   7   3   6   2   5]
- [ 21  28 141  39  26  19  30]
- [ 12   2  14 101   3  15  14]
- [  2   3   6   3  50   2   5]
- [  8   1  11   1   0  38   3]
- [  7   6   5  11   7  17  68]]
-Node Classification on random seed  542 -> 0.613
-Confusion Matrix:
- [[ 72   6   9   5   2   8  14]
- [  4 125   4   0  21   1   5]
- [ 14  18 143  36  33  18  42]
- [ 17   4  14 106   1  11  20]
- [  4   7   3   1  55   1   2]
- [  5   1   4   2   0  37   5]
- [  9   3   8  10   3  12  75]]
-Node Classification on random seed  543 -> 0.628
-Confusion Matrix:
- [[ 86   0   7   6   4  10   4]
- [ 11 112   6   2   4   4   4]
- [ 45  18 156  41  22  26  17]
- [ 16   2  20  88   6   2  11]
- [  4   7   3   2  66   1   3]
- [  4   1   3   0   0  46   9]
- [ 23   5   5   3   3   8  74]]
-Node Classification on random seed  544 -> 0.6
-Confusion Matrix:
- [[ 63   5   8   5   3  10  14]
- [  6 116   8   8   7   3   5]
- [ 19  24 127  53  27  14  35]
- [  6   5  21 114   3   2  15]
- [  2   9   5   0  62   1   2]
- [  5   1   9   1   0  39   9]
- [  6   7   9   4  14  10  79]]
-Node Classification on random seed  545 -> 0.592
-Confusion Matrix:
- [[ 65   6   7   2   7  13  13]
- [  2 146   5   0   6   2   4]
- [ 26  26 119  43  22  40  30]
- [ 10   3  15  84   5   7  11]
- [  0   7   2   1  63   3   3]
- [  2   2   3   1   2  49   4]
- [  5   2  29   7   8  22  66]]
-Node Classification on random seed  546 -> 0.678
-Confusion Matrix:
- [[ 79   3   2   4   7  10   6]
- [  6 112  10   2  11   0   0]
- [ 17  18 178  37  23  13  34]
- [ 12   3   8 107  16   5  15]
- [  1   2   4   1  74   0   4]
- [  1   1   2   4   3  46   6]
- [  7   3   5   4   4   8  82]]
-Node Classification on random seed  547 -> 0.621
-Confusion Matrix:
- [[ 74   0   2   7   6   2  20]
- [  3 127   0   5   9   6   1]
- [ 34  27 152  30  32  14  40]
- [ 11   3  18  93   5   4  17]
- [  2   2   4   0  63   1   1]
- [  5   6   4   4   0  34   7]
- [  8   4  12   8   4  11  78]]
-Node Classification on random seed  548 -> 0.667
-Confusion Matrix:
- [[ 68   1   7   0   8   1  14]
- [  1 133   6   8   6   1   6]
- [ 35  11 194  18  19   7  39]
- [ 19   2  16  91   4   5  16]
- [  1   6   6   0  63   0   1]
- [ 10   1   6   0   1  48   8]
- [ 14   5   4   3  10   7  70]]
-Node Classification on random seed  549 -> 0.607
-Confusion Matrix:
- [[ 62   3   3  11   3   6  15]
- [  4 120   6   3  12  12   5]
- [ 27  22 122  41  30  22  36]
- [ 15   7  20 112   5   2   5]
- [  0   4   1   5  66   1   3]
- [ 10   3   1   1   2  43   3]
- [ 12   3   9  10   4   6  82]]
-Node Classification on random seed  550 -> 0.62
-Confusion Matrix:
- [[ 62   4  14   3   9  14   5]
- [  4 113   8   2  13   7   2]
- [ 21  20 151  41  43  18  29]
- [  8   4  13 109   4   3  20]
- [  3   3   3   0  71   2   4]
- [  4   1   0   0   3  41   2]
- [  5   1  20   0   7  13  73]]
-Node Classification on random seed  551 -> 0.621
-Confusion Matrix:
- [[ 61   5   1   6   6   6  17]
- [  5 136   3   0   7   1   3]
- [ 26  19 132  43  19  15  54]
- [  6   4  11 113   7  11  17]
- [  1   4   6   5  57   0   2]
- [  7   1   1   2   0  47   6]
- [ 12   7   8   7   8  10  75]]
-Node Classification on random seed  552 -> 0.602
-Confusion Matrix:
- [[ 80   5   0   2   2  13  19]
- [  1 132   7   0   5   4   3]
- [ 21  24 130  40  41  26  35]
- [  8   5  11 111   7   7  13]
- [  0   3   2   4  59   0   6]
- [  6   2   1   0   0  34   8]
- [ 12   1   7   3  26  18  56]]
-Node Classification on random seed  553 -> 0.613
-Confusion Matrix:
- [[ 61   1   6  13   3   7   8]
- [  3 141   6   1   2   3   9]
- [ 29  27 116  36  21  34  45]
- [  8   4  17 111   2   9   9]
- [  1   5   6   1  59   0   4]
- [  1   5   4   2   0  49   0]
- [ 11   6   6   7   4  21  76]]
-Node Classification on random seed  554 -> 0.649
-Confusion Matrix:
- [[ 60   0   4   1   6  14  18]
- [  3 140   4   1   5  10   1]
- [ 17  38 152  23  29  18  39]
- [ 17   4   7 125   1   2   7]
- [  1   5   7   1  52   3   1]
- [  6   1   0   2   3  46   9]
- [ 11   7   8   2   3  12  74]]
-Node Classification on random seed  555 -> 0.621
-Confusion Matrix:
- [[ 71   4   8   9   3   8   7]
- [  4 135  13   2   4   4   2]
- [ 21  16 132  29  50  15  37]
- [ 10   5  15  96   4   5  14]
- [  0   5   4   0  64   0   2]
- [ 13   0   2   4   2  44   1]
- [ 15   9  12   3   7  11  79]]
-Node Classification on random seed  556 -> 0.632
-Confusion Matrix:
- [[ 80   1   5   6   4  10   7]
- [  2 136   8   8  11   3   4]
- [ 20  10 132  49  11  14  44]
- [  4   6  19 103  13   8  13]
- [  2   6   1   1  62   4   1]
- [  6   1   0   0   0  43  11]
- [ 11   2   9  13   7  13  76]]
-Node Classification on random seed  557 -> 0.627
-Confusion Matrix:
- [[ 77   3   6   0   2   6   7]
- [  3 136   1   1   9   3   2]
- [ 25  37 163  26  17  17  37]
- [ 29   5  20  70  10   2   7]
- [  1   7   4   2  57   1   0]
- [  7   1   2   3   3  58   4]
- [ 15   4  14  12  12   6  66]]
-Node Classification on random seed  558 -> 0.634
-Confusion Matrix:
- [[ 75   2   3   0   6   5  11]
- [  7 125   4   2   4   1  13]
- [ 23  33 159  31  25  13  32]
- [ 10   7  12 115   5   3  12]
- [  0   7   5   0  58   0   4]
- [  6   3   1   1   0  44  10]
- [  9   5  14  15   6  16  58]]
-Node Classification on random seed  559 -> 0.607
-Confusion Matrix:
- [[ 76   1   1   6   4   6   8]
- [ 15 118   0   1   8   4   4]
- [ 24  21 140  39  23  24  43]
- [ 13   6  18  98   1   9  10]
- [  2  11   8   2  56   0   2]
- [ 19   1   0   0   0  48   4]
- [ 11   8  10  12   6   8  71]]
-Node Classification on random seed  560 -> 0.591
-Confusion Matrix:
- [[ 60   1  12  12   4  11  11]
- [  3 125   9   5  13   3   3]
- [ 19  22 152  45  24  19  27]
- [ 21   2  22  85   6   6   4]
- [  5   6   6   3  52   0   1]
- [  9   4   1   3   1  52   6]
- [ 14   4   7  12   8  15  65]]
-Node Classification on random seed  561 -> 0.646
-Confusion Matrix:
- [[ 66   1  10   6   3  15   9]
- [  9 127  11   1   6   3   5]
- [ 19  26 167  30  17  27  26]
- [  7   6  10 110   6   6  11]
- [  1   6   4   1  58   0   1]
- [  4   2   2   1   1  46   7]
- [  7   4   8  10   6  19  72]]
-Node Classification on random seed  562 -> 0.607
-Confusion Matrix:
- [[ 72   1   2   4   4   7  11]
- [  1  98   5   1  19   5   9]
- [ 15  27 148  36  29  28  35]
- [ 15   9  18  93   5   7   8]
- [  1   0   8   2  65   1   2]
- [  7   5   2   0   0  48   5]
- [  8   9  11   5  10  16  83]]
-Node Classification on random seed  563 -> 0.622
-Confusion Matrix:
- [[ 74   4   4  24   2   8   7]
- [  2 139   3   2   4   2   7]
- [  6  23 161  34  26  27  40]
- [  3   5  18  89  11   6  19]
- [  0   7   5   1  52   3   1]
- [  5   2   1   2   1  51   3]
- [  2   6   6  14   9  23  56]]
-Node Classification on random seed  564 -> 0.65
-Confusion Matrix:
- [[ 72   1   9   5   3  11   6]
- [  2 125   5   0   9   0   2]
- [ 28  13 143  46  27  21  29]
- [  9   4  15 118   5  14   8]
- [  1  10   4   2  57   1   2]
- [  3   0   4   2   0  50   8]
- [  9   2  16   3   3   8  85]]
-Node Classification on random seed  565 -> 0.634
-Confusion Matrix:
- [[ 70   1   2   3   7  12   8]
- [  6 139   4   2   5   3   3]
- [ 18  20 142  36  28  32  25]
- [  6   6  13 105   2  10  16]
- [  2   7   2   3  59   0   6]
- [  6   1   1   0   0  57   3]
- [ 14   2   6   7  10  28  62]]
-Node Classification on random seed  566 -> 0.617
-Confusion Matrix:
- [[ 68   1   6   9   6   8  11]
- [  1 120   6   1   7   4   9]
- [ 28  13 147  30  35  17  53]
- [  5   2  23  92   5   7  10]
- [  1   6   6   4  53   0   0]
- [ 10   0   3   1   1  43   6]
- [  7   8  10   6  13   4  94]]
-Node Classification on random seed  567 -> 0.638
-Confusion Matrix:
- [[ 56   1   6   8   3  13  19]
- [  4 127  11   0   4   3   2]
- [ 24  13 147  26  33  20  52]
- [  8   3  10 106   6   9  29]
- [  1   7   2   1  62   0   0]
- [  7   1   0   0   1  50   3]
- [  8   1   1   5   6  11  90]]
-Node Classification on random seed  568 -> 0.609
-Confusion Matrix:
- [[ 66   2   7   7   5  13  10]
- [  9 108   7   0  15   1   4]
- [ 28  22 127  39  28  20  25]
- [  7   2  15 109   7  12  18]
- [  1   5   4   6  66   1   1]
- [ 10   0   0   4   1  52   0]
- [  9   2   2  14  10  18  81]]
-Node Classification on random seed  569 -> 0.632
-Confusion Matrix:
- [[ 71   5   2   8   4  11   9]
- [  3 137   6   4   2   2   2]
- [ 17  33 143  25  15  25  43]
- [ 22   9  14  99   4   6  11]
- [  1   7   7   3  56   1   7]
- [  5   1   0   0   0  48   4]
- [ 14   1   7  11   4  13  78]]
-Node Classification on random seed  570 -> 0.599
-Confusion Matrix:
- [[ 58   6   4   6   8  10  11]
- [  3 140   0  10   3   5   3]
- [ 30  30 155  25  27  32  25]
- [  7   4  16 102  19   8   9]
- [  1   2   3   5  49   1   4]
- [  8   1   1   0   1  30   5]
- [ 11   3  14  13  12  15  65]]
-Node Classification on random seed  571 -> 0.587
-Confusion Matrix:
- [[ 71   1   8   7   4  16  10]
- [  5 134   6   2   0   1   6]
- [ 29  21 123  43  33  32  34]
- [ 23   3  11  89   9  11   8]
- [  3   6   5   1  58   2   1]
- [  7   4   3   3   1  40   6]
- [  6   4  11   8   5  14  72]]
-Node Classification on random seed  572 -> 0.607
-Confusion Matrix:
- [[ 80   3   4   6   3  11   4]
- [  5 116   7   2   6   2   8]
- [ 29  14 122  44  60  19  31]
- [  6   4  11 113   5   3   5]
- [  0   3   2   0  61   0   3]
- [  6   0   2   0   4  45   3]
- [ 10   3  17  14   9  25  70]]
-Node Classification on random seed  573 -> 0.547
-Confusion Matrix:
- [[ 67   2   3  11   4  11  10]
- [  3 123   2   2  24   0   1]
- [ 18  25 119  56  38  36  34]
- [ 34   2  11  79   7  15  11]
- [  1   4   2   3  58   1   1]
- [ 12   1   4   1   0  29   3]
- [ 14   5   8   7   9  17  72]]
-Node Classification on random seed  574 -> 0.611
-Confusion Matrix:
- [[ 71   3   2   6   5   9  13]
- [  3 142   9   7   7   1   7]
- [ 16  23 128  40  15  15  47]
- [ 21   4   6 103   4   1  27]
- [  0   8   2   4  57   0   3]
- [  1   2   2   1   0  43   5]
- [ 15   3   8   6  20  18  67]]
-Node Classification on random seed  575 -> 0.606
-Confusion Matrix:
- [[ 69   2   3   2  12   2  23]
- [  3 143   3   0  12   3   5]
- [ 29  23 122  25  25  18  55]
- [ 17   3  10 105   3   3  13]
- [  1   6   4   0  77   1   1]
- [  6   6   1   4   0  33   4]
- [ 12   3  11   7  20  13  57]]
-Node Classification on random seed  576 -> 0.597
-Confusion Matrix:
- [[ 66   2  13   9   2   9   7]
- [ 18 119   7   1   1   3   1]
- [ 30  22 109  38  49  10  35]
- [ 12   2  18 125   1   4   6]
- [  2   9   3   5  62   1   1]
- [  6   2   1   1   0  39   6]
- [ 14   4  15   9   6  18  77]]
-Node Classification on random seed  577 -> 0.63
-Confusion Matrix:
- [[ 83   2  12   9   3   8   3]
- [  2 122   7   2   5   5  10]
- [ 26  16 171  51  19  18  28]
- [  6   3  15  93   2  13  10]
- [  2   4   6   4  53   0   0]
- [  6   2   3   0   0  43   5]
- [ 16   1  12   9   9  16  65]]
-Node Classification on random seed  578 -> 0.59
-Confusion Matrix:
- [[ 62   7   9  13   3   5  11]
- [  5 119   8   2  10   3   2]
- [ 30  21 141  32  35  17  45]
- [  8   6  19 102   8   4   6]
- [  2   7   2   2  56   0   6]
- [ 14   2   2   5   0  37   5]
- [ 10   1   9  13   8  13  73]]
-Node Classification on random seed  579 -> 0.612
-Confusion Matrix:
- [[ 75   2   2   6  10  14  10]
- [ 13 108   6   0   9   4   5]
- [ 30  21 145  46  21  24  44]
- [  7   1  12 118   4   4  11]
- [  1   5   4   0  63   1   2]
- [ 10   2   0   1   0  36   6]
- [ 18   2  10   3  12   5  67]]
-Node Classification on random seed  580 -> 0.645
-Confusion Matrix:
- [[ 74   2   0   3   6   8   8]
- [  0 143   6   2   5   2  11]
- [ 30  15 164  26  21  19  41]
- [ 28   3  15  78   7   8  11]
- [  0   4   5   1  56   1   3]
- [  8   0   1   3   2  43   3]
- [ 13   4   7   9   6   8  87]]
-Node Classification on random seed  581 -> 0.572
-Confusion Matrix:
- [[ 68   1   4   2   4  15  14]
- [ 11 130   4   4   9   1   3]
- [ 35  36 122  60  19  21  43]
- [ 26   1   9  85   6   2  12]
- [  0   6   2   0  52   2   3]
- [ 13   1   7   0   4  36   3]
- [  8   8   6   1   8  14  79]]
-Node Classification on random seed  582 -> 0.575
-Confusion Matrix:
- [[ 63   1   5   4   7   8  16]
- [  7 129   5   4   3   0   9]
- [ 23  22 135  42  19  27  40]
- [ 20   2  22  72   5  14   9]
- [  0   1   4   3  67   0   9]
- [ 13   1   0   0   2  37   9]
- [ 16   2   7  23   7  14  72]]
-Node Classification on random seed  583 -> 0.609
-Confusion Matrix:
- [[ 57   1   2   8   3  19   2]
- [  3 120   9   0   9   9   2]
- [ 18  16 149  34  40  16  47]
- [ 12   5  14 109   6   6  10]
- [  2  12   5   3  61   4   0]
- [  6   4   2   2   0  44   6]
- [  9   3   6  15   8  13  69]]
-Node Classification on random seed  584 -> 0.615
-Confusion Matrix:
- [[ 62   3   2   7   4  17  10]
- [  6 128  17   0  10   3   0]
- [ 18  12 160  34  37  14  35]
- [ 12   5  24  95   4  10  11]
- [  0   3   3   1  62   1   4]
- [  2   1   2   2   1  39  15]
- [ 14   3   8   9   4  17  69]]
-Node Classification on random seed  585 -> 0.617
-Confusion Matrix:
- [[ 57   4   3   5   7  16   9]
- [ 11 125   4   5  11   4   3]
- [ 15  16 151  32  29  26  39]
- [  7   3   8 101  10   3  13]
- [  3   1   0   1  71   1   2]
- [  5   1   2   8   1  38   5]
- [ 13   3   8  15  11  20  74]]
-Node Classification on random seed  586 -> 0.621
-Confusion Matrix:
- [[ 79   1   6   0   1  13   8]
- [  8 124  11   1   7   7   4]
- [ 27  13 153  36  23   9  46]
- [ 20   7  19  88  10   4   7]
- [  2   7   5   1  59   1   4]
- [ 11   2   2   0   1  45   2]
- [ 24   4  11   7   2   5  73]]
-Node Classification on random seed  587 -> 0.581
-Confusion Matrix:
- [[ 66   2   3   2   4  11  17]
- [  1 143   4   2   4   2   7]
- [ 25  25 103  22  44  25  57]
- [ 19   7  16  95  14   6  12]
- [  1   9   2   4  67   1   6]
- [  6   1   1   1   0  40  11]
- [ 11   5   3   4   8  14  67]]
-Node Classification on random seed  588 -> 0.612
-Confusion Matrix:
- [[ 71   2   8   5   2  13   9]
- [  4 129   4   2  10   4   4]
- [ 29  23 151  21  12  31  32]
- [  8   6  17  99   1   6  20]
- [  3  10   3   4  50   4   1]
- [  7   3   2   2   6  37   7]
- [  8   5   8  18   4  20  75]]
-Node Classification on random seed  589 -> 0.629
-Confusion Matrix:
- [[ 66   6  11   5  10   9   7]
- [  6 130   9   2   5   0   2]
- [ 18  32 135  28  49  16  30]
- [ 11   3   8 119   4   5   4]
- [  2   8   2   2  57   1   2]
- [  8   0   3   2   1  50   4]
- [ 13   4   8   9   7  15  72]]
-Node Classification on random seed  590 -> 0.64
-Confusion Matrix:
- [[ 60   2   3   4   5   7  13]
- [  4 121   6   4   2   0   6]
- [ 21  19 150  33  31  14  54]
- [ 16   1   7 120   3   3  12]
- [  2   6   2   2  67   2   1]
- [ 11   0   2   4   2  48   7]
- [ 17   1   4   5   9  13  74]]
-Node Classification on random seed  591 -> 0.632
-Confusion Matrix:
- [[ 76   1   3   2   4   7  19]
- [  5 144   8   2   3   0   6]
- [ 15  36 143  28  19  17  40]
- [ 16   4  13 116   3  13  12]
- [  2   9   5   3  51   1   4]
- [  8   2   0   0   2  34   5]
- [  9   6   3   5   9  19  68]]
-Node Classification on random seed  592 -> 0.622
-Confusion Matrix:
- [[ 82   2   3   3   3   4  10]
- [ 10 136  12   3   9   2   5]
- [ 24  19 145  29  38  19  34]
- [ 13   9  15 104   2   4   5]
- [  3   4   7   2  59   0   1]
- [  8   4   0   5   2  33  10]
- [ 14   7   5   9   7  13  63]]
-Node Classification on random seed  593 -> 0.617
-Confusion Matrix:
- [[ 75   2   0   7  12  13  15]
- [  4 119   1   0   5   2   0]
- [ 30  17 123  23  55  39  29]
- [  8   5  17 109   3   2   8]
- [  0   6   2   2  71   1   3]
- [  8   1   2   2   0  49   4]
- [  5   2   4   9   5  30  71]]
-Node Classification on random seed  594 -> 0.617
-Confusion Matrix:
- [[ 67   1  12   5   5   6   5]
- [  3 136   6   0   2   0  10]
- [ 20  21 136  47  36  21  35]
- [ 18   7  12 106   6   7   6]
- [  1   2   3   2  55   0   8]
- [ 10   1   3   2   1  42   6]
- [ 14   2  10   6   9  12  75]]
-Node Classification on random seed  595 -> 0.652
-Confusion Matrix:
- [[ 71   1   0  11   3   2  10]
- [  5 125   2   8  10   1   3]
- [ 27  16 154  31  30  16  31]
- [ 25   5  12 106   6   2   8]
- [  1   6   6   0  65   0   1]
- [  5   0   2   9   0  50   4]
- [ 18   3   6   4   7  11  81]]
-Node Classification on random seed  596 -> 0.604
-Confusion Matrix:
- [[ 56   2   2   9   4  23   9]
- [ 12 125   4   4   4   2   2]
- [ 24  33 147  49  33  20  27]
- [ 14   5  10  99   2  13   6]
- [  3  10   0   1  59   1   5]
- [  3   1   5   4   4  34   3]
- [ 14   4   8   3   5   9  84]]
-Node Classification on random seed  597 -> 0.579
-Confusion Matrix:
- [[ 66   2   5   5   2  11   8]
- [  7 118   7   4  13   8   2]
- [ 39  13 126  35  35  15  40]
- [ 21   1  23  82   8  10  14]
- [  3   7   0   0  68   3   0]
- [ 12   0   0   1   1  48   3]
- [ 17   4   8  12   9  13  71]]
-Node Classification on random seed  598 -> 0.582
-Confusion Matrix:
- [[ 64   2  11   8   9  13  11]
- [  6 132   5   2   6   3   3]
- [ 21  20 112  30  32  29  53]
- [ 12   2  16  97   5   3  21]
- [  3  11   6   2  60   1   4]
- [ 10   2   1   2   0  50   3]
- [ 18   2   9   7   7   7  67]]
-Node Classification on random seed  599 -> 0.614
-Confusion Matrix:
- [[ 68   1  10   3   3  13  13]
- [  5 104   2   1  19   1   5]
- [ 29  27 160  17  20  46  23]
- [ 19   1  20 109   6   2  12]
- [  0   8   3   1  52   2   4]
- [  3   1   0   0   2  38  12]
- [ 14   1   5   9   6  17  83]]
-Node Classification on random seed  600 -> 0.644
-Confusion Matrix:
- [[ 74   2   2   2   2   8  22]
- [  5 147   4   0   7   2   2]
- [ 14  27 154  30  19  21  34]
- [  6   5  21  92  11   2  13]
- [  2   5   3   0  57   1   3]
- [  7   0   2   1   1  43   3]
- [ 19   2  12  15   7  12  77]]
-Node Classification on random seed  601 -> 0.597
-Confusion Matrix:
- [[ 77   1   0   1  19  10   4]
- [  8 127   5   2   5   3   5]
- [ 32  48 122  40  21  11  29]
- [ 15   3  20 101   9   4  10]
- [  3  10   2   4  59   2   1]
- [  3   3   4   4   2  41   7]
- [ 11   7   4   5   9  17  70]]
-Node Classification on random seed  602 -> 0.588
-Confusion Matrix:
- [[ 57   2   2   5   5  16  10]
- [  5 124   6   0  16   1   5]
- [ 16  13 130  36  55  19  35]
- [  9   3  15  90   8  15  13]
- [  2   4   7   1  60   1   3]
- [  7   1   3   1   2  51   4]
- [ 13   4  14  10   8  17  76]]
-Node Classification on random seed  603 -> 0.628
-Confusion Matrix:
- [[ 69   5   0   3   7   6  10]
- [  5 117   6   6  10   1   5]
- [ 25  12 162  50  29  15  39]
- [ 12   3  16 114   8   5  12]
- [  0   7   2   2  49   0   3]
- [  6   1   3   1   2  43   7]
- [ 14   4   6  10   4  10  74]]
-Node Classification on random seed  604 -> 0.642
-Confusion Matrix:
- [[ 68   4   4   5   4  13  15]
- [  8 131   6   6   1   1   3]
- [ 25  19 152  27  20  19  36]
- [  9   2  12 112   7   8  15]
- [  1  10   4   1  56   1   0]
- [  6   2   8   0   1  50   1]
- [  7   3   9   4   9  22  73]]
-Node Classification on random seed  605 -> 0.619
-Confusion Matrix:
- [[ 73   6  10   3   2   8   9]
- [  3 131  13   0   8   8   3]
- [ 29  13 133  41  22  25  33]
- [ 11   4  11 107   3   7  18]
- [  3   5   9   3  62   0   1]
- [  8   0   0   0   2  47   8]
- [ 15   2   4  11   4  16  66]]
-Node Classification on random seed  606 -> 0.616
-Confusion Matrix:
- [[ 68   3   9   9   3   9  14]
- [  2 122  12   3  11   5   6]
- [ 28   6 140  32  25  27  51]
- [  6   1   2 102   5  15  12]
- [  2   9   3   0  56   0   5]
- [  3   2   2   3   0  46  10]
- [ 14   1   3  10   4  17  82]]
-Node Classification on random seed  607 -> 0.614
-Confusion Matrix:
- [[ 81   1   5   6   5  11   3]
- [  3 119   5   1  15   1  12]
- [ 21  23 126  24  49  45  25]
- [  9   2  10  97   3   9  12]
- [  0   2   3   3  71   0   3]
- [  5   3   2   1   0  47   3]
- [ 16   2   8   9   6  20  73]]
-Node Classification on random seed  608 -> 0.624
-Confusion Matrix:
- [[ 64   2   7   7   2  11   9]
- [  5 146   7   4   5   2   4]
- [ 18  47 138  24  21  18  48]
- [ 12   3  13  97   6   6  16]
- [  0   9   3   3  51   1   1]
- [  6   0   0   1   0  46   5]
- [  6   6  13   8   5  12  82]]
-Node Classification on random seed  609 -> 0.608
-Confusion Matrix:
- [[ 83   6   4   6   2   6  10]
- [  1 123   5   3   7   4  11]
- [ 28  24 138  28  32  17  52]
- [  4  17  13 107   2   2  11]
- [  2   4   4   3  50   1   4]
- [  7   4   0   0   0  41   6]
- [ 20   5   7   4  14  12  66]]
-Node Classification on random seed  610 -> 0.617
-Confusion Matrix:
- [[ 62   0  11   7   2  15  11]
- [  8 122   9   2   4   3   9]
- [ 20  29 156  25  23  19  40]
- [ 11   5  15 106   6   5  14]
- [  4   7   4   1  59   2   3]
- [  4   0   7   1   0  34   5]
- [  8   2  14   9   7  12  78]]
-Node Classification on random seed  611 -> 0.581
-Confusion Matrix:
- [[ 70   2  12  13   3  13  11]
- [  9 103   9   4  15   3   5]
- [ 23  33 132  28  25  28  32]
- [ 11   2  23  89   2  10   7]
- [  2   6   4   1  61   1   0]
- [  6   1   2   1   0  60   6]
- [ 16   3  16   9  10  12  66]]
-Node Classification on random seed  612 -> 0.645
-Confusion Matrix:
- [[ 73   2   4   4   4  12   4]
- [  2 129   2   0  10   1  12]
- [ 32  24 130  24  22  18  41]
- [  4   4  12 121   7   5  18]
- [  3   6   6   2  59   0   2]
- [  1   2   0   4   0  51   2]
- [ 18   1   6   9   9  16  82]]
-Node Classification on random seed  613 -> 0.605
-Confusion Matrix:
- [[ 78   5   5   6   5  15  11]
- [  5 125   3   6   1   4   6]
- [ 32  26 128  35  20  18  50]
- [  7   1  24 113   1   4  13]
- [  2   7   7   1  55   0   3]
- [ 12   1   2   3   0  39   4]
- [ 16   2  11   5   4  12  67]]
-Node Classification on random seed  614 -> 0.629
-Confusion Matrix:
- [[ 77   6   3   3   4  11  16]
- [  5 121  11   1   8   6   2]
- [ 27  19 151  34  26  14  40]
- [ 10   4  13 120   6   3  13]
- [  2   6   6   1  58   4   0]
- [  3   2   2   1   0  33   5]
- [  6   7   7   7  12  15  69]]
-Node Classification on random seed  615 -> 0.628
-Confusion Matrix:
- [[ 66   5   4  10   5  20  12]
- [  8 139   3   0   6   1   2]
- [ 23  16 141  30  13  34  40]
- [ 11   5  18 100   3  10   8]
- [  1   8   6   1  73   2   3]
- [  7   0   3   0   0  42   3]
- [ 10   1   5   8   7  20  67]]
-Node Classification on random seed  616 -> 0.633
-Confusion Matrix:
- [[ 53   3   6  22   0  14   5]
- [  6 151   5   1   3   1   2]
- [ 22  27 142  23  35  32  33]
- [ 15   2  10 111   7   5   4]
- [  1   8   2   0  70   1   2]
- [  3   2   1   5   0  46   6]
- [  9   6   4  18   7   9  60]]
-Node Classification on random seed  617 -> 0.617
-Confusion Matrix:
- [[ 72   3   2   4   3  12   7]
- [  4 130   7   3   7   2   4]
- [ 21  11 131  61  33  16  41]
- [ 10   2   9 114   8   5  16]
- [  0   4   6   3  57   1   5]
- [ 14   0   3   1   0  45   2]
- [  8   2   9  13   5  16  68]]
-Node Classification on random seed  618 -> 0.621
-Confusion Matrix:
- [[ 54   1   6  12   5  10  20]
- [  2 125   6   3   5   5   2]
- [ 19  26 177  27  28  25  32]
- [ 24   1  22  87  10   8   9]
- [  4  10   3   1  58   0   2]
- [  4   0   3   1   1  41   3]
- [  5   4   5   8   2  15  79]]
-Node Classification on random seed  619 -> 0.614
-Confusion Matrix:
- [[ 81   1   5   5   8  12  16]
- [  5 128   3   3   2   2   3]
- [ 31  25 131  28  22  21  34]
- [  9   1  23  96  12   9  17]
- [  1   6   6   1  59   0   2]
- [  6   2   4   3   0  38   6]
- [  9   3   8  15   7  10  81]]
-Node Classification on random seed  620 -> 0.617
-Confusion Matrix:
- [[ 78   3   1   4   6   7  15]
- [  2 130   4   1  11   3  10]
- [ 12  20 146  30  23  23  35]
- [  7   2  20  98   3   8  21]
- [  2   8   3   2  59   1   2]
- [  9   0   0   2   4  43   4]
- [ 16   4  11   9  14  21  63]]
-Node Classification on random seed  621 -> 0.601
-Confusion Matrix:
- [[ 70   1   2  10   4   9   7]
- [  3 122   6   4   7   3   3]
- [ 31  12 122  52  32  17  43]
- [ 12   2  18  98   6  12  18]
- [  2  13   2   1  67   1   2]
- [  8   0   1   1   0  43   3]
- [ 14   2   4   9   9  13  79]]
-Node Classification on random seed  622 -> 0.637
-Confusion Matrix:
- [[ 79   2  19   8   0   9   5]
- [  6 125   3   2  12   2   3]
- [ 21  24 133  45  20  19  21]
- [  7   2  21 110   4   3  18]
- [  2   7   2   1  66   2   2]
- [ 10   0   1   0   1  54   5]
- [ 24   2   8   4   4  12  70]]
-Node Classification on random seed  623 -> 0.617
-Confusion Matrix:
- [[ 73   0   5   2   5   6  13]
- [  2 123   5   0  17   2   0]
- [ 19  16 155  30  51  23  31]
- [ 11   4  14  80   4   3  21]
- [  1   3   4   4  75   0   0]
- [  8   0   7   3   1  30   7]
- [ 10   1   9   4  26  11  81]]
-Node Classification on random seed  624 -> 0.647
-Confusion Matrix:
- [[ 81   7   2   8   5   5   9]
- [  5 138   3   2   4   2   7]
- [ 32  21 147  38  18  23  33]
- [  7   6  12  97   3   2  10]
- [  1   7   0   2  51   1   3]
- [  7   2   0   3   0  49   2]
- [ 19   3   5  17   1  16  84]]
-Node Classification on random seed  625 -> 0.599
-Confusion Matrix:
- [[ 83   2   3   9   5   9   6]
- [  4 135  12   0   4   1   7]
- [ 29  26 115  41  33  27  51]
- [ 21   5  13  92   7   6  11]
- [  1  13   2   0  56   1   3]
- [  9   0   2   3   0  39   1]
- [  8   7   3   3   5   8  79]]
-Node Classification on random seed  626 -> 0.645
-Confusion Matrix:
- [[ 85   1   6   7   3   5   2]
- [  2 123   6   5   6   0   3]
- [ 14  31 139  36  23  23  33]
- [  3   2  22 123   9   2   9]
- [  1  10   2   1  59   0   4]
- [  4   3   6   2   1  44   7]
- [  8   5  12  18   8  10  72]]
-Node Classification on random seed  627 -> 0.578
-Confusion Matrix:
- [[ 68   7   6   4   4  14  14]
- [  6 112   3   0   8   6   7]
- [ 28  28 114  40  40  16  49]
- [  7   3   5 114   7   6  14]
- [  2   7   3   1  57   0   4]
- [  2   0   6   2   1  48  13]
- [ 11   4  18   8   4  14  65]]
-Node Classification on random seed  628 -> 0.664
-Confusion Matrix:
- [[ 77   2   4   1   3  13  13]
- [  6 141   2   3   5   2   1]
- [ 37  26 150  14  26  19  36]
- [  7   3  13 116   5  11   8]
- [  0   5   4   0  53   1   2]
- [  5   0   6   0   0  49   3]
- [ 15   4   8   8   2  13  78]]
-Node Classification on random seed  629 -> 0.597
-Confusion Matrix:
- [[ 77   5   2   5   5  12   5]
- [  6 134   5   2   5   1   5]
- [ 30  42 114  32  52  29  26]
- [  4   1  19 101   1   7  10]
- [  0   7   2   2  59   1   0]
- [  9   2   1   1   1  43   5]
- [ 11   3  18   5   8  16  69]]
-Node Classification on random seed  630 -> 0.61
-Confusion Matrix:
- [[ 60   2   3   1   1  16  24]
- [  3 131   9   2   3   3   3]
- [ 17  16 141  46  18  26  35]
- [  7   1  14 107   5   7  23]
- [  5   3   6   2  57   2   6]
- [  7   1   9   2   0  39   8]
- [  6   2  10   6   6  24  75]]
-Node Classification on random seed  631 -> 0.613
-Confusion Matrix:
- [[ 72   4   3   4   0   8  14]
- [  6 138  12   3   4   1   1]
- [ 22  13 106  40  37  18  52]
- [  1   3  17 120   4   5  17]
- [  1   7   5   0  53   0   3]
- [  4   3   1   0   1  46   7]
- [ 10   3  16  12   7  18  78]]
-Node Classification on random seed  632 -> 0.641
-Confusion Matrix:
- [[ 67   4   6   3   5   9   8]
- [  6 128   7   4   4   2   2]
- [ 21  21 165  21  24  20  44]
- [  8   3  14 102   5   8  16]
- [  4  11   3   1  65   1   0]
- [  8   2   5   2   0  37   4]
- [ 18   1   8   4   6  16  77]]
-Node Classification on random seed  633 -> 0.61
-Confusion Matrix:
- [[ 62   2   2   2   4  12  16]
- [  5 125   2   2  10   2   5]
- [ 26  16 136  43  33  24  56]
- [ 10   1   2 110   1   8  16]
- [  4   6   6   1  54   0   5]
- [  2   2   1   2   0  44  11]
- [ 10   7  11   9   3  10  79]]
-Node Classification on random seed  634 -> 0.567
-Confusion Matrix:
- [[ 43   5   6  13   5  14  13]
- [  3 135   3   3   9   3   6]
- [ 23  30 135  46  38  21  33]
- [  9   5  11  96  10   4  13]
- [  5  10   7   1  47   2   1]
- [ 10   0   0   2   0  43   4]
- [ 19   6  10  12   5  13  68]]
-Node Classification on random seed  635 -> 0.587
-Confusion Matrix:
- [[ 54   1   8   6   2  14  22]
- [  5 120   7   5   8   2  12]
- [ 20  21 131  57  16  28  46]
- [ 11   4  12 110  10   6  14]
- [  1  10   9   0  48   1   1]
- [  3   0   6   1   1  41   4]
- [  8   1  10   8   3   9  83]]
-Node Classification on random seed  636 -> 0.648
-Confusion Matrix:
- [[ 81   1   2   6   3  15   6]
- [  6 129   1   6   2   7   2]
- [ 24  42 143  22  31  28  22]
- [ 13   1  13 112   4   6  16]
- [  1   8   2   0  62   1   1]
- [  2   4   0   0   5  40   2]
- [  9   4   8   4   1  21  81]]
-Node Classification on random seed  637 -> 0.595
-Confusion Matrix:
- [[ 59  11   1   4   4  10  15]
- [  6 136   7   1   7   2   2]
- [ 44  22 129  34  37  30  32]
- [ 13   4  14  93   5   5  12]
- [  2   9   2   0  58   0   1]
- [  5   1   4   1   2  46   3]
- [ 15   4  10  10   3  11  74]]
-Node Classification on random seed  638 -> 0.63
-Confusion Matrix:
- [[ 66   4   7   3   5   4  10]
- [  2 129   4   1   8   2   7]
- [ 22  25 153  33  27  17  38]
- [ 12   7  11  96   1   2  26]
- [  1   5   7   0  67   1   1]
- [  5   3   5   0   1  52   6]
- [ 12   3   6   8  12  16  67]]
-Node Classification on random seed  639 -> 0.602
-Confusion Matrix:
- [[ 73   6   2   0   4  18   6]
- [  7 133   3   5   6   6   4]
- [ 30  13 145  39  52  14  30]
- [  7   2  12  97  11   8  14]
- [  2   5   2   7  54   4   2]
- [  9   2   1   1   0  34   9]
- [ 20   4   6   8   6  11  66]]
-Node Classification on random seed  640 -> 0.566
-Confusion Matrix:
- [[ 87   3   2   3   3   5   4]
- [  6 114   7   2  13   3   6]
- [ 35  23 115  43  20  25  45]
- [ 22   7   9  72   8  30  15]
- [  3   8   0   0  51   4   7]
- [ 11   0   1   3   0  46   3]
- [ 10   5  12   7   2  19  81]]
-Node Classification on random seed  641 -> 0.59
-Confusion Matrix:
- [[ 53   2  10   4   5  16  11]
- [  3 120   8   1  23   1   2]
- [ 34  17 132  42  37  21  20]
- [  9   9  13  89  23  11   8]
- [  2   9   4   0  68   0   1]
- [  4   0   3   2   2  45   9]
- [  7   2  13   1   9  12  83]]
-Node Classification on random seed  642 -> 0.629
-Confusion Matrix:
- [[ 68   3   3   3   7  12  13]
- [  1 115   7   1   4   6   2]
- [ 18  12 150  37  34  22  50]
- [  9   3  18  94  12   7  11]
- [  2   2   3   2  69   1   1]
- [  3   1   1   3   1  55   4]
- [  6   6   3  13  14  10  78]]
-Node Classification on random seed  643 -> 0.592
-Confusion Matrix:
- [[ 64   2  10   0   6   9  23]
- [  2 121   3   4  13   0   2]
- [ 28   7 134  54  17  24  39]
- [ 17   4  19  97   8   6  19]
- [  0   5   4   4  60   0   2]
- [  5   0   2   1   1  50   5]
- [ 14   5   9   9   4  22  66]]
-Node Classification on random seed  644 -> 0.615
-Confusion Matrix:
- [[ 45   7   4   8   9   8  24]
- [  1 142   3   3   6   1   2]
- [ 35  21 135  43  22  16  35]
- [  6   4  18 112   2   3   9]
- [  3   4   5   3  57   0   5]
- [  8   1   2   4   1  42   3]
- [ 10   4   5  13   7  17  82]]
-Node Classification on random seed  645 -> 0.598
-Confusion Matrix:
- [[ 67   4   6   8   6  12  10]
- [  4 132  12   2   3   5   1]
- [ 23  31 125  37  40  15  41]
- [ 13   4  11  98   7   3   4]
- [  0  11   2   0  59   0   1]
- [ 10   4   2   1   0  47   5]
- [ 15   6   8   6  12  17  70]]
-Node Classification on random seed  646 -> 0.614
-Confusion Matrix:
- [[ 78   1   1   2   1  23   8]
- [ 10 122   2   3   3   0   1]
- [ 14  38 137  51  18  25  29]
- [ 13  20  20  94   4   7  11]
- [  0   4   3   1  55   0   0]
- [  7   0   2   3   1  55   7]
- [  8   2   5   9   7  22  73]]
-Node Classification on random seed  647 -> 0.563
-Confusion Matrix:
- [[ 64   9   5   5   8  10   6]
- [  5  98  10   4  20   3   6]
- [ 34  15 149  29  31  22  45]
- [ 11  16   8  85  21  10  13]
- [  2   7   5  10  45   0   7]
- [  7   4   1   2   0  46   1]
- [  9   4   3  11   4  14  76]]
-Node Classification on random seed  648 -> 0.588
-Confusion Matrix:
- [[ 68   7   4   2   3  12  12]
- [  7 117   7   2  11   6   7]
- [ 32  19 118  23  32  25  46]
- [ 12   5  11  99   9  12  16]
- [  4   8   3   0  59   1   4]
- [  9   4   2   0   1  45   4]
- [  4   5  17   4  12   8  82]]
-Node Classification on random seed  649 -> 0.596
-Confusion Matrix:
- [[ 60   3   3   8   2  10  18]
- [  4 113   7   0  11   4   4]
- [ 16  28 145  26  23  31  36]
- [ 11   4  25  90   7  12  24]
- [  1   6   5   1  62   1   4]
- [  6   1   3   1   0  52   0]
- [  6   2  11   2   9  28  74]]
-Node Classification on random seed  650 -> 0.648
-Confusion Matrix:
- [[ 66   2   1  10   6  21  13]
- [  1 134   2   5   8   4   4]
- [ 24  37 161  25  22  17  27]
- [  6   8  17 114   2   1  18]
- [  1   2   4   7  51   0   1]
- [  2   2   2   1   0  46   4]
- [ 15   3  10   1   4  12  76]]
-Node Classification on random seed  651 -> 0.636
-Confusion Matrix:
- [[ 82   2   1  12   7   4  16]
- [  4 115   2   2   9   4   5]
- [ 20  27 146  36  27  25  25]
- [ 14   4  12  99   1   5  23]
- [  1   6   5   0  61   1   1]
- [  9   0   1   0   0  55   7]
- [  8   2   5   8  13  10  78]]
-Node Classification on random seed  652 -> 0.58
-Confusion Matrix:
- [[ 63   6   9   3   4  12   5]
- [  3 127  12   3   3   1   1]
- [ 34  36 106  38  41  36  30]
- [ 11   9  19  97  10   9   6]
- [  1   5   7   4  55   2   1]
- [  4   4   2   2   1  49   3]
- [  4   2  12   5   4  16  83]]
-Node Classification on random seed  653 -> 0.621
-Confusion Matrix:
- [[ 89   6   3   4   3  10   5]
- [  3 128   5   4   5   4   6]
- [ 28  26 142  37  24  22  28]
- [ 17   5  26  85   6   7  13]
- [  7   9   4   1  59   0   1]
- [  4   1   3   1   0  47   2]
- [ 15   3   7   2   6  16  71]]
-Node Classification on random seed  654 -> 0.569
-Confusion Matrix:
- [[ 52   3   5   7   7   9  14]
- [ 13 117  21   5   5   1   2]
- [ 26  27 128  37  20  18  53]
- [ 11   6   7  96   7   9  12]
- [  4   3   4   3  64   6   4]
- [  5   0   0   2   0  46   8]
- [ 12   1  15   8   7  24  66]]
-Node Classification on random seed  655 -> 0.631
-Confusion Matrix:
- [[ 77   1   3   0   0  20   1]
- [  1 146   4   2   4   5   3]
- [ 33  35 145  43  25  28  15]
- [ 11   1  11 101  11   9   8]
- [  1   8   2   3  63   1   0]
- [  9   1   2   1   0  36   2]
- [ 17   4  14   9   2  19  63]]
-Node Classification on random seed  656 -> 0.575
-Confusion Matrix:
- [[ 63   0   4   3   5  25   8]
- [  3 123   4   0  11   1   6]
- [ 30  20 139  26  33  28  42]
- [ 18   5  24  86   4   9  13]
- [  5   9   5   0  56   1   6]
- [  9   5   2   2   1  43   4]
- [ 11   6   2  12   6  17  65]]
-Node Classification on random seed  657 -> 0.628
-Confusion Matrix:
- [[ 59   7   4   5   6  23   7]
- [  5 134   2   5   5   8   2]
- [ 21  17 135  36  22  25  36]
- [ 13   6  11 103   3   2  15]
- [  1   5   5   5  61   2   2]
- [  7   0   6   1   5  47   4]
- [ 17   4   5   4   6   7  89]]
-Node Classification on random seed  658 -> 0.604
-Confusion Matrix:
- [[ 69   1   4   3   2   0  17]
- [  6 125   3   0  12   2   4]
- [ 30  21 157  32  26  21  42]
- [ 12   2  16 103  11   8  22]
- [  4   7   6   1  46   6   2]
- [  5   1   2   6   5  31  10]
- [ 13   3   8   1   5  14  73]]
-Node Classification on random seed  659 -> 0.595
-Confusion Matrix:
- [[ 67   1   0   5   4  12  11]
- [  2 119  10   1  11   1   5]
- [ 30  18 115  45  32  19  51]
- [  9   2  16  99  10   3  14]
- [  1   3   9   0  61   2   4]
- [  3   3   1   1   1  54   4]
- [ 15   5  11   7  12  11  80]]
-Node Classification on random seed  660 -> 0.577
-Confusion Matrix:
- [[ 75   7   4   2   1  14  14]
- [  3 118   5   0   8   5   8]
- [ 32  25 113  51  31   9  45]
- [ 14   7  20  90   6   5   8]
- [  3   4   2   0  60   0   3]
- [  3   1   1   2   3  36  11]
- [ 10   5  15  16   8  12  85]]
-Node Classification on random seed  661 -> 0.58
-Confusion Matrix:
- [[ 76   1   2   9   6  10  13]
- [  8 111   3   1  13   3   5]
- [ 34  19 127  46  39  42  34]
- [  3   5  12  98  10   4  21]
- [  1   7   3   1  51   1   2]
- [  3   1   1   1   2  44   6]
- [  4   6  10   1  15  12  73]]
-Node Classification on random seed  662 -> 0.648
-Confusion Matrix:
- [[ 76   3   4   8   2  17   6]
- [  3 121   3   4  12   7   4]
- [ 37  11 156  31  24  24  39]
- [  3   2  13 115   6  11   7]
- [  0   4   4   3  54   2   1]
- [  3   0   2   0   3  48   2]
- [ 11   4   7   5   6  14  78]]
-Node Classification on random seed  663 -> 0.588
-Confusion Matrix:
- [[ 71   1   1   9   5   6   6]
- [  3 143   2   0   6   3   5]
- [ 37  39 109  38  30  25  28]
- [ 35   7  11  96   5   7   7]
- [  1   3   6   3  59   1   6]
- [  2   0   2   2   0  47  10]
- [ 12   2   6  18   5  17  63]]
-Node Classification on random seed  664 -> 0.604
-Confusion Matrix:
- [[ 91   0   3   6   1  15   6]
- [  6 123   5   5   5   1   6]
- [  7  22 119  45  43  17  54]
- [ 11   4  10 103   9   7  18]
- [  2   5   3   3  51   1   3]
- [  6   3   1   1   0  42   8]
- [  5   3  14   5   6  21  75]]
-Node Classification on random seed  665 -> 0.603
-Confusion Matrix:
- [[ 79   3   4   8   2   7   4]
- [  2 126   1   1  10   1   4]
- [ 29  11 134  34  36  22  57]
- [ 14   8   6  89   5  11  19]
- [  2   7   3   5  64   0   2]
- [ 18   0   0   1   0  41   5]
- [ 11   3   0  18   3  20  70]]
-Node Classification on random seed  666 -> 0.617
-Confusion Matrix:
- [[ 78   7   7   2  10  13   2]
- [  5 123   4   0   3   5   6]
- [ 31  28 119  38  34  26  34]
- [ 15   4  14 103   4   4   7]
- [  1   6   5   3  60   0   0]
- [  5   1   4   0   0  54   1]
- [ 16   0   6   7   8  17  80]]
-Node Classification on random seed  667 -> 0.588
-Confusion Matrix:
- [[ 69   4   5   7   5   8  13]
- [  3 116   2   1   9   6   5]
- [ 14  17 122  42  65  33  44]
- [ 14   1  15  94   5   7  10]
- [  2   2   3   3  60   0   3]
- [  9   2   4   2   1  47   3]
- [ 10   4   4   8   6  11  80]]
-Node Classification on random seed  668 -> 0.588
-Confusion Matrix:
- [[ 72   3   6  13   2  14  10]
- [  8 105   2   5  10   1   1]
- [ 23  27 147  26  16  28  52]
- [ 11   3  14  92   6  11  12]
- [  2  13   5   2  51   1   3]
- [  3   1   6   0   1  51   2]
- [ 16   5   8  11  10  19  70]]
-Node Classification on random seed  669 -> 0.634
-Confusion Matrix:
- [[ 80   5   0   2   4  12  11]
- [  7 143   6   2   4   2   4]
- [ 18  28 157  23  23  20  45]
- [ 13   2  22  79   9   7  11]
- [  1  11   3   1  51   0   3]
- [  5   1   2   1   0  36  14]
- [ 17   6   3   2   7   9  88]]
-Node Classification on random seed  670 -> 0.652
-Confusion Matrix:
- [[ 83   3   2   3   5   9   8]
- [  5 145   2   0   5   2   7]
- [ 24  37 155  22  30  16  36]
- [ 25   0  16  98   6   0   6]
- [  1  12   4   0  63   0   3]
- [ 12   1   3   2   0  38   5]
- [ 17   3   7   3   2   4  70]]
-Node Classification on random seed  671 -> 0.635
-Confusion Matrix:
- [[ 69   0   3   3   0   8   7]
- [  0 107   8   3  15   1  10]
- [ 19  12 168  48  25  28  23]
- [ 10   1  14 111   7  12  15]
- [  2   4   4   7  60   5   0]
- [  6   0   0   0   0  48   3]
- [ 18   3   9  15   6  11  72]]
-Node Classification on random seed  672 -> 0.633
-Confusion Matrix:
- [[ 66   2   2   4   5   8  21]
- [  6 118   5   2   7   1   2]
- [ 13  25 151  33  34  23  37]
- [ 11   4   7 113   5   5  12]
- [  1  10   3   0  70   0   3]
- [  3   1   2   3   0  47   9]
- [ 11   5  10  14   2  16  68]]
-Node Classification on random seed  673 -> 0.633
-Confusion Matrix:
- [[ 85   5   3   1   3   7  14]
- [  8 125   3   1  10   2   9]
- [ 17  19 145  34  21  22  48]
- [  3   6  16  95   1   8  15]
- [  0   7   5   1  69   1   3]
- [  4   5   3   2   0  40   3]
- [  8   4  20   2   7  16  74]]
-Node Classification on random seed  674 -> 0.55
-Confusion Matrix:
- [[ 54   0  10  10   2  15  10]
- [  5 134  14   1   3   2   9]
- [ 33  28 108  37  24  34  46]
- [ 23   3  14  91   3   8  13]
- [  2   8   4   0  60   0   5]
- [  8   2   4   5   1  37   6]
- [  8   0  16   6   7  21  66]]
-Node Classification on random seed  675 -> 0.609
-Confusion Matrix:
- [[ 80   4   7   1   5   7   8]
- [  8 120   7   2   6   6   3]
- [ 20  20 126  27  33  28  37]
- [  5   3  17 114   6   7  22]
- [  0   3   3   0  54   0   1]
- [  4   0   2   1   1  46   7]
- [  8   2  11  18  17  24  69]]
-Node Classification on random seed  676 -> 0.601
-Confusion Matrix:
- [[ 66   3   8   2   4  12   5]
- [  6 115  13   0  17   2   5]
- [ 26  13 153  25  42  28  31]
- [ 10   6  27  87   4   5  13]
- [  1   2   3   0  63   0   2]
- [  6   4   2   4   1  39   4]
- [ 10   4  12   7  10  20  78]]
-Node Classification on random seed  677 -> 0.605
-Confusion Matrix:
- [[ 63   0   7   4   5  32   5]
- [  3 130   8   4   5   3  10]
- [ 25  26 137  30  26  14  51]
- [ 10   1  14  95   5   3  15]
- [  2   4   2   2  68   1   5]
- [  7   1   3   1   1  36  11]
- [ 17   5   7   8   2  10  76]]
-Node Classification on random seed  678 -> 0.583
-Confusion Matrix:
- [[ 77   1   2   5   7  10   5]
- [  6 115   1   5  10   1   0]
- [ 31  15 116  68  27  20  34]
- [ 16   2  24  97   4   1  26]
- [  3   3   9   2  67   0   0]
- [ 11   0   2   3   2  43   2]
- [ 18   3   8   2  17  11  68]]
-Node Classification on random seed  679 -> 0.627
-Confusion Matrix:
- [[ 77   2   2  10   4   9   5]
- [  5 130   2   4   6   3   6]
- [ 15  21 148  31  32  30  44]
- [ 16   2  16 106   6   8  10]
- [  0   7   4   3  64   0   0]
- [  6   0   1   5   4  37   0]
- [ 13   0   6   4  13  18  65]]
-Node Classification on random seed  680 -> 0.601
-Confusion Matrix:
- [[ 70   6   2   0   3  10  19]
- [  4 124   8   4   4   1   0]
- [ 21  14 129  33  26  38  50]
- [  5   6  17 113   5   4  20]
- [  3  10   4   2  54   1   2]
- [ 11   3   4   4   0  40   6]
- [ 13   4   3   2   8  19  71]]
-Node Classification on random seed  681 -> 0.622
-Confusion Matrix:
- [[ 71   3   5   6   1   5  19]
- [  4 121   4   3   8   3   8]
- [ 24   8 131  20  50  18  59]
- [  6   4  15  99   5   8  18]
- [  1   6   2   0  64   3   1]
- [  6   2   2   1   0  47   6]
- [ 10   2   3  10   5  14  89]]
-Node Classification on random seed  682 -> 0.613
-Confusion Matrix:
- [[ 64   6   3  10   5   8   9]
- [  8 124   7   1   9   4   1]
- [ 19  34 123  46  38  15  42]
- [ 10   3  12 114   8   3  11]
- [  2   8   3   4  53   0   2]
- [  6   0   2   5   2  52   2]
- [  6   4   9   6   3  11  83]]
-Node Classification on random seed  683 -> 0.604
-Confusion Matrix:
- [[ 79   4  15   9   7  14   3]
- [  7 122   8   4   1   6   1]
- [ 22  25 131  63  16  22  29]
- [ 23   2   8  92   2   4  13]
- [  0   6   9   2  55   1   1]
- [  1   0   8   5   4  43   6]
- [ 12   3   8   6   6  10  82]]
-Node Classification on random seed  684 -> 0.6
-Confusion Matrix:
- [[ 77   5   8   2   6   3   4]
- [  9 128   7   5  11   0   4]
- [ 28  22 132  57  23  16  46]
- [ 21   3   6 110   0   4  11]
- [  0   3   1   1  52   0   5]
- [  2   4   8   4   2  42   3]
- [ 11   3  13  13   5  21  59]]
-Node Classification on random seed  685 -> 0.603
-Confusion Matrix:
- [[ 68   3   2   4   3  11  11]
- [  5 119   5   4   9   4   1]
- [ 20  25 137  30  56  22  39]
- [  4   8   9 108  12   3  11]
- [  1   6   2   0  59   0   3]
- [  3   5   4   2   0  38   6]
- [ 11   4   8  10  15  16  74]]
-Node Classification on random seed  686 -> 0.624
-Confusion Matrix:
- [[ 87   4   3   6   7   5   4]
- [  1 127   5   2  17   4   3]
- [ 37  13 138  31  29  23  32]
- [  4   7  19 102   6   6  15]
- [  1   3   3   0  60   1   1]
- [  7   4   2   2   1  35   2]
- [ 22   3   5  12   9  15  75]]
-Node Classification on random seed  687 -> 0.601
-Confusion Matrix:
- [[ 52   6   2   9   6  16  19]
- [  8 126   4   3   3   1   6]
- [ 31  32 141  53  17  18  23]
- [  9   9  13 111   5   5   8]
- [  2   8   7   4  58   1   2]
- [ 10   0   2   1   0  35   9]
- [  8   1  17   4   7  10  78]]
-Node Classification on random seed  688 -> 0.617
-Confusion Matrix:
- [[ 78   0   6   4   2   8   8]
- [ 17 116   6   5   7   9   7]
- [ 17  31 150  19  40  20  49]
- [  7   5  21  95   2   3  10]
- [  0   8   4   0  57   2   0]
- [  5   1   3   0   2  52   4]
- [ 12   7   4   5   6  17  69]]
-Node Classification on random seed  689 -> 0.61
-Confusion Matrix:
- [[ 51   2   3   9   3  10  19]
- [  5 148   8   2   6   5   2]
- [ 19  20 153  34  16  32  46]
- [  7  10  19  98   8   4  16]
- [  2  11   4   0  48   1   4]
- [  8   0   4   2   1  39   3]
- [  5   4   7   1  11  17  73]]
-Node Classification on random seed  690 -> 0.569
-Confusion Matrix:
- [[ 69   1   4   4   4  15  12]
- [  6 128   6   4  10   9   2]
- [ 24  22 113  42  22  36  51]
- [ 30   7   3  93   9   8   8]
- [  0   8   7   1  57   1   2]
- [  7   1   1   1   0  47   3]
- [ 17   2   6   5   9  21  62]]
-Node Classification on random seed  691 -> 0.635
-Confusion Matrix:
- [[ 89   1   8   7   4   7   6]
- [  6 113   6   2  14   3   8]
- [ 32  16 150  22  40  17  24]
- [ 10   1  18 106   9   1   7]
- [  1   3   6   4  64   0   6]
- [  7   2   1   0   3  49   3]
- [ 13   3  16  10   7  11  64]]
-Node Classification on random seed  692 -> 0.612
-Confusion Matrix:
- [[ 41   5   2   9   7  18  22]
- [  7 127   2   2   9   5   1]
- [ 15  14 136  41  25  29  48]
- [ 10   7  16 112   3   4  16]
- [  3  10   3   3  54   0   1]
- [  3   2   5   0   0  42   8]
- [  7   4   4   0   4  14 100]]
-Node Classification on random seed  693 -> 0.609
-Confusion Matrix:
- [[ 61   2   3   5   2  10  24]
- [  4 121   7   4   0   3   6]
- [ 15  21 161  36  17  27  45]
- [ 12   6  26 102  10   5  12]
- [  3   7   7   2  58   2   5]
- [  7   0   5   4   1  35   2]
- [ 11   3  12   3   4  11  71]]
-Node Classification on random seed  694 -> 0.631
-Confusion Matrix:
- [[ 75   5   8   4   1   9  13]
- [  4 125   6   1   7   8   2]
- [ 14  26 141  24  26  31  49]
- [  6   8  18 115   4   5  14]
- [  0   3   8   0  58   0   1]
- [  1   2   2   2   3  50   9]
- [ 11   1   6   4   8  15  67]]
-Node Classification on random seed  695 -> 0.582
-Confusion Matrix:
- [[ 77   0  12  10   5   3   6]
- [  7 114   4   1  14   4   5]
- [ 31  26 135  39  37  12  39]
- [ 19   6  14  79   7  11  14]
- [  3   4   3   1  56   2   2]
- [  9   0   4   4   1  42   3]
- [ 14   2  11   9   9  11  79]]
-Node Classification on random seed  696 -> 0.59
-Confusion Matrix:
- [[ 69   1   7   7   7  13  10]
- [  9 115   5   1   9   3  10]
- [ 21  28 113  35  29  45  40]
- [  9   0   8 109   1   9   9]
- [  1   3   1   6  64   0   1]
- [  2   3   6   1   5  51   8]
- [ 20   4  10   7   5  11  69]]
-Node Classification on random seed  697 -> 0.62
-Confusion Matrix:
- [[ 87   4   3   2   3  14   9]
- [  0 139   5   2   0   3   1]
- [ 35  16 126  39  37  38  13]
- [ 19   2  26  89   5  11   6]
- [  1   8   2   1  60   2   0]
- [  2   0   0   9   1  53   1]
- [ 10   8  14   7   4  17  66]]
-Node Classification on random seed  698 -> 0.635
-Confusion Matrix:
- [[ 72   2   4   4   3   6  14]
- [  5 120   8   4  15   3   7]
- [ 28  15 163  28  28  16  34]
- [ 15   3  12 103   4   3   9]
- [  2   7   7   1  52   4   5]
- [  2   2   4   9   0  44   3]
- [  9   2   4  11   8  15  81]]
-Node Classification on random seed  699 -> 0.624
-Confusion Matrix:
- [[ 72   3   6   7   4  17   5]
- [  2 123  11   4   8   4   6]
- [ 34  19 158  27  25  19  23]
- [ 16   3  12 106  12   4  11]
- [  4   5   4   2  49   1   1]
- [ 10   2   4   1   5  45   2]
- [ 13   4   9   5  11  11  71]]
-Node Classification on random seed  700 -> 0.622
-Confusion Matrix:
- [[ 63   4   4   2   4  15  15]
- [ 10 125   2   2  10   1   1]
- [ 30  20 146  21  37  21  43]
- [ 11   4  20 104   5   6  18]
- [  0   5   2   1  63   2   2]
- [  5   2   1   0   1  52   1]
- [  7   2   8   5   8  20  69]]
-Node Classification on random seed  701 -> 0.635
-Confusion Matrix:
- [[ 88   4   1   5   3   8   7]
- [  7 122   4   0  13   3   8]
- [ 23  18 151  41  27  27  23]
- [ 10   3  12 101   3   4  18]
- [  5   2   0   1  63   1   2]
- [  2   2   5   3   1  37   8]
- [ 14   2   5   6  12  22  73]]
-Node Classification on random seed  702 -> 0.598
-Confusion Matrix:
- [[ 55   2   7   7   9  16  11]
- [  0 121  16   3   4   1   6]
- [ 40  23 156  39  22  22  41]
- [ 25   4  12  93   4   5  10]
- [  2  12   5   0  56   0   0]
- [  3   0   3   2   0  34   3]
- [  2   4  16   7   5   9  83]]
-Node Classification on random seed  703 -> 0.658
-Confusion Matrix:
- [[ 67   4   3   5   2   9  15]
- [  9 134  10   1  11   2   2]
- [ 19  11 161  35  35  13  26]
- [ 10   1  12 105   4   7  12]
- [  6   5   2   0  62   0   7]
- [  6   2   0   5   0  49   4]
- [ 13   4  10   9   7   4  80]]
-Node Classification on random seed  704 -> 0.592
-Confusion Matrix:
- [[ 62   3   3   9   4  18   9]
- [  7 128  13   3   4   4   3]
- [ 19  22 126  31  51  17  47]
- [ 13   4  13  99   4   5  21]
- [  1   4   1   6  48   2   4]
- [  2   1   1   4   1  51   3]
- [  5   6   7   8  11  14  78]]
-Node Classification on random seed  705 -> 0.608
-Confusion Matrix:
- [[ 80   7   5   1   4   5   5]
- [  7 118   7   1  14   1   3]
- [ 36  23 137  24  27  17  50]
- [  7   7  25 108   3   1  18]
- [  1   7   2   2  62   2   2]
- [ 11   1   3   0   4  36   6]
- [  9   7   7   7  12  11  67]]
-Node Classification on random seed  706 -> 0.641
-Confusion Matrix:
- [[ 82   2   1   2   8  11  13]
- [  7 132   2   2   7   0   5]
- [ 21  33 134  44  30  18  26]
- [  7   3  12  99   4  10  12]
- [  1   6   3   9  61   1   0]
- [  4   0   2   0   1  42  10]
- [ 15   1   2  10   7   7  91]]
-Node Classification on random seed  707 -> 0.571
-Confusion Matrix:
- [[ 58   1   7  10   2  12  13]
- [  9  99   3   9  10   7   1]
- [ 38  18 153  48  17  16  45]
- [ 25   2  20  89   3  10  23]
- [  3   2   7   4  51   2   0]
- [  3   1   4   0   0  50   3]
- [  7   1   8   8  13  14  71]]
-Node Classification on random seed  708 -> 0.607
-Confusion Matrix:
- [[ 88   1   5   9   2  11   5]
- [  6 137   6   1   9   1   1]
- [ 26  19 138  31  34  15  52]
- [  6   5  17  88   9   7  18]
- [  2   6   4   2  54   4   4]
- [  6   1   2   3   3  39  10]
- [ 14   4  10   4  13   5  63]]
-Node Classification on random seed  709 -> 0.65
-Confusion Matrix:
- [[ 76   3   6   3   6   5  10]
- [  4 118   7   5   4   1   4]
- [ 23  22 146  39  25  17  28]
- [  7   4  26 101   9   5  10]
- [  1   7   4   4  66   0   4]
- [  4   0   3   2   1  58   4]
- [ 10   3   9   6   6   9  85]]
-Node Classification on random seed  710 -> 0.641
-Confusion Matrix:
- [[ 69   1   5   8   3  11   9]
- [  1 118   5   0  22   1   2]
- [ 22  22 153  22  17  22  37]
- [  9   2  19 109   9   7   8]
- [  2   4   6   1  67   0   2]
- [  5   1   2   2   7  49   3]
- [  7   5  14  10   8  16  76]]
-Node Classification on random seed  711 -> 0.638
-Confusion Matrix:
- [[ 71   2   5  12   4  13   6]
- [  3 131   3   4   6   0   7]
- [ 20  16 164  36  24  11  37]
- [  9   6  25  91  15   4  12]
- [  0   8   2   3  62   1   6]
- [  7   0   1   0   6  46   9]
- [  6   1   5  11   4  12  73]]
-Node Classification on random seed  712 -> 0.624
-Confusion Matrix:
- [[ 57   2   4   6   5  15   9]
- [  2 124   3   1   8   3   2]
- [ 32  27 144  35  33  21  35]
- [  8   3  12 103   4   6  15]
- [  1   4   3   2  69   2   2]
- [  1   4   2   4   2  47   4]
- [  9   4   5   9  11  16  80]]
-Node Classification on random seed  713 -> 0.603
-Confusion Matrix:
- [[ 54   3   2  11   4  16  12]
- [  2 127   3   3   8   4   5]
- [ 19  36 139  33  29  27  36]
- [  7  11  13  97   6   5  13]
- [  1   5   3   1  64   0   3]
- [  4   0   0   3   6  47   8]
- [ 11   4   9   6  12  13  75]]
-Node Classification on random seed  714 -> 0.621
-Confusion Matrix:
- [[ 53   3   0   3   2  17  13]
- [  5 130  10   4   1   3  13]
- [ 19  24 147  31  12  23  43]
- [ 20   6   8 103   3  10  15]
- [  0  10   4   3  46   4   4]
- [  1   5   5   0   0  46   1]
- [  7   2  10  12  11  12  96]]
-Node Classification on random seed  715 -> 0.6
-Confusion Matrix:
- [[ 64   3   7   3   4  17  10]
- [  2 137   4   4   6   8   3]
- [ 32  24 123  56  37  14  37]
- [ 14   1  20  95   1   8  21]
- [  1   5   0   3  58   4   3]
- [  3   1   0   2   0  50   3]
- [ 10   1   7   5   2  14  73]]
-Node Classification on random seed  716 -> 0.59
-Confusion Matrix:
- [[ 68   2   4   4   1  11  16]
- [  7 116  19   4   3   3   7]
- [ 30  24 142  30  41  18  35]
- [ 14   4  14  92   4   6  21]
- [  6   3   3   1  63   2   4]
- [  3   0   4   0   0  45  12]
- [  8   3   9   3  13  14  64]]
-Node Classification on random seed  717 -> 0.65
-Confusion Matrix:
- [[ 76   4   5   9   0  13   2]
- [ 10 127   5   0   2   2   8]
- [ 30  18 152  29  20  18  37]
- [ 11   3   6 121   8   5  12]
- [  3   4   4   0  68   0   8]
- [  5   0   3   1   1  43   4]
- [ 11   2  14  18   3  12  63]]
-Node Classification on random seed  718 -> 0.584
-Confusion Matrix:
- [[ 66   0   7   7   2   8  21]
- [  6 126   5   1  14   9   0]
- [ 15  15 122  40  38  22  50]
- [ 14   3  24  92  10   9  10]
- [  3   6   0   0  64   3   3]
- [  9   1   1   4   0  43   4]
- [  9   2   2   9   8  22  71]]
-Node Classification on random seed  719 -> 0.585
-Confusion Matrix:
- [[ 69   8   0   6   5  12  13]
- [  4 128   4   5   5   6  10]
- [ 21  13 140  14  17  28  57]
- [ 11   1  20  90  12  14  13]
- [  2   3   2   1  52   7   4]
- [ 10   2   3   4   1  33   4]
- [  6   6  18  20   8  15  73]]
-Node Classification on random seed  720 -> 0.6
-Confusion Matrix:
- [[ 55   5   6   3   4   5  11]
- [  2 129   4   3  17   1   2]
- [ 22  23 132  49  41  14  33]
- [ 11   1  19 102   5  12  16]
- [  3   1   4   6  64   2   4]
- [  3   0   3   1   0  41   5]
- [ 11   3  19   3   4  19  77]]
-Node Classification on random seed  721 -> 0.621
-Confusion Matrix:
- [[ 70   4   3   2   3  15  10]
- [  4 130   6   5   9   4   2]
- [ 23  21 138  43  47  23  29]
- [ 17   5   7  93   2   6  14]
- [  2   4   5   2  61   0   1]
- [ 10   1   4   3   1  45   2]
- [ 10   1   5   6   3  15  84]]
-Node Classification on random seed  722 -> 0.643
-Confusion Matrix:
- [[ 92   0   2   7   5   4  14]
- [  1 116   6   2   7   4   9]
- [ 25  20 163  22  16  23  29]
- [ 16   1  15 103   4   8  12]
- [  0  10   4   0  59   4   1]
- [ 16   1   2   0   1  35   3]
- [ 13  11   6   8   3  22  75]]
-Node Classification on random seed  723 -> 0.627
-Confusion Matrix:
- [[ 82   4   8   1   2   9   9]
- [  2 125   6   1  13   8   2]
- [ 24  19 142  29  24  28  34]
- [ 13   3  19 110   6  13   6]
- [  1   3   3   5  50   3   0]
- [  2   3   1   0   2  47   3]
- [ 15   6   8   9   6  20  71]]
-Node Classification on random seed  724 -> 0.573
-Confusion Matrix:
- [[ 65   4  16   6   4  13   3]
- [  6 110   7   3   9   8   5]
- [ 37  12 145  21  34  25  36]
- [ 15   3  21  83  13  11   9]
- [  1   7   4   0  61   2   1]
- [  6   3   5   1   0  44   1]
- [  5   4   9  18   6  33  65]]
-Node Classification on random seed  725 -> 0.62
-Confusion Matrix:
- [[ 63   2   7   9   7  11  10]
- [  6 131   5   3   4   1  14]
- [ 26  33 161  31  22   7  37]
- [ 14   5  18  86   7   3   9]
- [  3   7   3   1  60   6   3]
- [  7   1   5   0   0  46   6]
- [ 12   2   9   5   9  10  73]]
-Node Classification on random seed  726 -> 0.617
-Confusion Matrix:
- [[ 78   6   2   6   2   5   8]
- [  4 117   8   6   5   1   7]
- [ 16  23 136  36  27  27  34]
- [ 15   3  21  95  11   3  15]
- [  1   7   8   1  55   4   2]
- [  5   1   2   1   0  48   2]
- [ 15   6  11   5  12   9  88]]
-Node Classification on random seed  727 -> 0.601
-Confusion Matrix:
- [[ 69   1   9   1   3  14  12]
- [  7 108   8   1   4   1   5]
- [ 25  26 140  52  19  32  34]
- [  5   2  23  99   8   9  17]
- [  0   6   2   3  65   2   4]
- [  9   0   2   1   0  49   7]
- [ 13   3   7   6   8   8  71]]
-Node Classification on random seed  728 -> 0.603
-Confusion Matrix:
- [[ 64   2  11   2   6  19   7]
- [  2 135   8   6  15   6   3]
- [ 24  12 137  42  19  21  32]
- [  7   5  16 107   5   0   9]
- [  4   2   2   1  64   1   3]
- [ 10   2   1   2   1  37   8]
- [ 17   2   8   9  25  20  59]]
-Node Classification on random seed  729 -> 0.64
-Confusion Matrix:
- [[ 77   2   2   3   2  13  13]
- [  7 120  13   1   8   2   4]
- [ 26  18 161  22  14  26  36]
- [ 13   6  19 108   8   6  18]
- [  1   5   5   1  51   0   4]
- [  2   0   3   1   1  51   8]
- [ 12   7   3   8   1  16  72]]
-Node Classification on random seed  730 -> 0.606
-Confusion Matrix:
- [[ 67   3   6   4   6   8  18]
- [  4 101   9   4   9   6   5]
- [ 17  24 149  43  40   9  50]
- [  7   2  28  82   5   4  10]
- [  1   8   2   4  55   3   2]
- [  2   1   2   2   0  54   5]
- [  8   3  11   9   6   4  98]]
-Node Classification on random seed  731 -> 0.645
-Confusion Matrix:
- [[ 68   1   2   6   6  17   4]
- [  1 132   3   4   2   4   7]
- [ 18  24 150  29  30  23  34]
- [ 11   5  21 100   6   4   6]
- [  1   6   9   0  56   1   3]
- [  8   1   2   5   0  50   1]
- [ 12   6   6   2   6  18  89]]
-Node Classification on random seed  732 -> 0.6
-Confusion Matrix:
- [[ 70   7   4   5   4  10   6]
- [  7 127   3   4   3   1   4]
- [ 18  24 119  30  42  21  54]
- [ 18   4  13  97   7   6  17]
- [  2   9   1   3  63   0   9]
- [  6   2   2   2   0  41   1]
- [ 15   3   4   4   6  19  83]]
-Node Classification on random seed  733 -> 0.613
-Confusion Matrix:
- [[ 71   0   4   5   3  16  15]
- [  4 128   1   0   6   7   6]
- [ 35  30 132  43  24  24  34]
- [  6   9  17 112   2   3  12]
- [  0   5   3   0  57   0   3]
- [  4   1   1   3   0  42   5]
- [ 19   3   6   6   4  18  71]]
-Node Classification on random seed  734 -> 0.641
-Confusion Matrix:
- [[ 68   3   5   6   6   7   7]
- [  2 130   4   5   5   1  14]
- [ 23  24 111  25  46  22  36]
- [  5   2  11 129   7   2   7]
- [  1  12   0   1  76   0   1]
- [  7   0   0   1   2  44   8]
- [  8   4  14   8  10   7  83]]
-Node Classification on random seed  735 -> 0.601
-Confusion Matrix:
- [[ 65   3   6  12   5  12  11]
- [ 13  98   8   0   3   1   5]
- [ 14  24 149  24  26  24  39]
- [  4   8  20  99   4   7  23]
- [  1   6   5   2  65   2   6]
- [  9   6   1   2   2  47   8]
- [ 18   3   6   5   8  13  78]]
-Node Classification on random seed  736 -> 0.628
-Confusion Matrix:
- [[ 82   2   3   1   2  13   6]
- [  4 125   4   1   7   5   2]
- [ 18  23 136  36  14  41  41]
- [  4   4   9 106   6   4  12]
- [  1  11   5   2  65   0   1]
- [  2   2   8   6   0  41   9]
- [ 17   3   9   7  11  16  73]]
-Node Classification on random seed  737 -> 0.629
-Confusion Matrix:
- [[ 79   4   1  10   1  17   2]
- [  2 129   2   9   7   4   1]
- [ 23  27 149  54  19  36  23]
- [ 10   1  11 102   2  12  11]
- [  1   4   2   0  57   2   0]
- [  4   2   0   2   0  51   1]
- [  9   3   3   6  18  25  62]]
-Node Classification on random seed  738 -> 0.611
-Confusion Matrix:
- [[ 79   0   2   7   2   6  11]
- [  4 125  11   4   8   6   0]
- [ 16  18 143  39  41  40  27]
- [  8  13  24  96   5   4  19]
- [  0   2   4   3  51   0   1]
- [  8   1   2   3   0  47   4]
- [ 17   2   9   1  12   5  70]]
-Node Classification on random seed  739 -> 0.596
-Confusion Matrix:
- [[ 60   3   7   6   7   9  13]
- [  9 119   3   3   4   3   6]
- [ 31  28 149  23  20  23  54]
- [ 19   2   8  95   3   7  19]
- [  2   5   2   6  62   1   1]
- [  6   1   3   0   0  43   8]
- [ 12   0  11   8   9  19  68]]
-Node Classification on random seed  740 -> 0.596
-Confusion Matrix:
- [[ 59   1   8   3   8   7  10]
- [  5 136   2   3  10   4   5]
- [ 38  17 117  28  28  17  69]
- [ 14   8  10 104   9   3  14]
- [  1   7   7   4  68   0   1]
- [  4   1   3   0   1  31   4]
- [  9   3   5   7   7  19  81]]
-Node Classification on random seed  741 -> 0.578
-Confusion Matrix:
- [[ 57   2   4   3   5  10  22]
- [  6 132   6   3   8   1   2]
- [ 40  23 112  45  21  19  34]
- [ 13   9  14 109   7   2  14]
- [  1  10   4   3  61   0   2]
- [ 13   0   6   3   0  37   4]
- [ 11   1   7  10  16  18  70]]
-Node Classification on random seed  742 -> 0.581
-Confusion Matrix:
- [[ 56   3   4  12   2  13  14]
- [  6 137   4   2   3   0   2]
- [ 38  32 128  54  17  20  34]
- [ 18  10  12  94   6  10  13]
- [  5   8   1   0  61   2   1]
- [  4   0   1   1   0  42  10]
- [ 13   2  15   7   5  15  63]]
-Node Classification on random seed  743 -> 0.597
-Confusion Matrix:
- [[ 65   3   2   3   4   8  15]
- [  1 124   7   4   8   4   6]
- [ 25  30 111  54  31  23  44]
- [  5   2  10 102   4   6  25]
- [  3   4   4   1  69   1   1]
- [  7   2   7   1   0  44   4]
- [ 14   3   4   4  10   9  82]]
-Node Classification on random seed  744 -> 0.652
-Confusion Matrix:
- [[ 79   2   3   2   2  13  12]
- [  9 118  12   2   3   3   4]
- [ 21  25 157  32  18  30  36]
- [  6   3  22 106   2   8   6]
- [  1  10   1   0  62   2   1]
- [  7   2   0   2   1  44   4]
- [  2   6   5  12   4  12  86]]
-Node Classification on random seed  745 -> 0.624
-Confusion Matrix:
- [[ 76   4   4   7   0  10   7]
- [  5 116  13   2   8   5   6]
- [ 26  22 136  29  47  17  39]
- [  5   2  19  99   8   3  13]
- [  6   5   0   1  56   2   2]
- [  6   0   0   2   2  47   9]
- [  8   3  11   3   7   8  94]]
-Node Classification on random seed  746 -> 0.61
-Confusion Matrix:
- [[ 66   2   7   6   1  19   9]
- [  4 120   3   2  12   6   6]
- [ 30  24 145  34  14  28  47]
- [ 10   3  17  91   6  11  13]
- [  1   9   4   2  53   2   2]
- [  6   2   1   2   0  49   5]
- [  2   1   4   3   6  24  86]]
-Node Classification on random seed  747 -> 0.636
-Confusion Matrix:
- [[ 76   0   2   4   5  13  11]
- [  2 146   8   3  16   3   5]
- [ 22  14 160  36  23  15  44]
- [ 10   7  23  89   3   5  10]
- [  2   6   4   7  41   1   1]
- [  4   2   1   4   2  42   3]
- [ 11   2  15   6   2   7  82]]
-Node Classification on random seed  748 -> 0.631
-Confusion Matrix:
- [[ 67   7   3   2   5   9   6]
- [  6 128   4   2   8   3   1]
- [ 20  20 149  46  36  22  31]
- [  6   6  13 104  10   2  13]
- [  0   1   4   3  60   3   0]
- [  4   1   3   5   1  42   2]
- [ 17   5   8   4  16  11  81]]
-Node Classification on random seed  749 -> 0.579
-Confusion Matrix:
- [[ 80   6   3   7   0   1  13]
- [  2 126   9   1   6   2   9]
- [ 28  26 123  20  22  20  46]
- [ 16   4  21 102   7   7  12]
- [  0   5   4   1  45   3   4]
- [  9   0   4   8   1  42   7]
- [ 15   6  11  22  24   9  61]]
-Node Classification on random seed  750 -> 0.618
-Confusion Matrix:
- [[ 48   2  17   4   7   8   5]
- [  0 143   2   6   9   1   8]
- [ 29  15 126  32  44  16  39]
- [  9   1  12 122   7   8   9]
- [  3   5   0   0  64   0   2]
- [  0   0   5   0   2  50   1]
- [ 14   1  16   7  21  15  65]]
-Node Classification on random seed  751 -> 0.609
-Confusion Matrix:
- [[ 63   4   5  14   9  24   9]
- [  6 114   8   3  12   2   5]
- [ 34  22 156  23  22  27  36]
- [  6   9  20  98   5   3  12]
- [  0   5   6   0  55   1   3]
- [  7   0   3   2   0  44   0]
- [  5   3   3   7   4  22  79]]
-Node Classification on random seed  752 -> 0.612
-Confusion Matrix:
- [[ 67   1   2   4   1  11   8]
- [  4 127  10   4   8   3   5]
- [ 15  28 131  45  54  18  33]
- [  6   4  19  99   4  14  13]
- [  4   6   4   1  60   1   3]
- [  2   0   0   0   0  54   2]
- [  4   5  10   2   8  22  74]]
-Node Classification on random seed  753 -> 0.633
-Confusion Matrix:
- [[ 73   3   2   3   2   7  11]
- [  2 130   3   4   6   1   8]
- [ 22  17 118  32  29  38  36]
- [ 14   2  15 118   2  11   5]
- [  0   5   2   1  78   2   1]
- [ 14   2   1   2   1  34   7]
- [ 19   8   5   9   1  12  82]]
-Node Classification on random seed  754 -> 0.603
-Confusion Matrix:
- [[ 47   2  12   8  14  13  11]
- [  2 128   6   3   3  10   3]
- [ 26  34 131  23  27  29  35]
- [  7   5  17 111   1   9  12]
- [  3  12   2   3  58   0   5]
- [  4   0   4   2   0  51   1]
- [ 10   2  15   8   5   9  77]]
-Node Classification on random seed  755 -> 0.618
-Confusion Matrix:
- [[ 75   1   4   6   4  16   5]
- [  3 139   8   3   5   0   2]
- [ 31  18 146  31  34  30  31]
- [ 18   1  10  98   3   8  10]
- [  0   5   4   1  67   0   4]
- [ 10   0   1   2   0  36   6]
- [ 12   3  11  11  10  20  57]]
-Node Classification on random seed  756 -> 0.64
-Confusion Matrix:
- [[ 81   7   1   6   3  11  13]
- [  5 115  11   1   1   0   4]
- [ 29  20 152  37  11  27  38]
- [  5   1  12 104   5   7  16]
- [  0  10   6   0  69   2   1]
- [  9   4   0   2   0  45   3]
- [ 19   3   6   8   5  11  74]]
-Node Classification on random seed  757 -> 0.613
-Confusion Matrix:
- [[ 82   2   4   6   3   4  16]
- [  3 122   5   1  10   7  12]
- [ 32  14 142  27  31  28  39]
- [ 15   0  15  94   9   8   6]
- [  2   1   2   0  59   1   6]
- [  4   3   0   1   1  39  14]
- [ 13   3  12   8   5  14  75]]
-Node Classification on random seed  758 -> 0.664
-Confusion Matrix:
- [[ 76   7   0   9   4   6   9]
- [  2 142   4   6   5   2   3]
- [ 28  31 158  19  23  17  33]
- [  8   3  10  93  16   7  16]
- [  1   5   4   2  65   2   3]
- [  4   0   1   0   2  52   5]
- [ 16   4   6   3   4   6  78]]
-Node Classification on random seed  759 -> 0.606
-Confusion Matrix:
- [[ 74   6   4   5   3  16   6]
- [  0 125   7   5   6   0   6]
- [ 21  19 147  56  22  35  18]
- [ 19   6  12  94   3   9  25]
- [  1   5   3   8  58   2   2]
- [  7   0   2   0   0  42   5]
- [  8   5  17   2   2  16  66]]
-Node Classification on random seed  760 -> 0.62
-Confusion Matrix:
- [[ 74   4   5  10   4  13  12]
- [  4 121   1   5  13   3   8]
- [ 19  26 134  34  28  22  43]
- [ 11   1  12 113   5   6  12]
- [  0   1   3   2  65   2   2]
- [ 11   0   3   2   1  44   3]
- [  9   2   3   9   7  19  69]]
-Node Classification on random seed  761 -> 0.619
-Confusion Matrix:
- [[ 63   2   3  12   3  16   7]
- [  3 120   8   0   2   3   3]
- [ 19  26 138  48  18  12  48]
- [ 13   2  11 122   8  12  16]
- [  2   6   1   1  49   2   7]
- [  7   1   3   3   0  48   6]
- [  9   5   4   8   6  15  79]]
-Node Classification on random seed  762 -> 0.64
-Confusion Matrix:
- [[ 84   1   6   1   6  18   4]
- [  3 131   1   3   6   8   5]
- [ 20  32 146  31  20  19  43]
- [ 15   5  13 101   4   4  11]
- [  0   5   2   5  62   0   4]
- [  3   1   5   0   0  47   5]
- [  7   3  10   8   4  19  69]]
-Node Classification on random seed  763 -> 0.613
-Confusion Matrix:
- [[ 79   0   5   9   7   6  11]
- [  4 129   7   5   6   2   4]
- [ 26  16 121  58  19  29  48]
- [  9   4   9  96   6   7  13]
- [  0   2   4   2  71   0   3]
- [ 11   1   1   0   0  31   5]
- [ 14   2   8   7   7  10  86]]
-Node Classification on random seed  764 -> 0.579
-Confusion Matrix:
- [[ 52   2   1   9   5  17   5]
- [ 11 139   6   3   5   2   8]
- [ 24  27 112  58  35  18  46]
- [ 11   3   6 102   6   8  17]
- [  0   7   8   1  59   2   3]
- [  7   2   4   1   0  46   1]
- [ 16   0   9   6   5  16  69]]
-Node Classification on random seed  765 -> 0.648
-Confusion Matrix:
- [[ 70   6   3   2   0  14  13]
- [  8 122   2   1   8   2   4]
- [ 19  28 159  32  29  16  38]
- [  9   6  11 100   3   9  12]
- [  1   8   3   2  65   2   2]
- [  5   5   1   0   0  41   6]
- [  9   4  10   7   6   6  91]]
-Node Classification on random seed  766 -> 0.625
-Confusion Matrix:
- [[ 74   1   4   3   6  15   6]
- [  4 138   0   2   6   4   5]
- [ 26   7 160  19  30  30  46]
- [ 13   2   9  77  10   8  18]
- [  1   8   4   2  58   1   2]
- [ 10   0   2   1   3  47   3]
- [  6   6   9   7   7  29  71]]
-Node Classification on random seed  767 -> 0.624
-Confusion Matrix:
- [[ 74   2   3  15   3   5  19]
- [  0 140  10   3   9   4   3]
- [ 35  24 124  39  25  15  46]
- [  8   1  13 114   2   2  13]
- [  1   3   5   6  48   1   1]
- [  8   0   3   3   0  37   6]
- [  8   3   5   2   5  17  87]]
-Node Classification on random seed  768 -> 0.655
-Confusion Matrix:
- [[ 69   2   3   4   6  13   3]
- [  6 126   5   9   3   2   4]
- [ 13  15 156  34  21  24  45]
- [  5   2  18 117   4  12   8]
- [  1   5   2   0  69   0   7]
- [  2   4   2   8   1  45   2]
- [  3   6   2  13   3  23  73]]
-Node Classification on random seed  769 -> 0.614
-Confusion Matrix:
- [[ 69   5   4   3   4  16   7]
- [  1 122   7   1  15   2  13]
- [ 12  21 145  44  32  15  35]
- [  7   1  18 107   1   5  14]
- [  0   4   1   2  59   1   5]
- [ 11   5   1   1   0  44   7]
- [ 16   4  13  11   3  18  68]]
-Node Classification on random seed  770 -> 0.61
-Confusion Matrix:
- [[ 64   6   6   4   3  17   6]
- [  3 134   4   1   3   3   5]
- [ 32  32 137  53  12  18  24]
- [ 13   7  12 105   4   4   8]
- [  1  15   5   0  58   1   3]
- [  6   6   2   1   0  37   8]
- [  8   1  13   9  13  18  75]]
-Node Classification on random seed  771 -> 0.617
-Confusion Matrix:
- [[ 62   3   4  14   6   4  13]
- [  2 115   6   1  12   0   7]
- [ 32  25 158  25  24  37  32]
- [ 14  10  13  95   2   3  17]
- [  1   9   1   3  53   1   2]
- [  3   1   2   1   0  50   5]
- [ 10   2   8   4   6  18  84]]
-Node Classification on random seed  772 -> 0.579
-Confusion Matrix:
- [[ 77   3   7   3   6  10   7]
- [  6 111   4   1  10   5   6]
- [ 32  23 106  37  29  32  51]
- [  8   2  28 118   8   7  11]
- [  0   4   2   3  63   1   7]
- [  6   1   1   4   1  37   4]
- [ 16   1   6  10   8  10  67]]
-Node Classification on random seed  773 -> 0.609
-Confusion Matrix:
- [[ 51   1   3   1  10  13  16]
- [  5 126  13   1   9   1   4]
- [ 14  40 151  38  32  26  27]
- [ 13   6  12  99   2   8   7]
- [  1   9   5   3  66   1   1]
- [  5   1   2   2   1  45  10]
- [  6   2   6  12   6  16  71]]
-Node Classification on random seed  774 -> 0.616
-Confusion Matrix:
- [[ 56   1   5   6   6  11  16]
- [ 15 118   9   2   6   1   6]
- [ 21  24 154  34  36  16  29]
- [ 17   5  24  91   7   5   7]
- [  2   6   4   0  63   2   3]
- [  8   0   3   0   2  50   8]
- [ 14   1   1   4   8   9  84]]
-Node Classification on random seed  775 -> 0.602
-Confusion Matrix:
- [[ 66   1   3   2   3  20   6]
- [  9 115   8   3   1   3   7]
- [ 24  15 146  43  35  30  39]
- [ 15   4   9  92   4   8  13]
- [  1   6  11   3  57   0   2]
- [  7   0   4   1   1  45   7]
- [ 13   2   8   5   4  18  81]]
-Node Classification on random seed  776 -> 0.643
-Confusion Matrix:
- [[ 74   2   1  11   2  13   7]
- [  3 131   2   1  15   1   2]
- [ 19  28 164  26  19  26  35]
- [ 13   4  18  88   5   7  15]
- [  2   7   6   0  64   1   2]
- [  1   1   4   6   0  44   4]
- [ 11   1   3   8  11  14  78]]
-Node Classification on random seed  777 -> 0.619
-Confusion Matrix:
- [[ 67   1   1   8   1  11   4]
- [  3 123   2   5   7   6   4]
- [ 28  11 163  34  30  29  35]
- [ 12   4  16 108   3   9  14]
- [  1   8  11   2  55   2   2]
- [  7   0   0   4   3  45   1]
- [ 11   7   9  10  10  15  58]]
-Node Classification on random seed  778 -> 0.598
-Confusion Matrix:
- [[ 74   5   3   3   5  15   7]
- [  0 124   7   0  10   2   6]
- [ 18  18 148  25  29  26  51]
- [ 15   9  19  95   4   5  17]
- [  2   7   4   2  57   1   1]
- [  9   1   4   1   2  40   6]
- [  6   7   6  16   8  20  60]]
-Node Classification on random seed  779 -> 0.591
-Confusion Matrix:
- [[ 77   0   2   6   2  18  12]
- [  3 134   7   4   3   2   6]
- [ 28  23 157  23  22  25  34]
- [  8  13  22  88   3   8  21]
- [  0   8   4   0  44   1   3]
- [  3   2   3   2   2  38   5]
- [ 12   1  16  24   6  22  53]]
-Node Classification on random seed  780 -> 0.597
-Confusion Matrix:
- [[ 59   1   2  13   7  10  18]
- [  2 110   8   6  16   6   4]
- [ 31  16 131  23  29  23  41]
- [ 12   1  12 122   5   7  12]
- [  0   4   4   1  53   1   4]
- [  5   0   4   3   1  44   8]
- [ 10   8  14  12   4  15  78]]
-Node Classification on random seed  781 -> 0.645
-Confusion Matrix:
- [[ 72   1  11   4   2  14  11]
- [ 11 127   7   5   7   1   4]
- [ 26  17 174  25  25  20  30]
- [  8   0  21 104   0   6  14]
- [  3   5   4   1  61   1   2]
- [  4   1   1   3   0  45   4]
- [ 16   5  10   0   5  20  62]]
-Node Classification on random seed  782 -> 0.629
-Confusion Matrix:
- [[ 86   1   0  10   4  15   7]
- [  5 105   5   0   3   4  20]
- [ 24  11 137  43  13  28  42]
- [  4   4  18 122   3   3  16]
- [  3   7   6   1  55   3   4]
- [  7   0   1   1   0  42   5]
- [ 10   0   8   9   5  18  82]]
-Node Classification on random seed  783 -> 0.641
-Confusion Matrix:
- [[ 67   2   3   5   6   9  11]
- [  3 120  10   1  10  10   3]
- [ 14  25 136  43  19  18  40]
- [  3   7  23 118   5   5  16]
- [  2   3   1   2  72   1   1]
- [  2   3   2   0   0  51   2]
- [  6   3  10   8   9  13  77]]
-Node Classification on random seed  784 -> 0.641
-Confusion Matrix:
- [[ 82   2   7   3   3   8   4]
- [  7 139   7   3  13   4   1]
- [ 30  19 138  31  20  18  37]
- [ 15   3   8 111   3   5  15]
- [  4   6   6   3  55   5   4]
- [  7   2   4   2   0  41   7]
- [ 13   1  10   5   5   9  75]]
-Node Classification on random seed  785 -> 0.615
-Confusion Matrix:
- [[ 77   1   7   2   1  20   1]
- [ 10 138   3   3   0   3   3]
- [ 24  26 136  29  15  40  48]
- [ 17   4   9  97   8   6  15]
- [  6  11   0   2  53   2   3]
- [  3   2   2   1   0  37   4]
- [ 13   6   8   7   5  15  77]]
-Node Classification on random seed  786 -> 0.649
-Confusion Matrix:
- [[ 71   3   1   3   2  13  11]
- [  5 116   7   4   8   5   2]
- [ 12  21 138  45  19  31  43]
- [  8   6  11 127   1   6   8]
- [  1   3   2   3  59   0   1]
- [  3   1   3   3   0  50   8]
- [  7   3   7  11   5  15  88]]
-Node Classification on random seed  787 -> 0.614
-Confusion Matrix:
- [[ 64   0   3   6   7   8  15]
- [  4 119  10   0   7   2   5]
- [ 33   9 148  36  42  14  39]
- [ 11   4  17  88   4   6  15]
- [  1  11   2   2  61   2   4]
- [  3   0   7   1   1  37   9]
- [  8   4  11   8   8   7  97]]
-Node Classification on random seed  788 -> 0.623
-Confusion Matrix:
- [[ 63   4   9   2   2  10  10]
- [ 10 130   4   3  10   5   3]
- [ 19  20 129  33  38  16  54]
- [  9   8   4 104   8   6  11]
- [  2  11   1   2  69   1   1]
- [ 15   0   0   1   2  35   6]
- [  8   3   3   3  13   7  93]]
-Node Classification on random seed  789 -> 0.638
-Confusion Matrix:
- [[ 60   1   3  14   4   6   7]
- [  6 134   9   5   5   0   2]
- [ 16  29 140  31  22  21  38]
- [  6   5  15 116   9   3  14]
- [  2  12   0   2  65   1   3]
- [  5   0   3   8   0  41   3]
- [ 11   1  12  12   6  10  82]]
-Node Classification on random seed  790 -> 0.597
-Confusion Matrix:
- [[ 72   1   2   7   6  11  12]
- [  5 123   9   3   7   2   6]
- [ 24  28 138  40  18  27  39]
- [ 12   4   7 108   5   4  23]
- [  1   8   3   2  51   0   1]
- [  8   1   5   2   0  42   8]
- [ 12   6   6  18  12   8  63]]
-Node Classification on random seed  791 -> 0.603
-Confusion Matrix:
- [[ 67   6   4  15   1  15   8]
- [  3 116   2   0   7   8   7]
- [ 20  43 131  24  25  35  41]
- [  3   4  29 112   8   5   8]
- [  0   9   6   0  50   1   3]
- [  3   1   3   0   0  50   6]
- [ 13   5   3   5   4  14  77]]
-Node Classification on random seed  792 -> 0.605
-Confusion Matrix:
- [[ 72   3   3   8   4  20   1]
- [  6 122   4   0   6   5   5]
- [ 24  14 133  32  29  24  60]
- [ 13   1  24  88   5   3  13]
- [  1   7   1   1  71   2   3]
- [  8   2   0   5   0  39   4]
- [ 10   5   3   8   8  20  80]]
-Node Classification on random seed  793 -> 0.629
-Confusion Matrix:
- [[ 68   1   3   4   2  14  12]
- [  3 131  14   1   5   7   1]
- [ 16  10 158  20  30  28  50]
- [ 14   4  19  88   5   3  16]
- [  0   4   4   1  75   1   2]
- [  5   3   2   4   0  38   7]
- [  9   7   7   8   4  21  71]]
-Node Classification on random seed  794 -> 0.643
-Confusion Matrix:
- [[ 75   4   5   8   2   7   8]
- [  3 134   5   0   9   0   2]
- [ 19  14 137  25  46  14  43]
- [  6   7  15 106   8   8  14]
- [  3   6   3   0  71   0   1]
- [  5   5   1   3   0  43   2]
- [ 10  10   8   9   6  13  77]]
-Node Classification on random seed  795 -> 0.594
-Confusion Matrix:
- [[ 62   3   5  12   1  20  11]
- [  2 125   5   4   6   2   4]
- [ 23  20 129  35  28  25  50]
- [ 14   3   9  95  19  10  10]
- [  1   4   3   2  60   1   4]
- [  2   0   6   0   0  46   4]
- [  5   7  17   6   8  15  77]]
-Node Classification on random seed  796 -> 0.603
-Confusion Matrix:
- [[ 84   0   2   2   0   7   0]
- [ 10 127   4   2   6   8   3]
- [ 28  24 127  31  19  40  49]
- [ 12   7  22  86  10  10  10]
- [  3   6   6   2  58   0   4]
- [  5   0   2   3   0  52   5]
- [ 14   0  21   5   2  13  69]]
-Node Classification on random seed  797 -> 0.654
-Confusion Matrix:
- [[ 77   1   2  11   2  13   8]
- [  7 131   8   0   9   3   5]
- [ 23  21 155  23  20  10  42]
- [ 13   7  15  98   2   4  14]
- [  1   6   6   0  66   0   1]
- [  7   1   1   0   2  53   2]
- [ 19   2   8   4  14   9  74]]
-Node Classification on random seed  798 -> 0.642
-Confusion Matrix:
- [[ 67   5   3   6   2  13  10]
- [  4 130   8   2   4   2   5]
- [ 34  14 174  27  16  19  33]
- [ 10   6  17  98   4   9  11]
- [  1   9   2   1  54   0   3]
- [  8   0   1   4   3  52   4]
- [ 17   2   8  11   9  11  67]]
-Node Classification on random seed  799 -> 0.588
-Confusion Matrix:
- [[ 58   5   8   7   2   8  12]
- [  9 101   5   6  15   6   8]
- [ 17  16 138  42  24  25  44]
- [ 13   4  13 105   4   8  15]
- [  1   6   3   5  60   1   2]
- [  9   1   1   7   1  38  10]
- [  6   7   9   8   7  12  88]]
-Node Classification on random seed  800 -> 0.604
-Confusion Matrix:
- [[ 61   2   3   8   9  15   8]
- [  2 135  11   3   6   0   2]
- [ 19  21 143  41  40  27  37]
- [ 11  11  16  97   4   9   8]
- [  2   5   3   0  59   2   3]
- [  6   2   6   0   0  46   4]
- [ 16   3   4  10   9   8  63]]
-Node Classification on random seed  801 -> 0.563
-Confusion Matrix:
- [[ 62   4   9  13   9   3  14]
- [ 17 113   8   1   7   2   3]
- [ 22  22 113  32  39  24  43]
- [ 17   4  21 102  16   7   5]
- [  2   4   4   1  58   0   1]
- [  9   2   3   2   1  32   5]
- [ 20   2  10   9  10  10  83]]
-Node Classification on random seed  802 -> 0.628
-Confusion Matrix:
- [[ 82   2   3   1   0  11   6]
- [ 12  90   9  12  11   6   2]
- [ 23   8 155  40  37  30  37]
- [ 12   0  12 111   2   7  14]
- [  5   2   1   2  57   1   6]
- [  9   1   4   0   0  48   1]
- [  4   6   5   8   5  15  85]]
-Node Classification on random seed  803 -> 0.619
-Confusion Matrix:
- [[ 81   2   8   1   0  16   6]
- [ 11 133   3   2  11   1   5]
- [ 37  21 146  36  18  21  38]
- [ 19   2  11  83   2   6   8]
- [  5   5   4   1  62   0   1]
- [  9   2   5   0   1  50   1]
- [ 16   3  12   3   8  20  64]]
-Node Classification on random seed  804 -> 0.594
-Confusion Matrix:
- [[ 63   1   6   6   4   8  11]
- [  3 125   1   1  20   2  14]
- [ 23  26 132  45  39  26  27]
- [  8   3  24  97   7   3  12]
- [  1   8   5   0  68   0   3]
- [  5   0   1   2   0  45   3]
- [ 13   5  11   4  12  13  64]]
-Node Classification on random seed  805 -> 0.644
-Confusion Matrix:
- [[ 56   2   7   4   3  13  13]
- [  2 123   3   3   6   7   1]
- [ 14  29 168  26  18  27  36]
- [  7   2  15 113   7   1  17]
- [  0  10   7   1  55   1   8]
- [  6   2   2   2   0  44   5]
- [ 18   2   7   4   9   9  85]]
-Node Classification on random seed  806 -> 0.605
-Confusion Matrix:
- [[ 57   4   2  13   2  11   6]
- [  2 141   4   4  10   2   0]
- [ 23  19 135  45  41  25  36]
- [  5  10   7 107  11  11  11]
- [  0   9   3   0  63   0   5]
- [  4   4   1   3   0  37   8]
- [  8   3  11  14   7  11  65]]
-Node Classification on random seed  807 -> 0.606
-Confusion Matrix:
- [[ 73   7   2   1   1   8  14]
- [  5 142   5   4   3   2   8]
- [ 24  30 132  48  22  20  37]
- [ 16   1  16  98  12   6  12]
- [  1   7   3   3  59   2   2]
- [  8   0   3   1   4  34   8]
- [  8   2  13   6   4  15  68]]
-Node Classification on random seed  808 -> 0.587
-Confusion Matrix:
- [[ 55   5   3   5   6   4  29]
- [  4 132  12   4   5   0   0]
- [ 18  26 130  61  21  10  49]
- [ 25   2  14  96   8   4   8]
- [  0   5   3   3  65   0   3]
- [  5   1   2   1   0  40  11]
- [ 11   6  15   9   7   8  69]]
-Node Classification on random seed  809 -> 0.648
-Confusion Matrix:
- [[ 84   4   1   4   3  12   9]
- [  3 123   2   4   5   7   3]
- [ 19  22 133  26  17  31  34]
- [  6   6  12 118   7  14   9]
- [  5   5   1   1  64   0  10]
- [  2   2   2   3   0  49   3]
- [ 17   3   8  10   5  15  77]]
-Node Classification on random seed  810 -> 0.6
-Confusion Matrix:
- [[ 42  18  11   4   3  11   5]
- [  2 121   5   2  13   3   1]
- [ 21  28 142  29  21  29  47]
- [ 11   2  14 107   5   2  10]
- [  3   9   4   1  63   2   0]
- [  3   2   3   2   2  51   2]
- [ 11   7   8   5  21  18  74]]
-Node Classification on random seed  811 -> 0.599
-Confusion Matrix:
- [[ 61   3  14   0   7  15   5]
- [  7 143   8   1   8   1   2]
- [ 22  35 131  21  23  28  37]
- [ 10   7  24 102   4   5  12]
- [  1   9   8   0  57   0   3]
- [  6   2   4   0   0  42   6]
- [ 14   3  18   3  14  11  63]]
-Node Classification on random seed  812 -> 0.608
-Confusion Matrix:
- [[ 62   2   7   5   4  17  10]
- [  5 125   2   4   4   3   1]
- [ 30  14 128  34  38  28  32]
- [ 20   3  18 101   4  10   6]
- [  0   5   3   0  72   2   3]
- [  6   4   3   2   0  51   7]
- [  9   6   8  11   5  17  69]]
-Node Classification on random seed  813 -> 0.612
-Confusion Matrix:
- [[ 82   4   6   5   2   9   7]
- [  3 146   3   1   5   2   4]
- [ 20  27 113  37  21  32  41]
- [ 18   4  12 100  11   7  10]
- [  4   5   5   1  58   1   7]
- [  3   2   1   3   0  41   7]
- [ 10   5  12   7   4  20  72]]
-Node Classification on random seed  814 -> 0.61
-Confusion Matrix:
- [[ 59   1   8  10   4  11   6]
- [  1 128   9   1   2   1   6]
- [ 39  17 151  28  34  33  39]
- [ 10   4  10  98   6   9  14]
- [  0   6   2   2  61   4   3]
- [  3   0   1   2   0  40   8]
- [  5   5  15   3   8  20  73]]
-Node Classification on random seed  815 -> 0.591
-Confusion Matrix:
- [[ 68   2   2   5   7  11   7]
- [  5 122   4   4   6   5   9]
- [ 18  21 101  60  44  21  40]
- [ 17   4  10 117   6   8  11]
- [  1   6   7   2  62   0   1]
- [  2   1   1   3   2  38   5]
- [  8   3   3  19   4  14  83]]
-Node Classification on random seed  816 -> 0.616
-Confusion Matrix:
- [[ 73   2  10   4   3  15   7]
- [ 10 119   5  11   5   3   2]
- [ 38  18 151  25  40  16  34]
- [  2   2  29 107   6   7   4]
- [  3   7   4   2  53   0   1]
- [  3   1   0   4   0  43   9]
- [ 11   1   5  14   3  18  70]]
-Node Classification on random seed  817 -> 0.576
-Confusion Matrix:
- [[ 67   3   0   5   5  10   5]
- [  9 109   4   4  14   7   9]
- [ 20  15 120  40  52  26  34]
- [ 20   2  19 109   5   5  17]
- [  2   7   5   1  60   0   4]
- [  6   0   1   6   1  25   6]
- [ 12   5  11   5   8  14  86]]
-Node Classification on random seed  818 -> 0.612
-Confusion Matrix:
- [[ 70   4   8   6   3   7   9]
- [  4 133   4   2   4   5   1]
- [ 22   9 149  16  33  23  45]
- [  5   5  35  95   1  11  23]
- [  3   5   3   1  53   5   0]
- [  3   3   3   2   0  49   3]
- [  8   3  10  14  16  21  63]]
-Node Classification on random seed  819 -> 0.633
-Confusion Matrix:
- [[ 84   4   2   9   3  11   9]
- [  3 149   4   2   8   1   4]
- [ 19  21 151  35  27  24  33]
- [ 13   4  17  98   5   8  10]
- [  2   7   3   2  55   3   0]
- [  7   1   1   1   4  35   9]
- [ 14   4   5   7   8  13  61]]
-Node Classification on random seed  820 -> 0.601
-Confusion Matrix:
- [[ 61   1   4   3   6  20  13]
- [  3 117   8   3  12   2   0]
- [ 21  31 124  24  26  36  50]
- [  6   3  14 112   4  12  13]
- [  2   6   7   2  71   0   3]
- [ 10   0   2   1   2  36   9]
- [  2   3   5   4   9  17  80]]
-Node Classification on random seed  821 -> 0.625
-Confusion Matrix:
- [[ 82   1   1   2   0  17   8]
- [  2 135  10   3   6   2  10]
- [ 35  13 128  32  26  14  49]
- [ 16   3  13  93   9   5  21]
- [  1   9   3   1  59   1   3]
- [  5   4   2   1   0  56   3]
- [ 10   3   1   5   9  16  72]]
-Node Classification on random seed  822 -> 0.606
-Confusion Matrix:
- [[ 79   0   8   4   1  17   8]
- [  7 125   3   1   8   3   7]
- [ 18  19  91  26  53  26  44]
- [ 10   6  21 110   6   3  10]
- [  3   7   0   0  78   2   0]
- [  7   0   2   1   0  50   4]
- [ 10   2  10   5  11  21  73]]
-Node Classification on random seed  823 -> 0.619
-Confusion Matrix:
- [[ 65   9   4   3   2   4  12]
- [  5 136   6   8   2   5   4]
- [ 18  19 137  35  25  38  34]
- [ 17   6  13 113   9   6  10]
- [  0   6   6   0  53   1   7]
- [  8   3   3   2   0  38   4]
- [ 13   4   9   3   9   9  77]]
-Node Classification on random seed  824 -> 0.576
-Confusion Matrix:
- [[ 73   5   1   5   3  17  17]
- [  2 108  12   5   7   2   8]
- [ 47  17 123  37  36  14  32]
- [ 13   3  12 117   4   3  12]
- [  1   1   6   2  56   1   3]
- [  9   2   5   0   0  54   8]
- [ 19   1  10  11  11  20  45]]
-Node Classification on random seed  825 -> 0.595
-Confusion Matrix:
- [[ 72   5  11   7   4  18   1]
- [ 13 117   8   2   4   5   3]
- [ 20  11 123  45  34  33  40]
- [  4   0  16 105   6  12  17]
- [  3  11   5   2  51   0   2]
- [  3   1   0   2   3  40   3]
- [  8   1   5   8   6  23  87]]
-Node Classification on random seed  826 -> 0.618
-Confusion Matrix:
- [[ 67   2   4   0   5   8   8]
- [  6 117   4   3  10   3   7]
- [ 23  22 153  30  31  18  41]
- [ 16   2  24  90  13   6  22]
- [  1   3   1   1  71   0   3]
- [  2   1   5   1   0  41   9]
- [ 16   8   4   5   9   5  79]]
-Node Classification on random seed  827 -> 0.632
-Confusion Matrix:
- [[ 67   3  16   7   3  13   6]
- [  5 145   4   2   7   1   2]
- [ 12  29 133  37  28  19  45]
- [ 11   4  14  97   5   8  13]
- [  3   5   1   0  62   1   5]
- [  2   1   4   1   0  47   9]
- [  1   5  11   7  10   8  81]]
-Node Classification on random seed  828 -> 0.598
-Confusion Matrix:
- [[ 73   1   4   6   1   8  17]
- [  5 125   6   5  15   0   4]
- [ 13  14 150  31  15  33  63]
- [  5   2   9 101   4  11  26]
- [  4   4   6   6  49   2   0]
- [  5   2   0   3   0  44   6]
- [ 11   4   6   9  16  20  56]]
-Node Classification on random seed  829 -> 0.547
-Confusion Matrix:
- [[ 72   4   3   3   5  18   3]
- [  1 134   7   3   8   6   2]
- [ 47  17  98  30  35  17  70]
- [ 20   6  18  95   9   6  10]
- [  1   8   3   1  62   1   0]
- [  7   3   2   7   3  34   1]
- [ 22   3   6   5  17  15  52]]
-Node Classification on random seed  830 -> 0.64
-Confusion Matrix:
- [[ 68   1  11   1   4  11  16]
- [  4 134   5   5   8   4   0]
- [ 23  25 160  31  18  15  28]
- [ 10   3  21 109  11  11   6]
- [  0  10   5   1  56   2   3]
- [  9   4   3   1   0  48   5]
- [  3   7  10   8   4  13  65]]
-Node Classification on random seed  831 -> 0.603
-Confusion Matrix:
- [[ 67   2   6   4   3   8  14]
- [  6 121   6   5  10   1   6]
- [ 21  17 106  34  28  30  46]
- [  6   1  13 127   5   7  18]
- [  1   8   2   4  51   1   5]
- [  8   0   2   3   1  52   2]
- [ 27   7   2   9   9   9  79]]
-Node Classification on random seed  832 -> 0.616
-Confusion Matrix:
- [[ 60   1   6   4   5  19  10]
- [  8 127   1   0   0   4   4]
- [ 39  30 151  40  19  22  33]
- [  4   1  21  98   7   1  17]
- [  3   9   3   0  61   1   3]
- [  2   0   3   1   0  40   6]
- [ 15   2   6  13   5  16  79]]
-Node Classification on random seed  833 -> 0.64
-Confusion Matrix:
- [[ 67   1   7   3   2  15   7]
- [  3 123  11   6   5   5   1]
- [ 12  23 165  18  21  39  30]
- [ 19   2  14  92   6   8  17]
- [  0   9   7   3  60   1   2]
- [  7   4   1   1   0  42   4]
- [  5   6   4   8   7  16  91]]
-Node Classification on random seed  834 -> 0.638
-Confusion Matrix:
- [[ 83   5   5   5   3  10  10]
- [  4 132  11   1  11   1   4]
- [ 17  30 145  21  15  23  41]
- [  6   3  13  99   1   7  13]
- [  1   9   5   0  61   0   2]
- [  5   3   5   0   1  55   5]
- [ 14   5  11   9   4  23  63]]
-Node Classification on random seed  835 -> 0.569
-Confusion Matrix:
- [[ 66   6   1   3   5  21  15]
- [  2 135   7   2  14   3   1]
- [ 43  31 113  18  44  24  32]
- [ 12   5  27  81   7   8  20]
- [  1   4   1   2  60   0   5]
- [  3   1   1   5   4  34   3]
- [  9   2  10   7   9  13  80]]
-Node Classification on random seed  836 -> 0.603
-Confusion Matrix:
- [[ 67   2   5  11   0  11   8]
- [  5 108   2   2  14   5   6]
- [ 27  37 133  40  22  38  40]
- [  6   4  12 110   4   4  10]
- [  0   4   6   1  64   1   2]
- [  8   2   0   2   0  41   1]
- [ 14   5   7  10   3  16  80]]
-Node Classification on random seed  837 -> 0.624
-Confusion Matrix:
- [[ 58   2   4   3   5  11  20]
- [  0 139   8   4   5   1   4]
- [  9  33 144  27  19  16  71]
- [  2   5  12  88   6   5  26]
- [  3  10   3   2  62   0   1]
- [  3   3   3   0   0  51   6]
- [ 11   1  10   4   6  12  82]]
-Node Classification on random seed  838 -> 0.633
-Confusion Matrix:
- [[ 62   1   6   6   3  10  17]
- [  3 117   4   7  10   7   1]
- [ 16  16 160  34  25  16  52]
- [ 10   0  20 112   2   5  16]
- [  1   3   5   3  57   1   0]
- [  3   2   2   2   3  49   5]
- [  6   6   6  10   3  19  76]]
-Node Classification on random seed  839 -> 0.585
-Confusion Matrix:
- [[ 83   3   3   3   3  14   7]
- [  5 122   4   1   5   6   8]
- [ 42  22  89  42  20  27  56]
- [ 11   6  16 112   6   8  11]
- [  0   5   3   2  53   1   2]
- [ 11   3   0   0   1  54   3]
- [  7   0   5   9   9  25  72]]
-Node Classification on random seed  840 -> 0.616
-Confusion Matrix:
- [[ 72   3   2   6   1  11  15]
- [  3 125  13   0  12   2   4]
- [ 23  13 150  24  29  24  54]
- [ 20   5  10  88   8   6  19]
- [  0   7   2   2  59   0   3]
- [ 10   1   1   1   0  38   7]
- [  9   7   3   4   9  11  84]]
-Node Classification on random seed  841 -> 0.617
-Confusion Matrix:
- [[ 73   1   8   1   3   7   9]
- [  3 127   3   2   7   1   3]
- [ 21  22 151  25  47  22  31]
- [ 13   6  21  92   9  18  13]
- [  2  11   4   0  59   0   1]
- [  4   0   2   1   3  34   5]
- [ 11   0  12  14   5  12  81]]
-Node Classification on random seed  842 -> 0.593
-Confusion Matrix:
- [[ 67   1   1   7   7   8  17]
- [ 10 121   8   8   6   2   7]
- [ 20  17 139  24  23  12  52]
- [ 25   7  22  84   5   7  12]
- [  1   4   2   0  67   3   1]
- [  6   0   2   3   0  54   7]
- [ 13   4  14  14  11  14  61]]
-Node Classification on random seed  843 -> 0.634
-Confusion Matrix:
- [[ 71   1   3   2   5  15  14]
- [  3 127   9   0   6   4   7]
- [ 22  27 132  35  29  17  45]
- [  8   1   8 104   3   5   6]
- [  2   4   6   2  61   0   3]
- [  8   4   1   0   1  47   7]
- [  7  10   9  11   8   8  92]]
-Node Classification on random seed  844 -> 0.619
-Confusion Matrix:
- [[ 61   1   2   9   8  18  18]
- [  9 123   1   5   8   4   2]
- [ 24  26 144  23  25  25  45]
- [ 11   6  22 102   9   7  11]
- [  1   5   2   0  62   2   0]
- [  3   1   1   1   2  47   4]
- [  2   4   5   9   6  14  80]]
-Node Classification on random seed  845 -> 0.658
-Confusion Matrix:
- [[ 70   5   2   6   2   7  16]
- [  2 114  14   2   7   2   4]
- [ 18  29 181  39  18  20  35]
- [  5   4  14  98   4   6  17]
- [  1   4   1   3  56   4   5]
- [  4   1   0   1   0  49   2]
- [ 12   0   7   5   5   9  90]]
-Node Classification on random seed  846 -> 0.604
-Confusion Matrix:
- [[ 66   3   5   3   5  12   6]
- [  5 137   4   4   4   1   4]
- [ 29  21 117  37  36  26  35]
- [ 22   1  11 105   1   8  18]
- [  1   8   4   2  61   1   2]
- [  6   2   0   0   0  45   9]
- [ 11   1  13   3   9  23  73]]
-Node Classification on random seed  847 -> 0.614
-Confusion Matrix:
- [[ 73   2   1   5   5   9   8]
- [  7 132   2   2   5   3   3]
- [ 31  19 103  23  56  23  37]
- [  8   8  22 104   8   5  12]
- [  2   9   0   1  63   1   0]
- [  2   2   1   2   3  67   1]
- [ 12   3   8   9  10  16  72]]
-Node Classification on random seed  848 -> 0.587
-Confusion Matrix:
- [[ 77   0   6   5  11   9   4]
- [  2 132   0   5   9   1   5]
- [ 17  18 135  50  21  22  40]
- [ 20   8  19  75   3   7  18]
- [  1   8   4   2  50   0   4]
- [  4   0   2   8   3  47   6]
- [ 16   2  19  18   8   8  71]]
-Node Classification on random seed  849 -> 0.604
-Confusion Matrix:
- [[ 73   4   4  11   9  13   8]
- [  3 118   4   8   5   3   2]
- [ 15  19 140  46  37  12  36]
- [ 11  13  23 105   6  11   7]
- [  1   6   0   0  62   0   4]
- [  2   1   6   2   3  50   7]
- [  5  11   5  15   7  11  56]]
-Node Classification on random seed  850 -> 0.618
-Confusion Matrix:
- [[ 62   3   7   4   0  11  14]
- [  7 126   2   4   4   0   7]
- [ 20  20 132  39  37  15  48]
- [  7   4  13 111   3   7  15]
- [  9   2   4   1  57   0   5]
- [  5   4   3   0   1  49   4]
- [ 12   2   5   8  11  15  81]]
-Node Classification on random seed  851 -> 0.611
-Confusion Matrix:
- [[ 61   8   4   6   4  10  12]
- [  7 123   8   1   1   6   3]
- [ 32  34 136  34  22  21  38]
- [  8   4  18 103   2  10   4]
- [  0  12   5   1  53   1   4]
- [  4   4   0   1   1  51   5]
- [ 10   3   5   8   5  23  84]]
-Node Classification on random seed  852 -> 0.599
-Confusion Matrix:
- [[ 60   3   1   7  11  16   8]
- [  3 128   5   3  12   3   3]
- [ 25  17 132  39  44  22  36]
- [ 14   2  17  99   6  10  19]
- [  0   2   0   0  61   2   1]
- [  5   0   4   1   1  45   7]
- [ 18   1   7  12   7   7  74]]
-Node Classification on random seed  853 -> 0.585
-Confusion Matrix:
- [[ 73   5   6   4   8   6  12]
- [  3 111   4   2   5   5   9]
- [ 18  32 144  30  42  27  43]
- [ 19   1  38  86   4   4   9]
- [  2   5   3   4  63   2   2]
- [  5   0   3   0   5  39   5]
- [  5   2   5  11  10  10  69]]
-Node Classification on random seed  854 -> 0.572
-Confusion Matrix:
- [[ 72   1   4   6   1   9  12]
- [  4 123   1   5  14   1   4]
- [ 29  37 143  29  20  30  43]
- [ 14   4  18  84   2   4  30]
- [  3   8   4   1  50   4   1]
- [ 12   0   3   1   2  37   7]
- [ 18   4  16   3   4  15  63]]
-Node Classification on random seed  855 -> 0.623
-Confusion Matrix:
- [[ 69   1   7   0  10  16   7]
- [  5 121   2   0   3   6   4]
- [ 26  30 132  17  41  23  36]
- [  4   5  24 106   9   8  14]
- [  1   6   5   2  52   0   2]
- [  4   1   2   1   3  50   5]
- [ 12   4   6   6   8  11  93]]
-Node Classification on random seed  856 -> 0.65
-Confusion Matrix:
- [[ 75   2   1   5   1  10  12]
- [  2 125   4   0   5   3   2]
- [ 40  19 153  21  17  20  42]
- [ 16   4   6 103   3   8  10]
- [  3   6   6   0  68   0   6]
- [  7   2   4   1   1  42   5]
- [ 11   3   8   2  11  21  84]]
-Node Classification on random seed  857 -> 0.608
-Confusion Matrix:
- [[ 48   5   6   8   2  11  14]
- [  9 144  10   8   8   2   3]
- [ 23  24 136  24  34  29  34]
- [  6   6  12  91   7   4  13]
- [  3   4   3   2  63   0   2]
- [  5   2   1   1   6  45   5]
- [  5   4  11  12   7  17  81]]
-Node Classification on random seed  858 -> 0.617
-Confusion Matrix:
- [[ 76   4   1   4   2  12   5]
- [ 10 122   3   6   5   4   1]
- [ 21  36 132  52  30  28  17]
- [  7   7   8 130   2   8  11]
- [  3   8   6   3  55   1   3]
- [  6   0   3   3   2  39   5]
- [  8   4  10  12   8  14  63]]
-Node Classification on random seed  859 -> 0.643
-Confusion Matrix:
- [[ 69   1   7   2   3   6  16]
- [  6 120  10   5  13   3   9]
- [ 17  28 165  21  32  15  33]
- [  7   0  19  99   3   1  14]
- [  1   6   7   4  61   3   3]
- [  5   1   4   3   2  48   1]
- [  2   3  22   4   8   7  81]]
-Node Classification on random seed  860 -> 0.607
-Confusion Matrix:
- [[ 71   3   4   7   3  12  11]
- [  4 128   6   5   4   1   1]
- [ 32  21 123  63  13  24  43]
- [ 11   5  14 104   5   7  10]
- [  0  11   4   4  53   1   0]
- [  6   0   1   4   1  54   0]
- [ 11   2   7  15   2  15  74]]
-Node Classification on random seed  861 -> 0.618
-Confusion Matrix:
- [[ 70   5   1  10   2   9   6]
- [  4 131   6   5   3   0  11]
- [ 24  31 156  35  26  17  29]
- [ 10   5  13 105   1  12  20]
- [  2   6   5   1  57   1   1]
- [  4   0   8   3   0  35   8]
- [ 12   4  13  14   6   9  64]]
-Node Classification on random seed  862 -> 0.617
-Confusion Matrix:
- [[ 74   1   0   7   5  14   3]
- [  3 122  11   4   4   4   1]
- [ 33  21 146  47  20  25  40]
- [ 10   6  12 107   2   8  12]
- [  2   7   4   1  56   1   1]
- [  7   0   1   6   0  47   3]
- [ 13   2  14  11   4  13  65]]
-Node Classification on random seed  863 -> 0.611
-Confusion Matrix:
- [[ 67   2   2   5   5  10  12]
- [  6 124   9   3   6   2   4]
- [ 26  30 148  41  16  18  32]
- [  8   7  27  98   0   8  18]
- [  1   3   3   5  56   3   1]
- [  5   5   5   3   2  41   5]
- [ 21   3   9   1   3  14  77]]
-Node Classification on random seed  864 -> 0.641
-Confusion Matrix:
- [[ 54   0   9   5   2   7  17]
- [  3 137   5   0  12   1   5]
- [ 34  17 169  23  30  26  25]
- [ 11   4  29  95   1   4   7]
- [  1   7   4   3  67   1   0]
- [  2   1   6   3   0  43   3]
- [ 11   5  13   6   9   7  76]]
-Node Classification on random seed  865 -> 0.646
-Confusion Matrix:
- [[ 61   3   2   6   1  14  15]
- [  8 144   4   1   2   4   5]
- [ 17  31 162  46  14  21  16]
- [ 12   2  19  98   5  10   6]
- [  1  11   6   3  52   0   2]
- [  4   3   2   2   0  46   4]
- [ 15   2   6  11   2  16  83]]
-Node Classification on random seed  866 -> 0.615
-Confusion Matrix:
- [[ 79   0   3   1   4  15   3]
- [  5 121   9   3  20   3   3]
- [ 11  18 127  38  31  30  35]
- [  3   1  13 122   3  14   9]
- [  2   2   3   2  65   0   8]
- [  7   1   7   0   0  34   6]
- [  6   3  13   8   9  33  67]]
-Node Classification on random seed  867 -> 0.605
-Confusion Matrix:
- [[ 66   7   4   3   3  11   3]
- [ 12 121   8   1   1   3   2]
- [ 27  20 144  29  26  24  50]
- [  5  16  12 102   8  13  12]
- [  4   8   3   2  53   3   1]
- [  3   2   2   0   1  56   3]
- [ 22   4  13   1   1  22  63]]
-Node Classification on random seed  868 -> 0.627
-Confusion Matrix:
- [[ 72   2   7   2   5  10   3]
- [ 13 130   5   3  17   1   4]
- [ 34   7 155  40  26  21  28]
- [  9   5  17  95   4  15   6]
- [  1   5   3   2  66   1   5]
- [  4   0   6   1   0  47   7]
- [ 19   7   4   4   5  15  62]]
-Node Classification on random seed  869 -> 0.612
-Confusion Matrix:
- [[ 69   2   8   4   3   5  10]
- [  5 133   5   3  15   0   1]
- [ 19  22 144  34  23  28  48]
- [  6   2  25 117   3   5  11]
- [  6   9  12   1  49   0   2]
- [  9   0   1   2   2  33   5]
- [  8   7  12   5   4  16  67]]
-Node Classification on random seed  870 -> 0.608
-Confusion Matrix:
- [[ 65   3   9   9   2   5   9]
- [  1 124   5   4  13   4   1]
- [ 15  25 133  61  24  21  37]
- [ 11   3  18 109   2   3  12]
- [  0   5   2   4  60   0   8]
- [  4   1   2   6   4  48   7]
- [  5   3   8   8   9  19  69]]
-Node Classification on random seed  871 -> 0.608
-Confusion Matrix:
- [[ 76   4   5   4   4   5   5]
- [  4 135  10   1  15   2   7]
- [ 36  36 147  28  23  25  22]
- [  8   6  17 105   5   7   7]
- [  4   2   3   1  56   2   1]
- [  6   1   2   2   2  40   2]
- [ 10   6  12  10   7  33  49]]
-Node Classification on random seed  872 -> 0.599
-Confusion Matrix:
- [[ 72   2   8   5   5   8   7]
- [  0 117   5   1  10   5   5]
- [ 21  26 150  22  26  34  23]
- [ 17  14  20  88  10  13  10]
- [  0   8   3   1  60   5   1]
- [  6   7   3   1   2  45   3]
- [  6   5  17   8   8  20  67]]
-Node Classification on random seed  873 -> 0.595
-Confusion Matrix:
- [[ 69   2   2   3   2  19  12]
- [  0  99   7   4   1   6   7]
- [ 32  23 148  32  21  25  47]
- [ 21   9  17  87   6   8  12]
- [  1   4   1   1  57   2   3]
- [ 10   0   2   0   0  47   7]
- [  5   1  12   6  12  20  88]]
-Node Classification on random seed  874 -> 0.606
-Confusion Matrix:
- [[ 91   7   6   5   6   3   5]
- [  3 108   7   3  12   8   5]
- [ 31  18 129  48  19  27  43]
- [ 13   5   9 105   3   9  10]
- [  2   6   7   0  51   0   3]
- [  9   0   0   2   1  46   4]
- [ 15   5   3  11   7  14  76]]
-Node Classification on random seed  875 -> 0.632
-Confusion Matrix:
- [[ 81   3   3   5   4  10  15]
- [  4 125   4   7   6   7   3]
- [ 19  16 141  45  25  16  35]
- [ 11   5  11 118   3   4  20]
- [  1  10   9   1  60   0   3]
- [  9   1   1   5   0  31   4]
- [  7   2   3  11   5  15  76]]
-Node Classification on random seed  876 -> 0.584
-Confusion Matrix:
- [[ 72   6   0   2   2  11  16]
- [  3 137  11   3  14   1   2]
- [ 26  17 131  30  41  28  30]
- [ 21   5  12  85   5   3  17]
- [  0   8   1   1  59   2   3]
- [  3   3  11   3   0  42   3]
- [ 10  12  12  13  16   9  58]]
-Node Classification on random seed  877 -> 0.627
-Confusion Matrix:
- [[ 64   2   2   6   3  12   8]
- [  2 127   3   1  14   3   2]
- [ 20  18 176  28  33  10  37]
- [ 12   4  16 102  10   3  16]
- [  0   6   2   3  62   0  10]
- [  6   5   7   0   3  51   6]
- [ 16   3   6   9  17   9  45]]
-Node Classification on random seed  878 -> 0.591
-Confusion Matrix:
- [[ 59   2   2   2   4  20  10]
- [  0 127   7   3   5   5   3]
- [ 14  20 137  39  30  31  60]
- [  6   6  12  89   7  12  10]
- [  1  10   3   3  58   0   3]
- [  7   3   3   1   2  46   7]
- [  9   7   2   8  11  19  75]]
-Node Classification on random seed  879 -> 0.602
-Confusion Matrix:
- [[ 76   4   4   6   5   6   9]
- [  4 126   2   2  11   3   9]
- [ 18  17 142  26  20  30  60]
- [ 15   2  18  83  11   2  19]
- [  2   4   6   0  56   2   3]
- [  5   1   0   3   3  51   8]
- [ 12   3  13   1   3  26  68]]
-Node Classification on random seed  880 -> 0.614
-Confusion Matrix:
- [[ 80   4   1   8   2   9  10]
- [  4 122   3   7   7   5  13]
- [ 30  12 165  39  17  15  35]
- [ 12   8  14 103   3   6  17]
- [  2   7   5   1  57   1   3]
- [  4   0   6   0   0  38   2]
- [  9   9  12  10  16  18  49]]
-Node Classification on random seed  881 -> 0.591
-Confusion Matrix:
- [[ 67   2   8   8   4  10  18]
- [ 10 107   1   0  12   2   9]
- [ 37  42 147  26  17  21  29]
- [ 10   5  20 113   3  10  12]
- [  3   7   5   0  48   2   1]
- [  9   1   2   8   0  36   6]
- [  7   7  11  11   3  10  73]]
-Node Classification on random seed  882 -> 0.61
-Confusion Matrix:
- [[ 71   2  20   7   3  11   4]
- [  4 121  10   0   8   5   8]
- [ 31  33 144  18  17  29  39]
- [ 12   4  10 108   4   7   6]
- [  0   5   2   0  65   4   2]
- [  5   2   0   1   2  39   2]
- [  9   6  19  11   4  24  62]]
-Node Classification on random seed  883 -> 0.641
-Confusion Matrix:
- [[ 69   1   3   3   7  16   7]
- [  2 129   9   2   2   6   3]
- [ 18  31 180  13  14  21  35]
- [ 23   2  20  91  10   5  13]
- [  1   6   6   4  53   6   0]
- [  5   1   3   5   2  44   7]
- [  9   4   7  14   2  11  75]]
-Node Classification on random seed  884 -> 0.599
-Confusion Matrix:
- [[ 54   1   0   3   3  19  22]
- [  7 123   6   1   4   4   3]
- [ 20  14 136  30  19  27  55]
- [  4   5  28  99  11   7  12]
- [  4   4   7   0  51   2   3]
- [  5   2   1   1   0  50   8]
- [ 18   6  13   2   7  13  86]]
-Node Classification on random seed  885 -> 0.649
-Confusion Matrix:
- [[ 60   7   7   5   3  16  13]
- [  2 126  11   2  16   2   3]
- [ 21  11 167  22  30  17  34]
- [ 11   1   8 101   8   9  18]
- [  0   2   4   2  61   0   2]
- [  9   3   3   1   0  48   3]
- [  9   2   6   7   3  18  86]]
-Node Classification on random seed  886 -> 0.603
-Confusion Matrix:
- [[ 71   1   4   4   3  22  13]
- [  2 123  11   4  12   3   2]
- [ 26  22 116  41  16  19  44]
- [ 13   4  23 115   9   2  11]
- [  0   9   4   1  61   1   0]
- [  4   2   2   0   1  38   9]
- [  7   6   8   7  14  11  79]]
-Node Classification on random seed  887 -> 0.587
-Confusion Matrix:
- [[ 78   3   3   9   6   7   9]
- [  7 115   9   3   9   5   3]
- [ 41  31 119  31  40  16  39]
- [ 10   7   8 111  16   3  12]
- [  4   6   1   0  65   3   2]
- [  6   0   2   1   3  28   8]
- [ 12   4   6   8   3  17  71]]
-Node Classification on random seed  888 -> 0.623
-Confusion Matrix:
- [[ 83   2   2   3   2  16   3]
- [  6 125   6   6   8   0   1]
- [ 21  15 160  41  15  25  47]
- [ 14   7  16  82   2   8  10]
- [  4   7   8   1  46   2   3]
- [  5   2   2   0   3  47  10]
- [ 12   3  10   7   3  19  80]]
-Node Classification on random seed  889 -> 0.575
-Confusion Matrix:
- [[ 53   2  13  11   8  13  12]
- [  2 128   2   2   6   1   5]
- [ 32  24 108  40  40  27  37]
- [ 10   3  14 100   9  11   7]
- [  0  11   1   1  72   1   3]
- [  1   3   3   0   1  47  10]
- [ 10   4   7  13   6  19  67]]
-Node Classification on random seed  890 -> 0.637
-Confusion Matrix:
- [[ 78   6   3   2   8   8   0]
- [  3 132   6   6   5   3   2]
- [ 18  38 137  43  18  19  28]
- [ 12   2  22  96   4   5  10]
- [  2   7   5   0  59   1   1]
- [  5   2   0   2   2  55   3]
- [ 13   7   8   6   8  20  80]]
-Node Classification on random seed  891 -> 0.576
-Confusion Matrix:
- [[ 68   7  11   3   1  14   8]
- [ 12 116  11   0   9   1   7]
- [ 25  11 135  38  39  12  38]
- [ 22   1  12  73   7  18  13]
- [  3   6   2   0  62   0   3]
- [  5   3  10   1   2  44   5]
- [  9   1  22   9   9  14  78]]
-Node Classification on random seed  892 -> 0.646
-Confusion Matrix:
- [[ 66   6   2   4   2   7  10]
- [  8 114  10   2  11   1   5]
- [ 18  13 157  34  32  24  25]
- [  3   4  10 125   4  14  16]
- [  3   5   3   0  55   0   1]
- [  5   5   0   0   1  38   6]
- [ 15   5   6   8   7  19  91]]
-Node Classification on random seed  893 -> 0.649
-Confusion Matrix:
- [[ 66   2   8   7   8   3  10]
- [  9 122   7   1   3   1   4]
- [ 13  20 157  14  24  31  49]
- [  9   4  18 107   3   4  15]
- [  0   9   1   0  67   1   1]
- [  9   4   1   2   4  47   5]
- [  6   2  10  13   7   9  83]]
-Node Classification on random seed  894 -> 0.617
-Confusion Matrix:
- [[ 60   4  14   3   6   9   5]
- [  4 115   5   1   5   3   2]
- [ 14  18 168  30  43  14  36]
- [ 21   3  11 109   7   6   8]
- [  1   3   3   1  68   0   2]
- [ 11   4   1   4   3  38   5]
- [ 13   4  15  17  10  14  59]]
-Node Classification on random seed  895 -> 0.608
-Confusion Matrix:
- [[ 71   2   5   9   6  14   9]
- [  8 119   7   5   9   4   4]
- [ 13  33 126  40  29  13  48]
- [ 12   5  15 104   3   7   8]
- [  2   6   2   1  68   1   4]
- [  6   2   3   0   3  42   6]
- [ 11   3   6   3   5  20  78]]
-Node Classification on random seed  896 -> 0.642
-Confusion Matrix:
- [[ 58   0   4   3   2  23  15]
- [  1 129   4   4   4   1   6]
- [ 14  27 153  27  16  20  47]
- [ 12   1   9 123   2  18   8]
- [  0   9   3   3  57   1   2]
- [  1   1   1   2   0  59   5]
- [  4   6   4  16   6  26  63]]
-Node Classification on random seed  897 -> 0.635
-Confusion Matrix:
- [[ 76   5   2   5   3   5  16]
- [  6 113   8   2  15   6   1]
- [ 16  21 185  29  18  15  30]
- [ 19   7  19  89   7   5   7]
- [  0   4   6   0  46   3   4]
- [  6   1   2   1   1  51   7]
- [ 10   2  15  21   3  12  75]]
-Node Classification on random seed  898 -> 0.613
-Confusion Matrix:
- [[ 82   2   1   9   4  13   6]
- [  8 136   3   0   7   1   3]
- [ 41  15 135  20  17  22  45]
- [ 13   6  15  88   2  14  19]
- [  3   2  10   3  60   2   2]
- [  7   2   3   1   4  47   1]
- [ 13   3   6  11   8  20  65]]
-Node Classification on random seed  899 -> 0.609
-Confusion Matrix:
- [[ 69   8   3   5   5   8  15]
- [  3 114   6   5   9   5   2]
- [ 24  45 145  40  22  20  32]
- [ 14   7  12 106   2   9  13]
- [  2   4   6   2  56   1   2]
- [ 11   1   0   1   0  45   3]
- [ 18   1   5   6   5   9  74]]
-Node Classification on random seed  900 -> 0.587
-Confusion Matrix:
- [[ 69   6   9   1   4  10  14]
- [  2 112  15   4  11   7  10]
- [ 29  17 133  49  16  18  49]
- [  7   5   9  89   8  12  24]
- [  0   7   2   1  62   0   5]
- [  6   3   0   0   2  48   5]
- [  9   4   2   9   7  15  74]]
-Node Classification on random seed  901 -> 0.642
-Confusion Matrix:
- [[ 80   6   4   3   0  13   3]
- [  4 120  13   0   8   3   1]
- [ 22  23 157  58  14  26  34]
- [ 11   4  17 113   4   5   9]
- [  2   6   5   1  53   1   4]
- [  5   0   1   3   1  42   8]
- [  7   1   4  13   3   8  77]]
-Node Classification on random seed  902 -> 0.605
-Confusion Matrix:
- [[ 75   1   3   4   4   7   7]
- [  4 123   3   2   8   6   2]
- [ 29  25 127  29  29  19  48]
- [ 35   3  12  93   2   3  10]
- [  5   6   3   0  67   0   4]
- [ 10   2   2   2   2  37   8]
- [ 17   6   9   5   7  12  83]]
-Node Classification on random seed  903 -> 0.594
-Confusion Matrix:
- [[ 70   1   2   8   5  16   9]
- [  3 111   7   2  17   6   3]
- [ 22  21 132  42  36  16  54]
- [  8   7   5 105   6   6  16]
- [  1   8  11   0  65   0   1]
- [  4   3   3   0   0  43   4]
- [ 11   5   9   5   9  14  68]]
-Node Classification on random seed  904 -> 0.573
-Confusion Matrix:
- [[ 70   3   2   2   2  13  13]
- [  8 130   6   4  14   3   2]
- [ 29  29 120  23  34  18  55]
- [  6   9   7 101   6   8  22]
- [  4   7   3   1  52   2   7]
- [ 12   0   1   2   0  42   8]
- [ 20   1   9   3  20   9  58]]
-Node Classification on random seed  905 -> 0.553
-Confusion Matrix:
- [[ 75   4   8   3   2   8   6]
- [  7 115   9   5   9   3   3]
- [ 31  32 120  46  29  29  34]
- [ 22  12  16  75   8   4  24]
- [  0  10   1   2  65   1   2]
- [  8   1   2   5   2  44   1]
- [ 11   2  14   7   7  17  59]]
-Node Classification on random seed  906 -> 0.661
-Confusion Matrix:
- [[ 71   1  15   6   5   7   4]
- [  6 145   4   0   2   1   0]
- [ 37  11 163  18  25  27  30]
- [  8   6  21  95   5   4  13]
- [  2   9   3   0  65   4   0]
- [  8   1   3   1   1  44   2]
- [  5   8   9   3  13  11  78]]
-Node Classification on random seed  907 -> 0.613
-Confusion Matrix:
- [[ 75   1   3  11   5  12   9]
- [  7 131   3   6   8   2   5]
- [ 28  12 128  44  29  18  34]
- [  7   3  18  85   2   6  22]
- [  1   7   2   3  66   3   1]
- [  6   3   2   2   0  42   5]
- [ 27   2   5   0   3  20  86]]
-Node Classification on random seed  908 -> 0.633
-Confusion Matrix:
- [[ 67   3   9   4   4  13   7]
- [  7 133   5   0   6   0   1]
- [ 13  24 154  42  24  13  46]
- [  5   8  19  93   3   6  12]
- [  3  17   2   0  56   0   1]
- [  5   4   5   0   1  47   1]
- [  7   3   6   7   8  23  83]]
-Node Classification on random seed  909 -> 0.626
-Confusion Matrix:
- [[ 68   3  10   5   5  14   4]
- [  5 123   5   2   1   5   4]
- [ 20  32 141  24  37  21  34]
- [  7   3  10 118   3   8   7]
- [  1   6   2   0  77   0   3]
- [  9   2   2   1   8  33   7]
- [ 17   8  13   7  10   9  66]]
-Node Classification on random seed  910 -> 0.586
-Confusion Matrix:
- [[ 54   3  10   2   4  19  12]
- [  6 123   4   3   7   4   9]
- [ 33  29 126  46  45  18  27]
- [ 10   4  14 106   4   7   2]
- [  2   6   2   6  55   0   2]
- [  4   0   5   1   5  46   4]
- [ 13   3   8  15   5  11  76]]
-Node Classification on random seed  911 -> 0.561
-Confusion Matrix:
- [[ 78   3   5   7   5   9  15]
- [  3 141   5   3   5   5   6]
- [ 24  22  93  56  45  20  30]
- [  9   4  12  88  20   7  31]
- [  3   9   3   0  71   0   4]
- [  1   0   1   5   0  39   3]
- [ 14   6   8  10   5  16  51]]
-Node Classification on random seed  912 -> 0.611
-Confusion Matrix:
- [[ 73   2   6   3   3   7  15]
- [  3 136   5   1   2   1   6]
- [ 16  22 124  32  69  15  38]
- [ 16   7  10  99   7   5  15]
- [  2   9   1   2  49   0   5]
- [  2   0   3   0   1  45   9]
- [  7   2   8   8   5  19  85]]
-Node Classification on random seed  913 -> 0.575
-Confusion Matrix:
- [[ 59   7   2  11   2  11  13]
- [  8 141   1   3   5   3   5]
- [ 22  25 134  50  21  38  24]
- [ 27   3  14  79  15   6   7]
- [  0  10   9   4  57   3   3]
- [  2   1   0   2   1  43  10]
- [  8   5   5   8  11  20  62]]
-Node Classification on random seed  914 -> 0.612
-Confusion Matrix:
- [[ 78   1   4   5   8  10   5]
- [  4 127   4   2   4   2   6]
- [ 31  23 133  33  22  35  42]
- [  7   1  12 106   3   6   6]
- [  3   4   6   4  65   2   4]
- [  5   1   1   5   1  43   6]
- [ 12   6  11  19   5  17  60]]
-Node Classification on random seed  915 -> 0.612
-Confusion Matrix:
- [[ 71   2   3   3   3  10   7]
- [  3 125   3   5   7   2   1]
- [ 21  19 144  29  35  25  43]
- [ 26   4  11  95   6  12  11]
- [  1   3   6   0  51   1   8]
- [  6   2   1   3   1  44   6]
- [ 12   2  12  13   6  14  82]]
-Node Classification on random seed  916 -> 0.606
-Confusion Matrix:
- [[ 61   3   6  11   5  13  11]
- [  7 120   7   4   5   2   4]
- [ 23  22 162  27  17  30  30]
- [ 14   9  21  90   4   5  13]
- [  0   4   7   0  64   2   3]
- [  3   1   2   9   0  48   3]
- [ 11   9  11  13  15   8  61]]
-Node Classification on random seed  917 -> 0.67
-Confusion Matrix:
- [[ 78   1   3   4   2  15  17]
- [  4 127   8   1   3   3   7]
- [ 14  26 175  40  17   8  30]
- [ 11   2  14 107   4   6  26]
- [  0   3   2   3  55   3   2]
- [  3   0   2   0   0  43   4]
- [  6   5   4   5   6  16  85]]
-Node Classification on random seed  918 -> 0.611
-Confusion Matrix:
- [[ 51   4   2   3   4  17  24]
- [  7 119  16   3  11   2   2]
- [ 10  15 173  24  46  15  38]
- [ 18   5  22  78   6   8  23]
- [  1   1   4   0  57   0   3]
- [  4   0   2   1   0  46   5]
- [  5   1   5   8   5  19  87]]
-Node Classification on random seed  919 -> 0.632
-Confusion Matrix:
- [[ 58   3   7  11   4   9   6]
- [  1 136   7  13   2   2   4]
- [ 27  38 146  32  24  13  36]
- [  2   3  12 103   5  12  15]
- [  0   6   3   0  66   1   4]
- [  4   0   2   4   0  51   3]
- [  3   1   9  18   7  15  72]]
-Node Classification on random seed  920 -> 0.648
-Confusion Matrix:
- [[ 69   2   4   8   4  11  11]
- [ 12 132   4   4   3   2   2]
- [ 13  18 166  26  35  15  49]
- [ 13   4  22 104   7   5  10]
- [  1   1   2   2  61   0   3]
- [  1   1   3   3   1  39   5]
- [  5   5  15   3   5  12  77]]
-Node Classification on random seed  921 -> 0.629
-Confusion Matrix:
- [[ 87   1   1  10   6   6   5]
- [  5 126   3   1  15   3   2]
- [ 23  12 128  26  39  25  55]
- [ 17   3   8 104   5   6  11]
- [  0   5   4   3  68   0   1]
- [  7   2   0   2   4  46   7]
- [ 14   2   2   5  12  13  70]]
-Node Classification on random seed  922 -> 0.617
-Confusion Matrix:
- [[ 64   6   3   3   9  14   5]
- [  6 120   3   2  10   3   6]
- [ 30  19 165  24  26  29  42]
- [  8   4  23  83   2   4  20]
- [  1   4   6   0  67   2   1]
- [  7   0   3   2   0  44   3]
- [ 11   3  13   3   8  15  74]]
-Node Classification on random seed  923 -> 0.643
-Confusion Matrix:
- [[ 61   1   8   5   4  13  23]
- [  3 133   2   2   9   6   3]
- [ 24  13 163  33  24  23  33]
- [  6   2  14 106   5   7  18]
- [  2   2   2   0  51   0   4]
- [  4   2   1   3   3  46   3]
- [  9   3   7   1  14  16  83]]
-Node Classification on random seed  924 -> 0.581
-Confusion Matrix:
- [[ 61   1   5  11   8  12   5]
- [  8 117   3   7  14   5   9]
- [ 30  28 122  56  20  17  36]
- [  9   1  10 106   6   8  20]
- [  0   6   2   2  57   2   5]
- [  4   2   1   1   1  39   9]
- [ 12   2  17  10   5   9  79]]
-Node Classification on random seed  925 -> 0.581
-Confusion Matrix:
- [[ 64   7   5   6   2  25  11]
- [  5 104   5   1  10   5   5]
- [ 28  11 152  39  19  18  40]
- [ 14   4  15 103   2  11  23]
- [  7   7   6   0  55   1   7]
- [  3   3   3   0   1  45   4]
- [ 18   3   7   5   7  26  58]]
-Node Classification on random seed  926 -> 0.624
-Confusion Matrix:
- [[ 78   3   4   4   1  13   6]
- [  8 126   1   1  12   1   7]
- [ 20  39 138  33  31  25  37]
- [ 13   2  10 120   3  11   8]
- [  2  11   4   4  46   0   0]
- [  4   0   4   1   0  48   5]
- [  5   3  19   5   7   9  68]]
-Node Classification on random seed  927 -> 0.637
-Confusion Matrix:
- [[ 80   6   4   1   3  13   4]
- [  1 129   5   2  10   1   8]
- [ 26  26 147  34  26  12  45]
- [ 11   4   6 103   6   9  11]
- [  0   9   3   2  58   0   4]
- [  8   1   1   0   0  44   6]
- [ 19   2   5   6   6  17  76]]
-Node Classification on random seed  928 -> 0.608
-Confusion Matrix:
- [[ 81   1   3   8   3  16   4]
- [  5 128   1   9   5   2   3]
- [ 19  38 127  55  25  15  40]
- [ 13   5  14 106   7   6   6]
- [  2  12   4   2  52   1   1]
- [  7   0   5   2   0  40   4]
- [ 13   4   3  10   7  12  74]]
-Node Classification on random seed  929 -> 0.61
-Confusion Matrix:
- [[ 72   3   5   8   8   7   5]
- [  7 125   4   3   8   0   4]
- [ 38  36 137  32  31  11  35]
- [ 18   2  11  95   9   1  16]
- [  0   5   6   3  63   0   3]
- [  8   2   4   0   0  43   5]
- [ 13   4  10   2   7  16  75]]
-Node Classification on random seed  930 -> 0.648
-Confusion Matrix:
- [[ 68   5   2   5   6   4   4]
- [  3 132   6   1   2   3   4]
- [ 16  22 168  42  23  14  44]
- [  5   6  27  94   3   4  14]
- [  0   4   3   0  61   1   4]
- [  4   3   3   4   2  37   5]
- [  9   8   5  10   7  15  88]]
-Node Classification on random seed  931 -> 0.606
-Confusion Matrix:
- [[ 72   8   5   2   3  11   8]
- [  8 129   3   4   5   1   3]
- [ 32  16 128  48  38  16  34]
- [ 27   3   4  87   7   7  23]
- [  4   2   4   0  63   0   3]
- [  8   3   1   1   1  47   3]
- [ 12   2  13   3   4  14  80]]
-Node Classification on random seed  932 -> 0.578
-Confusion Matrix:
- [[ 53   1   6   3   3  14   5]
- [  1 132   3   6   2   2   8]
- [ 20  38 140  52  15  18  44]
- [ 13   6  23  93  10   6  21]
- [  1   7   4   4  53   0   3]
- [  7   1   3   2   2  53   4]
- [ 14   6   5  15   5  19  54]]
-Node Classification on random seed  933 -> 0.612
-Confusion Matrix:
- [[ 64   1   6   2   5  11  13]
- [ 10 107   6   6   2   4   4]
- [ 24  18 145  30  33  23  50]
- [ 12   0  15 101  14  10  12]
- [  1   3   5   1  67   1   1]
- [  4   2   0   0   0  51   8]
- [ 13   2  12   4  12   8  77]]
-Node Classification on random seed  934 -> 0.627
-Confusion Matrix:
- [[ 61   2  11   5   6   9  13]
- [  2 130   7   2   6   2   3]
- [ 20  22 137  34  19  18  51]
- [  6   2  19 103  11   5  11]
- [  1   9   5   2  55   0   5]
- [  5   1   1   2   0  44   8]
- [ 10   4   9   6   6  13  97]]
-Node Classification on random seed  935 -> 0.628
-Confusion Matrix:
- [[ 73   3   4   7   3   7   9]
- [  1 151   6   4   5   2   9]
- [ 18  23 143  38  17  17  43]
- [ 22   5  11  80   5   8  24]
- [  2  12   5   1  48   1   1]
- [  4   3   2   2   1  48   5]
- [ 12   3   9   4   2  12  85]]
-Node Classification on random seed  936 -> 0.584
-Confusion Matrix:
- [[ 71   2   4   4   3  10  11]
- [  7 123   4   3  17   2   4]
- [ 25  21 129  35  45  24  52]
- [  9   3   9 103   5   4  16]
- [  1   4   6   1  69   0   1]
- [ 10   1   2   3   7  29   6]
- [ 11   1   9   2  23   9  60]]
-Node Classification on random seed  937 -> 0.628
-Confusion Matrix:
- [[ 77   2   3   2   4  17  14]
- [  4 119   8   5   5   4   3]
- [ 14  18 141  32  18  25  42]
- [ 15   1  20 117   2   2  19]
- [  1   5   4   3  45   2   0]
- [ 11   1   1   4   1  47   6]
- [ 13   3   5   9   6  18  82]]
-Node Classification on random seed  938 -> 0.624
-Confusion Matrix:
- [[ 65   4   4   4   4  20   0]
- [  9 140   1   0   6   1   2]
- [ 17  22 129  46  31  31  45]
- [ 14   2  13  89   8  10  11]
- [  2   6   3   1  64   1   1]
- [  3   0   2   0   0  52   4]
- [ 13   1   3  13  10   8  85]]
-Node Classification on random seed  939 -> 0.63
-Confusion Matrix:
- [[ 66   2   4   6   9  10  17]
- [  2 135   3   9   1   4   4]
- [ 21  25 149  30  18  15  56]
- [ 16   1  15  93   3   1  11]
- [  0   5   7   2  60   0   2]
- [  5   3   2   1   0  52   4]
- [ 10   5   6   8  11  16  75]]
-Node Classification on random seed  940 -> 0.616
-Confusion Matrix:
- [[ 62   1   1   8   2  20   9]
- [  4 132   6   3   3   4  10]
- [ 16  29 132  34  30  31  34]
- [  9   8   9 119  13   4  13]
- [  0   5   4   4  55   1   3]
- [  4   0   3   0   1  49   2]
- [ 16   1  14   8   3  14  67]]
-Node Classification on random seed  941 -> 0.596
-Confusion Matrix:
- [[ 84   0  10   3   8   7   4]
- [  6 140  10   1   3   0   3]
- [ 19  12 106  55  34  17  48]
- [ 16   6  26  86   9   4  12]
- [  3   8   1   3  59   0   3]
- [ 11   2   2   1   0  52   3]
- [  6   6   5  18   6  13  69]]
-Node Classification on random seed  942 -> 0.636
-Confusion Matrix:
- [[ 79   2  10   8   3   3  10]
- [  3 124   6   2   2   1   6]
- [ 24  13 154  28  39  27  35]
- [ 12   3  17 114   5   8  10]
- [  3   7   2   3  45   2   6]
- [  8   1   2   0   0  47   8]
- [ 18   2   7   3   7   8  73]]
-Node Classification on random seed  943 -> 0.6
-Confusion Matrix:
- [[ 69   5  10   9   8   5   5]
- [  3 136   9   0  16   0   5]
- [ 23  20 132  25  47  26  25]
- [ 16  10  22  79   8   8   7]
- [  2   8   2   0  57   1   0]
- [  6   1   3   3   0  50   6]
- [  6   2   8   5   7  28  77]]
-Node Classification on random seed  944 -> 0.613
-Confusion Matrix:
- [[ 76   3   3   7   1  13  12]
- [  4 123  12   0   5   3   4]
- [ 17  28 135  32  25  20  49]
- [ 11   4  13  97   6   7  18]
- [  1  12   5   0  60   0   4]
- [  6   0   1   4   0  54   7]
- [  8   3   8   3  12  16  68]]
-Node Classification on random seed  945 -> 0.65
-Confusion Matrix:
- [[ 63   7   5   7   4  15   9]
- [  4 135   3   1   4  10   4]
- [ 12  13 181  35  20  20  31]
- [  8   2  26  90   2   7  10]
- [  3   2   5   2  55   1   4]
- [  9   0   5   0   0  58   3]
- [  5   3   4   7   5  33  68]]
-Node Classification on random seed  946 -> 0.643
-Confusion Matrix:
- [[ 67   3   5   5   6   9   6]
- [  4 136   4   1   8   4   2]
- [ 25  20 130  40  16  19  50]
- [  8   3  18 118   5   9   8]
- [  1   5   3   4  61   1   2]
- [  2   2   4   1   0  57   0]
- [ 11   3   5   7   8  20  74]]
-Node Classification on random seed  947 -> 0.568
-Confusion Matrix:
- [[ 59   0   8   5   3   7  11]
- [  8 106  19   0   8   0   3]
- [ 23  20 144  62  18  23  39]
- [ 16   7  23 102   1   2  14]
- [  5   8   3   2  53   2   3]
- [  6   0   1   2   2  35  10]
- [  4   5  25  15   7  12  69]]
-Node Classification on random seed  948 -> 0.629
-Confusion Matrix:
- [[ 66   2   4   7   4  18   8]
- [  1 119   6   2   8   3   1]
- [ 16  24 151  30  15  19  63]
- [ 15   1  21  88   6   4  10]
- [  2   5   5   2  71   0   4]
- [  1   1   1   3   0  42   8]
- [ 12   5   6   9   3  16  92]]
-Node Classification on random seed  949 -> 0.632
-Confusion Matrix:
- [[ 81   1   2   2   7   7   5]
- [ 13 112   3   3  14   1   4]
- [ 20  33 153  28  36  19  33]
- [  7   5  18 110   2   5  12]
- [  3   7   3   2  71   2   2]
- [  0   1   2   4   0  31   5]
- [ 11   8   8   7  12  11  74]]
-Node Classification on random seed  950 -> 0.624
-Confusion Matrix:
- [[ 82   3   2   4   5  11  18]
- [  0 117   4   3  18   4   2]
- [ 20  17 172  19  18  26  42]
- [  9   5  18  79   8  16   7]
- [  0   6   3   1  60   1   5]
- [  8   2   1   0   2  45   9]
- [  8   3   7  11   8  22  69]]
-Node Classification on random seed  951 -> 0.615
-Confusion Matrix:
- [[ 87   2   3   4   8   1  11]
- [  5 119   6   4  16   2   3]
- [ 30  10 150  10  40  20  46]
- [ 22   6  11  92   5  14   6]
- [  2   4   2   2  66   1   2]
- [ 11   0   2   3   1  33   3]
- [ 23   4  10   4   5  21  68]]
-Node Classification on random seed  952 -> 0.615
-Confusion Matrix:
- [[ 80   2   3   4   8  13  12]
- [  4 122   9   3   8   4   4]
- [ 21  20 149  28  22  11  44]
- [  8   6  14 106   1  11  15]
- [  0  10   4   3  54   0   3]
- [  3   2   1   3   0  36  10]
- [ 11   5   9   5  27  14  68]]
-Node Classification on random seed  953 -> 0.641
-Confusion Matrix:
- [[ 65   1   3  14   6  14   6]
- [  9 136   1   4   3   1   7]
- [ 15  12 158  29  30  21  41]
- [ 22   7  10 100   4  11  17]
- [  1   3   2   0  65   1   4]
- [  1   0   1   2   0  40   1]
- [  5   3   1  16   9  21  77]]
-Node Classification on random seed  954 -> 0.578
-Confusion Matrix:
- [[ 56   4   9   8   6  19  22]
- [  7 125   7   2  11   1   8]
- [ 22  10 138  40  17  19  36]
- [ 13   1  20  98   3  13  18]
- [  4   7   7   4  62   0   1]
- [  6   1   3   4   2  41   5]
- [ 14   5  15  10   1  17  58]]
-Node Classification on random seed  955 -> 0.574
-Confusion Matrix:
- [[ 62   3   2   6   5   9  18]
- [  1 147   5   0   3   1   5]
- [ 41  28 118  44  35   6  41]
- [ 21   8  19  90   7   5  13]
- [  5   8   3   1  59   0   3]
- [ 11   1   9   2   0  29   4]
- [ 13   7  11   4   8  10  69]]
-Node Classification on random seed  956 -> 0.61
-Confusion Matrix:
- [[ 68   1   1   6   5  19  10]
- [  4 120   8   1  23   6   5]
- [ 30  19 132  32  32  18  36]
- [ 17   5  15  84   8   7  10]
- [  3   2   3   0  68   0   3]
- [  2   2   1   0   1  50  14]
- [  2   3   6   5   8  17  88]]
-Node Classification on random seed  957 -> 0.582
-Confusion Matrix:
- [[ 81   0   7   6   5  15  13]
- [  1 111  11   1  19   3   2]
- [ 20  18 122  73  34  36  28]
- [  5   5  16 102   3   6   5]
- [  1   4   4   1  60   1   5]
- [  6   1   2   3   0  44   1]
- [  3   2   7  11  13  21  62]]
-Node Classification on random seed  958 -> 0.586
-Confusion Matrix:
- [[ 67   1   3   8   4  17  12]
- [ 12 135   2   2   5   2  12]
- [ 24  31 123  42  23  34  38]
- [ 11  11  23 100   0   5  11]
- [  3   7   2   3  51   1   4]
- [  6   0   1   1   0  35   9]
- [ 10   3   5  13   2  11  75]]
-Node Classification on random seed  959 -> 0.588
-Confusion Matrix:
- [[ 72   1   3   3   5   4   9]
- [  2 122   5   5   5   2   6]
- [ 43  21 116  43  49  13  27]
- [ 14   4  14  96   6   9  20]
- [  1   6   3   6  65   2   2]
- [  6   1   3   2   1  50   4]
- [ 24   3  11   9   6   9  67]]
-Node Classification on random seed  960 -> 0.616
-Confusion Matrix:
- [[ 87   7   6   5   2  10   7]
- [  7 113   8  10   8   0   1]
- [ 32  21 160  45  30  13  34]
- [ 16  10   6 104   5   3   7]
- [  2   3   6   4  55   1   2]
- [  3   0   2   1   1  39   2]
- [ 18   2  10   4  17  13  58]]
-Node Classification on random seed  961 -> 0.633
-Confusion Matrix:
- [[ 76   2   2   3   4  15  12]
- [  3 149   5   3   3   2   7]
- [ 27  40 146  38   9  10  26]
- [ 30   0  11  95  16   3  10]
- [  3   5   2   1  61   3   5]
- [ 16   1   1   3   1  39   3]
- [  7   3   6  10   8   8  67]]
-Node Classification on random seed  962 -> 0.588
-Confusion Matrix:
- [[ 68   3   7   5   1   9  10]
- [  3 154   1   3   6   3   1]
- [ 24  37 118  22  46  27  47]
- [ 11   6  18  97   5   7  10]
- [  0   8   1   3  56   1   8]
- [  5   2   3   4   1  36   5]
- [  8   0  12   9  20  10  59]]
-Node Classification on random seed  963 -> 0.621
-Confusion Matrix:
- [[ 62   3   2   4   2   7  11]
- [  3 127   8   4   0   4   7]
- [ 26  21 161  47  24  22  37]
- [ 21   5   9 100  15   4   7]
- [  0   9   3   1  56   0   2]
- [  8   0   6   3   1  29  10]
- [  7   4   4  13   6   9  86]]
-Node Classification on random seed  964 -> 0.629
-Confusion Matrix:
- [[ 62   2   3   4   3   8   5]
- [  4 124   3   6   7   2   6]
- [ 19  26 155  27  24  16  54]
- [ 13   4   9 113   1   1  22]
- [  2   7   3   1  58   1   6]
- [ 11   4   6   0   3  34   5]
- [ 16   2  11   5   9  10  83]]
-Node Classification on random seed  965 -> 0.61
-Confusion Matrix:
- [[ 75   6   5   3   3   8   5]
- [  4 110   8   1  10   3   4]
- [ 16  21 135  29  47  40  24]
- [ 10   6  14 113   9   6   3]
- [  0   7   1   4  56   0   2]
- [  3   3   4   2   0  54   4]
- [ 15   2   7  16  10  25  67]]
-Node Classification on random seed  966 -> 0.579
-Confusion Matrix:
- [[ 63   8   2  20   6   7  11]
- [  4 115   9   2  16   3   4]
- [ 21  25 129  30  26  36  30]
- [  8   2  17 103   7  12  15]
- [  1   2   6   0  58   1   3]
- [  3   5   1   3   2  44  11]
- [ 19   5   6   7  13  12  67]]
-Node Classification on random seed  967 -> 0.645
-Confusion Matrix:
- [[ 65  13   8   3   4  19  13]
- [  2 135   7   5   5   4   1]
- [ 24  18 160  32  19  16  31]
- [  7   1  16 106   3   7   7]
- [  2  12   4   1  57   0   3]
- [  4   4   2   3   2  50   1]
- [  9   3   4  13   4  19  72]]
-Node Classification on random seed  968 -> 0.596
-Confusion Matrix:
- [[ 58   1   6   9   3   9  12]
- [  3 131   2   4  13   1   8]
- [ 25  22 152  27  27  37  36]
- [ 16   2  20  97   7   8   9]
- [  1   8   6   1  65   3   1]
- [  4   1   0  10   2  31   3]
- [  8   9  12   6   4  18  62]]
-Node Classification on random seed  969 -> 0.623
-Confusion Matrix:
- [[ 66   3   8   5   7  12  14]
- [  2 160   1   3   7   2   5]
- [ 27  25 137  24  27  21  34]
- [ 10   4  14 106   5   5  28]
- [  2   5   3   2  52   1   3]
- [  4   0   3   2   3  35   4]
- [ 12   1  12   1   8  18  67]]
-Node Classification on random seed  970 -> 0.616
-Confusion Matrix:
- [[ 88   1   2   6   2  13   5]
- [  3 119   8   5   5  11   1]
- [ 30  24 124  25  29  45  37]
- [  8   4  16 113   4   2   7]
- [  1   7   2   1  60   1   3]
- [  3   1   2   7   0  46  10]
- [ 11   1   2   8   5  26  66]]
-Node Classification on random seed  971 -> 0.576
-Confusion Matrix:
- [[ 81   3   3   3   2  20   1]
- [  5 108   4   1  17  11   8]
- [ 19  23 116  54  19  38  42]
- [ 10   6  30  97   1   5   3]
- [  2   5   4   0  59   7   3]
- [  7   1   1   3   2  47   0]
- [  8   5   4   2   9  33  68]]
-Node Classification on random seed  972 -> 0.647
-Confusion Matrix:
- [[ 84   1   4   4   3  12   4]
- [  1 138   4   6   7   1   3]
- [ 20  27 163  30  15  22  31]
- [ 15   9  29  81   6   3  14]
- [  3   3   4   2  53   1   2]
- [  4   2   1   1   0  43  13]
- [  3   5  17   2   5  14  85]]
-Node Classification on random seed  973 -> 0.65
-Confusion Matrix:
- [[ 77   1   8   6   4   6   5]
- [  2 139  11   0   2   6   0]
- [ 20  33 156  60  15  16  25]
- [  8   2   4 128   5   1  11]
- [  1   6   5   0  57   2   3]
- [  7   0   4   5   1  37   8]
- [ 12   3   6   9  13  14  56]]
-Node Classification on random seed  974 -> 0.617
-Confusion Matrix:
- [[ 89   1   5   4   6  10   3]
- [  7 137   4   3  13   2   3]
- [ 33  20 117  26  31  20  44]
- [ 14   7  15  97   7   3  12]
- [  1   5   1   1  68   0   3]
- [  5   3   1   0   4  37   5]
- [ 11   8  13   5   8  16  72]]
-Node Classification on random seed  975 -> 0.588
-Confusion Matrix:
- [[ 73   1   1  10   4  10  11]
- [  5 111   6   3  12   3   6]
- [ 33  11 138  31  47  33  48]
- [ 13   1   9  97  12  10   9]
- [  2   2   3   0  60   0   4]
- [  7   1   2   3   5  39   5]
- [ 10   4   5  11   4  15  70]]
-Node Classification on random seed  976 -> 0.602
-Confusion Matrix:
- [[ 75   1   8   4   4   8   6]
- [  7 106   8   1  12   6   3]
- [ 25  20 139  41  43  22  42]
- [ 13   2  17  83   8   2  12]
- [  5   3   1   2  79   0   5]
- [  2   1   0   1   2  49  11]
- [ 16   2   6  10   4  12  71]]
-Node Classification on random seed  977 -> 0.595
-Confusion Matrix:
- [[ 57   7  13   3   8  15   6]
- [  0 131   9   3   5   2   3]
- [ 12  29 121  33  55  16  57]
- [  9   3  17 115   2   5  12]
- [  1   7   5   0  49   2   5]
- [  0   2   2   3   1  42   7]
- [ 12   1   9   6   7  11  80]]
-Node Classification on random seed  978 -> 0.602
-Confusion Matrix:
- [[ 80   2   5  10   4   1  11]
- [  2 123   4   2   6   5   4]
- [ 34  25 135  39  22  28  36]
- [ 14   1  19 109   4   4  18]
- [  5   5   5   1  53   1   4]
- [  8   0   1   5   1  32   7]
- [ 16   8  10   3   1  17  70]]
-Node Classification on random seed  979 -> 0.639
-Confusion Matrix:
- [[ 72   2   4   4   6  11   8]
- [ 14 128   5   1   4   0   7]
- [ 20  19 138  23  29  18  49]
- [  3   1  28 123   7   6  13]
- [  0   4   1   5  50   1   6]
- [  6   0   4   0   1  42   7]
- [  9   6   6   8   9   6  86]]
-Node Classification on random seed  980 -> 0.595
-Confusion Matrix:
- [[ 72   0   1   0   5  14  10]
- [  7 120   5   6   8   2   2]
- [ 30  37 138  33  29  15  39]
- [ 13   6  20  75   8  15  12]
- [  3  10   1   0  58   0   2]
- [  4   1   2   0   1  49   8]
- [  7   5   3   9   4  28  83]]
-Node Classification on random seed  981 -> 0.647
-Confusion Matrix:
- [[ 70   4   9  14   7   7   6]
- [  5 141   5   2   6   2   1]
- [ 21  16 151  42  12  29  27]
- [  8   2  10 112   3  12  10]
- [  5  11   7   9  50   0   1]
- [  6   0   4   0   0  47   2]
- [ 16   7   8   7   2   8  76]]
-Node Classification on random seed  982 -> 0.611
-Confusion Matrix:
- [[ 65   2   7   0  10  14  14]
- [  2 138   2   1   4   4   1]
- [ 30  21 136  55  17  16  36]
- [  5   4  14 110   5   7  10]
- [  2  15   3   2  46   3   2]
- [  5   2   3   0   2  43   7]
- [ 16   2   7  23   0  14  73]]
-Node Classification on random seed  983 -> 0.657
-Confusion Matrix:
- [[ 78   2   0   5   3   8   9]
- [  4 111   6   1  13   0   8]
- [ 12  20 168  33  20  25  46]
- [  8   9   6  98  10   3  23]
- [  1   6   3   1  67   0   2]
- [  8   0   1   5   1  35   4]
- [ 13   2   7   3   0  12 100]]
-Node Classification on random seed  984 -> 0.634
-Confusion Matrix:
- [[ 63   2  10   7   3   7   4]
- [  3 131   2   1   4   3   2]
- [ 30  17 159  37  29  13  47]
- [ 10   5  10 100  11   9  11]
- [  2   4   2   1  65   0   3]
- [ 10   1   3   2   0  38   3]
- [ 12   6  12  10   9   9  78]]
-Node Classification on random seed  985 -> 0.619
-Confusion Matrix:
- [[ 63   4   5   3   4  12   7]
- [  4 128   6   0  10   0   4]
- [ 23  22 153  19  16  29  57]
- [ 13   4  31  83   3   4  19]
- [  1  10   8   1  67   0   0]
- [ 12   1   0   1   0  38   5]
- [  9   4   9   8   6   7  87]]
-Node Classification on random seed  986 -> 0.569
-Confusion Matrix:
- [[ 52   3   8   7   7  18  19]
- [  1 122   1   2   8   1   5]
- [ 17  10 107  47  51  31  58]
- [  9   8  11  93   2   6  17]
- [  1   7   2   2  59   0   2]
- [  3   2   5   3   2  42   8]
- [ 15   1   5   4  10  12  94]]
-Node Classification on random seed  987 -> 0.66
-Confusion Matrix:
- [[ 64   6   4   6   1  12  13]
- [  7 131   4   3   3   2   7]
- [ 27  12 169  19  23  22  27]
- [  6   1  23 101   6   9  10]
- [  3   2   6   0  64   1   8]
- [  5   0   1   0   2  46   8]
- [ 11   2   9   8   5  16  85]]
-Node Classification on random seed  988 -> 0.592
-Confusion Matrix:
- [[ 73   3   7   1   5   8  16]
- [  8 139   3   1  10   0   0]
- [ 43  31 114  35  28  22  39]
- [  6   4  16  97  15  11  12]
- [  2   2   7   2  54   3   2]
- [  9   2   4   1   2  49   0]
- [  7   3  12   3   7  16  66]]
-Node Classification on random seed  989 -> 0.598
-Confusion Matrix:
- [[ 56   7   1   4   2  12  21]
- [  1 111   9   1  26   2   5]
- [ 33  17 144  30  32  19  42]
- [  7   4  24 110  11   3  12]
- [  2   0   1   2  63   1   1]
- [  1   3   2   3   2  49   4]
- [  5   5  16   8   6  15  65]]
-Node Classification on random seed  990 -> 0.652
-Confusion Matrix:
- [[ 81   2   3   4   0  10   5]
- [  6 132   7   1   1   3   5]
- [ 22  36 166  32  18  22  21]
- [  5  12   9 110  12   3  13]
- [  2  11   4   0  52   1   0]
- [  6   5   2   3   2  35   9]
- [  9   7   7   6   6  16  76]]
-Node Classification on random seed  991 -> 0.607
-Confusion Matrix:
- [[ 82   2   4   5   2  11  10]
- [  1 117  10   2  20   5   6]
- [ 17  29 133  42  34  15  26]
- [ 12   6   7 111   7   6  10]
- [  1   9   4   1  68   1   0]
- [  7   5   0   0   4  31   0]
- [ 16   7  14  13   4  18  65]]
-Node Classification on random seed  992 -> 0.595
-Confusion Matrix:
- [[ 65   3   2   4  13  13  13]
- [  2 119   5   2  12   1   4]
- [ 26  19 139  15  37  29  55]
- [ 17   2  20  88  10  11  15]
- [  0   0   4   1  60   1   2]
- [ 10   0   1   0   2  50   3]
- [  9   3   3  10  12  14  74]]
-Node Classification on random seed  993 -> 0.621
-Confusion Matrix:
- [[ 71   5   6   6   2  14   7]
- [  1 128   3   5   5   3   5]
- [ 24  36 132  26  30  31  41]
- [ 10   4   4 121  11   8   9]
- [  1   1   1   3  48   3   4]
- [ 10   1   2   1   1  50   4]
- [ 20   5   1   4   3  18  71]]
-Node Classification on random seed  994 -> 0.655
-Confusion Matrix:
- [[ 86   3   4   4   1   4  11]
- [  7 126  13   2  11   4   0]
- [ 26  16 170  30  19  24  32]
- [  9   5  15 100   2   6  19]
- [  2   5   4   2  56   1   1]
- [  7   1   2   0   0  49   4]
- [ 16   6   7   4   3  13  68]]
-Node Classification on random seed  995 -> 0.644
-Confusion Matrix:
- [[ 61   3   6  10   3  12   7]
- [  7 135   2   2   5   4   4]
- [ 12  21 176  25  39  15  45]
- [ 10   3  23 102   5   6   9]
- [  2  12   5   1  48   1   2]
- [  1   3   1   2   0  47   1]
- [ 11   1   4  11   8  12  75]]
-Node Classification on random seed  996 -> 0.613
-Confusion Matrix:
- [[ 66   5   3  10   5  12   3]
- [  3 111   5   3  14   5   6]
- [ 21  19 150  38  26  30  33]
- [ 15   7  19  99  10   2   4]
- [  0   3   5   5  55   2   1]
- [ 11   0   2   1   1  54   5]
- [  6   5  11  11   7  13  78]]
-Node Classification on random seed  997 -> 0.624
-Confusion Matrix:
- [[ 63   1   0   9   3  12  16]
- [  3 121   3   2  13   3   6]
- [ 24  28 159  26  18  24  51]
- [ 16   2  17  95   5   6   7]
- [  2   6   6   1  61   1   3]
- [  8   2   2   0   0  56   9]
- [  8   2   5   2   7  17  69]]
-Node Classification on random seed  998 -> 0.614
-Confusion Matrix:
- [[ 61   8   3  10   4  13   8]
- [  8 131  11   0   5   2   3]
- [ 28  11 132  33  23  31  38]
- [  6   7  17 112   7   5  10]
- [  2   6  10   0  52   0   2]
- [ 10   1   1   2   1  52   2]
- [ 16   3   5  13   4  17  74]]
-Node Classification on random seed  999 -> 0.571
-Confusion Matrix:
- [[ 78   1   4   9   1  12  12]
- [  6 116   6   6  11   5   5]
- [ 35  17 121  56  20  16  49]
- [  8   7   5  84   5   6  28]
- [  4   8   6   0  57   0   1]
- [  4   2   3   3  11  36   3]
- [ 14   2   5  10   9  14  79]]
-Node Classification on random seed  1000 -> 0.627
-Confusion Matrix:
- [[ 65   5   7   4   2   9  13]
- [ 10 127   2   0   7   0   5]
- [ 25  35 135  34  34  14  33]
- [ 15   3  17 121   3   8   6]
- [  2   3   2   1  69   2   3]
- [  3   2   3   2   0  44   2]
- [ 14   7  10   3   7  16  66]]
-Node Classification on random seed  1001 -> 0.625
-Confusion Matrix:
- [[ 63   3   7   6   1   5  10]
- [  6 136  11   3   5   3   3]
- [ 25  17 163  19  37  24  41]
- [  9   3  13  89   7   3  26]
- [  0   8   2   1  62   3   2]
- [  8   0   5   1   0  41   9]
- [ 14   1  13   8   6   7  71]]
-Node Classification on random seed  1002 -> 0.606
-Confusion Matrix:
- [[ 62   3   7   1   1  15  12]
- [  1 133   2   1   8   0   4]
- [ 32  22 130  46  28  17  41]
- [ 12  11  19  97   3  12   7]
- [  0   7   5   3  65   1   1]
- [  9   2   1   0   0  36  15]
- [ 10   2   1   9  11  12  83]]
-Node Classification on random seed  1003 -> 0.627
-Confusion Matrix:
- [[ 72   0   5   4   5  12   7]
- [  2 114   5   2  21   1   5]
- [ 27  22 146  54  21  17  23]
- [  7   5  16 114   5   1   7]
- [  1   3   2   2  62   1   4]
- [  7   3   2   4   1  39   7]
- [ 22   3   7   8   7  15  80]]
-Node Classification on random seed  1004 -> 0.66
-Confusion Matrix:
- [[ 66   5   4   8   6   3  10]
- [  4 136   7   3   5   3   3]
- [ 23  24 167  28  17  17  26]
- [  5   6  13 117   3   2   8]
- [  3   8   7   3  60   2   2]
- [  9   1   4   1   1  50   3]
- [ 13   3  13   6  17  11  64]]
-Node Classification on random seed  1005 -> 0.615
-Confusion Matrix:
- [[ 66   7   2  12   8  13  10]
- [  8 107   9   4   9   1   3]
- [ 18  26 144  25  25  17  34]
- [  9   5  16 110   6   6   5]
- [  2  10   8   3  65   0   3]
- [  4   4   3   6   7  36   6]
- [ 10   1  13   9   2  16  87]]
-Node Classification on random seed  1006 -> 0.587
-Confusion Matrix:
- [[ 64   4   5   4   6   9  20]
- [  4 115   7   1  15   5   2]
- [ 16  35 147  52  25  28  20]
- [ 12   2  17  98  14   4  17]
- [  0   7   7   3  60   1   4]
- [  4   1   4   3   0  42   6]
- [  6   1   9   7   6  20  61]]
-Node Classification on random seed  1007 -> 0.608
-Confusion Matrix:
- [[ 71   0   6   1   4  13   7]
- [  3 123   3   0   8   8   4]
- [ 22  22 138  40  29  36  37]
- [  6   3  14 104   4  16  11]
- [  5   6   3   2  51   0   4]
- [  2   6   1   2   0  43   6]
- [ 11   4  12   8   6  17  78]]
-Node Classification on random seed  1008 -> 0.658
-Confusion Matrix:
- [[ 72   3   5   6   4   8  11]
- [  1 113   7   2   4   2   7]
- [ 18  31 172  25  19  12  36]
- [ 12   1  21 119   2   2   9]
- [  0   9   4   2  66   1   2]
- [  4   0   4   5   2  46   8]
- [  7   3  12  13   7  11  70]]
-Node Classification on random seed  1009 -> 0.648
-Confusion Matrix:
- [[ 75   0  14   7   2   9   6]
- [  0 139   6   2   3   2   3]
- [ 18  18 131  51  24  24  25]
- [ 14   2  14 111   1   7  13]
- [  3   7   3   3  68   0   2]
- [  6   2   0   2   0  48   6]
- [ 15   5   7  10   4  12  76]]
-Node Classification on random seed  1010 -> 0.625
-Confusion Matrix:
- [[ 80   3   0  11   0   9   8]
- [  6 124   1   4  12   4   8]
- [ 24  16 121  43  33  24  54]
- [  6   4   5 117   3  10  10]
- [  3   3   2   3  51   1   4]
- [  6   0   2   1   0  50   3]
- [  5   0  10  11   3  20  82]]
-Node Classification on random seed  1011 -> 0.586
-Confusion Matrix:
- [[ 50   8  12   9   9   7  13]
- [  1 134   5   0  10   4   6]
- [ 28  27 126  20  47  25  36]
- [ 14   6  11  92   4   8   9]
- [  2  11   2   1  65   0   1]
- [  3   3   4   2   0  40   5]
- [ 12   3  17   4   3  22  79]]
-Node Classification on random seed  1012 -> 0.648
-Confusion Matrix:
- [[ 60   2   3   3   8  11  26]
- [  6 140   5   6   3   0   2]
- [ 20  14 154  40  22  15  43]
- [  2   3   7 100   8   9  10]
- [  0   7   5   0  68   1   2]
- [ 11   1   3   0   0  41   5]
- [  8   1  13   8   6  13  85]]
-Node Classification on random seed  1013 -> 0.58
-Confusion Matrix:
- [[ 62   5   5   6   6   8  17]
- [  5 114   9   7   7   6   9]
- [ 36  44 125  25  26  20  23]
- [ 14   2  10 101   3  15   9]
- [  0   7   7   2  63   1   3]
- [  5   2   5   4   0  40   3]
- [ 15   3   9  12   8  17  75]]
-Node Classification on random seed  1014 -> 0.633
-Confusion Matrix:
- [[ 65   5  11   4   2   6   9]
- [  8 131   5   0   2   5   1]
- [ 29  29 154  38  20   9  34]
- [  9   3  13  98   3   8  17]
- [  3   7   1   1  67   3   3]
- [  6   0   6   1   0  42   9]
- [ 22   2   9   5   9  10  76]]
-Node Classification on random seed  1015 -> 0.618
-Confusion Matrix:
- [[ 83   1   1   4   3  16  14]
- [  6 114   7   1  16   4   3]
- [ 24  17 129  29  41  24  39]
- [ 11   3  10 103   1   9  17]
- [  1  10   4   1  62   2   0]
- [  3   0   2   2   2  38   6]
- [ 11   1  12   4   9  11  89]]
-Node Classification on random seed  1016 -> 0.614
-Confusion Matrix:
- [[ 77   3   6   4   4  13   8]
- [  0 124   6   2  13   3   5]
- [ 24  22 123  35  35  31  42]
- [  5   6  15 103   6   7  17]
- [  2   4   4   2  62   2   4]
- [  7   0   2   1   0  41   4]
- [  5   3   2   7   6  19  84]]
-Node Classification on random seed  1017 -> 0.604
-Confusion Matrix:
- [[ 79   4   1   5   4   7  12]
- [  4 102  11   3  23   4   1]
- [ 24  23 140  38  18  22  49]
- [ 15   2   7 101  10   9  14]
- [  1  10   3   1  63   1   2]
- [  9   4   5   2   2  38   1]
- [ 15   3   1   7   8  11  81]]
-Node Classification on random seed  1018 -> 0.65
-Confusion Matrix:
- [[ 80   1   6   0   0   7   5]
- [  0 112   5   1   8   3   1]
- [ 18  21 136  34  31  32  29]
- [ 11   8  13 137   4   5   8]
- [  0   7   6   0  60   2   4]
- [  5   2   4   2   0  42   5]
- [ 10   5  14   9   7  17  83]]
-Node Classification on random seed  1019 -> 0.588
-Confusion Matrix:
- [[ 72   6  11   4   0  11   5]
- [  3 108   3   5  13   2   9]
- [ 21  22 132  56  20  24  35]
- [ 14   3  15  98  10   9   5]
- [  1   6   3   1  60   0   6]
- [  2   4  13   0   1  39   4]
- [ 14   1  18   7   7  18  79]]
-Node Classification on random seed  1020 -> 0.64
-Confusion Matrix:
- [[ 83   2   4   3   0   6  15]
- [  1 135   4   1   2   5   5]
- [ 24  16 157  31  22  14  40]
- [ 13   9  13  85  12   5  16]
- [  2   9   3   2  49   1   3]
- [ 12   0   2   1   0  49   9]
- [ 13   6   4   3  13  14  82]]
-Node Classification on random seed  1021 -> 0.599
-Confusion Matrix:
- [[ 60   6   3   5  12  10  14]
- [  4 120   1   4  14   3   6]
- [ 24  19 163  29  14  21  46]
- [ 13   4  30  85   8   9  13]
- [  3   3   4   1  58   2   4]
- [  5   1   1   1   1  49  11]
- [  4   3  12   3   7  23  64]]
-Node Classification on random seed  1022 -> 0.637
-Confusion Matrix:
- [[ 73   2   4  12   4  10  13]
- [  5 126   8   2  12   1   0]
- [ 18  30 146  31  25  15  44]
- [ 13   7  11 109   6   6  11]
- [  1   6   2   1  69   0   1]
- [ 10   2   0   2   1  44   5]
- [ 10   3   6   4   9  10  70]]
-Node Classification on random seed  1023 -> 0.594
-Confusion Matrix:
- [[ 66   5   8  12   3   7   7]
- [  3 109   2   4   8   2   7]
- [ 15  19 146  28  41  32  38]
- [ 19   3  24 104   2   4  15]
- [  8   1   4   2  52   2   3]
- [  7   2   1   1   0  49   3]
- [ 18   1  10   6   7  22  68]]
-Node Classification on random seed  1024 -> 0.632
-Confusion Matrix:
- [[ 71   2   5   5   4  11  11]
- [  9 120  14   2   4   5   0]
- [ 12   7 174  32  12  33  43]
- [  9   5  17 104   9  10  15]
- [  2   7   3   1  59   3   1]
- [  5   1   4   4   0  39  10]
- [  7   9  10   8   3  14  65]]
-Node Classification on random seed  1025 -> 0.628
-Confusion Matrix:
- [[ 75   3   0   4   7  12   7]
- [  3 132   6  10   7   2  10]
- [ 14  13 149  39  30  23  40]
- [ 15   7  12  94   2   5  11]
- [  0   3   1   4  67   0   5]
- [  9   1   3   1   0  40   2]
- [ 14   0  10   6   8  23  71]]
-Node Classification on random seed  1026 -> 0.591
-Confusion Matrix:
- [[ 68   1   8   3   4  17   6]
- [  7 129   4   4   7   4   4]
- [ 44  20 126  59  16  32  26]
- [ 12   7  16  97   4   4   8]
- [  2   6   5   4  71   0   3]
- [  4   3   0   0   2  43   8]
- [ 13   3  20   4   0  15  57]]
-Node Classification on random seed  1027 -> 0.6
-Confusion Matrix:
- [[ 53   5   4   8   5  11  15]
- [  5 117   6   1  11   3   7]
- [ 21  26 148  32  22  22  55]
- [  6   4  17  95   4   8  15]
- [  0   9   6   3  60   6   3]
- [  6   1   3   0   3  40  10]
- [ 12   2   5   4   5   9  87]]
-Node Classification on random seed  1028 -> 0.629
-Confusion Matrix:
- [[ 68  10   0   6   0   3  15]
- [  3 128   6   2  10   4   4]
- [ 22  14 169  26  15  27  50]
- [ 10   9  17  82   6   8   7]
- [  1  10   3   0  58   0   2]
- [  2   2   5   0   1  47  11]
- [  5   5  12   8  14  16  77]]
-Node Classification on random seed  1029 -> 0.574
-Confusion Matrix:
- [[ 79   1   8   7   6  13   6]
- [  3 125   4  13   5   5   4]
- [ 24  13 107  47  42  12  55]
- [ 13   3  13  94   4  10  20]
- [  0   7   2   1  51   2   2]
- [  4   1   6   5   0  44   3]
- [  9   7  12   9   9  16  74]]
-Node Classification on random seed  1030 -> 0.649
-Confusion Matrix:
- [[ 70   3   4   2   4  17  15]
- [  3 115   9   5  14   4   5]
- [ 23  16 179  19  18  21  38]
- [ 10   3  17 105   2   3  12]
- [  0   2   3   2  54   2   5]
- [  2   1   2   2   1  48   7]
- [ 10   7  15   7   5  11  78]]
-Node Classification on random seed  1031 -> 0.618
-Confusion Matrix:
- [[ 76   3   4   5   0  15   5]
- [  9 118  15   3   7   2   1]
- [ 24  18 143  28  30  23  44]
- [ 11   6   6  98   4   6  15]
- [  0   7   4   0  75   0   2]
- [  5   0   6   1   3  42   2]
- [  9   4   2  20  13  20  66]]
-Node Classification on random seed  1032 -> 0.575
-Confusion Matrix:
- [[ 71   1   6   2   3  10  15]
- [  5 125   6   2  19   5   4]
- [ 11  13 127  32  49  19  47]
- [ 17   4  15  75  17  14  15]
- [  2   3   3   0  53   1   6]
- [  7   2   2   1   1  48   6]
- [ 10   2  13   8  10  17  76]]
-Node Classification on random seed  1033 -> 0.633
-Confusion Matrix:
- [[ 67   3   0  12   1   6  14]
- [ 15 136   4   1   6   6   5]
- [ 23  29 162   7  13  33  42]
- [ 13   5  13  96  14  10  14]
- [  1   7   7   2  57   1   1]
- [  3   0   0   1   0  44   6]
- [ 17   1  12   0   5  14  71]]
-Node Classification on random seed  1034 -> 0.618
-Confusion Matrix:
- [[ 52   9   2   5   0   8  16]
- [  3 132  16   2   6   1   0]
- [ 16  30 143  29  24  19  61]
- [ 12   1  12 108   7   2  10]
- [  6  11   2   1  50   2   1]
- [ 10   2   1   0   1  43   6]
- [ 16   3   6   5   5  13  90]]
-Node Classification on random seed  1035 -> 0.641
-Confusion Matrix:
- [[ 76   3   5   9   4  12   5]
- [  4 116   5   5  13   1   4]
- [ 11  39 151  42  21  19  39]
- [  8   5   6 107   3   5  10]
- [  0   6   5   3  63   0   3]
- [  5   1   1   4   0  51   6]
- [ 11   7  10   8   3   8  77]]
-Node Classification on random seed  1036 -> 0.638
-Confusion Matrix:
- [[ 86   1   2   7   2  11   8]
- [  5 119   2   7   5   1   5]
- [ 21  27 137  38  28  15  40]
- [  7  10  10 101   3   6  17]
- [  0   6   4   3  64   4   2]
- [  7   0   2   2   0  40   6]
- [ 14   6   4   3   8  13  91]]
-Node Classification on random seed  1037 -> 0.619
-Confusion Matrix:
- [[ 59   2   3   4   4  19  13]
- [  1 127   6   4   6   5   5]
- [ 27  22 158  34  39   8  48]
- [ 14   2   7 105   4   9  10]
- [  0   4   6   2  62   0   3]
- [  5   2   2   0   1  41   6]
- [ 13   6  11  10   4  10  67]]
-Node Classification on random seed  1038 -> 0.62
-Confusion Matrix:
- [[ 56   6   0   4   6  12  26]
- [ 13 131  11   1   3   2   3]
- [ 19  24 158  23  20  15  51]
- [ 11   4  11 105   2   0  19]
- [  0  12   2   0  59   0   3]
- [ 11   2   0   4   1  38   3]
- [ 10   8   4   0  12  22  73]]
-Node Classification on random seed  1039 -> 0.637
-Confusion Matrix:
- [[ 67   2   8   8   8   5  13]
- [  1 131   3   3   2   4   6]
- [ 16  27 152  34  29  18  33]
- [ 10   4  27 111   4   2   7]
- [  2   2   5   0  58   0   2]
- [  0   2   9   1   0  43  11]
- [  6   4  13  14   7  11  75]]
-Node Classification on random seed  1040 -> 0.626
-Confusion Matrix:
- [[ 72   6   4   4   3   8   5]
- [  3 129   5   4   4   3   4]
- [ 16  42 166  47  23  11  37]
- [  5   6  30  99   3   5   7]
- [  0   9   3   5  47   1   1]
- [  4   3   0   2   0  39   3]
- [ 12   7   9   8   8  14  74]]
-Node Classification on random seed  1041 -> 0.613
-Confusion Matrix:
- [[ 71   1   1   6   3   6  26]
- [  6 126   3   4   8   4   5]
- [ 32  32 134  30  31  20  35]
- [  8   3   8 107  11   6  14]
- [  0   7   5   1  54   0   2]
- [  6   1   4   5   1  35   7]
- [  6   2  10   9   4  14  86]]
-Node Classification on random seed  1042 -> 0.636
-Confusion Matrix:
- [[ 77   4   5   8   2  17   9]
- [  6 115   4   4   5   2   4]
- [ 18  12 169  52  15  19  42]
- [  7   6  20  88   6   7  18]
- [  0   5   2   2  54   0   8]
- [  4   1   3   0   1  53   1]
- [ 14   2   9   2   5  13  80]]
-Node Classification on random seed  1043 -> 0.592
-Confusion Matrix:
- [[ 66   3   4   4   3  10  30]
- [  8 124   3  10   1   1   9]
- [ 31  27 109  41  25  23  37]
- [  9   5   9 109   9  11  22]
- [  1   4   3   1  58   1   4]
- [  6   0   1   6   1  44   9]
- [ 11   4   5   4   6   6  82]]
-Node Classification on random seed  1044 -> 0.606
-Confusion Matrix:
- [[ 70   2   8   4   3  15   7]
- [  1 117  11   5   8   2   3]
- [ 27  19 134  35  22  22  53]
- [ 14   3   8 109   4  10  18]
- [  1   6   5   3  55   1   3]
- [  5   3   6   1   0  52   0]
- [  6   5  14   4   5  22  69]]
-Node Classification on random seed  1045 -> 0.609
-Confusion Matrix:
- [[ 82   6   5   6   3   3   5]
- [  2 120   4   1  20   0   9]
- [ 17  15 132  35  34  26  61]
- [ 11   0  10  94  13   7  21]
- [  1   2   3   1  66   1   1]
- [  6   3   2   2   2  46  14]
- [ 12   3   3   0  10  11  69]]
-Node Classification on random seed  1046 -> 0.575
-Confusion Matrix:
- [[ 61   3   6   8   1   8  11]
- [  5 125  12   2   3   1   8]
- [ 49  16 100  30  41  34  39]
- [ 15   2   8 114  10   5  12]
- [  1   5   5   1  51   0   6]
- [ 14   2   6   3   0  36   5]
- [ 13   6   3   6  12   8  88]]
-Node Classification on random seed  1047 -> 0.625
-Confusion Matrix:
- [[ 67   2   1   5  10  11  10]
- [  9 107   5   6  20   1   4]
- [ 27  14 166  38  44  14  25]
- [ 13   3   9 120   3   3  16]
- [  1   4   7   3  53   0   1]
- [  5   1   8   2   1  43   4]
- [ 16   2  12   3   5   7  69]]
-Node Classification on random seed  1048 -> 0.596
-Confusion Matrix:
- [[ 77   2   2   3   6   5  10]
- [  5 127  10   2  18   1   6]
- [ 25  22 122  33  41  28  39]
- [  4   7  11  94  20  10  16]
- [  4   5   3   1  53   1   0]
- [  7   0   0   0   1  53   6]
- [  4   3  12  10   7  14  70]]
-Node Classification on random seed  1049 -> 0.603
-Confusion Matrix:
- [[ 62   5   9   5   3   8  11]
- [  3 131   5   1   9   2   0]
- [ 13  40 133  28  33  39  36]
- [  5   5  21 107   6  11   5]
- [  2   6   5   4  58   2   2]
- [  4   2   8   0   1  47   3]
- [  6   2   8  11  12  16  65]]
-Node Classification on random seed  1050 -> 0.613
-Confusion Matrix:
- [[ 65   5   2   4   0  19   5]
- [  6 129   4   2   5   1   6]
- [ 25  21 163  28  29  20  44]
- [ 12   4  23  80   9  14  19]
- [  3   5   4   1  59   1   1]
- [  8   2   4   1   1  37   4]
- [  5   2   9   2   6  21  80]]
-Node Classification on random seed  1051 -> 0.608
-Confusion Matrix:
- [[ 73   1   4   1   4  12  11]
- [  6 111   9   3   4   7   8]
- [ 39  21 126  31  28  29  33]
- [ 15   5  19 107   4   4  21]
- [  0   4   6   1  65   0   6]
- [  8   1   1   0   0  40   2]
- [ 13   3   9   6   2  11  86]]
-Node Classification on random seed  1052 -> 0.591
-Confusion Matrix:
- [[ 74   2   1  11   2   6   9]
- [  0 132   7   2   5   1   5]
- [ 20  27 124  40  42  20  34]
- [ 10   2  16  90  14  13  14]
- [  1  10   3   1  60   3   4]
- [  3   2   1   0   4  38   3]
- [ 19  11   9   4   5  23  73]]
-Node Classification on random seed  1053 -> 0.592
-Confusion Matrix:
- [[ 68   2  11   8   6  16   7]
- [  7 126   3   5   4   8   4]
- [ 29  17 153  33  34  24  18]
- [ 16   3  28  88   8   4   5]
- [  0   6   5   1  51   5   1]
- [  5   2   3   6   2  42   5]
- [ 10   1  20   7   6  23  64]]
-Node Classification on random seed  1054 -> 0.634
-Confusion Matrix:
- [[ 75   2   1   7   5  14   7]
- [  5 132   2   5  10   4   5]
- [ 17  51 147  39  15  23  32]
- [ 10   6   8  91   1   8  21]
- [  3   5   2   1  65   0   2]
- [  2   0   0   1   3  45   6]
- [ 15   2   2   9   6   9  79]]
-Node Classification on random seed  1055 -> 0.6
-Confusion Matrix:
- [[ 66   1   2   3   6  13  17]
- [  2 138   8   2  11   3   5]
- [ 25  21 149  37  30  29  28]
- [ 20   3  20  91   8   4  12]
- [  3   4   3   5  59   2   3]
- [  3   2   0  10   1  30   2]
- [ 11   3   5  10   9  14  67]]
-Node Classification on random seed  1056 -> 0.599
-Confusion Matrix:
- [[ 79   2   2   0   5  11  20]
- [  3 113   7   8   9   6   6]
- [ 26  13 147  35  37  18  37]
- [ 15   1  16 102   3   8  17]
- [  1  12   4   7  52   0   2]
- [  7   1   3   1   0  44   6]
- [  6   9   7   5   3  22  62]]
-Node Classification on random seed  1057 -> 0.636
-Confusion Matrix:
- [[ 77   1   6   5   7  13   8]
- [  4 143   4   4  11   1   7]
- [ 25  10 155  51  27  19  39]
- [ 15   8  11  82   8   1   6]
- [  1   1   2   1  69   0   3]
- [  6   1   1   1   2  39   8]
- [ 14   3   5   6   3  15  71]]
-Node Classification on random seed  1058 -> 0.616
-Confusion Matrix:
- [[ 83   3   6   3   3  11   6]
- [  5 107   7   3  11   4   1]
- [ 20  15 137  22  42  24  52]
- [ 10   3  17  96   7   8  19]
- [  2   4   1   5  67   2   7]
- [  1   2   3   3   0  50   2]
- [ 15   4  10   7   3  11  76]]
-Node Classification on random seed  1059 -> 0.62
-Confusion Matrix:
- [[ 68   3   9   4   3  13   6]
- [  3 117   6   6  12   1   3]
- [ 25  24 146  24  29  22  36]
- [  7   8   9  99   9   5  20]
- [  2   5   1   1  54   1   5]
- [  8   2   1   3   1  51  10]
- [ 13   4  10   6   6  14  85]]
-Node Classification on random seed  1060 -> 0.646
-Confusion Matrix:
- [[ 75   0   5   2   2  17   6]
- [  6 130   4   0   4   4   7]
- [ 15  13 153  52  35  27  26]
- [  6   5  21  91   3   8  11]
- [  1   5   6   1  65   2   2]
- [  6   1   0   5   0  45   7]
- [  3   2   5   5   9  15  87]]
-Node Classification on random seed  1061 -> 0.636
-Confusion Matrix:
- [[ 74   2   3   3   6   6  11]
- [  7 128   4   1   8   1   4]
- [ 25  10 142  79  17  16  28]
- [  4   6  11 117   4  10  11]
- [  0   4   8   0  63   1   1]
- [ 11   1   1   1   1  43   4]
- [ 26   3   7   4   5   9  69]]
-Node Classification on random seed  1062 -> 0.638
-Confusion Matrix:
- [[ 62   2   2   3   4  17  10]
- [  7 128   7   1  19   3   2]
- [ 19  23 161  18  20  16  50]
- [  9   3  23 107   2   5  17]
- [  1   1   3   4  61   0   4]
- [  4   6   0   2   3  50   4]
- [  6   3  13   3   7  16  69]]
-Node Classification on random seed  1063 -> 0.635
-Confusion Matrix:
- [[ 58   1   1   5   2  11  12]
- [  9 123   9   4   4   2   7]
- [ 19  22 159  32  22  23  27]
- [ 16   2  15 118   7   6  13]
- [  4   5  11   0  57   1   3]
- [  6   3   3   1   2  48   5]
- [  3   4   7  11   7  18  72]]
-Node Classification on random seed  1064 -> 0.59
-Confusion Matrix:
- [[ 67   4   5   3   3  10  10]
- [  4 112   9   4  11   9   9]
- [ 33  10 121  32  30  27  45]
- [ 14   2   9 109   4   7  18]
- [  5   2   8   1  67   1   2]
- [  1   3   4   2   2  59   6]
- [ 11   8   9   8   9  16  55]]
-Node Classification on random seed  1065 -> 0.604
-Confusion Matrix:
- [[ 80   2  12   4   3  10   2]
- [  4 130   7   3   6   2   1]
- [ 32  33 122  36  38  28  29]
- [ 15   0  21  96   7   3  16]
- [  2   2   1   1  62   0   2]
- [  8   4   3   1   1  46   3]
- [ 17   3  11   3   4  16  68]]
-Node Classification on random seed  1066 -> 0.613
-Confusion Matrix:
- [[ 55   4   7  16   1   5  10]
- [  3 135   6   1   2   1   3]
- [ 17  41 133  45  32  10  41]
- [  6   2  15  98  12   3  11]
- [  4   6   0   1  67   1   2]
- [  5   1   0   9   2  52   4]
- [ 16   5  13   6   6  12  73]]
-Node Classification on random seed  1067 -> 0.618
-Confusion Matrix:
- [[ 79   2  11   5   4   5   8]
- [  7 136  10   2  12   3   5]
- [ 40  15 134  33  19  34  29]
- [ 20   7  16  94   1   2  12]
- [  0   3   9   1  54   1   2]
- [  3   4   3   1   0  48  11]
- [  9   2  12   4   5  10  73]]
-Node Classification on random seed  1068 -> 0.632
-Confusion Matrix:
- [[ 81   0   2   4  11  11   9]
- [  7 124   3   3  14   3   2]
- [ 30  16 146  31  28  20  27]
- [  8   0  12 108   6   6  20]
- [  1   5   5   4  68   0   1]
- [  8   1   3   2   4  34   5]
- [  9   1  17   8   4  17  71]]
-Node Classification on random seed  1069 -> 0.632
-Confusion Matrix:
- [[ 75   3   4   9  12   8  10]
- [  1 118  19   1  14   1   2]
- [ 32  15 163  25  21  14  34]
- [ 13   4  24  97   5   6   8]
- [  0   3   2   1  65   0   7]
- [  5   1   4   3   3  38   2]
- [ 19   5   9   7   7   5  76]]
-Node Classification on random seed  1070 -> 0.631
-Confusion Matrix:
- [[ 70   2   7   4   1  19  10]
- [  7 101   3   8   9   4   1]
- [ 18  19 162  38  21  34  31]
- [  9   4  13 117   5  11   9]
- [  2   5   5   1  56   2   4]
- [ 10   2   1   0   1  47   1]
- [ 13   3   8   2  10  12  78]]
-Node Classification on random seed  1071 -> 0.622
-Confusion Matrix:
- [[ 68   5   7   9   3   7   6]
- [  7 134   5   0   8   0   2]
- [ 26  37 134  43  19  20  39]
- [ 17   1   1 103   3  11  17]
- [  1  12   2   1  56   1   0]
- [  8   1   2   0   0  47   9]
- [  6   8  11  12   4   7  80]]
-Node Classification on random seed  1072 -> 0.61
-Confusion Matrix:
- [[ 76   1   5   1   4   7  11]
- [  3 119  12   6   6   1   2]
- [ 23  30 130  32  41  22  33]
- [  8   4  27 112   5   5  10]
- [  3   4   2   0  59   0   4]
- [ 10   1   2   1   0  38  15]
- [ 13   2   7   3   6  18  76]]
-Node Classification on random seed  1073 -> 0.58
-Confusion Matrix:
- [[ 52   4   8   7   4  15  15]
- [  5 116  12   0   7   2   6]
- [ 21  25 142  34  23  30  47]
- [ 10   7  12 102   0  10  13]
- [  1  11   4   2  57   1   3]
- [ 13   0   1   4   0  38   8]
- [ 11   4   7   6   7  20  73]]
-Node Classification on random seed  1074 -> 0.61
-Confusion Matrix:
- [[ 65   4   6   3   5  18  18]
- [  4 123   1   5   7   3   6]
- [ 25  23 151  29  33  19  42]
- [ 13   6  22  81   2   3  20]
- [  4   4   2   1  53   1   1]
- [  3   0   4   2   3  50   5]
- [ 11   5   5   6   7   9  87]]
-Node Classification on random seed  1075 -> 0.631
-Confusion Matrix:
- [[ 78   9  12   2   7   9   2]
- [ 10 143   7   1   8   0   0]
- [ 19  30 127  47  27  15  38]
- [ 11   3   5 111   4   4  21]
- [  2   8   2   0  64   1   0]
- [  4   5   0   4   0  40   5]
- [  8   3   4   3   5  24  68]]
-Node Classification on random seed  1076 -> 0.595
-Confusion Matrix:
- [[ 71   6   5   3   4  10  17]
- [  7 129   7   8   5   0   9]
- [ 26  18 127  39  32  15  38]
- [ 15   4  18  99   7   4   9]
- [  1   3   5   4  60   2   0]
- [ 10   5   3   1   0  40   3]
- [ 16   4   3  16   9  14  69]]
-Node Classification on random seed  1077 -> 0.631
-Confusion Matrix:
- [[ 52   2   2   7   1  13  17]
- [  3 115   6   0  24   3   2]
- [ 24  16 184  21  31   9  32]
- [ 22   7  23  96   3   6  14]
- [  4   3   9   5  57   1   0]
- [  8   0   1   2   0  43   6]
- [ 11   2   4   7   9   9  84]]
-Node Classification on random seed  1078 -> 0.613
-Confusion Matrix:
- [[ 78   1   3   3   3   9   6]
- [  4 148   3   3   2   7   4]
- [ 53  10 140  26  26  17  39]
- [ 26   7  18  75   2   3  20]
- [  0   6   8   1  50   1   1]
- [  6   0   3   3   1  45   8]
- [  9   2   6   9   5  23  77]]
-Node Classification on random seed  1079 -> 0.544
-Confusion Matrix:
- [[ 73   0   6   4   1   7  18]
- [ 15 127   8   1   9   1   1]
- [ 25  14  87  51  49  25  58]
- [ 17   3  17  86   9   8  18]
- [  1   5   0   2  60   0   2]
- [  8   1   1   0   0  43   7]
- [ 25   1  16   5   7  10  68]]
-Node Classification on random seed  1080 -> 0.643
-Confusion Matrix:
- [[ 61   0   5   6   2  14  15]
- [  0 146   2   2   6   5   2]
- [ 16  27 132  42  18  19  49]
- [ 12   3  18 122   1   4   7]
- [  2   4   6   2  53   6   2]
- [  8   2   1   2   0  52   2]
- [  9   3   7   6   6  14  77]]
-Node Classification on random seed  1081 -> 0.601
-Confusion Matrix:
- [[ 83   7   7   2   2   9  10]
- [  5 123   4   0   2   8   7]
- [ 25  21 134  35  24  30  59]
- [ 12   8  13  76   7  12  16]
- [  2   8   2   2  57   2   0]
- [  4   0   0   3   2  48   8]
- [ 12   2   9   3   8   7  80]]
-Node Classification on random seed  1082 -> 0.595
-Confusion Matrix:
- [[ 68   3   2   4   4  12  17]
- [  1 135   8  14   3   0   4]
- [ 28  24 146  51  19  42  18]
- [ 12   4  10  85   3   6  19]
- [  2   7   4   5  45   2   1]
- [  2   3   0   0   1  38  10]
- [ 18   4   6  10   7  15  78]]
-Node Classification on random seed  1083 -> 0.616
-Confusion Matrix:
- [[ 65   2   2   4   7  13   8]
- [ 10 121  13   1   7   3   5]
- [ 29  12 137  29  42  23  30]
- [ 11   5   4 117   5   6   8]
- [  2   9   1   4  51   2   1]
- [  5   2   3   6   1  45   6]
- [  8   9  12   4   5  25  80]]
-Node Classification on random seed  1084 -> 0.592
-Confusion Matrix:
- [[ 70   2  19   2   4   7  13]
- [  2 123  10   4   7   1   6]
- [ 38  13 126  38  30  17  43]
- [ 15   4  22  87  13   2  14]
- [  1   5   4   0  60   0   4]
- [  7   3   4   1   0  46   4]
- [ 18   2   8   7   5   9  80]]
-Node Classification on random seed  1085 -> 0.6
-Confusion Matrix:
- [[ 73   7   1   6   3  13   8]
- [  2 118   7   6   8   4   2]
- [ 15  20 150  54  23  24  43]
- [  4   5  13 102  13  13   9]
- [  1   9   3   0  57   0   3]
- [  5   1   7   5   2  37  10]
- [ 21   0   8   4   8  10  63]]
-Node Classification on random seed  1086 -> 0.612
-Confusion Matrix:
- [[ 69   4   4   7   2   8   9]
- [  6 115  11   3  13   1   3]
- [ 33  16 137  33  44  16  37]
- [ 11   5  18 105   5   4  13]
- [  0   7   4   1  53   2   1]
- [  5   3   5   2   0  41   5]
- [ 13   4  12   4   8   6  92]]
-Node Classification on random seed  1087 -> 0.627
-Confusion Matrix:
- [[ 88   1   2   4   1  11   6]
- [  5 120   3   4   3   7   6]
- [ 21  18 132  26  43  31  37]
- [ 13   3  21  98   4   7  15]
- [  0   6   5   1  66   1   1]
- [  4   0   4   2   0  51   3]
- [  4   2  13   6   8  21  72]]
-Node Classification on random seed  1088 -> 0.624
-Confusion Matrix:
- [[ 62   5   2   7   5  15   2]
- [  2 143   2   0  11   4   2]
- [ 28  16 154  32  22  24  31]
- [ 21   7  13  99   8  14   9]
- [  2   4   5   2  55   4   1]
- [  1   2   2   2   0  38   9]
- [ 15   9   9   9   8  10  73]]
-Node Classification on random seed  1089 -> 0.603
-Confusion Matrix:
- [[ 65   1   9   6   5  10   4]
- [  9 127   2   4  11   2   3]
- [ 19  19 141  28  29  35  42]
- [ 16   2  10  90   8  16  13]
- [  3   7   3   0  63   1   3]
- [  4   5   0   1   1  49   2]
- [ 11   6   7   5  10  25  68]]
-Node Classification on random seed  1090 -> 0.629
-Confusion Matrix:
- [[ 68   2   6   4   6   3  17]
- [  6 129   8   1   4   7   4]
- [ 25  16 152  30  32  14  33]
- [  8   4  27 106   7   3   4]
- [  0   7   3   1  59   0   3]
- [ 12   2   4   2   0  44   4]
- [  9   5   8  14  11  15  71]]
-Node Classification on random seed  1091 -> 0.62
-Confusion Matrix:
- [[ 60   1  13   3   2  12   6]
- [  6 125   6   3   7   3   8]
- [ 25  30 136  19  39  30  38]
- [  9   1  17 109   2   5  16]
- [  1   0   6   3  67   1   0]
- [  2   0   4   4   0  45   8]
- [  3   2  12   3  12  18  78]]
-Node Classification on random seed  1092 -> 0.622
-Confusion Matrix:
- [[ 73   3   2   3   4  18   3]
- [  4 125   4   3  18   3   1]
- [ 17  32 137  28  27  32  30]
- [ 18   5  11  89   5  12   9]
- [  0   4   8   0  66   1   2]
- [  4   1   3   1   4  55   3]
- [ 11   6  10  10   7  11  77]]
-Node Classification on random seed  1093 -> 0.608
-Confusion Matrix:
- [[ 65   4   6   9   7   9  14]
- [  6 123   4   2  10   3   4]
- [ 14  23 143  44  18  35  31]
- [ 16  11  17 102   2   9  12]
- [  0   7   1   2  59   0   1]
- [ 11   1   1   1   0  35  10]
- [ 12   6   8   3  11   7  81]]
-Node Classification on random seed  1094 -> 0.633
-Confusion Matrix:
- [[ 80   1   2   5   3   7  10]
- [ 10 126   4   6  10   3   1]
- [ 37   9 138  29  25  20  44]
- [  9   1  23  67   3  13   6]
- [  0   5   2   3  73   2   4]
- [  6   1   3   0   1  55   6]
- [ 15   2   6   3   7  20  94]]
-Node Classification on random seed  1095 -> 0.585
-Confusion Matrix:
- [[ 73   0   3   5   6  16  17]
- [  4 114  10   1   7   3  12]
- [ 21  24 116  34  53  17  44]
- [  5   2  10  97  11   5  21]
- [  1   2   5   0  68   0   2]
- [  2   4   1   2   3  46   9]
- [ 11   3  13   4   8  14  71]]
-Node Classification on random seed  1096 -> 0.604
-Confusion Matrix:
- [[ 60   1   2   8   5  19  16]
- [  3 127   6   8   4   3   5]
- [ 23  33 134  49  19  23  33]
- [ 15   1  16  92   5   4  11]
- [  0   5   6   3  63   0   1]
- [ 12   1   0   1   0  37  10]
- [  6   3   8   2   6  20  91]]
-Node Classification on random seed  1097 -> 0.593
-Confusion Matrix:
- [[ 65   2  10   3   6   8  10]
- [  6 136   1   4  11   1   1]
- [ 24  18 120  46  31  20  52]
- [ 20   2  13  87   9   6  14]
- [  1   4   6   0  63   1   3]
- [  4   0   3   5   3  45   2]
- [ 16   1  11   8  11  10  77]]
-Node Classification on random seed  1098 -> 0.609
-Confusion Matrix:
- [[ 74   3   3   1   5  10   7]
- [  6 121   5   4   4   1   5]
- [ 34  16 151  40  15  34  22]
- [ 19   4  11 108   2   8  22]
- [  2   4   3   1  64   2   4]
- [  9   4   7   3   0  34  10]
- [ 12   3  17   3   5  21  57]]
-Node Classification on random seed  1099 -> 0.617
-Confusion Matrix:
- [[ 64   7   3   1   5  12  17]
- [  2 131  12   4   5   2   8]
- [ 24  22 131  35  22   6  41]
- [ 15   3  12 107   7   2  21]
- [  0   7   2   0  73   0   2]
- [ 14   2  10   1   1  36   5]
- [  7   8  14   3   9  10  75]]
-Node Classification on random seed  1100 -> 0.6
-Confusion Matrix:
- [[ 76   0   2   3   5   6  13]
- [  3 120   1   0  17   4   4]
- [ 14  16 133  59  39  36  38]
- [  7   6  20  86   5   5  18]
- [  1   3   7   1  66   1   0]
- [  1   3   1   1   2  43   4]
- [  7   2   5   4  17  19  76]]
-Node Classification on random seed  1101 -> 0.632
-Confusion Matrix:
- [[ 70   3   1   4   4  15  13]
- [  4 136   4   1   5   0   5]
- [ 26  24 172  14  13  25  51]
- [  7   4  23  95   6   7  10]
- [  2  11   6   4  42   1   2]
- [  5   3   4   1   0  50   6]
- [  8   6  10   4   6  20  67]]
-Node Classification on random seed  1102 -> 0.595
-Confusion Matrix:
- [[ 67   3   4  15   2  10   7]
- [  1 135  10   4   4   4   2]
- [ 23  30 112  32  62  20  27]
- [  9   7  11 108  10   9   7]
- [  0   5   2   1  54   1   4]
- [  5   1   4   5   1  44   7]
- [ 10   3   9  10  13  11  75]]
-Node Classification on random seed  1103 -> 0.656
-Confusion Matrix:
- [[ 68   6   6   5   5   7   3]
- [  6 128   6   0   3   1   2]
- [ 19  34 159  30  18  14  32]
- [ 12  10   6 113   3   7  11]
- [  3  10   3   0  58   1   1]
- [  4   2   6   1   1  42   3]
- [ 15   5  10   6   6  21  88]]
-Node Classification on random seed  1104 -> 0.586
-Confusion Matrix:
- [[ 68   1   6  11   2   9   6]
- [  8 120   9   4  11   2   5]
- [ 34  18 142  28  22  33  28]
- [ 25   1  21  91   9  11   7]
- [  0   3   8   0  58   0  11]
- [  4   1   2   4   6  36   3]
- [ 12   3  17   8   4  17  71]]
-Node Classification on random seed  1105 -> 0.611
-Confusion Matrix:
- [[ 80   3   7   5   2   8   1]
- [  6 136   4   3   3   1   5]
- [ 23  28 126  37  30  25  45]
- [ 17   4  17  98   5   5   6]
- [  2   8   1   3  64   0   4]
- [  7   2   4   1   3  43   2]
- [ 10   7  11  15   6  13  64]]
-Node Classification on random seed  1106 -> 0.671
-Confusion Matrix:
- [[ 61   1   1   2   4  18   6]
- [ 13 129   2   4   8   2   8]
- [ 24  14 191  20  14  26  28]
- [ 12   3  18  97   5   6  11]
- [  2   1   5   0  62   1   2]
- [  8   1   3   1   1  50   3]
- [ 18   3  10   4   5  11  81]]
-Node Classification on random seed  1107 -> 0.612
-Confusion Matrix:
- [[ 61   2   4   8   9   6  16]
- [  6 126   4   0   8   2   7]
- [ 13  15 148  63  23  15  39]
- [  9   3   8 103  12   6  21]
- [  2  10   3   1  54   0   2]
- [ 12   2   1   5   0  38   5]
- [ 11   5   7   9   7   7  82]]
-Node Classification on random seed  1108 -> 0.622
-Confusion Matrix:
- [[ 80   8   4   6   1  10   4]
- [  5 131  11   3   5   2   6]
- [ 20  23 145  24  29  14  54]
- [ 12  12  12  93   6   8   9]
- [  2  14   2   1  51   1   5]
- [  5   1   4   1   0  46   1]
- [ 14   5   3  14   4  13  76]]
-Node Classification on random seed  1109 -> 0.595
-Confusion Matrix:
- [[ 66   5   9   3   4   3  17]
- [  2 131   2   4   3   2   2]
- [ 22  26 111  55  22  34  48]
- [ 10   4  15  98  12  11  13]
- [  1   7   3   2  63   0   1]
- [  4   0   6   3   0  39   8]
- [  3   6  13   5   8   7  87]]
-Node Classification on random seed  1110 -> 0.618
-Confusion Matrix:
- [[ 68   3  13   4   3  14  11]
- [  5 134   3   2   9   0   2]
- [ 21  27 132  52  27  25  38]
- [ 11   6   5 104   7   4  16]
- [  1   8   2   1  56   0   2]
- [  4   4   1   4   0  46   3]
- [  6   3   5   8  11  11  78]]
-Node Classification on random seed  1111 -> 0.607
-Confusion Matrix:
- [[ 60   2   9   4   4  10  10]
- [  5 139   5   5   5   1   0]
- [ 18  20 145  36  19  17  61]
- [ 15   7  20  87   4   7   8]
- [  2   7   1   0  70   0   4]
- [  6   0   0   1   1  40  15]
- [ 18   7  14  10   5  10  66]]
-Node Classification on random seed  1112 -> 0.627
-Confusion Matrix:
- [[ 68   8   2   5   7  19   2]
- [  2 126   1  11   7   3   1]
- [ 19  22 154  31  26  18  43]
- [ 15   2  12  92   9   7  16]
- [  0   7   4   3  65   1   1]
- [  3   0   4   4   3  44   3]
- [  2   5  10   5   7  23  78]]
-Node Classification on random seed  1113 -> 0.629
-Confusion Matrix:
- [[ 89   6   2   5   1  14  15]
- [  0 119   8   2   5   5   1]
- [ 23  18 137  39  20  23  39]
- [ 14   5   9 108   2   9  14]
- [  2   6   7   3  57   2   2]
- [  4   3   3   2   0  51   3]
- [ 11   6  12   7   5  14  68]]
-Node Classification on random seed  1114 -> 0.616
-Confusion Matrix:
- [[ 58   3   6   7   5  19  15]
- [  3 119   8   0  12   1   4]
- [ 17  21 177  21  22  21  34]
- [ 18   7  14  94  11  12   9]
- [  1   3   5   5  66   1   6]
- [  5   1   4   0   1  37   6]
- [ 12   7   9   3  10  15  65]]
-Node Classification on random seed  1115 -> 0.615
-Confusion Matrix:
- [[ 72   3   4  12   2   9  12]
- [  5 133   1   4   6   1   2]
- [ 27  24 148  26  28  19  42]
- [ 12   2  20  89   5   4  25]
- [  2   8   3   2  59   3   2]
- [  4   2   2   3   3  49   3]
- [ 13   2   5  14  10   9  65]]
-Node Classification on random seed  1116 -> 0.631
-Confusion Matrix:
- [[ 69   3   1   4   1  23   6]
- [  2 123  10   4  10   1   2]
- [ 10  18 150  37  19  38  44]
- [  4   5  17 104   5   5  13]
- [  2   9   5   1  57   1   3]
- [  5   1   1   2   2  44   5]
- [ 10   2   8   3   1  26  84]]
-Node Classification on random seed  1117 -> 0.605
-Confusion Matrix:
- [[ 57   5   2   3   3   7  25]
- [  8 122   9   3  13   2   5]
- [ 24  35 146  22  26  26  33]
- [ 13   3  13 106  10   5   9]
- [  0   7   5   0  66   3   2]
- [  9   2   4   3   2  35   5]
- [ 18   1   8   3   6  13  73]]
-Node Classification on random seed  1118 -> 0.63
-Confusion Matrix:
- [[ 75   3  10   4   3  17   4]
- [  3 123  12   1   3   4   4]
- [ 16  23 156  34  19  17  52]
- [  7   4  22 109   1   7  13]
- [  0   7   7   1  59   1   2]
- [  8   0   4   3   1  40   3]
- [  6   4  11   8   5  16  68]]
-Node Classification on random seed  1119 -> 0.57
-Confusion Matrix:
- [[ 57   4  11   7   4   6   7]
- [  2 142   8   6   7   5   3]
- [ 20  33 117  50  44  25  30]
- [ 12   5   6 112  11   7   8]
- [  0   8   2   2  53   0   6]
- [  5   1   9   4   3  39   3]
- [ 17   7  14  11   4  13  50]]
-Node Classification on random seed  1120 -> 0.62
-Confusion Matrix:
- [[ 66   5  11   3   1  14  15]
- [  3 140   2   1   5   6   2]
- [ 28  16 138  28  21  31  49]
- [  4   4  14 106   2  10  16]
- [  1  10   6   0  53   0   1]
- [  8   1   1   1   5  32   9]
- [  8   6  15   5   2  10  85]]
-Node Classification on random seed  1121 -> 0.613
-Confusion Matrix:
- [[ 72   4   4   6   1  15   4]
- [  3 121   7   9   8   1   2]
- [ 21  21 139  29  29  34  35]
- [ 12   7  18 101   6   2  18]
- [  2   8   2   0  62   2   2]
- [  6   1   3   1   2  50   3]
- [ 10   4  11   7   7  20  68]]
-Node Classification on random seed  1122 -> 0.643
-Confusion Matrix:
- [[ 69   1   2   5   6  11   4]
- [  5 132   4   1   4   3   6]
- [ 24  41 161  27  20  18  32]
- [ 11   6   9  98   7   6  11]
- [  0   6   1   2  57   1   2]
- [  9   3   0   0   2  51   1]
- [  9   3   9  12   6  27  75]]
-Node Classification on random seed  1123 -> 0.589
-Confusion Matrix:
- [[ 69   7   1   7   0  14  11]
- [ 10 116   5   0   1   2   6]
- [ 26  29 114  39  42  32  30]
- [ 11   3  15 120   4   8   7]
- [  1   3   4   5  59   0   5]
- [  6   1   2   2   0  49   4]
- [ 18   7  12  10   9  12  62]]
-Node Classification on random seed  1124 -> 0.604
-Confusion Matrix:
- [[ 64   5   6   7   4   6   7]
- [  9 117  11   3  11   3   1]
- [ 41  20 144  42  19  16  33]
- [ 30   2  13 100   8   3   6]
- [  1   4   3   0  61   1   2]
- [  7   3   2   8   3  38   5]
- [ 10   5  15   2   5  14  80]]
-Node Classification on random seed  1125 -> 0.638
-Confusion Matrix:
- [[ 71   7   3   4   2   5   5]
- [ 10 122   3   6   3   3   7]
- [ 30  20 146  47  17  19  37]
- [  3   1  11 107   3   7  15]
- [  0   8   1   8  59   2   2]
- [ 13   1   4   1   1  41   2]
- [ 19   5  17   1   4   5  92]]
-Node Classification on random seed  1126 -> 0.621
-Confusion Matrix:
- [[ 67   4   8   4   5  12   8]
- [  7 139   7   2  11   2   3]
- [ 34  19 132  32  31  26  38]
- [ 15   1   6 106   6   6  11]
- [  0   4   0   3  64   2   1]
- [  4   5   0   3   0  45  11]
- [ 11   1   6  10   9  11  68]]
-Node Classification on random seed  1127 -> 0.575
-Confusion Matrix:
- [[ 62   3  16  11   7   5  14]
- [  1 127  16   2   6   1   1]
- [ 42  29  93  49  32  18  52]
- [ 14   4   9 113   3   3  12]
- [  1   7   1   0  69   1   1]
- [  5   2   2   4   3  42   3]
- [ 14   0  10   4   4  13  69]]
-Node Classification on random seed  1128 -> 0.619
-Confusion Matrix:
- [[ 65   3   5   2   5  23  13]
- [  1 139   7   2   6   2   8]
- [ 17  16 161  37  15  22  54]
- [  9   8  11  87  10   7  17]
- [  1   5   6   4  52   1   1]
- [  1   2   2   0   0  45   7]
- [  5   5  13   8   3  17  70]]
-Node Classification on random seed  1129 -> 0.637
-Confusion Matrix:
- [[ 76   1   4  11   7   5  12]
- [  4 114   3   3   9   3   4]
- [ 24  13 155  53  18  15  24]
- [  8   2  12 110  10  10  21]
- [  0   6   5   0  69   1   4]
- [  4   3   1   0   2  40   6]
- [ 13   1   1  21   9  10  73]]
-Node Classification on random seed  1130 -> 0.649
-Confusion Matrix:
- [[ 72   0   1   3   9  20  11]
- [  4 128   4   3   5   3   6]
- [ 21  14 142  27  43  12  31]
- [ 13   5  15  94   8   4  15]
- [  0   5   5   0  68   1   1]
- [  6   1   1   2   1  55   8]
- [  8   3   5   3   7  17  90]]
-Node Classification on random seed  1131 -> 0.601
-Confusion Matrix:
- [[ 69   3  14   4   3   8  10]
- [ 11 134   2   2   4   2  13]
- [ 21  21 133  25  28  25  59]
- [ 10   7  16  93  11   7  14]
- [  6   4   5   0  62   1   3]
- [  8   1   1   0   0  43   4]
- [  6   4   8   8   5  15  67]]
-Node Classification on random seed  1132 -> 0.631
-Confusion Matrix:
- [[ 70   1   0   3   3  12   6]
- [  4 154   5   2   3   1   0]
- [ 36  21 153  22  17  17  37]
- [ 34   6  10  85  10  18  11]
- [  0  10   6   3  51   3   4]
- [  6   2   0   0   0  46   3]
- [ 19   2   3   6   8  15  72]]
-Node Classification on random seed  1133 -> 0.619
-Confusion Matrix:
- [[ 84   3   8   1   1   6  16]
- [  3 107   5   4   8   6   3]
- [ 23  35 141  37  22  16  30]
- [  3   2  21 100   5   2  17]
- [  1   8   2   4  62   0   1]
- [  6   1  10   8   2  38   8]
- [ 18   3  13   4   4  11  87]]
-Node Classification on random seed  1134 -> 0.587
-Confusion Matrix:
- [[ 68   5   7   5   8  14   9]
- [  3 120   8   4   3   2   4]
- [ 23  29 126  47  47  18  30]
- [ 11   2  17  82   6   4  26]
- [  1   5   3   0  66   0   0]
- [  6   2   7   2   1  33   6]
- [ 10   2  11   2  13  10  92]]
-Node Classification on random seed  1135 -> 0.622
-Confusion Matrix:
- [[ 77   6   6   1   3   6   9]
- [  3 133   7   2   8   2   3]
- [ 23  14 144  41  35  23  42]
- [ 15   8  10  92  10   4  17]
- [  1   6   2   3  51   0   5]
- [  6   1   1   4   0  35   9]
- [ 19   3   6   2   4   8  90]]
-Node Classification on random seed  1136 -> 0.624
-Confusion Matrix:
- [[ 69   1   2   6  10  14   8]
- [  8 138   4   0   7   1   1]
- [ 22  26 141  24  20  18  53]
- [ 23   6   9  96   7   3  17]
- [  1   7   5   0  55   0   5]
- [  4   1   3   5   3  35   5]
- [ 11   2   8  10   6  10  90]]
-Node Classification on random seed  1137 -> 0.604
-Confusion Matrix:
- [[ 81   1   6   5   3  11   9]
- [  7 119   5   2   6   2  10]
- [ 34  19 136  37  23  22  38]
- [ 15   0  16  97  10   3  13]
- [  2   9   6   1  54   1   7]
- [  7   0   3   1   1  45   7]
- [ 18   2  12   6   6  10  72]]
-Node Classification on random seed  1138 -> 0.604
-Confusion Matrix:
- [[ 58   1  10   2   5  16  10]
- [ 12 138   2   1  10   1   6]
- [ 17  23 108  33  23  27  57]
- [ 13   3   9 103   9  15   9]
- [  2   4   3   0  73   3   3]
- [  9   2   3   0   0  39   3]
- [  9   9   4   2   5  21  85]]
-Node Classification on random seed  1139 -> 0.628
-Confusion Matrix:
- [[ 70   4   3   4   7  16   3]
- [  6 119   5   5  11   1   7]
- [ 25  23 151  23  21  19  37]
- [ 24   4  20 100   4   6  12]
- [  0   5   7   2  49   0   5]
- [  6   2   0   0   1  51   9]
- [ 10   4   6   4   3  18  88]]
-Node Classification on random seed  1140 -> 0.603
-Confusion Matrix:
- [[ 55   6   2  12   3  15  17]
- [  5 124   3   5   8   2   1]
- [ 21  32 146  40  24  32  35]
- [  7   3  11 105   2   5  11]
- [  1   8   1   2  53   1   4]
- [  8   0   3   1   0  38   3]
- [ 16   6   4   8  10  19  82]]
-Node Classification on random seed  1141 -> 0.586
-Confusion Matrix:
- [[ 57   2   4   7   0  18  18]
- [  6 132   7   2   7   3   3]
- [ 18  19 143  38  17  34  57]
- [ 18   4  24  80   3   6  14]
- [  0   7   5   4  53   3   2]
- [  7   1   4   2   0  43   3]
- [  4   2  14   3   5  19  78]]
-Node Classification on random seed  1142 -> 0.543
-Confusion Matrix:
- [[ 80   2   1   1   8  11   6]
- [  1 119   6   7  11   7   1]
- [ 47  25  94  34  33  25  54]
- [ 19   8  17  76  16  12  12]
- [  1   7   0   1  61   4   0]
- [  8   6   0   4   0  43   8]
- [  8   6   3   5  12  20  70]]
-Node Classification on random seed  1143 -> 0.607
-Confusion Matrix:
- [[ 60   0   6  10   0  17  11]
- [  1 120   7  12   9   4  10]
- [ 16  15 129  49  32  16  64]
- [ 10   0   5 106   4   5   8]
- [  5   2   2   9  58   3   0]
- [  2   1   5   0   0  55   5]
- [ 12   8   3   7   5  13  79]]
-Node Classification on random seed  1144 -> 0.621
-Confusion Matrix:
- [[ 58   3   9   7   9  12  13]
- [  7 132   5   1   4   3   4]
- [ 24  19 146  45  21  20  38]
- [  5   2  15  97   7   5  16]
- [  2  10   3   1  60   3   3]
- [  7   0   4   0   1  49   4]
- [ 11   4   5   7   8  12  79]]
-Node Classification on random seed  1145 -> 0.617
-Confusion Matrix:
- [[ 79   1   3  13   3   7   9]
- [  2 113   8   3  16   4   9]
- [ 16  14 142  45  35  16  37]
- [  7   0  23 112   4   3  17]
- [  2   5   1   1  62   1   2]
- [  7   1   5   0   1  44   6]
- [  7   3   8  20   3  15  65]]
-Node Classification on random seed  1146 -> 0.621
-Confusion Matrix:
- [[ 70   4   1   1   3   6  15]
- [  4 127  12   4   3   8   9]
- [ 37  12 147  26  19  19  58]
- [ 16   5  12 102   3   5  15]
- [  0   3   1   1  57   3   6]
- [ 10   2   3   6   0  40   1]
- [ 11   1  10   4   5  15  78]]
-Node Classification on random seed  1147 -> 0.606
-Confusion Matrix:
- [[ 65   6   3   8   1   8  14]
- [  2 121   3   9  11   2   3]
- [ 34  25 141  28  21  21  37]
- [ 17   5  23 100   7   7  14]
- [  0   5   6   0  64   1   0]
- [ 13   0   2   3   0  38   7]
- [ 10   2   7   5  14  10  77]]
-Node Classification on random seed  1148 -> 0.614
-Confusion Matrix:
- [[ 58   6   5   3   2   9  14]
- [  3 139   4   2   9   1   5]
- [ 17  29 141  24  22  29  58]
- [  9   4  15 113   6   4  14]
- [  1   5   4   1  54   0   2]
- [  8   5   2   1   3  35  15]
- [ 11   8   6   5   5  10  74]]
-Node Classification on random seed  1149 -> 0.62
-Confusion Matrix:
- [[ 78   4   3  12   4  10   9]
- [  4 119   6   4   3   1   2]
- [ 25  27 146  42  28  18  37]
- [  8   6  11 104   2   5  15]
- [  1   4   0   5  69   1   3]
- [  8   2   2   4   0  43   5]
- [ 15   2   2  15   8  17  61]]
-Node Classification on random seed  1150 -> 0.58
-Confusion Matrix:
- [[ 56   4   7  14   1  13   3]
- [  2 121   6   7   4   1   3]
- [ 36  16 123  50  22  18  48]
- [  3   2  14 109   4  20  20]
- [  1   7   7   2  61   0   0]
- [  9   2   5   2   0  44   7]
- [ 17   2  10  20   5   6  66]]
-Node Classification on random seed  1151 -> 0.621
-Confusion Matrix:
- [[ 81   5   3  12   2  10  10]
- [  2 122  11   5   2   1   4]
- [ 24  16 131  51  25  20  39]
- [  7   3  21 101   1   4   8]
- [  2   8   4   5  64   3   5]
- [  6   0   0   5   1  35   6]
- [ 12   4  11   3   4  14  87]]
-Node Classification on random seed  1152 -> 0.606
-Confusion Matrix:
- [[ 84   1   3   3   7  14  11]
- [  2 118   5   0   5   6   5]
- [ 21  17 135  47  25  22  37]
- [ 11   5  26  99   7   4  20]
- [  1   4   2   3  56   2   2]
- [  4   2   2   7   1  39   6]
- [  5   2   6   6   9  26  75]]
-Node Classification on random seed  1153 -> 0.604
-Confusion Matrix:
- [[ 75   0   5   6   6  10   4]
- [  6 130   8   7   1   2   4]
- [ 13  21 131  51  26  21  39]
- [ 20   7  20 111   2   2  11]
- [  0   9   5   5  55   3   4]
- [  7   1   1   3   0  39   2]
- [ 14   4  12  10   6  18  63]]
-Node Classification on random seed  1154 -> 0.63
-Confusion Matrix:
- [[ 69   5   2   9   3   7   1]
- [  2 134   4   2   7   0   5]
- [ 30  31 142  27  23  15  41]
- [ 18   8   5  97   5   7  23]
- [  1   7   0   1  64   2   1]
- [  5   1   1   7   0  51   3]
- [ 25   4   8  10   6   8  73]]
-Node Classification on random seed  1155 -> 0.629
-Confusion Matrix:
- [[ 77   1   5   3   5  11   9]
- [ 12 121   3   1   9   0   7]
- [ 34  29 135  26  23  31  35]
- [ 14   3  10 116   3  12  10]
- [  2   4   0   0  57   0   3]
- [  0   0   3   3   2  43   8]
- [  9   2   5  12   8  14  80]]
-Node Classification on random seed  1156 -> 0.608
-Confusion Matrix:
- [[ 69   1   5   5   2  10  17]
- [  3 129   5   3   6   8   4]
- [ 21  41 122  38  26  26  37]
- [  8   2  11 102  11   2  11]
- [  2   5   4   1  65   1   1]
- [  6   2   0   6   0  46   4]
- [ 13   4   8   7   8  17  75]]
-Node Classification on random seed  1157 -> 0.64
-Confusion Matrix:
- [[ 78   2   7   5   3   8   6]
- [  2 141   3   2   2   0   9]
- [ 27  36 140  29  18  30  34]
- [  7   8  11 120   5   5   6]
- [  0  15   1   0  52   3   2]
- [  5   5   5   6   0  27   6]
- [  9   6  11   8   1  12  82]]
-Node Classification on random seed  1158 -> 0.643
-Confusion Matrix:
- [[ 69   5   3   5   8  10  11]
- [  6 146   2   1   2   1   5]
- [ 23  22 146  28  25  21  39]
- [ 13   3  11 100   5  11   8]
- [  0  11   3   2  49   1   2]
- [  5   6   3   2   0  52   8]
- [  4   3  10  10   7  12  81]]
-Node Classification on random seed  1159 -> 0.656
-Confusion Matrix:
- [[ 73   1  12   2   3  12   7]
- [  1 133   6   1   8   0   3]
- [ 27  23 160  36  13  16  46]
- [ 13   2  10 104   3   9  13]
- [  2   8   4   0  60   1   4]
- [  6   0   3   0   0  52   6]
- [ 10   4  10   5   6   8  74]]
-Node Classification on random seed  1160 -> 0.614
-Confusion Matrix:
- [[ 71   3   1   0   7  17  14]
- [  2 132   5   3   7   5   4]
- [ 23  14 132  36  26  17  44]
- [ 12  10   9  88   9   7  25]
- [  3   4   4   0  60   0   2]
- [  7   2   2   4   2  46   9]
- [  8   5   5   2   7  20  85]]
-Node Classification on random seed  1161 -> 0.65
-Confusion Matrix:
- [[ 83   8   6   1   2   8  11]
- [ 13 108   6   7   4   3   4]
- [ 33   8 153  27  21   6  46]
- [  9   0  14 117   3   4  15]
- [  5  11   3   1  60   0   4]
- [  5   4   3   4   1  47   4]
- [  8   5   9   8   6  10  82]]
-Node Classification on random seed  1162 -> 0.612
-Confusion Matrix:
- [[ 77   7   2   2   2  20   4]
- [  7 117   9   3   5   3   7]
- [ 25  14 150  61  15  21  35]
- [ 12   2   6  92   3  14  19]
- [  3   5   6   2  54   3   0]
- [  7   2   3   0   1  45   6]
- [ 19   2   9   7   6   9  77]]
-Node Classification on random seed  1163 -> 0.589
-Confusion Matrix:
- [[ 80   2   4   0   6   8   7]
- [  4 118   4   4  12   3   4]
- [ 22  51 125  25  25  34  45]
- [ 13   5   9  90   5  11  23]
- [  3   9  10   0  52   1   0]
- [  4   1   4   1   1  47   6]
- [  2   6   7   3  15  12  77]]
-Node Classification on random seed  1164 -> 0.619
-Confusion Matrix:
- [[ 81   3   3   3   6   5   2]
- [ 10 114   3   4  20   1   4]
- [ 26   7 147  36  29  20  44]
- [ 16   3  17 105   2   4  11]
- [  2   5   8   2  57   2   3]
- [  5   0   4   3   1  43   8]
- [ 15   4   6   8  12  14  72]]
-Node Classification on random seed  1165 -> 0.632
-Confusion Matrix:
- [[ 67   1   1   3   3   5  22]
- [  6 131   6   6  12   1   7]
- [ 17  15 146  38  23  10  47]
- [ 15   4  14  88   9  10  12]
- [  2   4   5   2  66   2   0]
- [  9   0   1   0   0  50   6]
- [ 15   2   4  12   9   8  84]]
-Node Classification on random seed  1166 -> 0.619
-Confusion Matrix:
- [[ 76   0   9   3   3   6  10]
- [  5 119   8   2   9   4   2]
- [ 20  14 130  46  31  14  50]
- [  4   4  23 105   4   6  14]
- [  0   8   3   0  63   1   5]
- [  6   0   5   0   0  42   8]
- [ 14   4   9   7   7  13  84]]
-Node Classification on random seed  1167 -> 0.654
-Confusion Matrix:
- [[ 67   8   4   5   2  15   2]
- [  2 144   6   1  11   0   5]
- [ 16  33 160  20  13  17  47]
- [ 11   3  14 102   3   4   8]
- [  3  10   5   0  60   0   3]
- [  4   2   2   1   2  46   2]
- [ 10   3  18  10   4  17  75]]
-Node Classification on random seed  1168 -> 0.603
-Confusion Matrix:
- [[ 78   3   3   2   3  15   7]
- [  3 131   9   7   6   3   1]
- [ 33  16 128  38  18  20  46]
- [ 18   6   7  79  13  10  19]
- [  1   7   1   1  55   4   2]
- [  5   0   0   1   0  50   7]
- [ 16   1   8  11   5  21  82]]
-Node Classification on random seed  1169 -> 0.61
-Confusion Matrix:
- [[ 70   3   6   3   2  12   4]
- [  1 164   6   7   3   1   3]
- [ 20  33 130  37  25  13  30]
- [  8   0  17  86  21  12  12]
- [  1   5   4   3  64   1   2]
- [  6   0   5   4   3  43   4]
- [ 17   1  12  22   9  12  53]]
-Node Classification on random seed  1170 -> 0.642
-Confusion Matrix:
- [[ 60   7   4   6  10   7  13]
- [  2 151   2   2   9   3   3]
- [ 24  15 142  55  18  23  32]
- [  4   5  10 127   1   3  11]
- [  0   7   4   2  57   0   2]
- [  6   1   2   2   0  40   8]
- [  5   5  17   9   5  14  65]]
-Node Classification on random seed  1171 -> 0.633
-Confusion Matrix:
- [[ 74   3   3   6   6   9   7]
- [  4 150   1   0   5   3   4]
- [ 19  40 151  27  33  17  34]
- [ 14   8  15  86   6   8   7]
- [  0  10   3   1  69   0   2]
- [  9   0   7   1   0  32   7]
- [ 10   3   4   4  11  16  71]]
-Node Classification on random seed  1172 -> 0.599
-Confusion Matrix:
- [[ 67   1   3   0   8  14  14]
- [ 11 120   8   2   3   1   1]
- [ 45  30 140  22  31  12  45]
- [ 15   1  14  91   2  10  20]
- [  5   3   2   1  56   0   2]
- [  7   3   2   0   3  49   2]
- [ 11   1   5   3  24  14  76]]
-Node Classification on random seed  1173 -> 0.65
-Confusion Matrix:
- [[ 71   1   2  10   3  17   6]
- [  5 126   5   9  10   4   6]
- [ 15  16 157  40  27  19  28]
- [ 10   2  21 126   6   3  10]
- [  0   9   4   2  55   2   6]
- [  9   0   2   0   0  45   4]
- [  5   7   3   8   7   7  70]]
-Node Classification on random seed  1174 -> 0.651
-Confusion Matrix:
- [[ 88   0   3   8   7   9   4]
- [  2 133   4   2   3   5   3]
- [ 25  22 133  26  20  16  61]
- [ 19   2  18  90   4   6   8]
- [  1  10   4   2  67   0   1]
- [  6   5   2   0   0  50   3]
- [  8   3   8   6   4   9  90]]
-Node Classification on random seed  1175 -> 0.627
-Confusion Matrix:
- [[ 70   4   6   5   4   8  11]
- [  7 134   7   1   2   1  13]
- [ 22  26 131  39  24  30  29]
- [  9   2  11 123   6   4   6]
- [  5   8   5   2  55   1   7]
- [  3   0   1   3   2  43   6]
- [ 12   4   9   7  10  11  71]]
-Node Classification on random seed  1176 -> 0.598
-Confusion Matrix:
- [[ 70   3   3   2   4  11  14]
- [  1 145   4   5   8   3   7]
- [ 23  38 131  27  50  19  42]
- [ 23   4   9  87   4  12  12]
- [  1   3   3   1  56   3   4]
- [  6   2   2   4   3  37   8]
- [  6   0   6   6  10   6  72]]
-Node Classification on random seed  1177 -> 0.62
-Confusion Matrix:
- [[ 74   2   1   8   5   8  16]
- [  6 112   2   5  17   1   6]
- [ 26  20 152  38  25  12  46]
- [  8   6  19 109   5   8  10]
- [  4   5   1   0  60   0   5]
- [  3   0   1   1   0  47   5]
- [ 15   3   8  13   7   9  66]]
-Node Classification on random seed  1178 -> 0.613
-Confusion Matrix:
- [[ 74   3   7   5   5   7   6]
- [  6 139   8   0  11   3   4]
- [ 26  34 115  49  24  30  42]
- [  6   2  16 105   9   6   6]
- [  1   8   1   1  61   0   3]
- [  3   0   4   3   0  49   3]
- [ 12   3   9   9   6   6  70]]
-Node Classification on random seed  1179 -> 0.63
-Confusion Matrix:
- [[ 77   2   3   4   8  10   8]
- [  3 128   7   8   4   1   9]
- [ 19  11 153  38  23  20  36]
- [ 23   1  15  97   4   6  14]
- [  1  10   3   3  60   0   3]
- [  9   0   3   0   1  44   5]
- [ 12   3  17  11   0  12  71]]
-Node Classification on random seed  1180 -> 0.615
-Confusion Matrix:
- [[ 53   4   3   4   2   6   7]
- [  7 136   9   3   4   0   8]
- [ 28   9 163  31  28   9  45]
- [ 23   5  23  89   4   7   7]
- [  2   8   3   5  66   0   4]
- [  7   1   6   3   1  33   5]
- [ 19   3  12   8  11  11  75]]
-Node Classification on random seed  1181 -> 0.613
-Confusion Matrix:
- [[ 87   4   5   8   8  11   3]
- [  6 113   2   1   7   2   4]
- [ 23  21 149  17  26  16  51]
- [  8   3  20  89   4   9  31]
- [  3   7   1   4  52   0   3]
- [  6   1   1   2   0  44   7]
- [ 10   3   7   7  17  18  79]]
-Node Classification on random seed  1182 -> 0.624
-Confusion Matrix:
- [[ 71   2   3   4   5  13  12]
- [  6 131  10   0   3   0   6]
- [ 22  36 146  19  24  20  44]
- [ 18  10   7  95  10   3  16]
- [  1  11   5   0  50   0   2]
- [  8   4   4   0   3  52   6]
- [ 12   1   6   4   9   7  79]]
-Node Classification on random seed  1183 -> 0.612
-Confusion Matrix:
- [[ 67   2   3   3   6  16   8]
- [  6 127   3   4  10   0   6]
- [ 22  12 125  37  18  27  47]
- [  4   1  15 112   4   5  26]
- [  3   5   2   4  59   1   4]
- [  5   0   4   7   0  46   1]
- [ 19   2   9   8  10  19  76]]
-Node Classification on random seed  1184 -> 0.628
-Confusion Matrix:
- [[ 74   4   1   3   3   6  16]
- [  2 133   3   4   1   6   2]
- [ 25  22 150  27  32  21  50]
- [  6   8  13 101   1   4  19]
- [  2  10   4   4  58   0   4]
- [  1   3   3   2   1  39  10]
- [  4   3  14   2  12  14  73]]
-Node Classification on random seed  1185 -> 0.627
-Confusion Matrix:
- [[ 76   3  11   4   2   4   9]
- [  7 122  11   4   9   3   1]
- [ 26  22 142  36  45  16  28]
- [  8   1  24 110   8   9   3]
- [  3   3   4   1  51   0   5]
- [  4   0   1   4   0  43   6]
- [ 15   4   6   9   6   8  83]]
-Node Classification on random seed  1186 -> 0.607
-Confusion Matrix:
- [[ 70   2   7   3   9  11   7]
- [  3 119  22   3  10   2   3]
- [ 41  24 149  26  33  14  40]
- [  6   1  20 102   4   2  13]
- [  0   6   2   5  56   3   2]
- [  9   3   4   1   0  45   1]
- [ 11   7   3   7   7  16  66]]
-Node Classification on random seed  1187 -> 0.587
-Confusion Matrix:
- [[ 82   0   6  11   3   6   6]
- [  5 124   3   1   5   4   8]
- [ 32  39 121  31  31  20  36]
- [ 24   8  14  85   4   7  20]
- [  0   7   6   0  67   0   0]
- [  9   2   4   0   1  42   6]
- [ 10   3  16   7   8  10  66]]
-Node Classification on random seed  1188 -> 0.618
-Confusion Matrix:
- [[ 77   3   4   9   5   8   9]
- [  3 110   8   6  12   1   3]
- [ 25  20 147  34  26   8  41]
- [ 24  12  14 100   3   2  11]
- [  0   7   6   0  57   0   4]
- [  5   2   4   1   0  48   7]
- [ 17   5   6   8  11   8  79]]
-Node Classification on random seed  1189 -> 0.652
-Confusion Matrix:
- [[ 89   5   1   0   3   6  15]
- [  8 134   8   2   6   2   7]
- [ 12  20 140  34  28  22  38]
- [  8   4  11 109   1  11  15]
- [  2   8   4   0  53   2   0]
- [  2   2   2   0   0  37  13]
- [  9   1  11   6   8  11  90]]
-Node Classification on random seed  1190 -> 0.62
-Confusion Matrix:
- [[ 66   5   3   5   8  16  10]
- [  4 115   7   2  13   5   3]
- [ 38  24 141  25  20  17  39]
- [ 14   5  19 106   5   7  10]
- [  0   0   4   1  69   0   2]
- [  9   1   3   1   0  51   2]
- [  8   3   4   5  18  15  72]]
-Node Classification on random seed  1191 -> 0.626
-Confusion Matrix:
- [[ 83   2   1   5   2   6  10]
- [  9 110  10   0  15   1   8]
- [ 20   5 129  64  37  18  31]
- [ 14   3  10 112   2   2  14]
- [  0   4   0   2  68   1   1]
- [  1   1   1   4   1  46   4]
- [ 12   3  10  22   6  12  78]]
-Node Classification on random seed  1192 -> 0.634
-Confusion Matrix:
- [[ 72   3   1   8   7  10   5]
- [  6 142   4   5   4   2   7]
- [ 18  22 138  34  38  20  29]
- [ 12   8  12 118   3   5   5]
- [  0   4   2   2  63   4   3]
- [  7   4   0   1   2  51   2]
- [ 17   6  11  11   9  13  50]]
-Node Classification on random seed  1193 -> 0.609
-Confusion Matrix:
- [[ 72   4   6   4   1  10  10]
- [  2 125   6   0  13   1   9]
- [ 21  37 128  59  33  22  24]
- [  4   9   9 100   8   9   7]
- [  0   4   4   0  65   0   3]
- [  5   1   2   4   1  40   3]
- [ 11   3  17   3   4  18  79]]
-Node Classification on random seed  1194 -> 0.604
-Confusion Matrix:
- [[ 62   3   7   2   7  17  12]
- [  9 105   5   0   9   2   6]
- [ 28  14 147  26  29  39  28]
- [  1   9  20  87   3  15  11]
- [  4   4   8   1  69   0   1]
- [  7   0   0   2   3  61   3]
- [ 12   8  10   4  12  15  73]]
-Node Classification on random seed  1195 -> 0.6
-Confusion Matrix:
- [[ 68   1   9   8   2  10   7]
- [  6 120   5  12   4  12   5]
- [ 46  32 137  24  12  39  29]
- [ 10   3  15  91   4   6  11]
- [  5   7   6   1  62   2   1]
- [  4   0   2   4   0  36   2]
- [ 12   5  10  13   6   8  86]]
-Node Classification on random seed  1196 -> 0.607
-Confusion Matrix:
- [[ 69   2   0   3   4  10  18]
- [  9 137   1   2   3   1   2]
- [ 29  16 127  29  44  13  48]
- [ 14   6  16 105   6   9  15]
- [  1   4  11   1  53   1   2]
- [  5   0   3   3   0  51   1]
- [  7   4   7   8  12  23  65]]
-Node Classification on random seed  1197 -> 0.602
-Confusion Matrix:
- [[ 69   2   6   2   3   9  12]
- [  6 123   9   1  15   3   3]
- [ 16  20 148  45  21  20  35]
- [ 14   3  25 102  10   5  14]
- [  0   6   0   0  57   1   1]
- [  2   3   2   3   7  42   6]
- [ 11   3  11   9  13  21  61]]
-Node Classification on random seed  1198 -> 0.59
-Confusion Matrix:
- [[ 57   4   1   8   2  17  15]
- [  6 135   4   3   3   2   3]
- [ 15  39 125  34  26  19  46]
- [  8   5  17  92   8  11  14]
- [  0  13   4   2  59   4   2]
- [ 14   3   0   2   2  38   1]
- [ 10   7  13   6   2  15  84]]
-Node Classification on random seed  1199 -> 0.616
-Confusion Matrix:
- [[ 64   2   6   2   0   6  16]
- [  8 134   6   3   4   0   5]
- [ 33  20 170  54  17  16  36]
- [ 22   1  12  84   5   8  23]
- [  2   3   3   4  50   2   4]
- [  4   0   1   5   0  37   3]
- [  5   4  12   2   6  19  77]]
-Node Classification on random seed  1200 -> 0.621
-Confusion Matrix:
- [[ 53   2   7   6  15  17   9]
- [  2 146   6   1   5   6   5]
- [ 24  30 155  19  28  19  31]
- [  6   8  19  87   7   3  13]
- [  1   3   5   0  60   0   4]
- [  2   1   4   2   1  46   5]
- [ 10   2   9  12  10  20  74]]
-Node Classification on random seed  1201 -> 0.63
-Confusion Matrix:
- [[ 72   2   1   6   2  14  11]
- [  4 129   6   0   9   0   1]
- [ 14  31 130  16  52  22  46]
- [ 10   5  10 102  11   3  15]
- [  0  10   3   4  62   1   1]
- [  8   5   1   0   0  50   4]
- [ 10   1   5   4  12  10  85]]
-Node Classification on random seed  1202 -> 0.614
-Confusion Matrix:
- [[ 61   3   2  13   4  20   0]
- [  5 144   7   5   4   3   7]
- [ 20  25 122  44  28  22  44]
- [ 13   1  17  92   4  10   7]
- [  2   6   2   0  65   2   3]
- [  3   0   2   6   1  40   7]
- [  6  10   7   4   4  13  90]]
-Node Classification on random seed  1203 -> 0.637
-Confusion Matrix:
- [[ 84   3   4   4   2  10   6]
- [ 11 127  11   2   7   7   1]
- [ 11  16 142  34  31  18  34]
- [  9   5  12  97   9   6  21]
- [  3   4   5   0  67   3   3]
- [  4   0   3   2   1  51   3]
- [ 16   4   8  10   5  15  69]]
-Node Classification on random seed  1204 -> 0.598
-Confusion Matrix:
- [[ 57   4   6   9   5   3   6]
- [  4 117  14   7   3   5   5]
- [ 33  17 154  40  22  20  45]
- [  6   4  14 101  11   7  14]
- [  2  12   3   1  54   3   3]
- [  6   5   1   3   1  50   5]
- [ 18   5   4  11   7   8  65]]
-Node Classification on random seed  1205 -> 0.638
-Confusion Matrix:
- [[ 71   6   0   3   6   3   8]
- [  2 134   3   2  11   1   3]
- [ 19  17 140  27  24  18  51]
- [ 11   3  15  93   3   6  22]
- [  3   4   2   0  67   1   2]
- [  3   0   6   6   1  52   2]
- [ 14   6  12   3  23  10  81]]
-Node Classification on random seed  1206 -> 0.604
-Confusion Matrix:
- [[ 70   2   2   6   4  17   4]
- [  4 136   6   1   3   3   6]
- [ 28  15 148  30  25  24  42]
- [ 25   3  19  82   3   7   5]
- [  0   9   5   0  65   0   3]
- [  4   0   4   1   0  45   9]
- [ 18   2  10  19   9  19  58]]
-Node Classification on random seed  1207 -> 0.634
-Confusion Matrix:
- [[ 54   3  15   8   8   8   9]
- [  0 115   5   1  11   1  14]
- [ 18  12 153  43  26  18  32]
- [  6   1  19 119   5  10   9]
- [  3   1   4   0  64   1   3]
- [  4   3   4   0   2  47   7]
- [ 17   1  13   4   9   8  82]]
-Node Classification on random seed  1208 -> 0.66
-Confusion Matrix:
- [[ 67   3   2  12   1   2  11]
- [  3 137   8   0  14   1   2]
- [ 26  19 164  21  32  12  43]
- [ 21   3  13 104   4   5  14]
- [  1   7   0   1  57   1   3]
- [  2   0   2   1   0  40   4]
- [ 18   1   9   4  10   4  91]]
-Node Classification on random seed  1209 -> 0.634
-Confusion Matrix:
- [[ 60   2   1   3   6  14  13]
- [  5 143   3   5   3   3   6]
- [ 30  21 155  33   7  43  25]
- [ 12   4  11 104   3   3  11]
- [  2   6   5   6  62   0   1]
- [  2   0   1   1   1  37   8]
- [ 15   2  11  15  10  13  73]]
-Node Classification on random seed  1210 -> 0.623
-Confusion Matrix:
- [[ 73   1   1   3   3  19   4]
- [  3 107   7   0  16   7   3]
- [ 24  19 163  24  21  49  44]
- [ 11   1  15 104   4  14   9]
- [  1   4  10   0  53   2   2]
- [  4   1   0   2   1  46   4]
- [  4   4   4   5   4  23  77]]
-Node Classification on random seed  1211 -> 0.626
-Confusion Matrix:
- [[ 66   4   1   5   5   8  11]
- [  3 107   3   5   7   4   7]
- [ 21  35 150  36  35  10  42]
- [  5   8  14  96   5   3  23]
- [  0   8   4   0  66   0   1]
- [ 10   3   3   2   1  46   4]
- [  8   3   6   6   6   9  95]]
-Node Classification on random seed  1212 -> 0.607
-Confusion Matrix:
- [[ 75   0   6   2   4  18   3]
- [  4 117   7   2   9   1   5]
- [ 25  16 118  49  28  13  53]
- [  7   0  20 119   5   7  14]
- [  1   3   0   4  65   1   3]
- [  3   1   3   4   2  51   2]
- [ 15   5  14   2   8  24  62]]
-Node Classification on random seed  1213 -> 0.604
-Confusion Matrix:
- [[ 53   1   6  14   7  10   9]
- [ 10 120   6   4   6   2   7]
- [ 32  18 142  47  32  23  29]
- [ 11   1  14 104   7   3   9]
- [  4   2   3   2  58   1   1]
- [ 15   0   3   1   0  47   2]
- [ 16   1  15   2   8  12  80]]
-Node Classification on random seed  1214 -> 0.591
-Confusion Matrix:
- [[ 65   1   3  13   1   9   9]
- [  5 117   2   2   8   0   8]
- [ 13  18 119  59  34  19  62]
- [  4   5  24 112   3  10  13]
- [  1   7   3   0  63   1   2]
- [  5   3   2   1   1  43   6]
- [  7   4   7  12   4  18  72]]
-Node Classification on random seed  1215 -> 0.643
-Confusion Matrix:
- [[ 74   0   3   6   3  16  15]
- [  9 131   7   2   9   1   5]
- [ 24   9 156  28  24  12  44]
- [ 28   3  15  92   3   6  14]
- [  1   6   5   1  64   2   2]
- [  2   1   2   1   0  47   4]
- [ 12   6  10   2   3  11  79]]
-Node Classification on random seed  1216 -> 0.642
-Confusion Matrix:
- [[ 80   0   5   9   6   7  10]
- [  0 128   4   4  10   4   0]
- [ 14  40 141  47  19   8  41]
- [  9   2  12 104   3   1  14]
- [  1   4   1   0  71   0   4]
- [  2   2   2   4   5  36   5]
- [  8   6  16  10  11   8  82]]
-Node Classification on random seed  1217 -> 0.628
-Confusion Matrix:
- [[ 62   0   3  10   1  21  12]
- [  4 133   5   1   3   4   4]
- [ 12  21 168  30  19  11  47]
- [ 16   1  27  82   7   9   9]
- [  1   9   5   4  54   2   4]
- [  5   1   0   4   0  49   5]
- [  9   4   8  19   3  12  80]]
-Node Classification on random seed  1218 -> 0.639
-Confusion Matrix:
- [[ 76   4   2   1   1  20  11]
- [  5 138  13   0   7   4   2]
- [ 28  26 182  27  12  18  15]
- [ 10   6  11  92  14   1  18]
- [  3   8   2   2  44   2   4]
- [ 16   0   6   0   3  34   9]
- [ 14   2  13   7   5   9  73]]
-Node Classification on random seed  1219 -> 0.626
-Confusion Matrix:
- [[ 81   8   2   3   7   3   9]
- [  7 125   4   5   5   4   6]
- [ 32  22 166  34  23  20  30]
- [  7   5   6  90   7   7  15]
- [  4  10   7   3  46   3   7]
- [  6   0   1   1   0  53   5]
- [ 11   4  12   5   4  20  65]]
-Node Classification on random seed  1220 -> 0.624
-Confusion Matrix:
- [[ 68   5   5   0   5  15   2]
- [  8 135   3   0   8   1   4]
- [ 15  27 117  20  24  40  53]
- [  6   8  15  94  13  13   9]
- [  0   7   4   0  67   1   2]
- [  2   0   2   2   0  63   6]
- [  7   1   7   6   4  26  80]]
-Node Classification on random seed  1221 -> 0.614
-Confusion Matrix:
- [[ 63   3   0   3   5  20   6]
- [  3 119  13   1  14   3   6]
- [ 33  11 148  25  35  29  36]
- [  7   1  23  99   9   3  12]
- [  1   7   0   1  66   1   2]
- [  9   1   4   0   2  40   2]
- [  7   3  13   3   9  20  79]]
-Node Classification on random seed  1222 -> 0.598
-Confusion Matrix:
- [[ 81   7   0   3   5   6  10]
- [  5 105   8   7  13   0   2]
- [ 20  26 136  47  46  25  28]
- [ 12  14  15  84   2   5  11]
- [  3   2   0   5  62   3   2]
- [  4   4   0   0   1  36  11]
- [ 13   5  11   4   6  11  94]]
-Node Classification on random seed  1223 -> 0.614
-Confusion Matrix:
- [[ 78   6   1   6   6   9   8]
- [  4 128   1   4   5   2   8]
- [ 39  22 120  44  22  22  44]
- [  8   0   8 114   8   4  12]
- [  2   5   1   5  62   1   3]
- [  5   2   1   0   0  38   7]
- [ 16   3   4   7   5  26  74]]
-Node Classification on random seed  1224 -> 0.617
-Confusion Matrix:
- [[ 56   3   3   2   5  28  12]
- [  2 140   4   1  12   5   8]
- [ 22  24 130  42  22  17  48]
- [  5   3  13 115   4   6  11]
- [  3   1   5   0  57   2   3]
- [  3   1   0   3   1  57   1]
- [  4   0   9  14   6  25  62]]
-Node Classification on random seed  1225 -> 0.606
-Confusion Matrix:
- [[ 72   0   7   4   4  15   7]
- [ 11 118   6   2   7   6  12]
- [ 18  22 126  35  32  34  33]
- [  3   4  15 115   4   5  19]
- [  0   8   4   1  50   1   2]
- [  5   1   6   2   0  53   4]
- [  9   3  11   3   4  25  72]]
-Node Classification on random seed  1226 -> 0.616
-Confusion Matrix:
- [[ 79   4   3   3   1  17   7]
- [  7 139   2   4  14   0   4]
- [ 17  23 116  45  17  19  49]
- [ 11   5  13 117  14   4   9]
- [  0  13   0   2  54   1   3]
- [  6   2   4   0   0  40   7]
- [ 18   2  11   6   8   9  71]]
-Node Classification on random seed  1227 -> 0.581
-Confusion Matrix:
- [[ 73   4  10   6   5   4   8]
- [  9 112  13   2   2   2   3]
- [ 33  34 132  35  30  20  28]
- [ 27   5  12 103   8   4  12]
- [  3   6   1   3  48   0   3]
- [  2   1   2   4   3  53   2]
- [ 14   4  19   7   8  21  60]]
-Node Classification on random seed  1228 -> 0.604
-Confusion Matrix:
- [[ 70   2   1   5   9  10  12]
- [  6 140   7   3  11   2   4]
- [ 15  29 123  48  18  17  50]
- [ 15   2  11 111   5   2  14]
- [  1   8   4   1  60   3   2]
- [  4   0   0   0   1  43   8]
- [ 13   4   3   9   9  28  57]]
-Node Classification on random seed  1229 -> 0.632
-Confusion Matrix:
- [[ 76   3   7   4   7   6   2]
- [  8 120   4   0   7   0   9]
- [ 24  17 155  30  34  21  46]
- [ 11   2  18 117   6   3   9]
- [  1   5   7   4  56   0   4]
- [  8   1   7   6   0  36   6]
- [  9   5  13   5   6   3  72]]
-Node Classification on random seed  1230 -> 0.58
-Confusion Matrix:
- [[ 61   2   5  15   5   9   6]
- [  8 117   4   4   4   0   5]
- [ 37  31 120  37  21  18  53]
- [ 17  10  21  92   7   0   8]
- [  4  10   1   0  69   0   2]
- [  3   2   3   3   1  45   5]
- [ 22   4   2  15   6  10  76]]
-Node Classification on random seed  1231 -> 0.577
-Confusion Matrix:
- [[ 53   3  13   7   3  18  11]
- [  9 129   6  10   4   7   2]
- [ 22  21 129  39  26  35  39]
- [  7   4  18  90   2  11  16]
- [  3  10   2   4  65   0   1]
- [  4   2   1   3   4  40   2]
- [  7   3   4  11   7  22  71]]
-Node Classification on random seed  1232 -> 0.605
-Confusion Matrix:
- [[ 73   1   2   8   3  13   6]
- [  3 122  12   2   7   7   8]
- [ 40  26 113  36  29  27  32]
- [ 13   2  10 115   3   3  12]
- [  1  10   2   2  63   0   3]
- [ 11   4   1   2   1  41   1]
- [ 15   5   8   2   5  17  78]]
-Node Classification on random seed  1233 -> 0.631
-Confusion Matrix:
- [[ 83   5   0  11   7  10  11]
- [  3 133   4   2   6   2   0]
- [ 19  24 115  23  28  29  42]
- [  7   8  24 115   4   2   7]
- [  0   6   2   1  73   2   2]
- [  2   1   4   0   2  45   6]
- [ 19   9   4  12   5  14  67]]
-Node Classification on random seed  1234 -> 0.644
-Confusion Matrix:
- [[ 71   4   2   3   3  15  16]
- [  6 146   4   2   3   2   2]
- [ 16  10 144  46  16  25  40]
- [ 15   3  19  88   7   6  13]
- [  2  12   3   2  56   1   0]
- [  4   1   1   1   0  54   2]
- [ 12   2   5   8   9  13  85]]
-Node Classification on random seed  1235 -> 0.614
-Confusion Matrix:
- [[ 71   1   4   5   5  14   1]
- [  4 141   3   2  12   7   3]
- [ 28  23 133  35  24  35  31]
- [ 10   3  17  84   8   5  14]
- [  1   7   2   1  60   1   4]
- [  6   0   3   4   1  55   2]
- [  7   2  14  10   3  24  70]]
-Node Classification on random seed  1236 -> 0.603
-Confusion Matrix:
- [[ 64   2   4   2   3  15   7]
- [  3 145   5   1  10   3   2]
- [ 23  22 147  38  25  13  32]
- [  7   3  23  93   4  13  21]
- [  1   9   4   3  55   1   2]
- [  5   0   7   0   3  43   5]
- [ 13   4  23   6  21   9  56]]
-Node Classification on random seed  1237 -> 0.591
-Confusion Matrix:
- [[ 61   3   3  15   1  14   9]
- [  3 138   6   4   5   2   6]
- [ 34  26 127  53  22  31  31]
- [ 14   5   8  97   4  11  12]
- [  3   7   1   2  54   2   7]
- [  5   2   2   3   0  42   3]
- [ 10   3   8   8   8  13  72]]
-Node Classification on random seed  1238 -> 0.659
-Confusion Matrix:
- [[ 80   0   1   1   4  14   4]
- [  2 156   5   4   4   2   0]
- [ 26  19 131  30  44  24  30]
- [ 12   2  13 110  11  10   2]
- [  0   7   5   7  54   0   4]
- [  4   0   2   0   0  47   3]
- [ 13   4   5   4   3  16  81]]
-Node Classification on random seed  1239 -> 0.634
-Confusion Matrix:
- [[ 69   2   8   5   3   6  21]
- [ 12 124   4   2  11   0   3]
- [ 25  26 139  30  21  19  35]
- [ 10   1  17 106   0   3  16]
- [  1   3   3   3  64   1   2]
- [ 11   1   0   2   0  46   5]
- [ 10   4  12   4   9  15  86]]
-Node Classification on random seed  1240 -> 0.61
-Confusion Matrix:
- [[ 58   1   1   3   6  21   6]
- [  3 138   7   3   2   2   5]
- [ 30  26 135  40  22  19  36]
- [ 18   7  10  84   9   8  15]
- [  2  10   2   2  63   0   1]
- [  9   1   2   3   0  53   3]
- [  9   6   8   5   7  20  79]]
-Node Classification on random seed  1241 -> 0.634
-Confusion Matrix:
- [[ 75   4   6   4   4  10  15]
- [  3 124   3   5  10   2   1]
- [ 32  15 139  24  22  22  39]
- [ 13   6  16 102   5   3  10]
- [  2   9   5   0  66   0   1]
- [  9   3   4   0   0  49   7]
- [ 13   5  11   5   3  15  79]]
-Node Classification on random seed  1242 -> 0.555
-Confusion Matrix:
- [[ 63   4   4   5   4  29   7]
- [  3 127   5   5   3   5   3]
- [ 24  22 111  36  27  35  48]
- [ 17   6  19  83   2   5  27]
- [  0   6   2   7  63   1   3]
- [  5   1   0   0   0  49   5]
- [ 18   5  11  14   7  15  59]]
-Node Classification on random seed  1243 -> 0.637
-Confusion Matrix:
- [[ 73   9   2   4   5   9   5]
- [  2 114   8   8   5   5   8]
- [ 13  17 164  28  11  44  28]
- [  8   0  22 107   3  16   9]
- [  0   9   5   2  58   7   2]
- [  6   2   0   4   1  45   5]
- [  7   4   8   3  11  18  76]]
-Node Classification on random seed  1244 -> 0.641
-Confusion Matrix:
- [[ 53   0   4   8   7  12  11]
- [  6 138   6   3   3   3   6]
- [  9  28 133  32  48  33  28]
- [ 11   2  17 109   6  13  10]
- [  1   4   2   1  67   1   0]
- [  0   1   0   0   1  47   5]
- [  2   0   7   3   7  18  94]]
-Node Classification on random seed  1245 -> 0.59
-Confusion Matrix:
- [[ 75   2   3   6   4   6  10]
- [  3 133   6   2  13   0   6]
- [ 24  14 119  57  36  28  38]
- [ 17   3  13  88   5   7  17]
- [  1   6   2   3  56   0   3]
- [ 14   2   3   0   1  36   5]
- [ 11   2   6  14   6  11  83]]
-Node Classification on random seed  1246 -> 0.606
-Confusion Matrix:
- [[ 76   8   2   9   3   4  13]
- [  5 132   5   1  12   5   1]
- [ 12  22 127  45  24  36  29]
- [ 14   5  13  99  10   6  13]
- [  4   5   3   2  62   1   1]
- [ 10   1   4   0   2  37   3]
- [ 13   1  16  13  10   8  73]]
-Node Classification on random seed  1247 -> 0.558
-Confusion Matrix:
- [[ 63   2   4   6   2   7  18]
- [  2 127   4   3  17   3   5]
- [ 25  25 125  50  21  21  35]
- [ 30   6   8  82  16  14  18]
- [  1   9   6   0  58   0   2]
- [  2   0   5   4   0  49   5]
- [ 21   2  13   7   4  19  54]]
-Node Classification on random seed  1248 -> 0.615
-Confusion Matrix:
- [[ 48   7   9  11   3  11   6]
- [  2 135   5   1   4   4   6]
- [ 22  28 140  44  26  17  35]
- [ 11   1   6 123   5   9   8]
- [  1   8   4   6  50   2   7]
- [  8   0   1   1   0  49   5]
- [ 12   2  14  11   6  16  70]]
-Node Classification on random seed  1249 -> 0.647
-Confusion Matrix:
- [[ 70   5   3   5   2  18   3]
- [  4 129   2   1   4   3  10]
- [ 12  46 149  29  28  19  34]
- [  8   6  17 116   0  11   8]
- [  0   7   4   2  63   1   2]
- [  2   0   0   2   0  49   5]
- [  5   2  15   7   5  16  71]]
-Node Classification on random seed  1250 -> 0.617
-Confusion Matrix:
- [[ 72   0   9  12   3  10  10]
- [ 11 121   4   3   3   6   6]
- [ 16  21 132  22  34  43  32]
- [ 16   2  22  91   3  10   3]
- [  0   4   3   2  62   0  10]
- [  5   1   0   7   0  53   2]
- [ 11   3   8   4   4  18  86]]
-Node Classification on random seed  1251 -> 0.602
-Confusion Matrix:
- [[ 55   1   5   4   5  17  17]
- [  5 110  12   8   6   2   9]
- [ 30  14 153  34  26  20  43]
- [  8   5   6 105  19   9  12]
- [  2   2  10   0  57   4   6]
- [  1   0   7   0   0  54   5]
- [ 11   6  11   4   3   9  68]]
-Node Classification on random seed  1252 -> 0.588
-Confusion Matrix:
- [[ 69   1  11   2   3   5  11]
- [ 12 121   4   3   4   3   1]
- [ 22  31 123  49  29  35  37]
- [ 10   3  21  79  12   9  15]
- [  1   5   1   0  63   1   1]
- [  9   0   2   1   4  41   9]
- [ 13   1   6   5   7  13  92]]
-Node Classification on random seed  1253 -> 0.605
-Confusion Matrix:
- [[ 78   1   2   7   6  13   9]
- [  4 117   6   3   4   4   2]
- [ 32  19 148  30  26  18  38]
- [ 15   5  18 106   2   8  12]
- [  0   7   4   2  55   3   4]
- [  9   0   1   3   0  38  12]
- [ 24   1  12   4   8  17  63]]
-Node Classification on random seed  1254 -> 0.63
-Confusion Matrix:
- [[ 82   4  15   8   7   4  12]
- [  8 128   3   3   6   3   1]
- [ 23  15 155  40  23  22  28]
- [ 30   3  16  89  11   5   6]
- [  3   5   1   0  52   1   5]
- [  3   1   2   2   2  46   0]
- [ 10   4   6  12   8   9  78]]
-Node Classification on random seed  1255 -> 0.612
-Confusion Matrix:
- [[ 71   5   3   4   4  11  12]
- [  5 116  13   1  10   1   5]
- [ 28  13 154  38  29  27  32]
- [  7   6  18  90  16  10  15]
- [  1   4   2   1  61   2   3]
- [  5   0   0   0   0  45   4]
- [ 20   3   8   4   8  10  75]]
-Node Classification on random seed  1256 -> 0.596
-Confusion Matrix:
- [[ 77   1   7  10   4  12  11]
- [  2 114   4   5  16   5   5]
- [ 17  18 131  46  19  20  53]
- [  6   2  22 103   4  11  13]
- [  2   3   3   0  52   1   4]
- [  8   0   3   3   4  28   8]
- [  6   1   6  12   9  18  91]]
-Node Classification on random seed  1257 -> 0.633
-Confusion Matrix:
- [[ 70   1   1   3   2   7  11]
- [  3 114   4   1  17   5  15]
- [ 19  14 114  46  56  15  39]
- [  4   3   9 140  11   6  12]
- [  0   2   1   4  71   0   1]
- [  1   1   3   1   2  50   1]
- [  8   0   4   6  10  18  74]]
-Node Classification on random seed  1258 -> 0.635
-Confusion Matrix:
- [[ 82   6   6   4   6   7  12]
- [  0 117  12   5   1   7   3]
- [ 21  31 157  35  20  16  32]
- [  9   6   8 100   7   4  17]
- [  1   6   4   1  51   2   5]
- [ 11   2   0   0   0  49   5]
- [ 11   3  10   5  14  10  79]]
-Node Classification on random seed  1259 -> 0.611
-Confusion Matrix:
- [[ 71   5   2   4   6  15  21]
- [  1 125   5   4   3   3   7]
- [ 34  18 132  49  20  37  27]
- [ 21   0   7  96   4   9  13]
- [  1   6   3   1  62   1   4]
- [  4   1   2   0   2  50   1]
- [  8   3   4   8   6  19  75]]
-Node Classification on random seed  1260 -> 0.638
-Confusion Matrix:
- [[ 79   2   3   5   4   8  10]
- [  0 139   5   3   7   4   2]
- [ 24  41 124  28  22  22  36]
- [ 13   7  17 118   5   4   5]
- [  0   9   6   4  49   1   6]
- [  3   0   2   2   0  41   7]
- [ 12   5   6   5   4  13  88]]
-Node Classification on random seed  1261 -> 0.613
-Confusion Matrix:
- [[ 75   3   4   4   3  15   5]
- [  5 125   2   4   9   9   4]
- [ 28  18 163  23  20  36  36]
- [  7   4   6  97   6  16   6]
- [  0   3   4   1  54   3   3]
- [  2   3   7   1   1  45   4]
- [ 14   6  21   3   8  30  54]]
-Node Classification on random seed  1262 -> 0.639
-Confusion Matrix:
- [[ 63   4   5   6   4  15   4]
- [  3 129   2   2   1   5   7]
- [ 25  20 144  34  18  32  39]
- [ 14   4  10 116   2   6  19]
- [  3   6   1   3  62   0   4]
- [  6   0   3   2   1  34   8]
- [  3   6   9   5   8  12  91]]
-Node Classification on random seed  1263 -> 0.6
-Confusion Matrix:
- [[ 73   3   1   4   2   8   8]
- [  2 129   6   2   6   4   5]
- [ 25  22 139  38  22  18  52]
- [ 13   7  31  85   5   5  10]
- [  4  10   4   1  58   5   1]
- [  4   2   5   1   3  43   3]
- [ 16   7  12   5   4  14  73]]
-Node Classification on random seed  1264 -> 0.625
-Confusion Matrix:
- [[ 66   1   3   4   6  18  17]
- [  6 100   6   4  12   6   4]
- [ 17  11 162  30  22  26  51]
- [ 11  10  14 112  12   8  11]
- [  3   3   1   1  56   2   0]
- [  7   1   1   0   2  41   4]
- [  8   4   4   3   8  13  88]]
-Node Classification on random seed  1265 -> 0.615
-Confusion Matrix:
- [[ 70   0   3  10   2  14   8]
- [ 12 117   1   4  14   2   9]
- [ 21  23 144  39  11  26  46]
- [  4   2  14 122   6   7  15]
- [  3   5   1   0  63   1   3]
- [  5   5   2   0   4  41   4]
- [ 13   6   5   3  11  21  58]]
-Node Classification on random seed  1266 -> 0.616
-Confusion Matrix:
- [[ 92   2   2   2   2   9   8]
- [  6 128   7   0  10   0   3]
- [ 26  25 117  46  36  24  30]
- [ 15   6  13  87   8   6  16]
- [  2   3   3   0  68   2   5]
- [  5   3   3   1   0  48   6]
- [  6   5   8   7   4  19  76]]
-Node Classification on random seed  1267 -> 0.595
-Confusion Matrix:
- [[ 78   4   1   4   6  21  10]
- [  1 129  11   3   5   5   4]
- [ 20  19 101  64  38  20  28]
- [  9   5   6 106   7   6  10]
- [  3   6   4   2  61   3   3]
- [ 10   1   5   3   3  40   3]
- [ 19   1   3  12   4  13  80]]
-Node Classification on random seed  1268 -> 0.567
-Confusion Matrix:
- [[ 61   0   3   4   5  19  11]
- [  2 111   5   6   5  12   1]
- [ 27  16 136  38  45  28  33]
- [ 12   6  18  85  14   8  10]
- [  2  15   6   1  52   0   2]
- [  6   2   2   6   0  47   8]
- [  5   3  14   7  10  16  75]]
-Node Classification on random seed  1269 -> 0.633
-Confusion Matrix:
- [[ 70   1   6   5   4  18   7]
- [  9 137   7   4   8   4   3]
- [ 20  10 138  32  29  21  47]
- [ 15   5   5 117   6   4  10]
- [  1   4   2   1  53   2   5]
- [  4   0   3   1   2  48   4]
- [  9   1  12  10   9  17  70]]
-Node Classification on random seed  1270 -> 0.647
-Confusion Matrix:
- [[ 82   2   5   6   1  17   7]
- [  5 118   8   1   7   7   2]
- [ 18  23 156  29  16  36  31]
- [ 12   5   7 107   3   9   8]
- [  2   6   6   1  53   2   1]
- [  5   1   6   3   0  57   5]
- [ 13   6   6   4   7  14  74]]
-Node Classification on random seed  1271 -> 0.611
-Confusion Matrix:
- [[ 77   1   3   2   3  13  15]
- [  5 109   7   3   7   6   8]
- [ 19   9 144  36  24  15  64]
- [ 28   1  12  96   2   2   9]
- [  2   3   5   4  66   4   3]
- [  7   1   1   1   2  53   3]
- [ 10   3   9   8  10  19  66]]
-Node Classification on random seed  1272 -> 0.628
-Confusion Matrix:
- [[ 71   5   2   2   3  11   8]
- [  5 123   5   0   6   4   3]
- [ 32  23 140  27  35  40  24]
- [ 10   9   4 111  10  11   5]
- [  3   5   4   4  50   3   2]
- [ 10   1   0   2   0  58   2]
- [ 14   4   7   7   9  11  75]]
-Node Classification on random seed  1273 -> 0.661
-Confusion Matrix:
- [[ 78   1   2   3   5   7  12]
- [  5 140   5   1   2   0   4]
- [  9  27 158  36  24  15  38]
- [ 10   4  17 109   5   5  19]
- [  0   9   3   2  60   2   2]
- [  5   1   1   1   3  41   1]
- [  8   7   1  10  11  16  75]]
-Node Classification on random seed  1274 -> 0.591
-Confusion Matrix:
- [[ 62   1   8   2   5  10  17]
- [  7 114  19   2  13   3   3]
- [ 20  27 148  19  27  20  50]
- [  9   3  15 115  13   4  13]
- [  2   9   4   1  54   0   2]
- [ 11   0   0   2   2  41   5]
- [  1   7  10  11   9  23  57]]
-Node Classification on random seed  1275 -> 0.59
-Confusion Matrix:
- [[ 85   3   7   9   3  17  12]
- [  6 120   5   4   6   1   2]
- [ 19  15 133  39  23  30  61]
- [ 21   6  19  97   5   3  10]
- [  2   4   2   3  48   0   4]
- [  4   0   2   6   0  34  11]
- [  8   4   6  13   7   8  73]]
-Node Classification on random seed  1276 -> 0.614
-Confusion Matrix:
- [[ 48   1  15   6   3   6  12]
- [  4 114  19   2  10   2   3]
- [ 18  11 172  33  17  25  51]
- [  6   3  18 104   7   6  16]
- [  1   4   9   0  62   0   2]
- [  5   1   4   4   0  34   3]
- [  8   4  11  12   6  18  80]]
-Node Classification on random seed  1277 -> 0.628
-Confusion Matrix:
- [[ 74   2   4   8   5  12   4]
- [  6 139   2   6   6   4   4]
- [ 26  26 146  28  28  16  22]
- [ 11   4   9 102  17   9   4]
- [  1   7   3   0  53   1   2]
- [  7   0   4   3   0  47  13]
- [ 14   7  15  15   2  15  67]]
-Node Classification on random seed  1278 -> 0.602
-Confusion Matrix:
- [[ 62   6   2   5   5   4  23]
- [  6 110   7   2   8   5  10]
- [ 22  28 133  31  32  19  60]
- [ 10   6   8 106   3   2  17]
- [  1   4   1   1  61   2   2]
- [  4   2   1   2   1  48   5]
- [  9   1  10   4   5  22  82]]
-Node Classification on random seed  1279 -> 0.597
-Confusion Matrix:
- [[ 69   2   4   4   5   6  11]
- [  2 136   8   5  17   0  14]
- [ 16  15 146  52  41  13  38]
- [  7   7  12  87  12   4  23]
- [  2   5   2   6  54   0   1]
- [  6   0   2   3   2  35   4]
- [  4   2  14   7   9  16  70]]
-Node Classification on random seed  1280 -> 0.664
-Confusion Matrix:
- [[ 70   3   5   6   0   8  18]
- [  3 133  12   1   2   1   8]
- [ 13  20 167  33  19   4  45]
- [ 12   0  19 106   7   0  14]
- [  1  10   3   1  56   0   4]
- [  8   2   3   0   0  36   7]
- [ 10   3   8   5   4  14  96]]
-Node Classification on random seed  1281 -> 0.612
-Confusion Matrix:
- [[ 50   7   1   3   5  18  16]
- [ 10 122   3   1   5   6   4]
- [ 21  33 167  35  19  27  29]
- [  3   6  17 103   1   6   9]
- [  1   5   3   4  56   3   2]
- [  7   3   2   0   0  52   9]
- [ 17   5  18   5   8  11  62]]
-Node Classification on random seed  1282 -> 0.622
-Confusion Matrix:
- [[ 62   1   9   2   7  10  13]
- [  2 116   7   6   8   2   6]
- [ 26  24 137  51  26  21  23]
- [ 10   0  13 127   5   3  17]
- [  2   5   5   1  62   0   1]
- [ 12   1   2   1   0  38   2]
- [ 13   2  16   6   5  12  80]]
-Node Classification on random seed  1283 -> 0.601
-Confusion Matrix:
- [[ 69   2   3   8   4  10   4]
- [  9 125   4   3   5   3   4]
- [ 31  29 123  36  26  27  28]
- [  8   5  16 110   4   5   8]
- [  6  10   7   2  51   0   1]
- [  6   1   1   5   3  46   9]
- [  4   7   3  17  11  24  77]]
-Node Classification on random seed  1284 -> 0.589
-Confusion Matrix:
- [[ 70   3  10   1   4   5  10]
- [  5 133   6   0   3   8   0]
- [ 34  23 121  35  51  38  24]
- [ 27   2  12  90   5   6   6]
- [  3   6   4   1  53   1   2]
- [ 11   1   0   5   0  51   8]
- [ 11   7   9   5  10   9  71]]
-Node Classification on random seed  1285 -> 0.642
-Confusion Matrix:
- [[ 68   3   2   3   4   8   2]
- [  5 134   2   1   5   1   1]
- [ 25  24 154  34  23  21  42]
- [ 10   9  19  97   5   8  14]
- [  1   7   4   1  63   0   2]
- [  4   1   3   3   1  54   3]
- [ 20   4   1   6   5  21  72]]
-Node Classification on random seed  1286 -> 0.646
-Confusion Matrix:
- [[ 72   1   1   3   2   6  12]
- [  4 144   5   1   8   1  13]
- [ 22  18 155  41  30  16  34]
- [ 16   2  17  88   3   5   8]
- [  0   4   3   2  64   4   2]
- [  6   0   1   0   3  43   6]
- [ 14   5   5   4  13  13  80]]
-Node Classification on random seed  1287 -> 0.611
-Confusion Matrix:
- [[ 64   5   4   3   5   3  14]
- [  2 130   7   2  20   3   2]
- [ 26  25 138  34  22  31  32]
- [ 15   7  16 109   7  12   9]
- [  0   6   5   3  59   0   0]
- [  6   1   5   1   0  40   9]
- [ 10   5   2  11   8  11  71]]
-Node Classification on random seed  1288 -> 0.614
-Confusion Matrix:
- [[ 69   0   2   5   4  20  12]
- [  3 113   7   8   3   4   6]
- [ 27   7 136  37  24  27  45]
- [  8   4  17 113   4  14   6]
- [  2   5   4   2  58   0   2]
- [  5   0   0   2   4  61   2]
- [  8   2   7  15   9  23  64]]
-Node Classification on random seed  1289 -> 0.613
-Confusion Matrix:
- [[ 65   4   2   5   2  15  19]
- [  0 129   5   1   6   2   3]
- [ 20  28 144  43  29  29  20]
- [ 10   7  13 101   5   2  10]
- [  1  11   3   3  70   0   0]
- [  7   2   8   2   0  31   5]
- [  8   8  20   3   4  22  73]]
-Node Classification on random seed  1290 -> 0.619
-Confusion Matrix:
- [[ 68   4   4   5   2   7   8]
- [  3 132   5   6   2   8   5]
- [ 17  26 134  54  43  17  32]
- [  8   7  10  98   4   4  15]
- [  0   7   2   1  60   0   4]
- [  5   2   1   1   1  51   4]
- [ 15   3  13  15   5   6  76]]
-Node Classification on random seed  1291 -> 0.601
-Confusion Matrix:
- [[ 54   1   7   2   5  15  27]
- [  3 125  14   0  13   1   3]
- [ 19  27 170  38  11  39  21]
- [ 15   5  28  90   1   4  13]
- [  0   7   5   1  51   1   3]
- [  9   2   9   0   5  44   1]
- [  8   1   8   4   2  21  67]]
-Node Classification on random seed  1292 -> 0.608
-Confusion Matrix:
- [[ 51   2   3   9   0  14  11]
- [  6 141   7   1   6   1   4]
- [ 27  25 143  20  34  20  35]
- [ 15   4  25  91   9   6  14]
- [  0   9   2   2  58   4   2]
- [  7   2   5   1   5  40   7]
- [ 14   2   8  12   1  11  84]]
-Node Classification on random seed  1293 -> 0.659
-Confusion Matrix:
- [[ 80   4   6   5   5  10   3]
- [  3 131   6   0  11   5   3]
- [ 15  22 173  26  27  17  39]
- [ 10   2  17 107   4   9   2]
- [  3   7   4   0  62   1   4]
- [  6   3   3   2   1  48   2]
- [  8   4   6   3  12  21  58]]
-Node Classification on random seed  1294 -> 0.624
-Confusion Matrix:
- [[ 57   1   1   7   4  25  10]
- [  9 108   6   1   6   3   4]
- [ 24  26 154  36  20  25  31]
- [ 14   7  17 102   3   8  10]
- [  0  10   4   1  64   0   2]
- [  5   1   4   1   1  55   9]
- [  6   2   6   8   8  10  84]]
-Node Classification on random seed  1295 -> 0.613
-Confusion Matrix:
- [[ 51   3   9  15  14   9  14]
- [  3 131   7   6   4   0   4]
- [ 22  15 160  28  40   9  46]
- [  8   7  24  72  14   3  15]
- [  1   4   2   3  61   0   2]
- [  7   0   1   3   0  47   4]
- [  8   2   9   7  10   5  91]]
-Node Classification on random seed  1296 -> 0.62
-Confusion Matrix:
- [[ 71   5   2   9   3   5   6]
- [  2 132   7   3   9   4   4]
- [ 27  25 118  49  10  22  55]
- [  3   2  13 111   7   4  19]
- [  1   4   6   2  62   0   3]
- [  8   3   2   1   2  46   2]
- [  9   9   7   4   8  14  80]]
-Node Classification on random seed  1297 -> 0.605
-Confusion Matrix:
- [[ 58   1   5   8   7  13  16]
- [  7 121   5   4   7   5   0]
- [ 11  18 131  48  25  35  42]
- [ 12   3  14  98   6  16  13]
- [  3   2   4   2  63   4   3]
- [  6   1   0   0   1  49   3]
- [  5   0  10   4   8  18  85]]
-Node Classification on random seed  1298 -> 0.58
-Confusion Matrix:
- [[ 64   1   3   4   3  18  13]
- [  0 100   6   8   7   2  11]
- [ 24  13 117  43  37  14  50]
- [ 15   1  17  99  16  12  13]
- [  1   4   1   4  66   1   3]
- [  6   0   2   4   0  53   6]
- [  7   1  18  14   6  11  81]]
-Node Classification on random seed  1299 -> 0.587
-Confusion Matrix:
- [[ 61   1   1  11   3  15  10]
- [ 12 121   6   2  10   2   4]
- [ 18  31 125  43  16  28  41]
- [  1   5  27  92  17  12  16]
- [  3   7   1   2  59   1   4]
- [  5   2   2   1   1  41   3]
- [  9   4   7   5   5  19  88]]
-Node Classification on random seed  1300 -> 0.621
-Confusion Matrix:
- [[ 74   1   4  10   4  10   4]
- [  1 137  20  11   5   0   3]
- [ 13  35 133  46  20  26  33]
- [  5   4  18 104   2   5   5]
- [  1   8   3   3  61   5   4]
- [  1   0   2   6   1  43   6]
- [ 10   5  14  13   6   6  69]]
-Node Classification on random seed  1301 -> 0.616
-Confusion Matrix:
- [[ 83   2   4   6   4   6   2]
- [  5 127   3   2  20   0   2]
- [ 21  38 116  35  39  31  28]
- [  1   4  26 112   8   3  11]
- [  2   5   3   0  62   0   5]
- [  3   2   2   3   1  32   7]
- [ 11   1  14   6  10   8  84]]
-Node Classification on random seed  1302 -> 0.624
-Confusion Matrix:
- [[ 71   4   6   2   2   9   4]
- [  1 129   9   6  14   1   2]
- [ 25  25 138  27  22  21  40]
- [ 15   2  15  89   7   3  10]
- [  1   8   2   5  59   1   2]
- [  8   4   0   1   1  54   4]
- [ 15   6  18  13   5  10  84]]
-Node Classification on random seed  1303 -> 0.626
-Confusion Matrix:
- [[ 70   1   6   1   3   9  24]
- [  1 134   4   1   4   3   4]
- [ 18  19 138  21  48  19  39]
- [  7   3  26 111   4   7   9]
- [  1   3   7   0  50   2   2]
- [  2   1   2   2   1  41  17]
- [  8   9  11  14   4   7  82]]
-Node Classification on random seed  1304 -> 0.598
-Confusion Matrix:
- [[ 79   2   5   5   0  11  12]
- [  9 131   6   4   2   4   3]
- [ 23  22 129  30  30  24  36]
- [ 18   9  17  91  11  11  14]
- [  1   8   5   0  54   0   3]
- [ 11   0   2   1   0  46   1]
- [ 17   5   8   6   8  18  68]]
-Node Classification on random seed  1305 -> 0.596
-Confusion Matrix:
- [[ 77   6   8   3   5   7   4]
- [  4 104  15   3  10  14   6]
- [ 17  19 131  62  32  24  23]
- [ 11   4  11 103   4   4  27]
- [  1   2   3   5  46   2   2]
- [  7   0   3   2   0  46   3]
- [ 11   4  11   6   4  15  89]]
-Node Classification on random seed  1306 -> 0.628
-Confusion Matrix:
- [[ 76   1   2   3   2  11  17]
- [  4 127   8   4   5   6   3]
- [ 18  21 135  31  35  24  39]
- [ 10   7  12  99   8   5  17]
- [  1   6   1   0  66   2   2]
- [  3   1   0   2   2  45  11]
- [ 11   4   8   7  11   7  80]]
-Node Classification on random seed  1307 -> 0.619
-Confusion Matrix:
- [[ 66   7   6   9   6   9  13]
- [  3 124   0   5  15   2   1]
- [ 13  13 158  37  18  31  40]
- [ 17   4  16 108   4   5  13]
- [  1   6   6   2  54   4   3]
- [  8   1   2   2   1  44   3]
- [ 14   3   9  10   6  13  65]]
-Node Classification on random seed  1308 -> 0.562
-Confusion Matrix:
- [[ 60   3   5   8   4   7   8]
- [  4 106   7   4  13   6   4]
- [ 14  20 133  47  36  14  77]
- [ 13   9  22  84   8   1  17]
- [  1   7   2   2  56   1   4]
- [  1   0   5   0   2  41   9]
- [  4  10   2   7  12  18  82]]
-Node Classification on random seed  1309 -> 0.64
-Confusion Matrix:
- [[ 60   0   1   2  10   9  18]
- [  9 136   2   1   5   1   5]
- [ 29  29 175  24  21  17  44]
- [ 11   4  16  89   5   7  21]
- [  0  12   1   1  62   0   0]
- [ 12   3   1   0   1  43   0]
- [ 10   3   8   3   2  12  75]]
-Node Classification on random seed  1310 -> 0.625
-Confusion Matrix:
- [[ 78   1   2   5   3  10  13]
- [  5 119   5   3  10   0   5]
- [ 35  19 160  30  22  10  43]
- [ 16   6  17  91   6   4  13]
- [  1   4   3   1  59   1   1]
- [  2   0   3   2   0  53   8]
- [ 15   1  13  10  16  11  65]]
-Node Classification on random seed  1311 -> 0.638
-Confusion Matrix:
- [[ 70   2   7   2   7  12  14]
- [  5 130   2   0   7   2   3]
- [ 30  14 158  22  23  24  33]
- [  7   0  14 103   5   9  20]
- [  1   7   5   0  63   3   2]
- [ 10   1   2   0   0  46   5]
- [  8   3   9   7  20  15  68]]
-Node Classification on random seed  1312 -> 0.6
-Confusion Matrix:
- [[ 79   1   1   2   2  12   6]
- [  5 130   7   2   4   2   3]
- [ 15  28 141  44  34  31  34]
- [ 13   9  20  97   1   8  10]
- [  2   5   3   0  53   3   1]
- [  7   1   2   2   3  47   4]
- [ 19   3  16   5   3  27  53]]
-Node Classification on random seed  1313 -> 0.622
-Confusion Matrix:
- [[ 83   1   1   1   6  15  11]
- [  5 116   7   4  15   5   1]
- [ 27  12 146  28  51  24  30]
- [ 10   2  16 108  10   6  11]
- [  2   6   4   2  57   1   0]
- [  3   5   1   3   2  37   3]
- [  4   6   7   5   7  18  75]]
-Node Classification on random seed  1314 -> 0.628
-Confusion Matrix:
- [[ 56   3   6   2   0  21  15]
- [  4 122   9   2  10   6   6]
- [ 25  18 176  30  25  11  48]
- [ 14   5  12  89   8   1  14]
- [  4   9   1   0  60   4   3]
- [  2   3   1   4   1  47   2]
- [  7   7   9   3   3  14  78]]
-Node Classification on random seed  1315 -> 0.618
-Confusion Matrix:
- [[ 59   3   1   8   3  10  25]
- [  8 122   5   2  13   0   6]
- [ 17  16 146  17  31  33  44]
- [  5   2   9 100   6   6  19]
- [  2   7  11   1  62   0   1]
- [  3   1   0   1   1  42  16]
- [ 11   1   8   7  10  12  87]]
-Node Classification on random seed  1316 -> 0.613
-Confusion Matrix:
- [[ 71   0  11   6   2   7   6]
- [  8 131   9   5   8   1   3]
- [ 44  24 110  23  25  23  51]
- [  8   0   9 119   1   6  14]
- [  2   3   6   4  54   2   2]
- [  3   1   5   1   2  41  10]
- [  9   4  10   6   4  19  87]]
-Node Classification on random seed  1317 -> 0.612
-Confusion Matrix:
- [[ 81   1   2   4   9  14   6]
- [  7  97   6   0  19   3   4]
- [ 29  10 150  34  36  18  44]
- [ 13   3  18  92   4  11  11]
- [  3   1   2   2  67   2   4]
- [  7   2   1   3   1  43   6]
- [ 17   3  14   1   6   7  82]]
-Node Classification on random seed  1318 -> 0.631
-Confusion Matrix:
- [[ 57   3   3   5   4   7  15]
- [  2 131   6   3   5   4   7]
- [ 10  13 149  37  17  41  49]
- [ 17   7  15 101   5   3   7]
- [  1  10   1   0  51   2   2]
- [  7   0   7   1   0  45   9]
- [ 16   2   4   8   6   8  97]]
-Node Classification on random seed  1319 -> 0.601
-Confusion Matrix:
- [[ 61   3   4  10   5  14   8]
- [ 10 118   6   3   4   2   8]
- [ 19  13 137  47  39  30  33]
- [ 11   4  18  88   2   3  11]
- [  2   8   2   3  60   0   1]
- [  5   0   4   0   0  53   8]
- [ 16   4  14   7  12   6  84]]
-Node Classification on random seed  1320 -> 0.668
-Confusion Matrix:
- [[ 85   2   4   3   1   7  15]
- [  3 133   7   1   1   1   4]
- [ 28  10 155  33  16  34  21]
- [  5   1  15  99   9  12  11]
- [  4   6   6   0  63   2   3]
- [  8   0   3   2   1  47   2]
- [ 14   4   4   6   4  19  86]]
-Node Classification on random seed  1321 -> 0.641
-Confusion Matrix:
- [[ 47  10   7  12   6  20   5]
- [  2 152   3   0   2   3   1]
- [ 16  20 151  30  26  37  27]
- [  5   7   6 113   5   5   7]
- [  1   7   4   2  63   3   0]
- [  7   4   9   3   0  43   6]
- [  9   4   8   9   3  18  72]]
-Node Classification on random seed  1322 -> 0.622
-Confusion Matrix:
- [[ 77   3   2   6   2  11  14]
- [  4 114  15   3   4   5  12]
- [ 46  11 154  30  22  29  27]
- [  3   7  18 108   4   6  14]
- [  2  10   3   0  55   2   1]
- [  5   0   2   0   2  37   4]
- [ 13   5   5   7   5  14  77]]
-Node Classification on random seed  1323 -> 0.613
-Confusion Matrix:
- [[ 72   6   4   2   0  15  15]
- [  1 133   0   2   6   6   6]
- [ 25  20 153  27  30  25  47]
- [ 10   3  17  83  17  13  14]
- [  0   2   0   3  57   3   5]
- [  2   2   3   0   0  45   4]
- [  9   7  13   3   9  11  70]]
-Node Classification on random seed  1324 -> 0.619
-Confusion Matrix:
- [[ 71   3   4   9   3  10  15]
- [  5 122   3   2   6   7   1]
- [ 23  26 115  38  35  39  20]
- [  6   2  10 120   2  10  10]
- [  3   6   5   4  60   1   1]
- [  6   3   0   2   2  49   5]
- [ 11   3   3  14   3  20  82]]
-Node Classification on random seed  1325 -> 0.57
-Confusion Matrix:
- [[ 64   3   6   7   4   8  17]
- [  8 104   5   7  12   5   7]
- [ 23  13  98  46  56  43  32]
- [ 17   3   6 112   7   5  13]
- [  1   2   2   1  74   1   2]
- [  2   0   4   1   1  48   5]
- [  5   4   9  10   6  21  70]]
-Node Classification on random seed  1326 -> 0.584
-Confusion Matrix:
- [[ 70   0   6   8   2  16   7]
- [ 17 111   1   2  17   5   6]
- [ 28  20 129  44  16  19  66]
- [  8   2  19 103   9   3   7]
- [  0   9   2   2  67   1   5]
- [  5   0   3   0   2  40   6]
- [ 16   6   5  11   5  10  64]]
-Node Classification on random seed  1327 -> 0.615
-Confusion Matrix:
- [[ 81   3   8   4   7  12   4]
- [  4 125   2   4   4   6   7]
- [ 32  20 142  54  35   8  48]
- [ 20   2  12 100   5   5   3]
- [  1   5   4   1  62   1   0]
- [  7   2   4   0   0  36   2]
- [  6   3  10  10   6  14  69]]
-Node Classification on random seed  1328 -> 0.574
-Confusion Matrix:
- [[ 62   2   1   5   7  18  13]
- [  4 118   4   0   9   1   9]
- [ 35  19 117  48  55  19  29]
- [ 12   7   6  96   6   9  22]
- [  1   5   3   1  65   0   3]
- [  6   0   4   3   0  30  11]
- [  8   5  11   9   5  11  86]]
-Node Classification on random seed  1329 -> 0.6
-Confusion Matrix:
- [[ 60   5   4   9   4   2   5]
- [  5 142   4   3   7   2   5]
- [ 28  23 158  26  21  28  25]
- [ 13   7  23  65  12   6  27]
- [  3   6   4   1  61   4   1]
- [  7   3   1   3   6  46   1]
- [ 21   4  10   2  12  17  68]]
-Node Classification on random seed  1330 -> 0.586
-Confusion Matrix:
- [[ 60   0   8  11   4  12   8]
- [  4 122   5   8   5   3   5]
- [ 20  20 123  20  36  17  69]
- [  4   1  30 104   1   5  23]
- [  2   4   1   1  52   4   3]
- [  5   2   1   5   1  48   3]
- [ 23   3   2  15   5  15  77]]
-Node Classification on random seed  1331 -> 0.654
-Confusion Matrix:
- [[ 78   0   7   2   3  14   9]
- [  3 133   6   2   5   1   9]
- [ 30  22 153  29  13  18  35]
- [ 13   4  13 102   2   7  16]
- [  2   2   4   1  63   0   3]
- [  5   2   2   0   0  52   3]
- [  8   6  14   6   7  18  73]]
-Node Classification on random seed  1332 -> 0.633
-Confusion Matrix:
- [[ 65   6   3   5   5   1  17]
- [  1 121   6   0  10   0  10]
- [ 29  24 161  23  21  31  34]
- [  9   5  10 105   6  10   7]
- [  1   4   2   4  64   0   1]
- [ 11   3   2   1   3  41  12]
- [ 12   5  11   6  10   6  76]]
-Node Classification on random seed  1333 -> 0.604
-Confusion Matrix:
- [[ 71   2  10  10   1   9  10]
- [  6 115  12   1   7   4   5]
- [ 21  27 154  46  22  22  29]
- [ 23   4  14  82   9   8  15]
- [  0   5   3   1  63   0   2]
- [  5   1   2   2   2  53   5]
- [ 11   2  13   7   8  10  66]]
-Node Classification on random seed  1334 -> 0.599
-Confusion Matrix:
- [[ 54   1   8   6   2  15  18]
- [  2 111   8   8  12   2   4]
- [ 20  22 130  49  34  20  44]
- [ 14   9  15 114   2   6   7]
- [  0   7   2   0  59   0   2]
- [  2   1   4   2   0  42   6]
- [  8   5  11   9   6   8  89]]
-Node Classification on random seed  1335 -> 0.627
-Confusion Matrix:
- [[ 75   4   1   1   2  19  12]
- [  8 105   7   5   8   1   5]
- [ 23  14 147  35  28  24  36]
- [ 11   3  14 103   3   3  17]
- [  2   7   2   0  62   0   1]
- [ 10   1   2   2   1  49   2]
- [ 21   1   4  17   2  14  86]]
-Node Classification on random seed  1336 -> 0.566
-Confusion Matrix:
- [[ 74   5   6   7   6  19   4]
- [  5 110  13   3  13   5   3]
- [ 23  25 103  32  26  23  76]
- [ 10   3  19  94   2   4  20]
- [  1   5   6   0  72   2   4]
- [  1   2   3   3   0  39   7]
- [  8   1   6  11   7  15  74]]
-Node Classification on random seed  1337 -> 0.611
-Confusion Matrix:
- [[ 63   0   7  19   4  17   7]
- [  4 139   4   1   0   3   3]
- [ 18  23 145  30  29  30  48]
- [ 10   3  12  96   7   7  13]
- [  1   7   5   0  57   2   1]
- [  8   0   2   5   0  44   1]
- [  9   6   8   3  12  20  67]]
-Node Classification on random seed  1338 -> 0.567
-Confusion Matrix:
- [[ 70   1   1   3   5  20  15]
- [  3 115  11   5   3   3   5]
- [ 28  31  81  37  46  31  46]
- [  4   4   8 107  10  15  19]
- [  1   6   4   1  61   0   2]
- [  3   5   2   0   0  48   5]
- [  5   2   6  13   7  17  85]]
-Node Classification on random seed  1339 -> 0.643
-Confusion Matrix:
- [[ 80   3   6   5   6   6  14]
- [  4 122   2   1   9   4   3]
- [ 33  17 157  28  21  17  32]
- [  5   6  16 110   7   4  14]
- [  2   6   6   5  66   0   1]
- [  7   3   6   3   0  43   3]
- [  4   2  14   3  12  17  65]]
-Node Classification on random seed  1340 -> 0.625
-Confusion Matrix:
- [[ 71   2   9   5   3  19   5]
- [  3 122   8   2  10   2   6]
- [ 15  13 164  36  16  30  28]
- [  6   4  30  87   7  13  13]
- [  1   2  10   0  64   0   2]
- [  5   2   2   2   0  54   2]
- [  8   5   3   8   5  33  63]]
-Node Classification on random seed  1341 -> 0.595
-Confusion Matrix:
- [[ 63   0   4   8   8  17  12]
- [  6 113   5   0  23   9   2]
- [ 41  12 133  29   9  30  37]
- [ 16   4  12 100   2  17  11]
- [  2   6   1   0  62   1   2]
- [  6   3   1   1   0  46   9]
- [ 10   4   6   2   9  28  78]]
-Node Classification on random seed  1342 -> 0.603
-Confusion Matrix:
- [[ 68   2   9   4   0  25  11]
- [  6 134   4   0   6   1   5]
- [ 16  25 120  35  45  17  36]
- [  5   4  16 105   7  13  20]
- [  2   4   2   5  59   0   7]
- [  4   2   0   0   0  41   6]
- [ 12   5  10   5   1  20  76]]
-Node Classification on random seed  1343 -> 0.63
-Confusion Matrix:
- [[ 76   4   3   1   5  10   6]
- [  5 133   4   5  14   2   8]
- [ 20  25 155  43  24  14  34]
- [  9   5  18 107   4   4  17]
- [  2   2   1   3  61   0   1]
- [ 10   1   2   1   1  26  10]
- [ 11   4  15  12   4   6  72]]
-Node Classification on random seed  1344 -> 0.6
-Confusion Matrix:
- [[ 61   2   5   1   3  16  10]
- [  6 127   7   3   7   2   3]
- [ 16  21 132  37  30  44  35]
- [ 13   3   3 109   4  13  16]
- [  2   8   3   1  60   2   5]
- [  2   0   0   6   0  44   7]
- [ 13   1  10   9   7  24  67]]
-Node Classification on random seed  1345 -> 0.597
-Confusion Matrix:
- [[ 62   1   2   6   7   9  15]
- [  2 126   2   3  11   3   4]
- [ 31  29 127  42  25  23  29]
- [ 25   3  19 101   9   4  20]
- [  1   4   4   3  44   2   1]
- [  1   2   2   3   1  55   7]
- [  9   5   6   9   7  12  82]]
-Node Classification on random seed  1346 -> 0.595
-Confusion Matrix:
- [[ 50   3  29   6   3  14  11]
- [ 10 114   6   3  15   3   3]
- [ 14  15 139  24  51  21  30]
- [  9   1  19  99   9   3   9]
- [  2   5   6   1  60   0   1]
- [  3   5   2   4   0  58   4]
- [ 10   6  15   7   9  14  75]]
-Node Classification on random seed  1347 -> 0.644
-Confusion Matrix:
- [[ 60   2   3   5   9  21   1]
- [  4 151   5   2   6   1   5]
- [ 12  27 142  39  25  23  47]
- [  6   1   9 103   5   6  10]
- [  0  10   4   1  65   0   1]
- [  6   1   1   0   2  46   3]
- [ 12   4   6   9   6  16  77]]
-Node Classification on random seed  1348 -> 0.644
-Confusion Matrix:
- [[ 65   1   4   2   2  11   9]
- [  8 146   5   2  11   2   5]
- [ 19  24 157  20  20  24  34]
- [ 17   3  25  98   5   6   9]
- [  0   8   7   0  74   4   1]
- [  5   0   1   5   0  39   5]
- [  9   4  12   5   4  18  65]]
-Node Classification on random seed  1349 -> 0.627
-Confusion Matrix:
- [[ 74   2   4   8   3  13   1]
- [  4 129  12   2   5   1   9]
- [ 20  22 146  53  29  10  37]
- [ 10   5  15 100   4   4   4]
- [  1   9   4   2  50   0   3]
- [  3   1   1   1   0  48   7]
- [ 12   3   6  11   7  25  80]]
-Node Classification on random seed  1350 -> 0.666
-Confusion Matrix:
- [[ 90   0   3   4   3  13   2]
- [  2 132   2   3   5   2   9]
- [ 16  18 155  27  32  21  50]
- [  4   1  19 115   1   5  15]
- [  1   8   3   3  51   1   2]
- [  5   1   2   4   1  45   2]
- [ 10   2   8   6   3  15  78]]
-Node Classification on random seed  1351 -> 0.604
-Confusion Matrix:
- [[ 65   1  12   8   2  12  17]
- [  5 117   4   2  19   1   3]
- [ 15  18 135  31  29  20  54]
- [ 15   5  11  95   5   4  14]
- [  4   7   2   3  66   0   2]
- [  0   1   2   1   2  54   6]
- [  6   2  12   9   3  27  72]]
-Node Classification on random seed  1352 -> 0.612
-Confusion Matrix:
- [[ 82   0  12   8   0   7  13]
- [  1 121   4   0   7   4   9]
- [ 24  26 126  41  37  16  37]
- [ 10   8  17  92   7   0  14]
- [  3  11   3   2  64   0   1]
- [  2   3   4   0   1  44  12]
- [  3   4  14   6   6  11  83]]
-Node Classification on random seed  1353 -> 0.638
-Confusion Matrix:
- [[ 66   3  10   2   3  16   6]
- [  4 122   5   3   8   1   2]
- [ 31  16 158  25  31  32  24]
- [ 13   3  22 106   3   8   5]
- [  3   5   3   1  64   1   3]
- [  3   0   9   3   0  52   1]
- [ 11   0  11   8   7  17  70]]
-Node Classification on random seed  1354 -> 0.611
-Confusion Matrix:
- [[ 63   6   2   7   3  15  10]
- [  3 128   8   2   3   1   2]
- [ 22  20 170  31  26  29  35]
- [  7   7  21 103   4   7  14]
- [  1   6   6   1  55   0   3]
- [  8   2   3   1   2  40   4]
- [ 11   3  18  12  17   6  52]]
-Node Classification on random seed  1355 -> 0.601
-Confusion Matrix:
- [[ 59   3   9   9   6  17   7]
- [  4 127   9   1   3   0   4]
- [ 20  30 152  32  15  41  39]
- [ 10   6  12  81   5  12  24]
- [  2   9  10   1  54   0   2]
- [  1   1   1   5   0  62   1]
- [  9   2  12   2   7  16  66]]
-Node Classification on random seed  1356 -> 0.647
-Confusion Matrix:
- [[ 91   3  10   7   5  14   5]
- [  7 122   1   6   7   1   4]
- [ 16  43 146  28  23  20  22]
- [  6   2  23 104   0   6  12]
- [  1   2   2   0  58   0   3]
- [ 10   3   5   0   0  46   2]
- [ 21   7   8   0   9   9  80]]
-Node Classification on random seed  1357 -> 0.601
-Confusion Matrix:
- [[ 67   2   0   7   5  16  13]
- [  4 121   4   2   9   6   0]
- [ 26  29 128  29  35  22  48]
- [ 13   7  25  88  13   3   5]
- [  2   4   6   1  63   1   0]
- [  5   0   0   1   0  46   5]
- [  8   4   9   5  10  15  88]]
-Node Classification on random seed  1358 -> 0.619
-Confusion Matrix:
- [[ 65   1   3   0   7  16   5]
- [  1 135   5   2  10   2   8]
- [ 21  25 139  30  24  25  41]
- [ 11   4  15  86  10  13   8]
- [  2   5   2   2  74   1   2]
- [  6   0   3   0   2  42   6]
- [ 11   4   9   7   9  23  78]]
-Node Classification on random seed  1359 -> 0.626
-Confusion Matrix:
- [[ 77   0   9   9   5   7   9]
- [  5 114   2   7   6   4  12]
- [ 25  13 135  52  19  13  40]
- [ 11   6  14  91   6   5  10]
- [  0   6   9   3  65   0   4]
- [  7   0   4   4   0  51   5]
- [ 12   0   9   8   3  11  93]]
-Node Classification on random seed  1360 -> 0.615
-Confusion Matrix:
- [[ 67   2   2   2   5  17   1]
- [  1 126   5   7   8   7   1]
- [ 34  23 153  49  19  24  31]
- [  9   6   5  91  16  12   9]
- [  0   9   1   0  73   2   3]
- [  3   3   3   3   5  45   4]
- [ 13   2  10   2  11  16  60]]
-Node Classification on random seed  1361 -> 0.61
-Confusion Matrix:
- [[ 67   2   3   4   0   8  23]
- [  4 119   6   5   0   3   2]
- [ 32  21 131  31  29  20  52]
- [ 20   6   8 103   8   3  10]
- [  0  11   5   7  68   2   3]
- [  9   0   5   0   1  47   2]
- [  5   5   5  10   8  12  75]]
-Node Classification on random seed  1362 -> 0.63
-Confusion Matrix:
- [[ 78   4   5   6   3  11   5]
- [ 12 114   5   5   4   0   3]
- [ 19  23 137  47  27  23  47]
- [  8   3  17 103   5   5   6]
- [  0   9   1   2  58   0   4]
- [  3   2   0   4   1  48   8]
- [ 10   3  11   6   7   6  92]]
-Node Classification on random seed  1363 -> 0.633
-Confusion Matrix:
- [[ 75   3   4   4   5  11   6]
- [  4 131   5   6   2   0   7]
- [ 15  29 148  44  16  29  35]
- [  8   3  11 109   5   9  17]
- [  2  10   4   2  50   0   5]
- [  3   2   1   3   0  43   3]
- [  6   2   9   6   7  24  77]]
-Node Classification on random seed  1364 -> 0.595
-Confusion Matrix:
- [[ 57   1   7   7   3  18  23]
- [  4 135   3   7   0   3   2]
- [ 15  31 127  47  25  20  40]
- [  3   5  16  85   9   6  15]
- [  3   9   7   1  56   1   2]
- [  2   2   3   0   0  40  13]
- [  4   9  10   3   8  18  95]]
-Node Classification on random seed  1365 -> 0.601
-Confusion Matrix:
- [[ 53   8   5  11   3  13  13]
- [  7 137   2   1   7   0   2]
- [ 24  24 143  28  31  17  34]
- [ 27   6  11 100   5   4  18]
- [  3   8   3   2  62   3   3]
- [  9   0   1   5   0  43   7]
- [ 19   9  11   3   5   7  63]]
-Node Classification on random seed  1366 -> 0.613
-Confusion Matrix:
- [[ 81   1   3   0   4  16   4]
- [  3 115  11   2   4   5   4]
- [ 30  31 129  47  16  29  58]
- [  7   1  12 106   4   4  14]
- [  4   4   4   0  64   1   2]
- [  4   1   1   2   1  39   5]
- [ 15   3   8   6   6  10  79]]
-Node Classification on random seed  1367 -> 0.566
-Confusion Matrix:
- [[ 58   1   1   3  10  14  14]
- [  6 105  12   7  10   7   3]
- [ 23  16 107  52  27  21  50]
- [ 17   2  13  90   3   8  23]
- [  0   3   6   1  74   1   4]
- [  5   2   0   8   7  36   7]
- [ 15   2  11  10   3   6  96]]
-Node Classification on random seed  1368 -> 0.612
-Confusion Matrix:
- [[ 74   4   3   6   1  12  11]
- [  6 140  13   3   2   3   5]
- [ 14  28 147  40  24  19  43]
- [  4   4  21  91  12   5  13]
- [  0  10   1   0  58   0   3]
- [  5   3   8   3   1  28  16]
- [  5   2  16   7   1  11  74]]
-Node Classification on random seed  1369 -> 0.624
-Confusion Matrix:
- [[ 83   2   3   3   3  13  16]
- [  4 121  10   2   9   0   7]
- [ 33  25 139  29  20  32  30]
- [ 13   6   6 109   4   9  12]
- [  4   3   6   0  55   0   0]
- [  4   2   0   5   1  46  10]
- [ 17   3   9   4   4  13  71]]
-Node Classification on random seed  1370 -> 0.601
-Confusion Matrix:
- [[ 66   8   5   3   2   9   7]
- [  2 133   3   7   7   0   2]
- [ 28  29  97  43  28  28  45]
- [ 14   8  10 108   9   4  21]
- [  2  10   1   2  61   0   1]
- [  2   0   1   3   1  49   8]
- [ 12   5  11   6   1  11  87]]
-Node Classification on random seed  1371 -> 0.605
-Confusion Matrix:
- [[ 59   2   4  20   6  15   9]
- [  2 142   3   3  10   5   8]
- [ 25  24 142  36  21  17  34]
- [ 12   6  15  95  12   7  12]
- [  0   6   4   5  56   0   2]
- [  6   2   3   1   0  45   2]
- [  6   4  13  10   8  15  66]]
-Node Classification on random seed  1372 -> 0.621
-Confusion Matrix:
- [[ 75   2   6   8   3  17   4]
- [  4 127   6   2  11   7   1]
- [ 17  36 149  42  19  17  45]
- [ 13   5   7 109   2   7  10]
- [  1   4   0   2  49   3   4]
- [  6   2   2   0   0  49   8]
- [ 11   2   9  12   5  17  63]]
-Node Classification on random seed  1373 -> 0.646
-Confusion Matrix:
- [[ 81   3   3   5   4  16   3]
- [  5 128   1   0  12   7   1]
- [ 28  20 171  22  21  32  22]
- [ 17   2  21  92   2   4  21]
- [  1   5   1   4  60   1   3]
- [  9   2   3   4   0  44   4]
- [  9   0   9   5   3  19  70]]
-Node Classification on random seed  1374 -> 0.608
-Confusion Matrix:
- [[ 67   4   5   3   5  11  15]
- [  6 111  11   4  28   3   3]
- [ 23  36 138  23  15  18  35]
- [  8  13  11 109   9   8  12]
- [  3   5   7   2  61   0   0]
- [  3   4   4   1   3  40   9]
- [ 13   6   6   3   7   7  82]]
-Node Classification on random seed  1375 -> 0.603
-Confusion Matrix:
- [[ 76   2   2   7   8  11   8]
- [  3 125   1   1  10   3   5]
- [ 16  34 151  42  27  21  31]
- [ 14   6  17  86   5   5  19]
- [  1   2   8   0  63   1   2]
- [  5   4   1   0   6  36   6]
- [ 16   3   6  10  17  11  66]]
-Node Classification on random seed  1376 -> 0.596
-Confusion Matrix:
- [[ 57   1   3  10   6   3  15]
- [  6 133  13   2   7   1   4]
- [ 23  20 146  34  34  21  41]
- [ 14   3  15  83   7   3  23]
- [  0   5   4   4  62   0   1]
- [  6   0   8   4   2  33   7]
- [  3   3  17  12   8  11  82]]
-Node Classification on random seed  1377 -> 0.633
-Confusion Matrix:
- [[ 76   0   5   7   3  13   9]
- [  4 130   4   1   7   3   2]
- [ 25  24 150  17  23  22  39]
- [ 17  11  24  91   2   9  11]
- [  1   4  10   0  58   0   2]
- [  6   2   4   1   1  49   1]
- [ 18   9   4   5   7  10  79]]
-Node Classification on random seed  1378 -> 0.604
-Confusion Matrix:
- [[ 64   1   7   0   3  11  15]
- [  6 123   7   4  21   4   3]
- [ 27  19 134  37  37  25  41]
- [  7   5  11 102   5   7  15]
- [  3   4   1   0  56   1   3]
- [  8   0   6   0   1  46   6]
- [ 14   3   6  10   7   5  79]]
-Node Classification on random seed  1379 -> 0.648
-Confusion Matrix:
- [[ 64   2   8   6   3   6  15]
- [  4 147   4   2   3   4   4]
- [ 17  18 166  39  16  23  37]
- [  6   5  11 108   5   6  11]
- [  0   6   9   1  53   0   2]
- [  5   3   4   2   0  40   4]
- [ 13   3   7  17   7  14  70]]
-Node Classification on random seed  1380 -> 0.682
-Confusion Matrix:
- [[ 69   6   2   6   4  12   5]
- [  4 137   7   3   2   3   1]
- [ 14  10 174  27  22  17  43]
- [  8   3   7 112   3   4  12]
- [  0  10   7   1  66   0   2]
- [  6   4   1   1   0  43   9]
- [ 15   1  10   5   7  14  81]]
-Node Classification on random seed  1381 -> 0.646
-Confusion Matrix:
- [[ 74   5   2   5   8  14  10]
- [  3 122   6   4  12   2   1]
- [ 19  23 171  32  20  21  34]
- [ 14   2   9 108   6   5  20]
- [  0   2   5   2  52   1   7]
- [  2   4   3   0   0  46   2]
- [ 15   7   4   4   1  18  73]]
-Node Classification on random seed  1382 -> 0.63
-Confusion Matrix:
- [[ 72   1   1   5   5   3  14]
- [ 16 124   4   0  11   1   3]
- [ 21  26 131  34  31  19  45]
- [  7   3  14 106   4   9  18]
- [  1   6   1   0  67   0   3]
- [  8   1   5   0   0  45   8]
- [ 12   2   4   8   4  12  85]]
-Node Classification on random seed  1383 -> 0.623
-Confusion Matrix:
- [[ 69   2   4   9   4  13  14]
- [ 10 114   4   6   6   7   2]
- [ 15  22 156  37  29  28  34]
- [ 10   4  18 110   4   3  10]
- [  0   5   8   0  55   2   2]
- [  9   1   1   0   2  44   3]
- [  6   5  10   5   6  17  75]]
-Node Classification on random seed  1384 -> 0.607
-Confusion Matrix:
- [[ 73   1   9   3   1   7  11]
- [  0 137   3   3   4   2  11]
- [ 37  26 123  49  27  16  27]
- [ 10   4  31 101   4   8  10]
- [  2   5   4   1  54   1   3]
- [  2   1   4   5   1  39   4]
- [ 10   0   9  15   4  18  80]]
-Node Classification on random seed  1385 -> 0.624
-Confusion Matrix:
- [[ 67   2   7   2   4  13   4]
- [  5 127   4   3  15   6   3]
- [ 13  27 145  28  22  21  36]
- [ 17   5  21 106   6   2  15]
- [  3   2   3   2  68   1   4]
- [  7   1   1   1   0  41   4]
- [ 13   7   9   9   8  20  70]]
-Node Classification on random seed  1386 -> 0.609
-Confusion Matrix:
- [[ 71   3   3   5   4  23   4]
- [  3 122  12   1   4   1   6]
- [ 22  28 123  42  22  23  39]
- [ 19   6  11 105   3   7  13]
- [  4   6   4   4  57   3   1]
- [  1   0   2   0   3  48  13]
- [ 11   3   7   7   2  16  83]]
-Node Classification on random seed  1387 -> 0.6
-Confusion Matrix:
- [[ 61   1   5  12   5   6  17]
- [  3 124   8   8   6   2   6]
- [  8  21 137  35  37  22  35]
- [  1   5  26 102   7   7  21]
- [  0   8   6   0  62   1   3]
- [  5   6   0   4   1  39   1]
- [ 13   6  14   8   8  12  75]]
-Node Classification on random seed  1388 -> 0.596
-Confusion Matrix:
- [[ 71   5   6   5   2  14  13]
- [  4 112   6   2   9   7   3]
- [ 27  36 148  33  16  26  34]
- [ 22   4   9 100   3  12   5]
- [  0   1   8   1  59   1   5]
- [  3   0   3   2   0  49   6]
- [ 11   5  26   7   8  14  57]]
-Node Classification on random seed  1389 -> 0.608
-Confusion Matrix:
- [[ 63   0   2   8   5  14   4]
- [  7 112   4   0  16   6   6]
- [ 29  11 134  32  30  28  42]
- [  9   5  30  98   6   4  11]
- [  0   3   3   3  63   0   4]
- [  9   1   0   1   0  55   3]
- [  9   3   9   8   7  20  83]]
-Node Classification on random seed  1390 -> 0.599
-Confusion Matrix:
- [[ 50   7   4   8   3  15  18]
- [  2 138   3   2  18   2   0]
- [ 20  34 143  23  32  15  38]
- [  9   3  26  86   7   0  19]
- [  0   7   0   0  62   1   5]
- [  7   2   7   0   0  44   5]
- [ 15   2  11  16   4  11  76]]
-Node Classification on random seed  1391 -> 0.632
-Confusion Matrix:
- [[ 74   1   2   7   2  13  11]
- [  4 131   5   5   6   1   6]
- [ 21  23 151  47  24  11  44]
- [ 15   3   7 100   5   5   6]
- [  4   7   7   1  59   1   2]
- [  5   1   2   1   1  43   4]
- [  8   5   6  12   7  20  74]]
-Node Classification on random seed  1392 -> 0.628
-Confusion Matrix:
- [[ 81   4   4   5   5  16  10]
- [  2 140  10   1   6   2   2]
- [ 37  23 129  22  43  18  24]
- [ 18   3  17 105  11   2   7]
- [  2   9   2   2  56   0   2]
- [  2   4   1   4   0  50   7]
- [ 12   8   8   3   2  12  67]]
-Node Classification on random seed  1393 -> 0.611
-Confusion Matrix:
- [[ 68   1   5   8   1   8  19]
- [  3 124   3   6   3   5   8]
- [ 26  28 124  57  25  10  45]
- [ 11  12   8 125   4   4  12]
- [  3   1   2   2  52   0   3]
- [ 10   2   0   1   0  43   6]
- [ 13   7  13   3   6   5  75]]
-Node Classification on random seed  1394 -> 0.575
-Confusion Matrix:
- [[ 72   2   2   6   2  12  13]
- [  7 112   8   2  10   4   1]
- [ 18  23 146  29  50  18  41]
- [ 12   8  19 102   7   5  20]
- [  2   9   0   6  45   0   3]
- [  0   2   3   4   2  41   8]
- [  5   3   7   6  36  10  57]]
-Node Classification on random seed  1395 -> 0.635
-Confusion Matrix:
- [[ 89   6   8   3   3   3  11]
- [  4 110   5   3   6   6   3]
- [ 13  27 145  43  24  22  31]
- [ 10   7  19 102   4   2  17]
- [  3   5   5   1  65   2   1]
- [  2   0   0   4   0  47   5]
- [ 15   5   6   7   7  17  77]]
-Node Classification on random seed  1396 -> 0.626
-Confusion Matrix:
- [[ 57   3   3  13   6   9  11]
- [  2 126   3   1  15   2   2]
- [ 32  29 151  35  21  25  24]
- [ 13   5   8 106   9   5   9]
- [  0   2   3   3  65   0   2]
- [  8   1   1   2   0  44   2]
- [ 10   7   6  18  16   8  77]]
-Node Classification on random seed  1397 -> 0.661
-Confusion Matrix:
- [[ 86   2   4   1   3  11  10]
- [  4 146  10   1   3   7   3]
- [ 18  19 165  19  20  29  35]
- [ 19   6   9  83   2   3  19]
- [  3   4   9   0  62   0   0]
- [  6   0   3   0   0  42   3]
- [ 10   7   9   2   9  17  77]]
-Node Classification on random seed  1398 -> 0.615
-Confusion Matrix:
- [[ 58   4   8   6   8  12  10]
- [ 11 121   5   1   9   5   3]
- [ 24  17 141  28  18  46  37]
- [  4   3  11 111   6  11  23]
- [  3   6   5   1  70   0   0]
- [  6   1   2   1   1  41   1]
- [  7   8   3   5   5  20  73]]
-Node Classification on random seed  1399 -> 0.549
-Confusion Matrix:
- [[ 75   1   2  10   3  11  13]
- [  3 139   7   2   6   2   5]
- [ 16  26 114  62  53  18  30]
- [ 11   6  27  82   4   9   8]
- [  2   2   6   1  46   0   7]
- [  7   3   3   3   2  35   7]
- [ 16   3   7  23  14  10  58]]
-Node Classification on random seed  1400 -> 0.587
-Confusion Matrix:
- [[ 70   2   2  11   6   8   8]
- [  0 122   8   1  11   1   5]
- [ 34  19 112  37  45  20  37]
- [ 18   3  13  90   7  13  17]
- [  1   4   4   3  69   1   4]
- [  5   2   3   4   1  42   4]
- [  8   3   8   5  16  11  82]]
-Node Classification on random seed  1401 -> 0.615
-Confusion Matrix:
- [[ 77   0   2  12   2   9  12]
- [ 12 123   5  11   5   1   0]
- [ 34  18 121  37  38  16  40]
- [ 16   3  10 116   5   5   8]
- [  1   5   4   5  48   3   2]
- [ 12   1   1   1   1  49   1]
- [ 12   2   6   8   3  16  81]]
-Node Classification on random seed  1402 -> 0.584
-Confusion Matrix:
- [[ 75   5   5  10   9  12   3]
- [  4 123   4   4   8   1   5]
- [ 23  21 111  20  54  21  45]
- [  8   3  13 106   6   5  13]
- [  1   2   8   2  64   2   4]
- [  6   3   1   2   1  46   1]
- [ 14   8  10  14  11  24  59]]
-Node Classification on random seed  1403 -> 0.604
-Confusion Matrix:
- [[ 69   3   1   9   2   8  13]
- [  6 121   8   3   6   2   2]
- [ 48  17 124  33  40  37  17]
- [ 12   5  14 119   5   4   9]
- [  2   8   3   4  63   0   0]
- [  5   2   2   2   0  42   3]
- [  9   3   4   9  15  21  66]]
-Node Classification on random seed  1404 -> 0.641
-Confusion Matrix:
- [[ 84   2   4   6   1   8   6]
- [  3 129   6   2  16   2   4]
- [ 31  21 139  24  34  21  32]
- [  7   5  20 111   4   3   9]
- [  2   4   2   1  58   0   3]
- [  8   1   3   3   6  41   6]
- [ 14   5   8   4   7  11  79]]
-Node Classification on random seed  1405 -> 0.622
-Confusion Matrix:
- [[ 74   0   2  11   4   7   5]
- [  8 126   4   1  10   3   7]
- [ 14  22 137  28  47  28  40]
- [  6   6  14 108   9   9  11]
- [  0   8   3   1  59   3   2]
- [  1   0   8   0   5  43   8]
- [  1   1   9   5   7  20  75]]
-Node Classification on random seed  1406 -> 0.611
-Confusion Matrix:
- [[ 68   1   5  10   4   9  13]
- [  8 116   4   9   9   4   7]
- [  5  21 145  28  35  37  32]
- [  7   4   8  90  12  14  14]
- [  4   7   2   1  52   2   3]
- [  8   4   3   0   0  50   2]
- [  7   2  16   6   9  13  90]]
-Node Classification on random seed  1407 -> 0.644
-Confusion Matrix:
- [[ 83   0   4   6   5  13  11]
- [  1 136   3   1   3   1   7]
- [ 24  19 147  31  41  17  29]
- [ 13   6  12  90   5   1  17]
- [  1   4   1   2  68   1   6]
- [  6   0   3   2   3  39   7]
- [  6   4   6   7   6  21  81]]
-Node Classification on random seed  1408 -> 0.612
-Confusion Matrix:
- [[ 65   5   3   6   3   9  10]
- [  7 122   5   1   9   2   3]
- [ 15  30 153  29  42  15  40]
- [  7  12  30  90   2   8  10]
- [  2  10   7   5  58   2   0]
- [  3   0   0   1   0  37  16]
- [  5   8   9   5   4   8  87]]
-Node Classification on random seed  1409 -> 0.619
-Confusion Matrix:
- [[ 70   7  11   2   3   6   3]
- [  2 138  13   1   8   0   6]
- [ 18  31 128  41  40  24  23]
- [ 11   2  22 101   7   1   8]
- [  1   8   1   6  58   1   2]
- [ 13   4   2   0   2  37   2]
- [ 21   3   3   5   8   9  87]]
-Node Classification on random seed  1410 -> 0.559
-Confusion Matrix:
- [[ 74   7  16   4   3   7   3]
- [  7 119  17   0  10   4   4]
- [ 36  22 125  43  16  23  33]
- [ 18   4  46  69   8  12  10]
- [  0   8   5   0  63   1   1]
- [ 14   4   0   3   3  37   2]
- [ 12   6  10   4   0  15  72]]
-Node Classification on random seed  1411 -> 0.625
-Confusion Matrix:
- [[ 63   4  10   6   4  12  10]
- [  2 150   8   3   5   0   5]
- [ 15  28 163  44  17  19  45]
- [  7   4  27  88  10   7  10]
- [  2   6   4   2  57   0   3]
- [  2   2   7   0   2  36   5]
- [  7   1   8   3   4  15  68]]
-Node Classification on random seed  1412 -> 0.621
-Confusion Matrix:
- [[ 72   4   4   5   2   8  10]
- [  5 109  14   8  15   0   2]
- [ 29  13 153  44  27  11  42]
- [ 18   3  12  93  10   3   9]
- [  1   6   2   0  57   0   5]
- [  2   0   7   4   3  45   5]
- [  9   2  15   8   6   6  92]]
-Node Classification on random seed  1413 -> 0.601
-Confusion Matrix:
- [[ 72   4   3   4   8  12   7]
- [  9 116   4   0  19   3   2]
- [ 29  45 110  44  29  14  42]
- [  9  12   9 116   6   4  11]
- [  1   6   1   1  59   2   5]
- [  3   2   3   3   3  48   4]
- [  6   3   3   2  12  10  80]]
-Node Classification on random seed  1414 -> 0.588
-Confusion Matrix:
- [[ 49   3   0   4  15  12  22]
- [  0 130   7   4  10   3   6]
- [ 31  27 132  30  27  22  40]
- [  9   8  15  96   8   3  13]
- [  1   9   1   2  57   0   2]
- [  4   2   2   2   2  38  13]
- [ 10   6   4   5  18  10  86]]
-Node Classification on random seed  1415 -> 0.632
-Confusion Matrix:
- [[ 76   6   2   7   3   7   9]
- [  5 119   7   2   7   1   7]
- [ 19  27 163  35  23  16  42]
- [ 11   4  17 115   7   6   7]
- [  1   6   2   2  50   1   1]
- [ 11   2   3   4   0  39   3]
- [  8   6   9  16   3  13  70]]
-Node Classification on random seed  1416 -> 0.646
-Confusion Matrix:
- [[ 69   5   6   5   3   6   8]
- [  7 127  17   1   5   3   7]
- [ 28  21 134  37  11  24  40]
- [ 12   1   9 117   3   4  11]
- [  3   5   4   1  55   2   6]
- [  3   1   0   0   2  59   7]
- [  8   4  13   6   2  13  85]]
-Node Classification on random seed  1417 -> 0.625
-Confusion Matrix:
- [[ 55   2   4  11   4  15  15]
- [  4 138   5   5   8   2   6]
- [ 15  31 143  37  20  27  27]
- [ 11   4   7 110   7   7  14]
- [  0   5   5   2  58   2   5]
- [  2   2   0   2   3  49   6]
- [  7   0  12  13  12   9  72]]
-Node Classification on random seed  1418 -> 0.608
-Confusion Matrix:
- [[ 64   4   3   4   4  14  11]
- [  5 145   8   3   3   1   1]
- [ 28  45 125  18  23  27  50]
- [  6   7  18  85   4  14  17]
- [  1   3   2   0  55   2   1]
- [  2   0   3   4   4  47   2]
- [ 14  11  10   4   1  10  87]]
-Node Classification on random seed  1419 -> 0.619
-Confusion Matrix:
- [[ 81   3   8   1   0   6   5]
- [  5 118  13   4  14   4  11]
- [ 32  17 135  23  29  24  41]
- [ 11   3  10 113   1   4  12]
- [  0  10   8   3  56   0   1]
- [  5   2   3   0   2  48   5]
- [ 16   6   8  10   8  13  68]]
-Node Classification on random seed  1420 -> 0.597
-Confusion Matrix:
- [[ 82   3   3   9   0   7   8]
- [  4 137   8   0   4   2   2]
- [ 18  29 132  37  28  45  29]
- [  7   1  20  86   5  18  22]
- [  2   7   4   5  52   0   2]
- [  9   3   4   0   5  38   9]
- [  4   2   6  10  17   5  70]]
-Node Classification on random seed  1421 -> 0.605
-Confusion Matrix:
- [[ 61   1   4  13   7  18  10]
- [  2 144   1   1   9   0   6]
- [ 16  25 145  35  21  18  44]
- [  4   8  15  89   4  13  19]
- [  1  11   4   3  56   1   3]
- [  3   2   2   2   4  40   9]
- [ 15   3   2  20   5  11  70]]
-Node Classification on random seed  1422 -> 0.608
-Confusion Matrix:
- [[ 67   4   8   3   3  10   8]
- [  4 129   1   4  19   0   6]
- [ 20  25 152  23  23  30  38]
- [  8   8  18  83  14   8  15]
- [  0   5   5   2  65   2   2]
- [  9   1   0   1   1  34   5]
- [ 14   3   6   6   3  27  78]]
-Node Classification on random seed  1423 -> 0.595
-Confusion Matrix:
- [[ 62   0   3   5   7   6  10]
- [  3 122   5   3  13   2   4]
- [ 34  20 142  46  32  17  29]
- [ 18  14  20  94   3   6  15]
- [  0   8   3   1  63   3   1]
- [ 11   1   2   1   1  41   3]
- [ 15   3  13   1  13  10  71]]
-Node Classification on random seed  1424 -> 0.619
-Confusion Matrix:
- [[ 69   2   0   9   1  11  22]
- [  8 128   7   4  14   4   3]
- [ 19  15 138  29  27  27  30]
- [ 14   1  17 106   1   4  12]
- [  1   6   6   1  59   1   2]
- [  8   0   3   0   2  39  10]
- [ 25   2  21   3   3   6  80]]
-Node Classification on random seed  1425 -> 0.618
-Confusion Matrix:
- [[ 56   3  11  11   3  10  15]
- [  8 131   3   6   5   4   4]
- [ 30  22 141  30  21  16  42]
- [ 11   5  19 108   2   6   9]
- [  1  10   4   0  47   1   3]
- [  1   2   4   1   5  48   5]
- [ 12   2   7   2   6  20  87]]
-Node Classification on random seed  1426 -> 0.591
-Confusion Matrix:
- [[ 68   2   4  10  10  15   8]
- [  7 118   3   2   9   4   6]
- [ 27  22 130  51  25  20  39]
- [ 13   1  17 114   3  11  16]
- [  3   5   7   1  62   2   2]
- [  5   0   0   1   0  39   4]
- [ 11   3   7  14  10   9  60]]
-Node Classification on random seed  1427 -> 0.593
-Confusion Matrix:
- [[ 63   1   5   4   2   6  15]
- [ 11 118  20   0   4   5   3]
- [ 29  27 132  52  14  18  38]
- [  7   2  12 100   4   6  21]
- [  5  10   5   3  55   0   0]
- [  3   3   4   0   1  45   6]
- [  6   3  13   6  16  17  80]]
-Node Classification on random seed  1428 -> 0.598
-Confusion Matrix:
- [[ 59   3   1   6   1   5  22]
- [  5 122  15   0   8   7   4]
- [ 23  39 125  34  31  19  35]
- [ 13   9  10  91   2   4  13]
- [  1  10  10   3  52   0   2]
- [  2   1   3   1   0  46  14]
- [ 13   3   9   5   5  11 103]]
-Node Classification on random seed  1429 -> 0.622
-Confusion Matrix:
- [[ 73   3   5   2   5  23  12]
- [  5 127   2   1  16   2   4]
- [ 35  18 143  52  25   6  35]
- [  4   5  20 104   5   7   8]
- [  2   9   2   1  53   1   2]
- [  6   3   1   0   0  51   3]
- [  7   5   5   7   6  18  71]]
-Node Classification on random seed  1430 -> 0.58
-Confusion Matrix:
- [[ 70   3   3   5   1  12  15]
- [  6 132   4   4   9   2   3]
- [ 33  20 115  28  59  33  33]
- [  5   4  13  75  17   2  20]
- [  4   4   6   2  64   3   2]
- [ 11   1   0   0   0  48   4]
- [ 11   2   7   3   9  17  76]]
-Node Classification on random seed  1431 -> 0.649
-Confusion Matrix:
- [[ 68   3   2   1   1  10  18]
- [  4 129   2   6   6   1   3]
- [ 16  20 165  30  20  14  38]
- [ 16   2  21  85   6   7  11]
- [  1   7   6   4  66   0   3]
- [  9   0   3   1   0  41  13]
- [ 16   1   7   3  12   7  95]]
-Node Classification on random seed  1432 -> 0.608
-Confusion Matrix:
- [[ 65   1   2   6   1  11  17]
- [  6 122   1   4  13   3   2]
- [ 32  21 155  23  39  15  36]
- [ 11   2  22  86   4   8  26]
- [  4   4   8   1  54   3   4]
- [  1   1   2   6   0  44   4]
- [  9   7   9   0  13  10  82]]
-Node Classification on random seed  1433 -> 0.617
-Confusion Matrix:
- [[ 76   1   5  11   4   2  12]
- [  2 128   2   2  22   1   7]
- [ 33  19 144  21  35   8  32]
- [  9   5  14  89   9   5  16]
- [  3   5   3   0  58   0   4]
- [ 10   0   3   0   2  54   7]
- [ 18   1  15   7  14  14  68]]
-Node Classification on random seed  1434 -> 0.635
-Confusion Matrix:
- [[ 68   1   1   3   5   9  10]
- [  4 130   6   0   5   4   2]
- [ 20  23 159  37  23  17  31]
- [ 22   9  13  82   5   8  12]
- [  4  11   1   3  59   0   2]
- [  4   1   4   4   0  51   7]
- [ 15   5   8   7   2  17  86]]
-Node Classification on random seed  1435 -> 0.617
-Confusion Matrix:
- [[ 61   2   9   5   3   6  14]
- [  4 126   2   4   5   0   8]
- [ 30  21 132  56  18  16  43]
- [  8   3  17 112   3   2  20]
- [  3  15   3   0  59   0   2]
- [  2   2   3   3   1  42  12]
- [  9   1   4   7  12   5  85]]
-Node Classification on random seed  1436 -> 0.606
-Confusion Matrix:
- [[ 73   3   0   7   3  12   4]
- [  3 119   6   2   9   6   4]
- [ 34  19 137  38  27  24  47]
- [ 16  11  17  98   2   4  12]
- [  2   3   4   1  64   0   0]
- [  2   2   3   4   0  54   4]
- [ 15   1  17   8   4  14  61]]
-Node Classification on random seed  1437 -> 0.621
-Confusion Matrix:
- [[ 77   1   6   4   6  11   5]
- [  9 112  20   1   3   5   1]
- [ 31  23 142  36  21  17  33]
- [  3   3  20 120   2   5  13]
- [  5   6  10   2  53   1   5]
- [  7   5   0   0   0  50   3]
- [ 18   2  11   3  11  11  67]]
-Node Classification on random seed  1438 -> 0.639
-Confusion Matrix:
- [[ 72   0   1   7   2  14   6]
- [  4 125   2   3  12   7   6]
- [ 21  43 148  33  27   7  31]
- [  9   5  12 107   2   3  10]
- [  3   6   2   0  71   0   3]
- [  4   2   6   4   0  42   1]
- [ 29   4  10   1   7  12  74]]
-Node Classification on random seed  1439 -> 0.585
-Confusion Matrix:
- [[ 74   2   8   2   2  12  10]
- [  7 110   3   6  10   3   5]
- [ 21  15 148  52  27  29  25]
- [ 21   2  22  90  10  12  13]
- [  0   5   5   2  56   0   1]
- [  7   0   7   1   1  41   3]
- [ 24   0   7   6   5  22  66]]
-Node Classification on random seed  1440 -> 0.622
-Confusion Matrix:
- [[ 63   1   1   7   2   4  18]
- [  6 119  16   4   2   2   3]
- [ 29  27 130  29  17  30  37]
- [ 11   1  15 131   2   6   9]
- [  1   5   8   1  58   2   1]
- [  5   0   3   5   0  38  12]
- [  9   5  10   8   6  18  83]]
-Node Classification on random seed  1441 -> 0.611
-Confusion Matrix:
- [[ 59   2   3   7   5   7  12]
- [  5 124   5   3   5   7   1]
- [ 54  35 132  31  10  21  37]
- [ 11   3  11 119   2   5  11]
- [  1   8  11   3  63   3   3]
- [ 10   1   2   0   0  44   9]
- [ 15   7   5   5   6   7  70]]
-Node Classification on random seed  1442 -> 0.648
-Confusion Matrix:
- [[ 65   3   4   1   7   8  17]
- [  7 130   4   2   9   3   5]
- [ 17   5 167  28  39  21  30]
- [  8   2  13  97   4   9  29]
- [  3   4   5   2  56   1   1]
- [  7   0   4   0   1  38   8]
- [ 12   2   8   1   6  12  95]]
-Node Classification on random seed  1443 -> 0.625
-Confusion Matrix:
- [[ 53   3  11   4   3   4  20]
- [  2 119   3   0  18   2  10]
- [ 18  16 165  17  44   7  35]
- [ 12   3  15 114   5   6  24]
- [  3   2   5   2  66   1   2]
- [  7   1   2   0   1  36   7]
- [ 25   5   5   8   5  12  72]]
-Node Classification on random seed  1444 -> 0.628
-Confusion Matrix:
- [[ 82   1   6   3   7   7   5]
- [  3 124   9   2   4   1   2]
- [ 17  18 153  39  19  28  35]
- [  7   3  28  93   5   7  16]
- [  1  12   6   2  64   0   1]
- [ 10   2   2   5   0  41   3]
- [  8   2  13  11   6  16  71]]
-Node Classification on random seed  1445 -> 0.595
-Confusion Matrix:
- [[ 86   4  10   4   2   4  12]
- [  2 124   6   4   9   3   6]
- [ 41  18 118  38  27  25  37]
- [ 20   4  23  92   4   3  14]
- [  1   5   4   3  54   0   2]
- [  5   3   2   2   2  42   8]
- [ 13   3   5   4   7  16  79]]
-Node Classification on random seed  1446 -> 0.594
-Confusion Matrix:
- [[ 69   2   6   3   3  13  13]
- [  3 124   8   2  11   0   6]
- [ 55  24 115  43  24  27  33]
- [ 10   5  14  94   0   5  14]
- [  1   6   2   2  55   2   3]
- [  2   1   0   1   2  54   4]
- [  8   2   9   8   6  23  83]]
-Node Classification on random seed  1447 -> 0.624
-Confusion Matrix:
- [[ 65   0  10   4   1  15  17]
- [  3 137   3   3   2   7   4]
- [ 22  24 159  38  21  14  44]
- [ 14   7  16  87  11   4   7]
- [  1  10   4   4  41   2   2]
- [  4   2   4   0   0  47   4]
- [  4   5   7  20   0  12  88]]
-Node Classification on random seed  1448 -> 0.573
-Confusion Matrix:
- [[ 68   1   3   6   4  15  12]
- [  6 113   5   4  20   3   1]
- [ 20  18 148  31  23  27  41]
- [ 27   1  16  78   6   7  23]
- [  1   3   7   1  58   2   0]
- [  2   1   1   8   3  42   9]
- [ 10   5   7   7  23  17  66]]
-Node Classification on random seed  1449 -> 0.594
-Confusion Matrix:
- [[ 49   2   5  12   6  19  17]
- [ 10 108   6   3   5   3  10]
- [ 20  26 124  50  30  14  42]
- [ 14   5  13 118   8   3   6]
- [  0   5   6   0  72   2   5]
- [  5   2   1   5   0  51   2]
- [  2   3   6   8   8  17  72]]
-Node Classification on random seed  1450 -> 0.588
-Confusion Matrix:
- [[ 81   5   1   6  11  15   1]
- [  2 113   8   5   7   8   0]
- [ 19  17 123  24  65  17  40]
- [ 16   4  14  92  15   5  17]
- [  2   7   2   1  56   1   1]
- [  8   4   4   1   0  47  11]
- [  9   5   9   9   2  14  76]]
-Node Classification on random seed  1451 -> 0.579
-Confusion Matrix:
- [[ 74   0   7   5   1  10   8]
- [  4 117  15   2   8   2   7]
- [ 18  25 107  46  74  39  31]
- [  1   0  12  96  11   6  20]
- [  1   4   3   0  64   0   4]
- [  6   0   1   0   1  38   3]
- [ 11   1  11   5   5  13  83]]
-Node Classification on random seed  1452 -> 0.609
-Confusion Matrix:
- [[ 57   1   3   1   2  18  19]
- [  2 147   5   3   7   3   3]
- [ 27  25 152  36  21  18  37]
- [ 14   8  21  69   5   1  28]
- [  6   9   4   3  63   1   2]
- [  5   4   1   1   0  46   8]
- [ 10   3   6   4   3  13  75]]
-Node Classification on random seed  1453 -> 0.604
-Confusion Matrix:
- [[ 64   2   5  10   0  14  10]
- [  5 133   4   0   5   0   0]
- [ 28  20 149  24  29  29  38]
- [ 12   3  25  97  12  11   7]
- [  2  10   8   1  51   2   3]
- [  7   4   2   1   5  39   3]
- [ 16   5   8   9   7  10  71]]
-Node Classification on random seed  1454 -> 0.6
-Confusion Matrix:
- [[ 67   1   7  10   3   6   7]
- [  3 126   8   4   3   8   4]
- [ 46  21 131  15  27  22  58]
- [ 10   4  17 100   5   7  13]
- [  2   4   9   2  47   1   7]
- [  7   1   0   5   2  39   2]
- [ 15   3   7   6   7  11  90]]
-Node Classification on random seed  1455 -> 0.629
-Confusion Matrix:
- [[ 60   4   5   3   6   8  15]
- [  4 126   8   3   5   3   2]
- [ 12  14 139  32  36  15  54]
- [ 13   3  16 118   1   5  17]
- [  1   6   5   2  71   0   1]
- [  4   1   6   0   1  41   4]
- [  9   4  12   5  11  15  74]]
-Node Classification on random seed  1456 -> 0.634
-Confusion Matrix:
- [[ 74   6   4   6   2  14   7]
- [  3 143   5   1   4   2   4]
- [ 17  26 134  52  30  13  33]
- [ 12   4  18 104   7   4  12]
- [  0   4   4   2  68   0   4]
- [  4   1   1   2   0  34  12]
- [ 14   6   5   8   8   5  77]]
-Node Classification on random seed  1457 -> 0.614
-Confusion Matrix:
- [[ 76   3   1   3   4   9   9]
- [  4 150   7   1   3   4   7]
- [ 41  13 135  33  32  19  36]
- [ 13   5  21 108   6   6  19]
- [  1   7   0   0  40   4   4]
- [  6   1   3   1   2  38   9]
- [  7   5   9   6  13   9  67]]
-Node Classification on random seed  1458 -> 0.605
-Confusion Matrix:
- [[ 78  10   2   7   3   4   2]
- [  4 133   5  11   8   0   0]
- [ 23  33 132  48  23  11  49]
- [ 21   1  11  96   6   3  16]
- [  1   7   7   0  62   0   2]
- [ 10   1   4   2   0  44   2]
- [ 22   0  13  15   3   5  60]]
-Node Classification on random seed  1459 -> 0.584
-Confusion Matrix:
- [[ 64   4   5   8   5  14   6]
- [  2 141   5   2   4   2  11]
- [ 24  19 134  27  16  35  49]
- [  9   3  30  92   6   6  17]
- [  3   9   7   0  53   2   2]
- [  5   2   0   0   1  37  12]
- [ 15   4  16   0  14  15  63]]
-Node Classification on random seed  1460 -> 0.627
-Confusion Matrix:
- [[ 56   2   8   7   2  10  16]
- [  8 140   2   2   7   5   9]
- [ 31  26 119  40   9  17  51]
- [  8   5   3 134   5   1   9]
- [  3  10   4   2  58   1   6]
- [  5   3   5   6   0  47   5]
- [  4   4   9   8   2  13  73]]
-Node Classification on random seed  1461 -> 0.595
-Confusion Matrix:
- [[ 72   2   6   7   7  10  10]
- [  4 117   8   4   7   0   1]
- [ 27  18 145  26  61  16  29]
- [  5   0  19  81   4   8  24]
- [  0   7   4   2  61   0   2]
- [  2   2   8   0   2  50   4]
- [  8   3  12   5  26  15  69]]
-Node Classification on random seed  1462 -> 0.609
-Confusion Matrix:
- [[ 80   5  10   1   5  22   7]
- [  2 132   7   3   2   0   3]
- [ 28  32 134  58  16  19  29]
- [ 12   7  12 109   8   3   5]
- [  0  12   2   1  58   1   1]
- [  7   1   2   4   2  41   2]
- [ 12   7  14   4   5  18  55]]
-Node Classification on random seed  1463 -> 0.626
-Confusion Matrix:
- [[ 84   3   0   3   9   7  12]
- [  6 113   5   1   3   7  12]
- [ 19  25 153  31  18  35  41]
- [  8   6  25  89   1   4   8]
- [  1  11   5   0  57   2   1]
- [  1   0   5   3   1  44   7]
- [ 12   4   5   6  12   9  86]]
-Node Classification on random seed  1464 -> 0.619
-Confusion Matrix:
- [[ 77   0   4   3   5  11   9]
- [ 10 116   6   5   7   6   0]
- [ 35  22 146  27  30  28  17]
- [  6   1  13 101   7   7  13]
- [  2   9   3   3  60   1   1]
- [  7   3   2   9   5  44   6]
- [ 20   2  17   6   5   8  75]]
-Node Classification on random seed  1465 -> 0.648
-Confusion Matrix:
- [[ 69   7   1   2   2  17  28]
- [  5 130   2   2   4   3   4]
- [ 21  12 163  27  20  14  50]
- [  2   7  10 102   5   8   7]
- [  4   6   3   0  68   1   4]
- [  5   1   2   3   3  41   4]
- [ 13   3   9   5  11  15  75]]
-Node Classification on random seed  1466 -> 0.58
-Confusion Matrix:
- [[ 63   3   9   3   2   7  18]
- [  1 124  10   7  16   4   3]
- [ 25  24 128  46  17  24  47]
- [ 18   6  14  86   6   6  10]
- [  1   3   7   0  64   3   1]
- [  9   3   0   0   2  34  11]
- [ 16   4   6   3  10  15  81]]
-Node Classification on random seed  1467 -> 0.64
-Confusion Matrix:
- [[ 71   1   4   4   5   8   9]
- [  6 123   8   0  15   0   5]
- [ 20  20 150  33  24  20  49]
- [  8   3   4 115   6   2  12]
- [  1   7   7   1  59   0   2]
- [  9   2   3   0   1  36  13]
- [ 13   3   6   8  11   7  86]]
-Node Classification on random seed  1468 -> 0.643
-Confusion Matrix:
- [[ 69   3   6   7   2  11  11]
- [  2 138   2   6   7   1   1]
- [ 18  24 157  21  36  12  34]
- [ 10   3  21 107   3   5  17]
- [  1   5   5   2  59   2   3]
- [  9   1   1   8   1  31   7]
- [ 15   5  12   2   5  10  82]]
-Node Classification on random seed  1469 -> 0.619
-Confusion Matrix:
- [[ 87   3   0   5   2  14  15]
- [  8 123  13   0   7   7   1]
- [ 24  28 140  30  25  19  32]
- [ 16   3  18  98   5   6  15]
- [  1  11   2   1  62   1   3]
- [  6   1   7   1   1  35   2]
- [ 15   4   9   2   5  13  74]]
-Node Classification on random seed  1470 -> 0.6
-Confusion Matrix:
- [[ 69   1  11   8   3   8  13]
- [  1 131   4   3   8   3   3]
- [ 24  23 132  35  36  17  32]
- [  5   4  35  83   9   3  21]
- [  0  15   4   1  62   1   3]
- [  3   0   2   1   1  43   8]
- [  4   4  18  11   2  12  80]]
-Node Classification on random seed  1471 -> 0.572
-Confusion Matrix:
- [[ 74   0  10   4   8   9  10]
- [  3 121   5   1   9   4   6]
- [ 22  35 127  54  23  19  41]
- [  9   3  34  93   6   4   6]
- [  1  10   4   1  56   2   5]
- [ 11   1   8   1   2  35   2]
- [ 12   4  14  10   5  10  66]]
-Node Classification on random seed  1472 -> 0.619
-Confusion Matrix:
- [[ 63   3   5  11   3  16   2]
- [  4 125   3   3   7   1  11]
- [ 23  21 164  40  23  17  32]
- [  0   4  25  93  21   3  19]
- [  0   2   5   2  62   0   1]
- [  3   2   1   1   0  40   7]
- [ 10   1   4  21   9  15  72]]
-Node Classification on random seed  1473 -> 0.653
-Confusion Matrix:
- [[ 86   2   4   1   0  13   2]
- [  3 132   8   3   9   0   0]
- [ 36  17 129  18  22  19  42]
- [ 13   1  13 115   5   4   8]
- [  2   8   2   1  66   1   3]
- [  6   3   0   2   2  45   8]
- [ 23   2   8   7   5  21  80]]
-Node Classification on random seed  1474 -> 0.617
-Confusion Matrix:
- [[ 64   3   2  14   3  10  11]
- [  4 118   5   0  20   3   1]
- [ 25  21 150  29  18  14  52]
- [ 21   3  13 111   6   5   5]
- [  2   3  12   4  57   0   0]
- [  8   2   1   2   1  47  12]
- [ 11   2   4   9   8  14  70]]
-Node Classification on random seed  1475 -> 0.619
-Confusion Matrix:
- [[ 78   2  13   4   5   4  11]
- [  4 118   4   2   0   5   9]
- [ 23  18 163  30  28  32  25]
- [  9   1  14  99   6   4  14]
- [  4   5   6   5  59   2   1]
- [ 10   0   3   2   1  41  12]
- [  8   2  11  14   7  21  61]]
-Node Classification on random seed  1476 -> 0.594
-Confusion Matrix:
- [[ 58   2   8   9   5  11  20]
- [ 14 130   3   4   7   2   4]
- [ 24  23 100  47  33  40  35]
- [  5   2  13 113   5   6  18]
- [  1   6   2   4  77   0   0]
- [  3   2   1   1   0  47   2]
- [ 15   1   6   5   5  12  69]]
-Node Classification on random seed  1477 -> 0.608
-Confusion Matrix:
- [[ 57   4   2   5   6   8  18]
- [  3 125   5   5   6   3   3]
- [ 25  20 133  53  28  18  32]
- [ 12   8  20 101   5   5  11]
- [  0   7   3   0  68   4   5]
- [  3   3   1   6   1  34   9]
- [ 15   3   4   1   5  17  90]]
-Node Classification on random seed  1478 -> 0.617
-Confusion Matrix:
- [[ 67  11   5  11   2   6   4]
- [  0 138   9   6   5   2   4]
- [ 15  31 143  25  29  19  45]
- [  5   7  27  79   2  10  22]
- [  1   2   2   5  63   1   3]
- [  3   2   3   2   0  49   6]
- [ 12   2   7   3   7  20  78]]
-Node Classification on random seed  1479 -> 0.613
-Confusion Matrix:
- [[ 68   2   1   9   3  10  11]
- [  1 149   6   2   6   8   2]
- [ 27  43 107  49  21  29  23]
- [  9   2  15 118   5   7   5]
- [  0   9   7   0  52   1   5]
- [  7   4   3   1   1  38   2]
- [  8   3   6  10   5  19  81]]
-Node Classification on random seed  1480 -> 0.595
-Confusion Matrix:
- [[ 72   2   2   4   3  13  12]
- [  7 128   6   2   6   5   6]
- [ 31  17 125  29  37  22  55]
- [  8   1  15  94   5   8  26]
- [  0   8   3   2  63   1   3]
- [  5   0   4   0   0  50   4]
- [  8   2   6  10   9  18  63]]
-Node Classification on random seed  1481 -> 0.561
-Confusion Matrix:
- [[ 70   0   8   7   6   9   1]
- [  1 126   8   4   6   2   1]
- [ 14  39 104  47  42  45  31]
- [ 14   3   6  90  18   8  10]
- [  4   3   3   6  58   2   5]
- [  7   2   1   1   1  48   1]
- [ 24   3  17   6   8  15  65]]
-Node Classification on random seed  1482 -> 0.619
-Confusion Matrix:
- [[ 63   1   2   5   3  15  10]
- [  1 138   5   1   7   3   4]
- [ 30  25 140  22  34  28  50]
- [ 10   6  17  98   2   7   5]
- [  3   5   1   1  70   0   2]
- [  5   1   0   3   1  44   4]
- [  6   3   4   9  17  23  66]]
-Node Classification on random seed  1483 -> 0.621
-Confusion Matrix:
- [[ 74   2   5   2   4  17   5]
- [  1 126   6   9   3   3   3]
- [ 13  33 147  34  47  14  22]
- [ 15   8  17  84   6  12  14]
- [  2   8   3   4  52   1   4]
- [  3   3   3   1   2  48   2]
- [  8   2   7  11   5  15  90]]
-Node Classification on random seed  1484 -> 0.596
-Confusion Matrix:
- [[ 72   1   8   4   3   7   4]
- [  5 122   3   0   7   3   4]
- [ 34  26 130  32  26  26  42]
- [  6   5  13 112   6   7  16]
- [  0   9   3   3  62   4   0]
- [  5   2   3   0   1  42   1]
- [  9  11  25  15   1  24  56]]
-Node Classification on random seed  1485 -> 0.601
-Confusion Matrix:
- [[ 69   4   5   7   7  13   5]
- [  7 128   9   1   3   6  17]
- [ 21  15 156  34  29  21  27]
- [ 18   4  21 101   4   5  10]
- [  0   4   5   1  51   0   2]
- [ 14   1   4   4   1  33   5]
- [ 15   6   5  19  10  10  63]]
-Node Classification on random seed  1486 -> 0.635
-Confusion Matrix:
- [[ 77   1   0   9   4  10  17]
- [  2 126   7   1   6   7   6]
- [ 15   9 156  36  22  17  45]
- [  8   0  12 111   8   8  19]
- [  0   8   7   0  61   0   1]
- [  3   2   5   5   1  35   8]
- [ 11   9   5   8  11  12  69]]
-Node Classification on random seed  1487 -> 0.608
-Confusion Matrix:
- [[ 60   3   4  14   2  11   6]
- [  5 127   2   1   6   1   4]
- [ 20  40 128  23  28  19  52]
- [ 12   5  13 106   6   5  11]
- [  0  15   1   0  61   0   2]
- [ 10   2   1   7   1  43   6]
- [ 13   4   4  15   8  10  83]]
-Node Classification on random seed  1488 -> 0.614
-Confusion Matrix:
- [[ 69  11   8   6   5   8   2]
- [  6 131   7   1  11   4   0]
- [ 11  30 122  47  29  23  42]
- [ 13   3  14 109   1   4   8]
- [  2  11   3   6  60   0   0]
- [ 10   3   0   1   0  42   6]
- [ 17   5   6   3   6  13  81]]
-Node Classification on random seed  1489 -> 0.6
-Confusion Matrix:
- [[ 69   1   0  10   3  20   5]
- [  5 117   2   4  19   5   5]
- [ 20  23 137  31  41  28  31]
- [  7   8  10 104   7   7   7]
- [  3   3   5   5  57   0   3]
- [  4   1   3   4   3  41   1]
- [ 20   7   4  16   6  13  75]]
-Node Classification on random seed  1490 -> 0.617
-Confusion Matrix:
- [[ 55   0   2  11  17  13   6]
- [  4 138   2   1   5   1   4]
- [ 23  21 154  24  31  24  30]
- [ 19   6  10  90  15  16   5]
- [  1   8   3   1  62   0   2]
- [  8   3   2   2   0  42   3]
- [ 19   5  10   6   4  16  76]]
-Node Classification on random seed  1491 -> 0.623
-Confusion Matrix:
- [[ 77   3   3   4   7   9  14]
- [  9 108   8   2   8   2  10]
- [ 22  31 152  36  20  21  31]
- [ 12   1  14 117   6   5   9]
- [  1  11   1   4  53   0   3]
- [  9   1   2   2   3  40   1]
- [ 10   6  10   1   7  18  76]]
-Node Classification on random seed  1492 -> 0.63
-Confusion Matrix:
- [[ 67   4   4   9   7   5  12]
- [  7 137   4   8   8   1   0]
- [ 20  18 142  57  27  12  32]
- [  5   4  15  96  13   3  19]
- [  2   4   4   2  64   0   1]
- [  5   2   2   1   1  46   3]
- [ 13   6   8   1   7  14  78]]
-Node Classification on random seed  1493 -> 0.57
-Confusion Matrix:
- [[ 64   2   6   2   6  16  11]
- [  6 116   6   4   1   1   1]
- [ 25  43 111  43  16  32  46]
- [ 15   4  15 100  11   9  17]
- [  0   7   5   1  53   2   5]
- [  3   5   4   2   0  45   7]
- [ 13   5  11   5   3  14  81]]
-Node Classification on random seed  1494 -> 0.605
-Confusion Matrix:
- [[ 84   1   6   6   7   9   3]
- [  3 128   7   4   4   3   2]
- [ 30  12 146  41  48   3  37]
- [ 20   6  15  89   8   4   5]
- [  1  10   3   4  46   0   2]
- [  7   4   1   3   3  46   4]
- [ 23   6  11   8   9  12  66]]
-Node Classification on random seed  1495 -> 0.632
-Confusion Matrix:
- [[ 71   4   4   8   6   4  10]
- [  4 129   8   1   7   1   2]
- [ 21  16 167  37  26  35  20]
- [ 21   4  11 102   5  15   8]
- [  1   7   3   0  61   1   0]
- [  6   2   3   2   7  34   6]
- [ 18   4   5   9   1  15  68]]
-Node Classification on random seed  1496 -> 0.612
-Confusion Matrix:
- [[ 64   1   6   7   3  13  10]
- [  5 125   7   4  14   1   2]
- [ 18  28 128  39  25  25  37]
- [  9   2  19 112  13   4   9]
- [  2   7   4   1  57   1   2]
- [  3   2   2   2   1  47   2]
- [  6   8  14   4   3  23  79]]
-Node Classification on random seed  1497 -> 0.621
-Confusion Matrix:
- [[ 71   2   0   4   6   9   9]
- [  4 130  13   2   3   4   3]
- [ 11  19 159  30  27  21  58]
- [ 18   5  14  94  16   3   9]
- [  1  11   3   0  58   2   6]
- [  8   2   3   2   1  45   6]
- [  9   3   5   7   5  15  64]]
-Node Classification on random seed  1498 -> 0.638
-Confusion Matrix:
- [[ 75   1   3   4   4  14  11]
- [  2 119   8   2   8   2   5]
- [ 21  18 163  40  24  11  35]
- [  4   2  20 112   3  11  13]
- [  0   7   2   3  54   2   1]
- [  9   1   6   1   0  36  10]
- [ 17   3  11   4   8  11  79]]
-Node Classification on random seed  1499 -> 0.619
-Confusion Matrix:
- [[ 79   0   9   6   2   7   7]
- [  8 126   8   6   8   0   6]
- [ 17   7 159  53  19  17  42]
- [ 11   6  15  93   2   6  19]
- [  3   9   8   1  52   4   1]
- [  5   3   1   2   0  40   6]
- [ 10   3  17   5  11  11  70]]
-Node Classification on random seed  1500 -> 0.615
-Confusion Matrix:
- [[ 64   2   1   4  10   8  11]
- [  7 124   8   7   7   3   0]
- [ 22  27 134  33  26  23  46]
- [  4   3  24  98   6   4  15]
- [  2   7   3   0  64   1   6]
- [  1   2   2   7   0  49   4]
- [ 16   4   4   4  10  11  82]]
-Node Classification on random seed  1501 -> 0.599
-Confusion Matrix:
- [[ 83   1   7   4   1   4  13]
- [  4 126   5   4  11  10   2]
- [ 33  20 120  23  42  24  42]
- [  6   2  16  77  16   6  10]
- [  1   3   5   3  78   0   6]
- [  6   0   4   0   1  49   2]
- [ 20   5   5  12  11  11  66]]
-Node Classification on random seed  1502 -> 0.575
-Confusion Matrix:
- [[ 43   6  10  10   4  17  12]
- [  5 134  11   0  12   2   0]
- [ 21  16 141  42  19  28  34]
- [ 21   5  21 101   3  16   8]
- [  1   5   6   9  51   1   0]
- [  4   0   3   1   3  46   5]
- [ 11   1  14   6   7  25  59]]
-Node Classification on random seed  1503 -> 0.634
-Confusion Matrix:
- [[ 81   1   1   8   3   7  12]
- [  3 121   6   3  13   9   2]
- [ 19  14 152  48  19  21  31]
- [  8   4  17 107   7   5  13]
- [  1   8   4   5  67   0   0]
- [ 10   0   2   3   2  45   7]
- [ 10   5   8   8   5  14  61]]
-Node Classification on random seed  1504 -> 0.631
-Confusion Matrix:
- [[ 76   2   7   5   1  12  15]
- [  6 134   6   1   3   1   8]
- [ 16  22 174  15  20  26  45]
- [ 14   4  35  77   8   5  11]
- [  6   8   1   1  49   1   3]
- [  6   0   4   0   0  40   4]
- [ 12   3   8   1   7  16  81]]
-Node Classification on random seed  1505 -> 0.603
-Confusion Matrix:
- [[ 82   2   1   5   4   5   7]
- [  1 129  12   2  12   2   4]
- [ 27  20 139  38  18  18  42]
- [ 12   6  19  99   7   4  16]
- [  3   8   2   1  56   1   4]
- [ 10   1   1   0   2  39   7]
- [ 16   6  20   3  18  10  59]]
-Node Classification on random seed  1506 -> 0.614
-Confusion Matrix:
- [[ 79   3   3   1   3  18   3]
- [ 13 123   3   3   6   3   1]
- [ 24  20 133  36  22  24  46]
- [ 13   1  10 101  12  10  14]
- [  6   4   3   2  58   0   4]
- [  4   0   2   3   1  57   1]
- [ 18   6  10   3   9  18  63]]
-Node Classification on random seed  1507 -> 0.631
-Confusion Matrix:
- [[ 75   0   3   5   3  12   6]
- [  6 121   5   2  15   2   2]
- [ 18  19 152  44  23  15  33]
- [  7  10  23 105   3   7  12]
- [  0  11   3   1  52   0   5]
- [  6   2   3   3   3  40   6]
- [  5   1  16   3   3  23  86]]
-Node Classification on random seed  1508 -> 0.607
-Confusion Matrix:
- [[ 61   1   3   6   1  14  15]
- [  4 121   4  12   7   0   6]
- [ 10  25 133  38  45  18  37]
- [  7   3   7 119   6  10  11]
- [  0   6   8   2  62   1   4]
- [  5   4   0   3   5  42  13]
- [  5   2   8  11   5  21  69]]
-Node Classification on random seed  1509 -> 0.659
-Confusion Matrix:
- [[ 85   5   1   4   3   5   9]
- [  4 142   2   1   4   2   8]
- [ 19  15 145  20  30  37  27]
- [  6   7  13 124   2   3  13]
- [  1  12   8   1  54   2   3]
- [  6   2   1   4   2  46   7]
- [  8   6   9   8   7  14  63]]
-Node Classification on random seed  1510 -> 0.626
-Confusion Matrix:
- [[ 79   2   8   2   2   5   7]
- [  7 136   3   2   3   4   1]
- [ 26  17 130  34  29  28  32]
- [  6   4  24  84   6   6  14]
- [  1  11   3   1  61   1   3]
- [ 12   1   8   1   0  40   5]
- [ 15   3  14   4   5  14  96]]
-Node Classification on random seed  1511 -> 0.599
-Confusion Matrix:
- [[ 69   4   2   4   4  17   6]
- [  3 119   2   6   8   4   5]
- [ 26  23 117  44  35  19  57]
- [  4   0  15  94   6   4  21]
- [  4   7   2   0  63   1   3]
- [  8   0   0   3   7  46   1]
- [ 14   3   6   4   4  15  91]]
-Node Classification on random seed  1512 -> 0.637
-Confusion Matrix:
- [[ 82   8   0   1   6   9   5]
- [ 10 140   1   1   3   1   4]
- [ 18  24 148  37  22  22  40]
- [ 15   9  16  99   2   9  13]
- [  4   9   4   2  47   0   1]
- [  5   2   1   0   0  45   9]
- [ 15   2  13   2   3  15  76]]
-Node Classification on random seed  1513 -> 0.628
-Confusion Matrix:
- [[ 73   3   4   1   3  18  11]
- [  3 125   6   0   8   3  10]
- [ 22  28 143  28  35  15  32]
- [ 15   1  25 108   5   3   7]
- [  2   8   7   2  59   0   2]
- [  0   1   4   1   3  44   6]
- [  6   4   5   8   6  21  76]]
-Node Classification on random seed  1514 -> 0.626
-Confusion Matrix:
- [[ 78   1   6   9   4  11  11]
- [  5 142   9   1   8   0   3]
- [ 16  20 139  36  28  17  37]
- [ 11   4  19 109   3  11   5]
- [  2   7   5   2  63   2   1]
- [ 10   1   2   2   2  41   3]
- [ 13   2   6   5  13  21  54]]
-Node Classification on random seed  1515 -> 0.62
-Confusion Matrix:
- [[ 75   0   1   5   8   3   9]
- [  7 100  10   0   5   1   2]
- [ 30  13 149  34  38  10  44]
- [ 24   2  11 123   8   4  14]
- [  0   3   3   2  62   2   1]
- [  9   3   3   1   4  32   7]
- [ 16   6  12   4  12   9  79]]
-Node Classification on random seed  1516 -> 0.619
-Confusion Matrix:
- [[ 49   2   6   3   7  16  11]
- [  7 126   6   3   9   3   1]
- [ 23  38 147  31  19  17  32]
- [ 20   7  11 104   9  13  14]
- [  1   8   3   3  51   1   4]
- [  2   1   1   3   1  47   5]
- [  8   4   6   3  10   9  95]]
-Node Classification on random seed  1517 -> 0.628
-Confusion Matrix:
- [[ 69   2   4   7   6  17   9]
- [  8 129   3   4  15   3   6]
- [ 33  16 159  31  27  10  31]
- [ 11   3  13 105   5   4  19]
- [  1   5   7   1  57   0   5]
- [  7   1   1   4   2  43   2]
- [ 15   7   6  11   5   5  66]]
-Node Classification on random seed  1518 -> 0.606
-Confusion Matrix:
- [[ 73   2   1   3   2  19   7]
- [  4 120  13   0   4  10   1]
- [ 25  20 139  32  24  34  37]
- [ 21   1  19  89   5   6  14]
- [  3  14   4   1  54   0   3]
- [  5   0   0   9   3  36   6]
- [ 17   3   3   4   4  11  95]]
-Node Classification on random seed  1519 -> 0.645
-Confusion Matrix:
- [[ 77   7   4   6   2  14  12]
- [  6 142  11   0   5   0   3]
- [ 20  41 138  33  18  18  33]
- [  5   3  23 103   1   4   9]
- [  2   6   3   1  58   2   1]
- [  4   1   1   0   2  55   6]
- [  9   3   8   4   6  18  72]]
-Node Classification on random seed  1520 -> 0.593
-Confusion Matrix:
- [[ 70   5   3  11   6  10   2]
- [  2 133   1   0  22   6   6]
- [ 18  22 118  40  36  23  40]
- [ 10   9  18  87  14   5  15]
- [  0   6   1   0  64   0   0]
- [  5   0   5   2   0  51   3]
- [ 12   2  14  11   6  16  70]]
-Node Classification on random seed  1521 -> 0.59
-Confusion Matrix:
- [[ 70   2   8   3   1   9  14]
- [  5 126   7   1   8   2   4]
- [ 17  19 128  48  37  26  27]
- [  9   8   9 102   5  16  17]
- [  0  14   0   5  54   3   3]
- [  3   4   0   4   1  51   5]
- [  8   4  12  17   6  19  59]]
-Node Classification on random seed  1522 -> 0.619
-Confusion Matrix:
- [[ 84   1   3   5   2  10  13]
- [  3 115   8   4   4   5   9]
- [ 24  36 136  40  17  15  30]
- [ 10   3  12 109   8  10  20]
- [  0   3   6   1  64   2   4]
- [  4   2   1   1   0  39  12]
- [  7   7  12   6   6  15  72]]
-Node Classification on random seed  1523 -> 0.613
-Confusion Matrix:
- [[ 78   1   8   9   5  13   2]
- [  9 127   5   1  10  11   4]
- [ 24  35 143  29  21  17  32]
- [ 10   3  17  92   6   5  11]
- [  3   5  10   1  58   2   0]
- [  4   2   5   3   1  53   3]
- [ 11   1   7  12   5  24  62]]
-Node Classification on random seed  1524 -> 0.568
-Confusion Matrix:
- [[ 71   0   2  10   5  23   5]
- [ 15  94   2   3  23   3   3]
- [ 26  29 135  37  16  35  32]
- [ 17   3  18  83  12   7  18]
- [  0   4   4   3  63   1   1]
- [  5   1   2   2   0  49   3]
- [ 13   3  13  11  10  12  73]]
-Node Classification on random seed  1525 -> 0.626
-Confusion Matrix:
- [[ 71   2   0   2   4   8  11]
- [  6 127   6   4   9   0   6]
- [ 33  23 151  38  28  20  37]
- [ 19  11  19  92   0   3  15]
- [  1   0   2   3  61   0   2]
- [  9   0   3   1   1  43  12]
- [  9   1  11   6   2   7  81]]
-Node Classification on random seed  1526 -> 0.596
-Confusion Matrix:
- [[ 71   2  10   4   4   7   2]
- [  3 110   2   9   5   5   4]
- [ 26  13 124  40  33  15  54]
- [ 18   3   9  99   9   4  24]
- [  3  10   1   1  73   0   4]
- [  5   3   1   0   2  49   9]
- [ 12   2   6  15   8  17  70]]
-Node Classification on random seed  1527 -> 0.641
-Confusion Matrix:
- [[ 81   1   5   7   3   5   5]
- [  6 129   6   2   9   8   4]
- [ 18  14 165  28  35  15  34]
- [ 17   4  14 103   9   8  10]
- [  3   6   1   3  58   1   1]
- [ 10   0   1   3   0  36   9]
- [ 10   2  11  13  10   8  69]]
-Node Classification on random seed  1528 -> 0.586
-Confusion Matrix:
- [[ 78   1   9   1   1  10  12]
- [  7 121   5   1   8   4   6]
- [ 30  17 119  54  27  31  47]
- [ 20   2  18  93   3   8   9]
- [  1   8   7   1  56   0   2]
- [  4   4   1   1   0  36   7]
- [ 15   6   2   4   8  12  83]]
-Node Classification on random seed  1529 -> 0.611
-Confusion Matrix:
- [[ 68   5   7   8   1  10   6]
- [  2 149   3   8   5   1   6]
- [ 20  21 135  48  11  34  35]
- [  8   2  30  85   5  11   4]
- [  2  11   2   0  58   2   1]
- [  2   1   4   8   3  40   8]
- [ 16   7   4  11   5  11  76]]
-Node Classification on random seed  1530 -> 0.62
-Confusion Matrix:
- [[ 65   4   8   3   4  12  11]
- [  4 135   4   4   4   6   3]
- [ 28  21 145  39  32  26  32]
- [  5   5  15  95   3  10   9]
- [  0   6   4   1  71   0   2]
- [  7   1   0   3   0  37   2]
- [  7   5   4  11  12  23  72]]
-Node Classification on random seed  1531 -> 0.624
-Confusion Matrix:
- [[ 78   0   1   2   8   7  16]
- [  3 122  10   1   8   2   6]
- [ 29  19 163  44  24  28  38]
- [  9   4  15  83   2   8  20]
- [  0   5   5   1  53   1   2]
- [  3   2   3   0   2  44   3]
- [  8   6  10   4   7  10  81]]
-Node Classification on random seed  1532 -> 0.58
-Confusion Matrix:
- [[ 68   0   2   6   5   4  33]
- [  5 109   4   1  14   3   9]
- [ 22  36 120  28  26  20  64]
- [ 11   3  11 107   2   4   6]
- [  0   3   2   0  66   0   7]
- [  3   0   1   0   5  45   9]
- [  9   4   5  20   9  24  65]]
-Node Classification on random seed  1533 -> 0.629
-Confusion Matrix:
- [[ 72   1   4   6   4  14  12]
- [ 10 120   4   2  11   3   1]
- [ 24   8 160  25  32  28  40]
- [ 18   1  15 104   7   7  14]
- [  3   3   1   1  58   1   3]
- [  5   1   2   0   1  47   6]
- [ 14   3   9  11   4  12  68]]
-Node Classification on random seed  1534 -> 0.593
-Confusion Matrix:
- [[ 53   4   5   2   7   7  17]
- [  9 139   7   0  10   2   2]
- [ 28  21 157  42  25  10  49]
- [ 25   5  14  77   6   6  13]
- [  0   7   2   2  56   2   1]
- [  5   2   0   2   1  46   4]
- [  3   5  11  15   9  20  65]]
-Node Classification on random seed  1535 -> 0.614
-Confusion Matrix:
- [[ 84   2   3   4   4  16   9]
- [ 16 102   7   4  12   1   5]
- [ 25  23 138  29  30  24  29]
- [ 13   3  13 108   3   5  11]
- [  0   7   3   4  55   0   5]
- [  9   0   3   2   0  50   5]
- [  9   1  12   4  16  15  77]]
-Node Classification on random seed  1536 -> 0.565
-Confusion Matrix:
- [[ 59   3  10   6   2  13  13]
- [  4 125  13   9   2   6   2]
- [ 24  29 114  39  15  36  53]
- [ 10   6  17  91   3   5  14]
- [  0   9  11   1  55   1   3]
- [  9   2   2   3   1  45   6]
- [ 11   5  12   3   9  13  76]]
-Node Classification on random seed  1537 -> 0.603
-Confusion Matrix:
- [[ 69   2   8   3   7   9  10]
- [ 19 127   3   4   5   2   5]
- [ 21  24 137  36  19  29  44]
- [ 14   6   5 119   4   4  11]
- [  0   2   3   0  61   1   8]
- [  2   6   3   2   1  38   5]
- [ 19   3   7  14   5  22  52]]
-Node Classification on random seed  1538 -> 0.591
-Confusion Matrix:
- [[ 53   0  14   6   2  20   4]
- [  5 118   9   1   9   1  10]
- [ 22  34 140  32  21  28  38]
- [  7   5  30  98   8   7   3]
- [  1   3   5   3  68   0   2]
- [  2   0   3   6   2  47   4]
- [ 12   4  13   3   4  26  67]]
-Node Classification on random seed  1539 -> 0.595
-Confusion Matrix:
- [[ 58   1   6  10   4  14   8]
- [  4 129   3   8   3   4   4]
- [ 38  20 112  36  33  32  36]
- [  9   2   9 114  12   6  15]
- [  1   7   5   1  62   2   4]
- [  7   1   2   4   0  53   2]
- [ 14   8   7   9   8   6  67]]
-Node Classification on random seed  1540 -> 0.574
-Confusion Matrix:
- [[ 65   2   3   3   4   5   7]
- [  8 102   9   3  21   1   2]
- [ 28  27 133  31  45  28  37]
- [ 18  10  17 104   3   5  12]
- [  4   2   4   2  59   0   3]
- [  6   2   0   3   0  43   1]
- [ 22   2  15  10   7  14  68]]
-Node Classification on random seed  1541 -> 0.605
-Confusion Matrix:
- [[ 79   1   3   5   2  15   5]
- [  1 133   7   6   5   0   3]
- [ 30  18 125  30  20  31  45]
- [ 17   2  19 108   4   6  18]
- [  0  11   2   2  51   0   4]
- [  2   1   1   2   1  44  11]
- [ 16   7   4  11   6  21  65]]
-Node Classification on random seed  1542 -> 0.626
-Confusion Matrix:
- [[ 65   7   4   3   5  11  17]
- [  3 138   1   2   4   4   3]
- [ 13  39 147  46  40  13  36]
- [  7   8  13  98   6  10  14]
- [  0   7   1   2  52   2   0]
- [  1   1   3   0   0  49   6]
- [ 10   6   4   6   7   9  77]]
-Node Classification on random seed  1543 -> 0.617
-Confusion Matrix:
- [[ 70   1   7   9   3   7   1]
- [  4 119   2   0   8   0   4]
- [ 32  22 154  35  27  15  34]
- [ 13   5  21  94   6   3  30]
- [  1   8   4   1  59   2   3]
- [  9   1   3   0   1  51   4]
- [ 14   1  20   7   8   7  70]]
-Node Classification on random seed  1544 -> 0.625
-Confusion Matrix:
- [[ 85   2   4   5   5   6   5]
- [  2 127   6   3  11   3   2]
- [ 22  17 150  47  36  20  21]
- [ 11   3  17  97   1   6  12]
- [  2   8   2   3  64   1   2]
- [  7   3   4   2   1  41   5]
- [ 21   7   5   7   9  19  61]]
-Node Classification on random seed  1545 -> 0.625
-Confusion Matrix:
- [[ 80   3   5   3   3  10  15]
- [  6 140   5   7   7   4   2]
- [ 28   8 158  33  28  17  34]
- [ 22   4  20  92   4   9   7]
- [  1   4   6   1  56   1   3]
- [  5   4   1   5   0  45   5]
- [  3   1  15  16   5  15  54]]
-Node Classification on random seed  1546 -> 0.65
-Confusion Matrix:
- [[ 75   2   4   3   4  16   2]
- [  7 128   7   2   2   2   0]
- [ 23  16 152  32  25   6  45]
- [ 20   3  16 118   4   4   5]
- [  0   9   2   2  66   0   3]
- [  8   4   4   0   3  36   4]
- [  9   6   8   7   6  25  75]]
-Node Classification on random seed  1547 -> 0.584
-Confusion Matrix:
- [[ 53   4   4   7   6  19   9]
- [  5 126   6   2  14   0   2]
- [ 26  23 156  47  25  24  27]
- [ 16   7  19  82   5  13  12]
- [  6   6   0   0  67   3   1]
- [  7   0   8   3   7  32   3]
- [ 10   4   5  11   9  11  68]]
-Node Classification on random seed  1548 -> 0.577
-Confusion Matrix:
- [[ 67   1   4   3   4   6  13]
- [  4 126   3   5   7   5   7]
- [ 18  29 112  53  41  11  51]
- [ 15  11  13  99   7   2  13]
- [  2   8   2   5  51   1   3]
- [  6   1   8   1   0  46   9]
- [ 10   9   8   9  10   5  76]]
-Node Classification on random seed  1549 -> 0.57
-Confusion Matrix:
- [[ 65   1  11   0   5  11   9]
- [  4 126   9   2   8   2   2]
- [ 22  26 122  56  20  24  48]
- [ 24   8   4  88   4  13   9]
- [  1   7   5   0  60   2   3]
- [  5   7   2   3   1  42   2]
- [ 17   7   8   2   6  30  67]]
-Node Classification on random seed  1550 -> 0.618
-Confusion Matrix:
- [[ 85   4   0   4   5  12   5]
- [  8 110   2   4   5   3   2]
- [ 27  24 142  41  24  36  36]
- [ 12   2  23  94   2   8   7]
- [  2   5   4   0  61   2   3]
- [  9   1   6   0   2  49   2]
- [ 11   2   8   7   9  13  77]]
-Node Classification on random seed  1551 -> 0.603
-Confusion Matrix:
- [[ 79   2   2   4   2  14  12]
- [  8 122  15   0   1   3   5]
- [ 26  27 143  34  22  20  42]
- [ 25   1  21  81   2   7   9]
- [  3  13   1   0  55   1   5]
- [  5   1   3   4   0  40   5]
- [ 11   5  13   5  10   8  83]]
-Node Classification on random seed  1552 -> 0.589
-Confusion Matrix:
- [[ 72   5   2   8   3  15   3]
- [  6 116   5   7   5   1   3]
- [ 29  38 117  32  34  23  39]
- [ 14   7  17 107  11   5   9]
- [  0   8   0   1  62   2   2]
- [  4   3   4   1   0  35  10]
- [ 13   1   7   6   7  21  80]]
-Node Classification on random seed  1553 -> 0.608
-Confusion Matrix:
- [[ 68   7   9   0   2   8   7]
- [  5 125   7   3  16   0   4]
- [ 28  19 135  52  36  33  23]
- [  8   5  27  99   3   7  10]
- [  2   7   2   0  54   0   2]
- [  8   0   0   3   0  50   4]
- [ 12   3   8   2   6  14  77]]
-Node Classification on random seed  1554 -> 0.601
-Confusion Matrix:
- [[ 51   3   4   4   6  15  11]
- [  7 142   6   2   6   3   2]
- [ 19  45 150  43  29  26  19]
- [ 32   9   7  94  14   0  10]
- [  1   2   6   1  54   3   3]
- [  5   4   3   2   0  39   4]
- [  6   5  11   6   5  10  71]]
-Node Classification on random seed  1555 -> 0.615
-Confusion Matrix:
- [[ 61   8  12   5   5   6   1]
- [  3 111  12   2   5   5   3]
- [ 21  27 158  29  32  25  28]
- [ 12   0  24  97   7  11  11]
- [  1   4   3   1  65   0   3]
- [  3   0   3   3   0  53   7]
- [ 19   1  14   8   7  14  70]]
-Node Classification on random seed  1556 -> 0.65
-Confusion Matrix:
- [[ 84   5   3   4   6  15   4]
- [  5 115   7   5   5   9   3]
- [ 18  31 168  14  23  15  37]
- [  7   5  17 116   5   8  16]
- [  0   4   4   1  70   0   0]
- [  8   0   4   1   2  32  11]
- [  8   3   9   2   8  18  65]]
-Node Classification on random seed  1557 -> 0.617
-Confusion Matrix:
- [[ 74   7   4   9   6   7   3]
- [  4 130   6   0   9   1   4]
- [ 25  36 119  41  20   6  50]
- [ 20  11  11 110   3   4  12]
- [  1   7   4   1  58   0   3]
- [  5   1   3   4   3  46   5]
- [ 14   4   8   6  10   5  80]]
-Node Classification on random seed  1558 -> 0.615
-Confusion Matrix:
- [[ 59   1   2   4   1   7  18]
- [  4 119  10   4   5   6   9]
- [ 30  35 139  20  21  35  30]
- [  9   3  21 110   5   3  24]
- [  4   6   7   1  60   1   0]
- [  3   1   2   4   1  50   3]
- [  6   3  15   5   1  15  78]]
-Node Classification on random seed  1559 -> 0.636
-Confusion Matrix:
- [[ 73   2   5   2  10  14   4]
- [  2 132   4   1  11   2   3]
- [ 19  36 159  27  35  13  41]
- [ 12   3  11  94   6   6   6]
- [  1   8   1   0  62   2   1]
- [  7   1   1   2   1  54   3]
- [ 19   4  10  10   8  10  62]]
-Node Classification on random seed  1560 -> 0.619
-Confusion Matrix:
- [[ 68   6   0   3   8  13   7]
- [  8 139   6   2  13   0   2]
- [ 20  26 149  30  23  15  51]
- [ 17   7  18  86   4   9  14]
- [  2   3   5   1  65   1   2]
- [  7   3   8   1   0  43   3]
- [ 18   5   3   2   5  10  69]]
-Node Classification on random seed  1561 -> 0.626
-Confusion Matrix:
- [[ 57   3   5   2   1  21  14]
- [  4 121   4   2   8   4   5]
- [ 19  22 154  27  25  18  40]
- [ 14   2  17 114   3   4  19]
- [  7  11   6   1  55   1   1]
- [  8   1   0   0   4  40   5]
- [  9   2  15   2   8  10  85]]
-Node Classification on random seed  1562 -> 0.619
-Confusion Matrix:
- [[ 71   4  12   3   3  13   2]
- [  2 121  13   2   3   4   4]
- [ 27  27 143  24  24  26  52]
- [ 10   4  16  96   6   7  13]
- [  1   6   4   1  57   2   1]
- [  3   0   2   2   0  48   8]
- [ 14   4   4   8   9  11  83]]
-Node Classification on random seed  1563 -> 0.584
-Confusion Matrix:
- [[ 67   1   2   6   4  13   9]
- [  4 107   1   2  17   3  11]
- [ 21  34 135  29  32  27  49]
- [ 31   2  17  81   9   9   4]
- [  2   4   2   1  65   2   7]
- [  9   3   5   2   0  44   3]
- [  8   2  12   1   6  10  85]]
-Node Classification on random seed  1564 -> 0.597
-Confusion Matrix:
- [[ 57   1  18   5   2  16   3]
- [  1 145   3   7   3   1   3]
- [ 24  24 105  25  36  31  38]
- [ 10   6  19 100   7   9  17]
- [  0   7   6   2  70   1   1]
- [  3   1   2   4   0  40   7]
- [ 11   4   7  10  13  15  80]]
-Node Classification on random seed  1565 -> 0.567
-Confusion Matrix:
- [[ 60   0  10   2   4  11  10]
- [  4 112  16   3  11   4   5]
- [ 26  28 111  52  19  15  63]
- [  8   2  12 104  13   4  13]
- [  2   9   2   0  60   1   3]
- [  3   1   2   3   1  43  10]
- [ 13   3  19   6   9  11  77]]
-Node Classification on random seed  1566 -> 0.586
-Confusion Matrix:
- [[ 53   2   7   9   4  14   8]
- [  3 117   2   1  14   4   5]
- [ 26  12 138  40  30  13  45]
- [ 22  11   5  85   9  10  17]
- [  1   6   3   1  66   0   3]
- [ 12   1   4   2   1  40   4]
- [  8   6  14   8  12  15  87]]
-Node Classification on random seed  1567 -> 0.629
-Confusion Matrix:
- [[ 70   4   4   5   1   9  12]
- [  2 140   4   1   9   1   6]
- [ 28  25 117  43  43  15  38]
- [  7   3  11 118   3   7  10]
- [  2  11   2   4  55   0   1]
- [  6   0   3   2   0  53   3]
- [  4   7   5   6   5  19  76]]
-Node Classification on random seed  1568 -> 0.619
-Confusion Matrix:
- [[ 72   1   2   7   6   9   4]
- [  3 125   6   4   7   3   2]
- [ 35  25 124  42  20  24  34]
- [ 22   3   7 115   7   6   4]
- [  4   5   1   3  51   1   3]
- [ 11   1   1   1   2  53   1]
- [ 24   5   8   4   3  20  79]]
-Node Classification on random seed  1569 -> 0.597
-Confusion Matrix:
- [[ 68   1   5   3   3   5  12]
- [  3 106   5   1  15   5   4]
- [ 15  18 147  40  32  15  47]
- [  8   4  27  89   7  21  12]
- [  7   7   1   1  65   1   6]
- [  2   3   3   0   1  42   6]
- [ 12   3  11   4   8  19  80]]
-Node Classification on random seed  1570 -> 0.605
-Confusion Matrix:
- [[ 60   0   3  15   4  10  10]
- [  3 123   4   4  13   8   8]
- [ 13  11 146  48  24  18  40]
- [  9   1  19  83   8   7  24]
- [  0   8   4   1  51   2   2]
- [  4   1   0   5   3  42  15]
- [  7   4   9  15   5   6 100]]
-Node Classification on random seed  1571 -> 0.606
-Confusion Matrix:
- [[ 72   1   8   9   2  15   4]
- [  5 133   7   6   1   3   9]
- [ 29  25 144  16  26  37  31]
- [  7  10  28  82   2   7   9]
- [  2  10  10   1  56   0   1]
- [  4   2   1   0   0  44   2]
- [  8   3  14   7   1  31  75]]
-Node Classification on random seed  1572 -> 0.593
-Confusion Matrix:
- [[ 57   3  10   9   3   7  18]
- [  4 135   2   2   4   3   3]
- [ 23  24 141  39  22  31  46]
- [ 10   8  11 104   1  10  22]
- [  3   7   5   0  51   1   1]
- [  2   0   1   1   0  37   9]
- [ 18   6  15   4   5  14  68]]
-Node Classification on random seed  1573 -> 0.624
-Confusion Matrix:
- [[ 68   2   4   7   3   6  19]
- [  3 147   4   1   9   4   6]
- [ 22  17 145  32  26  11  49]
- [ 21   9  15  81   0  10  15]
- [  1   8   2   0  62   0   5]
- [  2   1   9   1   0  42   4]
- [  9   6   7  10  11   5  79]]
-Node Classification on random seed  1574 -> 0.586
-Confusion Matrix:
- [[ 72   2   3   6   1  11  11]
- [  5 122   6   1   2   2   8]
- [ 29  28 102  52  40  17  36]
- [ 13   2  14 103   7   8  21]
- [  4  10   2   3  53   0   3]
- [  5   2   0   1   2  53   8]
- [ 11   3   5   6  14  10  81]]
-Node Classification on random seed  1575 -> 0.582
-Confusion Matrix:
- [[ 79   1   7   1   7  12  15]
- [  7 118   7   3   6   2   9]
- [ 13  23 139  25  26  20  62]
- [ 23   1  17  81  13  11  15]
- [  3   8   2   1  54   1   1]
- [  7   1   2   1   2  40   2]
- [  8   2   7   7   9  28  71]]
-Node Classification on random seed  1576 -> 0.63
-Confusion Matrix:
- [[ 82   4   8   2   5   8   4]
- [  1 146   1   2   6   0   2]
- [ 20  26 138  30  25  36  29]
- [ 14   0  21  95   7   6  12]
- [  0   7   4   1  62   1   4]
- [  6   2   1   3   2  33   2]
- [ 22   4   9   5   7  21  74]]
-Node Classification on random seed  1577 -> 0.646
-Confusion Matrix:
- [[ 86   2   2   9   1  12  10]
- [ 15 118   8   3  10   0   2]
- [ 27  10 157  40  20  18  28]
- [ 19   3  17  96   4   4   9]
- [  1   4   2   1  64   0   1]
- [  3   2   1   3   2  43  10]
- [ 12   2  11   9   9   8  82]]
-Node Classification on random seed  1578 -> 0.621
-Confusion Matrix:
- [[ 67   3   7   6   4  22   4]
- [  4 126   3   0   7   3   5]
- [ 26  32 159  28  22  21  45]
- [ 15   1  16 113   5  10   7]
- [  1   9   3   1  53   1   1]
- [  6   3   0   1   1  46   3]
- [  7   3  22   4   5  12  57]]
-Node Classification on random seed  1579 -> 0.62
-Confusion Matrix:
- [[ 69   1   6   5   3  14   8]
- [  7 124   1   4  10   5   3]
- [ 25  15 154  20  19  37  35]
- [ 11   4  16  97   5  14  12]
- [  1  10   3   3  70   1   1]
- [  7   0   1   3   2  39   7]
- [ 20   7   6   3   2  23  67]]
-Node Classification on random seed  1580 -> 0.642
-Confusion Matrix:
- [[ 77   1   4   5   2  10   7]
- [  5 124   9   3   3   1   1]
- [ 25  18 160  43  13  15  48]
- [  9   2   8 112  10   6  17]
- [  0   7   3   2  54   2   2]
- [  4   0   1  11   1  50   1]
- [  7   5  14  10   4  19  65]]
-Node Classification on random seed  1581 -> 0.653
-Confusion Matrix:
- [[ 76   4   3   5   6   3  15]
- [  1 115   9   2  11   1  11]
- [ 22  13 168  28  28  14  44]
- [ 20   2  16  98   3   4  12]
- [  2   3   3   0  63   0   2]
- [  8   0   1   0   0  39  14]
- [ 13   2   4   3   7   8  94]]
-Node Classification on random seed  1582 -> 0.605
-Confusion Matrix:
- [[ 75   1   5   7   3  12  10]
- [  5 125   5   1  11   3   2]
- [ 26  42 136  38  23  29  24]
- [ 18   6  16  84  13   9  16]
- [  1   3   3   1  63   1   2]
- [  6   1   0   2   0  52   4]
- [  8   5  11   7   8   7  70]]
-Node Classification on random seed  1583 -> 0.6
-Confusion Matrix:
- [[ 57   3   2  10   3  17   8]
- [  1 124   6   1   9   2   4]
- [ 30  14 140  32  46  26  45]
- [  7   5  13 110   7   3  16]
- [  2   7   5   0  59   0   0]
- [  6   3   3   1   3  57   2]
- [  9   4  12   6  18   9  53]]
-Node Classification on random seed  1584 -> 0.657
-Confusion Matrix:
- [[ 80   0   6   6   4  10   7]
- [  5 131   4   4  15   0   3]
- [ 25  17 176  23  24  12  32]
- [ 21   1  24 102   5   6   7]
- [  0   4   2   2  57   1   4]
- [  8   0   2   2   0  36   7]
- [ 14   1   5  13   8   9  75]]
-Node Classification on random seed  1585 -> 0.585
-Confusion Matrix:
- [[ 81   1   8   2   7  12   4]
- [  2 134   3   2   8   7   2]
- [ 27  34 105  53  28  46  27]
- [ 15   5  19  91  10   5   5]
- [  0  11   1   0  67   2   2]
- [  6   0   4   0   1  44   4]
- [ 14   3  10   2   8  15  63]]
-Node Classification on random seed  1586 -> 0.639
-Confusion Matrix:
- [[ 62   3   3   2   5   9  15]
- [  2 129  11   3   9   1   1]
- [ 17  41 181  28  26  13  25]
- [ 15   2  18 110   7   3   7]
- [  1   3   6   4  57   0   1]
- [  5   3   1   4   0  40   1]
- [  9   3   5  18   9  22  60]]
-Node Classification on random seed  1587 -> 0.612
-Confusion Matrix:
- [[ 73   2   5   8   5   7  13]
- [  4 133   4   3  15   0  11]
- [ 41  25 125  29  38  29  17]
- [ 12   4  10 103   7   7  17]
- [  1   6   3   2  61   0   3]
- [  4   1   3   1   3  50   8]
- [  9   4   3   4  10  10  67]]
-Node Classification on random seed  1588 -> 0.587
-Confusion Matrix:
- [[ 50  12   9  10   5   9  11]
- [ 13 119  14   2   2   0   3]
- [ 28  35 144  20  14  30  45]
- [ 11   8   8  94   6   4  18]
- [  0   9   3   2  55   2   0]
- [  7   2   1   0   1  50   4]
- [ 13   7  14   8  11  12  75]]
-Node Classification on random seed  1589 -> 0.547
-Confusion Matrix:
- [[ 57   2   7  18   4  16  13]
- [  6  96   5   4  14   3   5]
- [ 21  14 140  42  21  33  45]
- [ 20   2  21 101   7  12   7]
- [  1   6   4   3  54   1   4]
- [  3   5  12   2   2  39   4]
- [  8   3  17   8   5  23  60]]
-Node Classification on random seed  1590 -> 0.614
-Confusion Matrix:
- [[ 56   0   5   4   3  12   7]
- [  0 154   3  10   6   1   5]
- [ 22  18 133  36  35  27  34]
- [ 10   1   9 111  14  12  13]
- [  0   3   8   3  59   1   2]
- [  8   0   1   2   0  41   5]
- [  4   5  20   9   8  20  60]]
-Node Classification on random seed  1591 -> 0.579
-Confusion Matrix:
- [[ 85   1   0   3   6  11   8]
- [  3 111   5  10  17   0   9]
- [ 22  22 118  51  38   9  51]
- [  9   4  10 100   2   4  17]
- [  1   6   4   3  56   0   0]
- [  5   3   6   0   1  54   8]
- [ 12   3   6  17  15  19  55]]
-Node Classification on random seed  1592 -> 0.601
-Confusion Matrix:
- [[ 62   0   5   8   3  27  13]
- [  5 128   8   2  11   1   4]
- [ 12  18 144  43  35  22  35]
- [  8   4   8  80  13  10  16]
- [  2   2   7   2  62   4   6]
- [  2   3   0   0   2  52   1]
- [  8   3  18   8   2  18  73]]
-Node Classification on random seed  1593 -> 0.602
-Confusion Matrix:
- [[ 80   7   2   4   2   7   7]
- [  5 120   1   1  14   0   2]
- [ 30  43 143  18  30  24  30]
- [ 28   5  12  88   8   1  14]
- [  2   4   3   5  68   2   3]
- [  9   0   2   3   1  38   9]
- [ 20   1  11   5   8  15  65]]
-Node Classification on random seed  1594 -> 0.577
-Confusion Matrix:
- [[ 61   2   5   5  10  12  23]
- [  6 114   2   5   6   2   9]
- [ 21  16 132  23  33  38  51]
- [ 18   0  23  96   4   8  12]
- [  1   5   5   0  63   3   3]
- [ 10   0   4   1   1  38   4]
- [ 19   2   2   9   8  12  73]]
-Node Classification on random seed  1595 -> 0.615
-Confusion Matrix:
- [[ 84   2   7   4   3   5  11]
- [  9  91   9   5  28   3   4]
- [ 22   8 137  36  29  30  24]
- [ 25   9  12 115   3  12   6]
- [  1   3   3   1  61   1   5]
- [  6   4   3   0   1  40   7]
- [ 10   5  12   3   6   8  87]]
-Node Classification on random seed  1596 -> 0.667
-Confusion Matrix:
- [[ 85   8   1   9   3   8   8]
- [  2 134   5   3   6   1   5]
- [ 21  11 175  23  12  18  37]
- [ 13   4  31  86  11   3  12]
- [  2   4   4   1  64   0   2]
- [  3   1   1   5   2  47   3]
- [ 14   5   6   7   8  10  76]]
-Node Classification on random seed  1597 -> 0.594
-Confusion Matrix:
- [[ 65   3   9   4   2  18   1]
- [  5 110   4   1  16  10   1]
- [ 22  31 138  21  22  34  49]
- [ 15   0  19  87  14   6   9]
- [  1   6   3   1  70   4   4]
- [  5   2   2   4   1  54   3]
- [  6   6  17   6   7  12  70]]
-Node Classification on random seed  1598 -> 0.604
-Confusion Matrix:
- [[ 65   1   1   5  13  18  20]
- [  2 117   5   4  16   2   8]
- [ 17  22 153  19  19  29  47]
- [ 12   3  25  90   5  10  10]
- [  0   8   4   0  60   0   1]
- [  4   2   0   1   0  48   5]
- [  4   0  14  15   6  19  71]]
-Node Classification on random seed  1599 -> 0.621
-Confusion Matrix:
- [[ 79   3   4   4   5  18  11]
- [  2 123   2   1  11   3   3]
- [ 22  35 135  33  22  18  44]
- [  9   5  21  86   7   3  10]
- [  1   6   4   1  63   0   2]
- [  4   2   4   0   0  50   7]
- [  7   5   6  16   8  10  85]]
-Node Classification on random seed  1600 -> 0.612
-Confusion Matrix:
- [[ 85   3   5   4   5   5  10]
- [  2 127   4   6   9   2   1]
- [ 33  17 127  30  28  27  51]
- [ 15   4  27  85   8   5   8]
- [  1   3   5   1  62   3   3]
- [  5   0   1   0   1  45   8]
- [ 19   3   4   7   7   8  81]]
-Node Classification on random seed  1601 -> 0.63
-Confusion Matrix:
- [[ 74   5   5   5   0   5  18]
- [ 10 133  11   1   2   0   2]
- [ 18  28 155  31  31  11  34]
- [ 10   5  23  97   3   8  22]
- [  1  10   7   1  62   0   2]
- [  2   3   6   3   0  41   4]
- [  8   4   6   6   9  10  68]]
-Node Classification on random seed  1602 -> 0.614
-Confusion Matrix:
- [[ 69   3   1  17   1  12   1]
- [  6 115   5   0  12   3   3]
- [ 29  14 135  40  31  13  25]
- [ 19   8  15 117  10   3   8]
- [  3   9   3   1  65   0   2]
- [  8   0   2   1   1  51   2]
- [ 30   3  11  10   2  19  62]]
-Node Classification on random seed  1603 -> 0.616
-Confusion Matrix:
- [[ 56   1   3   6   3  16  17]
- [  6 131   1   2   8   4   3]
- [ 22  19 136  25  26  21  45]
- [ 12   2  12 107   2  10  21]
- [  3   5   2   3  54   0   5]
- [  7   3   2   1   0  59   7]
- [ 12   2   6   6   6  27  73]]
-Node Classification on random seed  1604 -> 0.667
-Confusion Matrix:
- [[ 82   1   3   1   3  21  16]
- [  3 132   5   1   4   2   1]
- [ 16  20 157  43  12  34  28]
- [ 10   4  10 109   4   7  14]
- [  1   9   5   2  59   1   1]
- [  5   2   2   1   0  43   1]
- [  6   2   6   5   3  18  85]]
-Node Classification on random seed  1605 -> 0.628
-Confusion Matrix:
- [[ 83   2   4   3   3   9   6]
- [  5 129   2   5   1   2   3]
- [ 27  30 145  34  33  24  42]
- [ 14   2  14  93   9   5  13]
- [  2  10   3   2  59   1   0]
- [  7   2   2   0   3  48   4]
- [ 12   4   9   3   5  11  71]]
-Node Classification on random seed  1606 -> 0.621
-Confusion Matrix:
- [[ 69   0   6   6   2   4   8]
- [  5 126   4   3   5   3   8]
- [ 28  30 135  45  37  11  27]
- [ 10   9  16 111   2   3  17]
- [  3   8   3   3  61   0   4]
- [  2   2   1   1   0  35   9]
- [ 10   6  12   7  15   4  84]]
-Node Classification on random seed  1607 -> 0.573
-Confusion Matrix:
- [[ 74   6   6   1   2  11  15]
- [  4 123   6   2   3   2   7]
- [ 56  37 100  41  25  23  49]
- [  9   5  14 104   2   4  17]
- [  0   4   7   3  54   0   2]
- [  5   6   4   0   5  41   3]
- [ 10   6   3   4   2  16  77]]
-Node Classification on random seed  1608 -> 0.619
-Confusion Matrix:
- [[ 72   5   6   7   5  13  11]
- [  5 122   7   4   9   3   2]
- [ 23  27 132  19  29  36  39]
- [ 12   4  19 103   3  12  18]
- [  1   4   2   3  71   1   2]
- [  1   0   3   1   1  42   3]
- [  9   3   7   3   3  16  77]]
-Node Classification on random seed  1609 -> 0.64
-Confusion Matrix:
- [[ 57   5   2   2   4   9  19]
- [  3 115   4   6   4   5   4]
- [ 31  11 187  29  21  14  43]
- [  4   4  21 115   4   5  16]
- [  2   5   8   3  52   2   9]
- [  2   2   1   1   2  39  15]
- [  4   5   9   6   4  10  75]]
-Node Classification on random seed  1610 -> 0.61
-Confusion Matrix:
- [[ 67   9  10   8   4  16   8]
- [  6 138   2   0   8   2   2]
- [ 33  17 138  34  19  31  23]
- [  4   3  18 100   6  18  16]
- [  1   5   4   1  50   0   6]
- [ 10   2   7   1   0  38   4]
- [ 11   2   9   7   7  16  79]]
-Node Classification on random seed  1611 -> 0.615
-Confusion Matrix:
- [[ 63   6  10   2   1  15  16]
- [  2 127  14   3   6   4   3]
- [ 16  28 161  42  22  17  40]
- [ 13   2  15  91   5   2  18]
- [  0   4   6   0  57   0   5]
- [  6   2   3   1   3  47   5]
- [ 14   1  12  10   7   4  69]]
-Node Classification on random seed  1612 -> 0.598
-Confusion Matrix:
- [[ 75   0   1   2   7  15   9]
- [  3 131   4   2   1   6   5]
- [ 12  24 128  64  23  19  49]
- [ 15   3  16  93   7   6  14]
- [  1   9   1   5  50   3   2]
- [  9   0   3   0   1  53   5]
- [ 11   6   6  10   5  18  68]]
-Node Classification on random seed  1613 -> 0.642
-Confusion Matrix:
- [[ 66   2   2   4   8  14  22]
- [  2 127   3   1  10   1  13]
- [  9  16 161  39  23  20  42]
- [  8   4  14 124   5   4  10]
- [  1   4   3   1  56   2   3]
- [  7   1   2   6   0  42   6]
- [ 10   3   5   4  10  14  66]]
-Node Classification on random seed  1614 -> 0.611
-Confusion Matrix:
- [[ 60   6   6   4   2  10  10]
- [  5 139   4   5   8   2   0]
- [ 34  16 138  38  24  15  49]
- [ 15   1  13  89   4  15  10]
- [  1   8   5   0  65   1   6]
- [  9   0   5   3   0  46   2]
- [ 11   2   8  11   9  12  74]]
-Node Classification on random seed  1615 -> 0.632
-Confusion Matrix:
- [[ 53   7   4   2   8  10  10]
- [  8 142   4   1   4   3   6]
- [  9  20 134  52  40  12  35]
- [  8   4   5 105  14   5  17]
- [  2   4   1   0  70   0   4]
- [  3   1   2   0   3  40   5]
- [  9   6  12   4  11  13  88]]
-Node Classification on random seed  1616 -> 0.614
-Confusion Matrix:
- [[ 77   2   4   5   5   7  12]
- [  1 130  12   3   8   4   5]
- [ 20  17 132  43  24  20  26]
- [ 11   9  17  92   5  19  22]
- [  0   9   4   2  69   2   0]
- [  3   0   3   3   0  43   8]
- [ 11   3  14   3   9  11  71]]
-Node Classification on random seed  1617 -> 0.622
-Confusion Matrix:
- [[ 68   1   3   3   4  19   6]
- [ 14 121   4   1   8   3   2]
- [ 33  22 139  18  21  31  35]
- [ 13   4  19 105   5  12  13]
- [  1   7   4   0  57   5   3]
- [  5   1   0   1   2  55   6]
- [  9   1  13   5   4  17  77]]
-Node Classification on random seed  1618 -> 0.643
-Confusion Matrix:
- [[ 80   0   5   5   3  15   3]
- [  1 133   8   0   6   6   2]
- [ 19  19 138  29  24  30  38]
- [  6   2  13 114   4  13  16]
- [  0   6   4   1  64   0   1]
- [  7   0  11   3   2  31  10]
- [  8   5   6   4   7  15  83]]
-Node Classification on random seed  1619 -> 0.661
-Confusion Matrix:
- [[ 64   3   1   6   3  16  16]
- [  6 165   3   3   8   2   0]
- [  8  28 170  17  25  21  33]
- [ 12   7   7 100   9   7   8]
- [  1   6   5   0  52   2   3]
- [  2   6   1   0   0  47   3]
- [  5  10  18   6   4  18  63]]
-Node Classification on random seed  1620 -> 0.603
-Confusion Matrix:
- [[ 70   0   2   5   7  19  11]
- [  9 117   8   3  12   6   4]
- [ 24   7 130  32  29  31  39]
- [ 15   5  15  92   5  12  10]
- [  1   6   4   1  66   1   3]
- [  7   1   5   5   1  43   2]
- [ 19   3   8   5   8   7  85]]
-Node Classification on random seed  1621 -> 0.627
-Confusion Matrix:
- [[ 69  11  11   6   3  20   3]
- [  4 146   5   2   1   1   4]
- [ 22  15 153  14  28  31  28]
- [ 18   3  15  97   5   6  16]
- [  3   3   7   2  49   2   3]
- [  7   1   1   2   2  39   6]
- [ 17   2  14   9   6  14  74]]
-Node Classification on random seed  1622 -> 0.619
-Confusion Matrix:
- [[ 73   1   3   5   1   9  11]
- [  5 123   6   7   5   3   7]
- [ 15  28 139  25  36  28  40]
- [ 13   3  21  96   5   5  16]
- [  2   1   4   1  60   0   3]
- [  5   5   2   1   1  54   5]
- [ 12   2   9  17   9   4  74]]
-Node Classification on random seed  1623 -> 0.642
-Confusion Matrix:
- [[ 70   1   7   4   0  12   4]
- [  1 144   4   4   1   5   5]
- [ 20  26 130  38  28  19  39]
- [ 12  10   3 117   7   3  17]
- [  0  11   3   3  56   3   3]
- [  4   1   3   5   0  44   8]
- [  7   3  14   5   5  10  81]]
-Node Classification on random seed  1624 -> 0.642
-Confusion Matrix:
- [[ 85   2   2  11   4   6   3]
- [  8 114   2   5  11   2   3]
- [ 15  37 152  18  27  24  41]
- [ 16   3  15 102   5  10  12]
- [  1   5   5   2  52   1   1]
- [  6   2   0   1   0  48   7]
- [ 13   6   8   7   3   8  89]]
-Node Classification on random seed  1625 -> 0.619
-Confusion Matrix:
- [[ 69   2   3   6   3  18  21]
- [  1 122  13   3   5   5   1]
- [ 27  12 126  51  21  24  44]
- [  4   1  10 119   5   5  13]
- [  1   9   3   2  58   0   1]
- [ 11   0   3   4   1  35   9]
- [  2   2  15   3   4  13  90]]
-Node Classification on random seed  1626 -> 0.604
-Confusion Matrix:
- [[ 67   6  17   4   2  10   7]
- [  2 118   7   5   7   6   4]
- [ 16  21 126  30  47  16  47]
- [  7   7  21  96   4   9  13]
- [  0   6   2   2  65   3   1]
- [  0   0   3   1   0  41   6]
- [  8   3  11   7  13  15  91]]
-Node Classification on random seed  1627 -> 0.636
-Confusion Matrix:
- [[ 71   3   7   2   4   2  21]
- [  4 128  10   1   8   4   2]
- [ 19  15 158  30  23  15  48]
- [ 11   7  11 103   5   3  18]
- [  3   5   0   2  62   0   2]
- [ 13   2   0   3   0  40   9]
- [ 16   4  13   5   6   8  74]]
-Node Classification on random seed  1628 -> 0.616
-Confusion Matrix:
- [[ 61   4   3   4   5   8  11]
- [  4 119  13   3   8   2   5]
- [ 20  32 129  31  39  20  40]
- [ 11   5   9 113   8   5  18]
- [  0   5   2   1  67   0   4]
- [  6   2   2   1   3  48   3]
- [  4   3   6   9   7  18  79]]
-Node Classification on random seed  1629 -> 0.637
-Confusion Matrix:
- [[ 81   3   6   3   4   4   8]
- [  2 119   6   3   6   0   8]
- [ 25  36 153  33  18  16  31]
- [ 11   5  15 119  10   3  14]
- [  2   7   4   1  57   0   2]
- [  7   0   2   3   1  43   4]
- [ 15   4  11  11   4  15  65]]
-Node Classification on random seed  1630 -> 0.586
-Confusion Matrix:
- [[ 52  13   2   9   3  10  12]
- [  6 144   3   5   4   1   1]
- [ 33  38 124  23  38  22  30]
- [ 19   5  17  93   9   4  16]
- [  1   7   1   0  59   1   5]
- [  8   1   2   1   1  40   4]
- [  8   4  12   8  12  15  74]]
-Node Classification on random seed  1631 -> 0.582
-Confusion Matrix:
- [[ 69   5   5   7   2  11  21]
- [  2 122   1   2   3   4   3]
- [ 18  38 113  49  36  17  44]
- [  8   5  21 111   8   5  13]
- [  2  11   1   3  46   5   0]
- [  5   0   2   2   1  43   8]
- [ 14   4   3  14   7   8  78]]
-Node Classification on random seed  1632 -> 0.571
-Confusion Matrix:
- [[ 78   0   5   4   9   5   8]
- [  7 120   8   4   7   2   9]
- [ 10  24 117  36  57  38  40]
- [ 14   1  18  96  14   7   6]
- [  0   8   4   3  43   3   2]
- [  5   0   2   9   7  36   3]
- [ 10   3  14   4   8  11  81]]
-Node Classification on random seed  1633 -> 0.606
-Confusion Matrix:
- [[ 62  11   7   7   4  16   6]
- [  1 117  17   3  11   6   5]
- [ 15  10 138  41  44  19  19]
- [  8   7  20  99   7   8  18]
- [  1   3   7   4  70   0   2]
- [  7   0   5   5   1  46   4]
- [  8   4   7   6   6  14  74]]
-Node Classification on random seed  1634 -> 0.626
-Confusion Matrix:
- [[ 75   2  12   1   1   9   4]
- [ 10 139   6   5   4   4   0]
- [ 24  18 109  54  34  15  35]
- [  3   4  18 116   4   3  15]
- [  3   8   3   1  60   0   3]
- [  8   0   1   0   5  50   1]
- [ 12   6   8   7   9  14  77]]
-Node Classification on random seed  1635 -> 0.571
-Confusion Matrix:
- [[ 78   6   3   3   3  13  10]
- [ 13 117   3   2  10   5   2]
- [ 29  26 112  42  27  22  39]
- [ 27   7  16  96   5   4  16]
- [  0   2   4   1  61   3   4]
- [  6   1   4   4   4  31   9]
- [ 13   2  13   9   5  12  76]]
-Node Classification on random seed  1636 -> 0.648
-Confusion Matrix:
- [[ 79   4   4   1   0   7  13]
- [  3 118   1   3  11   3   7]
- [ 15  26 160  24  17  20  64]
- [ 14   3   7 102  12   6  16]
- [  0   5   3   0  69   0   2]
- [  6   2   0   2   0  41   6]
- [ 13   4   9   3   5  11  79]]
-Node Classification on random seed  1637 -> 0.575
-Confusion Matrix:
- [[ 74   3   3   5   3   9  10]
- [  1 123   2   3  20   1   9]
- [ 13  28  93  41  36  27  65]
- [ 19   3  13 103  15  12   7]
- [  4   1   1   2  64   0   4]
- [  5   0   1   0   1  41   7]
- [ 13   1   2   7  10  18  77]]
-Node Classification on random seed  1638 -> 0.603
-Confusion Matrix:
- [[ 51   3   5   8   6  16  24]
- [  1 139   2   5   8   4  10]
- [ 11  34 128  23  54  21  35]
- [  7   5  13  91   9   6  14]
- [  1   9   2   1  60   1   2]
- [  2   4   4   4   0  49   8]
- [  4   4   4   4   6  13  85]]
-Node Classification on random seed  1639 -> 0.618
-Confusion Matrix:
- [[ 64   3   3   3   3   2  15]
- [  6 131   4   6   5   6  13]
- [ 32  15 128  36  33  13  44]
- [  5   2  22 104   6   6  15]
- [  2   8   4   2  63   1   5]
- [ 10   0   0   2   0  40   9]
- [  9   7   2  12   5   6  88]]
-Node Classification on random seed  1640 -> 0.612
-Confusion Matrix:
- [[ 80   2   1   3   2  13  19]
- [  3 142   3   2   6   0   4]
- [ 19  23 120  58  21  30  39]
- [  4   7  10 101   3   7  16]
- [  1   9   7   3  51   1   3]
- [  1   0   0   4   0  33  15]
- [ 11   4  13   8   5   8  85]]
-Node Classification on random seed  1641 -> 0.619
-Confusion Matrix:
- [[ 75   2   0   4   0  11  10]
- [  8 129   9   3   6   3   5]
- [ 19  17 139  41  32  33  27]
- [ 10   1  11  93   3  24  14]
- [  0   9   2   0  68   2   0]
- [  8   0   4   2   0  48   4]
- [ 20   0   9   7   9  12  67]]
-Node Classification on random seed  1642 -> 0.621
-Confusion Matrix:
- [[ 75   6   3   6   1  10   5]
- [  4 127   6   0   5   4   5]
- [ 34  16 118  23  37  22  30]
- [ 18   5  21 107   5   2  24]
- [  3   7   1   1  60   4   3]
- [  4   1   1   1   2  49   4]
- [ 19   5   5   5   7  14  85]]
-Node Classification on random seed  1643 -> 0.627
-Confusion Matrix:
- [[ 61   3   5   5   1  12  14]
- [  8 140   3   7   6   3   5]
- [ 10  23 148  58  18  12  50]
- [ 14   3  11  97   6   7   9]
- [  1   6   1   1  59   0   4]
- [  1   1   2   2   0  45  12]
- [ 11   3   8   7   6  14  77]]
-Node Classification on random seed  1644 -> 0.653
-Confusion Matrix:
- [[ 91   5   1   4   1   8   7]
- [  5 123   7   0  11   2   0]
- [ 29  22 147  33  36  22  29]
- [  6   6  20 111   1   6  15]
- [  1   0   3   2  60   0   1]
- [  4   1   4   0   2  48   1]
- [  8   3   7   6   8  20  73]]
-Node Classification on random seed  1645 -> 0.63
-Confusion Matrix:
- [[ 63   0  11   6   5  16   5]
- [ 10 120   5   7   6   4   5]
- [ 22  18 157  41  28  17  32]
- [ 10   1  18 113   8   3   7]
- [  0   3   4   1  66   2   1]
- [  6   0   1   5   3  47   0]
- [ 14   4   9   6   8  18  64]]
-Node Classification on random seed  1646 -> 0.592
-Confusion Matrix:
- [[ 79   2   7   0   9  12  14]
- [  3 130   8   4  10   5   3]
- [ 36  23 128  42  38  15  19]
- [ 18   2  14  82   9   6   5]
- [  1  12   2   0  62   1   3]
- [  9   1   0   0   1  42   4]
- [ 21   1   5   8   6  29  69]]
-Node Classification on random seed  1647 -> 0.605
-Confusion Matrix:
- [[ 67   3   5   8   5   6   9]
- [  5 118  11   1  21   2   8]
- [ 25  22 141  37  38  22  32]
- [  2   1  21  98   4   8  22]
- [  2   1   1   3  69   2   3]
- [  3   1   0   8   0  56   3]
- [  5   3   8  11   4  19  56]]
-Node Classification on random seed  1648 -> 0.606
-Confusion Matrix:
- [[ 75   2   6   7   3  13   5]
- [  4 150   4   3  13   7   4]
- [ 22  32 139  35  30  26  36]
- [  8   9  19  90   2   3  21]
- [  2   3   3   2  52   3   2]
- [  7   1   0   0   1  37   5]
- [  5   4  12   4  12  14  63]]
-Node Classification on random seed  1649 -> 0.613
-Confusion Matrix:
- [[ 69   0  14   4   5   9   6]
- [  9 115   9   3  18   2   3]
- [ 25  20 142  32  30  15  50]
- [ 11   3  18 101   2   8  14]
- [  4   4   3   4  53   1   2]
- [  3   0   1   0   0  49   6]
- [  8   4  12   6   2  17  84]]
-Node Classification on random seed  1650 -> 0.668
-Confusion Matrix:
- [[ 76   3   3   3   2  11  15]
- [  3 130   6   3   4   2   2]
- [ 15  16 153  34  24  35  29]
- [ 10   1  15 116   5   4  15]
- [  1   3   7   0  56   1   2]
- [  4   0   0   0   1  53   5]
- [ 14   1   9   2   7  15  84]]
-Node Classification on random seed  1651 -> 0.592
-Confusion Matrix:
- [[ 61   4   0   4   6  13  17]
- [ 11 140   3   3  11   0   8]
- [ 19  22 112  37  49  18  39]
- [ 10   8   9 109   2   4  14]
- [  1   8   1   2  55   0   3]
- [  6   2   3   0   0  40   7]
- [ 14   5  18  11  10   6  75]]
-Node Classification on random seed  1652 -> 0.637
-Confusion Matrix:
- [[ 64   3   6   4  10   7  11]
- [ 10 128  11   3   8   1   0]
- [ 22  19 172  24  24  23  36]
- [  6   6  16  96   9   6  14]
- [  0   7   6   0  51   1   2]
- [  3   2   3   1   1  45   8]
- [ 10   3   7   5  13  12  81]]
-Node Classification on random seed  1653 -> 0.617
-Confusion Matrix:
- [[ 62   5   1   5   8  10   7]
- [  1 123   3   2  13   4   4]
- [ 29  25 133  38  19  20  49]
- [  6  10  19 118   3   1   7]
- [  3   6   4   8  54   0   3]
- [  6   3   2  10   0  43   2]
- [  8   3   9   3   6  18  84]]
-Node Classification on random seed  1654 -> 0.584
-Confusion Matrix:
- [[ 75   2   0   3   4   6   6]
- [  9 116   3   5  18   1   8]
- [ 29  24 118  33  25  20  61]
- [ 12   3  22  94   8   8  10]
- [  0   3   5   1  65   0   0]
- [  4   0   6   3   3  40  12]
- [ 13   3  11  14   6  12  76]]
-Node Classification on random seed  1655 -> 0.594
-Confusion Matrix:
- [[ 90   0   0   5  11   8  10]
- [  4 113   5   4   1   0   7]
- [ 25  18 101  61  21  20  52]
- [ 13   4   8 103   3   5  31]
- [  0  11   7   3  56   1   2]
- [  2   1   1   5   1  38   9]
- [  8   3   8   3  11  14  93]]
-Node Classification on random seed  1656 -> 0.656
-Confusion Matrix:
- [[ 87   4   9   7   1   3   8]
- [  2 142  10   3   7   0   0]
- [ 40  15 159  19  15   6  38]
- [ 11   7  14 117   7   0   8]
- [  0   4   5   1  50   1   2]
- [  9   3   5   4   0  30   5]
- [ 18   2  15  18  10   8  71]]
-Node Classification on random seed  1657 -> 0.612
-Confusion Matrix:
- [[ 52   4   7   8   4  16  16]
- [  1 137   5   1   2   3   6]
- [ 29  22 172  25  17  32  25]
- [  8   4  25 107   2   8   8]
- [  1  11   7   1  51   3   5]
- [ 10   1   5   5   2  35   4]
- [ 10   2  14   7   6  16  58]]
-Node Classification on random seed  1658 -> 0.614
-Confusion Matrix:
- [[ 72   2   7   0   4  17   5]
- [  0 130   8   2   9   3   7]
- [ 28  15 133  50  33  15  40]
- [ 15   3   7 100   9   9  17]
- [  0   6   6   0  60   0   2]
- [  7   1   0   0   1  40   3]
- [ 13   2   4   5  10  21  79]]
-Node Classification on random seed  1659 -> 0.578
-Confusion Matrix:
- [[ 53   2   8   2   1  13  12]
- [  5 139   6   9   7   5   8]
- [ 21  24 130  37  14  37  50]
- [ 15   1  20  79  17   5  28]
- [  1   5   5   2  61   0   2]
- [  9   0   1   4   1  41   7]
- [  5   2   8   6   5  12  75]]
-Node Classification on random seed  1660 -> 0.633
-Confusion Matrix:
- [[ 60   3   9   5   8   8  10]
- [  9 121   4   6   6   3   3]
- [ 26  21 156  29  11  21  44]
- [ 10   3  12 114   8   5  17]
- [  2  12   5   3  52   2   2]
- [  4   1   7   2   0  47   1]
- [  3   4  10  10   2  16  83]]
-Node Classification on random seed  1661 -> 0.611
-Confusion Matrix:
- [[ 79   6   4   4   1   6   9]
- [  1 126   1   6   7   1   4]
- [ 18  15 133  41  46  12  50]
- [ 11   2  25 100   2   4  19]
- [  3   3   3   3  71   1   3]
- [  2   2   4   1   0  39   8]
- [ 21   3  10  10  11   6  63]]
-Node Classification on random seed  1662 -> 0.652
-Confusion Matrix:
- [[ 80   2   2   2   4  19   2]
- [  4 137  13   5   7   2   4]
- [ 22  11 153  26  21  30  24]
- [ 10   6  11 109   5   9  15]
- [  0   4   1   1  58   1   4]
- [  8   1   7   0   5  35   3]
- [ 15   1  14   6   4  17  80]]
-Node Classification on random seed  1663 -> 0.593
-Confusion Matrix:
- [[ 63   3   2   3   5   8  21]
- [  2 114  12   6  12   7   4]
- [ 27  19 108  58  35  18  37]
- [ 10   8  10 113   3   6  15]
- [  0  12   5   1  57   2   1]
- [ 12   0   3   1   0  56   1]
- [ 14   2   4   5   4   9  82]]
-Node Classification on random seed  1664 -> 0.634
-Confusion Matrix:
- [[ 74   2   6   5   4  19   3]
- [  5 108   3   2   8   2   5]
- [ 35  12 165  19  30  35  27]
- [ 14   4  12  86  12  14   7]
- [  0   4   0   0  72   1   1]
- [  8   0   8   0   2  55   2]
- [ 10   6  13   3   9  14  74]]
-Node Classification on random seed  1665 -> 0.576
-Confusion Matrix:
- [[ 78   3   9  13   0   3   8]
- [  5 130  10   4   8   1   5]
- [ 36  15 120  46  21  30  41]
- [ 16   2  21  85   0   7  22]
- [  2   5   1   4  56   2   0]
- [  9   0   1   2   0  40  11]
- [  9   5   8  17  10  12  67]]
-Node Classification on random seed  1666 -> 0.628
-Confusion Matrix:
- [[ 63   3   5   4   3  12  11]
- [  7 116   2   5  13   5   4]
- [ 10  12 164  58  34  26  34]
- [  8   1  22 107   2   5   8]
- [  0   0   3   2  59   4   1]
- [  7   1   4   2   1  45   8]
- [ 10   3   2   9   5  16  74]]
-Node Classification on random seed  1667 -> 0.574
-Confusion Matrix:
- [[ 63   3   4   4   4   6  18]
- [  1 138   4   5   8   1   7]
- [ 16  30 114  42  36  27  38]
- [ 16   2  23  92  12   9  15]
- [  1  10   3   0  52   2   1]
- [  0   3   1   4   2  45   4]
- [ 10   4   4   9  22  15  70]]
-Node Classification on random seed  1668 -> 0.591
-Confusion Matrix:
- [[ 58   3   4   9   4  19   8]
- [  4 122   7   4  11   3   1]
- [ 28  34 134  14  53  22  31]
- [  8   5  19 101  12   5   7]
- [  1   8   2   1  58   0   0]
- [  7   2  11   2   4  35   6]
- [  5   4   6   8  10  17  83]]
-Node Classification on random seed  1669 -> 0.665
-Confusion Matrix:
- [[ 79   4   6   5   0   2   9]
- [  2 131   6   1   4   1   3]
- [ 36  23 150  38  13  17  30]
- [  8   2   8 125  10   4  13]
- [  1   3   1   3  55   1   7]
- [  3   3   3   4   0  39  10]
- [  4   2  14   9   8  14  86]]
-Node Classification on random seed  1670 -> 0.626
-Confusion Matrix:
- [[ 69   1  10   8   3   9   4]
- [  6 137   3   5   2   7  10]
- [ 11  35 111  52  28  16  45]
- [  2   4  15 112   2   8  10]
- [  1   4   3   1  58   1   5]
- [  2   0   2   2   0  53   3]
- [ 17   4   5   8   3  17  86]]
-Node Classification on random seed  1671 -> 0.638
-Confusion Matrix:
- [[ 68   2   7   5   6  15   9]
- [  5 114   3   1  12   4   4]
- [ 28  19 163  22  29  14  38]
- [  9   1  19 105   4   7   8]
- [  1   8   2   2  63   3   6]
- [  2   2   4   0   0  42   3]
- [ 18   3   6  10   4  17  83]]
-Node Classification on random seed  1672 -> 0.618
-Confusion Matrix:
- [[ 75   5  12   9   4   7   9]
- [  4 132   3   3  11   1   4]
- [ 26  21 151  40  27  18  32]
- [ 10   6  12  97   1  13  12]
- [  0   2   8   3  54   2   3]
- [  4   0   4   3   2  37   7]
- [ 11   3  15  13   6   6  72]]
-Node Classification on random seed  1673 -> 0.628
-Confusion Matrix:
- [[ 68   4   1   3   4  19  12]
- [  4 116   1   1  17   1   3]
- [ 23  19 129  18  52  19  43]
- [  6   8   6 120   6   6  14]
- [  1   3   4   1  68   0   1]
- [  3   0   4   0   0  45   8]
- [ 14   2   7  14  12   8  82]]
-Node Classification on random seed  1674 -> 0.618
-Confusion Matrix:
- [[ 82   3   4   1   2  16   6]
- [  1 127   6   0  17   6   7]
- [ 25  26 160  27  17  39  18]
- [ 23  10  15  76   2   7  12]
- [  1   3   5   1  63   0   3]
- [  4   0   1   1   1  49   4]
- [  9   8  13   8  10  20  61]]
-Node Classification on random seed  1675 -> 0.594
-Confusion Matrix:
- [[ 86   2   4   9   1   9   6]
- [  5 132   2   4   9   4   7]
- [ 30  17 121  54  24  25  33]
- [ 19  10  13  85  14   7  18]
- [  0   4   1   0  51   4   4]
- [  6   1   0   3   0  53   1]
- [ 12   2   3  17   6  16  66]]
-Node Classification on random seed  1676 -> 0.599
-Confusion Matrix:
- [[ 63   4   4   4   3  17  11]
- [  3 115   3   0  11   6   6]
- [ 24  12 157  59  19  24  42]
- [ 17   2  21  93   1   5  14]
- [  4   5   6   0  58   0   2]
- [  7   4   2   3   1  41   2]
- [ 15   9  11  11   4   3  72]]
-Node Classification on random seed  1677 -> 0.604
-Confusion Matrix:
- [[ 77   1   0   6   8  11   5]
- [  5 126   9   3   6   0   8]
- [ 23  19 132  33  17  30  48]
- [ 10   1  26  92   2   7  22]
- [  4   6   2   2  62   0   2]
- [  9   0   1   1   0  44   4]
- [ 17   8   7   6   7  20  71]]
-Node Classification on random seed  1678 -> 0.629
-Confusion Matrix:
- [[ 71   3   1   6   1   8   7]
- [  7 147   7   5   6   1  10]
- [ 25  22 120  43  17  28  41]
- [ 22   2  12  98   1   7  13]
- [  1   9   7   1  59   1   0]
- [  3   0   0   2   0  44   9]
- [  7   2  12   6   5  11  90]]
-Node Classification on random seed  1679 -> 0.613
-Confusion Matrix:
- [[ 80   3   7   0   2  12  12]
- [  4 127   7   2  13   3   1]
- [ 18  29 140  44  24  31  40]
- [  7   4  10 112   2   7  10]
- [  3   7   3   2  52   1   1]
- [  5   2   1   2   1  50   4]
- [ 10   4   9  12  12  16  52]]
-Node Classification on random seed  1680 -> 0.612
-Confusion Matrix:
- [[ 71   3   7   4   4  14  10]
- [  4 142   5   6  10   1   2]
- [ 21  22 147  26  27  28  18]
- [ 15   2  28  82  19  11   7]
- [  1   7   3   1  56   0   3]
- [  3   1   4   6   2  43   5]
- [  9   8  15   7   1  18  71]]
-Node Classification on random seed  1681 -> 0.576
-Confusion Matrix:
- [[ 70   8   5   7   2  11   9]
- [  5 124   6   4  18   3   1]
- [ 41  28 115  26  43  15  38]
- [ 12   7  34  69   8   5   6]
- [  1   9   3   0  66   0   1]
- [  4   1   1   6   0  43   3]
- [  9   3   5  20   7   9  89]]
-Node Classification on random seed  1682 -> 0.578
-Confusion Matrix:
- [[ 64   2   4   5   3  13   8]
- [  5 118   8   3  14   0   5]
- [ 28  30 111  34  31  33  40]
- [ 10   3  12 100   8   6  17]
- [  1   6   7   2  73   0   5]
- [  3   1   4   2   2  47   3]
- [  6   5  12  11   9  21  65]]
-Node Classification on random seed  1683 -> 0.66
-Confusion Matrix:
- [[ 68   2   6   6   5  10   6]
- [  5 132   4   1   4   1   4]
- [ 26  23 164  22  26  19  29]
- [ 12   9  11 115   2   5   9]
- [  2   2   3   2  63   1   5]
- [  7   3  10   0   1  35  10]
- [ 13   4  12   5   3  10  83]]
-Node Classification on random seed  1684 -> 0.622
-Confusion Matrix:
- [[ 88   7   5   4   3   4  17]
- [  1 122   6   2   6   3   5]
- [ 21  19 163  31  30  25  44]
- [ 10   6  14  94   8   3  13]
- [  1   5   2   6  47   0   1]
- [  3   3   1   4   1  36   9]
- [ 12  10  10  11   7   5  72]]
-Node Classification on random seed  1685 -> 0.586
-Confusion Matrix:
- [[ 78   4   0   2   2   8   9]
- [  1 129  11   3   7   7   1]
- [ 24  28 109  35  62  32  29]
- [  9   4  17 106   1   5   9]
- [  2  12   2   1  57   6   4]
- [  6   5   2   1   0  40   7]
- [ 10  10   4   8   7  17  67]]
-Node Classification on random seed  1686 -> 0.631
-Confusion Matrix:
- [[ 71   0   2   7   8  13   1]
- [  7 132   4   3   9   7   7]
- [ 18  20 128  33  17  22  57]
- [ 12   2  12 104   3   4  20]
- [  4   3   2   1  68   0   2]
- [  2   1   2   0   1  56   4]
- [  7   1  10  18   7  16  72]]
-Node Classification on random seed  1687 -> 0.587
-Confusion Matrix:
- [[ 62   3   2  13   6   6   8]
- [  1 150   3   2   8   1   3]
- [ 25  37 136  51  23  16  46]
- [ 16  10  11  75   8   4  20]
- [  2   6   5   0  51   2   1]
- [  7   1   6   1   4  48   4]
- [ 13   4  12   9   3  10  65]]
-Node Classification on random seed  1688 -> 0.594
-Confusion Matrix:
- [[ 77   3   2   6   3   9  14]
- [  6 124   6   2   4   5   2]
- [ 23  22 120  52  21  39  28]
- [ 15   6  17 114   2  11   8]
- [  2   9   5   1  51   1   3]
- [  6   3   4   2   2  44   6]
- [  8   7   8   7  13  13  64]]
-Node Classification on random seed  1689 -> 0.588
-Confusion Matrix:
- [[ 56   1   4   4   6  26  14]
- [ 11 129   4   2   4   3   6]
- [ 17  17 137  57   8  39  36]
- [ 14   7  13  92   6  12  15]
- [  0   6   4   0  54   2   3]
- [  3   2  10   1   0  54   4]
- [  7   4   9   8   3  20  66]]
-Node Classification on random seed  1690 -> 0.619
-Confusion Matrix:
- [[ 74   3   3   6   1  14   6]
- [  2 117   5   3  19   1   1]
- [ 22  39 158  25  17  27  31]
- [ 10   7  10 112   5   0  18]
- [  3   7   3   5  51   0   1]
- [  8  12   3   1   0  32   8]
- [ 10   3   6   9   9  18  75]]
-Node Classification on random seed  1691 -> 0.654
-Confusion Matrix:
- [[ 66   1   0   5   3  17   9]
- [  7 130   3   0   8   6   3]
- [ 22  17 144  47  20  19  33]
- [  7   3  15 116   6   2  17]
- [  3   5   3   0  67   0   4]
- [ 11   2   2   0   0  47   2]
- [  7   3   4  13   7  10  84]]
-Node Classification on random seed  1692 -> 0.632
-Confusion Matrix:
- [[ 65   4   1   2   5  19  12]
- [  4 128   6   3  17   0   1]
- [ 27  11 157  37  40   8  42]
- [  4   3   7 101   9   6  20]
- [  3   5   8   0  63   1   0]
- [  7   1   1   0   0  47   6]
- [ 16   3   8   7   5   9  71]]
-Node Classification on random seed  1693 -> 0.579
-Confusion Matrix:
- [[ 69   7   5   8   1   6  10]
- [  2 134   6   1   3   3   7]
- [ 27  27 133  26  33  10  44]
- [ 19   7  28  87   1   7  22]
- [  2  10   2   4  38   2   3]
- [ 14   2   1   1   0  48   9]
- [ 27   5   3  16   4   6  70]]
-Node Classification on random seed  1694 -> 0.578
-Confusion Matrix:
- [[ 94   1   3   3   5   7  10]
- [ 10 112  11   0   8   3   7]
- [ 39  22  98  40  29  36  45]
- [  7   3  13  92   4  12  12]
- [  4  10   2   4  53   2   2]
- [  9   2   4   2   1  43   3]
- [ 13   8   5   3   4  14  86]]
-Node Classification on random seed  1695 -> 0.628
-Confusion Matrix:
- [[ 76   3   9   7   6  12   4]
- [  5 125   2   1   5   5   4]
- [ 42  17 149  39  30  23  20]
- [ 10   4  12 116   9   6  10]
- [  0   6   5   1  55   0   2]
- [  3   0   1   1   2  46   8]
- [ 13   2   6  13   7  17  61]]
-Node Classification on random seed  1696 -> 0.619
-Confusion Matrix:
- [[ 65   2  12   5   3  20   5]
- [  2 139   3   4   5   4   6]
- [ 15  18 162  38  18  25  39]
- [ 16   3  22  83  13   3  18]
- [  3   9   6   1  57   0   3]
- [  6   2   1   3   0  51   1]
- [  6   3  10   7   5  16  62]]
-Node Classification on random seed  1697 -> 0.619
-Confusion Matrix:
- [[ 83   4   0   2   3   2   6]
- [  3 129   2   6  13   3   2]
- [ 13  32 130  53  15  23  44]
- [  8   7  19 105   9   6  20]
- [  0   5   9   0  48   0   3]
- [ 10   2   7   2   0  45   2]
- [ 15   4   4   7   6  10  79]]
-Node Classification on random seed  1698 -> 0.588
-Confusion Matrix:
- [[ 79   5   1   3   4  11  12]
- [  7 132   6   0  12   2   2]
- [ 27  20 100  52  30  28  56]
- [ 10   3  11 101   9  11  13]
- [  0   2   5   0  58   0   2]
- [  2  11   4   0   3  47   0]
- [  9   4   5   2  14  14  71]]
-Node Classification on random seed  1699 -> 0.636
-Confusion Matrix:
- [[ 91   2   3   1   6   6   7]
- [ 11 125   5   1   3   3   5]
- [ 37  22 170  18  24  17  40]
- [ 13   3   7 103   7   8  10]
- [  1  13   4   1  43   0   3]
- [  7   6   4   0   2  45   7]
- [ 16   1  10   9   9  12  59]]
-Node Classification on random seed  1700 -> 0.647
-Confusion Matrix:
- [[ 74   1   9  10   1  23   9]
- [  3 134   5   3  11   6   2]
- [ 25  13 140  38  31   9  36]
- [ 17   6   7 117   3   5  13]
- [  0   3   1   2  69   1   3]
- [  8   0   1   0   0  36   2]
- [ 18   4   4   5   5  10  77]]
-Node Classification on random seed  1701 -> 0.621
-Confusion Matrix:
- [[ 74   4   5   5   3   8   6]
- [  4 129   5   0   9   5   3]
- [ 26  25 125  48  29  22  42]
- [ 16   3  11 114   2   5  15]
- [  2   5   5   0  56   1   6]
- [  2   0   7   4   1  39   3]
- [  7   1   9   4  12   9  84]]
-Node Classification on random seed  1702 -> 0.572
-Confusion Matrix:
- [[ 71   5   9   4   8  10  12]
- [  8 130   8   4  12   2   2]
- [ 16  14 104  57  18  40  42]
- [ 24   7  19  87   7   7  15]
- [  0   6   5   0  74   0   4]
- [  5   1   2   3   1  43   3]
- [ 16   4   7   4   7  10  63]]
-Node Classification on random seed  1703 -> 0.624
-Confusion Matrix:
- [[ 61   0   7  11   1   7   7]
- [  4 123   2   6   5   5   6]
- [ 17  21 148  43  23  32  31]
- [ 11   2  13 116   4   6  16]
- [  5   9   4   3  60   0   1]
- [  5   1   4   4   3  50   3]
- [ 14   3   7   5  15  10  66]]
-Node Classification on random seed  1704 -> 0.63
-Confusion Matrix:
- [[ 92   4   4   2   8   6   6]
- [  2 122   3   3  12   4   3]
- [ 20  26 123  31  36  25  29]
- [ 18   6   9 105   9   3   8]
- [  1   5   1   3  65   0   2]
- [  4   2   2   3   2  42   7]
- [ 19   5   1  13  10  13  81]]
-Node Classification on random seed  1705 -> 0.628
-Confusion Matrix:
- [[ 66   2   3   7  10  10  11]
- [  4 130   6   4  10   3   5]
- [ 21  18 139  28  21   9  53]
- [ 12   3  12 104   4   4  21]
- [  2   3   2  10  68   2   3]
- [  6   1   1   2   0  45   6]
- [  4   5  12  11   7  14  76]]
-Node Classification on random seed  1706 -> 0.627
-Confusion Matrix:
- [[ 78   3   2   2   3  12  13]
- [  3 122   7   2   7   9   3]
- [ 20  25 149  31  19  38  32]
- [ 11   1  15 109   5   5  14]
- [  1   5   4   2  59   1   2]
- [  1   4   1   3   0  51   9]
- [ 11   6  17   4   6  14  59]]
-Node Classification on random seed  1707 -> 0.618
-Confusion Matrix:
- [[ 71   4   6   7  11   4   5]
- [  6 132  14   0   8   0   1]
- [ 32  30 143  26  30  22  38]
- [  9   4  16  95   6   7  14]
- [  1   7   3   0  63   2   4]
- [  4   2   2   0   1  40   4]
- [ 13   4  10   2  11  12  74]]
-Node Classification on random seed  1708 -> 0.63
-Confusion Matrix:
- [[ 65   5  11  18   2   6   5]
- [  9 125   4   4  14   1   4]
- [ 29  12 155  48  46   8  23]
- [ 10   2   4 121   8   7  15]
- [  1   6   4   1  61   0   1]
- [  4   1   3   0   3  41   4]
- [ 14   4   8   3   6  12  62]]
-Node Classification on random seed  1709 -> 0.617
-Confusion Matrix:
- [[ 72   1   3  10   2  10   5]
- [ 10 128   7   0  10   7   7]
- [ 24  27 137  31  18  41  31]
- [ 13   8  11  96   6   9  10]
- [  0   2   2   3  67   1   5]
- [  6   1   4   1   1  46   6]
- [ 20   5   9   4   5   7  71]]
-Node Classification on random seed  1710 -> 0.615
-Confusion Matrix:
- [[ 75   2   2   5   5   9   6]
- [  6 128   5   1   5   3   1]
- [ 20  34 153  35  18  24  45]
- [ 17   8  13  77   6   5  18]
- [  1   8   7   4  50   2   1]
- [  2   1   4   2   0  47   6]
- [ 14   4  16   9   6   5  85]]
-Node Classification on random seed  1711 -> 0.674
-Confusion Matrix:
- [[ 74   2   3   3   3  18   5]
- [  5 125   9   2   5   1   3]
- [ 24  16 203  21  16  22  43]
- [  3   1  21 111   2   9   9]
- [  2   4  10   0  49   0   3]
- [  4   0   0   0   1  41  10]
- [ 10   3  14   6   6   7  71]]
-Node Classification on random seed  1712 -> 0.609
-Confusion Matrix:
- [[ 60   3   5   7   2  15  10]
- [  6 152   1   7   2   3   6]
- [ 17  29 122  43  25  35  19]
- [  7   8  12 102  11  14  17]
- [  0  13   2   1  45   1   4]
- [  1   4   1   2   1  46   3]
- [ 18   4   6   8   5  13  82]]
-Node Classification on random seed  1713 -> 0.6
-Confusion Matrix:
- [[ 77   3   0   3   5   9   9]
- [  5 128   7   5  11   3   2]
- [ 29  26 112  55  16  15  49]
- [ 18   6   9  97   4   6  12]
- [  2   6   3   3  64   0   6]
- [  9   1   0   1   3  35  14]
- [ 20   6   9   2   5   3  87]]
-Node Classification on random seed  1714 -> 0.622
-Confusion Matrix:
- [[ 59   3   1   7  11   9  25]
- [  4 133   3   8  10   1   4]
- [ 14  16 141  41  14  25  56]
- [  9   3  18  90   9   4  23]
- [  0   8   2   3  57   0   2]
- [  3   2   1   1   0  51   9]
- [  6   5   2   4   5   7  91]]
-Node Classification on random seed  1715 -> 0.619
-Confusion Matrix:
- [[ 80   9   7   2   1  10   7]
- [  6 127   2   6  13   2   5]
- [ 14  25 141  33  44  18  24]
- [  5   4  24  93   9   3  22]
- [  0   5   3   1  73   1   3]
- [  7   1   4   0   3  39   4]
- [ 18   2   8   5   9  12  66]]
-Node Classification on random seed  1716 -> 0.636
-Confusion Matrix:
- [[ 61   1   2   9   5  15   8]
- [  2 130   4   2   5   3   9]
- [ 22  16 137  46  18  12  51]
- [ 14   3  15 110   1   8  20]
- [  3   4   3   1  58   2   2]
- [  4   0   1   1   1  54   8]
- [  8   2  10   4   5  14  86]]
-Node Classification on random seed  1717 -> 0.632
-Confusion Matrix:
- [[ 86   0   4   8   1  15   6]
- [  4 125   4   4   7   3   4]
- [ 19  23 137  31  25  34  44]
- [ 13   3  17 108   3   8  13]
- [  2   4   1   1  63   0   4]
- [  5   1   1   2   2  42   3]
- [  8   5   5  10   7  14  71]]
-Node Classification on random seed  1718 -> 0.602
-Confusion Matrix:
- [[ 51   0   4   6   6  22   5]
- [  7 131   5   3  15   8   5]
- [ 21  10 130  22  36  16  59]
- [ 12   6  16 106  19   7  13]
- [  1   1   3   0  69   0   3]
- [  4   0   1   1   1  38   7]
- [ 12   1   4   6  12  18  77]]
-Node Classification on random seed  1719 -> 0.637
-Confusion Matrix:
- [[ 72   1   6   4   4   9  12]
- [  1 142   8   1  13   5   3]
- [ 23  25 131  35  27  22  37]
- [  7   2  15 112   4   5   9]
- [  3   3   3   2  61   0   1]
- [  8   1   1   1   1  37   7]
- [  7   2  10  11   7  17  82]]
-Node Classification on random seed  1720 -> 0.633
-Confusion Matrix:
- [[ 71   5   7   4   3   4  13]
- [ 11 122   6   1   3   2   8]
- [ 19   9 157  31  31  18  22]
- [ 12   0  15 114   2  17  10]
- [  1  12   3   1  56   1   2]
- [ 10   0   2   1   0  47   6]
- [ 14   4   5   8   9  35  66]]
-Node Classification on random seed  1721 -> 0.622
-Confusion Matrix:
- [[ 85   1   7   2   3   8   7]
- [  6 138   3   2   4   2   3]
- [ 20  24 124  42  33  19  40]
- [ 17   4  11 102   5   2  13]
- [  0  12   4   0  54   1   0]
- [  7   3   0   4   1  35   5]
- [ 14   1  12  12   9  15  84]]
-Node Classification on random seed  1722 -> 0.642
-Confusion Matrix:
- [[ 80   0   7   3   2   9   4]
- [  8 108   7   1  13   5   3]
- [ 26  18 160  35  27  13  40]
- [ 13   1  18 114   5   0  13]
- [  1   1   1   3  65   0   5]
- [  9   6   4   0   1  35   9]
- [ 17   5   7   2   5  11  80]]
-Node Classification on random seed  1723 -> 0.589
-Confusion Matrix:
- [[ 58   0   6   3   5  19  10]
- [ 13 114  13   5   6   2   6]
- [ 23  19 159  25  20  33  58]
- [ 26   3  14  95   6   6   9]
- [  3   2   3   0  60   2   4]
- [  3   2   5   1   1  45   4]
- [ 11   2   6   4   2  26  58]]
-Node Classification on random seed  1724 -> 0.623
-Confusion Matrix:
- [[ 73   1   7   9   1  10   7]
- [ 12 127   4   3   4   1   3]
- [ 39  18 128  31  27  20  43]
- [ 18   5  15  99   1   5  22]
- [  3   6   4   1  66   0   5]
- [  2   1   1   4   1  42   4]
- [ 14   4   8   5   2   6  88]]
-Node Classification on random seed  1725 -> 0.601
-Confusion Matrix:
- [[ 67   1   8   6   3  10  11]
- [ 10 126   5   3   2   3   8]
- [ 16  17 133  53  28  24  41]
- [ 16   0   6 104   3   5  14]
- [  2   4   5   3  67   0   0]
- [ 11   2   2  12   0  41   5]
- [ 12   8  10  10   3  17  63]]
-Node Classification on random seed  1726 -> 0.643
-Confusion Matrix:
- [[ 64   2   4   0   1   8  18]
- [  5 125   4   1   8   2   2]
- [ 26  16 161  38  25  17  36]
- [ 11   3  16  85  12   4  19]
- [  6   6   4   0  62   0   2]
- [  1   4   1   0   3  56   6]
- [  4   2  10   3  11  16  90]]
-Node Classification on random seed  1727 -> 0.591
-Confusion Matrix:
- [[ 62   2   3   4   5  11  17]
- [  9 130   3   0  17   3   5]
- [ 26  28 132  22  31  26  45]
- [ 13  10  10 101  11  12  10]
- [  0   2   3   2  61   2   3]
- [  5   0   4   6   2  35   2]
- [ 11   4  11  14   5  10  70]]
-Node Classification on random seed  1728 -> 0.644
-Confusion Matrix:
- [[ 59   4   1   5   3  17   9]
- [  3 119   4   3   9   1   1]
- [ 25  26 145  26  30  18  47]
- [  6   4  15 119   0  12   6]
- [  1   3   2   2  65   2   4]
- [  8   0   0   2   0  45   6]
- [ 16   2   6   6   6  15  92]]
-Node Classification on random seed  1729 -> 0.645
-Confusion Matrix:
- [[ 77   3   4   7   4   9  12]
- [  1 137   2   2   1   5   1]
- [ 28  18 134  32  17  25  47]
- [ 13   2  13 115   6   9   8]
- [  2   9   5   3  59   1   2]
- [  5   2   2   1   0  47   2]
- [  9   4   9  11   4  15  76]]
-Node Classification on random seed  1730 -> 0.627
-Confusion Matrix:
- [[ 60   3   6   1   8   7  14]
- [  6 116  11   6   7   1   6]
- [ 25  16 155  26  31  20  35]
- [ 16   5   5 118   5   9   8]
- [  2   5   5   3  70   2   0]
- [  4   2   1   1   0  38   4]
- [ 11   3   6   7  17  23  70]]
-Node Classification on random seed  1731 -> 0.617
-Confusion Matrix:
- [[ 84   1   2  12   2   4   3]
- [  4 113  13   1  10   1   2]
- [ 33  23 131  33  31  13  50]
- [  6   3  15 103   8   6  12]
- [  4   8   6   1  68   0   2]
- [  7   0   2   2   1  45   1]
- [ 11   1  12   8  14  15  73]]
-Node Classification on random seed  1732 -> 0.616
-Confusion Matrix:
- [[ 83   1   7  16   0   7   5]
- [  7 126  10   3   9   5   3]
- [ 25  14 123  34  27  18  37]
- [ 28   5  11 101   3   9  18]
- [  3   6   1   3  56   1   0]
- [  4   0   1   2   0  51   2]
- [ 14   3   6  13   4  19  76]]
-Node Classification on random seed  1733 -> 0.637
-Confusion Matrix:
- [[ 71   3   1   5   3   6  12]
- [  2 131  13   1   9   0   6]
- [ 16  13 156  23  38  22  50]
- [  6   2  19 110   3   3   4]
- [  1   3   9   4  60   0   2]
- [  9   1   2   8   0  33   2]
- [ 13   6  12   7  13  11  76]]
-Node Classification on random seed  1734 -> 0.629
-Confusion Matrix:
- [[ 55   6   7   3   3  20   3]
- [  3 133   8   2   5   1   4]
- [ 28  15 146  40  21  20  43]
- [ 12   5  18  92   6  13  10]
- [  1  12   4   0  61   4   0]
- [  6   0   3   1   2  52   6]
- [  3   1   5   8   2  17  90]]
-Node Classification on random seed  1735 -> 0.6
-Confusion Matrix:
- [[ 57   4   9   7  10  13  10]
- [  3 117   2   7   7   4   5]
- [ 33  17 132  55  14  29  36]
- [ 10   3   6 113   3   6  15]
- [  0   4   2   4  63   0   3]
- [  5   0  11   2   0  41   8]
- [  6   3   9   6   6  23  77]]
-Node Classification on random seed  1736 -> 0.625
-Confusion Matrix:
- [[ 64   0   8  11   3  11   5]
- [  7 117   3  10   5   8   5]
- [ 22  10 155  40  25  25  46]
- [  7   8   9 107   7   7  12]
- [  1   5   4   5  70   0   1]
- [ 10   1   1   1   0  40   3]
- [ 24   4   2   5   7   7  72]]
-Node Classification on random seed  1737 -> 0.602
-Confusion Matrix:
- [[ 62   5   4   6   5  12   8]
- [  2 147  12   1   3   1   7]
- [ 30  32 126  37  23  28  31]
- [  4   2  28  99  11   1   9]
- [  2   9   8   1  56   3   2]
- [  6   0   1   4   1  45   5]
- [ 12   4  10  10   2  16  67]]
-Node Classification on random seed  1738 -> 0.658
-Confusion Matrix:
- [[ 66   2   5   3   3  14   5]
- [  3 128   8   3   2   8   3]
- [ 36  12 169  23  12  25  40]
- [  9   6  15 120   5   1  21]
- [  1   7   4   3  56   1   2]
- [ 10   0   0   5   2  40   2]
- [ 10   6   2   4   5  14  79]]
-Node Classification on random seed  1739 -> 0.598
-Confusion Matrix:
- [[ 74   2   4   4   3   7   9]
- [  4 111  14   7  21   3   5]
- [ 18  21 157  37  18  24  49]
- [ 15   1  13  77   8  12  13]
- [  1   6   5   1  61   2   4]
- [  5   0   3   2   5  36   4]
- [  9   4   8  11   7  13  82]]
-Node Classification on random seed  1740 -> 0.609
-Confusion Matrix:
- [[ 75   5   3   1   1   7   9]
- [  4 143   8   0   9   0   3]
- [ 19  25 130  36  13  44  44]
- [ 13   8  25  86   3   7  12]
- [  0   6   4   2  49   1   3]
- [  8   1   0   0   0  55  14]
- [ 10   2   7  10   5  19  71]]
-Node Classification on random seed  1741 -> 0.603
-Confusion Matrix:
- [[ 68   4   0   6   7   8  17]
- [ 10 113   9   5   8   3   5]
- [ 24  18 147  47  16  17  39]
- [ 17   1  27  97   2   2   6]
- [  3   5  10   0  57   1   5]
- [  3   0   5   1   0  49   5]
- [ 10   6   9  17   4  15  72]]
-Node Classification on random seed  1742 -> 0.608
-Confusion Matrix:
- [[ 96   5   1   1   2   6   4]
- [  6 116  11   3  10   2   5]
- [ 30  44 125  26  25  15  44]
- [ 25  13   9  94   2   3  13]
- [  0   8   3   0  60   1   1]
- [ 10   5   1   2   1  36   5]
- [ 16   3   6   5   6  14  81]]
-Node Classification on random seed  1743 -> 0.621
-Confusion Matrix:
- [[ 55   4   7   3   3  19  10]
- [  9 143   5   1   5   3   5]
- [ 15  22 152  20  24  18  51]
- [ 15   3  15  84   2   7  18]
- [  5   6   2   1  66   0   2]
- [  3   4   1   0   0  44  11]
- [ 16   6   7   4   8  19  77]]
-Node Classification on random seed  1744 -> 0.6
-Confusion Matrix:
- [[ 75   2   0   9   4   9  16]
- [  3 134   8   5   1   4   2]
- [ 20  19 122  40  45  21  39]
- [  8   5  15  97   4  12  12]
- [  1   8   3   3  57   3   1]
- [  4   1   2   1   4  46   4]
- [ 10   4  11  19   6  12  69]]
-Node Classification on random seed  1745 -> 0.595
-Confusion Matrix:
- [[ 69   4   1   1   5  20  10]
- [  2 128   4   0   8   5   1]
- [ 30  32 137  28  18  27  29]
- [ 10   0  15  98   9  14  18]
- [  0   7   4   0  57   0   4]
- [  0   2   7   4   1  55   2]
- [  4   5  28   4  19  23  51]]
-Node Classification on random seed  1746 -> 0.622
-Confusion Matrix:
- [[ 65   7  13   6   0   5  12]
- [  3 133   0   3   9   4   1]
- [ 17  26 138  48  23  17  43]
- [  7   5  11 112   0   2  11]
- [  0  10   1   7  61   0   8]
- [ 12   3   3   0   0  46   5]
- [ 10   2   8   9  12  15  67]]
-Node Classification on random seed  1747 -> 0.616
-Confusion Matrix:
- [[ 69   2   3   5   9   8   7]
- [  2 130   3   1   9   1   2]
- [ 28  16 140  26  45  25  52]
- [ 10   6  12 102   8   6  14]
- [  0   8   2   2  57   2   1]
- [ 10   1   2   1   0  40   4]
- [ 13   5   6   4   7  16  78]]
-Node Classification on random seed  1748 -> 0.623
-Confusion Matrix:
- [[ 54   3   1   5   4  14  12]
- [  5 138  10   6   1   3   4]
- [ 28  19 133  45  26  15  39]
- [  6   5  11 102  14   4  17]
- [  2   7   3   2  59   0   0]
- [  4   1   3   0   6  46   2]
- [ 13   4  11   8   2  12  91]]
-Node Classification on random seed  1749 -> 0.605
-Confusion Matrix:
- [[ 71   5  10   6   2  10   5]
- [  7 109   5   0   7   5   6]
- [ 23  24 138  33  24  39  27]
- [ 11   4  22 101   4   9  10]
- [  1   3   5   1  65   1   5]
- [ 11   0   5   0   1  55   7]
- [ 18   2   8  14   4  11  66]]
-Node Classification on random seed  1750 -> 0.602
-Confusion Matrix:
- [[ 74   1   4   2   2  14  12]
- [ 16 115   4   2   6   4   1]
- [ 32  27 149  31  25  31  19]
- [ 16   2  16  90   2  12  14]
- [  2   8   4   1  60   0   2]
- [  6   2   0   6   0  41  11]
- [ 17   8   8   5   7  16  73]]
-Node Classification on random seed  1751 -> 0.559
-Confusion Matrix:
- [[ 69   1   5  14   3  15   7]
- [  2 121  15   1   8   1   2]
- [ 30  25 110  44  51  18  31]
- [ 13   2  37  93   3   3  10]
- [  0   3   3   2  65   0   3]
- [  6   2   2   1   1  40   7]
- [ 13   2  12   8  15  20  61]]
-Node Classification on random seed  1752 -> 0.603
-Confusion Matrix:
- [[ 66   7   4   3   9  12   9]
- [  4 111   4   1  17   6   1]
- [  9  43 125  44  24  33  31]
- [  4  11  16 114   1   5  11]
- [  2   6   3   0  60   2   1]
- [  2   6   1   2   1  48   6]
- [ 16   5  15   4   5  11  79]]
-Node Classification on random seed  1753 -> 0.6
-Confusion Matrix:
- [[ 59   1   2   7   2   8  25]
- [  4 121   8   3   7   2   7]
- [ 22  20 144  42  25  26  35]
- [ 12  10  12  93   4   7   5]
- [  4   7   6   3  62   1   6]
- [  3   2   1   1   0  53   7]
- [ 11   6   8  11   8  19  68]]
-Node Classification on random seed  1754 -> 0.584
-Confusion Matrix:
- [[ 71   1   2   5   2  12  22]
- [  6 117   3   2  19   3   5]
- [ 28  28 128  52  33  23  26]
- [ 14   1  18 101   5   9   5]
- [  4   2   3   3  64   0   3]
- [ 13   0   0   8   6  31   1]
- [ 18   4   7  11   3   6  72]]
-Node Classification on random seed  1755 -> 0.624
-Confusion Matrix:
- [[ 67   1   5   3   9  12  10]
- [  4 126   6   8   5   2   3]
- [ 22  16 155  32  22  15  40]
- [ 18   2  21  97   7   2  16]
- [  2   5   5   5  68   1   2]
- [  7   3   0   0   2  28  16]
- [ 11   4  11   3   9   9  83]]
-Node Classification on random seed  1756 -> 0.609
-Confusion Matrix:
- [[ 77   2   2   4   2   5  11]
- [ 14 114  10   0   9   2   9]
- [ 36  12 137  28  36  18  39]
- [ 14   6   7 105  11   6  15]
- [  1   4   1   1  56   0   4]
- [ 13   2   3   2   2  42   5]
- [ 12   1   9   4  11  18  78]]
-Node Classification on random seed  1757 -> 0.626
-Confusion Matrix:
- [[ 74   3   3   3   2  11   4]
- [  5 132   5   7   4   2   1]
- [ 35  18 136  44  22  24  35]
- [ 18   3  19  99   3   9  15]
- [  3   6   2   2  60   3   6]
- [  2   3   0   0   0  42  12]
- [  7   5   8   6   7   7  83]]
-Node Classification on random seed  1758 -> 0.615
-Confusion Matrix:
- [[ 63   3   1  14   7  15   4]
- [  5 131   8   6   8   6   1]
- [ 14  20 159  32  21  31  39]
- [ 14   2  19 107   4   9   4]
- [  2  12   3   1  54   1   1]
- [  8   3   1   2   3  35   6]
- [ 13   1   2   6   9  24  66]]
-Node Classification on random seed  1759 -> 0.613
-Confusion Matrix:
- [[ 74   3   6   7   1  11   5]
- [  4 127   2   4   4   1   4]
- [ 29  27 137  24  32  31  39]
- [ 17   6  22 101   3   7   9]
- [  1  12   2   6  54   0   2]
- [ 10   2   0   1   4  47   2]
- [ 11   2  11   8   2  13  73]]
-Node Classification on random seed  1760 -> 0.589
-Confusion Matrix:
- [[ 77   6   9   7   3  12   9]
- [  5 121   5   4   4   2   4]
- [ 45  29 114  37  22  25  37]
- [ 14   4   9 100   8   4  18]
- [  1   7   4   1  58   0   5]
- [ 10   0   0   1   0  37  11]
- [ 17   7  10   4   6   5  82]]
-Node Classification on random seed  1761 -> 0.655
-Confusion Matrix:
- [[ 65   4   1   9   9  13  17]
- [  1 133   3   0   9   4   8]
- [ 23  32 175  17  17  14  36]
- [ 13   2  13 107   2   7  14]
- [  2   4   4   0  54   0   4]
- [  3   0   1   3   0  39   6]
- [  7   3   9   5   7  19  82]]
-Node Classification on random seed  1762 -> 0.651
-Confusion Matrix:
- [[ 97   2   2   5   0   8   2]
- [  8 139   8   1   7   1   2]
- [ 28  15 133  43  20  22  34]
- [ 17   4  11 112   2   3  15]
- [  2   7   8   2  52   2   1]
- [  3   2   4   1   4  38   9]
- [ 14   1   4  10   4  11  80]]
-Node Classification on random seed  1763 -> 0.61
-Confusion Matrix:
- [[ 54   2   7   9   9  20  10]
- [  0 134   3   5  15   4   7]
- [ 13  17 139  22  39  19  41]
- [ 16  11  18 101   5   4  11]
- [  0   4   2   1  64   3   6]
- [  2   2   0   2   2  41   8]
- [  9   5   7  11   9  10  77]]
-Node Classification on random seed  1764 -> 0.578
-Confusion Matrix:
- [[ 62   1   1  10   4  11  16]
- [  6 111   7   3   6   5   2]
- [ 17  19 136  32  24  17  81]
- [ 12   5  14 121   5  11  12]
- [  1   5   2   0  45   1   4]
- [ 10   2   1   0   0  47   8]
- [ 12   5   3  22   9  16  56]]
-Node Classification on random seed  1765 -> 0.625
-Confusion Matrix:
- [[ 78   2   1   3   5   7  16]
- [  5 134   7   2   3   4   3]
- [ 34  14 134  24  34  29  38]
- [ 15   7   5 123   3   7  17]
- [  1   6   3   5  50   1   0]
- [  6   3   4   1   0  33  11]
- [ 20   4   5   8   4   8  73]]
-Node Classification on random seed  1766 -> 0.587
-Confusion Matrix:
- [[ 62   2   6  14   4   6  11]
- [ 11 109   7   4  29   5   4]
- [ 19  34 132  41  30  23  33]
- [  9   4   6 119   3   4   6]
- [  2   3   2   1  59   3   0]
- [  7   1   2   6  11  31   9]
- [ 10   2  15   8   8   8  75]]
-Node Classification on random seed  1767 -> 0.633
-Confusion Matrix:
- [[ 66   2   2  14   4  15  10]
- [  3 135   7   2   4   2   3]
- [ 31  22 157  31  14   9  42]
- [  7   1  22  97   7   6  14]
- [  1  11   3   2  54   3   3]
- [  6   1   3   3   1  41   9]
- [ 10   3   5   9   8  12  83]]
-Node Classification on random seed  1768 -> 0.628
-Confusion Matrix:
- [[ 76   1   3   6  11   6  16]
- [  3 124  10   0   6   0   2]
- [ 12  31 145  37  20  19  34]
- [  8   6  18 119   2   6  11]
- [  0   7   3   1  58   0   5]
- [  4   2   2   3   1  43   6]
- [  9   7  14  17   6  17  63]]
-Node Classification on random seed  1769 -> 0.62
-Confusion Matrix:
- [[ 71   7   2   9  10  11  10]
- [  8 126   4   0  10   2   2]
- [ 21  18 138  44  17  34  25]
- [  3   4  20 116   4   7   9]
- [  0   9   3   0  61   1   2]
- [  3   5   2   4   1  42   2]
- [ 19   1   6  15   7  19  66]]
-Node Classification on random seed  1770 -> 0.67
-Confusion Matrix:
- [[ 82   1   0   4   7   5   3]
- [  3 138   3   2  10   4   5]
- [ 25   9 150  37  25  25  35]
- [  8   2  23 114   8   6   5]
- [  0   4   4   2  60   0   3]
- [  9   2   1   1   1  42   1]
- [ 17   1   5   6   4  14  84]]
-Node Classification on random seed  1771 -> 0.604
-Confusion Matrix:
- [[ 61   3   4   6   6   9  16]
- [  4 124   2   5   3   5   6]
- [ 44  14 145  19  18  49  31]
- [ 19   2  11  96   8   6  15]
- [  4   6   0   1  52   1   3]
- [  9   0   0   1   1  53   8]
- [ 18   2   5   1   7  24  73]]
-Node Classification on random seed  1772 -> 0.615
-Confusion Matrix:
- [[ 75   1  10  11   4   3   5]
- [  6 118   6   0   5   4   0]
- [ 28  19 152  26  22  20  45]
- [  9   0  20  92  14  14  15]
- [  1   5   3   1  54   1   1]
- [  5   1   2   2   1  43   5]
- [ 11   1  13  14  16  15  81]]
-Node Classification on random seed  1773 -> 0.606
-Confusion Matrix:
- [[ 62   2   3   4   7  10  16]
- [  6 130   2   7   6   1   1]
- [ 22  27 107  64  27  21  31]
- [ 14   4  11 110   8   8  10]
- [  3   7   7   3  70   0   0]
- [  1   1   4   1   1  40   9]
- [  7   3   7   9   2  17  87]]
-Node Classification on random seed  1774 -> 0.594
-Confusion Matrix:
- [[ 68   3   5   4   4  13  20]
- [  3 129   4   1   9   3   3]
- [ 17  12 135  47  58  13  41]
- [ 15   5  21  78   9   8   7]
- [  3   4   4   1  63   0   4]
- [  6   1   1   4   1  43   8]
- [  7   1   4   9  14   9  78]]
-Node Classification on random seed  1775 -> 0.589
-Confusion Matrix:
- [[ 75   3   4   6   3  13  13]
- [  5 117  14   0  10   3   6]
- [ 29  20 145  42  13  24  42]
- [ 17   2  14  90  17   6  13]
- [  3   2   5   3  58   2   3]
- [  5   2   3   0   0  48   2]
- [  9   1   3  17   3  29  56]]
-Node Classification on random seed  1776 -> 0.592
-Confusion Matrix:
- [[ 68   1   1  19   8  11  13]
- [  5 130   2   1  10   3   0]
- [ 21  10 109  41  35  25  42]
- [  6   4  23  99   8   5   8]
- [  1   6   3   2  60   1   4]
- [ 15   0   1   1   0  41   9]
- [ 20   4   7  13   6  13  85]]
-Node Classification on random seed  1777 -> 0.62
-Confusion Matrix:
- [[ 67   0   3   5   2   9  17]
- [  3 115   6   4   5   7   2]
- [ 33  13 159  21  33  29  32]
- [ 16   6  17  97   8   5  13]
- [  3   7   6   0  64   1   0]
- [  5   0   2   1   0  55   4]
- [ 10   4   7   5  12  24  63]]
-Node Classification on random seed  1778 -> 0.645
-Confusion Matrix:
- [[ 65   4   3   7   3   9   7]
- [  1 124  10   2   7   5   0]
- [ 20  11 165  25  22  43  23]
- [ 12   6  15 109   5   8  14]
- [  2   2   5   1  54   2   3]
- [  0   3   3   5   1  56   2]
- [ 22   3   7   4   7  21  72]]
-Node Classification on random seed  1779 -> 0.637
-Confusion Matrix:
- [[ 64   4   3   9   6  12  13]
- [  5 137   6   1   6   3   7]
- [ 23  19 136  20  20  22  46]
- [ 22  10  12 112   3  11   5]
- [  0   8   3   1  68   1   2]
- [  7   0   1   1   2  37   9]
- [  6   4   8   7   5  10  83]]
-Node Classification on random seed  1780 -> 0.62
-Confusion Matrix:
- [[ 51   1   0  12   3  14  23]
- [  5 131   5   3   4   0   5]
- [ 23  18 147  22  19  30  49]
- [ 10   7  21 106   5   7  15]
- [  2  11   1   6  59   2   1]
- [  2   1   0   2   2  39  11]
- [  9   3   5   5   6  10  87]]
-Node Classification on random seed  1781 -> 0.612
-Confusion Matrix:
- [[ 75   1   2   9   4  19  11]
- [  4 118   9   2   5   6   1]
- [ 19  32 134  28  32  31  25]
- [ 18   6  27  89   3   5  14]
- [  2   1   3   3  59   2   3]
- [  3   2   3   0   0  47   4]
- [ 15   1   5   7  14   7  90]]
-Node Classification on random seed  1782 -> 0.606
-Confusion Matrix:
- [[ 55   7   5  11   7   7  11]
- [  2 137   6   0   7   0   6]
- [ 24   9 149  39  22   9  42]
- [ 28   7  22  94   6   7   4]
- [  1   8   2   1  63   1   5]
- [  7   0   4   3   0  32  12]
- [ 16   2   8  21   5  10  76]]
-Node Classification on random seed  1783 -> 0.566
-Confusion Matrix:
- [[ 63   7   9   6   8   6  17]
- [  4 135   6   0   5   2   2]
- [ 28  22  89  45  39  12  54]
- [ 20   6   8 109   7   2  11]
- [  1  13   2   1  59   0   3]
- [ 11   3   3   4   5  35   4]
- [ 15   8   7   8   6  14  76]]
-Node Classification on random seed  1784 -> 0.574
-Confusion Matrix:
- [[ 68   5   2   7   3   8   8]
- [  4 127   2   1  20   1   5]
- [ 29  33 111  44  44  24  39]
- [  9   8   7 104   5   5   8]
- [  1   9   5   1  62   0   1]
- [  8   2   1   1   3  35   3]
- [ 21   5   9  12  14   9  67]]
-Node Classification on random seed  1785 -> 0.629
-Confusion Matrix:
- [[ 77   1   3   3   2  18   2]
- [  3 128   4   4   4   3   7]
- [ 19  25 142  24  21  21  45]
- [ 11   9   9 105   2  11  15]
- [  1   4   5   3  71   0   7]
- [  1   2   4   2   2  42   7]
- [  3   5  10  13  21  15  64]]
-Node Classification on random seed  1786 -> 0.633
-Confusion Matrix:
- [[ 85   6   4   6   3  10  10]
- [  1 130   8   2   7   6   4]
- [ 29  20 152  19  32  19  34]
- [ 12   1  16  91   9   3  14]
- [  1  11   4   2  52   1   2]
- [  3   3   4   2   1  53   7]
- [ 18   3   1   5  11  13  70]]
-Node Classification on random seed  1787 -> 0.572
-Confusion Matrix:
- [[ 55   4  11   3  10  13   3]
- [  4 132   5   2   9   3   1]
- [ 17  18 111  43  54  28  41]
- [  6   1  14 102   2   9  23]
- [  0   2   4   6  50   0   2]
- [  4   1   6   1   2  43   8]
- [ 13   5  23   5  11  11  79]]
-Node Classification on random seed  1788 -> 0.62
-Confusion Matrix:
- [[ 72   2   4   0   1  11  18]
- [  4 126   4   1   5   9   2]
- [ 26  17 157  40  21  27  23]
- [  9   4  22  91   6   9  11]
- [  4  10   8   1  58   2   1]
- [ 11   4   2   1   1  40  12]
- [  8   3   6   2  16  12  76]]
-Node Classification on random seed  1789 -> 0.595
-Confusion Matrix:
- [[ 89   3   2   6   7  12   9]
- [  6 120   3   2  13   1   5]
- [ 28  24 106  31  55  24  24]
- [  9   5  17 108   5   3  11]
- [  1   3   3   4  71   0   3]
- [ 14   0   5   1   0  36   5]
- [ 17   5  11   7  10  11  65]]
-Node Classification on random seed  1790 -> 0.575
-Confusion Matrix:
- [[ 58   9   5   4   4  19  15]
- [ 10 122   1   4   8   4   5]
- [ 23  21 118  39  19  33  44]
- [ 21   3  19  96   4   4   9]
- [  1   6   6   2  63   2   3]
- [  6   0   1   1   1  43   9]
- [ 13   1  12  11   8  15  75]]
-Node Classification on random seed  1791 -> 0.586
-Confusion Matrix:
- [[ 67   3   4   7   4   8  16]
- [  5 139   4   3   7   1   2]
- [ 38  18 104  36  47  18  45]
- [ 19   2   8 104   5   6  17]
- [  0   9   2   0  63   1   1]
- [  4   1   4   6   3  37   4]
- [ 14   5   4   7  17   9  72]]
-Node Classification on random seed  1792 -> 0.631
-Confusion Matrix:
- [[ 83   1   4   3   4   5   4]
- [  4 134   4   3  10   1   1]
- [ 28  29 160  38  33  21  20]
- [ 20   2  12  93   4   8  13]
- [  1   6   6   1  56   0   5]
- [  6   1   3   2   0  37   5]
- [ 25   4   6  12   7   7  68]]
-Node Classification on random seed  1793 -> 0.569
-Confusion Matrix:
- [[ 64   4   6   3   5  15   6]
- [  8 121   3   4   9   3   7]
- [ 25  17 106  59  24  36  49]
- [ 12   6  15  91  11   7  14]
- [  2   4   2   3  56   1   1]
- [  3   1   5   1   0  45   6]
- [ 16   4  10   5   6  13  86]]
-Node Classification on random seed  1794 -> 0.636
-Confusion Matrix:
- [[ 75   0   1   5   5  10   2]
- [  9 127   2   2   4   8   8]
- [ 21  16 145  39  19  24  42]
- [  8   5   7 111   0   7  20]
- [  3   2   4   8  56   0   3]
- [  3   3   5   2   0  50   1]
- [ 22   2  11   8  13  10  72]]
-Node Classification on random seed  1795 -> 0.636
-Confusion Matrix:
- [[ 64   5   1   5   1  11  13]
- [  0 142   2   7   9   0   3]
- [ 14  29 142  25  19  15  56]
- [ 16   7  18 102   1   3  17]
- [  1   1   4   1  67   2   3]
- [  2   3   0   3   1  34  12]
- [  9   5   2  16   9  13  85]]
-Node Classification on random seed  1796 -> 0.637
-Confusion Matrix:
- [[ 66   0   6   5   3  11   8]
- [  7 134   6   5   8   6   3]
- [ 19  18 150  42  23  35  33]
- [  4   6  13 102   1   8   8]
- [  5   4   7   5  55   0   1]
- [  4   3   2   4   0  51   6]
- [  8   5   7   5   3  16  79]]
-Node Classification on random seed  1797 -> 0.62
-Confusion Matrix:
- [[ 76   0   2   3   0  10   8]
- [  4 138   6   0   7   3  10]
- [ 24  32 146  26  32  46  21]
- [ 10   1  16 102   5  13  15]
- [  1   4   4   2  54   1   2]
- [ 10   2   2   1   0  41   1]
- [  8   2   7  13   8  18  63]]
-Node Classification on random seed  1798 -> 0.615
-Confusion Matrix:
- [[ 68   3   1   7   1  14  10]
- [  3 138   8   3  10   3   3]
- [ 40  20 136  30  21  27  36]
- [ 14   7  15  94   6   7  14]
- [  2   6   2   2  58   2   1]
- [  3   3   0   3   2  40   3]
- [ 10   2  10  13   9   9  81]]
-Node Classification on random seed  1799 -> 0.629
-Confusion Matrix:
- [[ 84   4   7   6   5   9   3]
- [  3 147   5   1   6   2   6]
- [ 24  20 136  56  17  19  42]
- [ 14   6   6  97   4  10   8]
- [  3   5   5   0  58   0   4]
- [  7   0   1   2   0  55   0]
- [ 14   4   3  25   9   6  52]]
-Node Classification on random seed  1800 -> 0.607
-Confusion Matrix:
- [[ 70   1   5   2   5   5   6]
- [  2 129  13   1  12   4   3]
- [ 30  15 145  43  31  16  50]
- [ 12   2  18  96  10   9  12]
- [  3   6   9   1  57   1   5]
- [  5   2   1   2   2  44   9]
- [  7   2   3  11   7  10  66]]
-Node Classification on random seed  1801 -> 0.625
-Confusion Matrix:
- [[ 64   1   6   5   3  22   8]
- [  1 119   4   5   3   1   9]
- [ 13  16 156  29  25  22  40]
- [ 17   6  12  96  20   4  10]
- [  3  10   6   1  68   1   3]
- [  2   7   2   1   1  52   3]
- [  9   3  11   5   4  21  70]]
-Node Classification on random seed  1802 -> 0.641
-Confusion Matrix:
- [[ 62   7   9  10   2  10  12]
- [  7 129   4   3   7   2   2]
- [ 33   5 142  38  36  11  44]
- [ 12   2  17 101   3   4   6]
- [  2   8   1   3  72   0   1]
- [  5   1   1   3   2  47   2]
- [ 11   3   6   9   3  12  88]]
-Node Classification on random seed  1803 -> 0.572
-Confusion Matrix:
- [[ 60   4   8   4   2  11  14]
- [  2 123   3   2   8   0   2]
- [ 36  37 130  28  15  22  47]
- [ 23   7  16  85   6   4  29]
- [  1   6   2   1  51   1   1]
- [  9   4   0   0   1  53   5]
- [  8   8  21   8   7  15  70]]
-Node Classification on random seed  1804 -> 0.619
-Confusion Matrix:
- [[ 87   3   3   4   3   4   4]
- [  4 113   8   1   1   4   5]
- [ 26  36 124  27  39  17  35]
- [ 16   4  16  97   8   9  18]
- [  2   6   9   0  63   0   1]
- [  7   1   2   1   1  54   4]
- [ 11   3   5   4   6  23  81]]
-Node Classification on random seed  1805 -> 0.613
-Confusion Matrix:
- [[ 71   2   5   2   1   5  10]
- [  5 119  11   6  12   2  15]
- [ 22  22 149  43  21  22  32]
- [  6   0   8 105   1  10  21]
- [  3   5   8   4  60   0   5]
- [ 10   0   2   1   1  39   8]
- [ 11   1  13   6  14  11  70]]
-Node Classification on random seed  1806 -> 0.604
-Confusion Matrix:
- [[ 57   1   3   7   2  17  11]
- [ 12 122  13   3   9   4   2]
- [ 15  28 132  25  39  25  49]
- [ 19   6  15  99   3   4  14]
- [  2   3   2   1  67   1   2]
- [  3   0   1   1   2  47   6]
- [  9   4   4   9   9  11  80]]
-Node Classification on random seed  1807 -> 0.563
-Confusion Matrix:
- [[ 63   3  11   0   7  16  10]
- [  3 116   4   3   3   6   6]
- [ 37  16 117  41  37  39  50]
- [  8   5  12  98   1  13  15]
- [  2   4   6   2  68   1   2]
- [  6   1   3   0   0  35   7]
- [  6   6  12   8   2  23  66]]
-Node Classification on random seed  1808 -> 0.632
-Confusion Matrix:
- [[ 84   1   1   6   0  10   4]
- [  1 136   1   1   5   4   4]
- [ 16  43 120  34  24  24  28]
- [ 19   3  15 101   8   8  15]
- [  3  11   1   0  68   2   0]
- [  3   3   1   2   0  48   3]
- [ 20   4  13   4   4  19  75]]
-Node Classification on random seed  1809 -> 0.628
-Confusion Matrix:
- [[ 79   3   4   4   6  10  12]
- [  8 124   5   3   5   0   3]
- [ 24  21 136  53  21  13  40]
- [ 18   7  12 104   1   3   8]
- [  1  10   4   2  61   1   5]
- [  4   2   5   1   2  45   4]
- [  8   1  22   8   0   8  79]]
-Node Classification on random seed  1810 -> 0.619
-Confusion Matrix:
- [[ 71   1  12   5   7  10  15]
- [  8 115   7   5   7   2   4]
- [ 28  11 144  37  25  19  40]
- [ 12   4  15 113   3   7   4]
- [  2   6   1   5  59   0   1]
- [  2   1   4   1   0  51   4]
- [ 14   5   8   4  10  25  66]]
-Node Classification on random seed  1811 -> 0.59
-Confusion Matrix:
- [[ 79   4   2   5   4   9  10]
- [  7 109   7   4   8   4   4]
- [ 29  28 140  36  20  28  27]
- [  9  10  18  99   8  10  12]
- [  1   5   7   0  54   0   0]
- [  4   1   0   6   4  44  10]
- [ 19   5  17   5   8  15  65]]
-Node Classification on random seed  1812 -> 0.644
-Confusion Matrix:
- [[ 64   5   1   3   3  14  10]
- [  4 136   6   1   1   4   8]
- [ 23  34 175  29  12  21  46]
- [ 11   9  11  86   3   1  21]
- [  2   7   6   1  44   3   6]
- [  5   2   1   3   1  49   4]
- [  6   2  10   1   1  14  90]]
-Node Classification on random seed  1813 -> 0.598
-Confusion Matrix:
- [[ 67   3   5   9   4  12   5]
- [  3 129  11   4  12   6   2]
- [ 21  19 139  37  20  20  50]
- [  8   1  21  99  12  10   6]
- [  0   7   1   0  57   3   0]
- [  7   0   3   7   2  42   5]
- [ 18   4   8   8   4  24  65]]
-Node Classification on random seed  1814 -> 0.627
-Confusion Matrix:
- [[ 61   1  11   4   1  19  18]
- [  8 124   5   3   7   5   4]
- [ 12  28 159  43  17  18  36]
- [  6  12  13  99   0   7  24]
- [  1   5   2   2  61   0   2]
- [  3   1   7   0   1  40   5]
- [  4   4  14   5   6   9  83]]
-Node Classification on random seed  1815 -> 0.606
-Confusion Matrix:
- [[ 74  10   3   7   3  10   5]
- [  1 141   1   2   8   1   8]
- [ 25  22 120  57  19  18  47]
- [ 11   6   8 104   8   1  23]
- [  2   4   1   0  51   2  10]
- [  5   2   2   1   3  40   4]
- [ 19   1   7   8  10   9  76]]
-Node Classification on random seed  1816 -> 0.601
-Confusion Matrix:
- [[ 56   2   4   6   7  11  16]
- [ 10 111  10   1  15   6  12]
- [ 25  21 141  29  32  13  41]
- [  9   2   7 114  12   5  14]
- [  2   1   5   0  69   0   1]
- [  4   1   3   2   1  41   2]
- [ 13   3  18  12   7  14  69]]
-Node Classification on random seed  1817 -> 0.647
-Confusion Matrix:
- [[ 67   1   2   4   4  12   2]
- [  4 126  10   8   8   1   7]
- [ 18  16 181  25  17  16  54]
- [  5   3  19 101  14   7  10]
- [  0   4   3   2  63   0   3]
- [  4   1   4   0   0  41   4]
- [ 11   7  14  14   2  13  68]]
-Node Classification on random seed  1818 -> 0.596
-Confusion Matrix:
- [[ 57   3  10   3   6  15  10]
- [  2 114   6   4   2   2  12]
- [ 28  10 151  63  14  22  37]
- [ 21   5  13  94   2   7  14]
- [  1  10   2   1  53   1   5]
- [  8   2   3   1   1  55   5]
- [  4   2  18   4   6  19  72]]
-Node Classification on random seed  1819 -> 0.649
-Confusion Matrix:
- [[ 91   0   3   1   2   6  15]
- [  7 128   2   0   5   8   3]
- [ 28  27 144  24  19  16  45]
- [ 12   3  17 111   2   4  10]
- [  3   5   6   0  59   1   1]
- [  8   1   4   0   1  42   6]
- [ 19   5   4   4  11  13  74]]
-Node Classification on random seed  1820 -> 0.632
-Confusion Matrix:
- [[ 72   6   2   5   4  13   3]
- [  4 140   2   5  13   1   0]
- [ 30  12 130  29  48  18  43]
- [  9   3   4 113   8   6  10]
- [  0  11   5   0  68   0   2]
- [  1   1   2   1   7  41   8]
- [  8   5   4   6   8  21  68]]
-Node Classification on random seed  1821 -> 0.641
-Confusion Matrix:
- [[ 84   2   3   6   2   8   6]
- [  6 129   7   3   3   2   2]
- [ 21  17 127  57  25  14  37]
- [ 16   1  20 114   5   2   5]
- [  0   8   2   0  59   0   2]
- [  7   4   2   0   0  48   3]
- [ 10   4   5  16   8  18  80]]
-Node Classification on random seed  1822 -> 0.621
-Confusion Matrix:
- [[ 56   4  10   4   3  20  15]
- [  1 135   3   2   8   1   8]
- [ 18  26 155  26  19  18  47]
- [ 15   6  21 101   4   5  12]
- [  1   9   4   1  51   0   1]
- [  1   2   1   2   0  53   8]
- [  6   5   3   8  11  20  70]]
-Node Classification on random seed  1823 -> 0.652
-Confusion Matrix:
- [[ 69   2   6   3  10  12   2]
- [  6 130   7   0   7   2   5]
- [ 25  18 171  21  19  18  32]
- [ 26   2  17  99   5   8   9]
- [  1   2   3   2  64   0   1]
- [  5   1   3   0   1  53   8]
- [ 19   3   7   6  11  13  66]]
-Node Classification on random seed  1824 -> 0.598
-Confusion Matrix:
- [[ 79   3   1   3   2  10  14]
- [  1 115   3  10   9   2   5]
- [ 34  31 132  42  28  25  26]
- [ 13   2  19  92  26   6  10]
- [  0   8   1   1  73   1   1]
- [  0   3   0   1   2  29  14]
- [  9   6   7   9   7   7  78]]
-Node Classification on random seed  1825 -> 0.636
-Confusion Matrix:
- [[ 74   2   4   3   6  15   7]
- [  2 143   6   1   4   1   3]
- [ 19  31 127  34  15  17  47]
- [  8   2  14 103   9   2  10]
- [  1   6  12   0  69   0   1]
- [  3   0   2   3   0  48  15]
- [ 11   6  13   3  10  16  72]]
-Node Classification on random seed  1826 -> 0.62
-Confusion Matrix:
- [[ 76   4   2   2   4   6   4]
- [  4 104   9   6   4   7   6]
- [ 26  20 152  33  24  31  35]
- [ 14   4  26 107   8   2  13]
- [  0  11   3   0  63   1   2]
- [  5   3   2   0   1  48   0]
- [ 13   3  11   5   1  25  70]]
-Node Classification on random seed  1827 -> 0.629
-Confusion Matrix:
- [[ 69   8   2   3   3  16   8]
- [  7 117   3   1   5   2   3]
- [ 23  31 147  27  36  36  13]
- [ 12   2  11 112   6   6  10]
- [  5  10   3   2  62   0   3]
- [  6   1   4   2   1  49   3]
- [ 11   2   9   5  10  20  73]]
-Node Classification on random seed  1828 -> 0.65
-Confusion Matrix:
- [[ 95   7   2   6   1   4   4]
- [  4 149   4   1  12   0   4]
- [ 25  29 149  25  28  27  33]
- [  9  10   9 100  10  11   7]
- [  1   2   5   1  51   0   0]
- [  5   2   0   0   0  50   5]
- [ 15   1   2  18   7  14  56]]
-Node Classification on random seed  1829 -> 0.615
-Confusion Matrix:
- [[ 58   2   4  12   4   6   4]
- [  5 126   3   1   7   1   3]
- [ 12  37 136  42  30  19  45]
- [  4   8  12  92   5  14  18]
- [  1   2   1   1  65   1   6]
- [  8   1   0   1   0  50   3]
- [ 13   3  11  10  14  11  88]]
-Node Classification on random seed  1830 -> 0.632
-Confusion Matrix:
- [[ 76   2   5   2   8  15   1]
- [  4 139   4   2   5   2   7]
- [ 21  16 144  39  25  14  49]
- [ 11   0  13 107   6   3  26]
- [  1  10   4   1  59   2   1]
- [  4   1   3   0   1  44   2]
- [ 12   3  11  10   9  13  63]]
-Node Classification on random seed  1831 -> 0.608
-Confusion Matrix:
- [[ 73   6   3   3   2  13  12]
- [  1 118   5  10   7   3   6]
- [ 20  15 139  43  20  32  45]
- [  7  10  17  92   7   5  20]
- [  0   5   3   0  62   2   2]
- [  9   2   3   2   0  48   5]
- [  2   4   8   7   7  19  76]]
-Node Classification on random seed  1832 -> 0.632
-Confusion Matrix:
- [[ 75   4   3  11   3   8   8]
- [  3 138  12   1   4   3   5]
- [ 19  30 151  17  32  31  27]
- [ 11   3  16  98   9   2   6]
- [  1  12   2   1  57   1   2]
- [  7   0   2   5   2  55   5]
- [  4   3   7  21  11  14  58]]
-Node Classification on random seed  1833 -> 0.623
-Confusion Matrix:
- [[ 57   5   5  10   2   9  16]
- [  1 129  10   1   4   0   5]
- [ 21  27 140  36  30  14  50]
- [  4   3   7 115   7   5  20]
- [  0  12   1   0  58   2   3]
- [  5   1   4   1   0  40  13]
- [ 13   6   5   0  11   8  84]]
-Node Classification on random seed  1834 -> 0.566
-Confusion Matrix:
- [[ 76   1   5   2   2   6  17]
- [  7 108   3   3  10   7  11]
- [ 48  17 119  43  33  40  22]
- [ 10   4  13 108   6   3  13]
- [  1   7   1   7  47   4  10]
- [  3   3   0   0   2  50   6]
- [ 10   3   7  15   8  21  58]]
-Node Classification on random seed  1835 -> 0.647
-Confusion Matrix:
- [[ 82   3   6   4   7   6   8]
- [  4 130   4   5   8   1   2]
- [ 27  16 156  30  27  18  39]
- [ 27   9  17  90   7   2   8]
- [  1   5   4   0  62   1   3]
- [  9   0   0   1   1  53   5]
- [ 17   0   9   2   5   5  74]]
-Node Classification on random seed  1836 -> 0.619
-Confusion Matrix:
- [[ 69   6   2   3   4   7  11]
- [  6 133   4   1   7   2   4]
- [ 26  36 171  34  29  10  17]
- [ 21  10  31  72  12   6   6]
- [  0   5   4   0  69   0   1]
- [  2   1   4   0   0  43   7]
- [ 11   6  17   6   6  16  62]]
-Node Classification on random seed  1837 -> 0.609
-Confusion Matrix:
- [[ 63   4   4   7   7   5   9]
- [  5 146   7   4  11   1   0]
- [ 18  18 135  40  46   9  47]
- [  9   8  10 102   4   3  14]
- [  1   7   1   0  69   1   4]
- [  8   2   3   5   2  33   5]
- [ 12   8  11  13   6  12  61]]
-Node Classification on random seed  1838 -> 0.614
-Confusion Matrix:
- [[ 81   1   3   9   5  12   4]
- [  3 142   7   2   6   2   0]
- [ 18  29 137  57  10  36  37]
- [ 17   5  15  90   3   8  10]
- [  1   8   7   1  57   2   5]
- [  7   0   5   1   0  40   3]
- [ 16   1   7   6   5  12  67]]
-Node Classification on random seed  1839 -> 0.622
-Confusion Matrix:
- [[ 85   0   9   5   1   9   9]
- [  1 122  11   7   1   1  15]
- [ 21  19 155  37  17  31  28]
- [  6   0  19  97   4   2  11]
- [  2   5   4   5  66   0   3]
- [  1   4  11   5   1  29   5]
- [ 14   3  21   5   8  17  68]]
-Node Classification on random seed  1840 -> 0.616
-Confusion Matrix:
- [[ 67   8  13   5   7   9  10]
- [  5 134   6   1   8   4   1]
- [ 17  28 148  33  38  18  25]
- [ 16   6  10 110   6   7   5]
- [  1  11   2   1  57   2   1]
- [ 10   0   1   5   3  44   3]
- [  8   4   6  16   4  20  56]]
-Node Classification on random seed  1841 -> 0.607
-Confusion Matrix:
- [[ 80   1   3   9   4   4   6]
- [  4 125   4   7  15   1   2]
- [ 19  23 110  17  30  17  73]
- [  9   1   9  95  10   6  24]
- [  1   3   4   4  69   0   3]
- [ 10   2   4   4   0  43   7]
- [ 23   3   5   9   6   7  85]]
-Node Classification on random seed  1842 -> 0.629
-Confusion Matrix:
- [[ 76   2   5   4   6  13   4]
- [  4 133   2   0   5   0   2]
- [ 28  27 159  40  28  22  31]
- [ 13   6  12  97   5   3  13]
- [  3   6   5   5  52   1   3]
- [  5   6   0   1   0  49   3]
- [ 12   9   7   6   4  20  63]]
-Node Classification on random seed  1843 -> 0.618
-Confusion Matrix:
- [[ 80   1   4   2   2  14  13]
- [  3 114   7   3  14   1   9]
- [ 23  33 129  32  30  14  38]
- [  7  12  14 105   1   5   9]
- [  1   5   2   0  64   2   4]
- [  5   1   1   2   1  47   5]
- [  7   3   9  11   7  25  79]]
-Node Classification on random seed  1844 -> 0.621
-Confusion Matrix:
- [[ 71   2   6   4   1  18  12]
- [  2 127   3   2   7   4   8]
- [ 21  28 132  56  25  20  33]
- [  2   2   9 103   8   8  18]
- [  1   4   6   0  63   1   2]
- [  1   0   7   0   2  50   5]
- [  3   2   6  16   7  17  75]]
-Node Classification on random seed  1845 -> 0.582
-Confusion Matrix:
- [[ 49   9   3   8   7   9  22]
- [  2 117   5   4  11   1   7]
- [ 14  22 152  49  19  23  45]
- [  9   9   8 105   1   9  19]
- [  0   7   1   1  59   1   2]
- [ 11   1   1   1   1  39   5]
- [ 14  10   9   9   7  22  61]]
-Node Classification on random seed  1846 -> 0.606
-Confusion Matrix:
- [[ 81   3   2   2   2  14   5]
- [  6 124   3   1   7   4   4]
- [ 39  15 141  16  21  39  46]
- [ 19   4  10  87  11  11  13]
- [  0  11   3   1  67   1   2]
- [  8   1   5   2   3  36   2]
- [ 15   2  15   7   5  14  70]]
-Node Classification on random seed  1847 -> 0.611
-Confusion Matrix:
- [[ 65   3   4   0   5  12  18]
- [  0 135   3   6  10   1   9]
- [ 30  32 151  31  24  22  45]
- [ 13   2  18  75  11   8  10]
- [  3   3   2   0  67   0   3]
- [  4   0   0   1   0  40   5]
- [ 16   2   6   2   8  17  78]]
-Node Classification on random seed  1848 -> 0.629
-Confusion Matrix:
- [[ 77   5   5   6   3   7   7]
- [  7 134   2   2   9   0   8]
- [ 21  27 146  25  30  25  48]
- [  8   9  21  88   7   3  10]
- [  1   6   4   2  61   0   2]
- [  2   3   4   1   2  47  11]
- [ 10   4   7   7   2   8  76]]
-Node Classification on random seed  1849 -> 0.589
-Confusion Matrix:
- [[ 79   1   5   3   3  13   3]
- [  7 116  12   1  23   2   1]
- [ 23  24 127  52  21  28  49]
- [ 10   8  15  92   4  14  15]
- [  1   4   2   2  66   1   1]
- [  2   3   2   1   0  41   3]
- [  6   8   9   2  10  17  68]]
-Node Classification on random seed  1850 -> 0.584
-Confusion Matrix:
- [[ 59   2   8   2   9  16   9]
- [  3 108  11   2  13   4   7]
- [ 29  20 125  40  33  19  48]
- [ 10   0   7 116   7   5  15]
- [  1   9   2   2  63   2   2]
- [  4   3   3   1   0  39   9]
- [ 15   0   9  11   8  16  74]]
-Node Classification on random seed  1851 -> 0.627
-Confusion Matrix:
- [[ 69   5   5   1   9   8  12]
- [  6 134   3   4   7   1   4]
- [ 28  40 152  28  36  19  25]
- [  3   9  18 103   5   3   8]
- [  0   8   0   1  61   1   1]
- [  7   4   1   0   1  48   3]
- [  6   2   5  21   6  19  60]]
-Node Classification on random seed  1852 -> 0.626
-Confusion Matrix:
- [[ 76   1   2   5   0  12  20]
- [  0 138   9   2   3   2   3]
- [ 25  17 151  47  24  13  49]
- [ 16   6  15  99   9   4  11]
- [  1   4   3   1  52   1   2]
- [  1   0   2   4   1  41   7]
- [  9   3   5  18   4  13  69]]
-Node Classification on random seed  1853 -> 0.648
-Confusion Matrix:
- [[ 84   3   5   2   4   8   9]
- [  2 131   5  10   2   3   1]
- [ 33  29 148  31  17  15  29]
- [ 12   5   8 109   8   4  14]
- [  2   9   5   1  63   0   1]
- [ 13   0   3   0   2  30   7]
- [ 12   3  12   6  10   7  83]]
-Node Classification on random seed  1854 -> 0.608
-Confusion Matrix:
- [[ 83   2   5   6   4  13   5]
- [  7 128   4   2   6   0   2]
- [ 23  35 145  26  25  13  50]
- [  7   7  28 100   5   1   6]
- [  5  10   3   2  54   5   4]
- [  5   0   4   2   1  34   8]
- [ 21   7   6  12   7   8  64]]
-Node Classification on random seed  1855 -> 0.593
-Confusion Matrix:
- [[ 71   7   3   6   1   3   4]
- [  1 119   5   3   8   6   8]
- [ 29  28 126  52  20  24  31]
- [  6   5  22 104   5   7  10]
- [  1   6   6   1  58   1   3]
- [  3   2   2   2   4  45   5]
- [  8   7  19   6   7  30  70]]
-Node Classification on random seed  1856 -> 0.626
-Confusion Matrix:
- [[ 78   1   1   4   0  11  16]
- [  1 129   4   2  10   3   4]
- [ 14  27 147  39  19  20  41]
- [  7   3  26 101   9  10  16]
- [  0   7   6   3  55   2   2]
- [  6   1   2   0   0  36  13]
- [  6   4  12   4   4  14  80]]
-Node Classification on random seed  1857 -> 0.586
-Confusion Matrix:
- [[ 67   5   2   4   6   9  15]
- [  3 117   8   1  12   6   6]
- [ 33   8 123  49  45  21  47]
- [ 11   5  10  98  10   3   7]
- [  2   3   2   1  61   3   2]
- [  8   0   3   0   0  43  10]
- [ 12   2   4  11  12  13  77]]
-Node Classification on random seed  1858 -> 0.641
-Confusion Matrix:
- [[ 77   3   3   4   3  12   5]
- [  5 130   7   2   5   5   4]
- [ 27  27 140  52  14  26  29]
- [ 13   2  14 107   7   2  16]
- [  0   4   5   0  58   1   3]
- [  5   0   1   2   0  48   5]
- [  9   1  16   1   5  14  81]]
-Node Classification on random seed  1859 -> 0.654
-Confusion Matrix:
- [[ 82   5   6   3   1   9   1]
- [  0 137   7   3   0   4   2]
- [ 20  23 137  41  37  23  30]
- [  6   6  10 102  16   6  10]
- [  0   8   4   0  66   1   1]
- [  3   1   2   1   0  60   2]
- [  7   6   5  12   3  21  70]]
-Node Classification on random seed  1860 -> 0.654
-Confusion Matrix:
- [[ 81   2   0   3   5  19   3]
- [  3 138   9   3   5   3   3]
- [ 19  26 167  27  15  25  27]
- [  9   4  11  95  10   3   9]
- [  2   7   7   0  50   1   3]
- [  8   0   3   7   0  49   3]
- [ 14   2  14   3   2  27  74]]
-Node Classification on random seed  1861 -> 0.618
-Confusion Matrix:
- [[ 56   5  14   3   4  14   9]
- [  3 136   3   5  14   5   1]
- [ 23  25 133  19  26  24  48]
- [ 13   4   8 116   8   5  10]
- [  2   2   0   2  60   2   4]
- [  5   2   3   3   8  36   4]
- [  9   1   7  18   6  11  81]]
-Node Classification on random seed  1862 -> 0.599
-Confusion Matrix:
- [[ 68   2   3  10   6   8  15]
- [  5 117   8   0   8   7   5]
- [ 17  23 149  40  26  10  43]
- [ 13   3  20  86  11   8  18]
- [  2   8   8   6  59   1   1]
- [  6   4   4   0   0  43   5]
- [ 15   1  10   4   9   8  77]]
-Node Classification on random seed  1863 -> 0.626
-Confusion Matrix:
- [[ 71   2   8   2   9   3  15]
- [  3 137   5   3  12   3   4]
- [ 30  16 152  19  37  17  36]
- [ 13   4  17  99   5   2  14]
- [  2   8   3   0  63   1   4]
- [ 11   2   5   0   1  37   2]
- [ 19   4   9   2   4  18  67]]
-Node Classification on random seed  1864 -> 0.612
-Confusion Matrix:
- [[ 70   1  25   3   3   5   5]
- [  1 119   6   4  14   3   3]
- [ 30  22 115  41  24  23  48]
- [ 11   6  12 119   7   5   5]
- [  1   5   1   3  67   1   0]
- [  7   0   0   5   1  39   9]
- [ 15   6   5  11   1  10  83]]
-Node Classification on random seed  1865 -> 0.65
-Confusion Matrix:
- [[ 61   3   2   1   7  16  12]
- [  2 123  13   3   0   1   4]
- [ 23  22 147  22  24  18  30]
- [  4   7  23  99   7  11  15]
- [  0  10   2   2  72   1   1]
- [  4   2   0   1   4  57   6]
- [  4   3   5   3  16  16  91]]
-Node Classification on random seed  1866 -> 0.653
-Confusion Matrix:
- [[ 65   0   6   4   4  15   9]
- [  6 126   3   4   5   5   3]
- [ 20  20 167  23  20  41  30]
- [  6   7  16  98   2   3   6]
- [  2   7   5   3  59   1   0]
- [  8   2   1   1   1  52   8]
- [ 12   1   7   2  14  14  86]]
-Node Classification on random seed  1867 -> 0.629
-Confusion Matrix:
- [[ 81   4   6   3   4  10   3]
- [  7 126   0   2   7   3   2]
- [ 28   9 132  38  45  17  28]
- [ 17   6  19 102   6   7  21]
- [  3   2   3   2  69   2   3]
- [  5   1   1   2   0  46   5]
- [ 17   4   9   7   7   6  73]]
-Node Classification on random seed  1868 -> 0.606
-Confusion Matrix:
- [[ 76   2   6   5   3  12  24]
- [  3 119   4   2   2   5   6]
- [ 24  25 127  32  42  19  40]
- [ 11   4  12  86   6   4  30]
- [  0   8   6   1  51   0   2]
- [  5   0   6   3   0  61   2]
- [ 13   2   5   1  10   7  86]]
-Node Classification on random seed  1869 -> 0.622
-Confusion Matrix:
- [[ 64   0   5   2   3  18  10]
- [ 13 109  10   0   6   0   7]
- [ 16  18 150  58  24  14  40]
- [  7   4  17 115   2  14   9]
- [  1   2   4   2  44   2   3]
- [  3   0   2   2   3  54   3]
- [  4   1   8  18   3  20  86]]
-Node Classification on random seed  1870 -> 0.638
-Confusion Matrix:
- [[ 64   1   7   3   5  17   7]
- [  1 121   9   3   7   4   9]
- [ 22  24 155  24  18  31  31]
- [  9   4  16 119   3   7  11]
- [  2  11   1   1  54   1   5]
- [  0   3   0   3   2  50   9]
- [  3   4  10  10   5  19  75]]
-Node Classification on random seed  1871 -> 0.637
-Confusion Matrix:
- [[ 76   2   4   7   2   4  15]
- [  3 116   9   6   9   3   6]
- [ 21  19 167  28  29  12  38]
- [ 15   3  26  91   3   5  11]
- [  1   3   2   3  61   0   5]
- [  8   1   2   3   0  45  12]
- [ 12   2  11   9   2   7  81]]
-Node Classification on random seed  1872 -> 0.618
-Confusion Matrix:
- [[ 54   5   2   8   1  18   7]
- [  6 134   6   1   4   3   5]
- [ 23  23 146  27  27  16  45]
- [ 14   4  29  94  12   6  11]
- [  2   5   3   5  63   1   3]
- [  2   2   2   1   2  49   4]
- [ 12   2   6   8   6  13  78]]
-Node Classification on random seed  1873 -> 0.576
-Confusion Matrix:
- [[ 65   3   3   9   6   9   8]
- [  2 133   8   4   9   0   2]
- [ 19  44 129  43  29  34  24]
- [ 15   5  17  80  19  10   8]
- [  1   6   5   1  62   5   1]
- [  5   1   1   1   6  38   5]
- [ 14   3  14   5   6  14  69]]
-Node Classification on random seed  1874 -> 0.639
-Confusion Matrix:
- [[ 77   6   3   4   2   1  16]
- [  8 118   1   0   9   4   4]
- [ 21  30 174  23  11  20  31]
- [ 23   4  33  81   4   7  17]
- [  1   6   5   2  64   1   3]
- [  8   1   1   1   0  43   5]
- [  9   5  13   6   2  10  82]]
-Node Classification on random seed  1875 -> 0.595
-Confusion Matrix:
- [[ 80   3   3   7   5   5  19]
- [  2 107  14   2   9   1   8]
- [ 44   8 119  35  40  15  35]
- [ 12   3  17 101   4   5  10]
- [  0   7   3   3  63   1   0]
- [  5   3   6   0   4  38   6]
- [  9   3  22   2   8  17  87]]
-Node Classification on random seed  1876 -> 0.597
-Confusion Matrix:
- [[ 67   3   5   3   2  12  10]
- [  6 135   3   1   6   1   6]
- [ 35  18 133  24  33  21  44]
- [  7   3  24  89  19   5  17]
- [  2   6   3   0  58   2   2]
- [ 13   1   3   0   0  31   0]
- [ 28   6  12   3   6   8  84]]
-Node Classification on random seed  1877 -> 0.603
-Confusion Matrix:
- [[ 66   4   4  10   3   8   9]
- [  2 131  10   3   3   2   2]
- [ 16  25 165  39  22  31  44]
- [  7   6  17  91   6   5  16]
- [  2   4   8   2  58   1   4]
- [  6   1   1  10   3  30   8]
- [ 13   1   9  11   3  16  62]]
-Node Classification on random seed  1878 -> 0.651
-Confusion Matrix:
- [[ 79   3   6   4   2   7  11]
- [  6 133   7   0  10   0   2]
- [ 15  23 173  25  21  25  34]
- [ 20   3  13  94   4   6   7]
- [  0  11   5   2  54   1   1]
- [ 10   1   1   3   0  42   5]
- [ 19   4   4  11   5  12  76]]
-Node Classification on random seed  1879 -> 0.599
-Confusion Matrix:
- [[ 65   1   4   1   4  11  13]
- [  2 119   4   2   9   5   2]
- [ 23  30 138  29  22  25  56]
- [ 30   5  25  95   4   6   8]
- [  1   3   4   0  62   1   0]
- [  4   1   1   5   1  44   4]
- [  6   4   8  12   7  18  76]]
-Node Classification on random seed  1880 -> 0.628
-Confusion Matrix:
- [[ 73   2   4   5   3  10  11]
- [  5 110  16   7   5   2   3]
- [ 31  18 159  22  18  18  51]
- [ 11   1  10 103   3  10  20]
- [  7   6   4   2  60   2   1]
- [  6   2   2   0   1  39   8]
- [ 14   1  12   3   6   9  84]]
-Node Classification on random seed  1881 -> 0.601
-Confusion Matrix:
- [[ 62   0   8   9   6  18  11]
- [  5 125   5  10   6   1   7]
- [ 32  23 129  31  36  22  32]
- [  3   5  19  91   2   9  17]
- [  1   3   1   4  71   4   3]
- [  3   1   1   0   1  40  14]
- [  4   1   7   7   5  22  83]]
-Node Classification on random seed  1882 -> 0.611
-Confusion Matrix:
- [[ 66   2   2   4   5   9   5]
- [  7 133   1   4   8   3   4]
- [ 18  25 133  37  29  23  40]
- [ 19   2  17 111   9  10   7]
- [  1   6   3   4  53   1   2]
- [  2   4   6   7   0  39   1]
- [ 12   5  10   9   6  20  76]]
-Node Classification on random seed  1883 -> 0.611
-Confusion Matrix:
- [[ 68   1   1  13   0  16  10]
- [  4 123   9   1   0   2   9]
- [ 14  18 135  51  15  46  41]
- [ 21   0  12 124   3   6   6]
- [  0   6   2   3  42   1   6]
- [  1   0   6   5   0  44   4]
- [  8   4  10  13   4  17  75]]
-Node Classification on random seed  1884 -> 0.617
-Confusion Matrix:
- [[ 67   3   3   6   5  21   4]
- [  3 116  14   6   9  10   1]
- [ 12  19 156  27  30  31  34]
- [ 11   3   9 105  10  11   8]
- [  3   6   2   3  53   3   2]
- [  4   1   2   0   1  39   2]
- [ 11   2   8  10   9  24  81]]
-Node Classification on random seed  1885 -> 0.605
-Confusion Matrix:
- [[ 69   5   1   6   2  19   8]
- [  3 111  15   2   2   2   1]
- [ 33  17 151  37  33  18  49]
- [ 13   4   7 100  13  11  11]
- [  0   7  11   1  53   0   5]
- [  1   2   3   1   1  45   5]
- [  5   4   8  13   3  13  76]]
-Node Classification on random seed  1886 -> 0.575
-Confusion Matrix:
- [[ 67   1   8  12   3  10  13]
- [  7 125  10   4   6   3   3]
- [ 29  24 110  40  32  26  44]
- [  8   4  19  92   7   3  12]
- [  0   4   2   1  66   3   6]
- [  5   1   1   3   2  45   5]
- [  8   3   9  11  12  21  70]]
-Node Classification on random seed  1887 -> 0.645
-Confusion Matrix:
- [[ 62   6   4   9   1  10   1]
- [  6 132   5   5   8   4   1]
- [ 37  17 141  32  35  21  33]
- [ 11   4  13 124   3   5   5]
- [  2   0   1   2  71   0   2]
- [  2   0   3   1   3  53   0]
- [ 20   0  12  11   9  11  62]]
-Node Classification on random seed  1888 -> 0.607
-Confusion Matrix:
- [[ 67   3   7   5   4  15  10]
- [  7 128   5   8   1   5   0]
- [ 35  27 148  41  12  24  40]
- [ 11   8   9  94   6   7  22]
- [  1   9   3   2  58   0   7]
- [  7   1   2   1   1  43   2]
- [ 16   1   2   6   6  14  69]]
-Node Classification on random seed  1889 -> 0.65
-Confusion Matrix:
- [[ 81   1   2   6   3  14   3]
- [  5 128   2   7  13   2   2]
- [ 19  15 160  15  22  31  41]
- [ 32   0  19 109   5   5   7]
- [  0   5   4   2  52   0   2]
- [  7   0   1   1   0  56   1]
- [ 13   3   7   6   9  18  64]]
-Node Classification on random seed  1890 -> 0.596
-Confusion Matrix:
- [[ 52   4   3   9   3  16  17]
- [  6 102   6   4  14   2   2]
- [ 45  29 138  24  32  23  31]
- [  7   9  16 125   8   1  11]
- [  2   2   2   1  59   1   3]
- [  5   3   3   3   0  53   4]
- [  8   2   8  15   6  14  67]]
-Node Classification on random seed  1891 -> 0.631
-Confusion Matrix:
- [[ 76   1   3   4   5   8  13]
- [  5 115   9   4   8   5   3]
- [ 11  21 145  43  31  20  33]
- [  9   3  20  96   4   3  12]
- [  1   8   1   4  75   0   2]
- [  7   0   2   5   0  51   8]
- [ 11   1   8  11   6  16  73]]
-Node Classification on random seed  1892 -> 0.6
-Confusion Matrix:
- [[ 73   1   6   5   8  10  11]
- [  5 117   8   3  19   3   6]
- [ 17  19 137  42  28  33  23]
- [  7   4  23  80  16  17   8]
- [  1   0   1   3  71   2   3]
- [  7   0   1   0   1  43  10]
- [  9   3   4   6   4  23  79]]
-Node Classification on random seed  1893 -> 0.625
-Confusion Matrix:
- [[ 83   1   6   6   5   6   6]
- [  5 117   7   6  10   3   2]
- [ 24  14 140  41  25  24  33]
- [ 17   1  19 104   5   5   9]
- [  2   5   1   2  56   2   0]
- [  5   0   4   5   0  40   2]
- [ 18   4  20   5   5  15  85]]
-Node Classification on random seed  1894 -> 0.636
-Confusion Matrix:
- [[ 86   2   1   3   4  13   5]
- [  3 126   4   2  12   1   2]
- [ 26  21 140  39  28  14  31]
- [ 17   3  11  98   6  13  11]
- [  0   8   4   0  64   1   4]
- [  3   0   0   3   0  54   9]
- [ 11   2   8   8  14  17  68]]
-Node Classification on random seed  1895 -> 0.598
-Confusion Matrix:
- [[ 60   8  10   4   5  14  10]
- [  0 121   3   2  15   2   7]
- [ 21  20 140  33  20  35  41]
- [ 20   3  22  85   4   5  15]
- [  0   5   1   1  61   1   3]
- [  2   1   1   2   0  42   7]
- [  6  10   7  10   9  17  89]]
-Node Classification on random seed  1896 -> 0.573
-Confusion Matrix:
- [[ 62   1   8   6   5   8  13]
- [  4 127   7   6   9   1  11]
- [ 22  21 121  56  33  36  37]
- [ 13   4  10  98   6   3  11]
- [  0   7   1   5  58   2   3]
- [  2   1   7   0   0  41   3]
- [  9   3  22  13   6  12  66]]
-Node Classification on random seed  1897 -> 0.631
-Confusion Matrix:
- [[ 61   2   1   5   4  13  10]
- [  7 130   5   4   5   4  10]
- [ 20  14 153  29  35  21  32]
- [ 15   4  11 106   7   8   7]
- [  1   8   6   1  60   1   2]
- [  8   0   0   5   1  51   4]
- [ 19   5  14   3   7  11  70]]
-Node Classification on random seed  1898 -> 0.589
-Confusion Matrix:
- [[ 68   1   4   2   1  10  15]
- [  3 122   9   2   1   2   2]
- [ 17  30 103  57  30  34  49]
- [  9   7  10 108   4  12   6]
- [  1   8   9   0  58   1   5]
- [  5   0   3   0   0  56   1]
- [  9   3   9  13   3  24  74]]
-Node Classification on random seed  1899 -> 0.603
-Confusion Matrix:
- [[ 65   3   7   8   9  13  19]
- [  3 142  17   2   6   0   1]
- [ 29  20 145  31  20  14  29]
- [ 16   6  17  90  18  10  13]
- [  3   8   6   0  57   0   1]
- [  2   2   1   3   0  44   7]
- [  7   3   9  10   6  18  60]]
-Node Classification on random seed  1900 -> 0.623
-Confusion Matrix:
- [[ 57   2   4   5   6   8  14]
- [  1 123   8   1   9   0   5]
- [ 23   9 146  38  27  28  40]
- [  8   2  14  91   1   4  24]
- [  2  10   3   2  61   1   4]
- [  6   1   1   0   1  52   6]
- [  5   6  10   4   8  26  93]]
-Node Classification on random seed  1901 -> 0.643
-Confusion Matrix:
- [[ 63   1   2   3   3   7  10]
- [  9 145   6   2   4   5   4]
- [ 15  25 158  19  34  29  26]
- [ 11   2  13  78  13   3  22]
- [  4   4   2   0  57   1   4]
- [  3   2   3   4   1  54   3]
- [ 11   2   6   5   6  28  88]]
-Node Classification on random seed  1902 -> 0.615
-Confusion Matrix:
- [[ 75   4   5   1   3  11  10]
- [  5 114   7   2   9   2   1]
- [ 22   7 130  43  49  11  48]
- [ 22   9  12  89   6   7  13]
- [  1   5   3   1  68   1   3]
- [  5   1   7   0   1  48   7]
- [  7   3   9   5   5  12  91]]
-Node Classification on random seed  1903 -> 0.64
-Confusion Matrix:
- [[ 64   3   4   2   2  10  17]
- [  4 146   5   0   5   5   2]
- [ 21  22 133  37  30  31  34]
- [  5   4  14 114   1   8  11]
- [  1   6   4   3  58   0   0]
- [  9   2   0   1   0  54   3]
- [ 16   6  17   1  10   4  71]]
-Node Classification on random seed  1904 -> 0.638
-Confusion Matrix:
- [[ 68   1   3   3   3  17  14]
- [  5 120   8   3   9   1   3]
- [ 19   8 154  34  30  19  53]
- [ 19   1  19  99   4   4  10]
- [  1   5   7   2  71   0   1]
- [  0   0   3   0   1  56   9]
- [  9   2  12   2   8  10  70]]
-Node Classification on random seed  1905 -> 0.617
-Confusion Matrix:
- [[ 53   1   5   5   7  11  12]
- [  3 123   4   2  12   1   4]
- [ 32  31 161  21  19  19  35]
- [ 18   5  21 105   4   4   6]
- [  1   7   5   2  65   2   2]
- [  1   1   2   6   1  49   1]
- [ 13   4  12  16   9  16  61]]
-Node Classification on random seed  1906 -> 0.616
-Confusion Matrix:
- [[ 71   2   3   3   2   1  17]
- [  1 125   5   4  10  15   7]
- [ 23  28 146  32  20  20  40]
- [  9   1  18  89   8   2  18]
- [  0  12   4   3  64   0   2]
- [  5   5   0   3   6  40   6]
- [ 14   6   8  11   4   6  81]]
-Node Classification on random seed  1907 -> 0.606
-Confusion Matrix:
- [[ 54   2   4  20   4   9  18]
- [  9 132  11   4   7   3   3]
- [ 15  29 131  23  44  11  44]
- [ 11   4  20 107  10   2   9]
- [  1   7   4   0  59   4   1]
- [  0   1   4   2   2  34  14]
- [ 13   6   2   7   5   5  89]]
-Node Classification on random seed  1908 -> 0.587
-Confusion Matrix:
- [[ 73   1   6   4   6  14   8]
- [  1 129   6   3   8   3   1]
- [ 25  16 119  27  36  28  45]
- [ 12   6  24  90  10  17   4]
- [  0  10   4   2  57   2   3]
- [  7   0   2   2   2  43   4]
- [  8   6  15   7   8  20  76]]
-Node Classification on random seed  1909 -> 0.635
-Confusion Matrix:
- [[ 77   4   1   8   2   4  14]
- [ 12 110   3   1   2   2   5]
- [ 23  28 158  42   9  20  31]
- [ 10   7  11 107   2   3  28]
- [  2   7   9   3  63   1   1]
- [  6   2   1   0   0  46   5]
- [ 14   4   9  12   4  13  74]]
-Node Classification on random seed  1910 -> 0.636
-Confusion Matrix:
- [[ 71   0   1   3   2  16  10]
- [  5 127   4   5   4   8   2]
- [ 29  23 147  25  27  16  40]
- [ 15   3  14  97  13   5  18]
- [  1   7   3   1  67   0   3]
- [  2   0   3   1   0  54   5]
- [  6   5   8   6   5  20  73]]
-Node Classification on random seed  1911 -> 0.604
-Confusion Matrix:
- [[ 65   3   3   6   2  15  15]
- [ 12 117   5   5  10   2   6]
- [ 18  17 133  33  35  24  37]
- [ 23   1   6 117   3   3  17]
- [  4   3   0   3  52   2   4]
- [  7   2   2   1   0  42  12]
- [  1   9  13   8  11  13  78]]
-Node Classification on random seed  1912 -> 0.572
-Confusion Matrix:
- [[ 71   8   3   2   2  14   7]
- [ 12 119   4   4   6   3   4]
- [ 36  21 109  48  48  17  44]
- [ 11   3   8 104  16  14   8]
- [  0   6   1   2  59   1   2]
- [  4   1   3   2   0  40   7]
- [ 13   4   9   5   7  18  70]]
-Node Classification on random seed  1913 -> 0.614
-Confusion Matrix:
- [[ 75   0   3   4   3  11  13]
- [  8 109  12   1  11   4   4]
- [ 40  42 136  16  23  12  42]
- [ 11   1  15 111   6   7  11]
- [  1   8   2   1  58   1   5]
- [  5   3   0   2   1  52   6]
- [  9   4  10   8   6  14  73]]
-Node Classification on random seed  1914 -> 0.602
-Confusion Matrix:
- [[ 71   5   1   6   3  14   5]
- [  3 129   4   6   3   5   5]
- [ 26  22 118  40  51  23  34]
- [  9   0   7 123   7  10   8]
- [  0   6   3   2  48   3   1]
- [  5   1   0   2   3  41   8]
- [ 17   2   8  17  13  10  72]]
-Node Classification on random seed  1915 -> 0.623
-Confusion Matrix:
- [[ 52   4   8   7   1  12  11]
- [  4 127   3   3   5   2   2]
- [ 26  35 150  29  14  31  45]
- [  8   5  16  94   1   8  20]
- [  0   6   1   0  64   2   2]
- [  4   1   5   0   2  55   3]
- [  9   8   9   7   5  13  81]]
-Node Classification on random seed  1916 -> 0.639
-Confusion Matrix:
- [[ 74   1   6   9   3  12  10]
- [  9 136   1   2   6   3   5]
- [ 22  13 136  33  21  12  55]
- [ 16   2  28 100   9   4  12]
- [  1   5   3   2  61   0   1]
- [  6   1   0   1   1  53   7]
- [  8   3   3   3   9  13  79]]
-Node Classification on random seed  1917 -> 0.649
-Confusion Matrix:
- [[ 76   1   7   6   3   8   1]
- [  3 143   9   0   6   1   6]
- [ 13  21 141  26  33  29  42]
- [ 12   2   6 132   4   9  14]
- [  1   6   7   2  48   0   4]
- [  1   0   1   8   2  44   5]
- [  5   1   8   8  10  20  65]]
-Node Classification on random seed  1918 -> 0.63
-Confusion Matrix:
- [[ 74   5   2   2   4  13   8]
- [ 11 130   1   2   6   1   6]
- [ 18  23 143  31   9  21  55]
- [ 12   4  14 104   3   6  13]
- [  0   8   4   4  64   3   1]
- [  1   0   1   5   0  39   7]
- [  9   7   5  16  12  17  76]]
-Node Classification on random seed  1919 -> 0.636
-Confusion Matrix:
- [[ 76   2   8   6   0  11   3]
- [  4 136   3   1   3   2   6]
- [ 13  26 115  33  19  31  65]
- [  6   3  16  91   4   5  17]
- [  1   6   2   1  75   1   2]
- [  8   1   3   1   1  39   6]
- [ 10   5   6   3   6  14 104]]
-Node Classification on random seed  1920 -> 0.593
-Confusion Matrix:
- [[ 65   5   6   1   5  21   0]
- [ 10 124   4   3   9   5   3]
- [ 33  15 132  50  32  13  52]
- [ 10   5  12 101   7  12   3]
- [  1   4   2   2  58   0   3]
- [  5   2   3   0   0  40   5]
- [ 19   4   8  12   8  13  73]]
-Node Classification on random seed  1921 -> 0.634
-Confusion Matrix:
- [[ 59   2   9   2   4  11   8]
- [  2 131   4   5   4   2   7]
- [ 24  15 138  54  27  20  34]
- [ 16   2  21 114   1   3   8]
- [  2   6   4   1  63   0   1]
- [  1   1   3   2   1  50   8]
- [  8   4   7  11   4  17  79]]
-Node Classification on random seed  1922 -> 0.609
-Confusion Matrix:
- [[ 69   9   1   2   0   9   3]
- [  6 130   3   8   9   3   2]
- [ 29  16 144  42  19  15  35]
- [ 20   2  17 110   2   9  13]
- [  3   4   5   2  48   3   3]
- [  9   2   2   1   0  44   9]
- [ 27   7   9   7   3  21  64]]
-Node Classification on random seed  1923 -> 0.627
-Confusion Matrix:
- [[ 84   5   5   5   3  10   5]
- [  7 122   5   0   9   6   3]
- [ 29  18 134  27  20  35  35]
- [ 12   5  10 118   4   5  14]
- [  2   5   4   2  57   1   3]
- [  6   1   1   3   1  43   6]
- [ 13   1  21   6   5  15  69]]
-Node Classification on random seed  1924 -> 0.643
-Confusion Matrix:
- [[ 60   1   4   4   5  12   7]
- [  2 123   4   1   4   3   5]
- [ 28  16 142  20  24  23  47]
- [  8   1  14 133   4   6  13]
- [  0  10   7   0  54   1   3]
- [ 14   0   6   5   2  45   7]
- [ 14   5   9   4   4  10  86]]
-Node Classification on random seed  1925 -> 0.613
-Confusion Matrix:
- [[ 72   2   4   7   5  15  10]
- [  3 142   8   3  13   1   3]
- [ 17  23 155  32  21  29  26]
- [ 15   5  24  79   6   6  14]
- [  0   5   4   0  65   0   4]
- [  2   0   2   1   3  42   5]
- [ 14   5  15   2  12  21  58]]
-Node Classification on random seed  1926 -> 0.623
-Confusion Matrix:
- [[ 79   4   3   2   3   6   4]
- [  1 135   9   4   6   0   4]
- [ 25  28 155  26  19  40  36]
- [ 15   5  10  80  12   2  12]
- [  0  15   2   2  62   0   7]
- [  4   5   1   2   0  40  12]
- [  8   4  13   5   4  17  72]]
-Node Classification on random seed  1927 -> 0.647
-Confusion Matrix:
- [[ 71   5   1   7   6   7   5]
- [  1 127  15   2  11   2   4]
- [ 23  11 163  41  18  32  29]
- [  4   2  18 104   7   6  15]
- [  1   3   2   1  60   2   2]
- [  8   1   0   0   2  53   6]
- [ 11   3   5   7   5  22  69]]
-Node Classification on random seed  1928 -> 0.619
-Confusion Matrix:
- [[ 89   2   2   1   4   8  12]
- [  5 133   6   2   9   2   7]
- [ 38  24 110  54  13  19  33]
- [ 20   1   6 116   3   6  13]
- [  1  10   5   3  54   1   2]
- [  7   1   0   0   1  53   5]
- [ 14   3   9   7   7  15  64]]
-Node Classification on random seed  1929 -> 0.603
-Confusion Matrix:
- [[ 64   2   4   4   7   5  14]
- [  8 128   5   5  12   5   7]
- [ 25  25 138  47  56  12  19]
- [  6   5  11 100   4   9  20]
- [  2   4   2   1  57   1   3]
- [  6   0   2   0   1  42   7]
- [  4   3  19   7   6  12  74]]
-Node Classification on random seed  1930 -> 0.632
-Confusion Matrix:
- [[ 56   6   5   5   1  12  18]
- [  1 137  10   0   4   1   2]
- [ 31  27 162  25  31  13  34]
- [ 17   1  16 101   4  12  14]
- [  2   9   6   1  57   1   0]
- [  1   2   2   0   0  50   2]
- [ 11   7  13   4   9   8  69]]
-Node Classification on random seed  1931 -> 0.603
-Confusion Matrix:
- [[ 59   3   1   3   4  24  18]
- [ 10 113   3   6  15   2   4]
- [ 19  28 152  30  40  17  38]
- [ 13   5   9  86   5  10  14]
- [  2   4   2   1  74   1   1]
- [  2   1   0   1   1  40  11]
- [ 10   5   5   4  11  14  79]]
-Node Classification on random seed  1932 -> 0.627
-Confusion Matrix:
- [[ 55   0   4  18   6  11  10]
- [  5 122   2   2   8   2   8]
- [ 26  28 162  21  26  18  41]
- [ 13   0  17 104  10   7  12]
- [  2   7   3   0  57   1   2]
- [  5   0   1   2   1  41   7]
- [  9   5  10   4  11   8  86]]
-Node Classification on random seed  1933 -> 0.607
-Confusion Matrix:
- [[ 78   5   0   8   3  13  11]
- [ 11 123   4   1   7   9   3]
- [ 30  22 158  31  21  30  38]
- [ 11   4  20  90   7   4  11]
- [  2   5   2   0  54   2   1]
- [  6   0   3   3   7  42   1]
- [  7   3  10  11   7  19  62]]
-Node Classification on random seed  1934 -> 0.603
-Confusion Matrix:
- [[ 60   4   2   2   5  11  15]
- [  0 134   3   4   8   3   7]
- [ 30  24 117  14  31  45  49]
- [ 10   4   7  96  20   7  12]
- [  0   4   2   0  60   2   2]
- [ 11   0   0   0   2  52   2]
- [  4   4  11   6   5  25  84]]
-Node Classification on random seed  1935 -> 0.597
-Confusion Matrix:
- [[ 85   3  10   5   5   7   5]
- [  8 124   9   4   3   2   0]
- [ 28  47 114  28  26   8  60]
- [ 14   2  20  95   6   3  15]
- [  0   6   1   2  67   0   5]
- [  9   0   3   0   3  41   6]
- [ 14   7   9   6   5   9  71]]
-Node Classification on random seed  1936 -> 0.651
-Confusion Matrix:
- [[ 79   1   0  14   2   7   6]
- [  7 134   3  13   4   2   1]
- [ 17  16 142  41  17  27  38]
- [  7   4   7 120   8   5  17]
- [  1   8   6   1  49   2   2]
- [  5   0   2   5   0  42   2]
- [ 16   5   7   9   5   9  85]]
-Node Classification on random seed  1937 -> 0.622
-Confusion Matrix:
- [[ 71   9   6  13   5  12   4]
- [  6 142   3   1   5   4   4]
- [ 20  29 128  60  13  23  30]
- [ 11   7  19  91   1   4  17]
- [  3   3   2   2  67   3   2]
- [  4   1   0   5   1  40   3]
- [ 13   2   7   8   3  10  83]]
-Node Classification on random seed  1938 -> 0.614
-Confusion Matrix:
- [[ 69   2   9   1   4  11  11]
- [  7 115   1   3   5   2   7]
- [ 39  19 153  26  27  18  42]
- [ 10   9  15  91   6   6  15]
- [  1  14   6   3  58   1   1]
- [  7   0   2   1   3  50   6]
- [ 11   0  10   4   1  20  78]]
-Node Classification on random seed  1939 -> 0.622
-Confusion Matrix:
- [[ 88   7   5   3   0   7  11]
- [  2 107   5   5  16   2   6]
- [ 29  18 139  22  35  26  32]
- [ 11   2  11 114   6   5  14]
- [  1   6   7   3  56   1   0]
- [  8   6   0   2   0  43   2]
- [ 17   3   5   8   8  21  75]]
-Node Classification on random seed  1940 -> 0.621
-Confusion Matrix:
- [[ 74   3   2   3   2  14   8]
- [  7 126   5   4  13   5   3]
- [ 20  19 136  51  22  28  44]
- [  3   4   7 106   4   8  12]
- [  3   2   5   2  64   0   3]
- [  8   3   5   0   0  40   1]
- [ 14   1   9  13   8  11  75]]
-Node Classification on random seed  1941 -> 0.642
-Confusion Matrix:
- [[ 71   6   7   4   1  18  19]
- [  4 120   6   2   6   2   7]
- [ 23  14 150  41  22  19  29]
- [ 16   2  15 107   5   2  13]
- [  0  12   3   1  59   0   7]
- [ 10   1   0   1   1  51   2]
- [  7   2   8   5   4  11  84]]
-Node Classification on random seed  1942 -> 0.577
-Confusion Matrix:
- [[ 71   6   6   7   5  18  10]
- [  1 120  12   4  13   4   4]
- [ 35  21 118  49  16  15  29]
- [ 14   1  12 105   9   9  14]
- [  1   4   5   4  60   2   3]
- [  1   0   2   1   2  55   0]
- [ 15   2  14  23  15  15  48]]
-Node Classification on random seed  1943 -> 0.622
-Confusion Matrix:
- [[ 75   2  12   5   8   6   2]
- [  4 121   6   2   8   3   8]
- [ 35  12 139  51  38  12  28]
- [  8   3   7 101  11   5   7]
- [  2   8   4   4  72   2   0]
- [  6   0   5   0   3  40   6]
- [  7   3  16   9   7  13  74]]
-Node Classification on random seed  1944 -> 0.603
-Confusion Matrix:
- [[ 58   1   7   4   1  26   5]
- [  3 135   6   2   7   2   3]
- [ 26  10 138  36  16  37  44]
- [ 14   2  30 100   2  11   5]
- [  3   5   5   1  51   1   2]
- [  7   1   4   2   0  44   3]
- [ 11   6  17   7   8  14  77]]
-Node Classification on random seed  1945 -> 0.58
-Confusion Matrix:
- [[ 69   6   7   6   6  15  15]
- [  3 138   3   4   7   2   8]
- [ 28  21 122  37  41  22  42]
- [  8   0  16  92  11   7  16]
- [  1   5   4   4  40   0   2]
- [  4   1   3   0   1  45   7]
- [ 11   2  17  10   7  10  74]]
-Node Classification on random seed  1946 -> 0.636
-Confusion Matrix:
- [[ 77   0   3   3   1   6  16]
- [  6 112   4   9   6   2   4]
- [ 22  13 168  26  47  12  28]
- [ 14   7  17 104  12   2   7]
- [  3   2   3   3  64   0   2]
- [  7   2   6   3   0  39   8]
- [  9   3   5  13   6  22  72]]
-Node Classification on random seed  1947 -> 0.602
-Confusion Matrix:
- [[ 56   1   4   9   7  13   8]
- [  4 130   3   3   7   0   5]
- [ 17  19 146  32  41  17  54]
- [ 32   2  17  84  12  10  11]
- [  1   5   2   0  66   1   1]
- [  4   0   1   0   1  47   9]
- [  8   2  15   1  10   9  73]]
-Node Classification on random seed  1948 -> 0.602
-Confusion Matrix:
- [[ 69   6   7   3   6  12  10]
- [  1 122   7   2  10   1   4]
- [ 15  27 124  50  41  15  31]
- [ 18   1  15 113   8   5  11]
- [  2   3   6   3  53   0   1]
- [  3   2   4   0   0  53   3]
- [ 16   2  15  14   3  15  68]]
-Node Classification on random seed  1949 -> 0.581
-Confusion Matrix:
- [[ 68   2   5   8  13   8  16]
- [  6 114   5   9   6  17   2]
- [ 29  24 129  31  26  31  31]
- [ 15   4  16  91  11   5  10]
- [  3   5   7   1  57   2   1]
- [  5   1   2   3   1  51   6]
- [  5   1  10  10  10  16  71]]
-Node Classification on random seed  1950 -> 0.636
-Confusion Matrix:
- [[ 70   2   7   4   4   8  11]
- [  4 131   3   1   9   4   2]
- [ 17  17 151  29  22  24  37]
- [ 10   8  20 104   8   9  13]
- [  1   3   9   4  63   2   2]
- [  4   0   1   3   1  51   2]
- [ 15   2   8  18   9   7  66]]
-Node Classification on random seed  1951 -> 0.586
-Confusion Matrix:
- [[ 68   3   1   3   5  13  18]
- [  6 129   3   4  16   2   5]
- [ 23  24 117  41  34  19  34]
- [ 14   1  28  82   9   2  11]
- [  0   5   5   2  61   0   1]
- [  2   3   3   5   1  45   9]
- [ 19   4   9   4   7  16  84]]
-Node Classification on random seed  1952 -> 0.63
-Confusion Matrix:
- [[ 73   1   1   6   7   7   7]
- [ 18 116   2   0   9   2   3]
- [ 43   8 165  36  23  13  38]
- [  8   3  12  95  13   5  11]
- [  4   6   7   0  58   2   4]
- [ 15   0   2   2   1  45   4]
- [ 19   2  11   3   3   9  78]]
-Node Classification on random seed  1953 -> 0.62
-Confusion Matrix:
- [[ 69   1   0  12   5   6  13]
- [  3 136   4   7   0   3   4]
- [ 26  22 150  36  24  28  30]
- [  5   8  12 102   5  10  18]
- [  3   6   7   2  52   0   2]
- [ 11   0   2   1   1  36   9]
- [ 15   5  13   5  11   5  75]]
-Node Classification on random seed  1954 -> 0.648
-Confusion Matrix:
- [[ 66   2   4   5   6   9   7]
- [  1 151   5   1   7   1   2]
- [ 19  26 143  35  22  20  32]
- [ 13   4  23 111   2   4   5]
- [  0  10   2   3  62   1   1]
- [  5   4   3   1   0  47   8]
- [ 13   8   7  12   8  11  68]]
-Node Classification on random seed  1955 -> 0.629
-Confusion Matrix:
- [[ 75   0   2   9   4  15   4]
- [  3 106   6   0  15   2   5]
- [ 24  13 146  22  40  21  48]
- [  7   0  16 113  11   8  16]
- [  1   2   2   0  69   2   0]
- [ 12   2   2   1   1  40   4]
- [ 14   2  10   6   9  10  80]]
-Node Classification on random seed  1956 -> 0.593
-Confusion Matrix:
- [[ 64   2   7   5  14  21  12]
- [  8 135   9   2   6   4   0]
- [ 35  13 140  33  18  24  34]
- [ 17   6  20  86   2   7  13]
- [  4   6   3   1  61   1   2]
- [  9   1   0   0   0  46   2]
- [  3   3  16  10  14  20  61]]
-Node Classification on random seed  1957 -> 0.608
-Confusion Matrix:
- [[ 73   4   3  10   1  15  11]
- [  4 136   6   5   3   1   4]
- [ 15  21 145  43  17  17  52]
- [ 14   1  15  83  13  16  17]
- [  4   6   5   0  44   2   5]
- [  1   3   3   4   0  33   2]
- [  7   6  12   6   6  12  94]]
-Node Classification on random seed  1958 -> 0.609
-Confusion Matrix:
- [[ 59   3   0  11   2  11  18]
- [  9 115  12   3   5   2   0]
- [ 17  32 147  27  36  22  33]
- [ 12   9  14 102   8   7  12]
- [  1   4   4   4  45   2   5]
- [  4   1   2   1   0  49   7]
- [  5   2   4   9  10  21  92]]
-Node Classification on random seed  1959 -> 0.621
-Confusion Matrix:
- [[ 75   1   6   7   1  12   3]
- [  9 127   4   6   2   8   1]
- [ 19  28 132  38  33  16  40]
- [ 13   3  15  97   5  12  10]
- [  3   6   3   1  64   0   1]
- [  1   2   0   5   1  48   6]
- [ 18   2  14   5   9  10  78]]
-Node Classification on random seed  1960 -> 0.619
-Confusion Matrix:
- [[ 70   3   9   6   4   4   4]
- [  1 139   0   4  10   5   3]
- [ 15  12 122  50  24  29  40]
- [  7  12  14  95  11  10  12]
- [  1   7   4   3  56   3   3]
- [  9   3   0   6   0  49   7]
- [  6   3  15   1   2  19  88]]
-Node Classification on random seed  1961 -> 0.634
-Confusion Matrix:
- [[ 76   2   1   9   5   5   8]
- [  8 134   3   2  12   2   3]
- [ 35  20 149  16  24  21  58]
- [ 12   5  10  83   5   5  10]
- [  4   4   2   2  58   1   2]
- [  2   0   3   2   1  45   5]
- [ 19   6   9   1   2  20  89]]
-Node Classification on random seed  1962 -> 0.642
-Confusion Matrix:
- [[ 69   3   0   2   2  12  10]
- [  7 132   3   3   7   3   3]
- [ 17  28 141  32  28  24  36]
- [ 14   7  11  95   8   2   9]
- [  2  10   2   1  64   0   2]
- [  4   1   1   3   1  55   4]
- [  9   5  12  13   3  14  86]]
-Node Classification on random seed  1963 -> 0.59
-Confusion Matrix:
- [[ 75   2   3   6   6   6  10]
- [  3 117  11   1  13   3   4]
- [ 28  16 141  32  42  20  38]
- [ 14   5  29  92   3  11  11]
- [  4   5   5   0  54   0   3]
- [  5   0   0   2   0  39   5]
- [ 17   3  11  11   4  18  72]]
-Node Classification on random seed  1964 -> 0.606
-Confusion Matrix:
- [[ 63   2   1   7   5  13  20]
- [  2 140   7   2  14   3   2]
- [ 23  15 134  39  27  35  32]
- [ 16   2  13 108   4  13   6]
- [  2   3   2   1  56   1   1]
- [ 10   0   5   1   3  31   3]
- [  6   4   5   8  20  16  74]]
-Node Classification on random seed  1965 -> 0.604
-Confusion Matrix:
- [[ 58   3   4  17   6  13   4]
- [  3 126   6   1   7   1   2]
- [ 36  25 140  25  36  23  28]
- [ 19   3  14  92   6   9   5]
- [  1   5   1   3  69   1   0]
- [  3   6   1   5   2  34   9]
- [ 17   7   1  10   6  22  85]]
-Node Classification on random seed  1966 -> 0.653
-Confusion Matrix:
- [[ 73   1   4   4   5   6  15]
- [  4 143   3   0  12   0   2]
- [ 15  15 142  31  19  24  47]
- [ 13   3   7 104   1   5  15]
- [  1   7   4   1  65   1   5]
- [  6   1   1   4   4  45   5]
- [ 10   4  12   6  13  11  81]]
-Node Classification on random seed  1967 -> 0.59
-Confusion Matrix:
- [[ 60   5   2   8   3  10  20]
- [  5  98   6   5  11   0   6]
- [ 22  20 138  48  35  29  35]
- [  7   8  15 110   3   3  16]
- [  2   1   5   4  62   0   1]
- [  3   4   2   1   1  45   8]
- [ 16   6   2   7   9  16  77]]
-Node Classification on random seed  1968 -> 0.619
-Confusion Matrix:
- [[ 69   1   2   4   9  14   4]
- [  1 132   7   8   2   4   0]
- [ 15  24 143  28  28  32  51]
- [ 17   0   8 106   7   4  24]
- [  1   4   4   0  58   1   8]
- [  8   1   0   3   2  29   3]
- [ 14   0   8  12   3  15  82]]
-Node Classification on random seed  1969 -> 0.606
-Confusion Matrix:
- [[ 57   4   1   7   1  19   7]
- [  6 119  10   4  10   6   2]
- [ 24  17 136  34  27  41  33]
- [ 13   3  19 106   5   3  14]
- [  0   2   4   1  61   0   4]
- [  5   2   4   3   0  44   7]
- [ 11   4   7   7   8  15  83]]
-Node Classification on random seed  1970 -> 0.588
-Confusion Matrix:
- [[ 59   4   9   8   4  10  20]
- [  9 124   6   1   5   1   6]
- [ 37  21 119  37  20  10  55]
- [  3   5  15 106   4  14  16]
- [  1   5   2   0  65   0   0]
- [  4   0   3   1   0  46  13]
- [ 13   3   7  11   8  21  69]]
-Node Classification on random seed  1971 -> 0.584
-Confusion Matrix:
- [[ 77   2   3   5   3   5   7]
- [  2 122   5   3  20   3   1]
- [ 27  28 118  50  30  26  38]
- [ 18  13  21  91   5   4  16]
- [  2   4   4   1  63   1   1]
- [  8   1   4   4   0  45   5]
- [ 10   7   4   9   5  11  68]]
-Node Classification on random seed  1972 -> 0.649
-Confusion Matrix:
- [[ 73   0   7   4   7  13   9]
- [  1 128   3   1   5   4   4]
- [ 19  30 169  18  27  22  33]
- [  7   5  28  99   1   9   8]
- [  3   7   2   3  51   2   3]
- [  1   4   5   2   3  54   5]
- [  5   2   8   5   6  20  75]]
-Node Classification on random seed  1973 -> 0.612
-Confusion Matrix:
- [[ 79   4   5   6   4  10   6]
- [  8 119   1   2  10   3   5]
- [ 26  27 150  18  23  35  33]
- [ 10   7  20 102   1   9  17]
- [  2   8   1   1  48   3   4]
- [ 12   1   6   1   0  47   4]
- [ 13   3  13   7   7  12  67]]
-Node Classification on random seed  1974 -> 0.562
-Confusion Matrix:
- [[ 65   2   4   7   6  14   7]
- [  9 107   9   1  12   2   7]
- [ 28  27 138  35  26  25  32]
- [ 11  10  12  95  14   9  19]
- [  4   6   4   2  54   1   2]
- [  5   1   3   2   3  41   9]
- [ 17   6   6  12   4  23  62]]
-Node Classification on random seed  1975 -> 0.619
-Confusion Matrix:
- [[ 65   8  10   7   2  15   7]
- [  1 135   2   1   5   2   1]
- [ 17  26 154  22  19  25  63]
- [ 10   9  20  84   5   3  12]
- [  2   6   6   0  66   0   2]
- [  8   2   1   0   0  46   4]
- [ 21   6   9   0   6  16  69]]
-Node Classification on random seed  1976 -> 0.606
-Confusion Matrix:
- [[ 60   4   8   1   4  21   1]
- [ 10 112   5   9   5   6   4]
- [ 21  15 145  45  25  41  32]
- [  8   4  11  98   2  10  12]
- [  1   9   3   0  65   1   2]
- [  8   1   0   6   0  51   5]
- [  5   1   4   9   7  28  75]]
-Node Classification on random seed  1977 -> 0.585
-Confusion Matrix:
- [[ 49  10   4   4   4  15  13]
- [  7 110   6   0  11   1  15]
- [ 19  22 127  35  22  23  49]
- [ 15   5  18 105  10   6   9]
- [  4   3   3   2  66   1   5]
- [  4   4   2   0   2  50   7]
- [ 15   3  15   6   7   9  78]]
-Node Classification on random seed  1978 -> 0.604
-Confusion Matrix:
- [[ 70   2   7   5   3  12   9]
- [  2 126   4   3   6   4   7]
- [ 13  37 123  37  43  27  43]
- [ 12   6   8  99  11   4  14]
- [  0   6   1   2  69   1   2]
- [ 12   1   4   0   3  37   8]
- [  3   1  12   3   6  12  80]]
-Node Classification on random seed  1979 -> 0.635
-Confusion Matrix:
- [[ 75   3   5   4   4   1  10]
- [  1 126   7   1   9  12   2]
- [ 20  28 169  36  22  20  34]
- [ 18   1  24  99   5   8   8]
- [  0   2   3   5  65   4   2]
- [  4   1   2   0   0  39   6]
- [ 20   4   9   4   5  11  62]]
-Node Classification on random seed  1980 -> 0.58
-Confusion Matrix:
- [[ 65   0  18   4   1  17  14]
- [  5 125   9   3  12   5   2]
- [ 31  20 147  23  23  19  35]
- [ 16   4  24  81   9   6  23]
- [  2   7   7   2  54   1   1]
- [  5   2   9   0   1  37   3]
- [ 14   6  12   2   6  17  71]]
-Node Classification on random seed  1981 -> 0.646
-Confusion Matrix:
- [[ 74   1   0   3   5  22   6]
- [  4 132   6   2   9   4   5]
- [ 32  21 133  47  23  22  42]
- [ 16   3   3 120   5   3  11]
- [  0   2   7   1  56   0   4]
- [  1   1   3   5   0  51   5]
- [  8   4   3   3   3   9  80]]
-Node Classification on random seed  1982 -> 0.648
-Confusion Matrix:
- [[ 72   4   4   7   1   6   5]
- [  2 140   1   5   4   2   7]
- [ 31  26 159  35  17  12  31]
- [ 10   4  15  93  11   2  15]
- [  1   3   4   1  57   1   4]
- [  8   4   9   4   1  38   2]
- [  9   5  10   7   7  15  89]]
-Node Classification on random seed  1983 -> 0.61
-Confusion Matrix:
- [[ 55   5   6   9   7   8   9]
- [  6 117  13   5   5   6   2]
- [ 33  16 142  44  28  21  39]
- [ 20   0  10 103   3  10   9]
- [  1   7   2   1  70   1   3]
- [  4   0   1   3   0  45   5]
- [ 13   1  12  11   4   7  78]]
-Node Classification on random seed  1984 -> 0.618
-Confusion Matrix:
- [[ 78   3   3   9  10   9   2]
- [  4 132  12   1  11   2   3]
- [ 16  18 129  51  28  19  37]
- [  8   9  11 108   2   4  11]
- [  1   7   5   0  62   3   5]
- [  3   2   3   4   0  45   2]
- [ 19   1  11  15   6  12  64]]
-Node Classification on random seed  1985 -> 0.588
-Confusion Matrix:
- [[ 84   6   0   5   1   8  14]
- [  4 123   4   5  10   1   6]
- [ 38  21 102  49  33  25  52]
- [  7   6   9  93   9  10   7]
- [  4   7   3   2  55   0   1]
- [  3   4   4   1   0  50   5]
- [ 13   2   9   5   7  12  81]]
-Node Classification on random seed  1986 -> 0.607
-Confusion Matrix:
- [[ 68   2   1   2   7   8  18]
- [  7 128  10   1   3   2   0]
- [ 23  15 127  48  35  37  42]
- [  6   4   9  99   4   3  15]
- [  0   8   1   3  64   3   3]
- [  6   1   1   5   0  42   8]
- [ 14   4  10   7   5  12  79]]
-Node Classification on random seed  1987 -> 0.618
-Confusion Matrix:
- [[ 73   5   3   7   5   5  10]
- [  4 123  10   2  22   2   2]
- [ 31   7 148  20  32  17  48]
- [ 13   3  17 109   4   2  15]
- [  1   5   3   1  56   0   0]
- [ 11   1   1   6   1  39   4]
- [ 15   6   3  19  10   9  70]]
-Node Classification on random seed  1988 -> 0.606
-Confusion Matrix:
- [[ 74   3   5   4   4  17   4]
- [  3 140  14   2   6   1   3]
- [ 30  18 113  35  18  42  43]
- [ 12   3  13 100   2   9  10]
- [  1   6   9   0  50   1   0]
- [  2   3   3   4   0  54   1]
- [ 11   4  11   7   6  24  75]]
-Node Classification on random seed  1989 -> 0.626
-Confusion Matrix:
- [[ 67   0   6   2   3   9   7]
- [  6 132  11   3   2   2   6]
- [ 17  21 162  26  20  19  46]
- [ 20   7  14  95   7   6  14]
- [  6  11   3   2  61   0   0]
- [  3   3   2   7   5  38   4]
- [ 19  11   8   4   3   9  71]]
-Node Classification on random seed  1990 -> 0.604
-Confusion Matrix:
- [[ 70   8   8   7   1   8  14]
- [  2 119   8   6  11   6   6]
- [ 20  19 140  31  49  20  30]
- [  4   3  17 101   3   6  17]
- [  0   7   5   2  64   2   1]
- [  3   2   2   2   0  47   6]
- [ 10   1  13  10  10  16  63]]
-Node Classification on random seed  1991 -> 0.629
-Confusion Matrix:
- [[ 85   1   5   6   3  11   6]
- [  3 112   3   4  11   1   1]
- [ 31  18 166  23  20  28  34]
- [  7   3  22  89   5   3  20]
- [  4  10   4   5  56   4   2]
- [  9   4   3   1   0  39   1]
- [  9  10  10   8   6  12  82]]
-Node Classification on random seed  1992 -> 0.605
-Confusion Matrix:
- [[ 76   0   2  10   0  13   4]
- [ 11 110   8   4  23   8   3]
- [ 28  18 143  25  30  20  35]
- [ 15   3  21 103   9   8  11]
- [  4   6   5   4  53   3   4]
- [  4   4   1   0   0  46   1]
- [ 13   2   9  10   4  12  74]]
-Node Classification on random seed  1993 -> 0.613
-Confusion Matrix:
- [[ 86   3   4   3   5  11   4]
- [  7 118   8   1   8   3   2]
- [ 27  25 157  37  23  19  32]
- [ 16   6  13  90   5   7  12]
- [  2   8   7   3  54   1   3]
- [  7   2   1   2   4  41   0]
- [  4   4  15  11   7  25  67]]
-Node Classification on random seed  1994 -> 0.613
-Confusion Matrix:
- [[ 72   3   7   7   3  12   4]
- [  1 120  13   9  14   3   4]
- [ 19  14 137  44  29  28  35]
- [  6   2  17 100   5  10  12]
- [  0   5   8   0  63   0   3]
- [  9   1   5   1   0  55   0]
- [ 14   2   4   6   9  19  66]]
-Node Classification on random seed  1995 -> 0.612
-Confusion Matrix:
- [[ 61   4   3  11   4  12  14]
- [  2 128   7   3  10   3   4]
- [ 23  28 140  37  27  15  42]
- [  4   6  17 111   6   7   7]
- [  1   5   2   1  66   1   4]
- [ 11   2   0   2   2  44   3]
- [  5   4   8  15  11  15  62]]
-Node Classification on random seed  1996 -> 0.592
-Confusion Matrix:
- [[ 60   0   1   0   4  11  18]
- [  5 140   8   7   6   1   3]
- [ 14  27 139  42  26  43  39]
- [ 21   7  12  89   4   3  18]
- [  0   4   4   3  51   4   1]
- [  8   0   2   1   0  39   5]
- [ 14   2  11   7   0  22  74]]
-Node Classification on random seed  1997 -> 0.637
-Confusion Matrix:
- [[ 64   4   9   4   4  17   8]
- [  2 121   1   3   1   1   6]
- [ 28  24 142  42  22  11  27]
- [ 12   6  20 116   9   5  10]
- [  1   4   5   1  69   0   6]
- [  2   3   3   3   0  43   7]
- [  9   1   9   5   6  22  82]]
-Node Classification on random seed  1998 -> 0.596
-Confusion Matrix:
- [[ 79   1   3   5  12  20  12]
- [  1 108  10   2  21   3   4]
- [ 24  14 142  38  26  33  34]
- [ 16   6  18  95   3   5  17]
- [  0   3   0   3  60   0   4]
- [  2   0   9   1   2  42   3]
- [  5   1  10   3   7  23  70]]
-Node Classification on random seed  1999 -> 0.571
-Confusion Matrix:
- [[ 67   3   5   4   3   9  15]
- [  5 122   5   1   1   6  10]
- [ 23  16 121  64  28  20  56]
- [ 13   8  10  92   8   4   9]
- [  1   7   3   2  54   2   3]
- [  7   0   2   4   0  33   6]
- [ 17  10   6   9  11  13  82]]
-Node Classification on random seed  2000 -> 0.661
-Confusion Matrix:
- [[ 63   1   3  10   6  11   7]
- [  3 148   4   6   3   1   5]
- [ 23  16 182  19  19  22  45]
- [  9   5  27  87   3   6  10]
- [  1   8   3   0  52   2   1]
- [ 11   2   2   2   0  46   3]
- [ 13   4   6   7   3   7  83]]
-Node Classification on random seed  2001 -> 0.601
-Confusion Matrix:
- [[ 83   3   3   3   4  10  13]
- [  4 128   5   3   6   6   3]
- [ 33  14 145  25  29  22  48]
- [ 20  10  10  85   6   8   9]
- [  2   7   3   3  64   2   3]
- [  9   1   2   4   0  39   4]
- [ 14   6   9   2  15  16  57]]
-Node Classification on random seed  2002 -> 0.624
-Confusion Matrix:
- [[ 72   1   4  13   7  18   7]
- [  8 130   3   3   6   4   5]
- [  4  18 145  39  25  30  40]
- [  7   2   9 106   7   8  16]
- [  2   6   4   1  58   1   1]
- [  6   1   4   2   2  34  10]
- [ 14   4   9   7   9   9  79]]
-Node Classification on random seed  2003 -> 0.647
-Confusion Matrix:
- [[ 69   1   4   4   5   8   6]
- [  3 138   2   1   4   1   5]
- [ 36  29 137  31  17  21  38]
- [  7   4  18 106   2   2  14]
- [  1   8   8   0  62   0   0]
- [  5   4   2   2   0  56   5]
- [ 14   3  12   7   5  14  79]]
-Node Classification on random seed  2004 -> 0.634
-Confusion Matrix:
- [[ 56   7   3   1   4  13  15]
- [ 13 129   2   6   9   5   3]
- [ 28  28 153  27  21  11  28]
- [  9   3  14 109   8   6  11]
- [  2   0   6   2  69   4   0]
- [  6   1   3   5   1  44   2]
- [ 12   3   5  10  10  19  74]]
-Node Classification on random seed  2005 -> 0.629
-Confusion Matrix:
- [[ 71   3   3   0   3  15   8]
- [  4 138   6   1  12   3   2]
- [ 36  22 149  16  28  31  34]
- [  5   3  23 101   1   6  10]
- [  3   3  10   5  65   1   1]
- [  2   5   5   0   0  41   8]
- [ 25   5   4   5   4  10  64]]
-Node Classification on random seed  2006 -> 0.606
-Confusion Matrix:
- [[ 66   4   7   5   4  20  11]
- [ 10 117   3   0   4   8   4]
- [ 18  14 148  23  35  21  52]
- [  8   8  10  79   7  15  25]
- [  3   6   4   0  63   2   1]
- [  1   3   4   1   1  50   5]
- [ 11   4   5   3   4  20  83]]
-Node Classification on random seed  2007 -> 0.609
-Confusion Matrix:
- [[ 76  10   1  10   8  10   6]
- [  2 115   7   5   7   9   2]
- [ 26  11 129  38  33  31  37]
- [  8   9  19 107   6   3   8]
- [  0   3   4   4  64   0   0]
- [  3   2   5   8   1  38   1]
- [ 11   0   6   9  15  13  80]]
-Node Classification on random seed  2008 -> 0.607
-Confusion Matrix:
- [[ 74   2   7   7   4  20   2]
- [  2 118   5   7   3   9  11]
- [ 14  26 160  40  14  22  25]
- [ 14   3  17  99   6   3  16]
- [  0  11   5   1  46   0   5]
- [  9   0  10   1   0  42  10]
- [ 13   4  11  16   2  16  68]]
-Node Classification on random seed  2009 -> 0.613
-Confusion Matrix:
- [[ 73   2   2   5   2   5  14]
- [ 13 118  17   0   6   4   2]
- [ 14  28 156  42  20  30  35]
- [  5   6  18 103   5   2   9]
- [  3   6   6   0  55   2   1]
- [  3   2   0   7   0  39   6]
- [ 15   5  14  10   2  19  69]]
-Node Classification on random seed  2010 -> 0.61
-Confusion Matrix:
- [[ 68   2   2   8  11  12   8]
- [  4 129   6   2  15   3   3]
- [ 33   5 143  29  23  27  44]
- [ 10   3  27  93   4  10   8]
- [  1   6   2   2  63   0   3]
- [  8   1   7   0   2  41   1]
- [ 12   2  19   6   9  10  73]]
-Node Classification on random seed  2011 -> 0.621
-Confusion Matrix:
- [[ 64   2   5   7   6  10  11]
- [  5 118  15   0   8   6   6]
- [ 25  18 138  51  21  16  37]
- [  9   3  16 115   7   3  12]
- [  1   7   5   3  51   2   1]
- [  5   0   2   0   0  58   4]
- [ 10   5  15   7   4   9  77]]
-Node Classification on random seed  2012 -> 0.632
-Confusion Matrix:
- [[ 66   1   8  10   4   5   5]
- [  4 121   3   2   5   2   6]
- [ 22  12 175  32  23  20  49]
- [ 13   2  18 105   1   6  16]
- [  0   6   3   1  61   1   6]
- [  4   1   3   6   1  42   2]
- [ 13   5  10  16   6  15  62]]
-Node Classification on random seed  2013 -> 0.628
-Confusion Matrix:
- [[ 57   3   7  10   0  11  11]
- [  5 134   4   3   9   1   2]
- [ 29  18 164  35  19  13  33]
- [ 15   4  24  92   7   4  10]
- [  1  13   1   1  51   0   2]
- [  5   3   1   1   1  50   5]
- [ 20   7   9   6   6  13  80]]
-Node Classification on random seed  2014 -> 0.61
-Confusion Matrix:
- [[ 73   5   4   6   0  14  12]
- [  5 126   4   4   6   4   6]
- [ 17  19 158  24  26  31  31]
- [  7   7  18  80   7  10  28]
- [  1   4   5   1  59   1   2]
- [  9   1   2   1   0  45   5]
- [ 16   3  20   2   8  14  69]]
-Node Classification on random seed  2015 -> 0.621
-Confusion Matrix:
- [[ 75   2   1   4   5  10   9]
- [  3 109  11   2  12   4   5]
- [ 25  17 141  38  38  17  32]
- [ 16   4  14  96   4   7  16]
- [  1   7   3   3  67   2   4]
- [  5   3   3   1   2  41   8]
- [  7   6   5   8   6   9  92]]
-Node Classification on random seed  2016 -> 0.636
-Confusion Matrix:
- [[ 69   4   2   9   4   8  10]
- [  3 124   3   5   4   9   6]
- [ 17  19 163  27  36  10  36]
- [ 20  11   5  90   9  10  10]
- [  0   8   0   5  68   0   1]
- [  6   3   1   1   0  57   4]
- [  7   8  19   6   8  10  65]]
-Node Classification on random seed  2017 -> 0.643
-Confusion Matrix:
- [[ 67   2   5   2   3  19  14]
- [  3 141   7   6   5   1   4]
- [ 25  20 152  28  32  19  30]
- [ 11   6   8  91   6   6  19]
- [  1   3   2   0  56   3   1]
- [  3   2   1   3   1  53   9]
- [  5   3   7   6  10  16  83]]
-Node Classification on random seed  2018 -> 0.609
-Confusion Matrix:
- [[ 65   4   5   4   1   1  22]
- [  5 126   3   1  17   5   3]
- [ 30  28 141  34  28  21  43]
- [ 10   5  11  90   2  11  12]
- [  0   7   2   1  64   1   4]
- [  3   3   5   3   6  41   9]
- [  6   1  17   3   6   8  82]]
-Node Classification on random seed  2019 -> 0.555
-Confusion Matrix:
- [[ 75   3   3   7   3   9  11]
- [  5 114   6   1   7   2   5]
- [ 25  20  91  48  65  15  39]
- [ 10  10  28  99   8   5  10]
- [  2   6   1   1  55   2   8]
- [ 10   2   4   7   0  39   4]
- [  7   8  17   6   4  11  82]]
-Node Classification on random seed  2020 -> 0.652
-Confusion Matrix:
- [[ 75   1   6   7   4   6  12]
- [  4 131   1   5   9   5   2]
- [ 24  16 164  25  22  26  30]
- [ 11   4  25  91  15   7   9]
- [  1   7  11   0  66   2   0]
- [  3   0   1   3   0  35   1]
- [  6   1  10  11   3  12  90]]
-Node Classification on random seed  2021 -> 0.609
-Confusion Matrix:
- [[ 68   3   2   6   7   5  11]
- [  3 123   7   0  14   1   7]
- [ 17  30 135  27  21  18  47]
- [ 13   3  13 107   9   7  17]
- [  1   5   5   4  57   1   6]
- [  5   1   5   0   0  50   4]
- [  7   7  12  13  14  13  69]]
-Node Classification on random seed  2022 -> 0.623
-Confusion Matrix:
- [[ 54   5   9   7   2  10  15]
- [  2 140   5   0   9   1   3]
- [ 14  36 147  43  22  20  28]
- [ 11   5  22 105   7   1   9]
- [  3   5   6   1  52   0   1]
- [  5   5   0   4   0  45   4]
- [ 13   3   8  12   5  16  80]]
-Node Classification on random seed  2023 -> 0.606
-Confusion Matrix:
- [[ 65   0   2   7   7   7  15]
- [  4 110   4   5  16   3   3]
- [ 26  23 165  32  39  24  18]
- [ 17   5  20  96  16   8   6]
- [  1   8   5   1  63   1   2]
- [  4   3   0   3   0  46   5]
- [ 13   1  10  11  11   8  61]]
-Node Classification on random seed  2024 -> 0.656
-Confusion Matrix:
- [[ 67   1  14   2   2  18   7]
- [  5 133   6   4   7   2   2]
- [ 15  19 171  27  23  23  34]
- [ 11   4  18 101   5   7  12]
- [  0   5   3   1  60   0   1]
- [  1   2   2   3   0  45   5]
- [ 14   3  13   1  10  12  79]]
-Node Classification on random seed  2025 -> 0.619
-Confusion Matrix:
- [[ 81   1   3   6   9   7   4]
- [  8 120   6   6  12   2   4]
- [ 11   4 140  65  34  22  39]
- [ 10   1  14 102  14   4  10]
- [  3   4   6   2  64   0   3]
- [  0   0   1   2   1  52   5]
- [  6   4  16   6   7  19  60]]
-Node Classification on random seed  2026 -> 0.62
-Confusion Matrix:
- [[ 71   0   2   3   0  20  14]
- [  5 131   6   7   4   6   9]
- [ 12  12 133  42  11  35  43]
- [ 15   3  11 109   3   9  12]
- [  1   2   5   2  50   1   4]
- [  2   3   6   1   0  53   5]
- [ 10   3  13   9   7  22  73]]
-Node Classification on random seed  2027 -> 0.579
-Confusion Matrix:
- [[ 68   1  10   4   6   7  15]
- [  1 116   4   1   3   3   9]
- [ 38  29 109  50  23  31  32]
- [  8   7  18 112   5   5   8]
- [  3   8   6   2  48   0   2]
- [  7   2   2   3   0  46   5]
- [ 18   1   7  15   4  18  80]]
-Node Classification on random seed  2028 -> 0.606
-Confusion Matrix:
- [[ 73   2   1   8   0   9   8]
- [  4 119   5   4   9   7   1]
- [ 12  21 119  58  52  19  42]
- [  8   5  14 108   6   6   4]
- [  1   9   0   1  54   1   4]
- [  5   0   1   2   2  49   6]
- [ 14   3   8  10   8  14  84]]
-Node Classification on random seed  2029 -> 0.623
-Confusion Matrix:
- [[ 78   1   2   9   4  12   9]
- [  3 121   7   4   2   1   5]
- [ 23  15 145  35  14  22  46]
- [ 14   4  19  99   4  13  17]
- [  4   5   1   1  62   1   2]
- [  6   0   2   2   1  46   8]
- [  6   3  10  11   9  20  72]]
-Node Classification on random seed  2030 -> 0.61
-Confusion Matrix:
- [[ 72   2   0   5   5  21  10]
- [  3 134   4   2  10   2   2]
- [ 28  24 131  46  12  39  29]
- [  9   9  11  96   3   8   7]
- [  7   4  11   1  53   0   1]
- [  7   3   2   1   0  39   7]
- [  7   3   9   4   7  25  85]]
-Node Classification on random seed  2031 -> 0.603
-Confusion Matrix:
- [[ 57   6  12  12   1   9   6]
- [  6 124   9   2   2   7   3]
- [ 32  29 145  20  33  19  46]
- [ 23   6  13 113   3   1   7]
- [  3   8   1   3  52   1   3]
- [  6   1   2   1   3  39   7]
- [ 14   9   9   3   4  12  73]]
-Node Classification on random seed  2032 -> 0.61
-Confusion Matrix:
- [[ 78   2   6   3   9  11   8]
- [  2 132   4   5   8   2   6]
- [ 17  36 131  29  22  32  23]
- [ 15  11  24  98   9   5  15]
- [  0   5   3   2  54   2   1]
- [  3   1   6   1   3  47   9]
- [  5   3  12   5  10  15  70]]
-Node Classification on random seed  2033 -> 0.601
-Confusion Matrix:
- [[ 87   2   1   2   2  10  12]
- [  5 132  10   3  14   2   0]
- [ 35  24 118  21  26  34  38]
- [  9   2   7  88  13  10  22]
- [  3   3   3   6  63   0   2]
- [  2   2   0   1   2  34  11]
- [ 22  11   2   6   7  12  79]]
-Node Classification on random seed  2034 -> 0.638
-Confusion Matrix:
- [[ 61   1   3   7   1   8  14]
- [  2 123   6   2   2   2   6]
- [ 33  38 159  33  19  25  21]
- [ 13   6   7 112   1   6  16]
- [  1  16   4   1  50   0   4]
- [  2   1   1   3   1  46   3]
- [ 13   3  10   5   6  16  87]]
-Node Classification on random seed  2035 -> 0.572
-Confusion Matrix:
- [[ 65   2   6  10   4  10   8]
- [ 12 124   5   5   9   4   1]
- [ 32  26 100  57  32  11  40]
- [ 13   2  14 108   2   6  17]
- [  5   8   2   3  50   1   8]
- [  3   2   2   0   1  50   4]
- [ 11   4   7  12  10  17  75]]
-Node Classification on random seed  2036 -> 0.623
-Confusion Matrix:
- [[ 79   1   3   5   5   8  12]
- [  5 147   7   0   2   0   5]
- [ 39  15 118  22  29  21  40]
- [  9   3  23  99   9   9  20]
- [  1   7   5   0  57   1   6]
- [  3   1   0   1   3  42   9]
- [ 10   5   7   3   5  18  81]]
-Node Classification on random seed  2037 -> 0.626
-Confusion Matrix:
- [[ 68   1   2   8   3  11   7]
- [  3 144   6   1   9   3   0]
- [ 30  16 141  43  20  16  42]
- [ 17   5   7  93   6  10  16]
- [  3   3   3   2  60   0   4]
- [  6   5   4   0   3  42   7]
- [ 12   2  12   7   8  11  78]]
-Node Classification on random seed  2038 -> 0.616
-Confusion Matrix:
- [[ 62   1   5   8   5  19   7]
- [  4 137   2   0  14   4   1]
- [ 30  17 165  28  28  21  37]
- [ 12   4  15  93   4   6  17]
- [  1   8   3   1  63   2   1]
- [  3   6   3   2   0  38   5]
- [ 14   7   8  13  10   8  58]]
-Node Classification on random seed  2039 -> 0.621
-Confusion Matrix:
- [[ 66   0   3  12   2  16   6]
- [  4 126   5   3   8   7  10]
- [ 16  20 165  25  28  24  24]
- [ 12   9  21  99   8   7   7]
- [  2   2   2   6  59   1   6]
- [ 10   0   0   1   0  44   9]
- [  8   2   9  21   2  21  62]]
-Node Classification on random seed  2040 -> 0.638
-Confusion Matrix:
- [[ 73   5   2   5   5  15   6]
- [  5 133   4   1   7   4   2]
- [ 30  14 165  25  20  17  51]
- [ 10   4   9  95   3   6  17]
- [  0  12   6   2  52   1   2]
- [  7   0   0   1   5  50   4]
- [  7   3  17   8   3  17  70]]
-Node Classification on random seed  2041 -> 0.597
-Confusion Matrix:
- [[ 55   2   5  14   8  17   9]
- [  9 122   9   0   7   2   2]
- [ 26  16 144  26  20  28  43]
- [ 14   3  11 111  10   4  13]
- [  0   5   8   0  63   0   3]
- [  6   3   7   6   1  37   2]
- [  8   4  19  12  11  10  65]]
-Node Classification on random seed  2042 -> 0.653
-Confusion Matrix:
- [[ 72   1   0  10   3  11   3]
- [  3 117  12   7  18   6   1]
- [ 16  17 188  23  18  17  45]
- [  4   6  16 104   2   3  20]
- [  1   9   2   2  62   1   4]
- [  3   3   1   1   0  49   6]
- [  8   2   8  12   8  14  61]]
-Node Classification on random seed  2043 -> 0.595
-Confusion Matrix:
- [[ 75   3  10   2   4  10   4]
- [  2 127  12   6  14   6   3]
- [ 27   9 129  29  19  28  59]
- [ 13   7  24  92   5   9  10]
- [  2   6   4   1  55   0   8]
- [  1   0   2   2   0  46   6]
- [  5   4  11  19   6  13  71]]
-Node Classification on random seed  2044 -> 0.668
-Confusion Matrix:
- [[ 68   4   2   6   8  12  13]
- [  5 129   1   6   7   2   2]
- [  4  12 171  26  24  20  34]
- [  5  11  14 116   2   5  14]
- [  0   6   3   0  63   0   3]
- [  5   3   9   1   1  39   1]
- [  5   6  13  13   8  16  82]]
-Node Classification on random seed  2045 -> 0.618
-Confusion Matrix:
- [[ 62   4   2   6   2   6  14]
- [  0 136   6   3   7   2   5]
- [ 39  18 179  13  19  14  49]
- [ 10   9  21  77   2   8  18]
- [  1   9   2   1  57   2   5]
- [  4   2   1   6   2  44   1]
- [ 12   2  21   6  11  17  63]]
-Node Classification on random seed  2046 -> 0.616
-Confusion Matrix:
- [[ 70   2   4  11   2   7  15]
- [ 12 111   5   3   2   0   2]
- [ 26  36 174  30  26  13  24]
- [ 30   3  14  89   8   3  13]
- [  2  10   1   0  61   3   5]
- [  3   2   3   4   0  39   9]
- [ 15   4   6   5  15   6  72]]
-Node Classification on random seed  2047 -> 0.608
-Confusion Matrix:
- [[ 72   1   2   3   3   9  16]
- [  5 111  14   1  10   8   1]
- [ 14  32 129  44  30  33  28]
- [  6   4  15 113   2   4  19]
- [  2   4   3   7  60   1   2]
- [  2   1   1   5   0  44   5]
- [ 13   0   7   5  12  18  79]]
-Node Classification on random seed  2048 -> 0.598
-Confusion Matrix:
- [[ 55   1   4   5  13  14  10]
- [  5 130   4   4  10   3   2]
- [ 34  11 131  55  26  22  33]
- [ 17   1  17 109   6   5  14]
- [  2   4   3   4  62   0   4]
- [  6   0   0   2   0  37   7]
- [ 11   1  12   0  11  19  74]]
-Node Classification on random seed  2049 -> 0.632
-Confusion Matrix:
- [[ 58   2  13   7   5  14  12]
- [  6 146   2   2   8   2   1]
- [ 23  21 144  25  20  15  39]
- [ 11   2  29 101   6   4  10]
- [  3   9   4   0  62   0   1]
- [ 11   3   3   0   0  45   2]
- [ 16   6  11   4   4  12  76]]
-Node Classification on random seed  2050 -> 0.597
-Confusion Matrix:
- [[ 57   5   6   4   5  12   5]
- [  5 147   6   5   6   2   0]
- [  8  26 126  53  47  20  40]
- [  3   4  24  79   7   4  21]
- [  0   5   3   0  63   1   2]
- [  7   2   3   0   3  47   2]
- [  9   3  20   0   9  16  78]]
-Node Classification on random seed  2051 -> 0.609
-Confusion Matrix:
- [[ 54   5   2   5   6  19  14]
- [  5 122   9   3   6   9   7]
- [ 28  24 150  31  19  30  28]
- [ 12   6  18 101   7   8  11]
- [  0   7   2   0  69   0   2]
- [  4   2   0   0   1  47   7]
- [ 14   6   5   3   5  21  66]]
-Node Classification on random seed  2052 -> 0.618
-Confusion Matrix:
- [[ 86   3   4   3   0  18   3]
- [  7 124   2   4   7   3   4]
- [ 39  15 133  32  21  19  39]
- [ 18   4  12  89   8  10   9]
- [  6   8   4   2  61   1   3]
- [  7   1   2   6   0  37   5]
- [ 18   5   6   5   8  11  88]]
-Node Classification on random seed  2053 -> 0.609
-Confusion Matrix:
- [[ 75   1   8   2   4  12   2]
- [  4 120   4   1   7   4   6]
- [ 31  35 144  36  26  23  20]
- [ 10   2  30  92   2   9  20]
- [  2   4   6   2  61   2   5]
- [  4   1   0   1   2  43   4]
- [ 19   1   6   1  18  14  74]]
-Node Classification on random seed  2054 -> 0.648
-Confusion Matrix:
- [[ 59   2   2   4   2  19  12]
- [ 13 135   9   4   6   1   7]
- [  6  27 161  37  29  21  29]
- [  7   7  13 107   3   4  16]
- [  0   9   6   1  64   0   0]
- [  4   4   1   0   0  47   5]
- [  3   5   6   4   5  19  75]]
-Node Classification on random seed  2055 -> 0.597
-Confusion Matrix:
- [[ 65   4   5  10   6   6   8]
- [  5 133   4   4  16   2   4]
- [ 22  21 123  32  30  17  50]
- [ 13   5  16 100  16   5  18]
- [  1   5   6   1  59   1   1]
- [  8   3   4   7   3  33   2]
- [ 13   1   4   6  12   6  84]]
-Node Classification on random seed  2056 -> 0.631
-Confusion Matrix:
- [[ 61   0   9   6   2  17   6]
- [  2 124   3   3   4   1   1]
- [ 26  26 160  31  16  38  22]
- [  7   7  26 117   3   8  11]
- [  0   9   5   2  52   2   3]
- [  9   0   4   3   2  42   7]
- [  8   3  12  10   3  12  75]]
-Node Classification on random seed  2057 -> 0.607
-Confusion Matrix:
- [[ 56   2   6   6   1   6  12]
- [  2 126  15   7   4   0   5]
- [ 16  36 128  45  31  21  43]
- [  6   4  12 126   2   1  11]
- [  1   5   7   5  55   3   2]
- [ 10   0   0   2   1  43  11]
- [ 10   3   9  10   3  17  73]]
-Node Classification on random seed  2058 -> 0.603
-Confusion Matrix:
- [[ 65   2   3   5   3  10  14]
- [  5 123  12   2   8   7   4]
- [ 34  12 156  28  16  32  24]
- [ 21   4  17  96   4  10  12]
- [  5   3   8   1  53   0   2]
- [  6   2   6   6   0  39   5]
- [ 22   3  16   1   3  19  71]]
-Node Classification on random seed  2059 -> 0.603
-Confusion Matrix:
- [[ 56   4   3   6   1  12  28]
- [  4 102  11   4  21   2  10]
- [ 17  15 151  49  33  23  32]
- [  7   2  13  97   2  13  10]
- [  1   4   2   1  63   1   3]
- [  3   1   7   1   1  49   4]
- [  7   4   6   9  10  10  85]]
-Node Classification on random seed  2060 -> 0.64
-Confusion Matrix:
- [[ 89   4   2   8   4   9   4]
- [  3 126   4   5   6   2   1]
- [ 14  20 143  56  26  15  39]
- [ 10   6  11 116   8   3  11]
- [  1   4   5   2  54   0   0]
- [  6   3   2   3   0  42   5]
- [ 11   3  10  13   7  14  70]]
-Node Classification on random seed  2061 -> 0.616
-Confusion Matrix:
- [[ 66   1   2   6   6  12  15]
- [  9 114   2   0  12   4   0]
- [ 25  19 154  32  41  22  36]
- [ 11   3  16 106  10   4   6]
- [  4   1   7   0  54   1   4]
- [ 11   2   4   0   0  56   3]
- [ 15   4   7   1   9  17  66]]
-Node Classification on random seed  2062 -> 0.59
-Confusion Matrix:
- [[ 66   3   3   1   2  12   9]
- [  5 130  10   2   9   5   2]
- [ 21  19 122  44  39  32  46]
- [ 17   1  16 102   5   4  10]
- [  0   9   1   1  49   0   4]
- [  4   3   2   0   1  44   7]
- [ 11   4   5  11  14  16  77]]
-Node Classification on random seed  2063 -> 0.641
-Confusion Matrix:
- [[ 79   2   6   5   2  15   8]
- [  3 135  10   1   7   2   4]
- [ 24  10 153  40  34  17  45]
- [  7   0  13 100   4   4  17]
- [  1   4   4   9  58   0   0]
- [  2   0   1   0   1  43  13]
- [  9   1  12   7   4  11  73]]
-Node Classification on random seed  2064 -> 0.645
-Confusion Matrix:
- [[ 89   1   2   0   5   5   4]
- [  3 130   5   0   8   1   3]
- [ 16  16 156  26  23  37  52]
- [ 19   6  11  92   4   5  13]
- [  2   6   2   3  65   1   4]
- [  7   1   2   0   0  49   3]
- [ 20   5   6   3   8  17  64]]
-Node Classification on random seed  2065 -> 0.625
-Confusion Matrix:
- [[ 66   7  14   2   3  11   3]
- [  1 130   2  11   8   8   0]
- [ 28  31 123  30  13  23  56]
- [  6   1   4 109   9   4  10]
- [  2   3   9   1  61   0   2]
- [  1   0   3   0   0  53   6]
- [  4   5  12  10   7  25  83]]
-Node Classification on random seed  2066 -> 0.606
-Confusion Matrix:
- [[ 59   8   3   5   2  22  13]
- [  7 126   5   1  11   1   6]
- [ 21  17 158  25  28  24  41]
- [  4   5  38  99  10   5   8]
- [  3  11   0   1  51   1   3]
- [  2   0   2   4   1  43   3]
- [ 13   3  16   2   4  15  70]]
-Node Classification on random seed  2067 -> 0.583
-Confusion Matrix:
- [[ 70   4   2   2   6   5   9]
- [  3 123   4   7   4   4   2]
- [ 27  21 125  56  45  21  39]
- [ 13   5   9  84  20   6  18]
- [  1   7   3   0  61   1   3]
- [  4   2   4   2   2  43   3]
- [ 16   3   5   8   5  16  77]]
-Node Classification on random seed  2068 -> 0.589
-Confusion Matrix:
- [[ 61   5   4   3  11  11   5]
- [  4 129   8   2  12   2   1]
- [ 22  16 121  64  29  16  49]
- [ 14   1  12 107  10  10  18]
- [  3   4   4   1  57   2   3]
- [  4   0   7   1   2  34   2]
- [  9   2  12   6   7  13  80]]
-Node Classification on random seed  2069 -> 0.625
-Confusion Matrix:
- [[ 79   2   0   1   4   4  12]
- [  5 119   9   2   9   2   3]
- [ 28  21 133  30  48  24  39]
- [ 13   4   9 108   4   5  21]
- [  2   6   5   1  58   0   1]
- [  8   3   0   0   1  45   5]
- [ 21   0   7   7   5   4  83]]
-Node Classification on random seed  2070 -> 0.603
-Confusion Matrix:
- [[ 63   4   7  10   2   8  17]
- [  6 130   6   1   7   6   6]
- [ 21  30 148  20  25  23  44]
- [  9   6  13  96   6   2  13]
- [  0   1   5   1  50   0   1]
- [  1   3   1   7   1  56   5]
- [ 12  10   6  16  22  13  60]]
-Node Classification on random seed  2071 -> 0.578
-Confusion Matrix:
- [[ 59   2   5   4   8  19  14]
- [  6 108   1   4  10   6  13]
- [ 37  25 115  54  21  15  52]
- [ 21   1  11 104   8   9   8]
- [  1  10   0   1  70   1   1]
- [  2   6   0   3   0  42   6]
- [  9   4   3   4   2  15  80]]
-Node Classification on random seed  2072 -> 0.611
-Confusion Matrix:
- [[ 49   2   7   2  12  23  10]
- [  6 127   3   4   6   2   6]
- [ 16  14 142  34  40  22  44]
- [  8   7  14 115   1   4  15]
- [  1   5   4   0  63   0   1]
- [  0   0   0   0   2  43  20]
- [  8   3  10  15   9   9  72]]
-Node Classification on random seed  2073 -> 0.561
-Confusion Matrix:
- [[ 60   7   3   2   3  16   6]
- [  1 115   4   4   8   1   2]
- [ 30  31 111  30  36  28  54]
- [ 15   3  11 109   4   7  19]
- [  1   6   2   0  68   2   6]
- [  3   6   2   4   2  41   5]
- [ 12   4   3   5  12  39  57]]
-Node Classification on random seed  2074 -> 0.627
-Confusion Matrix:
- [[ 68   4   4   1   5  17   2]
- [  1 140   7   5   2   0   7]
- [ 30  27 140  56  21   9  26]
- [ 25   9  15  86   2   2   8]
- [  1   6   3   0  79   0   7]
- [  4   5   6   0   3  46   3]
- [ 11   1  11   8   6  13  68]]
-Node Classification on random seed  2075 -> 0.592
-Confusion Matrix:
- [[ 73   4   2   1   3  13  29]
- [  1 125   1   0   3   4   5]
- [ 29  35 116  54  22  16  42]
- [ 19   6  14  84   7   3   9]
- [  1   7   0   1  57   0   2]
- [  5   1   3   2   0  44  15]
- [ 18   6   9   2   5   9  93]]
-Node Classification on random seed  2076 -> 0.609
-Confusion Matrix:
- [[ 76   5   0   2   1  12  22]
- [  1 124   5   0   6  10   3]
- [ 21  26 140  44  29  22  39]
- [ 23   9   5  83   6   5  12]
- [  1   4   1   0  66   1   3]
- [  4   1   2   7   1  41   9]
- [ 16   4  10   0   8  11  79]]
-Node Classification on random seed  2077 -> 0.614
-Confusion Matrix:
- [[ 66   2   6   8   6   9   2]
- [ 11 124   6   7   3   2   8]
- [ 14  21 107  35  46  21  39]
- [ 17   1  12 129   1   5  13]
- [  3   4   0   0  71   0   2]
- [  5   1   3   5   6  44   4]
- [  7   8  12  11   7  13  73]]
-Node Classification on random seed  2078 -> 0.601
-Confusion Matrix:
- [[ 68   1   3  15   5  10  13]
- [  8 121   5   2  10   1   5]
- [ 17  16 137  60  22  18  44]
- [  2   5  20  93   4   8  19]
- [  0   7   2   2  67   1   3]
- [  5   1   1   5   2  40   6]
- [  5   0   5   7  18  16  75]]
-Node Classification on random seed  2079 -> 0.641
-Confusion Matrix:
- [[ 67   7   2  12   9   9  11]
- [  1 142   6   1  10   8   2]
- [ 17  16 141  34  21  14  56]
- [  7   7   7  98   4   2  19]
- [  0   4   5   0  60   0   5]
- [  1   3   1   3   1  53   9]
- [  6   3   6  10   5  15  80]]
-Node Classification on random seed  2080 -> 0.588
-Confusion Matrix:
- [[ 80   3   2   3   6  16   2]
- [  5 115   6   9   8   6   0]
- [ 20  31 131  38  14  25  40]
- [ 17   8  17 111   9   8  13]
- [  2   4   2   3  61   1   2]
- [  7   3   7   4   1  38   4]
- [ 13   5   4  15  10  19  52]]
-Node Classification on random seed  2081 -> 0.616
-Confusion Matrix:
- [[ 74   0   4   8   2  16   7]
- [  7 115   8   0  14   5   5]
- [ 31  16 136  25  43  30  36]
- [ 12   5  12 100   4   4   9]
- [  1   5   6   1  57   4   3]
- [  2   1   1   0   0  59  13]
- [  6   2   7   6   7  16  75]]
-Node Classification on random seed  2082 -> 0.662
-Confusion Matrix:
- [[ 79   2   0   4   4   7  15]
- [  3 140   3   6   5   2   3]
- [ 23  30 168  10  16  20  51]
- [ 11   3  18 104   3   1  12]
- [  2   8   4   2  60   2   0]
- [  5   3   1   1   0  37   6]
- [ 15   5  16   3  10   3  74]]
-Node Classification on random seed  2083 -> 0.566
-Confusion Matrix:
- [[ 71   8   3   2   3   7  12]
- [  8 113  12   5  10   1   6]
- [ 31  28 106  37  29  28  45]
- [ 20   1  18 105   4   5   8]
- [  1   7   2   2  58   0   3]
- [  7   0   3   0   1  44   7]
- [ 21  11  18   6   4  10  69]]
-Node Classification on random seed  2084 -> 0.61
-Confusion Matrix:
- [[ 66   1   2   3   0  17  14]
- [  7 119   5   2   9   4   0]
- [ 29  26 124  36  46  20  44]
- [ 13   6  11 106   2   6  10]
- [  4   8   4   2  61   0   2]
- [  3   1   1   1   0  54   2]
- [  5   4   8   3   6  23  80]]
-Node Classification on random seed  2085 -> 0.585
-Confusion Matrix:
- [[ 55   6  11  16   3   7   8]
- [  8 127   2   1   7   1   4]
- [ 15  31 114  36  46  22  36]
- [ 10   7   6 139   9   4   8]
- [  2   7   1   5  57   1   2]
- [  5   1   1   1   0  50   7]
- [  7   6  14  19  11  21  43]]
-Node Classification on random seed  2086 -> 0.594
-Confusion Matrix:
- [[ 58   2   7  14   7  12  19]
- [  9 119   3   2   8   0   2]
- [ 31  31 152  26  21  15  41]
- [ 19   5  27  97   4   8   7]
- [  0   2   5   2  49   1   2]
- [  8   0   1   6   0  41   7]
- [ 13   5   9  10   5  10  78]]
-Node Classification on random seed  2087 -> 0.644
-Confusion Matrix:
- [[ 61   5   4   8   3   8  19]
- [  3 133   9   1   4   2   5]
- [ 18  15 164  32  24  24  30]
- [  8   6  11  97   5   7  16]
- [  1   4   4   1  72   0   1]
- [  8   5   2   1   1  37   8]
- [  8   1  17   4   7  16  80]]
-Node Classification on random seed  2088 -> 0.652
-Confusion Matrix:
- [[ 82   7   9   3   0   7   6]
- [  5 130   5   1   3   1   3]
- [ 24  19 165  24  22  39  28]
- [ 11   4  18  91   2   8  14]
- [  0   6   7   1  69   0   3]
- [  9   0   0   4   1  41   7]
- [ 17   2   3   3  10  12  74]]
-Node Classification on random seed  2089 -> 0.644
-Confusion Matrix:
- [[ 71   3   3   5  11   9  10]
- [  4 119   1   2   9   1   5]
- [ 28  19 169  33  22  23  36]
- [ 16   5  12 100   4   1   6]
- [  0   7   5   2  67   1   1]
- [  5   4   0   2   0  47   5]
- [ 16   4  11   2   4  19  71]]
-Node Classification on random seed  2090 -> 0.605
-Confusion Matrix:
- [[ 70   1   3   5  10   4  10]
- [  2 120   9   2   9   4   4]
- [ 25  18 147  46  51  19  34]
- [  8   4  20  92   6  10  13]
- [  1   2   3   2  58   2   1]
- [  3   1   1   1   0  48   7]
- [  9   4  13   3   7  18  70]]
-Node Classification on random seed  2091 -> 0.609
-Confusion Matrix:
- [[ 54   5   1   8   5  11  13]
- [  2 106   9   4  10   2   6]
- [ 26  14 155  38  29  11  48]
- [ 15   2  14 110   7   2  18]
- [  2   4   5   0  66   1   5]
- [  5   1   3   0   0  47  15]
- [  8   2  13   3   8  16  71]]
-Node Classification on random seed  2092 -> 0.592
-Confusion Matrix:
- [[ 54   1   2  12  12  16  13]
- [  4 129   3   1  12   3   7]
- [ 29  38 152  22  20  23  29]
- [ 17   3  20  86  12  10  10]
- [  1   6   9   2  58   0   1]
- [  4   0   0   7   5  39   6]
- [  3   3  10   3   6  23  74]]
-Node Classification on random seed  2093 -> 0.615
-Confusion Matrix:
- [[ 77   2   3   3   3  15   3]
- [  3 126   4   5  10   2   3]
- [ 21  25 127  35  13  28  43]
- [  6   0  18 110   6   9  21]
- [  2  15   7   1  63   1   3]
- [  7   0   1   1   0  50   3]
- [ 14   2   7  14   5  21  62]]
-Node Classification on random seed  2094 -> 0.595
-Confusion Matrix:
- [[ 80   1   2   2   1  16  10]
- [  1 117   5   3   7   2  14]
- [ 29   9 149  31  26  31  43]
- [ 10   0  23  98  10   7  12]
- [  2   3   4   6  50   1   1]
- [  3   2   2  10   3  41   6]
- [ 11   2  19  16   2  17  60]]
-Node Classification on random seed  2095 -> 0.638
-Confusion Matrix:
- [[ 73   1   5   7   4   8   9]
- [  3 131   6   1   7   3   2]
- [ 23  26 142  33  29  22  32]
- [ 10   6   8 105   3  11  16]
- [  1   3   4   1  59   0   2]
- [  9   1   0   1   0  58   2]
- [ 14   5  12  10   9  13  70]]
-Node Classification on random seed  2096 -> 0.56
-Confusion Matrix:
- [[ 57   3   7   4   0   4  11]
- [  7 148   1   1  11   3   5]
- [ 40  24  87  45  37  29  46]
- [ 12   6  19  93   4   7  12]
- [  0   2   4   2  59   1   3]
- [  1   1   3   2   3  38   6]
- [ 11   8  12  21   9  13  78]]
-Node Classification on random seed  2097 -> 0.622
-Confusion Matrix:
- [[ 63   4   3   1   1  22  17]
- [  0 144   5   4   4   5   5]
- [ 19  28 169  18  19  28  28]
- [ 17  10  22  74   5   6  27]
- [  0   9   2   2  50   3   7]
- [  5   1   0   0   0  51   6]
- [  4   4  10   5  10  12  71]]
-Node Classification on random seed  2098 -> 0.618
-Confusion Matrix:
- [[ 64   2   6   1   2  20   8]
- [ 10 117   6   2  11   0   2]
- [ 20  22 156  29  24  17  47]
- [  7   7  26  94   4  10  11]
- [  5   5   6   2  61   1   1]
- [  5   4   3   2   1  45   3]
- [ 15   5   7   4   8  11  81]]
-Node Classification on random seed  2099 -> 0.585
-Confusion Matrix:
- [[ 70   8   2   4   5  12   7]
- [  6 128   7   3  10   3   5]
- [ 38  21 137  43  14  33  37]
- [ 13   7  13  85   6   6  10]
- [  1   7   5   0  60   0   0]
- [  7   1   2   2   1  44   2]
- [ 19   5   7  16  12  15  61]]
-Node Classification on random seed  2100 -> 0.637
-Confusion Matrix:
- [[ 74   2  10   5   3  10   6]
- [  3 127   8   1   6   4   9]
- [ 24  14 150  25  20  38  30]
- [ 13   2  11 117   6   5  19]
- [  1   6   3   0  49   0   3]
- [  2   0   4   4   0  46   6]
- [  6   1  13  12   5  23  74]]
-Node Classification on random seed  2101 -> 0.632
-Confusion Matrix:
- [[ 78   0   6   6   6   9   3]
- [  8 116   6   3   6   2   3]
- [ 10  26 142  54  26  19  52]
- [  6   3   6 109   6   7  16]
- [  0   3   5   3  62   0   1]
- [  5   5   0   2   2  48   6]
- [  6   2  12   7   8  12  77]]
-Node Classification on random seed  2102 -> 0.568
-Confusion Matrix:
- [[ 71   0   2   5   3  14  12]
- [  3 128   3   2  14   8   4]
- [ 40  32  85  60  26  22  39]
- [ 20   4  14  94  11   3  15]
- [  0   6   0   2  61   2   3]
- [  3   0   1   3   2  42   4]
- [  5   1   9   9   4  22  87]]
-Node Classification on random seed  2103 -> 0.615
-Confusion Matrix:
- [[ 77   5   1   0   4   8   8]
- [  7 120   5   1  15   3   4]
- [ 26  31 126  24  30  26  49]
- [ 12   3  16 115   9   2  10]
- [  2   5   2   1  61   0   5]
- [  7   3   0   2   0  47   3]
- [ 18   5   7  11   3  12  69]]
-Node Classification on random seed  2104 -> 0.596
-Confusion Matrix:
- [[ 79   1   2   3   3   8  15]
- [  2 137   4   6   4   3   6]
- [ 19  38 118  35  54  21  36]
- [ 15   9  14  80   8   5  10]
- [  2   6   3   2  54   0   2]
- [  5   2   3   1   2  43   4]
- [ 11   2   9   7  11  11  85]]
-Node Classification on random seed  2105 -> 0.572
-Confusion Matrix:
- [[ 68   3   6   4   9   5  12]
- [  3 118   6   2  15   3   2]
- [ 29  18 119  31  56  25  39]
- [ 12   3   7  94   5   9   9]
- [  0   2   3   0  70   0   4]
- [  4   0   1   6   0  55  10]
- [ 21   2  14  13  15  20  48]]
-Node Classification on random seed  2106 -> 0.623
-Confusion Matrix:
- [[ 72   2   3   1   4  13  22]
- [  0 141   8   0   3   3   6]
- [ 26  23 146  60  19  28  25]
- [  4   5   9  88   7   5  29]
- [  4  11   1   5  66   3   2]
- [  3   2   2   0   0  50   6]
- [  6   1   9   3   5   9  60]]
-Node Classification on random seed  2107 -> 0.607
-Confusion Matrix:
- [[ 77   2   5   5   7  12   8]
- [  4 131   6   3   2   0  11]
- [ 14  31 132  54  17  15  43]
- [ 10   3  16 104   7   1  17]
- [  0   9   4   1  61   0   3]
- [  5   4   0   5   2  40   3]
- [ 11   3  12  13   8  17  62]]
-Node Classification on random seed  2108 -> 0.622
-Confusion Matrix:
- [[ 58   5   9   7   5  12   5]
- [  0 120  11   5  14   0   3]
- [ 10  15 144  27  44  26  46]
- [ 21   2  11 109   8   5  12]
- [  0   4   2   1  66   0   0]
- [  4   3   1   2   2  42   5]
- [  9   6  13   4   5  14  83]]
-Node Classification on random seed  2109 -> 0.59
-Confusion Matrix:
- [[ 74   1   2   5   4   6   8]
- [  7 111  17   2  11   1   7]
- [ 21  17 136  21  32  23  54]
- [  9   7  15 101   8   8  13]
- [  3   6   5   5  57   0   3]
- [  8   1   2   6   1  47   4]
- [ 19   2  11  13   4  18  64]]
-Node Classification on random seed  2110 -> 0.627
-Confusion Matrix:
- [[ 66   5   4   6   4  19   6]
- [  2 126   5   8   4   0   2]
- [ 24  27 163  29  21  27  24]
- [  8   5  13  93   5   9  24]
- [  2   8   4   5  60   0   2]
- [  2   0   7   0   0  45   7]
- [ 18   6   6   4   4  17  74]]
-Node Classification on random seed  2111 -> 0.579
-Confusion Matrix:
- [[ 52  13   7   7   6   9  13]
- [  5 124   4   0   6   1   2]
- [ 25  32 123  50  23  24  33]
- [  8   6  17 106   3   4  22]
- [  1   6   1   5  60   3   3]
- [ 18   3   0   0   0  45   7]
- [ 10   4  16   8   6  10  69]]
-Node Classification on random seed  2112 -> 0.611
-Confusion Matrix:
- [[ 72   2   2   7   6   8   8]
- [  7 124   5   2   6   1   3]
- [ 31  16 138  26  36  21  56]
- [ 11   1  19  92   7   5  16]
- [  3   7   5   4  61   0   4]
- [ 10   0   1   0   4  46   5]
- [  8   7   6   5   5  13  78]]
-Node Classification on random seed  2113 -> 0.573
-Confusion Matrix:
- [[ 60   0  10   2   3  20   7]
- [  4 121   8   5   5   3  10]
- [ 31  22 127  28  18  29  52]
- [ 24   7  22  80   2   7  12]
- [  0   6   3   2  57   0   4]
- [ 10   0   2   2   1  50   3]
- [  7   1  17   1   7  30  78]]
-Node Classification on random seed  2114 -> 0.612
-Confusion Matrix:
- [[ 67   3   4   3   6   9  10]
- [ 10 127  11   2  15   2   5]
- [ 25  18 160  11  33  31  31]
- [ 20   6  10  77   8  11  16]
- [  4   8   3   4  56   0   6]
- [  3   3   6   0   2  44   4]
- [ 10   3  11   4   6  11  81]]
-Node Classification on random seed  2115 -> 0.63
-Confusion Matrix:
- [[ 80   4   1   1   4  14  11]
- [  7 122   7   5  12   0   2]
- [  9  16 154  33  22  41  43]
- [ 14   6  12  91   3   4  16]
- [  1   5   8   3  67   2   1]
- [  3   0   2   1   0  50   2]
- [ 10   3   1   5   4  32  66]]
-Node Classification on random seed  2116 -> 0.63
-Confusion Matrix:
- [[ 79   2   1   4   8   5   9]
- [  7 137   7   2   6   0   8]
- [ 33  16 141  37  42  14  17]
- [  3   1  19  97   7   4  19]
- [  0   8   4   1  63   0   4]
- [  8   1   3   1   3  41   4]
- [ 17   9  13  10   5   8  72]]
-Node Classification on random seed  2117 -> 0.636
-Confusion Matrix:
- [[ 77   5   2   3   5  11   8]
- [ 10 114  11   0   4   4   3]
- [ 28  17 155  35  19  25  27]
- [ 11   5  19 111   5  10  10]
- [  0   7   3   1  70   0   3]
- [  6   2   4   0   0  40   2]
- [ 13   3  14   8  10  11  69]]
-Node Classification on random seed  2118 -> 0.594
-Confusion Matrix:
- [[ 60   5   1   6   4  16  13]
- [  8 118   3   1  11   5   4]
- [ 24  24 136  39  25  25  41]
- [  8   4  13 106   4   6  15]
- [  5   3   4   2  60   0   3]
- [  2   0   0   0   0  47   7]
- [ 10   5  11   5  18  26  67]]
-Node Classification on random seed  2119 -> 0.637
-Confusion Matrix:
- [[ 91   0   8   3   1  16  17]
- [  1 139   8   1   6   4   3]
- [  8  21 147  40  22  17  46]
- [ 11   7   8  92   3  11  12]
- [  1   6   3   2  58   0   1]
- [  7   1   9   4   0  40   4]
- [ 21   1   7   7   8   7  70]]
-Node Classification on random seed  2120 -> 0.637
-Confusion Matrix:
- [[ 75   1   2   3   4  21   3]
- [  3 139   5   1   0   2   0]
- [ 35  22 150  32  17  25  26]
- [ 12   0  14 106   8   7  17]
- [  3  10   7   5  48   0   4]
- [  3   3   2   1   0  47   1]
- [ 19   4   8   5   6  22  72]]
-Node Classification on random seed  2121 -> 0.606
-Confusion Matrix:
- [[ 74   2   1   4   3  16   2]
- [  4 126   7   3  13   1   7]
- [ 34  18 135  35  24  30  28]
- [ 10   2  18 104  16   9   5]
- [  1   4   5   1  69   3   1]
- [  6   1   0   1   4  39   2]
- [  7   3  10  12  14  27  59]]
-Node Classification on random seed  2122 -> 0.634
-Confusion Matrix:
- [[ 65   1   2   1   4  11  20]
- [  2 141   9   2  12   4   5]
- [ 21  10 143  33  24  24  53]
- [ 11   2  11 101   9   6  11]
- [  3   8   6   3  56   2   1]
- [  8   1   5   3   0  45   4]
- [  4   1   7  10   3   9  83]]
-Node Classification on random seed  2123 -> 0.588
-Confusion Matrix:
- [[ 66   6  10   2   7  11   3]
- [  2 108   7   2  19   3   9]
- [ 15  21 128  41  44  26  37]
- [  9   1  21 102   4   2  15]
- [  5   5   2   4  58   1   6]
- [  5   4   0   0   7  47   5]
- [ 10   1   8   3  11  18  79]]
-Node Classification on random seed  2124 -> 0.596
-Confusion Matrix:
- [[ 56   4  17   5   4   9   9]
- [  6 117   6   0  10   2   4]
- [ 23  31 140  40  24  18  39]
- [ 14   6  12  94   5   6   8]
- [  1   6   3   0  55   3   3]
- [  5   0   3   1   2  59   8]
- [  9   5  10  18  15  10  75]]
-Node Classification on random seed  2125 -> 0.636
-Confusion Matrix:
- [[ 77   1  12   9   5   6   6]
- [  6 144   4   3   5   2   9]
- [ 17  24 136  22  27  22  37]
- [  9   6  12  96   5   3  20]
- [  0   7   2   0  58   1   4]
- [  6   1   3   1   1  41   6]
- [ 17   3  10   9   7  14  84]]
-Node Classification on random seed  2126 -> 0.612
-Confusion Matrix:
- [[ 82   2   3   7   6  10   6]
- [  4 107   6   3   9   3   6]
- [ 38  26 139  19  26  12  37]
- [ 12   3  23  86  13   7  21]
- [  3   5   4   0  58   1   1]
- [  1   0   5   4   1  57   0]
- [ 16   2   9   8   6  20  83]]
-Node Classification on random seed  2127 -> 0.6
-Confusion Matrix:
- [[ 66   1   3  11   5   7  11]
- [  4 147   3   3   2   5  10]
- [ 41  12 134  40  16  23  44]
- [ 18   1  12 103   1   3  18]
- [  1   2   5   2  53   2   2]
- [  8   2   3   1   1  32   7]
- [  9   3  15   7  17  19  65]]
-Node Classification on random seed  2128 -> 0.609
-Confusion Matrix:
- [[ 73   2   0  11   3  19   9]
- [  5 115   7   0   2   6   5]
- [ 18  23 147  26  32  25  36]
- [ 11  12  14  93   0   5   7]
- [  0   7   4   1  72   1   2]
- [ 15   0   5   0   3  30   5]
- [ 24   5  12  10   8  11  79]]
-Node Classification on random seed  2129 -> 0.629
-Confusion Matrix:
- [[ 74   4   3   1   6  10   7]
- [  2 136   8   1   5   1   2]
- [ 22  31 151  52  14  27  28]
- [ 17   3  10  86  11   8   9]
- [  0   9   1   5  58   2   4]
- [  8   1   2   2   1  53   3]
- [ 17   5   5   3   3  18  71]]
-Node Classification on random seed  2130 -> 0.644
-Confusion Matrix:
- [[ 73   3   7   3   3  19   8]
- [  4 134   6   2   1   1   3]
- [ 33  36 151  41  11  15  30]
- [  9   3  12 105   7   8   5]
- [  1   9   3   0  58   0   5]
- [  1   3   4   2   2  43   4]
- [ 18   4   6   3   4  17  80]]
-Node Classification on random seed  2131 -> 0.625
-Confusion Matrix:
- [[ 56   3   3   4   2  26  12]
- [  5 127   0   3   5   3   2]
- [ 27  12 158  45  25  21  30]
- [ 22   3   7 111  10   4   7]
- [  2   8   4   5  61   0   3]
- [  3   1   2   3   1  45   2]
- [  6   4   9  15   4  22  67]]
-Node Classification on random seed  2132 -> 0.595
-Confusion Matrix:
- [[ 81   1   5   1   5  13   4]
- [  9 131   5   3   5   2   3]
- [ 15  16 121  56  17  37  38]
- [ 17   3  17  89  12   8   8]
- [  4   7   6   2  60   2   2]
- [  7   3   3   2   0  41   5]
- [ 13   1   3  11   6  28  72]]
-Node Classification on random seed  2133 -> 0.625
-Confusion Matrix:
- [[ 72   3   1   6   5  27  13]
- [  5 135   4   4   7   3   3]
- [ 38  24 144  21  21  18  35]
- [  9   2  12 114   4   8   9]
- [  1   6   2   0  51   1   3]
- [  5   0   0   3   0  53   2]
- [ 11   5  10   6   6  32  56]]
-Node Classification on random seed  2134 -> 0.614
-Confusion Matrix:
- [[ 75   3   2   1   1  19  18]
- [ 10 124   3   1   2   4   5]
- [ 25  31 120  28  15  32  41]
- [ 10   1  15 105   3   7  20]
- [  2   3   4   1  62   2   5]
- [  0   1   5   0   2  41   7]
- [ 12   4   8   2  10  21  87]]
-Node Classification on random seed  2135 -> 0.601
-Confusion Matrix:
- [[ 74   0   5   8   8  20   4]
- [  3 135   5   2   1   1   5]
- [ 25  33 126  30  32  38  38]
- [  4  11  25 104   4  10  11]
- [  0   8   6   4  47   1   1]
- [  5   2   0   4   0  45   6]
- [  7   3   3   3   9  14  70]]
-Node Classification on random seed  2136 -> 0.603
-Confusion Matrix:
- [[ 68   4   5   4   1  15  13]
- [  1 118  10   2  14  10   1]
- [ 18  50 119  43  31  26  25]
- [  3   8  11 125   2   3  10]
- [  1   5   3   2  64   3   2]
- [  1   3   0   1   2  48   6]
- [  4   3  10  13  14  14  61]]
-Node Classification on random seed  2137 -> 0.624
-Confusion Matrix:
- [[ 70   2   8   4   3  14   1]
- [  2 124   7   3   8   4  10]
- [ 20  32 155  43  17  17  40]
- [ 10   6  13 108   2   6   5]
- [  1   9   4   5  42   1   7]
- [  1   0   7   0   2  59   5]
- [  7   2   7  13   9  19  66]]
-Node Classification on random seed  2138 -> 0.624
-Confusion Matrix:
- [[ 87   1   1  12   8   6   4]
- [  4 120   3   4   9   7   4]
- [  9  22 145  33  35  13  47]
- [ 14   4   6 110   5   8  12]
- [  1   9   0   1  58   0   1]
- [  9   1   6   1   5  29   1]
- [  9   5  13  19   8  16  75]]
-Node Classification on random seed  2139 -> 0.615
-Confusion Matrix:
- [[ 72   3   3   6   3  10   7]
- [  9 106   4   2   9   1   6]
- [ 18  19 159  39  43  10  38]
- [ 21  10  18  79   7  15   5]
- [  1   6   7   2  68   1   2]
- [  2   1   5   0   0  53   4]
- [ 14   2   8   5   4  15  78]]
-Node Classification on random seed  2140 -> 0.606
-Confusion Matrix:
- [[ 71   6   4   6   4   5  21]
- [  3 127   1   0  10   3   1]
- [ 18  36 113  36  38  18  34]
- [  6  10  11 113   6   2  13]
- [  1   7   3   6  68   1   4]
- [  5   7   1   3   0  48   6]
- [ 14   8   8   3  10  15  66]]
-Node Classification on random seed  2141 -> 0.6
-Confusion Matrix:
- [[ 88   1   7   1   8  18   3]
- [  5 118   6   4  10   5   3]
- [ 35  14 137  28  26  31  36]
- [ 16   4  28  83   2   6   9]
- [  0   5   4   5  57   1   3]
- [  6   0   2   1   2  51   5]
- [ 18   2  13   9   3  15  66]]
-Node Classification on random seed  2142 -> 0.624
-Confusion Matrix:
- [[ 65   0   3   2   5  13  20]
- [  5 139   2   2  13   1   7]
- [ 19  28 150  34  17  15  43]
- [ 11   5  26  94   3   2  10]
- [  3   7   3   1  54   0   4]
- [  5   1   2   3   2  43   8]
- [ 11   7   6   7   3  17  79]]
-Node Classification on random seed  2143 -> 0.624
-Confusion Matrix:
- [[ 74   3   1   3   3  15   7]
- [  2 136   9   5   6   2   4]
- [ 14  10 145  40  31  24  29]
- [ 15   6  19 106   4   7  13]
- [  0   7   2   2  53   0   4]
- [  5   0   8   4   2  44   6]
- [  8   4  13  11   6  22  66]]
-Node Classification on random seed  2144 -> 0.555
-Confusion Matrix:
- [[ 65   1   4   5   3   6   8]
- [  3 105   1   6  27   0   2]
- [ 26  30  94  42  46  22  59]
- [  5   5  16 110   3   7  15]
- [  2   5   2   0  74   0   2]
- [  9   3   3   4   5  43   4]
- [  8   6  17  15   2  16  64]]
-Node Classification on random seed  2145 -> 0.65
-Confusion Matrix:
- [[ 64   3   5   9   4  13  11]
- [  7 117   5   2   3   3   2]
- [ 21  18 152  43  16  16  43]
- [ 10   7  10 121   3   2  11]
- [  1   5   5   2  68   1   1]
- [  7   1   0   5   0  43   3]
- [ 12   6   4  12   6  12  85]]
-Node Classification on random seed  2146 -> 0.685
-Confusion Matrix:
- [[ 64   1   3  13   4   9  10]
- [  3 148   4   3   2   2   3]
- [ 17  32 159  23  31  19  23]
- [ 13   3   6 115   6   3   9]
- [  2   8   3   2  66   3   1]
- [  3   0   0   3   0  48   2]
- [  4   3  10  11   4  14  85]]
-Node Classification on random seed  2147 -> 0.622
-Confusion Matrix:
- [[ 68   3   7   4   3  16   9]
- [  4 136   2   5   1   1   5]
- [ 12  27 157  46  27  34  20]
- [ 13   2  14  86  11   6  14]
- [  0   5   2   2  61   1   1]
- [  6   2   1   1   3  51   2]
- [  7  10  16  10   3  20  63]]
-Node Classification on random seed  2148 -> 0.594
-Confusion Matrix:
- [[ 78   6   1  10   5  19   8]
- [ 11 122   5   3   7   5   5]
- [ 19  15 141  26  26  34  44]
- [  8   4  17  96  13   7  16]
- [  2   7   2   4  44   0   4]
- [  4   4   2   5   1  38  10]
- [  6   4   6   7   7  17  75]]
-Node Classification on random seed  2149 -> 0.614
-Confusion Matrix:
- [[ 63   2   5   9   6   9   9]
- [  2 133   6   3  10   4   2]
- [ 22  27 128  38  25  20  51]
- [ 13   2   2 107   3  10  16]
- [  0  10   3   2  59   1   5]
- [  4   0   2   3   1  43   5]
- [  5   2  17   5  11  14  81]]
-Node Classification on random seed  2150 -> 0.617
-Confusion Matrix:
- [[ 74   0   7   2   3  11   4]
- [  3 118   7   2   5   2   4]
- [ 35  29 166  27  19  17  31]
- [ 14   7  29  91   8   2  19]
- [  3   9   2   1  49   2   1]
- [  7   2   3   2   0  45   6]
- [  4   4  11  12  11  16  74]]
-Node Classification on random seed  2151 -> 0.633
-Confusion Matrix:
- [[ 84   4   2   3   3   4  12]
- [  4 124   4   0  13   2   8]
- [ 18  16 160  35  34  19  39]
- [  4   7  21  96   3   6  12]
- [  0   6   5   2  66   1   1]
- [  9   3   3   1   0  32   3]
- [ 11   2   9  17  10  11  71]]
-Node Classification on random seed  2152 -> 0.623
-Confusion Matrix:
- [[ 69   2   3   3   1  16   3]
- [  9 130   6   1   5   1   2]
- [ 12  28 145  42  21  26  35]
- [ 14   6  21  90   7  12  12]
- [  0   9   2   0  62   2   1]
- [  7   1   4   1   2  44   8]
- [ 13   7   9  12   5   6  83]]
-Node Classification on random seed  2153 -> 0.621
-Confusion Matrix:
- [[ 73   2  10   5   4  22   1]
- [  3 136   2   5  10   6   2]
- [ 31  20 144  37  39  23  21]
- [ 12   3  21  86   5   8   7]
- [  1   9   3   2  65   0   1]
- [  7   0   0   0   0  45   7]
- [ 12   4  13  10   3   8  72]]
-Node Classification on random seed  2154 -> 0.631
-Confusion Matrix:
- [[ 57   2   1   2   4  15  13]
- [  7 118   2   3  11   2   0]
- [ 22  20 164  38  12  15  51]
- [  8   4  22 116   2   3  11]
- [  4   1   7   0  61   1   1]
- [  9   0   4   5   7  44   7]
- [  9   0  12  16   6  10  71]]
-Node Classification on random seed  2155 -> 0.651
-Confusion Matrix:
- [[ 77   0   2   9   4  10   7]
- [  8 137   4   2  11   2   6]
- [ 27  16 152  30  32  24  22]
- [ 17   3  13  99   6   4   6]
- [  1   3   4   2  60   0   3]
- [  6   0   2   3   1  52   3]
- [ 11   1  14  14   5  11  74]]
-Node Classification on random seed  2156 -> 0.62
-Confusion Matrix:
- [[ 67   1   5   2   1   8  18]
- [  7 131   6   2   6   2   4]
- [ 21  33 144  38  23  24  36]
- [ 12   5  21 100  13   7   5]
- [  0   6   6   2  53   1   0]
- [  4   1   2   0   1  53   4]
- [  4   2  10   5  12  20  72]]
-Node Classification on random seed  2157 -> 0.596
-Confusion Matrix:
- [[ 64   6   7  15   0   9   9]
- [  4 127   5   2   7   0   7]
- [ 29  25 125  36  32  18  51]
- [ 13   6  15 101   4   6  16]
- [  2   9   5   2  61   0   3]
- [  6   1   2   0   0  42   4]
- [ 11   5   9   9   4  10  76]]
-Node Classification on random seed  2158 -> 0.604
-Confusion Matrix:
- [[ 74   2   3   4   8  21  10]
- [  4 113   4   0   4   6   6]
- [ 26  14 128  38  29  27  30]
- [ 12   2   6 101   7   8  27]
- [  2   9   3   3  62   1   4]
- [ 10   0   1   1   1  44   4]
- [  6   5   8   6   8  26  82]]
-Node Classification on random seed  2159 -> 0.6
-Confusion Matrix:
- [[ 61   2   6  11   3   9   6]
- [  6 118  12   1  16   3  10]
- [ 36  16 133  31  12  38  24]
- [ 16   4  19 107   8   9  11]
- [  3   0   7   5  62   0   2]
- [  8   0   2   5   2  49   4]
- [  6   2  15   8   9  13  70]]
-Node Classification on random seed  2160 -> 0.62
-Confusion Matrix:
- [[ 78   5   5   7   2  11  10]
- [  2 118   7   1  14   4   4]
- [ 32  27 130  28  27  28  37]
- [  6   7  13  99  10   8  12]
- [  1   5   7   3  64   2   1]
- [  2   0   1   1   1  49   5]
- [ 11   1   7   5  10  10  82]]
-Node Classification on random seed  2161 -> 0.594
-Confusion Matrix:
- [[ 60   1   1   3   7  30  10]
- [  5 122   7   4  10   3   5]
- [ 31  23 136  37  22  27  38]
- [ 14   2  13 102   1  12  10]
- [  0   5   8   0  58   1   2]
- [  8   3   1   1   1  46   3]
- [ 14   3  16   7   3  14  70]]
-Node Classification on random seed  2162 -> 0.594
-Confusion Matrix:
- [[ 62   3   5   4  11   7  11]
- [  3 127   4   3  11   8   1]
- [ 12  43 123  47  40  20  32]
- [ 29   1   8 106   7   3   5]
- [  2   3   9   0  63   0   1]
- [  2   2   1   9   2  47   3]
- [ 15   2   8  10   5  14  66]]
-Node Classification on random seed  2163 -> 0.621
-Confusion Matrix:
- [[ 73   2  14   4   3   6  13]
- [  8 139   1   1   5   2   1]
- [ 20  24 148  38  41  12  43]
- [ 18   8  16 101   7   2   8]
- [  0   7   4   2  50   1   0]
- [  2   4   1   0   1  45   5]
- [ 13   5  12   5  13   7  65]]
-Node Classification on random seed  2164 -> 0.659
-Confusion Matrix:
- [[ 67   1   1   5   2  10  13]
- [  3 134   6   2   3   4   2]
- [ 22  17 150  16  23  35  30]
- [ 19   3  12 113   6  10   6]
- [  1  15   4   3  48   0   1]
- [  3   2   0   7   1  60   3]
- [  7   5   5  10   5  18  87]]
-Node Classification on random seed  2165 -> 0.624
-Confusion Matrix:
- [[ 69   1   2   5   3   5  20]
- [  3 123   9   1   2   9   6]
- [ 21  18 148  38  33  18  43]
- [ 17  10  20 112   1   4   8]
- [  2   8   2   0  54   0   1]
- [  6   1   1   1   1  38   8]
- [  9   3   8   7   7  14  80]]
-Node Classification on random seed  2166 -> 0.599
-Confusion Matrix:
- [[ 61   1   9   3   3  15  13]
- [  5 115   5   3   7   2  11]
- [ 30  23 139  34  31  28  33]
- [ 18   2  26  96   4   6  14]
- [  1   5   1   4  58   1   8]
- [  9   0   4   0   0  46   3]
- [ 11   3   5   7   3  10  84]]
-Node Classification on random seed  2167 -> 0.661
-Confusion Matrix:
- [[ 75   5   2   2   2   6  14]
- [  9 124   4   1   8   5   2]
- [ 28  32 132  22  26  13  34]
- [ 19   2   8 122   2   6  11]
- [  0   3   6   3  63   1   1]
- [  7   0   1   1   0  52   9]
- [  5   3  11   6   6  13  93]]
-Node Classification on random seed  2168 -> 0.635
-Confusion Matrix:
- [[ 77   2   5   8   2  10  13]
- [ 14 128   7   2   2   2   3]
- [ 25  17 149  25  14  40  42]
- [  7   1  17 107   3   4  13]
- [  1  11   3   2  61   0   3]
- [  7   1   1   0   0  48   6]
- [ 10   3  12   5   6  16  65]]
-Node Classification on random seed  2169 -> 0.637
-Confusion Matrix:
- [[ 67   3   7   9   6   7  20]
- [  4 126   6   4  15   1   3]
- [ 29  10 147  18  25  26  30]
- [ 15   5  24 104   6   4   6]
- [  4   4   3   2  58   0   4]
- [ 10   2   3   2   0  52   7]
- [ 12   3   7   6   5   6  83]]
-Node Classification on random seed  2170 -> 0.612
-Confusion Matrix:
- [[ 76   4   9   2   3   9   4]
- [  3 119   3   3   8   6   6]
- [ 22  34 144  49  23  13  39]
- [  3   5  17 109   5   5  18]
- [  0   7   7   0  54   0   3]
- [  3   2   1   3   5  39   5]
- [  6   3  11   6   9  24  71]]
-Node Classification on random seed  2171 -> 0.612
-Confusion Matrix:
- [[ 71   5   0   3   4   7  18]
- [  4 118   3   9   5   6   2]
- [ 27  31 144  25  19  20  42]
- [ 26   3  13  95   6  12   7]
- [  0  10   3   3  58   0   6]
- [  3   2   3   1   1  50   3]
- [ 12   5  13   8   2  16  76]]
-Node Classification on random seed  2172 -> 0.589
-Confusion Matrix:
- [[ 66   1   6   5   3  14  21]
- [  5 133   6   5   2   2   2]
- [ 31  29 139  37  21  20  45]
- [  7   3  17  90   7  22  14]
- [  1   5   4   0  51   0   3]
- [  6   3   1   1   0  38   3]
- [  9   4  14   7  11  14  72]]
-Node Classification on random seed  2173 -> 0.654
-Confusion Matrix:
- [[ 88   1   2   0   4  11   5]
- [  6 137   3   0   3   3   4]
- [ 21  32 143  29  24  22  33]
- [ 16   2  17 109   0   5  12]
- [  0   7   3   2  63   1   5]
- [  9   0   5   1   0  46   4]
- [ 15   3  10   5   4  17  68]]
-Node Classification on random seed  2174 -> 0.59
-Confusion Matrix:
- [[ 96   0   1   7   7   3  10]
- [  4 130   8   1   4   2  10]
- [ 28  20 107  41  28  24  51]
- [ 11   1  25  81   8   3  15]
- [  1   6   4   1  61   1   5]
- [  4   3   2   2   0  40   1]
- [ 11   5   7  20   8  17  75]]
-Node Classification on random seed  2175 -> 0.607
-Confusion Matrix:
- [[ 67   2   4   4   7  16  11]
- [  5 112   9   5  11   5   5]
- [ 32  22 165  17  35  17  38]
- [ 14   6  22  94   7   2  14]
- [  2   6   2   1  53   0   5]
- [  7   4   2   4   0  35   1]
- [ 11   3  12   6   3  14  81]]
-Node Classification on random seed  2176 -> 0.617
-Confusion Matrix:
- [[ 76   0   1   5   4   8   8]
- [ 10 105  11   3  11   8   4]
- [ 21  12 151  39  35  26  34]
- [  9   7  20  92   3   2  18]
- [  2   7   5   3  69   0   1]
- [  9   0   1   2   1  44   5]
- [ 15   4   8   3   9   9  80]]
-Node Classification on random seed  2177 -> 0.647
-Confusion Matrix:
- [[ 78   3   7   6   6   6  11]
- [  2 130   5   4   6   2  10]
- [ 20  21 155  39  10  19  30]
- [ 13   7  12 109   1   5  15]
- [  1  10   4   4  55   0   4]
- [  6   2   7   1   1  33   5]
- [ 15   3   2  11   7  10  87]]
-Node Classification on random seed  2178 -> 0.637
-Confusion Matrix:
- [[ 75   1   3   3   5   3  10]
- [  7 119   6   8   4   6   7]
- [ 30  18 158  23  32  25  34]
- [ 10   3  21  98   3   4  19]
- [  2   6   4   6  54   4   1]
- [  7   1   1   1   0  52   4]
- [ 12   6   8   6   3   6  81]]
-Node Classification on random seed  2179 -> 0.636
-Confusion Matrix:
- [[ 65   1   0  10   1  10  17]
- [  4 127   2   4  19   2   4]
- [ 20  23 161  21  30  12  40]
- [  3   2  33  97   4   9  10]
- [  1   2  12   1  55   0   2]
- [  7   1   0   2   1  44   8]
- [  4   7   9   7   7  12  87]]
-Node Classification on random seed  2180 -> 0.625
-Confusion Matrix:
- [[ 73   2   3   3   6  18   1]
- [  4 125   6   3   2   2   6]
- [ 29  13 141  26   9  21  74]
- [ 13   1   9 113  12   6  13]
- [  1   5   3   4  52   5   4]
- [  4   1   2   2   0  44   4]
- [ 19   3   8  12   7   9  77]]
-Node Classification on random seed  2181 -> 0.632
-Confusion Matrix:
- [[ 63   3   2   8   0   8   9]
- [  7 131   6   3  18   0   1]
- [ 26  13 155  36  20  24  40]
- [ 14   4   8 108   5   7   9]
- [  2   8   7   1  48   0   4]
- [  9   0   3   0   1  43   3]
- [ 10   3  14   6   4  22  84]]
-Node Classification on random seed  2182 -> 0.604
-Confusion Matrix:
- [[ 65   2   7   6   4  16  10]
- [  2 133   4   2   8   2   6]
- [ 23  21 143  49  20  22  50]
- [  0   3  20 108   7   6  16]
- [  0   6   3   2  54   2   2]
- [  5   2   2   2   1  40   3]
- [  8   4  20  17   3   8  61]]
-Node Classification on random seed  2183 -> 0.599
-Confusion Matrix:
- [[ 51   6   6   4   3  11  19]
- [  2 132   5   7   9   1   2]
- [ 11  16 139  52  34  35  45]
- [  5   3  25  96   9   5  22]
- [  0   3   3   1  58   2   2]
- [  5   2   1   2   1  39   9]
- [  9   4   7   0   5   8  84]]
-Node Classification on random seed  2184 -> 0.604
-Confusion Matrix:
- [[ 64   2   3   5   8  10  12]
- [  5 116   1   3  27   2  10]
- [ 28  18 124  32  51  12  38]
- [  2   6  13  92   3   6  10]
- [  1   6   2   0  74   1   4]
- [ 10   0   4   2   0  42  10]
- [ 15   4   8   5  12   5  92]]
-Node Classification on random seed  2185 -> 0.597
-Confusion Matrix:
- [[ 58   8   6  14   3   5  11]
- [  7 127  10   2   7   1   3]
- [ 24  28 141  49  20  29  33]
- [ 18   1  22  92   8   2  13]
- [  1   5   1   4  60   1   0]
- [  5   2   0   3   4  45   8]
- [  7   4   6   5   6  17  74]]
-Node Classification on random seed  2186 -> 0.632
-Confusion Matrix:
- [[ 61   2   7  11   4  17   2]
- [  1 143   7   1   6   6   4]
- [ 19  22 145  22  29  23  41]
- [  6   5  13 101   6   4  11]
- [  1   7   3   2  73   1   2]
- [  6   8   1   3   1  48   4]
- [  6  10  13  11   5  15  61]]
-Node Classification on random seed  2187 -> 0.562
-Confusion Matrix:
- [[ 61   1   5   5   6   8  16]
- [  3 114   7   2  18   0  10]
- [ 32  17 119  54  26  24  44]
- [ 12   1  25  91   9   3  21]
- [  0   6   7   1  67   1   1]
- [  0   3   4   6   2  47   6]
- [  4   3   9   9   8  19  63]]
-Node Classification on random seed  2188 -> 0.611
-Confusion Matrix:
- [[ 73   4   2   2   6   3   9]
- [  7 108   6   5  13   2   6]
- [ 31  37 139  26  31  19  47]
- [  5   3  17 105   8   4  15]
- [  1  10   0   2  60   0   2]
- [  9   1   1   1   1  50   4]
- [ 20   7   7   5   3   7  76]]
-Node Classification on random seed  2189 -> 0.606
-Confusion Matrix:
- [[ 74   2   6   5   2  17   9]
- [  6 123   8   1   4   4   5]
- [ 19  17 130  67  24  28  38]
- [  8   5   7 101   3  10  13]
- [  3  14   6   1  57   0   1]
- [  3   1   3   3   1  48   2]
- [  8   5   7   6   3  19  73]]
-Node Classification on random seed  2190 -> 0.628
-Confusion Matrix:
- [[ 67   3   1   4   4  13  12]
- [  6 126   4   4   5   1   2]
- [ 23  31 143  33  31  21  41]
- [ 10   6  11 108   9   4  18]
- [  2   8   2   0  57   1   3]
- [  0   1   2   0   0  48   8]
- [ 13   9   8   0   2  16  79]]
-Node Classification on random seed  2191 -> 0.566
-Confusion Matrix:
- [[ 60   6   4   9   2   7  10]
- [  3 120  13   4   7   5   5]
- [ 18  26 105  36  53  38  37]
- [ 17   3  19  94   2  11  13]
- [  5   6   3   1  62   1   2]
- [  4   2   1   1   2  51   3]
- [  9   4   5   4   6  27  74]]
-Node Classification on random seed  2192 -> 0.621
-Confusion Matrix:
- [[ 77   4   1   2   6  13  18]
- [  4 123   8   0   8   4   2]
- [ 25  27 152  20  37  38  30]
- [  8   4  19  84   9   8  15]
- [  1   4   2   2  56   0   0]
- [  4   0   1   1   0  51   4]
- [  5  11   5  12   4  13  78]]
-Node Classification on random seed  2193 -> 0.583
-Confusion Matrix:
- [[ 65   6   2   7   4   9  11]
- [  0 131   5   3   6   3   5]
- [ 28  27 121  30  42  28  23]
- [ 20   4  30  89   1   7  12]
- [  1   7   1   2  56   1   3]
- [  9   2   2   2   0  44   7]
- [ 22   4  10  10   3  18  77]]
-Node Classification on random seed  2194 -> 0.625
-Confusion Matrix:
- [[ 71   1   5   4   2  14   8]
- [  4 100   7   3  20   4   5]
- [ 23  13 168  37  26  25  37]
- [ 14   0  20  85   8  10   7]
- [  2   7   3   1  61   3   3]
- [  1   1   1   2   0  56   8]
- [  8   0  12   3   6  17  84]]
-Node Classification on random seed  2195 -> 0.592
-Confusion Matrix:
- [[ 69   4   8   6   5   8   8]
- [  7 126   7   0   6   0   5]
- [ 31  27 145  21  28  31  56]
- [ 19  12  12  86   2   7  14]
- [  1   5   1   0  48   4   3]
- [  5   1   3   0   0  46   6]
- [ 13   4  14  12   3   9  72]]
-Node Classification on random seed  2196 -> 0.608
-Confusion Matrix:
- [[ 64   7   4   5   1   5   9]
- [  9 109   7   2   4   4   6]
- [ 21  29 123  55  26  39  24]
- [  4   3  21 107   7   5  12]
- [  2   4   2   1  69   1   4]
- [  2   7   4   2   1  53   4]
- [  9   5   8   4   9  14  83]]
-Node Classification on random seed  2197 -> 0.601
-Confusion Matrix:
- [[ 72   5   5   3   1  20  11]
- [  3 111  16   2   7   3   6]
- [ 14  19 129  46  30  19  40]
- [ 11   6  13 105   8   8  10]
- [  1   5   4   1  56   3  11]
- [  4   0   5   1   0  39   5]
- [  4   2  11  10   4  22  89]]
-Node Classification on random seed  2198 -> 0.669
-Confusion Matrix:
- [[ 71  13   2   5   3  13   9]
- [  4 122   7   1   5   2   6]
- [ 24  11 161  18  22  21  46]
- [ 14   1  16 122   5   0   7]
- [  3   5   4   1  64   2   2]
- [ 10   1   2   0   1  56   5]
- [  6   0   9   6   5  14  73]]
-Node Classification on random seed  2199 -> 0.625
-Confusion Matrix:
- [[ 76   2   4   5   3  11  12]
- [  2 116   5   5  11   7   9]
- [ 19  14 143  27  21  34  48]
- [ 14   1   7 127   7   5   8]
- [  2   6   6   1  52   1   3]
- [  1   1   1   7   7  38   4]
- [ 10   2   6  14   7  15  73]]
-Node Classification on random seed  2200 -> 0.67
-Confusion Matrix:
- [[ 77   3   1   1   5   8   8]
- [  5 141   3   1  15   5   0]
- [ 15  21 161  25  13  31  40]
- [ 17   2   9 101   4   7  14]
- [  1   4   3   1  66   4   2]
- [  1   0   4   3   4  52   1]
- [ 14   2   5   3  10  15  72]]
-Node Classification on random seed  2201 -> 0.586
-Confusion Matrix:
- [[ 67   3   9   5   2  20   6]
- [  6 118   8   1   9   6   3]
- [ 15  29 106  29  24  35  51]
- [ 10   7  14 120   1   3  32]
- [  1   8   2   0  57   3   1]
- [  7   4   3   0   0  42  10]
- [ 10   6   9   4   5  13  76]]
-Node Classification on random seed  2202 -> 0.615
-Confusion Matrix:
- [[ 79   5   3   2   5  14   9]
- [  4 135   4   2   5   3   3]
- [ 22  34 111  20  47  20  47]
- [ 15   2  22  87   9   2  14]
- [  0   8   3   1  69   0   4]
- [  6   1   0   3   0  42   3]
- [ 14   4   7   4   9   5  92]]
-Node Classification on random seed  2203 -> 0.614
-Confusion Matrix:
- [[ 65   2   1   3   4  12  20]
- [  7 113  10   0   6   3   2]
- [ 33  18 150  37  24  29  27]
- [ 23   5  16  92   9  11   8]
- [  3   5   7   0  57   0   2]
- [  8   1   0   2   3  52   2]
- [ 13   4  10   2   1  13  85]]
-Node Classification on random seed  2204 -> 0.636
-Confusion Matrix:
- [[ 73   2   5   5   2   9  11]
- [  7 126   4   4   5   2   7]
- [ 37  13 144  34  20  29  40]
- [ 10   9   7 117   1   5  21]
- [  1   1   2   4  63   1   4]
- [  6   2   1   1   0  38   9]
- [  9   6   6   8   6   8  75]]
-Node Classification on random seed  2205 -> 0.589
-Confusion Matrix:
- [[ 75   1   5   7   4  13  11]
- [  5 129   3   3   6   3   1]
- [ 35  27 116  28  34  44  32]
- [  7   2  15 100   7   1  14]
- [  3   6   2   1  64   4   0]
- [  9   3   3   3   0  48   3]
- [ 15   8  17   4   6  16  57]]
-Node Classification on random seed  2206 -> 0.611
-Confusion Matrix:
- [[ 58   6   4   9   3   6  12]
- [  6 140   4   1   5   1   3]
- [ 22  24 144  47  20  15  41]
- [ 13   8  13 108   5   5  24]
- [  0  11   5   0  42   2   3]
- [ 13   2   2   0   0  47   3]
- [  9   7  12   9   4  10  72]]
-Node Classification on random seed  2207 -> 0.65
-Confusion Matrix:
- [[ 71   3   1   3   3   8   8]
- [  3 128   5   1  13   2   3]
- [ 24  14 179  17  23  22  38]
- [  4   2  25  91  12   8  14]
- [  1   4   2   1  65   3   3]
- [  8   5   4   1   0  37   7]
- [  5   5  13   5  10  17  79]]
-Node Classification on random seed  2208 -> 0.64
-Confusion Matrix:
- [[ 73   4   6   3   7  10   3]
- [  3 139   5   4   8   2   3]
- [ 17  25 157  32  19  21  35]
- [ 10   0  12 113   6  14  18]
- [  2   8   4   5  55   0   5]
- [  2   1   5   2   0  45   3]
- [ 15   6  15   3   3  14  58]]
-Node Classification on random seed  2209 -> 0.609
-Confusion Matrix:
- [[ 57   4   6   6   4  19  11]
- [  4 126   6   1   8   3   3]
- [ 34  32 139  22  28  20  32]
- [ 11   6  15 115  10   4   8]
- [  1  11   4   3  51   1   2]
- [  6   2   6   0   3  35   0]
- [ 12   5  10   8   6  14  86]]
-Node Classification on random seed  2210 -> 0.63
-Confusion Matrix:
- [[ 77   2   2   6   6  14   3]
- [  1 118   6   1   6   2  12]
- [ 19  15 151  35  31  20  39]
- [ 14   3  13 104   8   9  13]
- [  0   5   4   3  61   0   0]
- [  6   0   7   1   0  34   2]
- [  8   3  17   7  17  10  85]]
-Node Classification on random seed  2211 -> 0.643
-Confusion Matrix:
- [[ 67   2   3   4   5  12   6]
- [  2 132   4   3  17   2   3]
- [ 17  20 144  33  26  28  48]
- [ 12   3   7 124   4   3  10]
- [  1   4   4   0  55   2   3]
- [  7   0   2   0   3  46   3]
- [  6   5   6  10  11  16  75]]
-Node Classification on random seed  2212 -> 0.621
-Confusion Matrix:
- [[ 66   1   2   8   7  13   6]
- [  8 138   5   3  10   2   0]
- [ 23  30 162  25  19  22  40]
- [ 10   2  24  98  10  12  15]
- [  1   4   5   0  51   0   3]
- [  7   1   2   1   2  39   3]
- [  8   1  12   8   6  18  67]]
-Node Classification on random seed  2213 -> 0.628
-Confusion Matrix:
- [[ 63   2   2  10   6  17  11]
- [  5 152   9   3   3   1   0]
- [ 29  23 134  21  29  19  25]
- [ 22   4  15  91  10  11   8]
- [  3   5   6   1  56   0   0]
- [  3   1   3   3   0  48   7]
- [ 13   8  15   2   4  13  84]]
-Node Classification on random seed  2214 -> 0.63
-Confusion Matrix:
- [[ 54   2   8   5   9  13  12]
- [  2 127   9   3  11   0   3]
- [ 22   5 143  23  22  19  64]
- [  3   1  17 118   6   2  16]
- [  0   6   7   0  64   2   2]
- [  2   2   5   2   2  48   6]
- [  7   4   6  19   4  17  76]]
-Node Classification on random seed  2215 -> 0.598
-Confusion Matrix:
- [[ 61   0  20   3   6  12   3]
- [  4 117   7   6  11   1   4]
- [ 14  29 135  49  31  34  18]
- [  9   3   6 108   7   7  17]
- [  1   6   4   4  58   0   5]
- [ 10   2   0   7   0  42  11]
- [  4   4  14   5   8  16  77]]
-Node Classification on random seed  2216 -> 0.592
-Confusion Matrix:
- [[ 76   1   2   1   1  21   7]
- [  5 117   5   5  10   6   2]
- [ 31  11 117  35  31  35  26]
- [ 18   2  17 101   8  14   4]
- [  1   6   5   2  58   5   2]
- [  8   1   1   5   0  48   5]
- [ 16   2   5  18   1  27  75]]
-Node Classification on random seed  2217 -> 0.633
-Confusion Matrix:
- [[ 74   4   1   6   3  16   8]
- [  2 114  10   5  16   0   1]
- [ 13  24 129  48  16  30  47]
- [  7   2   8 117   3   7   5]
- [  0   8   5   1  56   1   4]
- [  4   0   3   3   0  53   4]
- [ 12   9  12   5   3  11  90]]
-Node Classification on random seed  2218 -> 0.615
-Confusion Matrix:
- [[ 58   3   8   7   3  13  11]
- [  1 131   9   4   3   2   0]
- [ 23  37 132  24  32  14  50]
- [  5   5  23  98  10   6  11]
- [  0   6   0   2  63   0   2]
- [  9   1   1   4   0  45   9]
- [ 10   2   7  14   3  11  88]]
-Node Classification on random seed  2219 -> 0.613
-Confusion Matrix:
- [[ 76   1   7   3  10  14   3]
- [  2 117   7   4  11   2   8]
- [  5  15 146  52  25  49  39]
- [  6   2  15 103   6   3  11]
- [  1  11   2   3  56   2   3]
- [  5   2   2   4   0  43   0]
- [  8   0   6   8   8  22  72]]
-Node Classification on random seed  2220 -> 0.61
-Confusion Matrix:
- [[ 69   4   2   6   6   7  16]
- [  5 126   5   1   8   4   0]
- [ 22  22 143  31  48  16  32]
- [  8  10   7  90   7   2  23]
- [  2   5   2   1  64   1   2]
- [  5   3   1   1   0  44   9]
- [ 14   5   8   6  13  20  74]]
-Node Classification on random seed  2221 -> 0.612
-Confusion Matrix:
- [[ 78   1  10  11   4   8   7]
- [  2 132   5   2   5   2   6]
- [ 13  33 137  41  35  28  28]
- [ 10   1  25  95   4   6   6]
- [  1   3   9   1  66   1   2]
- [  4   0   5   9   2  43   5]
- [  7   2  14  14  11   5  61]]
-Node Classification on random seed  2222 -> 0.622
-Confusion Matrix:
- [[ 72   3   0   5   4   5   5]
- [  8 116   6   2  14   4   1]
- [ 31  14 161  20  32  25  42]
- [ 11   0  13 115  11   5  11]
- [  3   7   5   2  63   2   2]
- [  3   2   1   8   4  36   2]
- [ 15   1   9  14  13  13  59]]
-Node Classification on random seed  2223 -> 0.566
-Confusion Matrix:
- [[ 61   3   1   4   6  18  19]
- [  4 116   9   1  13   3   3]
- [ 29  27 139  28  47  12  41]
- [ 24   8  20  64  12   3  18]
- [  6   6   4   1  56   2   2]
- [  3   2   3   7   0  40   5]
- [ 10   5   3   4   8  10  90]]
-Node Classification on random seed  2224 -> 0.589
-Confusion Matrix:
- [[ 70   0   4  14   5  18   6]
- [  6 118   2   6  12   1   3]
- [ 26  22 123  28  37  35  23]
- [ 13   4  14  88  12  16   9]
- [  0   6   2   0  66   1   3]
- [  4   3   6   1   1  48   2]
- [  8   4   9  24   4  17  76]]
-Node Classification on random seed  2225 -> 0.616
-Confusion Matrix:
- [[ 58   5   5   4   7   8  10]
- [  4 126  12   1   9   3   4]
- [ 14  26 164  27  35  17  45]
- [ 22   2  12 102   3   6   9]
- [  1   5   5   3  45   5   9]
- [  3   3   3   2   0  42   7]
- [  9   5   7  14   7   6  79]]
-Node Classification on random seed  2226 -> 0.65
-Confusion Matrix:
- [[ 73  11   0   3   3   5  11]
- [  6 142   2   5   6   1   2]
- [ 16  19 131  30  31  23  33]
- [ 10   4   8 108   3  12  12]
- [  2   7   3   4  56   2   1]
- [  4   2   3   0   1  51  14]
- [ 11   4   5   3  10  18  89]]
-Node Classification on random seed  2227 -> 0.6
-Confusion Matrix:
- [[ 56   9   7  18   1  23   3]
- [  6 139   5   4   4   3   3]
- [ 32  27 144  29  19  20  40]
- [  5   2  15  91  13   4  15]
- [  1  10   5   1  47   0   5]
- [  1   1   2   3   0  56   3]
- [  5   4   3  11   4  34  67]]
-Node Classification on random seed  2228 -> 0.673
-Confusion Matrix:
- [[ 68   0   6   4   5   5   8]
- [  1 133   8   2   9   0   2]
- [ 17  17 175  20  16  22  49]
- [  8   6  14 104   4   6  19]
- [  0   9   3   0  67   0   5]
- [  0   2   3   0   0  42   6]
- [ 18   2   9   4   6  12  84]]
-Node Classification on random seed  2229 -> 0.604
-Confusion Matrix:
- [[ 75   6   3   9   2  18   2]
- [ 10 119   4   1  16   3   4]
- [ 29  24 135  31  12  37  34]
- [ 10   3  12  95   5  11  13]
- [  4   3   4   2  64   4   0]
- [  8   0   1   2   0  49   2]
- [ 19   4  10   8   3  23  67]]
-Node Classification on random seed  2230 -> 0.623
-Confusion Matrix:
- [[ 65   3   4   9   2  11   4]
- [  8 147   5   2   9   2   3]
- [ 32  18 142  32  35  17  27]
- [ 12   5  17  96   4   7  10]
- [  1   7   7   0  59   1   2]
- [  3   2   1   3   1  45   4]
- [  7   3  13  18   8  18  69]]
-Node Classification on random seed  2231 -> 0.601
-Confusion Matrix:
- [[ 60   3   7   8   2  12   5]
- [  3 138   8   4  11   4   1]
- [ 24  25 129  42  31  15  41]
- [  8   2   6 109   8   6  26]
- [  1   5   4   2  48   2   2]
- [  2   0   1   1   0  50   3]
- [ 11   5   7  11   3  37  67]]
-Node Classification on random seed  2232 -> 0.616
-Confusion Matrix:
- [[ 69   1   4   2   6   5  11]
- [ 12 133   6   1   7   1   6]
- [ 30  23 153  28  33  27  29]
- [  6   3  20  79  10   7  18]
- [  0   6   6   1  60   0   1]
- [  9   1   5   1   0  39   4]
- [  9   4   8   1  12  20  83]]
-Node Classification on random seed  2233 -> 0.573
-Confusion Matrix:
- [[ 52   2   9   4   6  20  11]
- [  4 123   7   9   8   4   6]
- [ 25  19 151  31  25  35  52]
- [ 21   1  12  74   6   5  28]
- [  0   6   2   1  47   1   3]
- [  4   2   0   0   2  51   2]
- [  5   3  11   4  11  20  75]]
-Node Classification on random seed  2234 -> 0.642
-Confusion Matrix:
- [[ 84   5   3   4   2   4   5]
- [  5 129   6   3   3   2   2]
- [ 35  18 158  27  27  21  31]
- [ 11   0  23 106  14   5  20]
- [  1  10   3   2  52   0   3]
- [  9   1   1   0   0  48   4]
- [ 16   1  10   2  12   7  65]]
-Node Classification on random seed  2235 -> 0.602
-Confusion Matrix:
- [[ 74   3   3   5   2   6  13]
- [  4 134   9   1  13   0   1]
- [ 22  22 137  42  38  15  50]
- [ 13   6  13  94   2   7  19]
- [  2   7   4   3  53   3   2]
- [  2   3   5   0   2  41   9]
- [ 14   4   7   4   7  11  69]]
-Node Classification on random seed  2236 -> 0.552
-Confusion Matrix:
- [[ 58   3   2   7   7  10  19]
- [  2 128   4   4   6   4   5]
- [ 29  21  94  57  31  21  43]
- [ 22   7  16  87  10  12  13]
- [  2   6   2   3  64   2   1]
- [  2   1   1   2   0  62   9]
- [ 20   7   6   8   4  17  59]]
-Node Classification on random seed  2237 -> 0.581
-Confusion Matrix:
- [[ 43   5  12   4   9  10  11]
- [  5 126  12   5  10   4   5]
- [ 13  16 130  47  23  26  52]
- [ 19   8  14 100   4   6  13]
- [  0   5   2   1  58   1   5]
- [  8   3   1   8   1  34  13]
- [  6   6   6   4  10   6  90]]
-Node Classification on random seed  2238 -> 0.614
-Confusion Matrix:
- [[ 79   3   4   5   5  14   2]
- [  6 135   6   5   3   1   2]
- [ 16  16 133  48  24  33  36]
- [  7   3  26  94   8   6  11]
- [  2   7   8   6  56   0   4]
- [  5   1   0   6   2  41   3]
- [  8   7   6   8   3  20  76]]
-Node Classification on random seed  2239 -> 0.662
-Confusion Matrix:
- [[ 50  10   3   6   1  20  14]
- [  1 131   5   3   6   2   4]
- [ 16  23 157  25  26  15  39]
- [ 10   4   7 119   2   6  19]
- [  1   6   1   0  61   0   1]
- [  8   0   0   1   0  55   5]
- [ 17   3   8   2   8  10  89]]
-Node Classification on random seed  2240 -> 0.652
-Confusion Matrix:
- [[ 78   4   5   5   3   4  17]
- [  6 141   0   3  11   1   1]
- [ 17  21 146  27  33  14  40]
- [  9   3  19  97   2   9  15]
- [  0   4   0   0  66   0   3]
- [  6   3   2   0   0  37   4]
- [ 16   3   5   9   9  15  87]]
-Node Classification on random seed  2241 -> 0.611
-Confusion Matrix:
- [[ 64   4   4   6   5  13  13]
- [  5 120   7   2   8   0  10]
- [ 26  35 145  21  12  14  47]
- [ 10   1  37  95   6   5  15]
- [  1   5   4   1  62   0   2]
- [  2   0   4   4   0  44   7]
- [  9   6   7   4  12  15  81]]
-Node Classification on random seed  2242 -> 0.634
-Confusion Matrix:
- [[ 82   0  10   8   4  10   4]
- [  5 133   1   2   4   4   6]
- [ 21  19 141  30  36  16  49]
- [  7   6  24 108   1  17   6]
- [  1   1   8   1  61   4   1]
- [  1   1   3   2   0  41  10]
- [  8   2  15   1   1  16  68]]
-Node Classification on random seed  2243 -> 0.591
-Confusion Matrix:
- [[ 63   4   6  10   6   9  10]
- [  3 130   9   4  10   0   8]
- [ 37  10 133  39  33  34  32]
- [ 21   3  12  94   4   6   7]
- [  0   1   5   1  61   1   2]
- [ 10   4   8   1   1  41   4]
- [ 11   1   5   9   7  21  69]]
-Node Classification on random seed  2244 -> 0.615
-Confusion Matrix:
- [[ 67   6   5   2   8  11  16]
- [  4 119   4   1   5   1   2]
- [ 28  24 158  19  26  10  41]
- [ 17   2  24  75   6  15  19]
- [  0   3   3   1  58   1   2]
- [  6   1   0   3   0  52   6]
- [ 10   5   7  11  13  17  86]]
-Node Classification on random seed  2245 -> 0.602
-Confusion Matrix:
- [[ 56   1  10   1   6  16  11]
- [  0 143   6   1   9   3   6]
- [ 23  26 116  33  13  29  55]
- [ 15   5  25 101   5   4   9]
- [  0   4   5   3  64   1   2]
- [  8   1   3   4   1  43   6]
- [ 10   3   8   9   7  11  79]]
-Node Classification on random seed  2246 -> 0.635
-Confusion Matrix:
- [[ 69   4   1   1   5  11   8]
- [  4 130   3   3   4  12   6]
- [ 29  21 156  21  28  15  42]
- [ 10   1  21  79   2   6  19]
- [  0   6   5   0  68   0   3]
- [  7   0   2   1   2  40   5]
- [ 16   7  13   3   8  10  93]]
-Node Classification on random seed  2247 -> 0.624
-Confusion Matrix:
- [[ 68   2   6   7   5  11  17]
- [  6 127   7   6   5   1   9]
- [ 15  21 124  40  32  25  36]
- [  8   4   7 114   7   3   6]
- [  0  10   3   2  67   0   1]
- [  5   3   4   1   1  43   8]
- [ 11   4   6  11  10  10  81]]
-Node Classification on random seed  2248 -> 0.605
-Confusion Matrix:
- [[ 54   5   6  19   0  20   8]
- [  3 140   5   0   8   0   3]
- [ 30  20 142  43  27  12  42]
- [ 15   3   7 108   2   4  16]
- [  2   6   4   0  51   0   1]
- [  1   1   6   1   0  40   8]
- [ 10   1  12  25   7  12  70]]
-Node Classification on random seed  2249 -> 0.654
-Confusion Matrix:
- [[ 79   3   4   5   2  14   0]
- [  3 130   4   3   1   1   3]
- [ 36  25 161  16  35  23  27]
- [  5   4  23 118   4   6   9]
- [  1   5   5   0  65   2   4]
- [  6   1   2   2   0  35   1]
- [ 21   8   4   8   6  14  66]]
-Node Classification on random seed  2250 -> 0.623
-Confusion Matrix:
- [[ 60   2  16   5   7   8   7]
- [  2 124  10   4   7   5   5]
- [ 20  22 151  43  34  20  27]
- [  8   0   9 107   5   3  24]
- [  1   3   3   2  59   0   5]
- [  1   2   1   3   2  43   1]
- [ 13   2   9   7  10  19  79]]
-Node Classification on random seed  2251 -> 0.634
-Confusion Matrix:
- [[ 73   6   0   9   1  10  10]
- [  7 123   4   6   2   2   3]
- [ 33  15 144  40  27  17  37]
- [  6   5  16 116   3   5  11]
- [  1   6   3   1  56   2   3]
- [  5   2   2   0   3  45   6]
- [ 15   2  15   8   8   9  77]]
-Node Classification on random seed  2252 -> 0.644
-Confusion Matrix:
- [[ 81   2   0   3   3  12   7]
- [  2 126   2   2   7   3  12]
- [ 21  48 148  25  21  25  26]
- [ 13   5  10 125   5   2  14]
- [  2   5   5   2  62   0   1]
- [  7   1   3   1   1  40   7]
- [  9   4  11   8   3  16  62]]
-Node Classification on random seed  2253 -> 0.641
-Confusion Matrix:
- [[ 78   2   8  11   3   9   5]
- [  5 130  14   1  10   7   6]
- [ 22  23 174  22  15  18  41]
- [  8   4  15  92   1   6  18]
- [  0  10   4   1  53   1   2]
- [ 14   0   2   0   1  42   3]
- [  9   5   5   9   8  11  72]]
-Node Classification on random seed  2254 -> 0.616
-Confusion Matrix:
- [[ 67   2   4   2   4  21   7]
- [  9 124   3   5   7   3   2]
- [ 21  27 153  22  33  30  35]
- [  6   5  20  97   3   9  12]
- [  0   9   1   4  50   2   2]
- [  1   2   0   2   1  45   2]
- [ 14   6  12   8   8  18  80]]
-Node Classification on random seed  2255 -> 0.599
-Confusion Matrix:
- [[ 74   6   2   5   3  13   5]
- [ 11 133   3   4   6   1   3]
- [ 42  28 129  28  36  22  26]
- [ 20   5  21  87   5   8  10]
- [  0   5   4   3  59   0   4]
- [  7   3   0   2   1  46   9]
- [  7   5  16  10   6   6  71]]
-Node Classification on random seed  2256 -> 0.662
-Confusion Matrix:
- [[ 80   1   0   1   4   9   9]
- [  4 131   6   3   3   0   2]
- [ 24  34 167  19  18  31  28]
- [  8   1  14 110   3   5   8]
- [  1   6   2   1  61   2   2]
- [  7   1   6   0   1  39   7]
- [ 24   6  12  11   9   5  74]]
-Node Classification on random seed  2257 -> 0.599
-Confusion Matrix:
- [[ 64   2   6  14   6   9  13]
- [  4 113   3   6  12   6   6]
- [ 19  26 142  39  21  17  39]
- [  9   4  26  94   5  10  27]
- [  0   4   3   3  61   3   2]
- [  5   3   3   1   2  41   8]
- [ 10   1  11   2   4   7  84]]
-Node Classification on random seed  2258 -> 0.6
-Confusion Matrix:
- [[ 69   1  12   9   1  12   8]
- [  6 128   0   4  10   7   0]
- [ 25  24 131  42  34  12  37]
- [  8   2  23  91  14   5  13]
- [  0   3   4   4  62   1   2]
- [ 14   2   2   3   0  34   7]
- [ 16   3  12   4   5   9  85]]
-Node Classification on random seed  2259 -> 0.626
-Confusion Matrix:
- [[ 61   1   5   3   0  12  12]
- [  6 110  10   5   9   2   3]
- [ 27  19 117  44  27  19  40]
- [  9   1  13 129   5   8  16]
- [  1   6   2   3  68   0   2]
- [  6   1   0   2   0  57   2]
- [ 15   2  12   7   9   8  84]]
-Node Classification on random seed  2260 -> 0.66
-Confusion Matrix:
- [[ 72   2   6   5   0  12   4]
- [  2 135   9   2   5   3   6]
- [ 24  16 157  15  29  11  53]
- [ 12   3  18 116   9   0  13]
- [  1   5   8   0  58   0   3]
- [  2   2   1   3   1  40   4]
- [ 15   3   9   6   1  17  82]]
-Node Classification on random seed  2261 -> 0.645
-Confusion Matrix:
- [[ 82   1   3   1   2   8   9]
- [  4 110  19   2  20   8   3]
- [ 19  28 145  34  27  15  35]
- [  5   1  24 106  11   6  15]
- [  1   5   2   2  63   0   1]
- [  8   0   1   1   1  53   1]
- [  8   4   5   2   6   7  86]]
-Node Classification on random seed  2262 -> 0.618
-Confusion Matrix:
- [[ 73   6   9   2   2  11   3]
- [  4 121   2   5  18   8   5]
- [ 20  13 139  27  32  35  23]
- [  7   5  22  98   2   6  16]
- [  1   4   9   3  57   2   0]
- [  7   2   1   3   3  48   1]
- [ 14   8   1   4   5  31  82]]
-Node Classification on random seed  2263 -> 0.605
-Confusion Matrix:
- [[ 58   2   1  13   3  10   2]
- [  9 135   2   6   2   3   3]
- [ 25  28 132  33  36  11  42]
- [ 11   7  25 106   3  12  17]
- [  0   9   1   3  60   5   2]
- [  5   1   3   0   2  42   2]
- [ 16   1   8   8   9  14  72]]
-Node Classification on random seed  2264 -> 0.628
-Confusion Matrix:
- [[ 83   3   3   2   2  11  11]
- [  7 127   2   0   4   5   6]
- [ 21  32 154  37  11  38  33]
- [ 13   1   9 100  13   8   9]
- [  1   4   5   1  63   0   5]
- [  3   1   1   1   2  39   2]
- [  4   4  11  13   6  27  62]]
-Node Classification on random seed  2265 -> 0.57
-Confusion Matrix:
- [[ 78   5   6   3   1   7   9]
- [  3 126   4   3   4   2   3]
- [ 26  29 125  54  36  18  32]
- [ 21   4  24  62  14   3  11]
- [  2   9   6   2  63   1   3]
- [  5   4   6   0   0  44   5]
- [ 17   3   6  12   6  21  72]]
-Node Classification on random seed  2266 -> 0.662
-Confusion Matrix:
- [[ 79   2   1   7   2  11   2]
- [  0 116  12   4   3   6   4]
- [ 22  29 177  19  22  24  26]
- [  3   3  29 111   2   2  14]
- [  0   5   4   1  60   1   2]
- [ 10   2   0   1   0  48   8]
- [ 13   3  10   9   6  14  71]]
-Node Classification on random seed  2267 -> 0.631
-Confusion Matrix:
- [[ 78   0   0   6   3  18   5]
- [  7 128   4   2  11   3   4]
- [ 29  21 136  36  29  24  34]
- [ 14   4  15 103   4  11   7]
- [  0   8   2   0  67   1   2]
- [  5   2   1   2   2  50   7]
- [  9   2   5   4   5  21  69]]
-Node Classification on random seed  2268 -> 0.633
-Confusion Matrix:
- [[ 74   1   7   3   0   8  10]
- [  6 112   9   3  12   6   3]
- [ 33   7 156  28  26  16  50]
- [ 19   6   9 104   8   2   7]
- [  0   5   3   4  66   2   2]
- [  4   2   3   3   1  48   2]
- [ 18   4   6  12   3  14  73]]
-Node Classification on random seed  2269 -> 0.64
-Confusion Matrix:
- [[ 76   2   2  12   5  13   7]
- [  2 126   4   5   4   4   4]
- [ 28  25 140  41  18  25  29]
- [ 17   8   4 110   4   0  10]
- [  1  13   2   1  61   1   1]
- [  5   0   1   1   1  45   6]
- [ 11   3   9   7   6  18  82]]
-Node Classification on random seed  2270 -> 0.588
-Confusion Matrix:
- [[ 71   2   2   5   0  15  22]
- [  5 139   5   3   3   0   4]
- [ 30  20 139  34  18  29  55]
- [ 17   2  16  80   7   6  16]
- [  4   5   5   2  50   2   2]
- [  5   0   9   4   1  38   6]
- [  6   9   9   8   7  12  71]]
-Node Classification on random seed  2271 -> 0.596
-Confusion Matrix:
- [[ 82   2   0   2   6  12  16]
- [  3 114  10   5  10   2   8]
- [ 30  23 134  49  14  15  39]
- [ 11   1  15  98  16  10   9]
- [  0   7   4   2  57   0   2]
- [  1   1   9   8   2  42  12]
- [ 13   5   8   7   8   7  69]]
-Node Classification on random seed  2272 -> 0.577
-Confusion Matrix:
- [[ 92   1   4   5   7   3   8]
- [  2 123   4   2  14  11   3]
- [ 40  20 124  38  31  23  27]
- [ 20   4  28  64   5  20  10]
- [  2   3   4   3  57   2   3]
- [ 10   0   0   0   1  37   9]
- [ 16   7   5   9   6  13  80]]
-Node Classification on random seed  2273 -> 0.639
-Confusion Matrix:
- [[ 83   2   6   2   2  11   5]
- [  3 124   3   3   7   1   5]
- [ 26  20 143  45  22  25  27]
- [ 10   4  16 115   2   8  13]
- [  1   5   6   3  57   2   2]
- [  6   3   8   1   1  43   3]
- [ 14   3   8   7   5  15  74]]
-Node Classification on random seed  2274 -> 0.633
-Confusion Matrix:
- [[ 87   1   2   2   2  13  10]
- [  5 124   2   3  13   8   3]
- [ 23  17 139  20  22  28  45]
- [ 12   6  21  93   2   5  21]
- [  2   5   4   1  66   1   4]
- [  4   0   3   2   0  45   6]
- [ 10   4   9   6   8  12  79]]
-Node Classification on random seed  2275 -> 0.611
-Confusion Matrix:
- [[ 63   1   2  12   6  10   7]
- [  4 111   4   1   8   2   3]
- [ 29  15 139  24  32  34  50]
- [ 14   4  16 101   7   8   9]
- [  4   6   2   2  72   1   0]
- [  7   1   3   0   2  44   7]
- [  4   1  14   4   8  21  81]]
-Node Classification on random seed  2276 -> 0.603
-Confusion Matrix:
- [[ 68   2   3  10   4  14   7]
- [  5 137   0   1  10   3   2]
- [ 23  18 114  34  55  26  32]
- [ 16   8  14 110   3   6   5]
- [  1  11   3   1  61   1   4]
- [  9   1   0   0   1  49   3]
- [ 13   4   7  12   6  19  64]]
-Node Classification on random seed  2277 -> 0.639
-Confusion Matrix:
- [[ 78   1   8   4   5   8  12]
- [  7 123   4   6   3   1  11]
- [ 27  23 147  28  36  22  27]
- [ 21   2   6 115   1   7  15]
- [  1   5   2   0  57   1   2]
- [  6   0   1   2   2  40   6]
- [  7   5  12   6   8  10  79]]
-Node Classification on random seed  2278 -> 0.649
-Confusion Matrix:
- [[ 73   1   8   2   2  14   7]
- [  3 132   6   3   4   1   3]
- [ 33  19 151  40  13  23  33]
- [ 10   3  19  90   5   7  13]
- [  1  10   9   5  63   0   0]
- [  1   3   2   0   1  53   3]
- [ 17   1   8   5   2  11  87]]
-Node Classification on random seed  2279 -> 0.614
-Confusion Matrix:
- [[ 70   3   5   6   4  11   3]
- [  7 120   8   2  11   2   3]
- [ 20  36 125  29  18  17  35]
- [ 18   3  12  96  13  10  11]
- [  3   6   1   0  72   1   4]
- [  5   4   2   2   0  44   5]
- [ 18   2   9  11   5  21  87]]
-Node Classification on random seed  2280 -> 0.618
-Confusion Matrix:
- [[ 62   1   7   3   1  18   8]
- [  2 102  11   4  20   2   3]
- [ 21  12 147  40  29  25  41]
- [  4   7   5 122   8   5  10]
- [  0   7   5   2  70   1   4]
- [  2   0   3   3   4  45  10]
- [ 12   5   8   8   7  14  70]]
-Node Classification on random seed  2281 -> 0.67
-Confusion Matrix:
- [[ 87   4   4   8   6  11   5]
- [  5 126   3   2  10   1   2]
- [ 15  19 142  31  27  16  42]
- [ 12  11  10 112   3   3  10]
- [  2   7   4   0  51   0   0]
- [  4   1   3   4   2  53   6]
- [ 16   6   2   8   2   3  99]]
-Node Classification on random seed  2282 -> 0.603
-Confusion Matrix:
- [[ 72   3   1   4   5  12   9]
- [  4 123  14   5   6   4   1]
- [ 19  40 114  23  36  28  37]
- [  6   4  10 106   6  15  13]
- [  0   6   7   1  74   0   1]
- [  8   0   0   2   0  47   3]
- [ 16   5   3  23   7  10  67]]
-Node Classification on random seed  2283 -> 0.577
-Confusion Matrix:
- [[ 57   2   0   8   1  13  19]
- [ 12  97   4   7  21   8   6]
- [ 39  12 145  31  23  40  28]
- [ 16   2  22  94   4   8  20]
- [  0   2   6   2  65   0   2]
- [ 10   5   0   0   0  45   5]
- [  6   1  10   9   4  15  74]]
-Node Classification on random seed  2284 -> 0.602
-Confusion Matrix:
- [[ 61   1   2   2   2  11  20]
- [  2 118   8   2  14   3   3]
- [ 33  27 150  28  23  14  51]
- [ 12   5  22 104   6   2  11]
- [  0   5   5   3  60   0   1]
- [  4   3   0   2   4  42   4]
- [ 11   6   5   1  22  18  67]]
-Node Classification on random seed  2285 -> 0.621
-Confusion Matrix:
- [[ 75   3   2   7   3  19  10]
- [  9 132   1   4   7   2   1]
- [ 20  12 121  49  28  14  48]
- [  9   4  10 110   3  11  13]
- [  1  12   1   2  53   3   3]
- [  7   3   2   1   2  46   2]
- [  2  16  10   8   3  12  84]]
-Node Classification on random seed  2286 -> 0.634
-Confusion Matrix:
- [[ 73   4   9   3   8   5   5]
- [  3 128  10   4   2   1   5]
- [ 30  27 142  40  29  24  26]
- [  6   1  14 102   4   8  15]
- [  0   5   6   3  61   1   4]
- [  6   1   4   0   2  38   8]
- [ 11   3  10   7   7   5  90]]
-Node Classification on random seed  2287 -> 0.6
-Confusion Matrix:
- [[ 58   4   3   6   3  10  17]
- [  3 139   6   0  10   5   2]
- [ 23  18 141  35  19  24  39]
- [ 30   1  20  81  12   6   4]
- [  1   7   6   2  62   3   2]
- [ 10   0   2   0   0  45   7]
- [  9   3  14   9   8  17  74]]
-Node Classification on random seed  2288 -> 0.585
-Confusion Matrix:
- [[ 66   2   8   3   4  12   9]
- [  4 122   5   4  12   5   5]
- [ 26  23 147  34  25  34  38]
- [ 23   4  18  82  14   8   6]
- [  0   3   4   4  49   1   1]
- [  9   2   2   0   0  46   5]
- [ 11   1  12  11   9  14  73]]
-Node Classification on random seed  2289 -> 0.644
-Confusion Matrix:
- [[ 85   1   0   4   5   6   7]
- [ 10 126   4   1  11   0   1]
- [ 25  36 141  25  27  21  33]
- [ 19   4  19 102   2   6  10]
- [  1   7   0   0  63   0   3]
- [  9   0   0   1   0  36   3]
- [ 16   1   7   8  10  13  91]]
-Node Classification on random seed  2290 -> 0.645
-Confusion Matrix:
- [[ 70   0   6   5   3  15   7]
- [ 12 137   6   2   7   0   1]
- [ 25  17 160  32  13  11  45]
- [ 14   5  17 108  13   6   8]
- [  1   6   3   1  57   1   3]
- [  3   0   2   0   3  44   6]
- [ 15   2  10   9   7  13  69]]
-Node Classification on random seed  2291 -> 0.613
-Confusion Matrix:
- [[ 83   1   4   7   4   6   5]
- [  1 107   5   5  10   3   8]
- [ 23  22 133  31  51  18  38]
- [ 15   3  13 107  15   3   9]
- [  2   3   1   3  64   2   0]
- [  3   2   2   2   1  45   8]
- [  8   3  16   4  12  15  74]]
-Node Classification on random seed  2292 -> 0.601
-Confusion Matrix:
- [[ 80   1   2   9   4   6  13]
- [  2 124   7   2   7   5   9]
- [ 36  30 134  32  14  41  21]
- [  9   5  25  94   3   5  14]
- [  2   8   1   6  57   0   4]
- [  8   0   2   3   0  35   8]
- [ 11   1  14   7   5  17  77]]
-Node Classification on random seed  2293 -> 0.585
-Confusion Matrix:
- [[ 73   3   8  10   6  17   4]
- [  2 132  10   2   4   1   3]
- [ 28  27 112  37  33  20  49]
- [  4   7  13  84   7  17  10]
- [  2   2   2   1  67   0   7]
- [  2   0   3   2   0  43   5]
- [  8   5   9  21   7  17  74]]
-Node Classification on random seed  2294 -> 0.637
-Confusion Matrix:
- [[ 77   2   1   5   2   8   5]
- [  5 135   9   0   6   6   8]
- [ 20  17 162  24  40  20  46]
- [ 12   5  12 102   3  12  11]
- [  1   5   6   1  52   3   1]
- [  7   1   3   2   4  32   1]
- [ 14   4   5   2   9  15  77]]
-Node Classification on random seed  2295 -> 0.608
-Confusion Matrix:
- [[ 61   3   7   5   1  16   5]
- [  3 136  13   4   3   2   2]
- [ 17  20 140  46  18  41  34]
- [ 17   1  17 105   5   4  12]
- [  4   6   4   1  58   2   4]
- [  2   2   6   2   2  50   2]
- [ 12   6   8  16   3  14  58]]
-Node Classification on random seed  2296 -> 0.635
-Confusion Matrix:
- [[ 80   3   1   8   5   5   4]
- [  3 137   3   5   3   0   5]
- [ 23  18 161  23  24  26  56]
- [  9   8  12 100   4  10  11]
- [  1   6   7   4  57   2   3]
- [  5   1   2   1   2  37   2]
- [ 16   7   5   7   4  21  63]]
-Node Classification on random seed  2297 -> 0.623
-Confusion Matrix:
- [[ 71   3   3   3   6  13   6]
- [  4 126   4   0  14   1   6]
- [ 20  37 152  26  25  16  29]
- [  5   9  20 107   5  15   9]
- [  1   6   6   3  61   1   2]
- [  8   2   3   0   0  43   7]
- [ 13   5   8   7   3  23  63]]
-Node Classification on random seed  2298 -> 0.619
-Confusion Matrix:
- [[ 76   7   0  11   4  11  10]
- [  2 138   1   7   1   0   0]
- [  9  23 156  35  38  21  38]
- [ 15  11  18  85   5   8   9]
- [  0  10   2   6  59   1   6]
- [  1   1   3   2   0  43   4]
- [  5   4  13  19   2  18  62]]
-Node Classification on random seed  2299 -> 0.594
-Confusion Matrix:
- [[ 62   3   9   7   4   9   6]
- [  9 111   7   1  10   4   6]
- [ 25  21 149  32  31  31  46]
- [  7   1  13  92  17   9  13]
- [  3   8   7   1  67   0   0]
- [  5   1   2   3   0  54   5]
- [ 10   1   9  10   5  15  59]]
-Node Classification on random seed  2300 -> 0.634
-Confusion Matrix:
- [[ 76   8   5   8   2  16   8]
- [  4 125   9   1   7   2   7]
- [ 16  37 135  30  25  17  30]
- [ 12   5   6 120   3   4  12]
- [  3   7   5   1  63   0   0]
- [  5   0   0   0   0  32  17]
- [ 15   4  11   8   5  11  83]]
-Node Classification on random seed  2301 -> 0.611
-Confusion Matrix:
- [[ 54   2   0  11   5  18  13]
- [  2 121   4   5  16   2   5]
- [ 25  19 158  22  25  15  49]
- [  9   5  22  90   2   3  15]
- [  2   5   3   4  63   0   1]
- [  3   1   2   7   0  50   3]
- [ 10   7  13   1  15  18  75]]
-Node Classification on random seed  2302 -> 0.613
-Confusion Matrix:
- [[ 54   6  10   3   3  14  10]
- [  5 156   3   0   5   1   5]
- [ 13  23 143  21  28  26  54]
- [  3   4  30  91   6   8  16]
- [  3  10   2   0  54   1   1]
- [  4   3   5   2   1  39   6]
- [ 18   5   6   8   2  13  76]]
-Node Classification on random seed  2303 -> 0.614
-Confusion Matrix:
- [[ 58   8   3  12   7  13   6]
- [  6 125  14   3   6   1   1]
- [ 30  31 119  45  29  16  32]
- [ 17   2  10 104   4   6  12]
- [  2   1   2   1  75   0   4]
- [  1   0   1   3   1  51   7]
- [ 16   8   5   8   3   9  82]]
-Node Classification on random seed  2304 -> 0.617
-Confusion Matrix:
- [[ 71   6  11   4   6   9  11]
- [  4 112   4   4   5   8   8]
- [ 21  18 156  46  21  31  38]
- [ 17   5  13  99   2   5   7]
- [  2   7   3   0  66   3   8]
- [  5   1   2   0   1  43   7]
- [ 13   2  12   3   3   7  70]]
-Node Classification on random seed  2305 -> 0.607
-Confusion Matrix:
- [[ 64   2  13   6   1   8  11]
- [  5 120   7   1   9   5   1]
- [ 27  22 144  36  22  24  28]
- [ 10   5  27 111   5   6   7]
- [  2   6   2   0  55   3   2]
- [  7   1   2   4   0  44   4]
- [ 11   7  15   8   7  24  69]]
-Node Classification on random seed  2306 -> 0.586
-Confusion Matrix:
- [[ 69   2   2   3   7   5  10]
- [  2 117  11   2  16   2   1]
- [ 34  30 132  34  18  33  39]
- [ 17   8   9  97   9   4  14]
- [  0  10   8   2  58   0   2]
- [  5   0   9   0   2  38   2]
- [ 18   3  13   8   4  16  75]]
-Node Classification on random seed  2307 -> 0.6
-Confusion Matrix:
- [[ 65   2   2   2   4  17  11]
- [  4 125   9   5  12   2   1]
- [ 22  27 118  44  33  19  41]
- [ 15   4  15 102   7   6  17]
- [  2   5   2   1  65   1   1]
- [  7   2   2   6   0  44   3]
- [ 14   6  12   3   2  10  81]]
-Node Classification on random seed  2308 -> 0.601
-Confusion Matrix:
- [[ 64   1   7   8   6   8  13]
- [  8 127   5   2  12   4   2]
- [ 17  22 126  19  48  18  55]
- [  8   0  19 103   8   7  12]
- [  2   7   4   2  65   0   2]
- [  6   1   1   0   2  37   6]
- [ 10   7   7  12   7  14  79]]
-Node Classification on random seed  2309 -> 0.629
-Confusion Matrix:
- [[ 80   3   1   2   5  11   9]
- [  5 139   2   1   5   2   2]
- [ 42  15 128  32  21  21  35]
- [ 11   4  27  95   4   2  13]
- [  2   7   2   5  61   1   1]
- [  4   3   1   2   0  54   5]
- [ 12  10  18   5   4  14  72]]
-Node Classification on random seed  2310 -> 0.61
-Confusion Matrix:
- [[ 72   2   1   4   5  12  11]
- [  7 147   6   2   3   2   2]
- [ 14  39 135  40  23  22  43]
- [  7   3  36  83   4   7  14]
- [  1  10   1   1  66   0   1]
- [  6   0   2   0   0  42   1]
- [ 14   3  12  11  11   7  65]]
-Node Classification on random seed  2311 -> 0.644
-Confusion Matrix:
- [[ 69   1   4   6   5   6   9]
- [ 14 121   5   0  11   7   2]
- [ 27  28 149  25  27  12  50]
- [  9   7  11 105   5   3   8]
- [  4   6   4   4  60   1   3]
- [  4   1   3   1   0  45   0]
- [  6   6   7   7  10   7  95]]
-Node Classification on random seed  2312 -> 0.6
-Confusion Matrix:
- [[ 58   2   4   7   4  19   7]
- [  4 128   3   9   8   2   3]
- [ 24  23 131  57  41  16  23]
- [ 18   3  18 114   9   2  11]
- [  0   8   6   3  50   0   2]
- [ 11   0   3   1   0  44   4]
- [ 13   2   8   5   6  11  75]]
-Node Classification on random seed  2313 -> 0.618
-Confusion Matrix:
- [[ 50   9   4   0   5  12  16]
- [ 10 126   8   6   9   4   3]
- [ 43  17 147  28  20  33  40]
- [  9   2  10 106   5  11   9]
- [  0   2   4   1  60   1   1]
- [  3   0   2   1   0  44  22]
- [  9   2   5   3   7   6  85]]
-Node Classification on random seed  2314 -> 0.577
-Confusion Matrix:
- [[ 66   5   7   7   9  17   1]
- [ 10 118  12   6   5   3   3]
- [ 40  16 120  44  32  16  35]
- [  7   3  15 104   2   6  14]
- [  1   5   5   8  52   0   4]
- [  6   2   6   3   1  48   1]
- [ 21   7  11   9   7  11  69]]
-Node Classification on random seed  2315 -> 0.6
-Confusion Matrix:
- [[ 71   4   6   5   4  10  13]
- [  5 137   7   4  12   6  10]
- [ 17  16 138  36  39  17  24]
- [ 13   1  30  97   4   4   9]
- [  3   7   0   3  51   2   2]
- [  5   2   2   1   0  48   5]
- [  9   3  14  24   7  15  58]]
-Node Classification on random seed  2316 -> 0.607
-Confusion Matrix:
- [[ 66   3   9  13  10  14   8]
- [  2 138   4   1   7   4   4]
- [ 14  16 131  25  50  26  36]
- [  4   2  27  90  12  11  17]
- [  2   3   5   0  58   0   5]
- [  3   3   2   3   0  46   3]
- [ 13   4  13   1   7   7  78]]
-Node Classification on random seed  2317 -> 0.597
-Confusion Matrix:
- [[ 73   1   2   3   1   5  10]
- [  5 125  12   3   7   4   8]
- [ 30  24 125  36  35  19  37]
- [ 18   2  25  80   6  10  14]
- [  2   5   4   1  71   1   2]
- [  6   0   2   7   2  51   6]
- [ 15   6   9   0   6  12  72]]
-Node Classification on random seed  2318 -> 0.576
-Confusion Matrix:
- [[ 71   3  14   9   5   4   8]
- [  4 135   5   0  12   3   5]
- [ 14  29 121  47  42  17  44]
- [ 10  11  11 100   7   3  13]
- [  5   5   1   0  51   0   8]
- [  8   0   3   2   1  40   7]
- [  7   2  22  16   5  12  58]]
-Node Classification on random seed  2319 -> 0.637
-Confusion Matrix:
- [[ 69   5   2   8   6  10   2]
- [  2 120   6   2  11   4   4]
- [ 21  13 138  20  18  31  43]
- [ 11   3   7 114   6   5  20]
- [  0   8   7   1  65   1   0]
- [  7   4   1   2   1  42   9]
- [  4   2   9   6  11  30  89]]
-Node Classification on random seed  2320 -> 0.647
-Confusion Matrix:
- [[ 61   4   1   3   2   7  14]
- [  6 130   5   3  10   1   2]
- [ 18  27 158  36  34  17  32]
- [ 13   4  14 114  10   7  11]
- [  1   4   5   4  64   0   1]
- [  6   1   0   1   0  40   2]
- [ 13   2   8  13   6   5  80]]
-Node Classification on random seed  2321 -> 0.655
-Confusion Matrix:
- [[ 67   1   2   3   2  11  11]
- [  6 123   6   3   6   0   5]
- [ 22  18 164  21  18  26  55]
- [ 10   5   9 104   2   9  20]
- [  1   5   2   0  71   0   2]
- [  4   1   2   3   0  48   3]
- [ 18   2   3   1   7  20  78]]
-Node Classification on random seed  2322 -> 0.609
-Confusion Matrix:
- [[ 80   2   1   4   3  11   7]
- [ 12 124   7   1   5   2   8]
- [ 30  25 119  54  26  23  41]
- [ 11   2   7 112  12   2  12]
- [  2   6   0   3  68   2   2]
- [  7   3   0   2   1  45   4]
- [ 16   2   6  10   6  11  61]]
-Node Classification on random seed  2323 -> 0.602
-Confusion Matrix:
- [[ 80   3   7   3   1  19   2]
- [  7 115   8   1   5   7   5]
- [ 14  18 127  44  47  19  36]
- [ 13   4   9 119   7   6   7]
- [  1  12   3   0  68   2   4]
- [  5   0  10   2   4  33   3]
- [  7   2  11  17   7  16  60]]
-Node Classification on random seed  2324 -> 0.628
-Confusion Matrix:
- [[ 75   2   5   4   4  12   7]
- [  4 125   8   8  10   6   6]
- [ 26  26 163  30  22  39  21]
- [  8   4  10 109   4   5  15]
- [  0   8   2   2  54   1   3]
- [  6   1   3   5   0  40   3]
- [ 11   3  13   4   9  12  62]]
-Node Classification on random seed  2325 -> 0.566
-Confusion Matrix:
- [[ 60   6   5   3   1   8  20]
- [  2 120  11   5   6   3   2]
- [ 24  32 141  42  29  23  30]
- [ 27   8  15  91   8  19   6]
- [  1  12   0   4  60   0   2]
- [ 15   2   6   1   1  30   8]
- [ 10   4   6   8   4  15  64]]
-Node Classification on random seed  2326 -> 0.589
-Confusion Matrix:
- [[ 75   3   4   6   3  19   5]
- [  3 127   2   4  14   5   2]
- [ 21  18 134  42  39  43  25]
- [ 14   2  17  87   5   8  20]
- [  1   4   5   0  50   1   0]
- [  5   1   3   0   1  46   6]
- [ 12   0  20   2  12  14  70]]
-Node Classification on random seed  2327 -> 0.661
-Confusion Matrix:
- [[ 88   1   0   5   4   7   6]
- [  7 119   6   5   2   4   4]
- [ 28  22 149  42  17  17  38]
- [ 17   2   5 117   7   4  12]
- [  1   9   5   2  57   0   4]
- [  5   0   3   0   2  51   5]
- [ 11   3   4  10  10   3  80]]
-Node Classification on random seed  2328 -> 0.583
-Confusion Matrix:
- [[ 60   8   5   3   8  17  11]
- [ 12 135   6   1   9   4   0]
- [ 31  27 142  29  24  19  24]
- [ 23   7  12  95   3  13   9]
- [  3   5   2   3  59   0   3]
- [  8   1   3   4   8  41   5]
- [ 14   3   7   9  12  22  51]]
-Node Classification on random seed  2329 -> 0.621
-Confusion Matrix:
- [[ 73   4   4   2   3   5  12]
- [  5 120  16   0  16   4   9]
- [ 20  22 142  30  15  12  55]
- [ 12   7  16  89   2   5  16]
- [  3   3   8   2  69   1   1]
- [  3   2   2   2   1  54   8]
- [ 12   3  11   4  15   6  74]]
-Node Classification on random seed  2330 -> 0.637
-Confusion Matrix:
- [[ 65   4   6   4   8   3  17]
- [  8 137   2   2  15   0   6]
- [ 17  21 165  36  20  11  39]
- [ 19   5  17 104   2   5  17]
- [  0   2   2   2  62   0   1]
- [ 10   1   2   1   0  32   8]
- [ 23   3   8   4   6   6  72]]
-Node Classification on random seed  2331 -> 0.597
-Confusion Matrix:
- [[ 48   2   4  10   3  13  18]
- [  6 125   4   0  16   4   3]
- [ 25  17 131  38  35  22  26]
- [ 11   7   5 110  12  10   7]
- [  1   7   2   4  56   1   5]
- [  7   4   2   0   1  50   4]
- [  8   8   8   8  11  24  77]]
-Node Classification on random seed  2332 -> 0.61
-Confusion Matrix:
- [[ 70   1   8   4   3  10  13]
- [  2 142   6   2   4   3   6]
- [ 17  15 108  57  52  31  20]
- [  7   3  14 108   5   4  19]
- [  2   6   1   0  53   0   4]
- [  3   1   0   3   6  47   5]
- [  9   4   5  10   3  22  82]]
-Node Classification on random seed  2333 -> 0.627
-Confusion Matrix:
- [[ 66   5   5   6   6  13   2]
- [ 11 124   8   4   9   0   3]
- [ 24  36 157  34  20  13  42]
- [ 20   2  19 104   1   4   5]
- [  0   8   8   0  62   1   2]
- [  7   0   1   0   0  42   2]
- [ 18   2   8   5   8  11  72]]
-Node Classification on random seed  2334 -> 0.622
-Confusion Matrix:
- [[ 68   0   2   1   2  21   6]
- [  4 107   4   3  12   5   6]
- [ 34  10 170  17  23  38  31]
- [  2   6  18 109   7   7  17]
- [  3   7   6   1  59   0   2]
- [  8   0   1   3   3  44   3]
- [  9   3   8  21  10  14  65]]
-Node Classification on random seed  2335 -> 0.639
-Confusion Matrix:
- [[ 65   2   9   5  10  10   4]
- [  8 142   4   1   5   4   2]
- [ 25  23 159  23  18  24  40]
- [ 13   2  18 103  12  10   8]
- [  2   6   3   0  58   0   2]
- [  3   3   3   0   2  33   4]
- [ 16   5   5   6   3  18  79]]
-Node Classification on random seed  2336 -> 0.598
-Confusion Matrix:
- [[ 65   5  11  10   7   8  14]
- [  1 125  12   3   7   2   4]
- [ 18  23 122  39  24  27  60]
- [  8   3   6 117   5   2   8]
- [  3  12   0   1  57   0   0]
- [  5   1   5   7   0  39  10]
- [  4   3   2  18   5  19  73]]
-Node Classification on random seed  2337 -> 0.612
-Confusion Matrix:
- [[ 74   3   1   2   2  12  14]
- [  2 125  14   6   1   5   8]
- [ 30  36 141  43  12  15  44]
- [ 24   1  20 102   8  10   8]
- [  1   5   4   5  53   2   1]
- [  5   0   1   0   0  35   5]
- [ 14   2   4   8   1   9  82]]
-Node Classification on random seed  2338 -> 0.591
-Confusion Matrix:
- [[ 60   4   1   7   7  14   7]
- [  5 120   7   3  13   4   6]
- [ 37  19 132  36  36  18  39]
- [ 21   7  13  88   7   7   8]
- [  1   3   3   1  59   2   3]
- [  3   0   2   0   1  40   5]
- [ 25   4   7   8   6   9  92]]
-Node Classification on random seed  2339 -> 0.58
-Confusion Matrix:
- [[ 61   1   3   9   2   9  14]
- [  5 100   6   5  17   7   2]
- [ 13  22 153  41  39  15  50]
- [ 15   2   8 111   8   6  11]
- [  2   4   2   1  57   2   2]
- [  6   2   7   9   2  41   3]
- [  8   3  11  16   3  27  57]]
-Node Classification on random seed  2340 -> 0.617
-Confusion Matrix:
- [[ 69   2   3   9   5  13  10]
- [  2 124   5   6  11   2   8]
- [ 25  24 137  42  23  21  27]
- [  5   1  10 119   4   7  11]
- [  1   5   3   3  61   0   0]
- [  3   1   6   2   0  48   5]
- [  9   7  19  19  10  14  59]]
-Node Classification on random seed  2341 -> 0.664
-Confusion Matrix:
- [[ 88   2   0   3   6  10   8]
- [  4 133   7   2  11   2   5]
- [ 23  12 142  46  29  20  20]
- [ 11   5  11 116   2   6  11]
- [  1   5   3   0  68   1   2]
- [  7   1   2   1   2  47   5]
- [ 13   1  11   7   8  10  70]]
-Node Classification on random seed  2342 -> 0.61
-Confusion Matrix:
- [[ 72   0   4   5   3   9  14]
- [  3 132   3   4   5   2   2]
- [ 20  33 111  68  32  20  40]
- [ 10   4   9 114   3   6  12]
- [  4   8   1   2  63   0   1]
- [  6   1   0   2   0  47   2]
- [ 10   3   2   9   5  23  71]]
-Node Classification on random seed  2343 -> 0.589
-Confusion Matrix:
- [[ 60   2   5   3   3  17  22]
- [ 10 113   5   1  11   5   4]
- [ 27  15 120  52  73  21  23]
- [ 15   1   6  93   2   4  22]
- [  3   2   3   2  69   1   1]
- [  5   0   2   1   0  45   4]
- [ 11   2   8   2   8   7  89]]
-Node Classification on random seed  2344 -> 0.576
-Confusion Matrix:
- [[ 60   6   5   4  10  14   7]
- [  4 126   5   1   8   2   3]
- [ 21  16 133  26  36  23  52]
- [ 31   5  18  87   6   2  14]
- [  0   5   6   0  56   0   1]
- [  5   3   1   0   0  52   5]
- [  7   5  10   3  41  13  62]]
-Node Classification on random seed  2345 -> 0.573
-Confusion Matrix:
- [[ 68   3   1   5   8  14   8]
- [  5 142   6   2   6   6   5]
- [ 33  20 103  52  35  17  40]
- [ 20   3  16 100   6   3  11]
- [  2   9   4   2  49   2   2]
- [  7   1   3   0   0  45   9]
- [  8   4  18  10   5  16  66]]
-Node Classification on random seed  2346 -> 0.635
-Confusion Matrix:
- [[ 70   4   3  13   0   7  21]
- [  4 123   5   2   5   3   2]
- [ 26  21 157  22  21  31  36]
- [  7   7  10 106   3   8  12]
- [  2   3   9   2  41   4   1]
- [  9   1   1   3   1  43   5]
- [ 16   5   5   9   7   9  95]]
-Node Classification on random seed  2347 -> 0.567
-Confusion Matrix:
- [[ 65   0   5   5   9  14   7]
- [ 15 113   4   1  21   2   3]
- [ 14  17 125  22  70  34  37]
- [ 10   9  25 101   5   7   7]
- [  3   8   2   1  62   0   1]
- [  7   0   0   1   0  41   6]
- [ 15   1  16   3   7  19  60]]
-Node Classification on random seed  2348 -> 0.599
-Confusion Matrix:
- [[ 84   3  11   6   2   1   7]
- [  2 116   7   4  13   6   6]
- [ 30  29 109  30  27  32  40]
- [  9   2   9 109   3  10  12]
- [  4   5   3   4  59   0   2]
- [  5   0   5   0   0  40   2]
- [ 13   4  14  13   8  18  82]]
-Node Classification on random seed  2349 -> 0.625
-Confusion Matrix:
- [[ 93   3   0   3   0  11   9]
- [  4  99  12   7  11   5   3]
- [ 31  18 149  29  12  33  31]
- [  9   3  18 102  11  12  20]
- [  2   1   3   0  60   0   4]
- [  8   0   6   1   1  45   4]
- [ 18   3   7   1   7  14  77]]
-Node Classification on random seed  2350 -> 0.622
-Confusion Matrix:
- [[ 79   1   2   3   4  17  12]
- [  5 119   1   4   4   3   2]
- [ 37  27 140  34  25  30  19]
- [ 11   8  18 103   5   5  10]
- [  3   8   3   1  64   3   2]
- [  7   1   1   2   0  47   6]
- [  6   4   7  11   3  23  70]]
-Node Classification on random seed  2351 -> 0.584
-Confusion Matrix:
- [[ 65   2  11   3   1  22   4]
- [  6 135   4   5   5   5   3]
- [ 21  29 136  33  20  41  39]
- [ 18   3  12  88   2  10  12]
- [  0   5   5   1  55   2   8]
- [  1   1   3   7   0  40   7]
- [ 17   3   8  10   3  24  65]]
-Node Classification on random seed  2352 -> 0.613
-Confusion Matrix:
- [[ 69   1   3   1   9  17   7]
- [  5 117   5  12  13   3   1]
- [ 19  14 141  47  26  26  43]
- [ 10   0  20 102   3   8  15]
- [  0   7   5   2  57   1   2]
- [  6   4   0   0   1  43  10]
- [  9   4   6   4   4  14  84]]
-Node Classification on random seed  2353 -> 0.593
-Confusion Matrix:
- [[ 62   4  13  10   0   4   5]
- [  4 136   6   4   6   2   3]
- [ 31  27 103  60  46   9  19]
- [ 15   7  15 119   7   3  19]
- [  2   8   3   0  51   2   2]
- [ 13   4   1   2   0  46   3]
- [ 18   3   7   6   7   7  76]]
-Node Classification on random seed  2354 -> 0.628
-Confusion Matrix:
- [[ 84   2   5   6   4   5   5]
- [  8 133   5   8  11   1   4]
- [ 32  17 133  33  37  22  40]
- [ 12   4   7 102   5  11   9]
- [  1   6   2   2  59   3   3]
- [  7   1   1   5   2  43   2]
- [ 17   3   2   8   8   6  74]]
-Node Classification on random seed  2355 -> 0.622
-Confusion Matrix:
- [[ 75   3   6   1   2  17  13]
- [  6 133   4  11   7   2   1]
- [ 37  15 157  23  21  22  42]
- [  5   7  10  98   9   7  23]
- [  1   3   4   2  49   0   2]
- [  6   2   3   1   6  30   3]
- [ 14   4   8   4   6  15  80]]
-Node Classification on random seed  2356 -> 0.575
-Confusion Matrix:
- [[ 62   2  10   2   4  14   4]
- [  6 126   3   2  20   0   3]
- [ 29  24 139  40  26  30  34]
- [ 15   0  19  84   6   9  25]
- [  0   3   5   2  55   1   4]
- [  2   0   3   1   1  50   6]
- [ 14   4  27   6   7  12  59]]
-Node Classification on random seed  2357 -> 0.602
-Confusion Matrix:
- [[ 77   3   2   5   4  10   8]
- [  4 130  15   2   4   2   1]
- [ 31  31 137  38  42  27  18]
- [ 20   4  18  83   1   4   5]
- [  0   9   4   1  62   0   5]
- [  5   5   3   2   0  46   1]
- [  5   6  14  14   4  21  67]]
-Node Classification on random seed  2358 -> 0.585
-Confusion Matrix:
- [[ 49   2   2  15   5  12  18]
- [  2 122   8   0   8   4   6]
- [ 24  33 149  34  19  26  40]
- [ 12   4  27  94   4   5  12]
- [  5   9   1   3  61   1   4]
- [  7   1   3   1   0  44   3]
- [  7   4   6  15   3  20  66]]
-Node Classification on random seed  2359 -> 0.641
-Confusion Matrix:
- [[ 57   7   7   5   1   8   2]
- [ 11 114   6   3  11   4   6]
- [ 30  12 158  40  27  16  36]
- [  9   4  13 110   3   3  17]
- [  3   7   7   0  69   1   2]
- [  3   3   4   1   0  43   7]
- [ 13   3   7   7   1   9  90]]
-Node Classification on random seed  2360 -> 0.611
-Confusion Matrix:
- [[ 90   4   7   5   4  12   2]
- [  5 111   4   0   6  10   6]
- [ 28  27 122  35  22  31  46]
- [ 14   2   7 110   4   6  18]
- [  1   8   3   0  48   1   4]
- [  4   0   2   4   1  45   6]
- [ 10   3  10   8   7  12  85]]
-Node Classification on random seed  2361 -> 0.59
-Confusion Matrix:
- [[ 67   3   3  11   4   7  12]
- [  4 107  13   8   2   2   5]
- [ 30  19 131  42  10  21  50]
- [ 17   3  12 112   3   4  24]
- [  2  14   5   2  54   2   5]
- [  8   1   3   3   0  46  10]
- [  7   7  13   6   3  10  73]]
-Node Classification on random seed  2362 -> 0.609
-Confusion Matrix:
- [[ 50   2   5  10   3  17  16]
- [ 15 132  13   5   4   4   5]
- [ 19  24 152  34  12  20  44]
- [  9   3  25 101   9   4   8]
- [  3   2   2   0  54   0   2]
- [  4   0   4   2   2  42   6]
- [ 16   2  11   1   9  15  78]]
-Node Classification on random seed  2363 -> 0.607
-Confusion Matrix:
- [[ 66   5   4   5   1   7  18]
- [  7 120   6   6   9   2   1]
- [ 27  21 124  29  44  26  39]
- [  8  11   7 119   2  10  12]
- [  1   9   1   2  54   1   2]
- [  6   2   1   1   0  46   9]
- [ 14   1   6  10   6  14  78]]
-Node Classification on random seed  2364 -> 0.635
-Confusion Matrix:
- [[ 61   1   2   7   3  18  12]
- [  4 122   6   1   9   2   3]
- [ 21   9 153  23  36  25  37]
- [ 17   5  20 109  11   9   9]
- [  3   9   4   1  51   0   0]
- [  2   0   7   0   0  54   2]
- [  7   1  10  11   6  12  85]]
-Node Classification on random seed  2365 -> 0.59
-Confusion Matrix:
- [[ 79   0   5   7   6  17  12]
- [  5 109   4   3   8   8   8]
- [ 23  21 125  51  31  13  46]
- [  9   5  16  94  10   3  16]
- [  1   1   1   3  58   3   2]
- [  2   0   4   0   2  50   7]
- [ 13   4  10   9   7  14  75]]
-Node Classification on random seed  2366 -> 0.619
-Confusion Matrix:
- [[ 84   2   8   6   6  12   6]
- [  4 121   3   4  13   3   5]
- [ 29  17 131  52  21  27  35]
- [  4   6  20  96   8   5   7]
- [  1   3   6   4  59   0   0]
- [  4   0   1   2   0  50   6]
- [ 18   2   2  11   7  11  78]]
-Node Classification on random seed  2367 -> 0.625
-Confusion Matrix:
- [[ 71   5   9   5   5   8   6]
- [  2 145   4   0   1   6   2]
- [ 28  33 124  30  15  27  37]
- [ 16   6  10 100   7   7   7]
- [  0  11   4   5  61   2   6]
- [  6   0   0   1   1  45   7]
- [ 11   5  17   9   3  11  79]]
-Node Classification on random seed  2368 -> 0.573
-Confusion Matrix:
- [[ 64   4   0   2   3  13  15]
- [  9 126   7   3   3   6   6]
- [ 30  28 107  34  31  29  45]
- [  8   1  17 108  10   2  17]
- [  4   5   4   2  47   2   2]
- [  6   1   3   5   0  49   6]
- [ 10   3   7   7  11  26  72]]
-Node Classification on random seed  2369 -> 0.622
-Confusion Matrix:
- [[ 79   4   9   3   5   8  11]
- [  2 141   1   6   8   2   2]
- [ 12  20 122  51  26  18  35]
- [ 12   3  14 121   5   3   6]
- [  1   6   3   6  57   1   0]
- [ 10   3   2   2   6  46   1]
- [  6   4  16  18   7  20  56]]
-Node Classification on random seed  2370 -> 0.606
-Confusion Matrix:
- [[ 70   6   4   6   1  11  10]
- [  9 127   2   4  13   4   1]
- [ 29  16 137  35  25  23  33]
- [ 10   2  17  85   4  23  17]
- [  1   7   5   5  74   0   3]
- [  4   1   1   0   0  46   5]
- [ 17   4  10  10   2  14  67]]
-Node Classification on random seed  2371 -> 0.636
-Confusion Matrix:
- [[ 61   4   1   4   1  15   6]
- [  4 143   6   4   4   1   1]
- [ 10  22 139  36  37  23  34]
- [ 11   9  15 113   6   9  17]
- [  2   4   3   4  55   0   2]
- [  8   0   4   0   0  39   8]
- [ 18   1   4   7   4  15  86]]
-Node Classification on random seed  2372 -> 0.601
-Confusion Matrix:
- [[ 67   1   1   7   1   8  14]
- [  1 136   6   0  10   3   8]
- [ 39  17 123  43  31  30  25]
- [  6   4  11 107   8   7  13]
- [  3   6  10   0  55   3   3]
- [  4   0   0   0   0  47  11]
- [ 11   4   9  10  12  19  66]]
-Node Classification on random seed  2373 -> 0.565
-Confusion Matrix:
- [[ 65   1   8   9   0  11   8]
- [  7 116   5   7   4  10   6]
- [ 22  19 129  42  26  43  43]
- [  2   2  19 103  11   7  15]
- [  5   8   3   1  51   1   1]
- [  7   3   1   5   1  40   4]
- [ 14   4  12   6   4  28  61]]
-Node Classification on random seed  2374 -> 0.588
-Confusion Matrix:
- [[ 66   3   5   8   6  16   6]
- [  5 123   9   0   1   6   2]
- [ 19  23 140  31  23  25  45]
- [ 21   6  22  82   5   8  12]
- [  1   6   4   1  61   1   3]
- [ 11   1   1   4   0  38   9]
- [ 16   3  12   8  11  13  78]]
-Node Classification on random seed  2375 -> 0.662
-Confusion Matrix:
- [[ 71   1   3   4   6   7  17]
- [  8 142   2   3   2   1   3]
- [ 17  26 144  48  21  15  29]
- [  9   8  17 117   4   5   6]
- [  1   8   3   5  57   2   2]
- [  4   0   0   1   0  48   2]
- [ 12   3  12   7   3  11  83]]
-Node Classification on random seed  2376 -> 0.599
-Confusion Matrix:
- [[ 77   2   4   9   4   9  21]
- [  2 118   1   5  20   1   2]
- [ 19  30 125  42  23  21  40]
- [ 12   7  18  96   2   3  16]
- [  1   3   4   0  63   2   2]
- [  4   6   0   5   2  46   5]
- [ 15   3  12   7   7  10  74]]
-Node Classification on random seed  2377 -> 0.62
-Confusion Matrix:
- [[ 77   4   2   8   3  13   4]
- [  2 138   4   2   5   5   2]
- [ 21  25 123  46  14  27  42]
- [  7   2  16 103  11   8  13]
- [  0   2   4   4  62   2   5]
- [  9   3   0   5   1  44   8]
- [ 20   3   3   5   9  11  73]]
-Node Classification on random seed  2378 -> 0.547
-Confusion Matrix:
- [[ 57   3  14   7   4  23  10]
- [  3 123   9   5   8   2   1]
- [ 20  24 108  49  19  43  51]
- [  9   7  15  79   4   8  31]
- [  1  12   4   1  46   0   2]
- [  3   0   5   3   1  53   3]
- [  5   4  10   3   6  21  81]]
-Node Classification on random seed  2379 -> 0.623
-Confusion Matrix:
- [[ 72   4   1   4   2  12   7]
- [  4 127   2   4   4   6   4]
- [ 36  27 143  45  12  26  39]
- [  9   1   4 113   2   4  15]
- [  1  10   3   1  55   1   2]
- [  1   0   4   2   0  54   6]
- [ 23   4  15   5   6  19  59]]
-Node Classification on random seed  2380 -> 0.627
-Confusion Matrix:
- [[ 72   3   2   3   2   8  15]
- [  1 114   4   3   7   5  12]
- [ 35  21 153  48  23  19  33]
- [  2   5  21 115   5   2  10]
- [  1   8   3   2  60   1   6]
- [  4   0   4   2   0  34   9]
- [  5   3   9   8   8  11  79]]
-Node Classification on random seed  2381 -> 0.607
-Confusion Matrix:
- [[ 63   4  13   3   2  15  10]
- [ 14 119   4   2   9   1   8]
- [ 20  13 148  56  13  25  53]
- [ 16   0  15  89   4   4  15]
- [  0   3   5   2  58   0   4]
- [  4   2   5   4   0  47   5]
- [  9   3  11   2   5  10  83]]
-Node Classification on random seed  2382 -> 0.583
-Confusion Matrix:
- [[ 61   1   5   7   2  12  28]
- [  4 121   8   3   5   9   3]
- [ 49  32 127  28  17  25  31]
- [ 22   4   6 115   2   4  10]
- [  2   7   7   6  50   0   2]
- [  5   0   1   2   0  32   1]
- [ 20   2  14   4   9  18  77]]
-Node Classification on random seed  2383 -> 0.632
-Confusion Matrix:
- [[ 80   0   2   5   6  17   6]
- [  1 116   6   5   6   1   9]
- [ 15   8 162  36  30  29  41]
- [ 14   3  14 107   6   7  14]
- [  2   8   1   3  58   1   2]
- [  4   1   1   2   0  41   8]
- [  8   1  14   2   7  22  68]]
-Node Classification on random seed  2384 -> 0.634
-Confusion Matrix:
- [[ 83   3   4   6   4   4  12]
- [  2 116   6   0   8   0   6]
- [ 20  31 147  26  24  23  47]
- [  6   8   7 104   8   2  13]
- [  5   9   1   0  62   0   2]
- [  2   2   3   7   0  52   5]
- [  8   4   8  24   6  10  70]]
-Node Classification on random seed  2385 -> 0.639
-Confusion Matrix:
- [[ 70   2   2   2   4  13  14]
- [  4 131   7   1   8   2   2]
- [ 28  15 155  35  22  12  46]
- [ 20   1  16  84   6   3  11]
- [  2   5   6   2  65   0   1]
- [  3   1   3   0   0  52   4]
- [ 11   6  11   4  10  16  82]]
-Node Classification on random seed  2386 -> 0.648
-Confusion Matrix:
- [[ 72   2   1   3   4  21   8]
- [  4 124   7   1   6   3   1]
- [ 19  10 151  31  19  35  19]
- [ 12   6  10 105   7  11  17]
- [  0   7   5   0  72   1   2]
- [  6   3   5   1   0  60   3]
- [ 15   3   5  15   9  15  64]]
-Node Classification on random seed  2387 -> 0.631
-Confusion Matrix:
- [[ 67   3   1   7   3  14   6]
- [  4 138   2   0  11   4   3]
- [ 26  30 137  24  19  26  41]
- [ 10   4  16 109   2   8  17]
- [  1   4   5   0  71   1   0]
- [  5   0   6   0   1  33  10]
- [  8   9   4   9   8  17  76]]
-Node Classification on random seed  2388 -> 0.631
-Confusion Matrix:
- [[ 74   7   7   1   5   4   7]
- [  3 135   0   4   2   2   2]
- [ 33  29 125  17  32  24  35]
- [  9   3  22 112   8  11   6]
- [  0   7   7   0  70   0   1]
- [  6   5   2   4   1  43   5]
- [ 15   1  12  14   5  11  72]]
-Node Classification on random seed  2389 -> 0.632
-Confusion Matrix:
- [[ 69   4   3   5   3  14   8]
- [  3 117   5   3   7   3   5]
- [  7  22 138  67  28  22  48]
- [  8   3  18 118   2   3  11]
- [  1   5   7   3  59   1   1]
- [  6   1   0   0   1  41   4]
- [ 10   2   4   8   6   6  90]]
-Node Classification on random seed  2390 -> 0.608
-Confusion Matrix:
- [[ 71   5   5   2   5  10  10]
- [  5 130   9   7   8   3   1]
- [ 35  25 124  49  18  20  22]
- [ 13   5  13 113   5   2  12]
- [  0   8   5   3  49   0   2]
- [  6   5   2   4   3  45   4]
- [ 13  11  13   5   5  14  76]]
-Node Classification on random seed  2391 -> 0.626
-Confusion Matrix:
- [[ 70   1   2   8   5  20   8]
- [  1 130   7   0   3   1   5]
- [ 39  18 135  28  27  23  21]
- [  9   2  24  96   9   6  19]
- [  1   7   7   1  59   1   2]
- [  4   1   2   1   1  53   7]
- [ 11   3  11   5   7  16  83]]
-Node Classification on random seed  2392 -> 0.604
-Confusion Matrix:
- [[ 58   2   8   5   5  13   9]
- [  2 144   0   3   4   2   5]
- [ 10  28 139  21  48  30  44]
- [  6   5  24  83   4   7  22]
- [  1   8   3   2  54   0   3]
- [  5   1   7   3   3  40   2]
- [  8   5  13   5   5  15  86]]
-Node Classification on random seed  2393 -> 0.597
-Confusion Matrix:
- [[ 77   2   5   5   6  16   4]
- [  2 140   4   1   8   1   3]
- [ 24  35 129  36  18  22  51]
- [ 10   5  11  80   3   6  23]
- [  1   4   6   1  61   3   2]
- [  5   0   1   1   0  53   2]
- [ 14   6   7   8  24  17  57]]
-Node Classification on random seed  2394 -> 0.603
-Confusion Matrix:
- [[ 88   2   0   2   3   4  11]
- [  9 112   6   0  14   3   3]
- [ 30  33 138  38  25  26  29]
- [ 10  13  13 117   7   1  13]
- [  2   9   5   0  49   1   4]
- [  4   3   1   1   2  36  11]
- [  9   7   1  12  25   5  63]]
-Node Classification on random seed  2395 -> 0.614
-Confusion Matrix:
- [[ 73   3   3   2   2   9  11]
- [  7 104   5   0   8   2   2]
- [ 24  30 140  28  28  17  41]
- [ 15   6  31 106   6   3  16]
- [  3   6   0   1  67   2   4]
- [ 14   0   1   2   0  45   6]
- [ 18   3   7   7   5   8  79]]
-Node Classification on random seed  2396 -> 0.608
-Confusion Matrix:
- [[ 67   1   1   8   6  25   7]
- [  4 137   6   3  11   4   2]
- [ 20  24 131  38  26  27  35]
- [  1   4  19  98   2   5  16]
- [  0   2   7   0  64   1   1]
- [  3   2   6   8   0  36   6]
- [ 12   2  21   9   5  12  75]]
-Node Classification on random seed  2397 -> 0.636
-Confusion Matrix:
- [[ 63   0   4   6   3  14  10]
- [  4 118   5   4  11   3   2]
- [ 25  11 141  40  32  35  33]
- [ 10   1  18 109   6   4   9]
- [  0   3   1   1  71   0   2]
- [  7   1   0   2   0  48  11]
- [  6   3   6   8   5  18  86]]
-Node Classification on random seed  2398 -> 0.669
-Confusion Matrix:
- [[ 63   1   1   2   8  21   1]
- [  3 137   3   1  15   1   8]
- [ 17  15 166  29  13  26  34]
- [ 21   5  15 104   5   4  12]
- [  0   0   3   1  70   3   0]
- [  0   0   1   3   0  53   2]
- [ 11   7   5  11  10  13  76]]
-Node Classification on random seed  2399 -> 0.59
-Confusion Matrix:
- [[ 59   0   3   9   9  15   7]
- [  7 128   5   3   8   3   6]
- [ 27  18 104  51  30  16  48]
- [  9   4  11 112  16  10   7]
- [  0   9   3   1  63   1   7]
- [  1   1   1   6   1  46   6]
- [ 10   2   7   2   9  21  78]]
-Node Classification on random seed  2400 -> 0.656
-Confusion Matrix:
- [[ 68   0   4   5   5  12  12]
- [  4 130   2   2   9   4   7]
- [ 25  18 167  35  18  18  38]
- [  8   1  12 109   8   3  10]
- [  2   7   1   4  59   0   2]
- [  4   0   5   7   2  38   7]
- [  5   1  12   6   8  11  85]]
-Node Classification on random seed  2401 -> 0.637
-Confusion Matrix:
- [[ 76   3  12   7   3  10   2]
- [  6 128   4   3   3   3   4]
- [ 26  27 139  33  13  22  45]
- [ 17   5   9 104   4   4   6]
- [  3   6   2   1  61   0   1]
- [ 10   2   0   0   1  44   4]
- [ 22   7   5   5   6  17  85]]
-Node Classification on random seed  2402 -> 0.605
-Confusion Matrix:
- [[ 87   1   0   5   0  17   1]
- [  2 124   6   5   6   5   2]
- [ 17  22 128  38  26  22  57]
- [ 35   3  17  89   5   9  16]
- [  0   3   4   3  56   1   3]
- [  4   0   1   0   0  50   4]
- [ 17   4   3   8   7  16  71]]
-Node Classification on random seed  2403 -> 0.58
-Confusion Matrix:
- [[ 64   2   3   6   4  19  23]
- [  6 119   3   6   8   1   8]
- [ 26   9 139  48  28  21  43]
- [ 14   5  22  94   8   6   9]
- [  1   8   4   3  49   0   1]
- [  8   1   3   1   0  41   1]
- [  4   2   6   8   7  34  74]]
-Node Classification on random seed  2404 -> 0.588
-Confusion Matrix:
- [[ 73   1   4   2   3   6   9]
- [  5 123   3   4   3   5   1]
- [ 17  34 132  35  40  19  39]
- [ 16  11  11  85  10   5  24]
- [  2   3   2   1  67   3   2]
- [ 16   2   4   3   0  39   4]
- [ 15   6  15   5  10  12  69]]
-Node Classification on random seed  2405 -> 0.636
-Confusion Matrix:
- [[ 71   1   8   2   4   6   9]
- [  7 145   5   1   8   1   2]
- [ 23  13 144  38  41  18  29]
- [ 17   4  14  91   7   2  14]
- [  2   0   3   0  57   2   6]
- [  5   1   5   0   0  52   2]
- [ 10   5  12   5   3  29  76]]
-Node Classification on random seed  2406 -> 0.616
-Confusion Matrix:
- [[ 66   2   7   7   2   6   9]
- [  4 134   4   0  11   2   9]
- [ 28  23 139  26  28  26  45]
- [  9   5  34  87   9   6  10]
- [  1   5   3   2  69   0   2]
- [  8   0   1   0   1  33   9]
- [ 13   0  15   1   6   5  88]]
-Node Classification on random seed  2407 -> 0.634
-Confusion Matrix:
- [[ 87   2   2   3   1  12   3]
- [  5 119  11   4   6   0   3]
- [ 23  25 152  30  30  28  32]
- [  9   4  16 103   8  18   7]
- [  0   7   6   2  64   0   2]
- [  4   0   1   1   2  45   7]
- [ 10   1   5   5  12  19  64]]
-Node Classification on random seed  2408 -> 0.595
-Confusion Matrix:
- [[ 65   2   2   4   8  16  16]
- [  6 120   7   7   4   5   7]
- [ 24  20 139  42  19  24  56]
- [ 16   2   6  95   4  11   6]
- [  1   9   1   0  62   1   2]
- [  8   1   0   3   2  40  10]
- [ 16  11   0   8   4  14  74]]
-Node Classification on random seed  2409 -> 0.597
-Confusion Matrix:
- [[ 60   6   5   9   3  22   9]
- [  4 125   6   1   9   5   0]
- [ 26  19 151  29  28  21  32]
- [  8  11  11 107   5  11  14]
- [  1  11   2   2  57   1   1]
- [ 11   3   3   0   0  38  10]
- [ 14   1  11  13   7  18  59]]
-Node Classification on random seed  2410 -> 0.601
-Confusion Matrix:
- [[ 73   3   4   4   3  16   7]
- [  3 123   4   4  11   1   3]
- [ 12  25 144  76  13  14  22]
- [ 19   7  13  79   9   7  15]
- [  0  10   3   6  55   1   4]
- [  4   3   2   2   1  51  13]
- [ 19   5   8  11   5   7  76]]
-Node Classification on random seed  2411 -> 0.611
-Confusion Matrix:
- [[ 69   0   7   3   2   8   7]
- [  6 144   1   1   7   6   7]
- [ 17  32 115  55  29  25  40]
- [ 12   3  15 105   2   4  19]
- [  1   3   3   5  55   1   2]
- [  6   1   1   0   3  44   7]
- [ 12   6   8   5   2  15  79]]
-Node Classification on random seed  2412 -> 0.607
-Confusion Matrix:
- [[ 78   2   5   5   4  11  14]
- [  5 124   3   4   6   3   3]
- [ 19  10 151  38  24  37  29]
- [ 13   5  20  86   5  10  14]
- [  2  10   5   2  64   2   1]
- [  4   0   5   2   0  44   6]
- [  6   4   1  12   8  34  60]]
-Node Classification on random seed  2413 -> 0.626
-Confusion Matrix:
- [[ 79   3   1   3   3  13   9]
- [  7 133   2   2   8   3   4]
- [ 27  19 148  23  15  18  52]
- [ 16   5  18 103   5  10  13]
- [  1  10   4   3  52   3   2]
- [  9   2   7   1   1  40   3]
- [ 16   2   3   7   4  17  71]]
-Node Classification on random seed  2414 -> 0.629
-Confusion Matrix:
- [[ 81   3   2   2   5  13   2]
- [  3 130   0   2   6   2   4]
- [ 40  25 133  30  15  37  32]
- [ 12   5  16  96   6   7  13]
- [  3   6   1   0  53   2   5]
- [  8   3   1   0   3  47   4]
- [ 21   6   5   6   6   9  89]]
-Node Classification on random seed  2415 -> 0.623
-Confusion Matrix:
- [[ 67   2   4  15   3  22   7]
- [  5 133   2   2  12   1   0]
- [ 13  32 157  32  17  34  29]
- [  4   0  22 104   4  13  14]
- [  5   9   2   0  49   2   1]
- [  8   2   2   0   0  39   7]
- [ 12   8   4   7   4  15  74]]
-Node Classification on random seed  2416 -> 0.606
-Confusion Matrix:
- [[ 72   2  16   4   2   9  10]
- [  5 123   3   2   1   1   3]
- [ 13  22 144  49  27  16  34]
- [ 14   1  20  99   3   9  20]
- [  2   5   2   2  65   0   0]
- [ 12   0   4   3   0  45   5]
- [ 16   9   8  11  12  17  58]]
-Node Classification on random seed  2417 -> 0.589
-Confusion Matrix:
- [[ 78   1   2   5   5   9  16]
- [  5 124   4   4   5   3   3]
- [ 29  20 136  58  23  33  18]
- [  6   5  22  91   6  21   3]
- [  1   9   9   1  57   1   0]
- [ 10   2   0   8   2  33   5]
- [ 13   1   6  13   7  17  70]]
-Node Classification on random seed  2418 -> 0.614
-Confusion Matrix:
- [[ 62   2   5  12   1   4  17]
- [ 11 117   4   2  13   1   2]
- [ 23  13 140  29  37  24  35]
- [ 14   1  14 109   6   2  18]
- [  1  10   1   2  66   2   4]
- [ 11   0   5   4   1  38   3]
- [ 12   3   2  12   6  17  82]]
-Node Classification on random seed  2419 -> 0.641
-Confusion Matrix:
- [[ 64   7   5   3   3   6  13]
- [  5 145   5   0  10   1   5]
- [ 32  19 148  29  22  20  38]
- [ 12   5  11 103   0   8   6]
- [  5   4   7   1  64   1   4]
- [  9   2   4   0   0  38   2]
- [  5   0  17   8   8  17  79]]
-Node Classification on random seed  2420 -> 0.632
-Confusion Matrix:
- [[ 71   1   7   5   4   9  11]
- [  6 130   3   0   7   3   5]
- [ 22  20 158  32  27  25  44]
- [ 12   2  12 123   3   8   7]
- [  0   6   5   2  45   0   4]
- [  4   1   3   5   0  39   9]
- [ 12   3   4  14   6  15  66]]
-Node Classification on random seed  2421 -> 0.608
-Confusion Matrix:
- [[ 65   2   4   5   7  15   5]
- [  5 129   4   2   7   2   5]
- [ 38  13 137  55  24  20  26]
- [ 16   0  12 107   7   8   7]
- [  3   5   2   0  69   1   5]
- [  4   1   5   2   1  50   0]
- [ 17   6  18  17   4  12  51]]
-Node Classification on random seed  2422 -> 0.66
-Confusion Matrix:
- [[ 83   2   5   3   4  13   3]
- [  6 121   3   6   5   0   8]
- [ 20  19 145  25  32  24  43]
- [ 10   5  18  97   9   5   8]
- [  4   2   3   1  68   1   3]
- [  6   0   0   0   1  53   2]
- [ 13   3  11   2   3   9  93]]
-Node Classification on random seed  2423 -> 0.591
-Confusion Matrix:
- [[ 77   3   8   3   3  17  10]
- [  4 118  14   5   7   9   3]
- [ 15  19 115  34  32  24  35]
- [ 14   5  19 111   7   9  10]
- [  3   5   2   0  55   1   7]
- [  3   2   2   1   1  50   6]
- [ 13   6  14   9   3  22  65]]
-Node Classification on random seed  2424 -> 0.609
-Confusion Matrix:
- [[ 60   2   9  11   3  11   8]
- [  3 132   5   4  10   2   6]
- [ 23  21 135  31  21  29  52]
- [ 10   3  20  92   4   7  27]
- [  0   5   3   2  60   0   0]
- [  8   0   0   3   0  43   6]
- [  5   6   4  12   5  10  87]]
-Node Classification on random seed  2425 -> 0.664
-Confusion Matrix:
- [[ 81   5   2  10   1  13  12]
- [  6 124   7   1   5   0   1]
- [ 14  15 170  35  16  18  26]
- [ 11   3  26 109   4   2  12]
- [  2   6   7   4  64   1   2]
- [  5   1   2   1   1  48   5]
- [ 13  12  10   2   6  11  68]]
-Node Classification on random seed  2426 -> 0.589
-Confusion Matrix:
- [[ 60   3   4  10   5  11   8]
- [  3 112   2   1  15   5   2]
- [ 28  24 131  46  13  26  39]
- [  7   7  31 116   4   4  13]
- [  0   2   6   1  62   1   1]
- [  3   2   8   4   5  41   7]
- [ 15   3  12  11   3  16  67]]
-Node Classification on random seed  2427 -> 0.603
-Confusion Matrix:
- [[ 56   4   4  12   6  17   8]
- [  8 129   3   3   7   3   3]
- [ 45  28 124  18  24  20  51]
- [  5   7   7 106   9   7  13]
- [  1   4   0   1  71   2   1]
- [  7   0   2   2   1  47  11]
- [ 21   1   8   5  10   8  70]]
-Node Classification on random seed  2428 -> 0.604
-Confusion Matrix:
- [[ 68   2  11   9   2  11   8]
- [  9 124   4   1  14   0   6]
- [ 22  33 150  23  27  17  40]
- [ 20   9   8  92   4   6  13]
- [  3   8   1   2  57   4   8]
- [  5   4   4   7   0  39   7]
- [ 12   3   5   5   5  14  74]]
-Node Classification on random seed  2429 -> 0.649
-Confusion Matrix:
- [[ 68   3   3   4   2  11  25]
- [  3 136   8   2   5   6   0]
- [ 25  15 160  19  23  35  22]
- [ 12   1  15 104   2   8  10]
- [  0   8   5   1  60   0   1]
- [  2   2   3   1   1  48   8]
- [ 10   6  12   6   7  19  73]]
-Node Classification on random seed  2430 -> 0.584
-Confusion Matrix:
- [[ 67   0   2   8   3  14  12]
- [  6 123   5   4   7   1   8]
- [ 18  30 131  44  20  22  50]
- [ 17   4  20  85   7  16  21]
- [  3   2   5   2  53   1   0]
- [  5   2   3   1   4  50   0]
- [  8   7   9   1   6  18  75]]
-Node Classification on random seed  2431 -> 0.609
-Confusion Matrix:
- [[ 59   6   6   2   3  30   8]
- [  5 133   2   1  11   1   5]
- [ 43  16 141  17  21  26  35]
- [  6   6  25 104   0   6  23]
- [  3   5   4   3  58   0   2]
- [  3   1   3   0   1  43   4]
- [ 16   4  11  11   4  12  71]]
-Node Classification on random seed  2432 -> 0.612
-Confusion Matrix:
- [[ 55   8   6   7   5  16  12]
- [  4 119   8   1   3   2   6]
- [ 18  14 150  39  38  21  40]
- [ 10   0  10 102  10   7   7]
- [  0  12   4   4  57   0   2]
- [  3   1   2   2   0  56   5]
- [ 11   3  15   8  10  14  73]]
-Node Classification on random seed  2433 -> 0.621
-Confusion Matrix:
- [[ 64   7   8   4   3  11  19]
- [  4 129   3   2  11   1   4]
- [ 21  20 169  23  17  24  37]
- [  5   7  20  93   6   8  17]
- [  2   3  10   1  62   0   4]
- [  9   2   3   4   2  32   0]
- [ 16   5   5   8   6  17  72]]
-Node Classification on random seed  2434 -> 0.608
-Confusion Matrix:
- [[ 74   2   6   4   2   9   6]
- [  4 112   6   1   6   3   8]
- [ 13  17 126  44  36  17  48]
- [ 17   3  15 110   0   9  15]
- [  0   7   4  10  60   2   6]
- [  8   3   5   1   0  50   3]
- [  5   3  16   9   5  14  76]]
-Node Classification on random seed  2435 -> 0.61
-Confusion Matrix:
- [[ 73   3   4   7   6   7  14]
- [  8 122   3   7   4   3   5]
- [ 22  23 137  48  38  21  28]
- [ 14   1  10 107   7   7   8]
- [  2   5   4   2  63   0   4]
- [  5   1   4   0   0  48   8]
- [  9   4  12  10   6  16  60]]
-Node Classification on random seed  2436 -> 0.601
-Confusion Matrix:
- [[ 71   3   1  13   0  10   7]
- [  2 134   7   3   3   1   7]
- [ 20  32 120  50  22  16  48]
- [  2   4  12 105   4  21  17]
- [  2   6   6   1  56   0   1]
- [ 13   2   3   2   0  39   2]
- [ 16   4   6   4   8  18  76]]
-Node Classification on random seed  2437 -> 0.604
-Confusion Matrix:
- [[ 53   3   4   9   3   9  15]
- [  9 131   4   1  17   4   5]
- [ 17  31 155  18  39  15  39]
- [ 27  10  13  86  14   5   3]
- [  1   6   3   1  59   1   2]
- [  8   1   3   2   0  43   5]
- [  6   4  11   9   7  12  77]]
-Node Classification on random seed  2438 -> 0.611
-Confusion Matrix:
- [[ 80   2   5   7   3  14  12]
- [  8 106   5   1  17   2   3]
- [ 29  28 144  26  20  31  34]
- [ 15   5  19 103   9   5   5]
- [  4   6   1   0  59   1   1]
- [  6   1   3   1   1  44   1]
- [ 16   5   3  14   6  14  75]]
-Node Classification on random seed  2439 -> 0.597
-Confusion Matrix:
- [[ 83   1  10   4   1  16   4]
- [  7 119  12   2  13   0   1]
- [ 31  36 144  47  20  22  21]
- [  7   8  15  91   2   9   8]
- [  3   6   7   1  50   3   3]
- [  7   0   7   1   0  41   2]
- [ 15   3  19   5   5  19  69]]
-Node Classification on random seed  2440 -> 0.626
-Confusion Matrix:
- [[ 67   4  10  13   4   7  13]
- [  4 123  14   3   2   1   5]
- [ 30  27 152  47  21   9  42]
- [  6   3  18 113   3   3   7]
- [  0   5   2   1  53   1   3]
- [  6   0   1   0   0  46   8]
- [ 12   0  13   4  11  11  72]]
-Node Classification on random seed  2441 -> 0.644
-Confusion Matrix:
- [[ 64   3  15   4   4   5   8]
- [  3 128   3   4   7   3   1]
- [ 23  29 145  32  24  16  35]
- [ 17   4  11 107   3   5  18]
- [  0   3   4   3  68   2   2]
- [  5   2   2   1   0  46   3]
- [ 10   4   4   6  14  14  86]]
-Node Classification on random seed  2442 -> 0.639
-Confusion Matrix:
- [[ 71   2   4   3   9   7  10]
- [  2 109   3   6   6   4  15]
- [ 21  11 172  28  24  19  46]
- [ 12   2  18  87  11   8   9]
- [  4  10   3   3  64   0   3]
- [  5   1   2   0   2  46   4]
- [ 13   4   3   6   4  14  90]]
-Node Classification on random seed  2443 -> 0.589
-Confusion Matrix:
- [[ 66   1   2   3   5  19  11]
- [ 15 116  17   2   9   1   0]
- [ 17  15 141  31  19  17  47]
- [ 27   5  13  92   1  13  20]
- [  3   3   8   3  52   1  11]
- [  7   1   2   0   1  43   6]
- [ 10   2  10   9   8  16  79]]
-Node Classification on random seed  2444 -> 0.609
-Confusion Matrix:
- [[ 66   1   9   5   4  10  13]
- [  7 131   7   3   6   3   4]
- [ 27  28 112  39  22  22  48]
- [  9   1  17 117   4   4  13]
- [  1  12   1   0  61   0   1]
- [  1   0   9   0   4  44   9]
- [ 12   2  11   5   6  11  78]]
-Node Classification on random seed  2445 -> 0.608
-Confusion Matrix:
- [[ 74   2   1   7   5  12  19]
- [  7 115   9   7   8   0   7]
- [ 20  26 126  53  28  17  29]
- [ 10   4  14 115  16   2   7]
- [  2   6   6   1  54   4   3]
- [  3   2   0   1   2  52   3]
- [  9   4   5   8   4  19  72]]
-Node Classification on random seed  2446 -> 0.623
-Confusion Matrix:
- [[ 76   3   2   5   3   4  25]
- [  2 115   9   3   9   3   2]
- [ 27  26 121  32  25  24  35]
- [ 10   4   7 121   5   2  14]
- [  1   6   1   3  59   2   8]
- [ 10   3   4   3   0  42   8]
- [  8   7   7   4  12   9  89]]
-Node Classification on random seed  2447 -> 0.613
-Confusion Matrix:
- [[ 55   2   7   5   6   7   8]
- [  5 126   7   9  11   1   7]
- [ 22  31 152  27  37  15  46]
- [  7   5  18  96   3   5   8]
- [  2   1   5   4  59   1   8]
- [  6   0   2   0   2  47   8]
- [ 10   0   8   8  10  13  78]]
-Node Classification on random seed  2448 -> 0.646
-Confusion Matrix:
- [[ 68   2   3   3   4  12   7]
- [  2 139   3   7   3   3   7]
- [ 30   9 176  33  26  33  30]
- [  9   6  15  91   4   5  11]
- [  1   8   7   1  58   0   1]
- [  6   2   1   4   0  50   7]
- [ 17   2   6   5   6  13  64]]
-Node Classification on random seed  2449 -> 0.623
-Confusion Matrix:
- [[ 65   6   1   4   6   8  13]
- [  8 119   5   0  23   2   6]
- [ 17  12 153  15  28  18  35]
- [ 15   5  23  93   4  12  11]
- [  2   4   6   0  65   2   1]
- [  6   2   7   3   2  46   5]
- [  7   4   8   6  14  21  82]]
-Node Classification on random seed  2450 -> 0.643
-Confusion Matrix:
- [[ 79   1   2   0   3  11  13]
- [  1 141   4   4   5   2   3]
- [ 23  21 146  27  46  15  31]
- [ 17   8  17  97   2   6  18]
- [  0  10   4   3  56   0   3]
- [  5   1   0   2   0  46   8]
- [  6   5  11   0   7  12  78]]
-Node Classification on random seed  2451 -> 0.65
-Confusion Matrix:
- [[ 82   7   9   3   2  11   8]
- [  4 114   5   2   5   2   4]
- [ 18  18 142  21  34  19  41]
- [ 11   3  16 114   5   7  10]
- [  3   5   1   3  66   1   6]
- [  6   1   0   3   0  52   6]
- [ 14   1   2   7  12  14  80]]
-Node Classification on random seed  2452 -> 0.58
-Confusion Matrix:
- [[ 64   4   3   5   3   6  19]
- [  1 113   6   4  12   6   7]
- [ 21  22 127  46  41  21  45]
- [  8   2  13 114   6   8  12]
- [  0   5   5   7  65   0   3]
- [  3   0   1   2   4  32  10]
- [  3   4   9  14  11  18  65]]
-Node Classification on random seed  2453 -> 0.618
-Confusion Matrix:
- [[ 84   2   3   4   1  15  10]
- [  8 115   4   0  18   0   1]
- [ 24  24 147  13  22  39  38]
- [ 10   0  18  94  11  10  20]
- [  1   5   3   1  59   3   2]
- [  3   2   2   4   0  56   2]
- [ 14   8   3   6   4  24  63]]
-Node Classification on random seed  2454 -> 0.632
-Confusion Matrix:
- [[ 91   0   3   3   3  20   8]
- [  2 131   4   0  11   5   5]
- [ 21  26 142  23  42  11  29]
- [ 10   1  25 104   7   3  22]
- [  3   4   5   4  56   2   2]
- [  2   1   2   1   1  36   3]
- [ 19   2   4   5   9  15  72]]
-Node Classification on random seed  2455 -> 0.602
-Confusion Matrix:
- [[ 62   5   6   3   3  13   9]
- [  5 139   2   1   6   5   1]
- [ 15  37 129  58  20  15  40]
- [ 17   5   9 104   2  12  17]
- [  2   6   1   4  50   1   3]
- [  5   3   1   1   1  53   6]
- [ 15   2   5   8  12  16  65]]
-Node Classification on random seed  2456 -> 0.634
-Confusion Matrix:
- [[ 91   6   2   0   3  14   3]
- [  3 125   5   0   9   8   2]
- [ 20  32 158  31  20  20  33]
- [ 17   6  10 103   4  10   9]
- [  1   8   5   1  51   2   3]
- [  7   0   1   1   1  40   4]
- [ 12   4  13   1   7  28  66]]
-Node Classification on random seed  2457 -> 0.611
-Confusion Matrix:
- [[ 73   6   4   6   4   8   8]
- [ 11 122   6   1  10   0   3]
- [ 26  13 133  41  30  12  41]
- [ 22   2  16  90   4   4   8]
- [  2   9   1   1  67   0   2]
- [  4   2   2   4   6  49   3]
- [  8   5   6  26   8  14  77]]
-Node Classification on random seed  2458 -> 0.622
-Confusion Matrix:
- [[ 64   4   1   9   3  13  11]
- [  7 127   5   2  13   2   8]
- [ 18   9 135  29  20  27  52]
- [ 11   2  17  97   9  11   9]
- [  3   5   6   1  60   2   2]
- [  7   0   6   5   0  52   3]
- [ 11   3   5   5   7  15  87]]
-Node Classification on random seed  2459 -> 0.575
-Confusion Matrix:
- [[ 65   5   4  11   8   5   7]
- [  6 126   3   5   9   0  11]
- [ 19   8 106  50  56  24  65]
- [  6   2   9 115   8   3  15]
- [  2   6   8   2  56   1   0]
- [  5   1   3   8   0  40   6]
- [ 11   2   8  10   8   5  67]]
-Node Classification on random seed  2460 -> 0.626
-Confusion Matrix:
- [[ 79   1   3   1   4   8  18]
- [ 11 121   7   1   4   1  14]
- [ 22  19 140  25  38   5  47]
- [  9   6  16 102   4   6  15]
- [  0   7   4   5  52   3   0]
- [  7   0   2   2   0  49   2]
- [ 18   4  10   7   5  13  83]]
-Node Classification on random seed  2461 -> 0.631
-Confusion Matrix:
- [[ 96   5   5   3   0   3  11]
- [  3 119  11   2  14   4   5]
- [ 15  25 134  39  25  16  52]
- [ 15   5  19  86   2   5   3]
- [  1   3   3   4  68   1   2]
- [  3   0   2   1   2  44   3]
- [ 18   6  12   4   9   8  84]]
-Node Classification on random seed  2462 -> 0.618
-Confusion Matrix:
- [[ 85   1   2  10   3   4   8]
- [  4 126  17   0   9   7   3]
- [ 33  12 137  25  12  37  38]
- [  8   6  24 106   6   6   7]
- [  1   9   8   2  58   0   4]
- [  2   1   2   9   1  36   4]
- [  8   3  11  19   6  10  70]]
-Node Classification on random seed  2463 -> 0.585
-Confusion Matrix:
- [[ 67   2  10   3   5  16   7]
- [  3 133   3   1  10   7   9]
- [ 19  24 131  35  34  18  38]
- [ 17   8  24  87   1   4  13]
- [  2   4   9   1  60   1   3]
- [  6   1   0   5   1  40   6]
- [ 14   1  23   6   4  17  67]]
-Node Classification on random seed  2464 -> 0.628
-Confusion Matrix:
- [[ 60   2   1  17   3   2   7]
- [  2 131   3   6   7   2   2]
- [ 22  22 169  26  16  29  34]
- [ 13  10  20  95   4   6  14]
- [  1   7   5   0  64   1   2]
- [ 12   0   2   0   1  41   8]
- [ 15   3  10   5   4  26  68]]
-Node Classification on random seed  2465 -> 0.598
-Confusion Matrix:
- [[ 70   3   7   8   2   7  16]
- [  9 106  12   2  10   2   5]
- [ 19  19 149  28  29  33  47]
- [  6   1  20 106   3   8  13]
- [  3   3   3   1  66   0   3]
- [  5   1   0   2   2  47  12]
- [ 10   7   3  19   4  15  54]]
-Node Classification on random seed  2466 -> 0.617
-Confusion Matrix:
- [[ 72   0   2   4   2  16   9]
- [ 10 125   8   3   4   5   1]
- [ 19  14 127  63  17  29  46]
- [ 15   5   7  99   3   5  15]
- [  2   5   6   3  59   0   2]
- [  0   2   2   2   1  55   4]
- [  7   4   7   8   8  18  80]]
-Node Classification on random seed  2467 -> 0.625
-Confusion Matrix:
- [[ 63   6   0   3   5  14  11]
- [  3 123   2   1  12   1   2]
- [ 43  28 147  26  29  18  32]
- [  8   5  19  92   8   6  20]
- [  1   7   2   0  67   3   3]
- [  5   4   3   0   5  43   2]
- [  6   4  15   0   3  10  90]]
-Node Classification on random seed  2468 -> 0.621
-Confusion Matrix:
- [[ 57   1   6   3   6  13   7]
- [  3 122   6   0   9   0   5]
- [ 27  16 144  41  31  30  32]
- [  9   0  24 110   6   2  12]
- [  4   6   1   5  56   2   3]
- [  0   0   4   1   0  52   4]
- [ 11   4   5  19   3  18  80]]
-Node Classification on random seed  2469 -> 0.613
-Confusion Matrix:
- [[ 81   1   3   2   6  18  10]
- [  7 113   4   2   7   5   5]
- [ 21  35 130  35  24  22  44]
- [ 10   4   8 108   9   7  14]
- [  3   1   2   1  61   1   1]
- [  5   0   2   4   2  54   1]
- [ 15   4   8  11   6  17  66]]
-Node Classification on random seed  2470 -> 0.643
-Confusion Matrix:
- [[ 85   1   6   5   4   8   4]
- [  8 122   3   1  15   2   7]
- [ 32  14 139  37  31  14  34]
- [ 11   4  15 111   0   3  10]
- [  1   2   6   1  66   0   9]
- [  3   0   3   2   1  56   3]
- [  9   3  16   7   6  16  64]]
-Node Classification on random seed  2471 -> 0.583
-Confusion Matrix:
- [[ 54   2   4   4   5   9  21]
- [  9 108   3   3  12   2   7]
- [ 17  26  95  41  50  32  35]
- [  2   1  20 105  15   9  20]
- [  1   3   2   1  65   4   2]
- [  3   1   1   2   0  60   9]
- [ 14   1   3   1   5  15  96]]
-Node Classification on random seed  2472 -> 0.639
-Confusion Matrix:
- [[ 76   1   4   5   2  11  14]
- [  2 116   8   1  14   3   6]
- [ 27  25 160  21  22  17  46]
- [ 14   7   9  92   1   0  17]
- [  0   7   2   2  70   1   6]
- [  1   0   2   0   0  40  12]
- [  5   2  12   2  13  17  85]]
-Node Classification on random seed  2473 -> 0.588
-Confusion Matrix:
- [[ 70   3   4   7   2   5   5]
- [  8 116   8   2   9   3   0]
- [ 44  14 114  22  56  23  38]
- [ 10   0  13 118   3   4  14]
- [  4   5   5   4  54   1   4]
- [ 13   0   1   4   0  41   3]
- [ 24   7   8   4   7  21  75]]
-Node Classification on random seed  2474 -> 0.594
-Confusion Matrix:
- [[ 80   3   5   4   3   9   9]
- [  6 120   1   4  10   1   9]
- [ 23  25 133  52  23  25  30]
- [  9   2  30  95   9  11   6]
- [  4   5   2   1  53   3   1]
- [  1   1   2   5   1  50   3]
- [ 14   3  11  13  15  12  63]]
-Node Classification on random seed  2475 -> 0.607
-Confusion Matrix:
- [[ 61   1   2   9   6  12  15]
- [  4 109   8   5  18   1   4]
- [ 24  20 146  36  30  24  44]
- [  6   3  15 104   5   6  28]
- [  2   8   0   2  58   1   3]
- [  8   1   2   1   0  43   8]
- [  3   1   5  10   6   6  86]]
-Node Classification on random seed  2476 -> 0.575
-Confusion Matrix:
- [[ 67   1   3   3   3   5  15]
- [  7 119  10   5   7   3   8]
- [ 24  18 116  52  38  13  71]
- [  2   3  17 106   5   4   6]
- [  1   3   8   0  63   1   3]
- [  8   4   2   1   2  42   3]
- [ 16   4  14  17   4  11  62]]
-Node Classification on random seed  2477 -> 0.601
-Confusion Matrix:
- [[ 74   2   5  16   2   9  11]
- [  4 122   3   1   6   2   7]
- [ 20  23 130  49  26  18  33]
- [ 17   5  10 109   5   4  12]
- [  0   4   6   3  58   0   6]
- [  7   0   1   5   0  40   3]
- [ 16   8  11  10  13  16  68]]
-Node Classification on random seed  2478 -> 0.63
-Confusion Matrix:
- [[ 83   2   1   4   2  14  12]
- [  4 129   5   2   8   3   1]
- [ 13  38 145  23  29  34  32]
- [  5   9   9  84   9  15  14]
- [  0   7   3   2  67   2   2]
- [  8   0   0   1   1  46   6]
- [ 10   4   9   9  10   8  76]]
-Node Classification on random seed  2479 -> 0.612
-Confusion Matrix:
- [[ 76   1   3   9   3   7   8]
- [  1 127   4   2  18   3   3]
- [ 28  19 134  43  14  20  40]
- [ 10   7  13 113   3   7  18]
- [  1   4   4   2  50   4   3]
- [  1   2   2   3   1  40   7]
- [ 18   1  12  15  11  13  72]]
-Node Classification on random seed  2480 -> 0.598
-Confusion Matrix:
- [[ 85   1   2   2   6   6  10]
- [  8 128   3   5   2   6   5]
- [ 26  27 118  49  26  18  45]
- [ 12   5   5 116   9   8  16]
- [  2   7   6   0  54   0   2]
- [  7   0   6   3   1  27  12]
- [  9   1   9  14  14   7  70]]
-Node Classification on random seed  2481 -> 0.559
-Confusion Matrix:
- [[ 74   4   9   3   2  14   9]
- [  3 101  12   2  12   7   6]
- [ 26  21 125  50  25  33  49]
- [ 20   3  14  91   4   6   9]
- [  2   3   3   1  68   1   3]
- [  6   0   1   2   1  35   6]
- [ 15   2  12   0  24  16  65]]
-Node Classification on random seed  2482 -> 0.63
-Confusion Matrix:
- [[ 71   9   6   7   6  15  10]
- [  2 136   5   2   4   0   8]
- [ 13  26 143  38  21  20  39]
- [  9   6  13 114   9   7  12]
- [  3   5   0   5  62   2   6]
- [  4   2   5   5   0  29   6]
- [  5   4   5   8   6  12  75]]
-Node Classification on random seed  2483 -> 0.556
-Confusion Matrix:
- [[ 77   4   5   4   2   9   7]
- [  4 122   3   3   6   4   3]
- [ 29  34 105  18  54  25  55]
- [  7   5  13  93  13  18  24]
- [  0   7   1   0  57   4   3]
- [ 10   0   0   6   0  37   5]
- [  9   7   5   6  10  22  65]]
-Node Classification on random seed  2484 -> 0.613
-Confusion Matrix:
- [[ 63   3  10   0   6  11  11]
- [  4 131   9   1   8   3   2]
- [ 51  26 122  18  35  27  26]
- [ 13   5  12 109   7   6  11]
- [  0   5   4   2  69   0   5]
- [  5   1   2   1   2  51   8]
- [ 16   2   6   7   9   7  68]]
-Node Classification on random seed  2485 -> 0.657
-Confusion Matrix:
- [[ 65   0   2   5   3   9  19]
- [  5 134   4   3  12   0   3]
- [  8  22 166  44  18  10  38]
- [ 16   2  14  97  11   3   9]
- [  2   5   2   2  77   1   2]
- [  1   1   2   2   0  43  12]
- [  3   1  10  15   7  15  75]]
-Node Classification on random seed  2486 -> 0.62
-Confusion Matrix:
- [[ 64   0   5   2   6  14  12]
- [  2 120  10   9   4   5   6]
- [ 12  30 136  44  27  23  43]
- [ 10   3   5 113   4   3  17]
- [  0   9   7   5  55   2   3]
- [  6   0   1   2   0  40   4]
- [  8   6   5   8   6  12  92]]
-Node Classification on random seed  2487 -> 0.627
-Confusion Matrix:
- [[ 71   1   5   7   5  12   5]
- [  7 134   3   0   3   2   2]
- [ 20  31 164  27  28  24  30]
- [ 22   1  23  84   4   8   7]
- [  1   7   3   1  57   0   3]
- [  4   2   1   2   2  43   6]
- [ 22   2  14  13   5   8  74]]
-Node Classification on random seed  2488 -> 0.585
-Confusion Matrix:
- [[ 62   2   5   5   4   9   8]
- [  3 131   3   5   6   0   5]
- [ 18  21 127  54  24  30  51]
- [ 19   2  18  95  10   5   8]
- [  1   9   2   2  52   4   4]
- [  5   2   2   2   1  59   3]
- [ 10   1   9  16  15  12  59]]
-Node Classification on random seed  2489 -> 0.616
-Confusion Matrix:
- [[ 70   5   1   6   3   9  16]
- [  4 119  12   2   8   3   3]
- [ 18  23 146  36  38  22  47]
- [  8   6  10  96  13  10  11]
- [  0   3   4   4  58   0   1]
- [  1   1   3   0   0  47   6]
- [  7   4  10   3  15   8  80]]
-Node Classification on random seed  2490 -> 0.598
-Confusion Matrix:
- [[ 66   2   9   4   5  10   5]
- [  3 129   8   3   5   2   2]
- [ 26  12 136  45  39  20  39]
- [  9   5  16  95   9   7  16]
- [  2  13   3   0  55   0   1]
- [  6   1   3   2   0  44   2]
- [  6  10  12   5  15  20  73]]
-Node Classification on random seed  2491 -> 0.63
-Confusion Matrix:
- [[ 73   2   4   5   4   5   5]
- [  3 150   2   2   6   1   1]
- [ 15  24 141  44  33  20  33]
- [ 17   6  11  85   4  14  19]
- [  2  12   7   1  55   3   4]
- [  9   3   1   1   0  56   3]
- [  6   5   9   5   7  12  70]]
-Node Classification on random seed  2492 -> 0.617
-Confusion Matrix:
- [[ 62   3   3   6   0  22  11]
- [  1 127   5   8   5   1   4]
- [ 23  20 148  48  27   3  54]
- [ 13   9  15  95   7   8  16]
- [  1   5   2   2  61   0   2]
- [  1   2   0   0   0  50   9]
- [  5  11   5   7   7  12  74]]
-Node Classification on random seed  2493 -> 0.642
-Confusion Matrix:
- [[ 69   2   3   3   2  12   8]
- [ 10 113  12   4  11   2   8]
- [ 28  12 184  26  23  21  25]
- [ 13   1  16 104   7   1  15]
- [  2   9   3   1  58   1   4]
- [  3   1   1   3   3  45   3]
- [ 13   2  10   9   5  20  69]]
-Node Classification on random seed  2494 -> 0.642
-Confusion Matrix:
- [[ 63   1   2  13   2   9  19]
- [  6 114   7   4  18   0   7]
- [ 17  14 147  36  31  24  26]
- [  7   3  11 133   3   4  10]
- [  3   3   1   2  53   3   2]
- [  0   0   4   3   0  54   6]
- [  9   1  11  16   5  15  78]]
-Node Classification on random seed  2495 -> 0.594
-Confusion Matrix:
- [[ 67   4   9   4   3  16  11]
- [  5 114   0   6  10   1   3]
- [ 20  26 119  45  25  20  58]
- [  5   0  12 127   4   5  10]
- [  2   2   9   0  53   1   2]
- [  6   4   4   0   0  45   3]
- [ 27   4   6   7   3  24  69]]
-Node Classification on random seed  2496 -> 0.643
-Confusion Matrix:
- [[ 64   1   8   6   2  11  19]
- [  7 113   3  11   9   4   5]
- [ 13  22 166  22  17  29  40]
- [ 11   5  12 101   8   4   8]
- [  2   7   7   4  66   2   0]
- [  3   0   2   0   1  53   3]
- [  9   2   6   9   6  17  80]]
-Node Classification on random seed  2497 -> 0.633
-Confusion Matrix:
- [[ 83   2   6   6   9   5   6]
- [  2 123   7   0  10   3   1]
- [ 28  14 133  40  17  21  32]
- [  8   2  19 105   3   8  24]
- [  4   5   8   2  60   0   2]
- [  7   0   2   3   2  49   7]
- [ 19   3  11   8   5   6  80]]
-Node Classification on random seed  2498 -> 0.627
-Confusion Matrix:
- [[ 75   6   0   9   6   6  13]
- [  6 127   3   4   1   1   3]
- [ 24  19 139  56  18  22  40]
- [  3   6  13  93   3   4  18]
- [  1   9   1   0  58   0   4]
- [  3   3   2   1   2  47   5]
- [ 12   4  10   3  10  19  88]]
-Node Classification on random seed  2499 -> 0.643
-Confusion Matrix:
- [[ 73   1   2  10   2   7  15]
- [  8 127   2   4   4   2   7]
- [ 14  21 162  32  27  25  38]
- [  9   5  11 113   5   8  11]
- [  3   6   5   1  58   0   1]
- [  7   1   3   1   0  50   4]
- [ 15   1  10   6   4  19  60]]
-Node Classification on random seed  2500 -> 0.624
-Confusion Matrix:
- [[ 55   3  11   8   6   7   8]
- [  8 110   6   0  10   2   3]
- [ 25  35 165  34  16  24  25]
- [ 16   4  16 105   6   6  12]
- [  2   1   3   3  64   2   1]
- [  9   1   0   1   0  46   6]
- [ 23   4   4   7   2  16  79]]
-Node Classification on random seed  2501 -> 0.649
-Confusion Matrix:
- [[ 75   4   2   2   7  10   5]
- [  1 132   5   4   7   1   4]
- [ 27  26 152  23  21  17  29]
- [ 15  14  19 103   6   8   9]
- [  2   7   3   4  70   0   2]
- [  5   1   4   1   1  46   1]
- [ 14   2   6  16   2  14  71]]
-Node Classification on random seed  2502 -> 0.624
-Confusion Matrix:
- [[ 71   3   3   4   4   9   3]
- [  0 138   7   2   4   4   3]
- [ 25  21 127  31  32  20  43]
- [ 10   3  13 105   7  16   6]
- [  0   8   8   1  63   1   3]
- [  5   3   2   2   2  53   3]
- [  9   5   7  10  14  20  67]]
-Node Classification on random seed  2503 -> 0.65
-Confusion Matrix:
- [[ 74   1   0   5   3  19  10]
- [  9 132   3   2   2   2   3]
- [ 25  25 158  29  32  10  27]
- [ 14   3  14  99   4   4  15]
- [  1  12   4   2  56   1   5]
- [  1   1   1   0   0  52   9]
- [ 12   4   4   3   9  20  79]]
-Node Classification on random seed  2504 -> 0.611
-Confusion Matrix:
- [[ 87   2   6   2   4   9   2]
- [  3 119   8   1   5   1   2]
- [ 33  21 150  37  17  25  54]
- [ 13   6  17  93   1  10  21]
- [  0   4   2   1  53   1   1]
- [  1   2   6   3   0  42   7]
- [ 12   4  20   2   3  20  67]]
-Node Classification on random seed  2505 -> 0.608
-Confusion Matrix:
- [[ 72   3   6   4   5  12  14]
- [  3 157   0   3   6   1   4]
- [ 28  16 141  33  20   4  56]
- [  7  13  28  81   7   2  14]
- [  0  11   6   3  56   1   1]
- [  6   4   6   1   0  33   6]
- [ 13   5  13  14   6   7  68]]
-Node Classification on random seed  2506 -> 0.603
-Confusion Matrix:
- [[ 65   1   6   7   2   9  11]
- [  3 116   4   4  20   1   3]
- [ 24   7 140  42  36  19  42]
- [ 12   5  11 100  10   5  21]
- [  1   7   5   5  68   1   0]
- [  4   1   2   1   3  47   6]
- [ 10   4  12   7  10  13  67]]
-Node Classification on random seed  2507 -> 0.584
-Confusion Matrix:
- [[ 57   2   6   2   2  18  16]
- [  4 126  12   1   7   2   4]
- [ 26  24 136  44  11  28  53]
- [ 18   9  15 101   2   5  10]
- [  1   9   3   7  47   2   4]
- [  9   1   2   2   1  42   5]
- [  9   2  14   3   3  18  75]]
-Node Classification on random seed  2508 -> 0.651
-Confusion Matrix:
- [[101   1   1   6   4   9   2]
- [  6 127   0   2   6   1  10]
- [ 18  15 140  36  26  28  41]
- [ 11   2  14 108   2  10   4]
- [  1   4   3   2  62   1   1]
- [ 12   1   2   0   1  46   1]
- [ 24   3   9  11   5  13  67]]
-Node Classification on random seed  2509 -> 0.607
-Confusion Matrix:
- [[ 72   0   3   3   7   5  20]
- [ 10 130   1   1  13   1  11]
- [ 26  17 135  42  29  19  53]
- [ 19   2  12 105   8   6  14]
- [  3   3   2   0  49   2   4]
- [  5   0   3   2   0  34  10]
- [  7   1   3  15   7   4  82]]
-Node Classification on random seed  2510 -> 0.595
-Confusion Matrix:
- [[ 67   2   1   7   7  11   7]
- [  3 118  11   1   6   3   4]
- [ 29  22 139  26  29  17  61]
- [  5   1  20 103   5   3  12]
- [  6   3   3   1  60   2   3]
- [  5   2   2   3   5  43  11]
- [ 18   2  16  10   5  15  65]]
-Node Classification on random seed  2511 -> 0.62
-Confusion Matrix:
- [[ 70   6   3   3   6  20   6]
- [  3 120   1   0  17   0   5]
- [ 28  17 149  30  18  27  47]
- [  7   2  25 109   5   5  15]
- [  1   1   5   0  65   1   2]
- [  3   1   0   1   2  47   1]
- [ 11   3   6   7  13  26  60]]
-Node Classification on random seed  2512 -> 0.585
-Confusion Matrix:
- [[ 57   1  12   6   4   9  10]
- [  4 120   6   1   6   3  11]
- [ 29  17 146  27  30  16  46]
- [ 13   6  23  91   8   5  12]
- [  1   7   7   1  62   0   3]
- [  8   1   3   2   0  42   7]
- [ 10   2  18   3  24  13  67]]
-Node Classification on random seed  2513 -> 0.607
-Confusion Matrix:
- [[ 65   1  13   1   5  15  10]
- [  2 116  10   4  16   2   7]
- [ 18  22 154  42  37  12  32]
- [  6   3  14  96   3   6  13]
- [  2   3   2   3  61   0   2]
- [  5   0   6   3   7  38   3]
- [  9   2  17   9  11  15  77]]
-Node Classification on random seed  2514 -> 0.607
-Confusion Matrix:
- [[ 67   3   5   3   0   6  17]
- [  8 124   7   2   7   0   8]
- [ 40  17 140  35  23  22  39]
- [ 10   3  12 111   4   4  13]
- [  3   3   3   1  57   0   4]
- [ 12   3   5   1   0  36   5]
- [ 13   6  18   6  11  11  72]]
-Node Classification on random seed  2515 -> 0.638
-Confusion Matrix:
- [[ 61   3   2   4   4  18  12]
- [  3 136   5   3   3   2   3]
- [ 31  24 158  29  20  21  31]
- [  9   1  19  89  10   7  16]
- [  1   8   7   0  64   0   0]
- [  3   2   5   2   1  46   5]
- [ 11   5  11   0   9  12  84]]
-Node Classification on random seed  2516 -> 0.599
-Confusion Matrix:
- [[ 66   4   2   1   1  13  24]
- [  2 132   3   1   6   3   5]
- [ 28  22 124  24  27  17  54]
- [ 16   4  15 108   7   2  16]
- [  0  14   2   3  60   1   2]
- [  3   0   5   2   0  37   9]
- [  9   3  13   4  23  11  72]]
-Node Classification on random seed  2517 -> 0.63
-Confusion Matrix:
- [[ 68   1   5   2   4   7  16]
- [  8 116   5   3   9   2   3]
- [ 18  22 168  30  32  18  34]
- [  3   3  17 109  18   5   8]
- [  4   3   1   1  57   0   1]
- [  6   2   3   0   2  38  18]
- [ 10   4   8   4   8  22  74]]
-Node Classification on random seed  2518 -> 0.592
-Confusion Matrix:
- [[ 67   8   7   6   5  10   4]
- [  0 131   7   5   4   3   2]
- [ 19  27 142  17  21  15  63]
- [ 21   4  19  94  10   6  19]
- [  2   8   7   1  43   0   0]
- [  5   3   3   0   0  46  13]
- [  7   5  13  14   8  17  69]]
-Node Classification on random seed  2519 -> 0.593
-Confusion Matrix:
- [[ 63   4   7   2   2  15   9]
- [ 12 109   4   1  10   2   3]
- [ 20  26 168  21   9  29  51]
- [ 15   8  13  72  13  11  18]
- [  1   5   2   2  64   2   1]
- [ 12   2   6   4   0  36   4]
- [ 15   7   8  16   6   9  81]]
-Node Classification on random seed  2520 -> 0.564
-Confusion Matrix:
- [[ 78   1   3  12   3  15   6]
- [  3 129   0   0  15   4  10]
- [ 23  23 103  50  37  23  46]
- [ 13   8  19  83   3   4  21]
- [  2   9   2   3  57   1   4]
- [  7   0   4   1   0  40   2]
- [  7   5   7   9   7  24  74]]
-Node Classification on random seed  2521 -> 0.598
-Confusion Matrix:
- [[ 95   0   5   1   4  10   6]
- [  6 130   2   0   6   1   3]
- [ 26  24 137  25  30  34  50]
- [ 21   9  15  86   3   3  10]
- [  1   4  12   6  44   0   5]
- [ 11   2   0   0   0  44   6]
- [ 20   4  10   8   7  12  62]]
-Node Classification on random seed  2522 -> 0.627
-Confusion Matrix:
- [[ 67   0   9   2   3   8  16]
- [  7 122   8   4   6   2   1]
- [ 39  25 132  25  16  20  54]
- [  6   4  10 100   3   7  11]
- [  2   6   1   3  70   3   6]
- [  3   3   0   1   1  54   8]
- [ 16   1  11   5   4  13  82]]
-Node Classification on random seed  2523 -> 0.611
-Confusion Matrix:
- [[ 62   3   9   6   5   6  17]
- [ 10 135   4   3   5   1  11]
- [ 18  13 115  52  29  22  41]
- [  3   5  14 114  10   7  11]
- [  1   3   2   3  68   1   1]
- [  7   1   3   6   0  45   7]
- [  6   2  10   4  12  15  72]]
-Node Classification on random seed  2524 -> 0.632
-Confusion Matrix:
- [[ 62   5   1  12   1  11  13]
- [  5 128   4   1   3   2   1]
- [ 20  28 138  41  35  13  34]
- [  9  12  10 115   4   5  11]
- [  0   4   3   0  65   0   3]
- [  6   1   2   1   0  46   7]
- [ 14   3  18   9   4  12  78]]
-Node Classification on random seed  2525 -> 0.653
-Confusion Matrix:
- [[ 80   1   7   2   3   7   8]
- [ 15 122   4   5  16   4   2]
- [ 22  17 175  23  21  23  35]
- [  8   3  10 111   2   4  15]
- [  2   4   4   4  56   1   2]
- [ 12   0   6   0   1  35   3]
- [ 13   3  11   2   6  16  74]]
-Node Classification on random seed  2526 -> 0.624
-Confusion Matrix:
- [[ 74   4   1   4   6   5  12]
- [  1 119   3   5   2   4   5]
- [ 27  24 140  45  30  19  38]
- [ 17   7  13 100   8   8   9]
- [  0   7   7   0  70   1   2]
- [  5   2   1   4   3  43   4]
- [  6   6   6   4   5  16  78]]
-Node Classification on random seed  2527 -> 0.588
-Confusion Matrix:
- [[ 68   2   5   6  14   7   8]
- [  5 139  12   2   2   2   5]
- [ 28  25 109  49  32  18  48]
- [ 13   6  13 101   5   2  20]
- [  0   2   2   3  67   3   2]
- [ 12   2   0   0   0  34   7]
- [ 13   4  10   4   5  14  70]]
-Node Classification on random seed  2528 -> 0.634
-Confusion Matrix:
- [[ 74   2   4   4   5  12   4]
- [  8 124   9   3   6   1   2]
- [ 26  20 154  27  16  17  30]
- [ 12   6  28  90  11   3  18]
- [  1   6   2   1  72   3   2]
- [ 10   3   1   0   0  43   6]
- [ 17   7   4   4   6  19  77]]
-Node Classification on random seed  2529 -> 0.608
-Confusion Matrix:
- [[ 73   4  11   6   6  11   4]
- [  4 133  12   3  12   1   3]
- [ 23  20 141  20  35  16  42]
- [ 15   3  17  87   5   8  13]
- [  1   6   7   2  54   2   2]
- [  8   0   5   0   1  43   4]
- [ 18   2  12  10   8  10  77]]
-Node Classification on random seed  2530 -> 0.557
-Confusion Matrix:
- [[ 60   6  11   8   5   7   5]
- [  2 120  10   3  11   9   7]
- [ 22  20 104  56  61  18  32]
- [  8   6  10  98  14   8  10]
- [  1   3   2   0  58   1   5]
- [  6   1   2   5   0  42   4]
- [ 25   0   6   5  11  17  75]]
-Node Classification on random seed  2531 -> 0.624
-Confusion Matrix:
- [[ 72   2   6   6   4   4  16]
- [  6 137  10   3  17   3   1]
- [ 15  27 109  28  18  28  46]
- [ 18   6   8 119   3   4  12]
- [  1   4   4   3  62   0   2]
- [  3   1   0   5   1  42   5]
- [ 10   5  11   8   5  17  83]]
-Node Classification on random seed  2532 -> 0.641
-Confusion Matrix:
- [[ 57   8   0   1   2  16  10]
- [  5 149   2   1   2   1   9]
- [ 15  35 143  26  16  27  36]
- [ 13  13  21 101   1   5  12]
- [  2  10   1   3  68   1   2]
- [  4   1   2   1   0  45   3]
- [  9   3   9   4  17  10  78]]
-Node Classification on random seed  2533 -> 0.657
-Confusion Matrix:
- [[ 81   2   4   5   2   7  22]
- [  9 122   5   0   6   3   1]
- [ 23  33 160  22  21  13  36]
- [  6   3  18  98   4   1  13]
- [  3   4   5   1  63   0   5]
- [  7   2   4   3   2  46   3]
- [  8   2  10   6   7  12  87]]
-Node Classification on random seed  2534 -> 0.607
-Confusion Matrix:
- [[ 73   6   5   6   3  10  14]
- [  4 118   2   6   8   1   3]
- [ 21  34 149  50  19  11  42]
- [ 10   7  12  86   7   9  13]
- [  0   3   3   5  59   1   1]
- [  1   0   5   5   3  52   1]
- [  6   5  11  16   8  16  70]]
-Node Classification on random seed  2535 -> 0.592
-Confusion Matrix:
- [[ 70   9   2   5   6  11  16]
- [  2 118   7   2   5   4   6]
- [ 22  24 138  31  22  30  33]
- [ 11   5  24  87   2  17  13]
- [  0  11   1   2  63   1   6]
- [  5   0   2   3   1  52  11]
- [ 11   3  12   6   9  15  64]]
-Node Classification on random seed  2536 -> 0.579
-Confusion Matrix:
- [[ 66   1   3   3   2   6  22]
- [  5 120   5   2  14   5   7]
- [ 26  37 119  53  21  31  29]
- [  8   6  21  96   8   2  13]
- [  1   5   3   2  61   4   1]
- [  6   2   6   1   1  46   7]
- [ 17   3  13   7   4   8  71]]
-Node Classification on random seed  2537 -> 0.607
-Confusion Matrix:
- [[ 70   2   5   8   2   7   8]
- [  2 135   8   3   5   3   6]
- [ 15  33 121  17  52  11  44]
- [ 10  11  17  90  17   7  16]
- [  0   6   4   0  65   1   2]
- [  1   2   4   0   1  43   8]
- [ 13   2  12   4  12  12  83]]
-Node Classification on random seed  2538 -> 0.626
-Confusion Matrix:
- [[ 60   1   5   3   2  21  19]
- [  3 142   4   4   9   0   5]
- [  7  28 161  35  28  20  22]
- [  3   5   8 109  11  10  16]
- [  2   4   4   2  61   0   4]
- [  9   1   5   0   2  36   6]
- [  0   3   4  23  11  25  57]]
-Node Classification on random seed  2539 -> 0.634
-Confusion Matrix:
- [[ 91   2   3   5   4   7   7]
- [  6 114   5   1   6   0   2]
- [ 22  13 162  17  24  39  36]
- [  6   4  19  92   9  12  21]
- [  2   7   3   4  69   0   0]
- [ 15   0   3   1   4  43   1]
- [ 23   2   8   5   8  10  63]]
-Node Classification on random seed  2540 -> 0.587
-Confusion Matrix:
- [[ 49   1   2   1   4  17  26]
- [  3 128   7   2  15   1   6]
- [ 29  28 133  23  18  27  45]
- [ 17   6  11  89   4  13  15]
- [  3  11   4   4  58   0   4]
- [  4   2   2   0   0  50   8]
- [ 12   3  12   3   7  13  80]]
-Node Classification on random seed  2541 -> 0.57
-Confusion Matrix:
- [[ 68   1   7   2  10  19   4]
- [  6 121  13   6   5   4   5]
- [ 22  11 148  32  25  27  31]
- [ 21   5  13  84   8  11  12]
- [  5   6  10   8  56   0  10]
- [ 10   1   4   0   2  35   7]
- [ 16   4  17   8   7  15  58]]
-Node Classification on random seed  2542 -> 0.59
-Confusion Matrix:
- [[ 62   1   8   4   2  13  12]
- [  6 127   2   9   5   4   5]
- [ 14   6 128  33  47  31  46]
- [  9   0   9  92  12  12  21]
- [  3   3   4   6  68   2   1]
- [  9   1   0   2   4  36   3]
- [ 21   1   9   6  13  11  77]]
-Node Classification on random seed  2543 -> 0.587
-Confusion Matrix:
- [[ 74   2   6   7   3   8   3]
- [  0 111   7   0  19   7   2]
- [ 17  18 124  14  74  20  37]
- [  9   4  43  88   5   2  12]
- [  1   8   1   0  71   0   1]
- [  9   0   1   2   0  45   1]
- [ 14   5  19   9  10  13  74]]
-Node Classification on random seed  2544 -> 0.611
-Confusion Matrix:
- [[ 78   3   2  11   9   6   7]
- [  5 127   8   2   3   3   7]
- [ 18  29 140  36  35  15  52]
- [ 20   7   8  97   7   4   9]
- [  1   9   4   1  51   1   0]
- [  7   2   1   1   0  41   9]
- [ 18   4  10   4   3   8  77]]
-Node Classification on random seed  2545 -> 0.556
-Confusion Matrix:
- [[ 63   0   0   3  10   4  37]
- [  3 117  12   4   8   1   4]
- [ 15  33 147  34  13  28  45]
- [ 16   3  32  80   0  18  12]
- [  1  11   5   3  53   0   5]
- [  9   1   1   4   0  36  12]
- [ 13   8  14  14   5   3  60]]
-Node Classification on random seed  2546 -> 0.62
-Confusion Matrix:
- [[ 65   2   2  12   1  12   8]
- [  2 126   4   2  17   6   4]
- [ 14  29 141  26  18  41  36]
- [  5   7  22 107   4   9  13]
- [  1   6   3   2  57   1   2]
- [  5   1   2   1   4  43   6]
- [  8   1  10   6   8  17  81]]
-Node Classification on random seed  2547 -> 0.589
-Confusion Matrix:
- [[ 66   1   4   3   6  21   8]
- [  7 109  10   1   6   6   5]
- [ 14  25 145  35  33  26  57]
- [  7   4  15  91   4   6  12]
- [  1   6   4   1  55   1   4]
- [  6   2   1   4   5  38   8]
- [  8   3   2  19   7  13  85]]
-Node Classification on random seed  2548 -> 0.597
-Confusion Matrix:
- [[ 65   5   8   3   2  16  10]
- [  8 141   6   3  13   4   0]
- [ 32  23 133  25  19  26  41]
- [ 26   4  11  87   6   3  16]
- [  1   8   3   2  61   2   2]
- [ 11   1   0   2   4  36   8]
- [ 13   2   7   8   6  13  74]]
-Node Classification on random seed  2549 -> 0.661
-Confusion Matrix:
- [[ 79   1   3   8   5  14   0]
- [  2 120   8   5   2   1   4]
- [ 18  28 165  41  13  21  24]
- [  9   4  16  99  13   7  14]
- [  1   7   0   0  70   1   3]
- [  2   3   2   0   0  36  15]
- [  9   6   3   3   8  15  92]]
-Node Classification on random seed  2550 -> 0.621
-Confusion Matrix:
- [[ 77   3   4   2   4   5   5]
- [  6 124   9   0  12   0   2]
- [ 31  21 158  39  28  17  37]
- [ 12   6  20  93   1   7   8]
- [  2   8  10   1  47   0   4]
- [  6   6   4   0   1  48   1]
- [  8   1  16   8  11  13  74]]
-Node Classification on random seed  2551 -> 0.627
-Confusion Matrix:
- [[ 67   2   8   1   3  18  13]
- [  2 141   2   0   1   0   3]
- [ 13  28 159  13  26  19  59]
- [ 10   7  19  88  10   5  21]
- [  0   7   3   1  60   1   3]
- [ 12   1   5   8   0  37   5]
- [ 12   4   5   7   5  11  75]]
-Node Classification on random seed  2552 -> 0.648
-Confusion Matrix:
- [[ 64   3   1   4   4  14  10]
- [  3 130  10   1   8   3   4]
- [ 20  16 158  28  21  42  22]
- [ 15   1  10 115   3  11  15]
- [  2   5   3   4  65   0   0]
- [  1   2   0   4   0  51   9]
- [  8   2  12   8   7  16  65]]
-Node Classification on random seed  2553 -> 0.637
-Confusion Matrix:
- [[ 49   2   1   9   4  20  27]
- [  6 132  13   0   2   2   4]
- [ 16  26 165  27  15  30  32]
- [  7   4  13 118   0  10  16]
- [  1   8   6   3  43   0   2]
- [  4   2   0   2   0  46   2]
- [  5   0   7  11   4  20  84]]
-Node Classification on random seed  2554 -> 0.618
-Confusion Matrix:
- [[ 68   2   6   5   5   9  16]
- [  8 122   6   2   6   3   3]
- [ 21  10 141  29  50  11  48]
- [ 13   4  15 105  10   6   9]
- [  2   7   0   1  60   0   5]
- [ 10   0   0   8   1  43   8]
- [ 18   2   3   3   2  15  79]]
-Node Classification on random seed  2555 -> 0.559
-Confusion Matrix:
- [[ 72   3   5   6   3   8   8]
- [  0 128   3  10   3   9   1]
- [ 30  42 117  41  21  15  62]
- [ 20   5   9  88  13   3  11]
- [  1   6   3   3  57   1   3]
- [ 13   1   2   0   0  37   6]
- [ 20   5  12   9  12  13  60]]
-Node Classification on random seed  2556 -> 0.591
-Confusion Matrix:
- [[ 80   2   2   0   1  10  18]
- [  3 146   2   5   3   2   3]
- [ 28  58 109  50  15  18  37]
- [ 11   2  16  87  10   2  14]
- [  2   8   5   7  55   0   1]
- [ 13   0   2   1   1  43   5]
- [  7   7  14   4   6  14  71]]
-Node Classification on random seed  2557 -> 0.622
-Confusion Matrix:
- [[ 68   2   9   3   3  12  22]
- [  7 117   4   2   5   0   5]
- [ 40  28 160  18  26  14  44]
- [  5   5  21  97  13   4   9]
- [  1   6   4   2  48   1   2]
- [  5   2   1   1   0  45   1]
- [  8   7   7  10   4  15  87]]
-Node Classification on random seed  2558 -> 0.617
-Confusion Matrix:
- [[ 76   1   3   1   5   6   9]
- [  6 111   8   4   8   3   9]
- [ 24  11 155  38  26  17  53]
- [ 15   4  18  98  11   7  12]
- [  3   2   4   2  68   0   2]
- [  7   0   3   1   0  35   5]
- [  6   2  14   7  15  11  74]]
-Node Classification on random seed  2559 -> 0.639
-Confusion Matrix:
- [[ 75   7   5   2   5  13   1]
- [  2 136   3   2   6   2   5]
- [ 27  19 138  39  17  28  38]
- [  7   8  12 112   7   3   8]
- [  4   6   3   6  61   2   4]
- [  5   1   2   0   4  51   2]
- [ 10   3   3  17   4  19  66]]
-Node Classification on random seed  2560 -> 0.61
-Confusion Matrix:
- [[ 74   4   8   9   3   8   6]
- [ 10 119   5   2  11   3   6]
- [ 19  29 145  23  24  25  29]
- [ 15   8  19 107   5   2  11]
- [  0   7   1   3  53   2   6]
- [  9   2   4   3   3  41   5]
- [ 12   2  15   8   7  17  71]]
-Node Classification on random seed  2561 -> 0.612
-Confusion Matrix:
- [[ 47   3   6   8   9  12  21]
- [  7 139   5   3   8   3   3]
- [ 17  17 151  34  29  24  49]
- [  5   3   5 106  10   7  14]
- [  2   5   4   3  53   1   1]
- [  7   2   4   4   1  34   7]
- [ 16   5   4   5   7   8  82]]
-Node Classification on random seed  2562 -> 0.62
-Confusion Matrix:
- [[ 74   3   2  10   3   4  11]
- [  3 139   1   2   7   5   7]
- [ 24  18 134  51  33  23  34]
- [  9   4  17  81  11   5  18]
- [  2   9   1   0  68   0   2]
- [  2   1   2   0   1  45   8]
- [ 14   2  10   1  10  10  79]]
-Node Classification on random seed  2563 -> 0.604
-Confusion Matrix:
- [[ 71   4   1   9   1  12   6]
- [  0 137   3   2  13   5   8]
- [ 25  37 118  40  38  19  27]
- [ 15   9  19 104   5   3   8]
- [  0  10   3   0  53   1   2]
- [  8   1   2   1   1  40   6]
- [ 14   7   3   8   6  14  81]]
-Node Classification on random seed  2564 -> 0.587
-Confusion Matrix:
- [[ 71   0   5   6   4   8  15]
- [  4 129  15   0   2   3   4]
- [ 30  16 109  57  30  15  49]
- [ 11   5  12 112  11   6  13]
- [  4  12   3   1  48   2   6]
- [  5   0   6   3   0  38   7]
- [ 12   3   3   7   2  16  80]]
-Node Classification on random seed  2565 -> 0.6
-Confusion Matrix:
- [[ 58   0   5  16   0   7  23]
- [  8 102  17   2  10   4   8]
- [ 21  23 154  29  22  20  33]
- [ 15   2   6 104  11   2  13]
- [  1   4   7   0  62   2   0]
- [ 10   0   2   0   0  49   7]
- [ 21   1  16  17   5  10  71]]
-Node Classification on random seed  2566 -> 0.639
-Confusion Matrix:
- [[ 85   1   1   4   4  13   4]
- [  5 129   7   7   4   3   3]
- [ 14  24 161  37  26  24  37]
- [ 16   3  16  91   3   9  11]
- [  0   7   3   1  61   1   5]
- [  5   2   0   0   1  32   8]
- [ 12   5   7   4   9  15  80]]
-Node Classification on random seed  2567 -> 0.64
-Confusion Matrix:
- [[ 62   4   5  12   7   5   9]
- [  0 138   5   5  12   0   2]
- [ 17  29 166  28  19  18  30]
- [  6   3  23  99   5   9   9]
- [  2   3   3   3  56   0   4]
- [ 13   2   3   0   0  42   6]
- [ 14   8   9  10   4  14  77]]
-Node Classification on random seed  2568 -> 0.565
-Confusion Matrix:
- [[ 61   0   2   3   6  18  13]
- [  4 129   5   2  16   7   6]
- [ 44  27 139  25  10  10  54]
- [ 24   3  13  71  12   7  18]
- [  2   7   0   0  60   3   2]
- [  5   0   4   2   6  32   5]
- [ 26   2   8   4  11  19  73]]
-Node Classification on random seed  2569 -> 0.646
-Confusion Matrix:
- [[ 75   1   8   1   5   7   7]
- [  2 120   4   1   5   7   4]
- [ 25  17 142  38  25  15  46]
- [ 11   1  13 112   9   2  21]
- [  0   6   4   1  71   2   3]
- [ 10   1   0   0   1  48   3]
- [ 14   3   4   6  10  11  78]]
-Node Classification on random seed  2570 -> 0.629
-Confusion Matrix:
- [[ 65   1   3   7   5  15  10]
- [  7 135   1   7  11   1   1]
- [ 20  20 138  49  18  14  37]
- [  2   3  11  93   6  10  11]
- [  1   5   9   0  77   1   3]
- [  5   1   5   3   0  47   4]
- [  8   3  21   8   9  15  74]]
-Node Classification on random seed  2571 -> 0.649
-Confusion Matrix:
- [[ 83   1   4   1   2   7   4]
- [  5 144   4   2   6   4   2]
- [ 30  31 127  20  39  14  34]
- [ 12   2  12 110   8   8   9]
- [  7   6   1   0  70   0   1]
- [  7   1   2   1   2  44   2]
- [ 23   2  14   5   6  10  71]]
-Node Classification on random seed  2572 -> 0.636
-Confusion Matrix:
- [[ 69   3   4   6   1  11  15]
- [  9 122   0   2   3   2  14]
- [ 11  31 142  28  18  30  39]
- [  4   1  18 107   6   9  18]
- [  0   5  12   0  51   0   4]
- [  6   0   1   3   0  50   5]
- [  6   5   3  10   4  17  95]]
-Node Classification on random seed  2573 -> 0.653
-Confusion Matrix:
- [[ 79   4   1   5   4   6   6]
- [  5 109   7   3  13   5   8]
- [ 22  18 179  12  22  18  36]
- [  8   9  20  93  10   4  11]
- [  2   3   5   1  66   1   3]
- [  8   1   3   1   1  55   6]
- [ 19   3   4   9   8  12  72]]
-Node Classification on random seed  2574 -> 0.605
-Confusion Matrix:
- [[ 75   9   2   5   8  10   7]
- [  4 132   4   1  15   5   2]
- [ 31  21 126  28  27  35  29]
- [ 18   4  12 104   7   6  12]
- [  2   5   6   0  65   0   2]
- [ 11   1   2   3   0  47   0]
- [ 17   3   4   4  11  22  56]]
-Node Classification on random seed  2575 -> 0.611
-Confusion Matrix:
- [[ 62   5   3   5   2   9  14]
- [ 14 119   7   0   6   5   7]
- [ 14  23 148  26  18  26  51]
- [  7   8  11 102   8   6   8]
- [  0  13   3   0  60   3   1]
- [  2   3   3  14   2  37   8]
- [  3   3   7  11   6  24  83]]
-Node Classification on random seed  2576 -> 0.639
-Confusion Matrix:
- [[ 79   6   4   6   3   7  10]
- [  4 137   1   3   5   4   3]
- [ 19  28 150  28  27  34  33]
- [  3   5   9 104   6   4  14]
- [  5   8   1   1  54   0   3]
- [  5   1   2   2   0  39   6]
- [ 15   4  12   7  13  10  76]]
-Node Classification on random seed  2577 -> 0.606
-Confusion Matrix:
- [[ 61   2   4  12   8  10  13]
- [  5 138   6   3  13   3   1]
- [ 25  12 135  44  38  14  42]
- [ 20   4  24  94   8   4   5]
- [  5   1   4   1  57   0   4]
- [  7   1   2   1   1  44   3]
- [ 12   1   3  11   6  11  77]]
-Node Classification on random seed  2578 -> 0.638
-Confusion Matrix:
- [[ 73   1   4   2   6   9   6]
- [  5 141   3   4   7   5   7]
- [ 15  22 131  53  25  30  34]
- [  9   3   5 115   6  11   8]
- [  1   6   4   2  50   1   3]
- [  5   2   0   2   2  51   8]
- [  3   1  11   8   8  15  77]]
-Node Classification on random seed  2579 -> 0.663
-Confusion Matrix:
- [[ 68   1   1   8   6  17  10]
- [  7 139   5   2   3   1   3]
- [ 24  20 148  28  20  21  42]
- [ 22   7   8  94   5   4   7]
- [  1   5   1   3  75   0   5]
- [  4   1   1   0   1  48   8]
- [ 10   2   5   5   5   8  91]]
-Node Classification on random seed  2580 -> 0.626
-Confusion Matrix:
- [[ 85   2   9   1   5   1   7]
- [  5 121   9   1   3   3   6]
- [ 29  49 118  43  24  16  23]
- [ 13   2   9 112   5   5   5]
- [  3   9   3   7  56   1   1]
- [ 14   4   1   1   0  47   3]
- [ 17  10   9   3   3  10  87]]
-Node Classification on random seed  2581 -> 0.626
-Confusion Matrix:
- [[ 84   0   9   5   4  13   9]
- [  5 117   6   1  10   1   2]
- [ 25  29 145  25  16  30  33]
- [  7   4  14 109   7   5  13]
- [  1   4   4   2  54   2   1]
- [  5   1   5   0   0  45   6]
- [ 17   6  24   5   2  16  72]]
-Node Classification on random seed  2582 -> 0.618
-Confusion Matrix:
- [[ 80   1   6   2   2  10  12]
- [  5 127  11   2   5   1   9]
- [ 17  22 150  28  37  15  40]
- [ 17   1  10  96  17   8  17]
- [  1   6   2   4  56   0   3]
- [ 10   0   1   0   0  44   7]
- [ 11   1   4  14   9  14  65]]
-Node Classification on random seed  2583 -> 0.578
-Confusion Matrix:
- [[ 72   9   3   4   6   7   7]
- [  4 109   2   3  22   3   8]
- [ 33  22 142  41  28  11  43]
- [  6  16  20  93   7   4  19]
- [  1   4   3   1  44   2   1]
- [  7   5   1   0   0  52   3]
- [  8   4  12  11  19  12  66]]
-Node Classification on random seed  2584 -> 0.614
-Confusion Matrix:
- [[ 76   3   1   4   2  10   6]
- [  5 129   2   5  12   8   1]
- [ 28  29 115  28  24  36  43]
- [ 10   5  13 104   4  10  20]
- [  1   1   2   3  59   0   2]
- [  4   0   0   2   0  51   5]
- [ 13   1   7   8   5  23  80]]
-Node Classification on random seed  2585 -> 0.622
-Confusion Matrix:
- [[ 84   1   4   3  10   8  16]
- [  7 128   5   2   7   0  10]
- [ 36  19 134  35  29  11  32]
- [ 12   3   8 105   7   5   8]
- [  4   7   5   1  64   0   3]
- [  6   0   0   3   1  43   9]
- [ 15   4   5  17   7  13  64]]
-Node Classification on random seed  2586 -> 0.624
-Confusion Matrix:
- [[ 81   8   5   6   8   2   3]
- [  7 126   7   2   5   2   5]
- [ 19  47 138  35  23  15  35]
- [ 16   6   6 101   4   7  12]
- [  0   3   3   2  57   1   2]
- [ 10   1   0   4   3  39   5]
- [ 15   4  13   7   7  11  82]]
-Node Classification on random seed  2587 -> 0.636
-Confusion Matrix:
- [[ 64   3   2   3   4  13  23]
- [  4 138   1   0   3   1   3]
- [ 16  28 148  24  39  17  33]
- [ 13   4  22  94   4   9  15]
- [  2  10   3   0  59   1   2]
- [  0   0   1   1   2  48   9]
- [  4   2   9   5   8  21  85]]
-Node Classification on random seed  2588 -> 0.652
-Confusion Matrix:
- [[ 67   3   6   7   3  11   6]
- [  0 152   3   1   6   2   5]
- [ 27  14 161  27  21  40  30]
- [ 25   2   7  95   6   4  11]
- [  0   5   1   3  64   2   3]
- [  8   1   2   2   1  55   5]
- [ 17   1   8   7   8   7  58]]
-Node Classification on random seed  2589 -> 0.608
-Confusion Matrix:
- [[ 76   5   3   6   3  13   4]
- [  7 132   3   2  12   1   2]
- [ 18  21 126  36  42  32  42]
- [ 12   9  22 100   7   5   9]
- [  0   7   1   0  60   1   2]
- [  4   2   2   4   2  39   4]
- [  6   2  10   6   8  15  75]]
-Node Classification on random seed  2590 -> 0.669
-Confusion Matrix:
- [[ 71   1   5   5   5  17   7]
- [  3 143   9   2   7   0   2]
- [ 22  10 163  24  16  37  28]
- [  9   3  21  95   2   9  13]
- [  2   5   4   1  67   3   1]
- [  7   1   0   1   0  54   3]
- [ 10   4  12   2   7  11  76]]
-Node Classification on random seed  2591 -> 0.583
-Confusion Matrix:
- [[ 61   8   8   6   0   9   9]
- [  4 103   7   1  18   3   3]
- [ 38  15 168  19  40  28  44]
- [ 30   4  16  83   5   8  10]
- [  3   8   2   2  60   0   4]
- [  2   1   1   0   0  47   5]
- [ 20   2   7   4  10  13  61]]
-Node Classification on random seed  2592 -> 0.6
-Confusion Matrix:
- [[ 66   3   5  14   3   6  10]
- [  4 122   4   0  12   3   5]
- [ 22  21 124  54  35  21  40]
- [  9   2  15 115   7   7   8]
- [  0   6   6   2  62   1   1]
- [ 11   1   0   0   1  38   3]
- [ 16   1  14   9   8  10  73]]
-Node Classification on random seed  2593 -> 0.637
-Confusion Matrix:
- [[ 75   7   2   3   5   9  10]
- [  2 120   3   2  13   1   3]
- [ 28   7 147  43  33  14  49]
- [  8   3   7 123   7   7   7]
- [  6   4   2   1  57   5   0]
- [  5   1   0   4   2  35   7]
- [ 13   4   7  10   8  11  80]]
-Node Classification on random seed  2594 -> 0.622
-Confusion Matrix:
- [[ 73   2   1   2   3  14  14]
- [ 10 124   4   0   4   3   6]
- [ 14  28 120  39  20  42  42]
- [  5   4  16 112   7   6   8]
- [  2   4   3   4  62   2   1]
- [  2   1   1   2   1  50  10]
- [ 11   5   3   5   8  19  81]]
-Node Classification on random seed  2595 -> 0.598
-Confusion Matrix:
- [[ 67   2   0   4   4  18   5]
- [  4 131   5   1  16   4   2]
- [ 38   9 126  25  37  33  53]
- [  8   1  13 106   6   7  12]
- [  2   5   1   2  56   0   4]
- [  0   0   0   2   3  63   4]
- [  7   2   7  12  19  25  49]]
-Node Classification on random seed  2596 -> 0.596
-Confusion Matrix:
- [[ 76   3   6   4   2   9   6]
- [  4 123   6   6   6   1   2]
- [ 24  26 113  69  26  20  28]
- [ 22   3  14  97   2  12  11]
- [  2   9   0   2  67   2   1]
- [  8   2   1   1   2  42   3]
- [ 20   1  11  12   5  10  78]]
-Node Classification on random seed  2597 -> 0.635
-Confusion Matrix:
- [[ 73   2   2   4   4  16   1]
- [  6 127   5   1  11   3   2]
- [ 16  16 138  50  18  29  39]
- [ 10   5  15  98   5   7  25]
- [  0   3   2   1  66   4   3]
- [  8   0   0   0   2  55   2]
- [ 12   1   8   6   7  14  78]]
-Node Classification on random seed  2598 -> 0.603
-Confusion Matrix:
- [[ 68   2  11  10   1  11   7]
- [ 10 138   7   2   7   4   4]
- [ 29  24 135  31  34  27  15]
- [ 14   7  10  96   5   9  19]
- [  3   7   5   2  66   0   1]
- [  8   2   0   4   0  36  11]
- [ 22   4   7   5   7   9  64]]
-Node Classification on random seed  2599 -> 0.618
-Confusion Matrix:
- [[ 80   2   4   5   2  19   7]
- [  4 116   7   5  13   8   3]
- [ 26  17 147  24  34  23  27]
- [ 12   0  24  93  10   3   7]
- [  1   5   4   2  64   1   2]
- [  5   2   3   6   0  46   0]
- [  8   5  14  13   6  19  72]]
-Node Classification on random seed  2600 -> 0.632
-Confusion Matrix:
- [[ 68   7   7  13   9   7   8]
- [  3 125   4   8   6   2   2]
- [ 15  13 152  45  29  11  54]
- [ 14   3  14 110   4   2  11]
- [  0   7   1   3  62   2   4]
- [  8   0   2   2   1  46   4]
- [ 12   3   2   9   7  10  69]]
-Node Classification on random seed  2601 -> 0.602
-Confusion Matrix:
- [[ 87   1   3   6   1  10   8]
- [  3 117  20   1   2   4   6]
- [ 36  26 118  32  33  16  52]
- [  4   5  19  87   7   6  12]
- [  2   3   5   1  63   1   2]
- [  4   1   5   4   1  48   6]
- [  3   5   9   5   5  23  82]]
-Node Classification on random seed  2602 -> 0.608
-Confusion Matrix:
- [[ 66   3   4  11   1   2  11]
- [  4 124   5   0  15   1   2]
- [ 19  15 162  37  30  25  42]
- [ 12   2  20 102   8   5   9]
- [  1   5   4   2  71   1   2]
- [  6   2   3   4   5  29   3]
- [ 21   3  14  15   4  14  54]]
-Node Classification on random seed  2603 -> 0.617
-Confusion Matrix:
- [[ 70   5   1   6   3  20   6]
- [  1 125   1   2  13   2   4]
- [ 32  36 138  28  52  14  16]
- [  6   3  32 109   3   5   8]
- [  0   2   2   2  68   0   6]
- [  5   1   1   3   1  44   2]
- [  3   2  13  12  13  16  63]]
-Node Classification on random seed  2604 -> 0.618
-Confusion Matrix:
- [[ 68   8   1   3   6   5  13]
- [  5 134   9   1   5   3   3]
- [ 26  25 145  39  21  17  45]
- [ 19   3  15 104   1   5   3]
- [  2   7   3   2  53   0   1]
- [ 14   0   3   0   4  36   6]
- [ 14   3  11   9  10  12  78]]
-Node Classification on random seed  2605 -> 0.649
-Confusion Matrix:
- [[ 65   2   2   1   6   9  15]
- [  2 120   5   5  13   2   5]
- [ 13  21 166  42  35  10  39]
- [ 14   2   8 107   5   9  12]
- [  1   3   4   0  70   0   5]
- [  2   1   3   0   0  41   4]
- [  3   3  14   9   8  14  80]]
-Node Classification on random seed  2606 -> 0.608
-Confusion Matrix:
- [[ 83   1   3   6   1  17   8]
- [  2 109   7   3  13   3   1]
- [ 26  14 151  31  46  23  24]
- [  5   3  27  94   4   8   9]
- [  0   9   2   1  57   0   2]
- [  3   1   2   4   0  46   4]
- [  6   5  16  24   6  22  68]]
-Node Classification on random seed  2607 -> 0.574
-Confusion Matrix:
- [[ 51   0   3   2  10  14  13]
- [ 15 126   5   0   3   1  12]
- [ 27  17 113  55  32  28  40]
- [  7   6   8 112   8  15  10]
- [  1   3   2   4  61   1   4]
- [  4   0   3   1   1  48   9]
- [ 11   2   8   4  15  22  63]]
-Node Classification on random seed  2608 -> 0.586
-Confusion Matrix:
- [[ 58   5   7   2   8  16   9]
- [  3 112   7   4  12   7   4]
- [ 26  31 135  39  40  29  32]
- [ 19   3  12 105   9   3  12]
- [  1   4   4   4  59   2   3]
- [  4   0   3   1   2  31   6]
- [ 15   2  10   2   5   7  86]]
-Node Classification on random seed  2609 -> 0.626
-Confusion Matrix:
- [[ 81   4   5   5   8   5   4]
- [  5 119   6  10   4   2   6]
- [ 30  22 149  41  21  34  24]
- [ 18   5   3  90  12   8  11]
- [  0   5   6   5  62   1   2]
- [  6   1   1   2   0  45   0]
- [ 15   2   7   6   8  14  80]]
-Node Classification on random seed  2610 -> 0.62
-Confusion Matrix:
- [[ 67   1   1   5   5  17   0]
- [  4 141   7   3  10   1   4]
- [ 11  31 123  47  22  24  39]
- [ 12   2  12 114   6   6  12]
- [  0   6   1   5  61   3   2]
- [  3   2   2   1   2  53   1]
- [ 10   1  14  21   7  17  61]]
-Node Classification on random seed  2611 -> 0.597
-Confusion Matrix:
- [[ 74   5   7   4   6   6   6]
- [  3 122   4   7  11   1  15]
- [ 25  24 116  21  44  19  48]
- [  9   6  13  96   5   4  23]
- [  0   3   2   1  67   1   2]
- [  4   2   3   0   0  52   3]
- [ 25   7   9   3  13   9  70]]
-Node Classification on random seed  2612 -> 0.598
-Confusion Matrix:
- [[ 75   3   3   1   7  22   7]
- [  2 118   6   0   9   0   4]
- [ 16  23 116  52  36  14  37]
- [ 11   7  11 106   9  10  20]
- [  0   7   3   4  62   0   3]
- [  1   3   0   0   3  47  15]
- [  1   5  10   9   7  21  74]]
-Node Classification on random seed  2613 -> 0.596
-Confusion Matrix:
- [[ 69   5   5   5   6  10  21]
- [  6 119   6   0   3   3   6]
- [ 24  30 132  33  35  26  36]
- [ 10  16   9  85  13   9   9]
- [  2   8   2   0  64   0   2]
- [  7   3   2   0   3  46   4]
- [  9   5   8   6   7  10  81]]
-Node Classification on random seed  2614 -> 0.604
-Confusion Matrix:
- [[ 49   4   2   4   8  27   6]
- [ 11 112   5   7   4   5   8]
- [ 15  26 135  50  18  28  26]
- [  6   3  12 104   6  19  15]
- [  1   6   3   4  57   1   0]
- [  3   0   0   0   1  60   3]
- [ 12   5   2   5  14  21  87]]
-Node Classification on random seed  2615 -> 0.631
-Confusion Matrix:
- [[ 83   3   3   7   3   3  13]
- [  7 121   9   8   2   1   5]
- [ 22  10 135  58  21   9  40]
- [ 13   2  17 102   8   8  15]
- [  2   6   7   4  60   0   2]
- [  5   0   3   1   0  51   8]
- [ 19   0   7   4   5   9  79]]
-Node Classification on random seed  2616 -> 0.595
-Confusion Matrix:
- [[ 65   4  14   5   2  15  12]
- [  8 132   4   0   4   6   6]
- [ 23  24 133  29  32  26  52]
- [  6   7   9  93   8   8  15]
- [  3   8   5   1  68   0   2]
- [  2   1   0   3   0  32   6]
- [  9   4  14   8   3  17  72]]
-Node Classification on random seed  2617 -> 0.611
-Confusion Matrix:
- [[ 90   3   0   6   1   5  13]
- [  4 144   0   8   7   0   3]
- [ 27  17 124  40  32  30  28]
- [ 17   7  20  77  10  13  10]
- [  0  10   5   3  58   0   0]
- [  9   1   1   1   1  43   3]
- [ 19   4   4   8   8  11  75]]
-Node Classification on random seed  2618 -> 0.576
-Confusion Matrix:
- [[ 72   5   5   5   2   4   6]
- [  4 130   6   6  19   3   6]
- [ 20  27 120  38  45  19  53]
- [  4  13  10  95  10   4  15]
- [  4   4   3   2  62   1   1]
- [  8   2   3   1   1  33   7]
- [ 11   3   9  11   6  18  64]]
-Node Classification on random seed  2619 -> 0.618
-Confusion Matrix:
- [[ 64   2  18   4   1  16   6]
- [  4 118   6   9  11   5   1]
- [ 23  16 141  34  30  21  27]
- [ 11   5  14 112  10   2  13]
- [  2   6   1   1  52   0   7]
- [  2   0   0   1   3  43  11]
- [  8   3   9   6  16  17  88]]
-Node Classification on random seed  2620 -> 0.644
-Confusion Matrix:
- [[ 82   4   2   7   6  14  10]
- [  3 125   3   9   5   1   5]
- [ 18  25 145  55  22  23  27]
- [ 10   5  14 115   3   3   5]
- [  1   5   2   1  53   2   1]
- [  6   1   1   1   2  42   4]
- [  7   4   9  11   8  11  82]]
-Node Classification on random seed  2621 -> 0.559
-Confusion Matrix:
- [[ 54   3   5  11   5   4   9]
- [ 13 121   7   2  24   2   5]
- [ 16  30  97  38  58  14  26]
- [  8   6  26  97   6   3  13]
- [  2   4   1   1  71   3   1]
- [ 18   3   2   1   3  35   1]
- [ 21   2  13   6   9  16  84]]
-Node Classification on random seed  2622 -> 0.655
-Confusion Matrix:
- [[ 73   2   1   7   3  13   7]
- [  6 121   3   1   5   2   7]
- [ 25  19 154  32  24  21  39]
- [  5   1  18 106   2   3  19]
- [  1   3   1   4  79   0   4]
- [  3   1   2   0   0  49   7]
- [ 11   7   8   4   7  17  73]]
-Node Classification on random seed  2623 -> 0.638
-Confusion Matrix:
- [[ 78   6   5   1   1   7  12]
- [  8 132   6   2   0   4   7]
- [ 29  21 158  24  23  33  26]
- [ 12   4  12  98   5   5  18]
- [  2  10   4   0  69   2   2]
- [  8   0   1   2   1  44   3]
- [ 25   3   7   7   4  10  59]]
-Node Classification on random seed  2624 -> 0.667
-Confusion Matrix:
- [[ 73   1   3   5   1   6  11]
- [  8 121   2   2   7   1   3]
- [ 27  14 167  21  15  31  44]
- [ 13   1  12 120   7   3  10]
- [  6   7   4   0  61   0   2]
- [  6   1   3   3   0  39   3]
- [ 11   3  10   2   2  22  86]]
-Node Classification on random seed  2625 -> 0.584
-Confusion Matrix:
- [[ 72   2  14   4   0  12  10]
- [  6 129   5   2   4   1   3]
- [ 23  31 121  53  16  23  42]
- [ 16  12  12  99  12   8  10]
- [  2   2   7   1  43   2   2]
- [  6   1   4   4   1  54   3]
- [ 16   2   9   5   2  26  66]]
-Node Classification on random seed  2626 -> 0.652
-Confusion Matrix:
- [[ 65   4   6   8  12  12   6]
- [  4 145   3   0   5   1   6]
- [ 12  20 173  41  33  15  17]
- [ 16   5   8  87   7   6  12]
- [  1   5   1   0  62   1   5]
- [  8   5   4   0   0  49   4]
- [ 19   2  13   4   9   8  71]]
-Node Classification on random seed  2627 -> 0.59
-Confusion Matrix:
- [[ 70   6   9   4   1  15   3]
- [  2 122   6   8  11   1   5]
- [ 13  25 117  55  25  24  52]
- [ 23   0  16  98   5   4   7]
- [  3   4   7   5  57   0   3]
- [ 10   0   0   3   0  41   4]
- [ 15   1   6  15   4  10  85]]
-Node Classification on random seed  2628 -> 0.604
-Confusion Matrix:
- [[ 67   5   0   7   4  16  12]
- [  7 107   6   2   7   5   3]
- [ 34  16 133  40  40  14  34]
- [  8   2  19 101   4   3  15]
- [  1   5   3   2  68   2   3]
- [  6   0   1   6   0  45   7]
- [ 13   5   6   3  11  19  83]]
-Node Classification on random seed  2629 -> 0.611
-Confusion Matrix:
- [[ 61   1   1   7   7  11  17]
- [  2 109   9   2   8   2   3]
- [ 13  22 161  41  14  24  42]
- [ 14   7  20 101   4  13   7]
- [  0   5   5   3  57   0   2]
- [  2   0   3   2   5  49  11]
- [ 11   5   8   3  11  22  73]]
-Node Classification on random seed  2630 -> 0.595
-Confusion Matrix:
- [[ 73   2   0  12   6   9   4]
- [  3 110   6  10  10   1   4]
- [ 37  15 131  40  33  17  38]
- [ 10   1  20 101   8   5  13]
- [  1   7   3   3  54   1   3]
- [ 11   1   8   4   0  45   2]
- [ 15   2   6  13   2  19  81]]
-Node Classification on random seed  2631 -> 0.623
-Confusion Matrix:
- [[ 68   1   3   7   3  13   8]
- [  3 117   9   5   3   3   6]
- [ 33   8 160  23  27  19  45]
- [ 12   5  18 102  10   3  10]
- [  0   7   5   0  57   3   1]
- [  3   1   7   4   0  47   4]
- [ 12   3   8  21   8  13  72]]
-Node Classification on random seed  2632 -> 0.621
-Confusion Matrix:
- [[ 62   0  11   4   4  16  16]
- [  2 126   6   3   7   4   6]
- [ 12  20 139  58  41  22  30]
- [  5   1  23 101   7   8  11]
- [  0   7   7   1  56   0   1]
- [  1   1   5   3   0  46   2]
- [  2   3   4   3   8  14  91]]
-Node Classification on random seed  2633 -> 0.619
-Confusion Matrix:
- [[ 73   1  10   4   6   8   4]
- [  7 133   5   6  10   2   4]
- [ 11  15 126  33  35  24  58]
- [  9   1  14 107   1   4  14]
- [  0   5   5   2  68   2   1]
- [  6   2   4   1   8  47   4]
- [ 22   2   8   2   8  13  65]]
-Node Classification on random seed  2634 -> 0.581
-Confusion Matrix:
- [[ 77   4   7   4   3  10   5]
- [  2 127   7   1   3  10   7]
- [ 17  39 120  42  28  26  42]
- [  4  12  11  96   6   7  15]
- [  1   6   6   1  57   4   4]
- [  3   1   0   1   5  45   4]
- [ 15   3  19   7  14  13  59]]
-Node Classification on random seed  2635 -> 0.591
-Confusion Matrix:
- [[ 61   2   9   3   8  16   5]
- [  1 129   4   5  11   1   4]
- [ 21  26 129  62  21  16  40]
- [ 14   5   8 101   6   6  10]
- [  1  10   3   2  61   1   1]
- [  5   7   2   0   0  36  10]
- [  7   6  16  10   6  18  74]]
-Node Classification on random seed  2636 -> 0.621
-Confusion Matrix:
- [[ 58   4   2   9   1  12  12]
- [  4 129   5   1  14   1   5]
- [ 17  14 168  24  21  25  42]
- [ 12   4  24  94   5   4   9]
- [  0   7   4   1  62   3   1]
- [ 13   0   6   1   2  36   9]
- [ 19  10  12   4   7   9  74]]
-Node Classification on random seed  2637 -> 0.631
-Confusion Matrix:
- [[ 71   1   2   8   0  24  11]
- [  6 124   7   2   6   5   3]
- [ 23  19 157  43  11  26  36]
- [ 15   0  21  89   4   4  10]
- [  0   5   8   3  61   3   3]
- [  8   0   3   2   0  44   3]
- [  9   2   4   7   5  17  85]]
-Node Classification on random seed  2638 -> 0.63
-Confusion Matrix:
- [[ 67   1   1   4   7  15  15]
- [ 12 135   3   2  12   2   2]
- [ 21  29 136  18  34  13  49]
- [ 16   3   8  92   7   1  13]
- [  2   6   5   1  68   1   2]
- [  3   0   5   2   2  40   6]
- [  4   6   7   5   7  18  92]]
-Node Classification on random seed  2639 -> 0.616
-Confusion Matrix:
- [[ 72   3   4   0   6  11  14]
- [  2 113   4   6  10   4   7]
- [ 21  49 132  34  21  14  49]
- [  7   1  15 106   5  11  14]
- [  0   5   2   1  56   0   2]
- [  3   0   3   3   2  49   4]
- [  6   6   4   8  10  13  88]]
-Node Classification on random seed  2640 -> 0.648
-Confusion Matrix:
- [[ 80   1   3   4   7  10  10]
- [ 14 126   7   0   3   2   6]
- [ 34  30 166  18   8  30  33]
- [ 11   5  16  96   2   9   9]
- [  1   4   4   0  63   0   1]
- [  6   2   1   0   1  40   3]
- [  9   4  15   2   8  19  77]]
-Node Classification on random seed  2641 -> 0.631
-Confusion Matrix:
- [[ 80   4   7   6   0  12   8]
- [  1 143   4   3   2   1   2]
- [ 16  26 136  29  21  40  40]
- [  9   8  15 107   2   9  13]
- [  1   8   9   2  51   0   2]
- [  5   1   3   4   1  50   4]
- [ 16   6  14   8   0   7  64]]
-Node Classification on random seed  2642 -> 0.58
-Confusion Matrix:
- [[ 53   5   7   6   5  17   7]
- [  3 130   5   2  10   1   6]
- [ 25  19 140  42  17  32  34]
- [ 22   5  18 106   3   9  12]
- [  3   9   2   2  56   1   2]
- [  0   4   0   0   1  38  14]
- [ 14   4   9  12   7  24  57]]
-Node Classification on random seed  2643 -> 0.633
-Confusion Matrix:
- [[ 67   0   5   4   6   8  12]
- [  0 130   4   1   5   1   4]
- [ 31  29 138  29  32  37  27]
- [ 15   2  13 112   2   1  13]
- [  0   9   4   1  60   2   3]
- [  7   1   2   2   1  48   8]
- [  1   6  14   7   6  12  78]]
-Node Classification on random seed  2644 -> 0.653
-Confusion Matrix:
- [[ 72   4   5   4   3  16   2]
- [  2 135   3   0  11   4   5]
- [ 21  25 126  33  24  24  47]
- [  3   1  15 135   3   3  12]
- [  1   7   1   3  72   1   2]
- [  6   1   1   2   4  40   6]
- [  7   2   6   8   6  13  73]]
-Node Classification on random seed  2645 -> 0.616
-Confusion Matrix:
- [[ 72   1  11   5   5  11   2]
- [  7 118   2   1   8   3   8]
- [ 19  26 158  30  40  21  34]
- [  5   4  34  78  10   5  10]
- [  0   4   3   3  61   1   4]
- [  4   0   4   2   0  51   7]
- [  9   4   9   3  14  11  78]]
-Node Classification on random seed  2646 -> 0.628
-Confusion Matrix:
- [[ 74   8   4  11   9  12   0]
- [  7 116   2   1   2   2  10]
- [ 20  18 146  27  29  19  35]
- [  8   1  25 112   3   6  14]
- [  0   8   2   2  61   1   5]
- [  9   3   4   1   0  53   3]
- [ 12   2   5  10  11  21  66]]
-Node Classification on random seed  2647 -> 0.582
-Confusion Matrix:
- [[ 69   3  10   8   2  14   3]
- [  7 142   4   6   4   2   1]
- [ 26  14  90  55  36  25  48]
- [  9   7   6  99   6   7  18]
- [  6   5   1   1  61   2   3]
- [  5   3   5   2   0  41   3]
- [  9   6  11  13   9  13  80]]
-Node Classification on random seed  2648 -> 0.593
-Confusion Matrix:
- [[ 61   2   4   7   4  19  19]
- [  3 112   1   3  11   6  10]
- [ 20  19 129  42  52  12  38]
- [  6   3   7 105  15   2  11]
- [  2   2   5   3  70   0   1]
- [  7   2   1   1   1  35   8]
- [ 11   4   6   5  10  22  81]]
-Node Classification on random seed  2649 -> 0.638
-Confusion Matrix:
- [[ 70   1   6   5   3  16  11]
- [  7 110   8   2  15   1   9]
- [ 23  11 176  36  11  30  24]
- [  6   2  12 109   4   6  24]
- [  0   6   3   2  57   2   2]
- [  3   0   1   6   1  36  10]
- [ 16   2   3  14  11   7  80]]
-Node Classification on random seed  2650 -> 0.582
-Confusion Matrix:
- [[ 71   2   5   7   5  19   7]
- [  5 138   3   1   5   5   4]
- [ 20  36 117  31  24  36  44]
- [  4   4  20  92   3  16  15]
- [  0   8   1   1  73   3   2]
- [  5   1   3   3   1  42   1]
- [ 17   8  13   4   7  19  49]]
-Node Classification on random seed  2651 -> 0.627
-Confusion Matrix:
- [[ 80   2   2   8   2   2   4]
- [  8 126   4   3   3   2   4]
- [ 35  21 157  25  36  21  36]
- [ 10   0  16 101   6   4  20]
- [  4   6   4   2  50   2   3]
- [  8   1   3   0   1  44   5]
- [ 15   3  17   9   7   9  69]]
-Node Classification on random seed  2652 -> 0.632
-Confusion Matrix:
- [[ 61   3   0  15   3  14  15]
- [  3 132   2   2   5   6   4]
- [ 27  13 132  32  24  38  28]
- [ 13   5  15 112   8   4   8]
- [  2   5   6   0  59   0   2]
- [  3   3   2   2   3  49   4]
- [ 19   3   9   2   2  14  87]]
-Node Classification on random seed  2653 -> 0.611
-Confusion Matrix:
- [[ 60   1   4   5   3  19   0]
- [  5 121   3   3  16   4   5]
- [ 20  28 148  24  33  26  35]
- [ 12   8  14  99  13   2   7]
- [  3   7   3   0  67   3   4]
- [  3   4   4   2   2  46   2]
- [ 15   2  16  11   3  15  70]]
-Node Classification on random seed  2654 -> 0.645
-Confusion Matrix:
- [[ 76   2   3   4   2   9  13]
- [  4 107   2   5  14   2   4]
- [ 20  26 169  19  29  24  39]
- [  6   6  14 112   7   6  17]
- [  5   7   4   3  54   0   0]
- [  4   0   1   0   4  53   7]
- [ 11   2  10   3   7  10  74]]
-Node Classification on random seed  2655 -> 0.589
-Confusion Matrix:
- [[ 75   1   5   6   6   6  14]
- [  3 137   8   0  12   1   8]
- [ 45  20 118  32  15  25  35]
- [ 20   3  12  98   1   9  24]
- [  1   5   8   6  45   0   4]
- [  2   2   2   3   3  50   3]
- [ 26   1   9  10   5  10  66]]
-Node Classification on random seed  2656 -> 0.604
-Confusion Matrix:
- [[ 62   1  13   3   7   7  15]
- [  5 131   7   2  15   2   3]
- [ 24  27 125  38  33  26  33]
- [ 17   4  28 109   1   2  13]
- [  0   9   2   0  61   1   3]
- [  2   5   7   5   1  30   3]
- [  8   4   5   2   4   9  86]]
-Node Classification on random seed  2657 -> 0.633
-Confusion Matrix:
- [[ 64   0   4   2   6  11   8]
- [ 12 118   3   0  15   3   2]
- [ 19  18 150  37  19  24  43]
- [  7   4  13 118   7   8  13]
- [  0   4   2   0  58   0   3]
- [  6   0   1   1   1  39   9]
- [ 10   4   7  17   5  19  86]]
-Node Classification on random seed  2658 -> 0.608
-Confusion Matrix:
- [[ 69   1   4  12   7   4  11]
- [ 12 118  10   0   6   6   2]
- [ 35  18 141  21  34  20  35]
- [  4   3  26  94   6   9  10]
- [  0   7   6   1  69   0   2]
- [ 11   1   5   2   0  41   1]
- [ 16   5  16   8   8   7  76]]
-Node Classification on random seed  2659 -> 0.575
-Confusion Matrix:
- [[ 57   1   1   5  12   8  20]
- [  2 124   0   2  10   2  11]
- [ 27  17 136  42  17  11  62]
- [ 17   4  14  96   1   4  25]
- [  3   1   7   0  56   0   2]
- [  3   4   7   2   2  43   2]
- [ 20   4  16  18   6  13  63]]
-Node Classification on random seed  2660 -> 0.605
-Confusion Matrix:
- [[ 68   2   7   8   7   6  16]
- [  5 111   9   1  10   5   5]
- [ 20  19 133  33  34  28  45]
- [ 11   1  19  95   2  13  19]
- [  2   4   1   5  59   1   2]
- [  3   4   0   2   1  46   5]
- [  2   2  11   7   6  12  93]]
-Node Classification on random seed  2661 -> 0.636
-Confusion Matrix:
- [[ 71   1   8   3   2   5   8]
- [  4 130   3   2   7   1   5]
- [ 21  16 109  30  57  25  29]
- [  6   1  13 110  13   3  17]
- [  1  11   3   0  72   0   2]
- [  3   0   2   6   0  43   3]
- [  8   3  11   8   7  16 101]]
-Node Classification on random seed  2662 -> 0.653
-Confusion Matrix:
- [[ 73   4  10   3   6  14   8]
- [  4 132   8   6   3   2   6]
- [ 17  11 166  20  29  21  36]
- [  7   3  17  92   5  12  14]
- [  1   6   3   3  67   1   4]
- [  1   1   2   1   0  50   6]
- [ 11   4   8   4   9  16  73]]
-Node Classification on random seed  2663 -> 0.611
-Confusion Matrix:
- [[ 59   8   6   0   6  11  10]
- [  3 120   6   1   6   2   3]
- [ 34  27 166  27  22  10  31]
- [ 11   6  18  89   6  11  15]
- [  2   6   8   0  59   0   4]
- [  6   3   4   6   0  41   9]
- [ 12   6  17   2  11  13  77]]
-Node Classification on random seed  2664 -> 0.593
-Confusion Matrix:
- [[ 78   2   2   0   0  10  16]
- [  6 127   5   3   3   3   7]
- [ 20  20 139  51  30  22  34]
- [ 15   4  21  90   5  12  12]
- [  0   4   4   3  45   2   2]
- [  6   1   5   0   1  45   7]
- [ 13   5  16  11   7  17  69]]
-Node Classification on random seed  2665 -> 0.598
-Confusion Matrix:
- [[ 55   7   6  12   2  10  17]
- [  7 128   5   0  10   3   3]
- [ 30  27 154  40  11  29  18]
- [ 16   6   8 121   6   8  11]
- [  0   3   1   3  49   5   3]
- [  6   0   2   3   0  33   8]
- [ 16   4  11  26  10   9  58]]
-Node Classification on random seed  2666 -> 0.598
-Confusion Matrix:
- [[ 80   1   6   4   5  12   8]
- [  4 120  10   3  10   3  11]
- [ 30  24 130  24  23  34  41]
- [ 12   7   7  95  11   9  10]
- [  2   7   3   1  56   0   3]
- [  7   0   5   0   1  36   7]
- [ 16   1   8   1   9  22  81]]
-Node Classification on random seed  2667 -> 0.639
-Confusion Matrix:
- [[ 59   7   6   3   8   6   7]
- [  9 126   2   3  13   1  13]
- [ 29  13 181  24  37  11  37]
- [  8   4  18 116   5   3   5]
- [  1   3   4   0  62   2   2]
- [  6   1   0   0   3  34   7]
- [ 20   7   5  10   5  13  61]]
-Node Classification on random seed  2668 -> 0.598
-Confusion Matrix:
- [[ 64   2   1   3   2   6  18]
- [  5 147   7   4   3   1   7]
- [ 26  14 111  48  28  22  49]
- [ 16   3  17  97  11   4  13]
- [  1  10   6   1  68   0   2]
- [  5   0   2   1   1  41   4]
- [ 15   1  13   6   7  17  70]]
-Node Classification on random seed  2669 -> 0.614
-Confusion Matrix:
- [[ 67   4   4   4   2  18  18]
- [ 12 128   3   3  10   0   3]
- [ 25  21 129  27  21  29  52]
- [  8   3  12 108   2   0  19]
- [  4   2   4   2  54   1   0]
- [  4   0   1   2   0  46  12]
- [ 15   3   8   4   7  17  82]]
-Node Classification on random seed  2670 -> 0.595
-Confusion Matrix:
- [[ 69   2   1   4   4   7  14]
- [ 10 124  16   5  13   5   7]
- [ 32  31 129  27  32  11  34]
- [  9   5  12 103   3   8  19]
- [  2   6   3   6  61   0   3]
- [  4   0   2   2   5  38   9]
- [ 15   8   6   5   6  12  71]]
-Node Classification on random seed  2671 -> 0.662
-Confusion Matrix:
- [[ 89   1   1   4   3   7  16]
- [  2 118   7   0   9   0  10]
- [ 32  11 157  22  14  28  24]
- [  6   3  32 107   1   3  15]
- [  2   3   5   0  60   0   3]
- [  5   1   3   6   1  53   4]
- [ 13   5  10   3   3  20  78]]
-Node Classification on random seed  2672 -> 0.653
-Confusion Matrix:
- [[ 84   4   3   3   1   5  12]
- [  1 121   2   7   7   2   1]
- [  8  16 154  25  43  32  39]
- [  5   2  14 117  11   5  14]
- [  4   4   5   2  61   0   2]
- [ 10   0   0   1   0  39   2]
- [ 11   9   6   7  11  11  77]]
-Node Classification on random seed  2673 -> 0.591
-Confusion Matrix:
- [[ 67   4   5   2   7   6   9]
- [  1 127   6   2  11   1   8]
- [ 25  27 113  21  51  17  54]
- [  6   5  15  84  16  15  12]
- [  1   5   2   2  69   3   6]
- [  2   1   3   2   1  48   6]
- [ 12   3   8   7  11   8  83]]
-Node Classification on random seed  2674 -> 0.634
-Confusion Matrix:
- [[ 63   1   5   8   2   9   4]
- [  2 132  10   1   6   2   3]
- [ 30  13 146  23  42  24  42]
- [  7   4  24 112   5   7  16]
- [  2   4   3   0  57   2   1]
- [  5   0   2   1   0  48   3]
- [ 17   2   6   8   5  15  76]]
-Node Classification on random seed  2675 -> 0.612
-Confusion Matrix:
- [[ 68   6   3   3   6  13   6]
- [  5 127   5   2   9   4   0]
- [ 41  24 139  36  23  26  35]
- [  9   4  17 102   3   4  12]
- [  5   5   2   1  55   1   2]
- [  2   1   0   2   2  55   6]
- [ 25   6  12   4   7   9  66]]
-Node Classification on random seed  2676 -> 0.611
-Confusion Matrix:
- [[ 79   1   0   7   2  13  10]
- [  5 118   6   1   9   5  14]
- [ 20  12 125  52  46  26  38]
- [  7   0  13 112   7   3   9]
- [  1   4   2   2  59   3   0]
- [ 11   1   5   1   0  47   1]
- [ 23   1   8   5   8   7  71]]
-Node Classification on random seed  2677 -> 0.624
-Confusion Matrix:
- [[ 75   5   2   3   5   3   3]
- [ 10 114   4   4  16   1   4]
- [ 32  23 142  46  18  23  31]
- [  4   4  17 116   0   7  15]
- [  4   5   4   2  60   1   5]
- [  4   4   3   0   1  42   6]
- [ 15   5   8   9   7  13  75]]
-Node Classification on random seed  2678 -> 0.582
-Confusion Matrix:
- [[ 55   1  13   3   2  14   1]
- [  5 134   3   5   8   6   1]
- [ 15  28 132  48  32  25  43]
- [  7   5  25  83   5  15   5]
- [  0  10   6   1  60   0   5]
- [  4   0   2   3   2  49   3]
- [  3   5  17  14  10  18  69]]
-Node Classification on random seed  2679 -> 0.615
-Confusion Matrix:
- [[ 77   4   6   3   3   5  10]
- [  5 116   6   9   5   4   6]
- [ 24  27 138  53  13  20  33]
- [ 17   2  13 100   6   7   7]
- [  5   8   1   3  65   0   1]
- [  8   2   3   4   2  52   6]
- [ 21   5  11   9   3   5  67]]
-Node Classification on random seed  2680 -> 0.655
-Confusion Matrix:
- [[ 71   2   0   3   5  16   7]
- [  1 136   4   1   7   9   3]
- [ 29  36 145  30  19  18  26]
- [ 10   4   8 124   8   8   8]
- [  2   6   4   1  54   2   3]
- [  6   2   2   4   0  41   2]
- [  7   4  13  12   5   8  84]]
-Node Classification on random seed  2681 -> 0.59
-Confusion Matrix:
- [[ 66   4   6   6   0   7  12]
- [  8 120   5   2   6  10   8]
- [ 26  14 162  21  18  28  51]
- [ 23   7  17  80   4   5  15]
- [  4   5   7   3  47   1   3]
- [ 11   0   3   1   0  52   1]
- [ 11   6  10   8   8  25  63]]
-Node Classification on random seed  2682 -> 0.596
-Confusion Matrix:
- [[ 65   4   3   1   3   7  30]
- [  3 132   4   3   5   3   3]
- [ 23  15 119  22  51  27  50]
- [ 20   3  14  98   2   5  18]
- [  3   7   0   3  64   2   7]
- [  5   1   1   2   1  36   2]
- [ 15   2  11   6   7  10  82]]
-Node Classification on random seed  2683 -> 0.588
-Confusion Matrix:
- [[ 55   1   2   6   4  10  21]
- [  2 138   3   2  11   4   4]
- [ 28  36 119  46  33  23  26]
- [ 20   2  10  96   4  10  17]
- [  1   6   3   2  58   0   6]
- [  3   1   2   5   6  51   2]
- [ 13   2   5   4  11  15  71]]
-Node Classification on random seed  2684 -> 0.638
-Confusion Matrix:
- [[ 80   4   2   2   6   7  10]
- [  7 128   8   2   9   3   8]
- [ 42  17 133  31  20  14  51]
- [ 13   4  10 112   6   6   8]
- [  1   2   2   0  59   0   4]
- [  2   1   3   3   1  40   1]
- [ 16   4   6   9   6  11  86]]
-Node Classification on random seed  2685 -> 0.615
-Confusion Matrix:
- [[ 68   8   1   3   4  13  15]
- [  3 130   3   1   5   8   7]
- [ 22  25 129  34  15  32  47]
- [ 10   7  18 100   5  13  10]
- [  1   8   1   0  59   1   7]
- [  4   1   1   2   0  43   3]
- [  7   3   5   7   7  18  86]]
-Node Classification on random seed  2686 -> 0.601
-Confusion Matrix:
- [[ 77   6   1   6   7   3  16]
- [  2 121   5   2   6   1   5]
- [ 36  22 127  28  49  19  33]
- [  7   5  23 109   8   5  10]
- [  1   6   3   3  61   0   6]
- [  6   0   1   0   2  36  10]
- [ 19   2   7   6  10  12  70]]
-Node Classification on random seed  2687 -> 0.636
-Confusion Matrix:
- [[ 61   0   1   4   8  15  14]
- [  3 127   4   4  15   7   7]
- [ 14  19 151  25  30  26  31]
- [ 17   4  11 112   6   6  12]
- [  1   4   3   1  62   2   3]
- [  8   2   2   0   1  53   1]
- [  5   3  11   5   6  23  70]]
-Node Classification on random seed  2688 -> 0.657
-Confusion Matrix:
- [[ 69  13   7   3   4   6   8]
- [  3 131   8   5   4   0   2]
- [ 22  27 168  29  13  20  24]
- [ 12  12  18 102   1   3   6]
- [  1   9   7   0  63   1   3]
- [  4   3   2   3   1  45   3]
- [ 19   6  14   7   3   7  79]]
-Node Classification on random seed  2689 -> 0.629
-Confusion Matrix:
- [[ 64   2   3   3   6  13  11]
- [  1 126   3   4   7   6   5]
- [ 17  27 138  39  26  16  47]
- [  5   4  11 125   3  10   8]
- [  1   8   2   3  56   0   4]
- [  2   2   4   3   0  51   7]
- [  3   4   7  16  11  17  69]]
-Node Classification on random seed  2690 -> 0.61
-Confusion Matrix:
- [[ 71   2   6   5   2  10   8]
- [  2 124   5   4   6   2  12]
- [ 21  48 136  31  20  14  44]
- [ 27   6  16  90   3   4  21]
- [  0   4   3   1  63   3   4]
- [  3   2   2   3   1  42   6]
- [  7   8   5   4   4  11  84]]
-Node Classification on random seed  2691 -> 0.579
-Confusion Matrix:
- [[ 78   3   5   6  10  13   6]
- [  1 133   6   3   3   1   2]
- [ 33  10 128  31  42  27  43]
- [ 13   4  32  78   5   2  16]
- [  1   8   2   0  56   3   2]
- [  6   3   1   4   2  34   4]
- [ 23   4  12   6   8  15  72]]
-Node Classification on random seed  2692 -> 0.583
-Confusion Matrix:
- [[ 67   7   6   4   5  18   2]
- [  6 132   6   2   4   5   5]
- [ 19  34 101  27  65  18  29]
- [  7   2  16 101   8   6   9]
- [  0   7   1   3  65   4   6]
- [  6   1   5   3   1  43   4]
- [ 14   2   4  15  15  16  74]]
-Node Classification on random seed  2693 -> 0.63
-Confusion Matrix:
- [[ 68   1   2   6   3  10   7]
- [  8 113   3   5   5   3  13]
- [ 15  15 173  23  31  21  50]
- [  8   3  20 103   6   7  13]
- [  1   3   2   2  60   3   1]
- [  5   2   6   1   0  47   2]
- [ 17   2   3  16   5  21  66]]
-Node Classification on random seed  2694 -> 0.64
-Confusion Matrix:
- [[ 75   5   7   9   1  14   5]
- [  9 131   5   0   4   3   1]
- [ 23  33 157  10  13  32  33]
- [  9   3  30 105   2  15   7]
- [  2   5   6   2  59   1   1]
- [  3   3   6   0   0  45   6]
- [  9   3  15   3  10  12  68]]
-Node Classification on random seed  2695 -> 0.627
-Confusion Matrix:
- [[ 66   1   2   5  13  12   7]
- [ 13 109  11   0  11   4   4]
- [ 33  20 153  28  26  29  18]
- [  6   3  13 116   5   6  15]
- [  2   6   3   0  67   0   1]
- [  5   1   3   1   3  50   2]
- [ 20   3  14   6   1  17  66]]
-Node Classification on random seed  2696 -> 0.592
-Confusion Matrix:
- [[ 66   1   5   0  11  18   4]
- [  4 113   7   1  12   5   3]
- [ 34  18 113  31  41  29  34]
- [ 17   2   8 116  12   7  14]
- [  6   6   3   0  49   5   1]
- [  3   1   1   0   2  58   4]
- [  6   3  10  10   8  21  77]]
-Node Classification on random seed  2697 -> 0.641
-Confusion Matrix:
- [[ 81   1   2   5   8   9   7]
- [  2 116   7   2   8   3   6]
- [ 28  26 161  26  22  25  31]
- [ 14   3  18 107   7   1   8]
- [  3   8   1   0  61   1   1]
- [  8   2   5   1   1  48   6]
- [ 14   4   7   9   5  14  67]]
-Node Classification on random seed  2698 -> 0.593
-Confusion Matrix:
- [[ 64   5   2   3   8  12  15]
- [  2 121  17   2   6   3   3]
- [  7  29 134  37  33  28  33]
- [  7   1  15 100   4   6  29]
- [  3  12   2   3  51   3   3]
- [  5   1   3   1   1  45   7]
- [  8   6   2   3  20  17  78]]
-Node Classification on random seed  2699 -> 0.624
-Confusion Matrix:
- [[ 66   0   2  11   2   9   4]
- [  6 132   5   2   8   1   1]
- [ 14  24 161  28  39  26  28]
- [ 19   6  21  83  14   8  11]
- [  0   6   3   0  63   2   2]
- [  7   0   1   1   1  45   3]
- [ 17   3  12   9   5  15  74]]
-Node Classification on random seed  2700 -> 0.594
-Confusion Matrix:
- [[ 74   7   1  10   1  14   5]
- [ 11 115  18   2   8   4   2]
- [ 27  25 141  45  18  24  31]
- [ 11   5  18  91   4   9  21]
- [  0   3   5   0  60   1   2]
- [  6   2   2   2   0  51   2]
- [ 14   5   6   2   7  26  62]]
-Node Classification on random seed  2701 -> 0.611
-Confusion Matrix:
- [[ 76   4   7   7   2  15   3]
- [  2 130   8   0  11   4   1]
- [ 34  17 139  41  29  16  44]
- [  6   5  16 102   0  11  12]
- [  3   7   3   4  52   1   1]
- [  5   0   4   4   0  45   5]
- [ 15   0   9  14   4  15  67]]
-Node Classification on random seed  2702 -> 0.61
-Confusion Matrix:
- [[ 65   4   7   3   3  16  10]
- [  3 132   5   3  18   2   5]
- [ 19  17 148  27  33  29  31]
- [  7   2  15 104   6  10  17]
- [  4   1   2   1  64   2   4]
- [  9   0   1   1   1  39   8]
- [ 15   3   8   2   8  28  58]]
-Node Classification on random seed  2703 -> 0.604
-Confusion Matrix:
- [[ 70   2   0   7   4  13   9]
- [  0 100   5   0  28   1   3]
- [ 30  24 141  27  23  42  33]
- [  8   4  13 104   5  11  16]
- [  4   6   4   1  64   1   1]
- [  6   2   1   0   1  50   9]
- [  8   7   6   7   9  15  75]]
-Node Classification on random seed  2704 -> 0.611
-Confusion Matrix:
- [[ 59   7  16   6  11   8   4]
- [  2 125   4   0   7   4   2]
- [ 20  23 137  34  16  36  54]
- [ 13   0   9 103   3  14  13]
- [  1   5   3   1  62   4   1]
- [  5   1   5   1   0  47   3]
- [ 13   3   6  10   8  13  78]]
-Node Classification on random seed  2705 -> 0.646
-Confusion Matrix:
- [[ 60   3   4  17   2   8   9]
- [  7 120  11   2   7   0   8]
- [ 25  31 158  30  20  13  39]
- [  3   6  17 111   1   2  13]
- [  5   5   3   0  68   0   4]
- [  6   2   0   2   2  39   6]
- [ 15   3   6   7   4   6  90]]
-Node Classification on random seed  2706 -> 0.621
-Confusion Matrix:
- [[ 92   1   4   5   4  14   5]
- [  5 113   9   5  15   5   5]
- [ 14  23 149  24  21  44  35]
- [ 11   5  17 103   5   9   5]
- [  2   4   1   4  56   3   0]
- [  1   0   1   1   0  49  17]
- [  5   2   7   9   4  28  59]]
-Node Classification on random seed  2707 -> 0.585
-Confusion Matrix:
- [[ 54   4  11   8   2  16  11]
- [  7 122   8   1   6   3   1]
- [ 25  18 127  27  39  50  23]
- [ 14   2  26 104   4   3  16]
- [  5   3   5   3  55   2   3]
- [  2   2   0   3   1  39  15]
- [ 13   4  17   0   3   9  84]]
-Node Classification on random seed  2708 -> 0.583
-Confusion Matrix:
- [[ 57   2  14   3   4  14   9]
- [  2 119   3   4  11  11   5]
- [ 10  25 115  45  28  43  32]
- [  9   3  12 109   3   6  27]
- [  2   4   1   4  59   2   4]
- [  6   1   4   1   0  40  17]
- [  9   1   5   3   8  20  84]]
-Node Classification on random seed  2709 -> 0.621
-Confusion Matrix:
- [[ 57   2   0   0   5  26   7]
- [  9 124   6   1   6   4   5]
- [ 12  21 142  38  21  26  49]
- [  6   6  23 112   4   8  10]
- [  0   4   5   2  55   0   2]
- [  6   0   2   3   2  51   4]
- [  6   3   2  10   5  28  80]]
-Node Classification on random seed  2710 -> 0.61
-Confusion Matrix:
- [[ 74   1  12   9   3  12   7]
- [  1 147   5   0   6   2   5]
- [ 25  12 101  40  55  28  30]
- [ 13   2  10 125   5  14   8]
- [  1   4   4   0  60   2   4]
- [  5   0   4   1   1  47   2]
- [  9   6  12   6   5  19  56]]
-Node Classification on random seed  2711 -> 0.586
-Confusion Matrix:
- [[ 58   3   1   3   1  12  14]
- [  3 115   8   0  18   4  11]
- [ 30  14 121  30  37  24  39]
- [ 10   7  17  96   9  10  10]
- [  0   2   4   0  72   0   6]
- [  5   1   0   2   1  44   8]
- [  8   1  11  16  18  16  80]]
-Node Classification on random seed  2712 -> 0.645
-Confusion Matrix:
- [[ 74  10   2  11   3   9   6]
- [  7 146   4   4   8   2   3]
- [ 33  16 146  23  34  15  29]
- [  9   1  16 105   4   9   7]
- [  2   6   2   2  61   1   4]
- [  5   3   0   2   4  51   6]
- [ 17   3   7   5   5  16  62]]
-Node Classification on random seed  2713 -> 0.56
-Confusion Matrix:
- [[ 57   2  12   5   7   9   8]
- [  4 123   3   0  16   3   5]
- [ 35  30 117  27  36  15  49]
- [ 12   1  13  90  22   9  24]
- [  0   4   1   0  64   0   2]
- [  7   2   3   0   9  33   4]
- [ 12   2  20   2  14  11  76]]
-Node Classification on random seed  2714 -> 0.608
-Confusion Matrix:
- [[ 71   3   1   5   2  14   6]
- [  2 120  13   1   2   1   2]
- [ 45  22 145  54  25  27  12]
- [ 22   5   3 106   2   3   8]
- [  6  10   4   4  58   1   3]
- [  4   1   1  10   1  44   2]
- [ 11   8   9  13   9  15  64]]
-Node Classification on random seed  2715 -> 0.622
-Confusion Matrix:
- [[ 70   2   9   3   9  10   8]
- [  4 144   5   3   7   5   1]
- [ 14  31 127  39  26  18  48]
- [  5   3   8 107  12   4  13]
- [  0   6   4   2  69   0   1]
- [  9   1   3   1   0  46  10]
- [ 13   2   7  13  10   9  59]]
-Node Classification on random seed  2716 -> 0.601
-Confusion Matrix:
- [[ 55   2   3   4   7  12  22]
- [  2 134   5   1   8   6   9]
- [ 36  19 117  49  26  32  27]
- [ 10   4   7 104   3  10  16]
- [  0   3   3   2  72   0   2]
- [  2   1   4   0   0  40  10]
- [ 18   1  11   1  10  11  79]]
-Node Classification on random seed  2717 -> 0.582
-Confusion Matrix:
- [[ 66   2   6   2   0  19  10]
- [  1 107  18   2  17   5   5]
- [ 18  23 130  23  52  21  38]
- [ 14   2  13  98  11   5  14]
- [  0   6   2   1  65   1   4]
- [  4   4   3   2   0  43   6]
- [  5   7  10   8   6  28  73]]
-Node Classification on random seed  2718 -> 0.636
-Confusion Matrix:
- [[ 67   4   4   3   7  15  17]
- [  2 133   9   2   4   1   8]
- [ 31  18 163  26  24  26  28]
- [ 14  10  11  92   2   9  12]
- [  3   5   3   4  61   0   1]
- [ 11   0   2   0   0  50   6]
- [ 14   4   1   7   4  12  70]]
-Node Classification on random seed  2719 -> 0.625
-Confusion Matrix:
- [[ 75   3   5   4   4  14   8]
- [  3 123  10   2   6   2   5]
- [ 23  14 159  21  23  32  40]
- [ 14   3  18 100   1  14  19]
- [  3   6   4   1  59   1   1]
- [  8   1   1   4   1  35  11]
- [ 19   2   5   3   7   9  74]]
-Node Classification on random seed  2720 -> 0.635
-Confusion Matrix:
- [[ 71   7   2   5   5   5  10]
- [  8 125   4   2  15   2   3]
- [ 20  20 149  30  35  25  41]
- [  6   3  17  97   3   2  19]
- [  0   7   3   0  62   0   2]
- [  3   1   3   3   0  46  10]
- [ 13   2   6   7   6  10  85]]
-Node Classification on random seed  2721 -> 0.644
-Confusion Matrix:
- [[ 79   0   8   7   1   9   4]
- [  3 138   6   8   5   1   0]
- [  8  24 144  42  33  21  42]
- [  0   0  22 117   3   5  15]
- [  1  11   5   1  45   0   3]
- [  6   2   0   1   0  39  13]
- [  6   2   6  12  11   9  82]]
-Node Classification on random seed  2722 -> 0.594
-Confusion Matrix:
- [[ 63   2  11   2   1  13  12]
- [  5 141   7   1   7  10   3]
- [ 28  24 139  16  19  24  49]
- [ 15   3  33  77   4   2  24]
- [  0   2   7   2  57   3   1]
- [  9   1   5   0   2  45  14]
- [ 15   3   5   2   5  15  72]]
-Node Classification on random seed  2723 -> 0.557
-Confusion Matrix:
- [[ 74   3   4   7   6  10  10]
- [ 10  99   7   2  11   1   7]
- [ 30  14 129  53  17  21  54]
- [ 14   3  14  94   7   6  14]
- [  0   9   6   2  60   1   5]
- [  2   1   6   9   6  32   4]
- [  6   4  28   5   8  16  69]]
-Node Classification on random seed  2724 -> 0.611
-Confusion Matrix:
- [[ 72   1   6   8   5   8   5]
- [  4 133   6   2   0   5   5]
- [ 21  21 143  45  29  19  41]
- [ 13   3  13  87  11   8  23]
- [  2   4   1   3  60   2   2]
- [  4   1   3   3   0  39   5]
- [ 14   4  11   5   5  18  77]]
-Node Classification on random seed  2725 -> 0.633
-Confusion Matrix:
- [[ 59   0   9   9   4  12   4]
- [  4 144  10   4   3   3   4]
- [ 28  25 141  20  16  21  57]
- [ 10   5   7 114   2   6   9]
- [  0   7   5   2  58   5   2]
- [  1   0   4   3   1  46   9]
- [ 12   6  10   3   9  16  71]]
-Node Classification on random seed  2726 -> 0.577
-Confusion Matrix:
- [[ 60   6   7  11   6   7  16]
- [  5 132   6   5  11   0   5]
- [ 21  27 103  47  38  23  50]
- [ 14   5  13 105   4   6  19]
- [  0   8   4   0  62   0   2]
- [  2   0   2   6   2  34   5]
- [  4   4   7  12   4   9  81]]
-Node Classification on random seed  2727 -> 0.597
-Confusion Matrix:
- [[ 64   5   8  11   3  10   6]
- [  6 124   7   1   1   9   4]
- [ 32  22 131  45  42  22  19]
- [  9   7  24  96   5   7  12]
- [  1   5   2   1  61   1   1]
- [  7   1   7   1   0  58   5]
- [ 15   1  17   1   8  12  63]]
-Node Classification on random seed  2728 -> 0.618
-Confusion Matrix:
- [[ 82   5   0   3   2  10   6]
- [  3 124   9   3  11   3   3]
- [ 23  12 144  32  35  11  48]
- [ 10   3  15 100   5   3  26]
- [  1   8   3   2  56   3   5]
- [  9   7   3   4   0  43   2]
- [  9   3   6  10  12  14  69]]
-Node Classification on random seed  2729 -> 0.612
-Confusion Matrix:
- [[ 72   5   3   2   6  15   9]
- [  9 107   4   2  10   5   7]
- [ 24  13 150  27  27  32  40]
- [  7   3  16 112   6   8  15]
- [  2   5   7   1  53   0   0]
- [  6   1   4   2   1  48   5]
- [ 21   3  11   4   8  12  70]]
-Node Classification on random seed  2730 -> 0.61
-Confusion Matrix:
- [[ 83   1   2  11   2   8  10]
- [  6 132   4   2   7   2   3]
- [ 20  24 133  57  24  12  36]
- [ 18   3  13 107   6   8   4]
- [  3   8   2   2  56   2   2]
- [  3   2   1   1   2  41   4]
- [ 17   5   8  18   9  18  58]]
-Node Classification on random seed  2731 -> 0.586
-Confusion Matrix:
- [[ 68   4  10  11   6   9   7]
- [  4 124   7   6   2   0  10]
- [ 32  28 125  49  26  30  22]
- [ 15   5  18  92   9   1   9]
- [  1  10   2   1  63   1   1]
- [  4   0   4   3   4  41  12]
- [  8   3  13  11   9   7  73]]
-Node Classification on random seed  2732 -> 0.631
-Confusion Matrix:
- [[ 85   0   1   2   6   6  10]
- [  5 121   4   2  13   0   8]
- [ 33  14 144  44  28  20  46]
- [ 19   1  12 102   8   0  12]
- [  0   5   2   0  62   0   3]
- [  3   2   4   1   0  39   5]
- [ 13   4   6   6   6  15  78]]
-Node Classification on random seed  2733 -> 0.627
-Confusion Matrix:
- [[ 71   1   1   6  12  21   3]
- [  5 137   2   4   7   0   3]
- [ 20  30 148  35  32  25  35]
- [ 19   3   8  83   4   7  24]
- [  1   6   1   0  66   0   3]
- [  8   0   0   0   1  40   6]
- [ 11   4   7   4   5   9  82]]
-Node Classification on random seed  2734 -> 0.591
-Confusion Matrix:
- [[ 85   2  14   4   4  17   9]
- [  1 127   6   2   1   2   9]
- [ 26  25 121  36  26  29  27]
- [ 11  12  15  90   6   4  19]
- [  1   5   3   2  56   1   4]
- [ 24   0   3   2   0  40   2]
- [ 23   5   6   2  10   9  72]]
-Node Classification on random seed  2735 -> 0.645
-Confusion Matrix:
- [[ 67   2   1   6   3  18   4]
- [  1 145   5   0   1   3   2]
- [ 31  28 131  39  30  26  20]
- [ 16   8   8  99   4  10  12]
- [  1   8   2   1  67   0   1]
- [  7   2   2   0   1  49   7]
- [  6   5   4   7   7  16  87]]
-Node Classification on random seed  2736 -> 0.621
-Confusion Matrix:
- [[ 70   0   1   2   8  11  14]
- [ 11 114   1   1  13  12   7]
- [ 27  14 159  33  30  10  39]
- [ 15   4  15 108  13   5   4]
- [  0   2   2   2  54   1   5]
- [ 13   1   0   5   0  44   4]
- [ 12   1   6  14   7  14  72]]
-Node Classification on random seed  2737 -> 0.591
-Confusion Matrix:
- [[ 72   1   4   7   4  13   8]
- [  6 126   5   4   6   8   3]
- [ 21  30 109  40  47  25  51]
- [  4   2  11 105   6  11  19]
- [  0   3   3   1  51   1   4]
- [  4   2   2   0   1  47   1]
- [  9   3   5   4  10  20  81]]
-Node Classification on random seed  2738 -> 0.649
-Confusion Matrix:
- [[ 70   3   2   3   1  21  11]
- [  4 130   5   6   3   1   0]
- [ 18  22 156  43  28  17  33]
- [  6   2  16 109   5   4   6]
- [  0   7   4   2  57   3   4]
- [  4   1   9   3   0  51   4]
- [  5   2  11   5   7  20  76]]
-Node Classification on random seed  2739 -> 0.619
-Confusion Matrix:
- [[ 64   4   1   6   6  18   8]
- [  2 137   4   4   9   0   5]
- [ 14  33 128  48  26  17  35]
- [  9   2  21  84  11   5  20]
- [  4   1   2   3  71   1   4]
- [  2   2   2   1   0  54   2]
- [  5   1   9   7  11  16  81]]
-Node Classification on random seed  2740 -> 0.618
-Confusion Matrix:
- [[ 70   4   2   0   4  17  20]
- [  0 138   9   5  10   6   3]
- [ 12  23 132  37  48  30  27]
- [  3   5  10  92   3   8   8]
- [  1   3   2   0  76   1   3]
- [  3   2   2   1   4  41  11]
- [ 11   4   8   6   7  19  69]]
-Node Classification on random seed  2741 -> 0.589
-Confusion Matrix:
- [[ 78   5   2   5   7   6  10]
- [  8 107   6   1  24   1   0]
- [ 21  19 110  47  50  28  29]
- [ 17   2  10  95   7   5  11]
- [  1   4   3   2  68   1   1]
- [  3   0   7   3   1  39   7]
- [ 15   4   4   7  10  17  92]]
-Node Classification on random seed  2742 -> 0.64
-Confusion Matrix:
- [[ 74   1   3   2   5  11  15]
- [  3 123   6   0   6   8   3]
- [ 32  13 141  46  20  21  35]
- [ 12   3   4 101   3   6  23]
- [  0   9   2   6  59   1   2]
- [  3   3   0   1   0  51   6]
- [  6   4   9   2  10  15  91]]
-Node Classification on random seed  2743 -> 0.573
-Confusion Matrix:
- [[ 73   3   5   5  10  15   9]
- [  2 117   9   2   5   6   7]
- [ 37  20 131  44  22  21  40]
- [ 12   4  24  75  11  12   8]
- [  2   9   1   1  59   2   5]
- [  4   0   3   2   0  45   7]
- [ 18   1  19   4   2  14  73]]
-Node Classification on random seed  2744 -> 0.642
-Confusion Matrix:
- [[ 77   6   1   3  10   6   6]
- [  6 125   7   0  14   5   4]
- [ 23  19 154  39  19  26  34]
- [ 16   1   7 106   5   5  13]
- [  0   4   3   3  60   1   4]
- [ 10   0   6   2   2  44   5]
- [  9   1  11  10   5   7  76]]
-Node Classification on random seed  2745 -> 0.588
-Confusion Matrix:
- [[ 63   2   3   3   6  15   6]
- [  5 125  10   5   9   6   4]
- [ 24  27 123  43  17  29  40]
- [ 10   3   6  93  13   8  20]
- [  1   5   5   1  65   1   9]
- [  5   3   0   1   1  48   2]
- [ 22   5  11   4  11  11  71]]
-Node Classification on random seed  2746 -> 0.606
-Confusion Matrix:
- [[ 57   2   5   4   6  21  16]
- [  2 110  14   2  13   0   3]
- [ 22  16 161  24  26  18  46]
- [ 19   2  14 101   4   4  23]
- [  1   4   9   2  61   1   5]
- [ 12   1   1   0   0  42   8]
- [  6   3   7   8   3  17  74]]
-Node Classification on random seed  2747 -> 0.609
-Confusion Matrix:
- [[ 68   4  13  10   0   8   8]
- [  5 121   5   3   5   1  17]
- [ 20  25 135  24  48  16  46]
- [  4   3  15 102  17   8   6]
- [  0   5   5   0  53   0   5]
- [  6   0   1   1   2  47   6]
- [ 18   3   9  11   4   4  83]]
-Node Classification on random seed  2748 -> 0.632
-Confusion Matrix:
- [[ 67   1   5   2   6  13   4]
- [  2 115   6   1  10   2   6]
- [ 29  36 152  26  21  25  34]
- [  3   2  18 104   5   7   7]
- [  0   8   9   3  62   0   2]
- [  7   2   4   2   1  48   5]
- [ 12   4   9   4   8  17  84]]
-Node Classification on random seed  2749 -> 0.615
-Confusion Matrix:
- [[ 74   3   1   4   9  15   6]
- [  1 122   3   4   4   2   1]
- [ 20  24 155  47  32  21  34]
- [ 10   3  19  93   5   9   8]
- [  2   7   6   1  57   1   2]
- [  7   1   2   1   1  41   8]
- [ 18   5   6   6   8  18  73]]
-Node Classification on random seed  2750 -> 0.613
-Confusion Matrix:
- [[ 79   1   9   1   3  11  11]
- [  5 129   9   3   8   0  11]
- [ 11  23 144  37  25  20  49]
- [ 15   6  15  93   4   6   8]
- [  1   8   5   2  63   0   2]
- [ 10   0   0   0   1  43   9]
- [ 19   1  11   5   7  15  62]]
-Node Classification on random seed  2751 -> 0.607
-Confusion Matrix:
- [[ 68   0   2   9   6  16   6]
- [  6 122   6   5   5   5   9]
- [ 12  19 127  53  24  28  42]
- [  4   6  18 111   1  10   3]
- [  0   6   4   2  70   1   4]
- [  3   1   3   4   1  42   5]
- [  5   3  13  16   9  18  67]]
-Node Classification on random seed  2752 -> 0.639
-Confusion Matrix:
- [[ 78   2  13   8   3   8   1]
- [  6 128   3   2  12   2   1]
- [ 20  24 149  38  37  18  32]
- [  8   0  31 113   3   4   8]
- [  2   6   6   0  65   2   3]
- [  3   0   0   5   0  42   2]
- [ 12   4   5  11   3  13  64]]
-Node Classification on random seed  2753 -> 0.653
-Confusion Matrix:
- [[ 69   2   3   2   2   5  11]
- [  3 139   1   1   6   1   5]
- [ 12  29 175  29  26   8  36]
- [ 23   4  15  97   7   6   8]
- [  0  10   7   2  54   0   4]
- [  9   4   1   0   0  44   5]
- [ 17   5  14   1   6  17  75]]
-Node Classification on random seed  2754 -> 0.572
-Confusion Matrix:
- [[ 76   7   5   1   3  12  16]
- [  3 127   5   2   5   2   2]
- [ 22  26 116  35  28  35  49]
- [ 14   2  18  96   7   9  13]
- [  2   8   4   2  55   0   5]
- [  4   3   3   1   3  55   2]
- [ 13   4  10   9  20  14  47]]
-Node Classification on random seed  2755 -> 0.626
-Confusion Matrix:
- [[ 77   3   5   1   1  13   4]
- [  3 147   5   8   2   3   4]
- [ 18  13 125  54  38  29  32]
- [  4   9  18  93  12   7  14]
- [  1   8   1   3  59   4   5]
- [  4   0   2   2   0  51   3]
- [  7   3   5   5   8  13  74]]
-Node Classification on random seed  2756 -> 0.594
-Confusion Matrix:
- [[ 63   5   5  10   5  11  14]
- [  6 106   9   4  16   5   3]
- [ 25  22 150  39  21  36  32]
- [ 12   5  11 108   6   7   7]
- [  1   2   3   1  64   1   2]
- [  6   0   2   1   0  38   5]
- [ 19   3  11  13   7  13  65]]
-Node Classification on random seed  2757 -> 0.613
-Confusion Matrix:
- [[ 61   3   4   1   2   9  11]
- [ 10 121  11   1   8   1   3]
- [ 28  29 161  23  29  29  34]
- [  9   2  10 112  10   6  11]
- [  2   6   2   1  57   1   1]
- [  8   1   2   6   1  44   7]
- [ 16   3  15   4  11  16  57]]
-Node Classification on random seed  2758 -> 0.613
-Confusion Matrix:
- [[ 46   1   2   5   7  10  33]
- [  7 138   7   9   4   2   8]
- [ 38  10 150  27  17  23  48]
- [ 16   2  11 103  10   9   5]
- [  2  10   4   2  63   1   1]
- [  5   1   0   2   0  43   7]
- [  6   4   6   3   4  18  70]]
-Node Classification on random seed  2759 -> 0.618
-Confusion Matrix:
- [[ 66   0   3   3   2  23   6]
- [ 11 110   7   1  16   4   7]
- [ 28  18 139  16  35  19  58]
- [ 11   3   6  97  12  10  22]
- [  1   2   0   0  74   4   1]
- [  3   0   3   0   3  50   6]
- [  6   0  12   2   6  12  82]]
-Node Classification on random seed  2760 -> 0.573
-Confusion Matrix:
- [[ 47   0   4  14   5  13  16]
- [  6 131   6   5   4   3   6]
- [ 13  23 110  60  54  23  52]
- [  5   3   8 101   4   5  18]
- [  1   6   1   0  65   0   1]
- [  8   1   5   1   1  48   4]
- [  7   2  14   3   7  15  71]]
-Node Classification on random seed  2761 -> 0.663
-Confusion Matrix:
- [[ 89   2   1   5   1   7   6]
- [  6 118   3   0   6   3   6]
- [ 20  22 155  32  17  31  51]
- [  3   6  14 121   5   3   8]
- [  2   6   2   1  49   1   4]
- [  7   0   5   0   0  55   4]
- [ 11   5  12   6   5   8  76]]
-Node Classification on random seed  2762 -> 0.614
-Confusion Matrix:
- [[ 72   2   8   3   4  12   6]
- [  3 122   4   1  15   5   3]
- [ 18  23 142  37  32  23  44]
- [ 11   3  18 102   6   7  13]
- [  0   6   3   3  65   0   2]
- [  5   1   0   2   0  42   5]
- [ 12   2   5   6   6  27  69]]
-Node Classification on random seed  2763 -> 0.625
-Confusion Matrix:
- [[ 75   2   2   9   2  11   9]
- [  0 135   8   3  10   2   4]
- [ 27  12 126  39  36  22  50]
- [ 11   3  18 100   7   3   5]
- [  2   3   2   0  73   1   3]
- [  4   1   4   4   0  48   5]
- [  3   0  12   4   5  27  68]]
-Node Classification on random seed  2764 -> 0.644
-Confusion Matrix:
- [[ 70   6   1   7   5  10   3]
- [  1 118   6   3   5   2   3]
- [ 40  14 170  36  23  16  34]
- [  6   3  19 115   6   9  11]
- [  1  11   2   5  63   0   1]
- [ 13   2   0   0   7  36   1]
- [ 13   3   8   3   6  11  72]]
-Node Classification on random seed  2765 -> 0.658
-Confusion Matrix:
- [[ 74   1   1   2   4  13   9]
- [  3 119   5   2  10   2   1]
- [ 17  20 166  24  29  20  43]
- [ 10   1  24 105   4   7   8]
- [  5   4   6   3  66   3   0]
- [  3   2   3   0   1  39   3]
- [ 10   3   7   4   7  18  89]]
-Node Classification on random seed  2766 -> 0.64
-Confusion Matrix:
- [[ 69   0   5   6   2   7   4]
- [  4 136   6   2  13   0   0]
- [ 28  11 153  35  23  20  36]
- [ 15   2  19  86  15   8  11]
- [  4   4   7   0  63   0   0]
- [ 10   0   0   0   0  41  13]
- [ 16   5   4  10  11   4  92]]
-Node Classification on random seed  2767 -> 0.609
-Confusion Matrix:
- [[ 88   4   8   1   2  14   8]
- [  5 115   2   1   9   2   1]
- [ 17  14 136  47  32  35  26]
- [ 11   6  27  96   2   6  10]
- [  2  11   3   3  64   1   0]
- [  6   2   4   5   0  49   3]
- [ 14   4  12   9   9  13  61]]
-Node Classification on random seed  2768 -> 0.61
-Confusion Matrix:
- [[ 64   1  10   4   6   7  11]
- [ 11 122   0   0  12   4   4]
- [ 23  24 135  23  24  27  56]
- [  5   0  34  99   5  14  11]
- [  2   6   8   0  59   1   1]
- [  7   1   2   1   0  43   6]
- [ 16   1   2   4   4  12  88]]
-Node Classification on random seed  2769 -> 0.579
-Confusion Matrix:
- [[ 46   2   2  10   7   7  13]
- [ 13 112   3   7   9   2   2]
- [ 17  40 117  27  23  36  52]
- [  5   3  26 114   9   8   7]
- [  0   6   4   2  71   0   2]
- [  5   0   0   3   2  42   6]
- [  8   6   8  14   4  21  77]]
-Node Classification on random seed  2770 -> 0.589
-Confusion Matrix:
- [[ 58   3   4   3   2  15  12]
- [  2 138   1   3  11   1   8]
- [ 14  30 130  25  36  26  59]
- [  8   9  13  97   3   7  22]
- [  1   7   0   4  51   3   5]
- [  3   1   1   1   6  34   9]
- [  5   4   8   8  10  18  81]]
-Node Classification on random seed  2771 -> 0.638
-Confusion Matrix:
- [[ 83   1   1   1   2  17   9]
- [  2 135   9   3   1   4   3]
- [ 21  32 137  42  10  22  44]
- [  9   5  19 109   4   6   9]
- [  1   7   7   0  62   1   1]
- [  2   1   1   1   0  50   4]
- [ 17   4   5   5   8  21  62]]
-Node Classification on random seed  2772 -> 0.61
-Confusion Matrix:
- [[ 67   0   5   5   5   5  13]
- [ 10 115   5   5   5   1   9]
- [ 14  35 142  43  17  35  33]
- [  8   2  14 105   2   6   8]
- [  3   2   3   0  68   1   3]
- [  5   1   2   2   3  45   5]
- [  9   8   6  24   4  24  68]]
-Node Classification on random seed  2773 -> 0.62
-Confusion Matrix:
- [[ 72   5   3   6   1  16  13]
- [  4 113   3   2  10   5  10]
- [ 19  22 135  49  23  29  39]
- [ 10   2  11 123   5   4   6]
- [  0   6   4   2  60   1   2]
- [  7   1   1   1   2  45   4]
- [ 15   5   5   7   7  13  72]]
-Node Classification on random seed  2774 -> 0.592
-Confusion Matrix:
- [[ 68   2  10   9   4  20   9]
- [  4 135   2   1   5   1   9]
- [ 31  34 142  24  18  26  42]
- [ 16   7  13  83   4   4  10]
- [  2   7   4   0  57   1   4]
- [ 17   1   4   2   0  31   5]
- [ 10   3  12   4   4  23  76]]
-Node Classification on random seed  2775 -> 0.594
-Confusion Matrix:
- [[ 77   2   3   5   8  18   8]
- [  1 127  16   1   8   3   1]
- [ 14  23 152  28  34  18  44]
- [ 10   7  16  87   6  19  10]
- [  0  13   6   3  51   4   2]
- [ 10   1   9   0   1  33   6]
- [  6   5  11  12   5   9  67]]
-Node Classification on random seed  2776 -> 0.614
-Confusion Matrix:
- [[ 63   1   8   6   5  12  10]
- [  8 132   8   1   5   0   7]
- [ 34  20 147  51  19  21  19]
- [ 11   3  16  87   2   4  19]
- [  2  11   3   5  54   2   4]
- [  1   2   2   1   0  45   5]
- [  4   3  18   7   3  23  86]]
-Node Classification on random seed  2777 -> 0.637
-Confusion Matrix:
- [[ 82   1   1   3   2  15   7]
- [  4 127   5   3   6   5   6]
- [ 21  19 170  45  10  32  34]
- [ 17   2  19  95   0   5  14]
- [  5   8   3   4  40   2   8]
- [  5   3   0   1   1  52   4]
- [ 10   1   5   7   3  17  71]]
-Node Classification on random seed  2778 -> 0.58
-Confusion Matrix:
- [[ 45   3   7  11   2  15  24]
- [  2 113  11   5  12   4   7]
- [ 24  18 163  42  34  16  27]
- [ 14   0  17  99   1   8  14]
- [  5   5   4   2  58   0   5]
- [  6   1   9   5   0  28   5]
- [  3   6  12  12   9  13  74]]
-Node Classification on random seed  2779 -> 0.598
-Confusion Matrix:
- [[ 64   1   9   3   4  17   9]
- [  3 135   6   2   4   3   8]
- [ 30  19 133  24  31  35  39]
- [ 12   2  25  76   6   2  15]
- [  0   8   6   0  62   3   2]
- [  7   2   0   4   0  43   3]
- [ 13   3  14   5   4  19  85]]
-Node Classification on random seed  2780 -> 0.606
-Confusion Matrix:
- [[ 76   0   2   4   4   5  18]
- [  1 133   8   2   9   3   5]
- [ 17  13 125  44  38  32  42]
- [ 10   3  14  91  12   6  21]
- [  0   2   4   1  61   1   4]
- [  8   2   0   0   0  39  11]
- [  8   4  10   5   6  15  81]]
-Node Classification on random seed  2781 -> 0.626
-Confusion Matrix:
- [[ 77   4   2  11   4  19   6]
- [  4 140   5   4   5   3   8]
- [ 25  18 149  29  11  32  24]
- [ 22   7  21  83   6   9   9]
- [  2   6   4   1  57   4   1]
- [  9   0   3   4   3  38   5]
- [  9   3   4   5   6  17  82]]
-Node Classification on random seed  2782 -> 0.576
-Confusion Matrix:
- [[ 77   6   5   3   3  10   2]
- [  1 120  13   1   7   3   2]
- [ 32  13 124  41  31  32  33]
- [ 27   3  19  85  13   5   9]
- [  2   3   4   1  69   2   1]
- [  6   0   1   0   2  43   5]
- [ 26   2  10   5  15  25  58]]
-Node Classification on random seed  2783 -> 0.602
-Confusion Matrix:
- [[ 83   2   9   1   5   9  10]
- [  1 123   6   2   7   2   3]
- [ 24  16 138  27  35  24  39]
- [ 18   2  28  83   7   8  14]
- [  0   7   2   0  60   1   3]
- [  3   4   3   3   0  48   8]
- [ 25   3  14   4   7  12  67]]
-Node Classification on random seed  2784 -> 0.61
-Confusion Matrix:
- [[ 61   5   6   2  11  11   9]
- [  7 125   5   2   5   2   6]
- [ 31  17 157  19  34  14  45]
- [  9   1  21 104   1  10  17]
- [  0   5   8   2  69   3   1]
- [  5   0   3   0   0  40   8]
- [  7   5   7  13  24   9  54]]
-Node Classification on random seed  2785 -> 0.587
-Confusion Matrix:
- [[ 82   3  10   3   4  12   5]
- [  5 138   6   2   4   1   4]
- [ 19  17 106  32  48  42  42]
- [  8   4  18 101   5  13   9]
- [  1   6   2   1  50   0   6]
- [  4   0   8   0   0  43   8]
- [ 11   3   9   8   8  22  67]]
-Node Classification on random seed  2786 -> 0.646
-Confusion Matrix:
- [[ 70   4   8   4   1  12  12]
- [  4 138   7   0   5   4   3]
- [ 12  30 138  36  27  19  37]
- [ 14   1   9 118   2   3   5]
- [  2  10   4   1  59   1   1]
- [  5   2   2   3   1  46   2]
- [  3   6   8  10  11  23  77]]
-Node Classification on random seed  2787 -> 0.62
-Confusion Matrix:
- [[ 95   2  10   1   1   3   6]
- [ 10 131   3   5   6   0   3]
- [ 17  27 135  39  23  31  26]
- [ 22   0  28  92  12   1  10]
- [  1   4   6   4  66   0   1]
- [  4   2   4   3   1  43   4]
- [ 21   1   8   8   7  15  58]]
-Node Classification on random seed  2788 -> 0.651
-Confusion Matrix:
- [[ 70   2   0   5   5  12   4]
- [  3 143   3   5   5   2   1]
- [ 32  15 161  22  24  20  42]
- [ 19   9  12  95   6   9   4]
- [  2   7   3   0  58   5   3]
- [  7   3   0   2   0  50   3]
- [  8   3   4  14   7  17  74]]
-Node Classification on random seed  2789 -> 0.576
-Confusion Matrix:
- [[ 69   1   6   2   3  12   8]
- [  1 108   8   1  18   7   7]
- [ 31  21 111  32  39  20  58]
- [  6  10  10 104   4   6  19]
- [  1   5   4   4  69   2   2]
- [ 10   0   2   1   0  47   8]
- [  5   4   7   7  13  19  68]]
-Node Classification on random seed  2790 -> 0.622
-Confusion Matrix:
- [[ 71   4   8   3   3   8   8]
- [  5 135   9   2   7   2   1]
- [ 30  14 163  33  28  18  35]
- [ 16   0  18  73   4   8  20]
- [  1   2   7   3  66   1   4]
- [  5   0   4   3   1  44   7]
- [  9   8  12  10   8   9  70]]
-Node Classification on random seed  2791 -> 0.62
-Confusion Matrix:
- [[ 66   2   1   3   6  16  17]
- [  3 139   3   0   3   4   0]
- [ 24  24 123  41  23  20  42]
- [  5   4  14  98   5   3  21]
- [  1   3   2   4  56   0   4]
- [  6   1   2   2   0  52   3]
- [ 18   8   8   4   6  24  86]]
-Node Classification on random seed  2792 -> 0.622
-Confusion Matrix:
- [[ 67   2   3   3   1   9  11]
- [  5 137   4   2   4   1   0]
- [ 30  13 125  33  21  40  58]
- [  6   2  16 104  10   4  16]
- [  1   8   2   0  71   1   2]
- [ 13   5   3   3   1  44   2]
- [  9   4   6   3   9  12  74]]
-Node Classification on random seed  2793 -> 0.629
-Confusion Matrix:
- [[ 79   2   2   7   5  13  11]
- [  3 119  12   1  15   5   5]
- [ 43  22 162  26  21  12  33]
- [  5   5  17 109   2   3  11]
- [  2   2   8   1  59   1   2]
- [  6   0   3   1   0  42   6]
- [  9   4   8   7  16  14  59]]
-Node Classification on random seed  2794 -> 0.656
-Confusion Matrix:
- [[ 66   2   2   6   3   7  12]
- [  5 138   3   2   2   3   1]
- [ 19  25 139  37  14  26  35]
- [ 10   6   7 116   6   4  11]
- [  2   8   1   1  60   0   3]
- [  9   2   2   0   2  51   7]
- [ 14  12   6   8  12   7  86]]
-Node Classification on random seed  2795 -> 0.616
-Confusion Matrix:
- [[ 73   4  16   3   4  14   6]
- [  5 123   6   4   7   3  10]
- [ 17  18 156  47  21  19  33]
- [  9   9  19 102   7  11  12]
- [  2   9   4   0  43   3   3]
- [  3   0   2   1   0  44   5]
- [  9   2  12   5   4  16  75]]
-Node Classification on random seed  2796 -> 0.555
-Confusion Matrix:
- [[ 68   4   3  10   7   5  12]
- [  7 128   5   0   3   3   9]
- [ 38  24 110  39  23  22  32]
- [ 26   6  23  81   4  15   8]
- [  6   3   2   3  59   0   2]
- [ 12   2   1   1   1  45   7]
- [ 14   9  22  10   8  14  64]]
-Node Classification on random seed  2797 -> 0.648
-Confusion Matrix:
- [[ 67   0   6   3   3  10  11]
- [  2 123   4   2   6   4   3]
- [ 21  25 158  28  22  14  49]
- [  2   8  14 111   4   3  12]
- [  2   5   3   1  52   1   0]
- [  3   3   2   2   0  43   6]
- [ 11   5  13  17   2  20  94]]
-Node Classification on random seed  2798 -> 0.618
-Confusion Matrix:
- [[ 78   1   4   7   5   9  12]
- [  8 125   4   0   3   2   5]
- [ 21  19 144  40  39  23  36]
- [ 13   3  19  98   5   6  11]
- [  0   6   2   0  54   0   7]
- [  4   3   3   1   1  41   5]
- [  7   7  10  11   7  13  78]]
-Node Classification on random seed  2799 -> 0.622
-Confusion Matrix:
- [[ 71   2   3   3   6  20   7]
- [  3 134   6   3   7   4   2]
- [ 14  18 150  41  12  47  35]
- [ 10   6  12 107   2   7   9]
- [  0   5   4   3  48   0   1]
- [  7   2   3   0   3  41   9]
- [  3   4   7   9   6  33  71]]
-Node Classification on random seed  2800 -> 0.63
-Confusion Matrix:
- [[ 73   2   3   6   1  13  11]
- [  2 120  13   3  14   4   1]
- [ 18  16 153  23  35  15  27]
- [ 14   4  26 110  12   6  11]
- [  2   4   2   1  58   1   4]
- [  4   1   1   2   1  41   7]
- [  8   4  13  16   7  12  75]]
-Node Classification on random seed  2801 -> 0.577
-Confusion Matrix:
- [[ 54   6  12   3   5  18  11]
- [  5 127  12   2  11   2   1]
- [ 15  30 119  50  25  32  25]
- [ 21   9  12  91  10   6  15]
- [  2   7   4   4  59   0   3]
- [  5   0   2   0   1  44   2]
- [ 12   5   7   8   5  18  83]]
-Node Classification on random seed  2802 -> 0.559
-Confusion Matrix:
- [[ 71   1   7  10   4   8   4]
- [ 14 124   3   0   7   1   7]
- [ 26  36 114  17  35  36  46]
- [  9  10  22  89   5  13  16]
- [  2  10   3   0  54   0   1]
- [  5   3   2   4   1  48   1]
- [ 11   7  11  13  14  16  59]]
-Node Classification on random seed  2803 -> 0.633
-Confusion Matrix:
- [[ 55   1   1   6  10   9  10]
- [  7 136   4   1   5   3   2]
- [ 24  14 140  40  32  21  43]
- [ 13   9  15 121   2  11   6]
- [  0   4   1   0  59   0   5]
- [  9   0   2   0   2  34   8]
- [ 16   5   2   2   6  16  88]]
-Node Classification on random seed  2804 -> 0.624
-Confusion Matrix:
- [[ 66   3   8   7   2   7  11]
- [  1 129   2   2  13   2   5]
- [ 36  25 131  28  30  21  41]
- [  9   3  21 111   4   6  14]
- [  0   1   7   1  54   0   6]
- [  3   2   2   1   0  34  14]
- [  6   2  13   3   6   8  99]]
-Node Classification on random seed  2805 -> 0.626
-Confusion Matrix:
- [[ 64   1   7   2   3   3  12]
- [  7 129   0   8  10   1   4]
- [ 19  23 135  40  35  29  35]
- [  6   5  18 101   4   9   7]
- [  1   5   0   1  64   2   2]
- [  6   1   3   2   0  55   5]
- [  6   2   9   9   9  23  78]]
-Node Classification on random seed  2806 -> 0.586
-Confusion Matrix:
- [[ 74   3   4   9   8  13   5]
- [  9 117   7  10   3   7   4]
- [ 24  17 149  41  24  26  35]
- [ 10   4  21  73   5  18  10]
- [  0   6   6   3  59   1   2]
- [ 11   0   3   2   0  38   7]
- [ 20   2   2   6   5  21  76]]
-Node Classification on random seed  2807 -> 0.61
-Confusion Matrix:
- [[ 74   1   3   5   1   4   9]
- [  6 114  15   3  12   1   1]
- [ 14  28 158  23  33  11  47]
- [ 25   8  21  79   7   5  10]
- [  0  10   7   1  66   0   0]
- [  9   0   3   2   0  46   4]
- [  7   6  13   9   5  21  73]]
-Node Classification on random seed  2808 -> 0.618
-Confusion Matrix:
- [[ 65   0   4   2   4   4  16]
- [  4 139   8   2   3   2   5]
- [ 24  33 142  63  20  15  25]
- [ 16   1  22  99   1   2   9]
- [  0  11   3   2  57   0   3]
- [  2   1   7   0   0  45   8]
- [ 10   2  15   9   4  20  71]]
-Node Classification on random seed  2809 -> 0.626
-Confusion Matrix:
- [[ 68   5   1  17   2  10   9]
- [  3 114   6   1   8   3  10]
- [ 12  38 143  27  18  23  41]
- [  9   5  12  95   6   3  12]
- [  0   5   6   0  71   2   7]
- [  8   1   0   2   0  46   9]
- [  9   5   6   8   5  20  89]]
-Node Classification on random seed  2810 -> 0.621
-Confusion Matrix:
- [[ 70   6   2   7   6  18   7]
- [  3 127   5   2  11   1   5]
- [ 15  18 143  36  31  23  31]
- [ 10   1  15 102   2   3  25]
- [  4   4   4   0  62   2   6]
- [  6   3   2   2   0  45   2]
- [ 15   3  10   6   5  22  72]]
-Node Classification on random seed  2811 -> 0.636
-Confusion Matrix:
- [[ 73   3   3   3   4  10  15]
- [  3 121  10   0   6   4   3]
- [ 26  15 138  36  24  20  43]
- [ 14   3   9 118   5   3  14]
- [  5  12   3   0  63   0   1]
- [  2   3   1   1   0  54   4]
- [  8   3  12   7   8  18  69]]
-Node Classification on random seed  2812 -> 0.589
-Confusion Matrix:
- [[ 45   2   9   9   1   8  20]
- [ 13 112   4   4  10   8   3]
- [ 29  18 137  34  37  18  41]
- [ 17   8  10 112   6   7  10]
- [  4   5   1   3  60   1   2]
- [  5   4   2   0   1  43   9]
- [ 10   3  10   4   3  18  80]]
-Node Classification on random seed  2813 -> 0.623
-Confusion Matrix:
- [[ 68   7   3   7   3   6  10]
- [  2 121  11   2   4   5   1]
- [ 12  18 156  27  33  33  38]
- [ 21   2  26  94   5   7   8]
- [  2   8   3   0  55   3   2]
- [  9   2   2   1   1  51   5]
- [ 13   4   5   2   7  17  78]]
-Node Classification on random seed  2814 -> 0.589
-Confusion Matrix:
- [[ 73   8   6   4   2  22   3]
- [  6 128   7   1   5   5   4]
- [ 27  37 132  20  41  37  30]
- [ 11   5  21 103   5   6  13]
- [  1   7   2   1  56   0   2]
- [  1   0   4   0   0  48   4]
- [  7   5  22   3  11  15  49]]
-Node Classification on random seed  2815 -> 0.596
-Confusion Matrix:
- [[ 75   2   3   6   1  11   7]
- [  4 115   4   2   3   0   6]
- [ 36  34 126  43  32  29  34]
- [ 12   3   3  95   6  12  24]
- [  0   5   4   0  67   1   2]
- [  6   1   1   6   0  44   8]
- [  9   4  13   3   7  17  74]]
-Node Classification on random seed  2816 -> 0.636
-Confusion Matrix:
- [[ 80   3   2   6  10  11   4]
- [  7 121   5   1  18   1   3]
- [ 27  18 148  24  37  17  22]
- [  6   4  18 100   6   3  10]
- [  0   4   3   1  68   0   4]
- [ 11   1   4   1   0  52   3]
- [ 17   6  11   7  11  17  67]]
-Node Classification on random seed  2817 -> 0.588
-Confusion Matrix:
- [[ 46   4   3  15   4  20  20]
- [ 10 106   4   1  18   3   4]
- [ 28  21 144  34  21  31  37]
- [ 10   5  11 104   4   8  16]
- [  2   5   2   0  59   1   1]
- [  4   3   2   3   5  41   6]
- [  3   1  12   5   8  17  88]]
-Node Classification on random seed  2818 -> 0.62
-Confusion Matrix:
- [[ 74   2   5  11   2   7  10]
- [  1 135   2   4   6   1   4]
- [ 23  36 159  35  25  21  23]
- [ 23   3  16  80   6   5  10]
- [  1   9   3   1  59   0   2]
- [ 12   1   0   6   1  39   8]
- [ 14   3  10   6   7  15  74]]
-Node Classification on random seed  2819 -> 0.608
-Confusion Matrix:
- [[ 65   1   3  11   3  11  11]
- [  5 127   3   3  10   6   2]
- [ 31  25 132  36  31  13  40]
- [  8  10  22  94   5   5  16]
- [  1   4   2   3  57   0   3]
- [  4   0   4   0   2  51   6]
- [  4   6  11   3   7  21  82]]
-Node Classification on random seed  2820 -> 0.599
-Confusion Matrix:
- [[ 80   1   3   9   3   5  10]
- [  3 123  13   8   6   1   4]
- [ 23  33 132  36  27  23  30]
- [ 13  12  23 101   4   7  10]
- [  1   3   2   3  61   2   0]
- [  3   0   4   1   2  41   4]
- [ 21   3   5  15  12  13  61]]
-Node Classification on random seed  2821 -> 0.575
-Confusion Matrix:
- [[ 52   0  12   6   7  15  19]
- [  7 125   2   1  15   2   0]
- [ 24  22 137  43  28  22  33]
- [ 12   2  10  97   9  27  18]
- [  2   2   5   1  64   4   0]
- [  4   0   1   5   3  35   3]
- [ 15   4  11  10   7  12  65]]
-Node Classification on random seed  2822 -> 0.638
-Confusion Matrix:
- [[ 68   0   1   7   5   4  20]
- [  2 129   9   1  14   4   2]
- [ 30  22 147  17  21  24  48]
- [  6   0  14 125   2   6  17]
- [  2   5   5   3  53   0   2]
- [  4   3   9   2   0  40   5]
- [ 11   0  14   1   7  13  76]]
-Node Classification on random seed  2823 -> 0.6
-Confusion Matrix:
- [[ 71   3   3  14   2   8  10]
- [ 10 113   1   3  11   4   5]
- [ 23  22 128  28  42  16  49]
- [  7   6  21 112   2   3  14]
- [  2   7   0   0  64   1   2]
- [  9   4   2   2   1  38   2]
- [ 19   4   8  13   4  13  74]]
-Node Classification on random seed  2824 -> 0.644
-Confusion Matrix:
- [[ 89   3   2   6   0   4   6]
- [ 10 124   6   5   5   3   4]
- [ 38  19 154  39  27  13  31]
- [ 11   3  20  98   2   4  11]
- [  2   3   2   5  68   0   2]
- [ 10   2   3   0   4  49   0]
- [ 15   4  12   6   7   7  62]]
-Node Classification on random seed  2825 -> 0.607
-Confusion Matrix:
- [[ 86   2   4   4   3  12   5]
- [  6 120   4   9   4   5   2]
- [ 33  16 127  34  19  24  35]
- [ 21   2   6  92   4  10  20]
- [  1   3   8   2  62   6   0]
- [  9   0   5   2   1  33  14]
- [ 11   4   7   9  10  17  87]]
-Node Classification on random seed  2826 -> 0.636
-Confusion Matrix:
- [[ 86   5   1   5   1   6   6]
- [  6 123   3   4  14   0  13]
- [ 35  15 130  17  51  26  24]
- [  6   6   6 102   7   7  10]
- [  0   3   5   0  72   2   3]
- [  4   5   4   2   0  47   2]
- [ 16   6   1  12   7  18  76]]
-Node Classification on random seed  2827 -> 0.598
-Confusion Matrix:
- [[ 55   3  12   6   1   8  11]
- [  5 148   6   1   7   0   3]
- [ 20  35 135  33  27  36  30]
- [  5   8  22  97   4  10   9]
- [  5   7   2   4  60   1   3]
- [  3   0   2   1   1  44   4]
- [  9   1  11  24   6  16  59]]
-Node Classification on random seed  2828 -> 0.571
-Confusion Matrix:
- [[ 65   1   4  15   8  11   8]
- [  0 114   3   2  19   2   5]
- [ 22  15 120  31  58  16  41]
- [ 20   4  13 101  12   3  11]
- [  2   5   1   2  68   1   2]
- [  4   4   0  10   1  43   0]
- [ 18   6   3  21   7  18  60]]
-Node Classification on random seed  2829 -> 0.64
-Confusion Matrix:
- [[ 67   3   3   7   4   4  24]
- [  8 136   5   4   9   0   3]
- [ 25  18 120  25  43  15  47]
- [  4   3  16 111   4   4   6]
- [  2   6   3   1  74   1   2]
- [  7   0   1   2   0  39  10]
- [  5   4  10  13   4   5  93]]
-Node Classification on random seed  2830 -> 0.653
-Confusion Matrix:
- [[ 65   4   3   3   6  13   2]
- [  9 134   4   0   6   1  12]
- [ 24  31 165  28  15  23  30]
- [  1  10   7 105  12   7  15]
- [  1   5   4   0  54   2   2]
- [  2   1   2   1   1  52   2]
- [  8   8   3   9   7  23  78]]
-Node Classification on random seed  2831 -> 0.643
-Confusion Matrix:
- [[ 69   1   3   6   4  13   5]
- [  3 129   4   3  11   4   4]
- [ 25  12 156  37  13  27  32]
- [ 20   4   9 107   5   5  10]
- [  5   4   9   1  61   0   4]
- [  4   3   0   9   6  34   6]
- [  8   1  10  10   3  14  87]]
-Node Classification on random seed  2832 -> 0.601
-Confusion Matrix:
- [[ 69   6   3   6   4  11  10]
- [  7 124   3   0  11   2   6]
- [ 21  22 156  23  20  28  58]
- [  2   9  23  89  10   7  15]
- [  3   5   6   0  59   1   4]
- [ 11   2   0   7   0  38   5]
- [ 15   2   9   5  11   6  66]]
-Node Classification on random seed  2833 -> 0.654
-Confusion Matrix:
- [[ 70   2   6   6   4   7   3]
- [  6 121  14   0   6   4   5]
- [ 18  24 165  22  20  21  42]
- [ 11   6  17 105   2  10  13]
- [  0   2   4   1  71   3   5]
- [  4   1   4   2   1  44   3]
- [  6   4   8  11   7  11  78]]
-Node Classification on random seed  2834 -> 0.595
-Confusion Matrix:
- [[ 66   3   1   6   8  19  17]
- [  3 115   4   1  12   7   3]
- [ 29  29 135  29  31  15  45]
- [  8   5  29  94  10   8  10]
- [  0   5   1   4  60   0   2]
- [  3   0   3   0   1  44   6]
- [  5   4   3  10   8  18  81]]
-Node Classification on random seed  2835 -> 0.594
-Confusion Matrix:
- [[ 65   3   1  10   7  15   9]
- [  4 108   6   6  15  14   3]
- [ 14   9 132  33  49  28  41]
- [ 10   2   7 109   9   7   5]
- [  1   4   3   6  72   2   4]
- [  6   0   2   1   0  29  25]
- [  6   6   2  12   9  10  79]]
-Node Classification on random seed  2836 -> 0.639
-Confusion Matrix:
- [[ 63   4   0   6   5   8  15]
- [  2 154   4   3   5   2   2]
- [ 27  24 156  16  23  21  47]
- [ 12   3  24  87  13   4  14]
- [  0   2   5   3  60   0   2]
- [  2   2   4   3   0  41   7]
- [ 11   8  11   3   9   5  78]]
-Node Classification on random seed  2837 -> 0.624
-Confusion Matrix:
- [[ 84   2   1   1   4   9  21]
- [  5 121   2   3   4   4   2]
- [ 30  16 151  40  24  25  44]
- [ 16   6  11  93   2   8  11]
- [  4   5   9   0  55   2   2]
- [ 11   1   5   1   0  42   3]
- [ 15   1   7   6   4   9  78]]
-Node Classification on random seed  2838 -> 0.616
-Confusion Matrix:
- [[ 67   4   3   7   2  13   6]
- [  4 131   5   6   4   2   5]
- [ 24  30 140  29  35  20  33]
- [ 16   7  21 101   9   4   8]
- [  0   8   2   0  61   0   1]
- [  6   1   2   1   0  45   6]
- [ 13   9  11  13   6   8  71]]
-Node Classification on random seed  2839 -> 0.598
-Confusion Matrix:
- [[ 54   3   6   8   8  15   7]
- [  2 113  17   4   4   3   6]
- [ 15  32 161  36  21  16  40]
- [ 21   8  17  93  13  15  10]
- [  0  11   3   0  53   0   4]
- [  4   1   0   1   0  37   5]
- [  9   4   9   3   9  12  87]]
-Node Classification on random seed  2840 -> 0.613
-Confusion Matrix:
- [[ 80   0  12   1   3  11  16]
- [  3 127   3   6  18   1   3]
- [ 28  16 119  32  35  37  33]
- [  7   1  22 104   4   3  12]
- [  1   7   2   3  62   1   2]
- [  9   2   0   2   0  47   3]
- [ 10   4  10   6   3  15  74]]
-Node Classification on random seed  2841 -> 0.641
-Confusion Matrix:
- [[ 70   5   4   3   6  10  15]
- [  2 126   3   3   5   0   7]
- [ 16  14 156  32  32  20  38]
- [ 17   6  11 105   3   7   5]
- [  1   5   0   4  64   4   2]
- [  9   0   2   2   3  38   9]
- [ 22   0  11  10   4   7  82]]
-Node Classification on random seed  2842 -> 0.647
-Confusion Matrix:
- [[ 94   4   2  13   3   6   1]
- [  2 126   2   4   1   3   0]
- [ 42  32 140  33  12  22  36]
- [  6   3  12 106   1   4  14]
- [  3   8   8   2  59   1   2]
- [  5   1   4   5   3  46   5]
- [ 11   7   5  10   3  12  76]]
-Node Classification on random seed  2843 -> 0.623
-Confusion Matrix:
- [[ 64   4   8   6   3   5  21]
- [  2 136   5   3   8   3   2]
- [ 15  13 146  68  26  21  25]
- [ 12   5  20  96   3   8   8]
- [  0   6   0   2  64   1   1]
- [  4   3   2   2   0  45   5]
- [  3   0  13  23   4  14  72]]
-Node Classification on random seed  2844 -> 0.595
-Confusion Matrix:
- [[ 78   2   0   6   4  16  12]
- [  7 117   6  10   2   5   6]
- [ 29  31 132  22  29  28  45]
- [ 13   5  10 102   4   8  20]
- [  0   3   2   4  64   1   3]
- [  7   3   5   0   0  29  10]
- [  9   8   7   6   3  14  73]]
-Node Classification on random seed  2845 -> 0.642
-Confusion Matrix:
- [[ 68   0   3   3   6  17   2]
- [  4 129   9   1   6   4   2]
- [ 11  37 150  33  36  29  36]
- [  7   3  16 105   3   6  10]
- [  1   5   4   0  70   0   1]
- [  5   3   2   0   0  48   5]
- [ 14   2   4   9   6  13  72]]
-Node Classification on random seed  2846 -> 0.634
-Confusion Matrix:
- [[ 52   1   3  12   2  15  11]
- [  7 135   2   8   5   5   2]
- [ 34  23 168  33  15  25  27]
- [ 15   3   4 105  12   4   7]
- [  2   7   8   1  55   0   1]
- [  7   0   3   5   2  56   1]
- [ 12   4   5   4   7  22  63]]
-Node Classification on random seed  2847 -> 0.619
-Confusion Matrix:
- [[ 84   2   9   5   1   7  11]
- [  5 124   4   2   1   3   7]
- [ 26  24 149  31  15  36  45]
- [  7   6  12 103   1   7  14]
- [  2   5   5   3  52   1   9]
- [  8   1   0   4   0  42   4]
- [ 13   4  20   6   4  11  65]]
-Node Classification on random seed  2848 -> 0.602
-Confusion Matrix:
- [[ 58   4  13   8   7  15   9]
- [  4 128   6   3   9   3   6]
- [ 35  16 122  28  45  13  52]
- [  9   2  24  92   9   4   4]
- [  0   3   2   2  70   1   1]
- [  7   0   1   2   3  44   3]
- [  3   2   4  12   6  18  88]]
-Node Classification on random seed  2849 -> 0.634
-Confusion Matrix:
- [[ 65   3   8   6   7   9   3]
- [ 11 136   4   3   6   1   4]
- [ 21   8 164  25  27  28  40]
- [ 10   4  20 111   2   5   9]
- [  2   6   7   1  49   3   1]
- [  4   2   1   8   0  45   1]
- [ 14   2  10  13   3  24  64]]
-Node Classification on random seed  2850 -> 0.56
-Confusion Matrix:
- [[ 61   2   1  10   7  15  15]
- [  6 129   6   4   7   2   2]
- [ 19  63 116  42  27  11  54]
- [  3   9  23  97   9   1  19]
- [  1   7   1   0  54   0   2]
- [  3   2   2   3   0  29   8]
- [ 16   8   5  12   8   5  74]]
-Node Classification on random seed  2851 -> 0.573
-Confusion Matrix:
- [[ 57   0  12   5  10  11  11]
- [  4 118   5   5   5   1   9]
- [ 24  47 127  27  27  23  38]
- [ 15   3   9  92  18   6  20]
- [  0   6   3   0  58   2   6]
- [  6   2   4   1   2  41   5]
- [ 16   2  13   2   9  13  80]]
-Node Classification on random seed  2852 -> 0.577
-Confusion Matrix:
- [[ 53   2   6  19   4   9  12]
- [ 10 117   4   1  21   0   2]
- [ 20  26 124  31  28  46  26]
- [  8   2  12 104   1  12  25]
- [  1   4   3   2  55   1   3]
- [ 11   0   2   0   1  46   5]
- [ 20   2  17   7   1  16  78]]
-Node Classification on random seed  2853 -> 0.577
-Confusion Matrix:
- [[ 61   3   4   4   7   2  19]
- [  2 111   5   4  18   4   2]
- [ 23  19 139  49  52  24  25]
- [ 13   5  16  92  14   7  13]
- [  1   3   5   0  48   4   5]
- [ 14   0   2   2   0  40   4]
- [ 12   3  11   3   6  14  86]]
-Node Classification on random seed  2854 -> 0.65
-Confusion Matrix:
- [[ 75   3   0   3   3   5   4]
- [  5 128   3   1  11   2   1]
- [ 26  21 139  49  30  14  43]
- [ 13   1  13 123   2   1   9]
- [  1   2   5   2  61   1   3]
- [  7   2   3   0   0  50   3]
- [ 12   4   9  10   9  14  74]]
-Node Classification on random seed  2855 -> 0.593
-Confusion Matrix:
- [[ 72   4   4   4   4   5  10]
- [  4 119   2   1  19   6   1]
- [ 25  27 142  18  36  28  52]
- [ 16   7  13  79  17   5  15]
- [  0   7   5   3  59   1   6]
- [  2   1   3   3   3  40   4]
- [ 14   4   7   4   6  11  82]]
-Node Classification on random seed  2856 -> 0.632
-Confusion Matrix:
- [[ 74   0   1   4   0  11   7]
- [  3 132   7   1   6   5   3]
- [ 19  31 137  59  12  22  37]
- [ 15   2   9 133   4   6   2]
- [  3   6   6   3  50   2   1]
- [  6   1   2   1   0  46   1]
- [ 20   6  13  13   2  16  60]]
-Node Classification on random seed  2857 -> 0.622
-Confusion Matrix:
- [[ 75   1   0   6   6   8  13]
- [  0 126   1   2   6   6   4]
- [ 23  35 137  30  16  35  38]
- [ 16   3  15 100   4  10  10]
- [  2   6   2   0  65   2   3]
- [  3   0   3   2   0  36  14]
- [  7   4   7   6  10  19  83]]
-Node Classification on random seed  2858 -> 0.581
-Confusion Matrix:
- [[ 72   1   3   1   6  13  10]
- [  4 127   6   5   2   2   6]
- [ 19  35 104  35  37  31  46]
- [ 13   5   7 104   9  12  17]
- [  2   7   2   0  58   2   4]
- [  5   1   2   7   0  43   4]
- [ 15   3   7  13   6  14  73]]
-Node Classification on random seed  2859 -> 0.583
-Confusion Matrix:
- [[ 69   0   3   7   4   5  14]
- [  2 134   8  10   4   1   4]
- [ 18  34 122  34  33  16  39]
- [ 15   3  41  88   4   4  13]
- [  2  11   1   2  53   1   3]
- [  8   0   4   5   0  43   2]
- [  7  10   8  12   5  20  74]]
-Node Classification on random seed  2860 -> 0.633
-Confusion Matrix:
- [[ 66   4   5   4   4  18   3]
- [  2 148   5   1   1   6   2]
- [ 29  12 139  36  20  27  38]
- [  9   2  20 102   6   8  10]
- [  0  13   8   0  54   0   1]
- [  4   2   6   1   0  49   1]
- [ 15   3   7   5   5  24  75]]
-Node Classification on random seed  2861 -> 0.632
-Confusion Matrix:
- [[ 64   0   3   1   5  15   5]
- [  1 133   5   4   7   6   2]
- [ 21  10 161  29  26  31  45]
- [ 13   2  22  95   5  11  22]
- [  0   3   7   1  56   0   2]
- [  3   1   1   2   0  51   3]
- [  5   0   8   8  11  22  72]]
-Node Classification on random seed  2862 -> 0.611
-Confusion Matrix:
- [[ 71   2   5   8   1  24   3]
- [ 12 125   4   6   9   1   4]
- [ 22  21 116  52  22  28  41]
- [  9   4  11 119   7   7   8]
- [  2   8   4   1  59   0   4]
- [  3   1   0   0   3  53   0]
- [  9   3   5   8   8  19  68]]
-Node Classification on random seed  2863 -> 0.632
-Confusion Matrix:
- [[ 74   2   0   8   1   7   8]
- [  3 146   1   2  15   3   3]
- [ 26  15 143  38  32  19  40]
- [  7   4  19  86   4   4  17]
- [  3   8   4   0  63   1   5]
- [  5   1   4   7   0  42   2]
- [  9   4   6   8   8  15  78]]
-Node Classification on random seed  2864 -> 0.582
-Confusion Matrix:
- [[ 81   5   1   3   1  14   8]
- [  4 111  10   2  14   1   0]
- [ 30  33 109  46  42  14  44]
- [ 30   1  18  98   6   4   7]
- [  1   5   3   0  71   1   1]
- [  6   0   5   0   0  41   4]
- [ 13   2  15   3   2  19  71]]
-Node Classification on random seed  2865 -> 0.591
-Confusion Matrix:
- [[ 62   4   6  14   2  11   8]
- [ 10 118   4   5   7   3  10]
- [ 10  20 146  35  40  18  41]
- [ 12   4  30  96   7   3   9]
- [  1   3   1   0  56   1   3]
- [  5   0   4   5   0  43   9]
- [  5   6  10  21   8  14  70]]
-Node Classification on random seed  2866 -> 0.639
-Confusion Matrix:
- [[ 71   2   3   1   3  13  10]
- [  7 136   3   0   2   2   3]
- [ 26  11 145  37  42  34  27]
- [ 16   3  16 107   3   7   5]
- [  3   7   0   2  55   1   4]
- [  0   1   2   0   0  51   8]
- [ 12   5   7   5  10  18  74]]
-Node Classification on random seed  2867 -> 0.617
-Confusion Matrix:
- [[ 74   1   2   8   3  10   4]
- [  8 142   3   4   7   2   5]
- [ 35  12 132  34  49  13  41]
- [  7   2  17  80  10  15   8]
- [  1   5   8   1  67   1   2]
- [  1   1   0   5   1  53   3]
- [ 16   1   4  12   7  14  69]]
-Node Classification on random seed  2868 -> 0.635
-Confusion Matrix:
- [[ 77   3   0   0   3   7  12]
- [  7 113   8   1  10   6   1]
- [ 18  22 159  31  26  19  47]
- [ 11   1  12 108   4   6  20]
- [  2   2   4   2  74   0   3]
- [  9   0  10   2   3  30   6]
- [ 11   5   8   3   9  11  74]]
-Node Classification on random seed  2869 -> 0.618
-Confusion Matrix:
- [[ 68   7   5   5   7   7   4]
- [  5 133   0   1  10   2   6]
- [ 17  23 123  43  35  28  39]
- [  7   5  11 117   4   4  10]
- [  2   5   4   4  63   2   3]
- [  5   1   1   1   0  46   4]
- [  9   5  14   9  12  16  68]]
-Node Classification on random seed  2870 -> 0.623
-Confusion Matrix:
- [[ 72   3   5   2   3  16   9]
- [  8 137   3   3   5   4   7]
- [ 19  24 150  49  24  19  28]
- [ 16   5  20  82   5   3  23]
- [  0   2   5   1  62   1   2]
- [  4   1   4   4   0  49   4]
- [ 12   6   6   4   2  16  71]]
-Node Classification on random seed  2871 -> 0.617
-Confusion Matrix:
- [[ 74   4   5   2   4  15   9]
- [  0 132   4   4   5  11   1]
- [ 31  26 135  52  21  26  34]
- [  8   7  15  90   6  10  10]
- [  0   4   7   1  59   3   0]
- [  5   1   1   1   0  53   3]
- [  7   5   4   6   9  16  74]]
-Node Classification on random seed  2872 -> 0.592
-Confusion Matrix:
- [[ 73   2   3   6   1  13  10]
- [  4 122   4   3  15   5   5]
- [ 38  25 115  34  24  21  42]
- [ 25   2  10 100  12   6  17]
- [  0   0   3   2  58   1   6]
- [  7   2   3   1   0  52  10]
- [ 13   1  11   8   7   6  72]]
-Node Classification on random seed  2873 -> 0.586
-Confusion Matrix:
- [[ 68   2   9   7   4   6   7]
- [ 13  99  12   1  22   1   1]
- [ 28  12 141  45  39  21  35]
- [ 16   3  17 109   7   6  12]
- [  2   5   4   1  61   0   3]
- [  6   1   1   2   0  46   5]
- [ 14   1   3  10   9  21  62]]
-Node Classification on random seed  2874 -> 0.649
-Confusion Matrix:
- [[ 67   5   2  17   4  10   4]
- [  2 135  10   1   3   4   2]
- [ 17  31 174  24  24  19  39]
- [ 11   5  21  99   2   8   6]
- [  0  10   2   1  65   1   4]
- [  4   0   3   1   0  44   4]
- [ 10   2   9   4  10  15  65]]
-Node Classification on random seed  2875 -> 0.602
-Confusion Matrix:
- [[ 64   3   3   4   5  16   5]
- [  5 129  12   4   6   2   7]
- [ 21  25 137  38  54  15  32]
- [  6   4  13 104   4  12  12]
- [  0   6   0   4  57   1   0]
- [  3   2   3   2   0  58   6]
- [ 11   6   4  19   6  17  53]]
-Node Classification on random seed  2876 -> 0.61
-Confusion Matrix:
- [[ 68   0   6   1   0  13   4]
- [  7 123   3   4   9   2   5]
- [ 21  15 144  55  20  26  36]
- [ 19   0  24 110   0  13  10]
- [  0   5   3   1  54   3   4]
- [  6   0   1   1   5  44   3]
- [ 23   2   5  15   3  17  67]]
-Node Classification on random seed  2877 -> 0.633
-Confusion Matrix:
- [[ 63   6   9   2   4  11  10]
- [  3 124  16   2   6   3   5]
- [ 20  25 157  44  19  25  34]
- [  6   7  11 108   8   6  12]
- [  2   1   5   1  60   2   2]
- [  8   1   5   2   2  37   4]
- [ 14   2  12   5   0   5  84]]
-Node Classification on random seed  2878 -> 0.632
-Confusion Matrix:
- [[ 71   3   8   1   7   4   4]
- [  8 117   3   3   6   4   6]
- [ 21  27 144  38  16  25  34]
- [ 18   5   5 111   3   4  10]
- [  3  10   5   0  66   0   3]
- [  9   3   8   2   3  37   4]
- [ 11   5  12   5   4  18  86]]
-Node Classification on random seed  2879 -> 0.631
-Confusion Matrix:
- [[ 77   0   1   1   2  11  11]
- [  7 130   5   2  14   3   6]
- [ 34  16 147  27  25  28  26]
- [ 14   3  18 100   1   4  17]
- [  2   5   7   2  59   0   1]
- [  5   1   4   0   0  44   3]
- [ 10   4  17   2  11  19  74]]
-Node Classification on random seed  2880 -> 0.572
-Confusion Matrix:
- [[ 63   7   4   6   4   6  11]
- [ 11 127  10   6   2   5   2]
- [ 49  31 141  26  34  26  31]
- [ 11   6  20  90   1   9  14]
- [  3   5   3   2  55   4   4]
- [  4   0   2   4   7  32   1]
- [ 12   3  13   5  11  13  64]]
-Node Classification on random seed  2881 -> 0.615
-Confusion Matrix:
- [[ 71   5   1   4   4  12  10]
- [  4 137   2   4  10   6   2]
- [ 21  21 135  24  33  33  38]
- [ 12   4  16  98   8   4  17]
- [  0   7   4   5  55   2   3]
- [  8   0   3   3   0  36   3]
- [  8   5   3   9  11  16  83]]
-Node Classification on random seed  2882 -> 0.603
-Confusion Matrix:
- [[ 48   1   4   1   1  14  17]
- [  4 132   4   5   6   2   4]
- [ 26  25 132  35  27  42  25]
- [  7   0  23 101   3  10  16]
- [  4   8   2   3  77   0   2]
- [  3   0   3   2   0  48   4]
- [ 13   4   6   2  20  19  65]]
-Node Classification on random seed  2883 -> 0.604
-Confusion Matrix:
- [[ 85   4   6   2   5  10   5]
- [  6 121  10  11   3   2   4]
- [ 20  31 134  40  20  29  42]
- [ 10   6   6  97   9  14  10]
- [  4   5   6   2  56   1   1]
- [  4   0   1   6   0  45   5]
- [  9   4  12   9   4  18  66]]
-Node Classification on random seed  2884 -> 0.634
-Confusion Matrix:
- [[ 62   5   4   3   3  21   6]
- [  1 110  10   0  12   9   0]
- [ 13  24 169  36  24  34  30]
- [  4   3  20 105  10   5  13]
- [  0   8   2   3  66   0   2]
- [  6   3   1   0   0  47   4]
- [  9   8   6   4   3  17  75]]
-Node Classification on random seed  2885 -> 0.595
-Confusion Matrix:
- [[ 88   1   4   3   8  12   2]
- [  3 133   3   3  11   7   4]
- [ 28  20 121  39  32  40  13]
- [ 18   2  29  85   6   7  12]
- [  2   3   6   1  67   3   1]
- [  7   0   2   3   4  33   5]
- [ 18   6  13  10   7   7  68]]
-Node Classification on random seed  2886 -> 0.615
-Confusion Matrix:
- [[ 70   1   2  10   8  15   4]
- [ 12 131   5   1   5   1   1]
- [ 25  50 142  25  23  24  30]
- [ 13  10  13 105   2   9   5]
- [  1   5   3   5  58   0   3]
- [  7   3   0   2   5  43   3]
- [ 13   4   5   5  12  15  66]]
-Node Classification on random seed  2887 -> 0.626
-Confusion Matrix:
- [[ 64   1   9   3   5  10   5]
- [ 11 124   4   2   8   1   4]
- [ 24  21 163  18  27  28  51]
- [ 16   4  16 101   8   6   4]
- [  1   4   5   1  62   2   2]
- [  5   2   3   5   0  44   3]
- [  5   2  11   9  13  15  68]]
-Node Classification on random seed  2888 -> 0.62
-Confusion Matrix:
- [[ 60   2   1   5   3   7  22]
- [ 10 131   8   0  11   2   2]
- [ 28  24 166  25  26  29  30]
- [ 13   2  14  91   9   3  14]
- [  2   5   3   1  58   1   0]
- [  8   1   0   1   5  39   7]
- [ 24   4   6   3   5  14  75]]
-Node Classification on random seed  2889 -> 0.614
-Confusion Matrix:
- [[ 75   2   9   9   1   8  12]
- [  4 140   0   4   7   6   2]
- [ 18  42 151  23  25  22  37]
- [ 19   2  17  84  13   5   8]
- [  0   7   1   2  60   1   1]
- [  4   0   1   3   0  45   7]
- [ 12   9  12   3   6  22  59]]
-Node Classification on random seed  2890 -> 0.629
-Confusion Matrix:
- [[ 53   4  10   2   6  10  11]
- [  2 130   0   3   4   2  11]
- [ 27  26 153  36  21  22  38]
- [  9   6  10 114   2   5   9]
- [  4   4   4   2  61   2   2]
- [  8   2   3   3   4  44   0]
- [ 14   1  18   6   8  10  74]]
-Node Classification on random seed  2891 -> 0.582
-Confusion Matrix:
- [[ 60   2   4  11   4   7  11]
- [  2 116  13   7  12   4   7]
- [ 29  20 137  33  28  25  41]
- [  5   4  22 105   2   6  18]
- [  1   3   6   2  52   0   3]
- [  3   3   1   2   5  46   4]
- [  8   3   5  13  20  19  66]]
-Node Classification on random seed  2892 -> 0.645
-Confusion Matrix:
- [[ 86   2   1   1   4  21   6]
- [  1 121   7   6  11  10   5]
- [ 23  21 135  21  23  13  50]
- [ 12   7  14 100   6   1  14]
- [  2   2   4   1  70   0   3]
- [  1   2   1   0   2  46   5]
- [  3  10   5   6   9  19  87]]
-Node Classification on random seed  2893 -> 0.613
-Confusion Matrix:
- [[ 71   3   3   1   3  12   5]
- [  5 147   5   1   7   1   3]
- [ 34  25 117  24  28  28  48]
- [  9   8  11  98   2  12  13]
- [  3   4   3   0  57   3   8]
- [  8   1   2   0   1  54   5]
- [ 18   4   4   5   6  21  69]]
-Node Classification on random seed  2894 -> 0.614
-Confusion Matrix:
- [[ 66   1   4   6   3   7   9]
- [  2 139   4   5   9   4   3]
- [ 34  14 141  33  52  22  35]
- [ 12   4  16  97  14   3   8]
- [  1   3   2   1  58   1   4]
- [  3   2   1   3   3  37  10]
- [  8   2  10  11   7  10  76]]
-Node Classification on random seed  2895 -> 0.631
-Confusion Matrix:
- [[ 59   3   9  18   7   6  12]
- [  7 107   6   0   7   1   4]
- [ 26  35 166  24  17  19  22]
- [  5  12  19 108   4   7  16]
- [  4   3   5   3  67   2   2]
- [ 12   0   2   2   2  38   9]
- [ 12   4   6   7   3   5  86]]
-Node Classification on random seed  2896 -> 0.575
-Confusion Matrix:
- [[ 79   1  10   4  10   7   8]
- [  5 123   5   2  22   2   7]
- [ 46  12 125  35  25  22  41]
- [ 19   3   9 102  10   5  13]
- [  0   7   2   1  59   2   2]
- [  4   2   3   4   1  41  10]
- [  6   2  31  11   8   6  46]]
-Node Classification on random seed  2897 -> 0.589
-Confusion Matrix:
- [[ 74   1   5   4   1  13  18]
- [  5 111   4   2   9   1   9]
- [ 30  16 142  33  27  32  36]
- [ 10   5  15  96   8  10  12]
- [  0   7   8   1  63   0   2]
- [  7   2   4   2   1  37  11]
- [  9   4  17   5  15  10  66]]
-Node Classification on random seed  2898 -> 0.601
-Confusion Matrix:
- [[ 91   2   3   5   2  15   9]
- [  4 131   3   0   4   3   3]
- [ 16  21 120  38  45  29  50]
- [  8  12  22  97   5   6   7]
- [  2   6   3   1  46   2   4]
- [  2   3   1   1   0  48   8]
- [ 13   8   9   8   6  10  68]]
-Node Classification on random seed  2899 -> 0.62
-Confusion Matrix:
- [[ 71   5   4   8   5   5  13]
- [  4 126   7   1  12   2   2]
- [ 20  21 139  28  32  18  54]
- [ 11   4  16 102  10   5  13]
- [  1   5   1   1  63   4   2]
- [ 10   0   3   0   2  44   9]
- [ 13   4   2   9   4  10  75]]
-Node Classification on random seed  2900 -> 0.614
-Confusion Matrix:
- [[ 74   0   3   5   4   4  15]
- [  4 113   8   0  30   4   6]
- [ 20  13 155  31  44  17  27]
- [ 10   9  11  95  11   3  20]
- [  1   2  12   1  56   1   3]
- [  1   3   3   7   1  41   6]
- [ 13   4   1   5   7  16  80]]
-Node Classification on random seed  2901 -> 0.654
-Confusion Matrix:
- [[ 77   0   2   5   6  13   9]
- [  4 118   5   2  24   0   9]
- [ 18  10 164  24  23  23  41]
- [  9   3  22 111   7   6   7]
- [  2   2   4   0  62   0   2]
- [  1   0   1   5   1  50   3]
- [  9   2   3  14   6  19  72]]
-Node Classification on random seed  2902 -> 0.6
-Confusion Matrix:
- [[ 76   5   1  10   5  16   6]
- [  3 136   2   6   6   3   3]
- [ 38  27 148  46  17  17  34]
- [ 20   5  23  81   2  11   9]
- [  3   9   2   1  52   0   5]
- [  3   0   2   0   1  44   6]
- [  9   3  10   9  10  12  63]]
-Node Classification on random seed  2903 -> 0.636
-Confusion Matrix:
- [[ 63   3   3   3   1  14  20]
- [  3 135  18   3   2   2   7]
- [ 13  16 156  35  24  17  50]
- [  5   2   8 115   6   2  24]
- [  1   5   8   0  45   1   6]
- [  8   0   1   3   2  50   4]
- [  9   3   7   2   8  15  72]]
-Node Classification on random seed  2904 -> 0.597
-Confusion Matrix:
- [[ 79   1   7  10   6   5   5]
- [  9 110  11   2   7   7   3]
- [ 30  12 155  40  27  22  43]
- [ 12   3  20  91   4   9  12]
- [  1   3   4   6  59   0   1]
- [ 17   4   1   0   0  38   5]
- [ 15   2  12   3   8  14  65]]
-Node Classification on random seed  2905 -> 0.655
-Confusion Matrix:
- [[ 64   6   1   4   3   6  16]
- [  5 131   7   1  20   4   2]
- [  8  14 181  22  18  23  47]
- [ 13  13  10 101   7   2  19]
- [  3   6   3   0  53   2   1]
- [ 10   0   4   3   1  34   4]
- [ 12   2   4   5   6   8  91]]
-Node Classification on random seed  2906 -> 0.638
-Confusion Matrix:
- [[ 60   4   2   4   9  12   9]
- [  1 144   4   5   1   5   4]
- [ 26  10 151  31  13  39  37]
- [  8   2  17 100   3   4  11]
- [  1   7   6   3  62   7   3]
- [  2   2   3   1   2  42   7]
- [ 11   2  12   7   7  18  79]]
-Node Classification on random seed  2907 -> 0.619
-Confusion Matrix:
- [[ 65   2   2  16   4   9   7]
- [ 13 115   6   6  13   1   4]
- [ 26  14 160  33  22  19  36]
- [  7   7  22  95   4   6  18]
- [  0   4   7   0  70   0   4]
- [ 11   0   3   2   1  44   2]
- [ 11   3   4  10   8  14  70]]
-Node Classification on random seed  2908 -> 0.621
-Confusion Matrix:
- [[ 77   4   1  10   3  20   6]
- [  2 114   4   7   8   7   3]
- [ 32  14 141  45  16  30  27]
- [ 10   0  12 109   5   5  12]
- [  0   4   9   1  63   2   3]
- [  8   0   0   1   1  53   1]
- [ 10   4   6   9  14  23  64]]
-Node Classification on random seed  2909 -> 0.639
-Confusion Matrix:
- [[ 50   4   5   9  10  14  10]
- [  1 123   9   2   4   1   1]
- [ 27  32 164  34  34   7  22]
- [  5   8  19 111   2   6   4]
- [  3   3   5   2  66   0   3]
- [  7   2   6   2   2  40  11]
- [ 10   3  14   6   1  11  85]]
-Node Classification on random seed  2910 -> 0.575
-Confusion Matrix:
- [[ 85   1   0   4   4   9   8]
- [  5  84   5   5  19   4   7]
- [ 18  27 148  52  19  23  39]
- [ 14   9  15 105   4   6  12]
- [  0  10   2   2  56   1   3]
- [  9   0   5   2   0  46   3]
- [  6   7  13  21  12  20  51]]
-Node Classification on random seed  2911 -> 0.592
-Confusion Matrix:
- [[ 61   9   5   1   3  12  11]
- [  5 112   4   3  12   2   4]
- [ 21  41 134  43  24  29  33]
- [  9   6  16 106   3   5  11]
- [  3   2   5   4  63   1   4]
- [  9   2   2   1   0  38   8]
- [  9   9  13   2   9  13  78]]
-Node Classification on random seed  2912 -> 0.598
-Confusion Matrix:
- [[ 74   2   5   2   3  11   4]
- [  2 127   8   1   2   3   8]
- [ 26  25 115  65  20  23  28]
- [ 35   5   8  97   6   9   4]
- [  1   7   4   0  58   1   2]
- [  3   1   1   5   1  48   9]
- [  4   3  13  21   8  13  79]]
-Node Classification on random seed  2913 -> 0.581
-Confusion Matrix:
- [[ 67   5   2   9   4   9  19]
- [  6 113  16   5   5   1   3]
- [ 25  17 141  42  23  19  60]
- [  3   3  13 106   3   7  12]
- [  0   4   9   0  54   2   2]
- [  7   4   1   2   0  37  14]
- [ 19   7  12   7  10   8  63]]
-Node Classification on random seed  2914 -> 0.61
-Confusion Matrix:
- [[ 77   1   6   5   1  16  11]
- [  1 126   9   5   6   1   2]
- [ 27  34 131  39  27  13  27]
- [ 15   4  23 107   6   7  13]
- [  0   8   5   0  68   1   3]
- [  3   2   0   1   2  40  11]
- [ 14   5  13   5   7  11  61]]
-Node Classification on random seed  2915 -> 0.604
-Confusion Matrix:
- [[ 72   3  15   4   2   8   3]
- [  3 130   3   1   9   9   8]
- [ 24  18 132  22  34  26  40]
- [ 11   2  28  98   3   8  11]
- [  0   7   8   5  59   0   3]
- [  9   1   1   1   0  44   8]
- [  7   9  14   4   9  15  69]]
-Node Classification on random seed  2916 -> 0.615
-Confusion Matrix:
- [[ 66   4   2   3   7  12  22]
- [  3 124   5   4  11   3   4]
- [ 18  33 136  51  14  12  52]
- [  7   4  13 124  11   4  12]
- [  1   6   3   0  49   0   3]
- [  6   0   2   3   1  38   5]
- [ 12   5   6   7   3  11  78]]
-Node Classification on random seed  2917 -> 0.621
-Confusion Matrix:
- [[ 58   1   8   4   3  18   9]
- [  4 123   1   4   7   8   4]
- [ 14  29 147  35  22  25  37]
- [ 13   1  17 107   4   7   8]
- [  3   8   8   2  68   1   1]
- [  5   0   1   0   0  53   3]
- [ 14   4   8   8   9  21  65]]
-Node Classification on random seed  2918 -> 0.637
-Confusion Matrix:
- [[ 63   4   6   6   5   6  10]
- [  2 137   6   4   5   3   5]
- [ 36  32 142  26  37  23  31]
- [ 10   7  12 102   0   3  13]
- [  1   0   7   0  73   1   2]
- [  0   0   3   0   2  47   3]
- [ 13   6   8   2   7  16  73]]
-Node Classification on random seed  2919 -> 0.611
-Confusion Matrix:
- [[ 70   1  10   4   4   9  10]
- [  3 132  10   0   2   3   4]
- [ 21  20 134  50  31  20  45]
- [  9   5  10  98   3   7  18]
- [  0   3   7   1  66   0   1]
- [ 10   0   1   0   1  41   6]
- [ 15   2   8  16   7  12  70]]
-Node Classification on random seed  2920 -> 0.601
-Confusion Matrix:
- [[ 83   1   3   3   5   5   6]
- [  1 118   5   5  18   5   3]
- [ 20  24 136  47  28  33  43]
- [ 19   4  15  91   8  12   4]
- [  1   7   4   4  59   2   1]
- [  5   3   2   0   1  49   2]
- [ 10   2  11   4   6  17  65]]
-Node Classification on random seed  2921 -> 0.585
-Confusion Matrix:
- [[ 74   2   3   7   8  11  13]
- [  4 128   8   5   1   6   7]
- [ 24  25 118  36  19  47  34]
- [ 10   4  15  96  14   5  18]
- [  1   7   1   2  62   3   3]
- [  7   1   3   2   6  37   3]
- [  8   3   7   3   7  22  70]]
-Node Classification on random seed  2922 -> 0.633
-Confusion Matrix:
- [[ 72   1   5   4   9  13   7]
- [  5 123   4   2  13   6   1]
- [ 41  27 143   7  17  37  33]
- [  8   3  15  93   7   7  19]
- [  1   4   3   0  75   1   3]
- [  2   0   1   4   0  44   4]
- [ 11   6   8   7   5  16  83]]
-Node Classification on random seed  2923 -> 0.623
-Confusion Matrix:
- [[ 76   5   7   9   3  11   4]
- [  7 106  14   3   7   1   5]
- [ 21  17 138  24  49  28  38]
- [  8   7  19 107   5   3   7]
- [  0   3   1   1  61   3   1]
- [  4   2   0   6   1  47  10]
- [  7   3   9  11   6   7  88]]
-Node Classification on random seed  2924 -> 0.645
-Confusion Matrix:
- [[ 71   4   4   6   1  11  11]
- [  4 133   5   4   3   2   6]
- [ 21  47 158  29  12  21  27]
- [ 20   2  16  97   7  11   8]
- [  0   8   3   1  63   0   1]
- [  4   2   0   2   1  40   6]
- [ 15   2  10   2   3  13  83]]
-Node Classification on random seed  2925 -> 0.562
-Confusion Matrix:
- [[ 52   0   3   4   6  20   6]
- [  4 122  12   1   7   2   6]
- [ 34  28 142  32  25  31  43]
- [ 28   6  27  70   9   1  15]
- [  0   4   4   1  55   2   7]
- [  2   3   2   0   0  46  11]
- [ 21   1  11   2   6  11  75]]
-Node Classification on random seed  2926 -> 0.592
-Confusion Matrix:
- [[ 76   2   1   9   3   8   3]
- [  6 135  10   1   8   4   2]
- [ 23  34 121  41  42  23  36]
- [  8   4  20  88  13   5  11]
- [  2   6   4   0  61   1   4]
- [  3   1   7   0   3  39   2]
- [ 12   4  16   5   5  16  72]]
-Node Classification on random seed  2927 -> 0.598
-Confusion Matrix:
- [[ 72   0   1   2   4   7  13]
- [  9 117   6   3   7   4   2]
- [ 20  38 139  61  15  17  31]
- [ 11   1  13 116   5   9  16]
- [  3  14   3   5  46   0   1]
- [  5   2   5   0   4  40   5]
- [ 17   4   7  12   6  14  68]]
-Node Classification on random seed  2928 -> 0.596
-Confusion Matrix:
- [[ 74   1   3  12   3   6   1]
- [  4 122   2   3   6   3   0]
- [ 30  31 136  64  40  15  31]
- [  9   6  12  93   5  11   9]
- [  1   6   3   2  70   0   1]
- [ 11   2   1   2   0  34   2]
- [ 25   7   4   7   9  14  67]]
-Node Classification on random seed  2929 -> 0.607
-Confusion Matrix:
- [[ 72   5   2  12   2  10   8]
- [  1 125   1   2   7   4   6]
- [ 27  17 171  19  33  17  36]
- [ 17  10  19  88   3   3  17]
- [  2  17   5   0  53   1   5]
- [  9   1   1   3   6  36   2]
- [  9   5   7  13  13  16  62]]
-Node Classification on random seed  2930 -> 0.648
-Confusion Matrix:
- [[ 76   1   3   4   0  14   6]
- [  1 137   4   1  14   0   2]
- [ 20  23 159  24  12  42  34]
- [  9   4  21 105   9   3  15]
- [  2   6   8   2  54   2   0]
- [  1   1   1   3   0  50   5]
- [ 12   4   7   3  13  16  67]]
-Node Classification on random seed  2931 -> 0.632
-Confusion Matrix:
- [[ 55   6   0   4   7  20   6]
- [  2 145   4   2   7   2   1]
- [ 19  19 148  52  28  15  40]
- [  7   7   5 109   2   6  25]
- [  0   4   3   1  71   1   4]
- [  3   0   2   0   2  40   6]
- [  9   1  11   5  10  20  64]]
-Node Classification on random seed  2932 -> 0.59
-Confusion Matrix:
- [[ 76   4   7   1   3   9  16]
- [ 10 112   6   0   6   4   3]
- [ 24  33 111  22  40  24  50]
- [ 16   3   5  90   7   9  22]
- [  2   7   4   0  69   0   1]
- [  5   4   5   0   0  47   5]
- [ 15   2   7   6   7  16  85]]
-Node Classification on random seed  2933 -> 0.628
-Confusion Matrix:
- [[ 66   1   3   2   7   6  22]
- [  2 120   5   5   9   4   2]
- [ 15  33 141  55  27  36  21]
- [  4   4  10 120   4   7  12]
- [  1   4   2   1  53   2   4]
- [  6   0   1   1   2  44   8]
- [  7   2  11   5   8  11  84]]
-Node Classification on random seed  2934 -> 0.6
-Confusion Matrix:
- [[ 80   2  16   4   4   7   3]
- [  5 155   7   2   4   0   5]
- [ 19  10 131  37  42  27  35]
- [  6   3  37  71  11   5  15]
- [  2  10   5   2  65   0   0]
- [ 11   0   2   5   0  36   4]
- [ 17   1  15   6   6   8  62]]
-Node Classification on random seed  2935 -> 0.596
-Confusion Matrix:
- [[ 79   2   8   2   6  12   3]
- [  2 113   5   4   5   3   3]
- [ 27  19 108  34  45  28  45]
- [ 15   0  28 103   9   6  17]
- [  1   2   0   0  65   2   1]
- [ 12   1   1   4   2  49   5]
- [  7   4   7   5   6  16  79]]
-Node Classification on random seed  2936 -> 0.635
-Confusion Matrix:
- [[ 75   7   4   4   8  10   9]
- [  1 126   3   4   3   4   2]
- [ 20  21 157  31  37  18  39]
- [  9   3  15  99   7   5  15]
- [  2   1   2   1  64   2   9]
- [  9   0   1   0   0  40   2]
- [ 19   1   4  16   3  14  74]]
-Node Classification on random seed  2937 -> 0.634
-Confusion Matrix:
- [[ 72   8   8   7   1   7   8]
- [  5 147   4   4   3   0   2]
- [ 28  22 130  26  26  19  34]
- [  7   4  25 104   9   6  15]
- [  3   8   7   0  67   0   1]
- [  9   1   1   7   0  39   2]
- [ 11   4   7  10   6  11  75]]
-Node Classification on random seed  2938 -> 0.559
-Confusion Matrix:
- [[ 67   6   2   8   5  11   2]
- [  1 109  13   4  10   1   3]
- [ 29  29 122  55  10  34  37]
- [ 12   6  15 100  16  12   6]
- [  2   6   4   0  57   0   6]
- [ 15   2   2   2   0  44   3]
- [ 19  10  13   6   5  19  60]]
-Node Classification on random seed  2939 -> 0.616
-Confusion Matrix:
- [[ 64   3   3   6   5  16   9]
- [ 11 125   4   7   7   5   0]
- [ 22  13 133  43  39  34  17]
- [  6   2  21 112   6   7  18]
- [  2   1   5   1  68   2   1]
- [  4   1   3   3   0  40   6]
- [ 14   1  11   6   6  13  74]]
-Node Classification on random seed  2940 -> 0.635
-Confusion Matrix:
- [[ 68   1  13   4   3   5  13]
- [  0 132   3   0   1   7   3]
- [ 21  38 166  21  23  15  44]
- [ 10   5  13  95   3   2  15]
- [  2   8   5   1  52   3   2]
- [  5   1   5   5   2  44  11]
- [  5   2  13   8  10  14  78]]
-Node Classification on random seed  2941 -> 0.645
-Confusion Matrix:
- [[ 69   1   4   7   3   4   7]
- [  3 136   9   5   4   5   0]
- [ 17  10 144  39  33  19  39]
- [ 11   1  28 103   6   6   5]
- [  1   9   3   0  62   1   2]
- [  6   1   4   2   0  55   4]
- [  9   0  11   9  13  14  76]]
-Node Classification on random seed  2942 -> 0.614
-Confusion Matrix:
- [[ 71   2   0   8   1  14   6]
- [ 12 134   6   9   6   0   6]
- [ 25  11 141  43  32  16  46]
- [ 12   5   3 106  12   4  13]
- [  5   8   0   0  51   4   2]
- [  5   1   1   4   3  34   7]
- [ 19   2   5   8   9  11  77]]
-Node Classification on random seed  2943 -> 0.586
-Confusion Matrix:
- [[ 66   0   9   3   2   9  11]
- [ 10 108   9   5   6   4   6]
- [ 19  30 122  39  31  28  49]
- [  6   6  13 115   2   6  21]
- [  4   2   4   6  50   1   0]
- [  9   4   3   0   0  44   6]
- [ 13  13   1   3   4  17  81]]
-Node Classification on random seed  2944 -> 0.581
-Confusion Matrix:
- [[ 68   2   3   1  10  14  15]
- [  3 113   3   1   7   0   4]
- [ 39  24 130  36  27  38  32]
- [ 24   3  15  99   3  11   7]
- [  2   5   3   4  51   1   2]
- [  2   2   7   2   2  48   5]
- [  7   6  11  15   3  18  72]]
-Node Classification on random seed  2945 -> 0.628
-Confusion Matrix:
- [[ 83   2  12   4   4  10   8]
- [  7 116   3   5  11   5   5]
- [ 28  34 145  31  34  10  24]
- [ 19   5  10 101   6   1   4]
- [  2  10   1   3  54   1   1]
- [  8   1   3   3   0  50   3]
- [ 10   1  19   4   6  14  79]]
-Node Classification on random seed  2946 -> 0.615
-Confusion Matrix:
- [[ 69   6   3  12   1   3  19]
- [  9 114  11   1   5   0   0]
- [ 20  38 147  26  21  14  39]
- [  5  11  23  94   5   9   4]
- [  5   7   5   1  55   1   4]
- [  5   5   0   9   3  49   8]
- [ 13   1   6   7   9  11  87]]
-Node Classification on random seed  2947 -> 0.634
-Confusion Matrix:
- [[ 61   8   6  12   2   8  14]
- [ 11 129   4   1  11   5   3]
- [ 20  23 145  40  22  24  31]
- [ 10   2   9 119   2   7  17]
- [  2   4   3   0  53   0   2]
- [  7   1   2   0   0  46   7]
- [  9   4   8   6   4  15  81]]
-Node Classification on random seed  2948 -> 0.641
-Confusion Matrix:
- [[ 69   0   3   8   4  13   7]
- [  3 122  13   4   6   6   4]
- [ 19  21 161  19  39  15  35]
- [  9  11  14  91   2   2  15]
- [  3   3   5   0  60   1   1]
- [  5   1   0   3   0  57   8]
- [ 11   4  10  13   2  17  81]]
-Node Classification on random seed  2949 -> 0.596
-Confusion Matrix:
- [[ 61   5   3   5   3  17   8]
- [  2 123   1   5  23   2   6]
- [ 28  26 117  42  31  20  45]
- [ 10   1   8 101   5   0  14]
- [  2   6   4   4  68   0   2]
- [  4   1   2   0   1  60   4]
- [ 14   8  12   4  13  13  66]]
-Node Classification on random seed  2950 -> 0.652
-Confusion Matrix:
- [[ 71   2   4  14   2  14   9]
- [  4 135   8   2   5   1   0]
- [ 17  26 156  30  22   9  40]
- [  8   0  16 115   1   2  15]
- [  2   7   6   1  52   1   1]
- [  8   2   1   2   1  59   5]
- [ 17   5   9   5  14  10  64]]
-Node Classification on random seed  2951 -> 0.569
-Confusion Matrix:
- [[ 54   4   5   5   2  17  25]
- [  8 136   4   1   7   1   3]
- [ 21  31 124  38  23  36  42]
- [ 21   5  13  85  11   5   9]
- [  3   4   3   1  58   0   2]
- [  9   3   7   0   0  37   5]
- [ 16   4  10   9   7  11  75]]
-Node Classification on random seed  2952 -> 0.581
-Confusion Matrix:
- [[ 77   2   3   1   6  17   3]
- [  2 128   6   6   9   7   1]
- [ 30  23 138  59  17  29  20]
- [ 16   7  15  85   3  10  13]
- [  2  11   3   1  50   1   2]
- [  8   1   6   3   2  51   1]
- [ 12   4  15   7   6  29  52]]
-Node Classification on random seed  2953 -> 0.613
-Confusion Matrix:
- [[ 74   1  11   8   3   6  14]
- [  4 125  11   2   8   8   1]
- [ 25  12 153  26  35  15  43]
- [  8   2  19  99   4   2  23]
- [  0   2   3   1  52   4   1]
- [  7   1   5   0   3  27  14]
- [ 19   8   4   7   9   8  83]]
-Node Classification on random seed  2954 -> 0.608
-Confusion Matrix:
- [[ 59   2   2   2   7  18  13]
- [  4 123   2   3  11   4   5]
- [ 29  22 129  27  30  22  52]
- [  2   5  17 106   9   3  22]
- [  0   7   3   0  64   3   2]
- [  7   1   1   0   0  49   6]
- [ 12   1   8   2  11  15  78]]
-Node Classification on random seed  2955 -> 0.604
-Confusion Matrix:
- [[ 69   2   5  10   4  12   9]
- [  3 128   5  10   6   2   3]
- [ 14  13 147  37  31  26  39]
- [ 20   3   8  97  14  12   9]
- [  0   8   4   3  59   0   1]
- [  5   2   3   3   1  34   8]
- [  8   3  18   8  13  11  70]]
-Node Classification on random seed  2956 -> 0.635
-Confusion Matrix:
- [[ 71   1   9   5   3   6   8]
- [  2 140  13   2  18   2   2]
- [ 20  22 156  31  23  16  41]
- [ 10   9  15 104   0  11  14]
- [  0   2   8   3  44   1   3]
- [  1   1   2   3   0  45   5]
- [  6   6   7   9  13  12  75]]
-Node Classification on random seed  2957 -> 0.625
-Confusion Matrix:
- [[ 67   1  19   2   4  18   7]
- [ 13 121   6   2   1   5   5]
- [ 22  23 143  23  22  29  41]
- [  8   2  18 116   4   2  10]
- [  1   7   5   0  65   1   3]
- [ 10   0   1   4   0  38   6]
- [ 11   2  11   6   7  13  75]]
-Node Classification on random seed  2958 -> 0.611
-Confusion Matrix:
- [[ 72   4  10   5   2  12   6]
- [ 16 101   8   7   9   4  10]
- [ 24  31 149  42  14  18  30]
- [ 10   5  12 112   6  12  16]
- [  5   2   8   2  55   0   1]
- [  4   0   4   2   4  47   4]
- [  8   4   8   5   2  13  75]]
-Node Classification on random seed  2959 -> 0.656
-Confusion Matrix:
- [[ 76   5   7   0   1   8   5]
- [  4 131   7   1  12   3   3]
- [ 31  19 145  30  27  35  25]
- [ 22   1   8 114   8   7   7]
- [  2   3   6   1  66   1   1]
- [  7   0   3   0   2  48   3]
- [ 13   2   4   5   4  11  76]]
-Node Classification on random seed  2960 -> 0.657
-Confusion Matrix:
- [[ 90   4   1   5   3   9  10]
- [  4 131   4   3   7   1   5]
- [ 22  18 135  30  23  17  40]
- [  9   1  16 108   5   3   6]
- [  2   8   4   2  70   2   4]
- [  6   3   4   0   2  46   7]
- [ 18   4   6   6   7  12  77]]
-Node Classification on random seed  2961 -> 0.618
-Confusion Matrix:
- [[ 72  12   1   2   2   7   4]
- [  4 124   8   0  20   4   4]
- [ 20  18 135  21  49  17  40]
- [  9   4  20  92   8   4  15]
- [  1   6   5   2  70   0   2]
- [  7   3   2   1   3  52   2]
- [ 17   4  16   1   6  11  73]]
-Node Classification on random seed  2962 -> 0.601
-Confusion Matrix:
- [[ 78   1   2   6   4  15  11]
- [  5 109   6   1  11   1   5]
- [ 30  19 149  41  23  21  36]
- [ 10   5  21  90  15   6   7]
- [  3  11   8   1  57   0   3]
- [  2   1   0   4   0  45   6]
- [  5   8  13   6   5  21  73]]
-Node Classification on random seed  2963 -> 0.618
-Confusion Matrix:
- [[ 80   2   2   4   4   9   7]
- [  8 126   4   0  21   3   1]
- [ 22  12 144  35  39  14  42]
- [  6   7  21  90   6   8  20]
- [  7   0   4   0  56   2   6]
- [  2   0   1   1   2  46   2]
- [ 15   5  12   4  11  11  76]]
-Node Classification on random seed  2964 -> 0.622
-Confusion Matrix:
- [[ 74   1  10   4   7   6  12]
- [ 12 114   4   0   6   4   4]
- [ 24  12 144  43  39  22  28]
- [  3   6  13 111   8   3  12]
- [  1   8   5   1  58   0   3]
- [  9   0   1   1   0  43   4]
- [ 21   3  15   7   8   8  78]]
-Node Classification on random seed  2965 -> 0.636
-Confusion Matrix:
- [[ 70   1   7   2   1  13  15]
- [  4 133  12   2   5   5   4]
- [ 28  15 136  43  30  14  38]
- [  4   2  17 114   7   7   8]
- [  0   3   2   5  58   1   4]
- [  7   4   1   2   1  45   2]
- [ 11   3   8  11   7   8  80]]
-Node Classification on random seed  2966 -> 0.624
-Confusion Matrix:
- [[ 61   0   4   4   1  12  18]
- [  7 131   5   1  21   2   3]
- [ 19  14 161  35  41  24  37]
- [  5   0  13 102   8   5  13]
- [  0   3   1   5  55   0   2]
- [  2   1   2   2   1  49   7]
- [  3   2  14  11  10  18  65]]
-Node Classification on random seed  2967 -> 0.618
-Confusion Matrix:
- [[ 64   3   5   3   2  19   4]
- [  3 138   3   2   5   7   2]
- [ 16  31 122  32  34  28  53]
- [  3  13   5 106  11   8  14]
- [  3   6   1   0  59   2   2]
- [  4   2   2   1   0  42   3]
- [  9   4   9   5   5  18  87]]
-Node Classification on random seed  2968 -> 0.606
-Confusion Matrix:
- [[ 62   2   2   4   4  17  12]
- [  0 119   2   4   8   7  11]
- [ 12  32 140  45  20  25  27]
- [ 33   1  14  99   4   3  15]
- [  2   5   6   3  67   1   4]
- [  6   2   3   1   0  46   3]
- [ 14   3   3  13   8  13  73]]
-Node Classification on random seed  2969 -> 0.624
-Confusion Matrix:
- [[ 62   8   7   1   6  18   4]
- [  4 135   2   4   2   2   3]
- [ 36  18 151  50  24  11  28]
- [ 16   0  18  95   1   3  20]
- [  1   6   8   2  69   1   6]
- [  5   0   3   1   0  43  11]
- [ 10   4   7   8   4  13  69]]
-Node Classification on random seed  2970 -> 0.57
-Confusion Matrix:
- [[ 76   3   2   4   2  12  12]
- [  9 113   3   3   7   0   1]
- [ 44  28 120  49  33  17  43]
- [ 15   4   7 108   4   8  16]
- [  5   6   1   2  53   1   6]
- [  8   0   3   4   0  45   4]
- [ 16   4  10   6  12  16  55]]
-Node Classification on random seed  2971 -> 0.622
-Confusion Matrix:
- [[ 70   4   8   3   2  10  10]
- [  3 134   6   0  10   3   5]
- [ 24  14 144  31  27  43  47]
- [  3   5  16 108   8   8   8]
- [  2   7   7   0  56   0   4]
- [  8   3   3   0   0  36   5]
- [ 10   3   9   3   8   8  74]]
-Node Classification on random seed  2972 -> 0.65
-Confusion Matrix:
- [[ 81   3   3   8   5   6  13]
- [  5 138   5   2  13   0   2]
- [ 17  23 165  31  29  25  30]
- [  6   1  17  95   6   4  23]
- [  0   2   2   2  72   0   1]
- [  4   1   3   2   4  33   7]
- [ 10   1   5  12   4  13  66]]
-Node Classification on random seed  2973 -> 0.644
-Confusion Matrix:
- [[ 74   4   6   3   2   9   2]
- [  3 120   4   4  12   1   6]
- [ 18  23 160  23  28  25  45]
- [ 14  12  17  92   5   5  14]
- [  2   1   2   2  66   1   3]
- [  7   0   1   0   1  52   3]
- [ 16   6   8   6   4   8  80]]
-Node Classification on random seed  2974 -> 0.625
-Confusion Matrix:
- [[ 70   1   4   5   4   9   4]
- [ 10 117   0   0  10   3   5]
- [ 18  23 149  27  22  25  53]
- [ 13   4  11 116   4   7  17]
- [  2   4   3   0  64   3   2]
- [  8   1   5   1   2  40   1]
- [ 16   3  13   6  11  15  69]]
-Node Classification on random seed  2975 -> 0.619
-Confusion Matrix:
- [[ 70   0   7   6   2   9   9]
- [  1 132  13   2   5   3   5]
- [ 29  10 109  60  14  16  50]
- [  5   3   9 121   2   3  12]
- [  2   0   5   1  73   0   0]
- [  5   4   0   3   0  45   6]
- [ 24   6  14   5  10  21  69]]
-Node Classification on random seed  2976 -> 0.601
-Confusion Matrix:
- [[ 60   1   2   5   4   9   7]
- [  2 141  10   1   7   5  10]
- [ 26  18 137  38  23  24  37]
- [ 22   5  19  97   9   3  13]
- [  1   8   3   2  53   2   6]
- [  5   2   1   3   3  38  12]
- [  7   1   7  17   5  14  75]]
-Node Classification on random seed  2977 -> 0.605
-Confusion Matrix:
- [[ 64   1   3   5  12  18   5]
- [  1 132   8   0   5   2   2]
- [ 22  21 136  44  21  38  38]
- [ 10   7  17  99   2  12  10]
- [  1   8   1   3  53   0   6]
- [  5   2   3   1   3  39   1]
- [  7   4  10   2   5  29  82]]
-Node Classification on random seed  2978 -> 0.612
-Confusion Matrix:
- [[ 77   1   5   1   5  10   4]
- [  2 124  13   3  12   2   2]
- [ 23  27 139  50  17  18  37]
- [ 21   1   9  94   8  17  13]
- [  1   2   3   2  63   0   3]
- [  8   3   4   3   0  44   1]
- [ 17   3   5   6   8  18  71]]
-Node Classification on random seed  2979 -> 0.619
-Confusion Matrix:
- [[ 74   2  10   8   5   7   6]
- [  7 114   2   0  14   5   1]
- [ 27  22 148  31  35  13  42]
- [  6   3  16 115   7   3  16]
- [  2   8   5   2  59   0   2]
- [ 16   0  10   2   0  38   5]
- [ 13   1   3   4   8  12  71]]
-Node Classification on random seed  2980 -> 0.597
-Confusion Matrix:
- [[ 84   1   2   5   4  10   8]
- [  2 128   8   2  19   6   5]
- [ 31  25 130  40  16  32  37]
- [ 23   0   9  88   3  11  11]
- [  1   4   4   3  68   0   3]
- [  4   1   1   6   0  33  14]
- [  7   1   8  11  17   8  66]]
-Node Classification on random seed  2981 -> 0.634
-Confusion Matrix:
- [[ 63   2  11  11   0   8   6]
- [  7 120   5   1   9   4   1]
- [ 19  25 156  18  30  22  42]
- [ 16   4  11  98   5  10  12]
- [  0   4   5   0  61   0   6]
- [  7   1   3   4   3  48   2]
- [  8   5   8  10   6  15  88]]
-Node Classification on random seed  2982 -> 0.634
-Confusion Matrix:
- [[ 80   2   3   2   3  18   3]
- [  5 120   5   2   5   5  10]
- [ 21  34 158  36  16  25  38]
- [  4   4  16 103   3   4   8]
- [  1   5   4   1  60   5   2]
- [ 11   2   5   3   1  41   1]
- [ 18   7   1   8   6  13  72]]
-Node Classification on random seed  2983 -> 0.585
-Confusion Matrix:
- [[ 53   0   3  16   3  17  15]
- [  5 109  10   5   6   6   0]
- [ 24  29 139  37  37  20  44]
- [  9   4  14 103   2  11   7]
- [  1   6   1   0  62   1   1]
- [  4   0   5   6   2  36   3]
- [ 14   4   9  13  10  11  83]]
-Node Classification on random seed  2984 -> 0.571
-Confusion Matrix:
- [[ 58   1   4   8   2  10  15]
- [ 11 108   9   5  11   4   4]
- [ 17  41 121  46  34  16  53]
- [ 20   1  20  89   5  19   7]
- [  1   3   1   1  68   0   1]
- [  4   0   3   1   0  44   5]
- [ 12   8   5   2   5  14  83]]
-Node Classification on random seed  2985 -> 0.627
-Confusion Matrix:
- [[ 73   3   9   2   3  19   9]
- [  0 127   3   1  14   0   2]
- [ 21   8 152  31  34  10  42]
- [ 18   5  20 104   4   5  12]
- [  2  10   3   0  53   1   2]
- [  4   1   3   0   0  54   5]
- [ 14   2  12  13  10  16  64]]
-Node Classification on random seed  2986 -> 0.6
-Confusion Matrix:
- [[ 57   2   4  13   4   6   7]
- [  5 128   1   3  11   4   2]
- [ 31  41 131  32  36  18  34]
- [ 22   3   4  95  16   8  10]
- [  0   6   2   0  70   2   2]
- [  9   3   0   4   0  42   5]
- [  5   2   2   6  13  22  77]]
-Node Classification on random seed  2987 -> 0.629
-Confusion Matrix:
- [[ 65   0   9   7   1  15  11]
- [ 10 117   8   2   4   3   5]
- [ 19  27 135  42  28  33  21]
- [ 10   5  10 121   5   8   6]
- [  0   6   5   3  55   3   0]
- [  7   0   5   2   0  57   3]
- [  8   1   8   9   5  17  79]]
-Node Classification on random seed  2988 -> 0.611
-Confusion Matrix:
- [[ 66   7   2   6   2  12   3]
- [  4 136   2   4  12   1   1]
- [ 26  33 134  37  26  15  44]
- [ 19   5  27  90   2   5  18]
- [  5   5   2   1  58   0   0]
- [  1   2   4   3   0  48   2]
- [ 20   2   7   8   5   9  79]]
-Node Classification on random seed  2989 -> 0.595
-Confusion Matrix:
- [[ 58   2   5   5   2  12   7]
- [  4 139  12   0   3   4   4]
- [ 25  19 121  68  18  32  44]
- [ 17   1   7 107   9   5  12]
- [  4   8   4   2  59   1   5]
- [  1   2   2   4   0  49   2]
- [  5   4   5  14   7  18  62]]
-Node Classification on random seed  2990 -> 0.612
-Confusion Matrix:
- [[ 74   3   2   4   3   8   9]
- [  3 122  14   3   5   8   0]
- [ 24  17 142  31  30  19  36]
- [ 22   5  14 111  14   8   6]
- [  1   9   5   2  52   2   3]
- [ 10   1   1   0   1  39   3]
- [ 17   5   8   7   8  17  72]]
-Node Classification on random seed  2991 -> 0.584
-Confusion Matrix:
- [[ 78   4   8   5   7   6   2]
- [  2 144   4   9   3   5   6]
- [ 31  22 115  42  36  20  42]
- [ 15   7  18  96  10   7   8]
- [  0   9   3   2  56   0   2]
- [ 13   0   7   0   0  31   6]
- [ 18   2  10   5   6  14  64]]
-Node Classification on random seed  2992 -> 0.638
-Confusion Matrix:
- [[ 84   4   7   2   2  10   7]
- [  2 135   7   7  10   0   7]
- [ 26  32 129  36  27  25  21]
- [  5   3   7 110   3   7  15]
- [  0  12   1   4  65   3   1]
- [  3   2   1   1   0  45   5]
- [ 17   5  12   6   8   9  70]]
-Node Classification on random seed  2993 -> 0.578
-Confusion Matrix:
- [[ 79   1   7   3   8  12   8]
- [  3 129   9   8   8   1   1]
- [ 26  25 114  46  31  30  43]
- [ 10   5  14 107   8   4  23]
- [  0   6   4   1  43   3   1]
- [  8   1   4   1   1  35   2]
- [  6   5  14  10   3  18  71]]
-Node Classification on random seed  2994 -> 0.631
-Confusion Matrix:
- [[ 85   3   5   5   4  11   3]
- [  1 124   5   2  11   4   4]
- [ 30  13 145  34  21  34  44]
- [ 21   1  10 111   1   4   9]
- [  1  11   7   2  52   1   1]
- [  8   2   0   1   1  41   3]
- [ 15   6   7   7   2  14  73]]
-Node Classification on random seed  2995 -> 0.63
-Confusion Matrix:
- [[ 75   4   0   7   2   6  17]
- [  7 116  14   0   9   6   7]
- [ 24  16 159  21  30  19  41]
- [  9   2  14 110   2   8  11]
- [  0  10   3   2  48   2   0]
- [  4   6   2   3   0  49   3]
- [  8   6   5  11  17  12  73]]
-Node Classification on random seed  2996 -> 0.626
-Confusion Matrix:
- [[ 66   5   1   2   9   7  18]
- [  3 129   5   0   6   2   8]
- [ 10  22 140  40  24   8  56]
- [ 18  15  16  92   2   3  15]
- [  0   6   2   0  72   1   1]
- [  9   3   1   0   1  42   7]
- [ 17   2   5  13   6   5  85]]
-Node Classification on random seed  2997 -> 0.55
-Confusion Matrix:
- [[ 70   8   2  10   2  10  17]
- [  4 109   6   6   1   4   3]
- [ 27  28 137  53  27  14  36]
- [ 16   3  20  96   2   7  15]
- [  2  10   6   0  53   1   1]
- [ 11   1   2   1   1  39   8]
- [ 14   5   7  21  23  15  46]]
-Node Classification on random seed  2998 -> 0.665
-Confusion Matrix:
- [[ 67   3   0   6   2  12   6]
- [  3 134   9   1  10   0   3]
- [ 45  11 174  25  16  20  20]
- [ 22   1  12 110   3   2  10]
- [  1   5   5   1  59   1   2]
- [  5   0   1   1   4  43   5]
- [ 11   5  10   7   5  24  78]]
-Node Classification on random seed  2999 -> 0.631
-Confusion Matrix:
- [[ 73   3   3   6   6   5  12]
- [  4 122   5   0  14   0   1]
- [ 18  22 144  52  23  17  39]
- [ 20   1  13 105   1   6  13]
- [  2   8   3   0  63   2   2]
- [ 10   1   2   3   2  44   3]
- [  7   1   7  12   6  14  80]]
-Node Classification on random seed  3000 -> 0.621
-Confusion Matrix:
- [[ 79   0   6   2   3  15   7]
- [  5 112   6   8   6   1  10]
- [ 20  17 126  39  24  23  55]
- [  4   2  16 127   2   4  14]
- [  2   9   0   1  57   4   2]
- [  1   0   2   1   0  60   5]
- [  9   2   8  25   5  14  60]]
-Node Classification on random seed  3001 -> 0.614
-Confusion Matrix:
- [[ 71   3   1   6   3  19   3]
- [  8 119   8   5   6   3   6]
- [ 33   6 137  34  27  30  38]
- [ 15   4   5 101   7  11  12]
- [  0   6   4   2  66   1   5]
- [  5   2   4   0   1  43   4]
- [ 12   2  14   6   6  19  77]]
-Node Classification on random seed  3002 -> 0.634
-Confusion Matrix:
- [[ 77   3   8  11   5   7   7]
- [  6 141   9   1   1   1  12]
- [ 20  28 139  34  20  23  25]
- [ 12   4  21  99   5   3   8]
- [  2   8   5   0  46   1   3]
- [  5   2   1   0   0  50   4]
- [  6   5  14  10   8  18  82]]
-Node Classification on random seed  3003 -> 0.629
-Confusion Matrix:
- [[ 59   2   5   7   3  13   9]
- [  2 122   9   6   5   2   6]
- [ 20  28 165  24  25  21  41]
- [ 15   4   4 115  15   6  14]
- [  1   5   6   1  51   0   3]
- [  2   0   2   1   3  44   2]
- [ 10   2  11  13   3  20  73]]
-Node Classification on random seed  3004 -> 0.55
-Confusion Matrix:
- [[ 63   3   1   7   7   8  15]
- [  3 113   5   3  14   2   3]
- [ 24  15 127  38  28  11  57]
- [ 27   2  25  73  13   4  20]
- [  4   2   3   2  65   3   2]
- [  7   2   1   1   0  43  14]
- [ 12   1   7   2  44   8  66]]
-Node Classification on random seed  3005 -> 0.646
-Confusion Matrix:
- [[ 68   1   5   8   3  12   7]
- [  5 127   7   3  10   3   4]
- [ 18  28 148  39  28  24  22]
- [  7   4  12 116   4   7  14]
- [  1   2   2   1  69   0   0]
- [  6   0   3   1   0  41   7]
- [  5   4  10   6  11  20  77]]
-Node Classification on random seed  3006 -> 0.58
-Confusion Matrix:
- [[ 79   1   7   4   1   9   5]
- [  7 117   9   5  10   3   2]
- [ 28  24 126  33  32  38  35]
- [ 32   1  11  77   8   5  17]
- [  1   5   3   1  68   2   3]
- [  5   0   1   3   0  44   2]
- [ 12   4   9  10   5  27  69]]
-Node Classification on random seed  3007 -> 0.629
-Confusion Matrix:
- [[ 66   1  11   6   5  11  13]
- [  8 120  10   4   5   4   3]
- [ 16  19 151  27  24  34  27]
- [  6   2  11 104   5  10  14]
- [  0   9   3   2  66   1   4]
- [  5   2   3   4   2  44   6]
- [ 19   3   9   3  13   7  78]]
-Node Classification on random seed  3008 -> 0.627
-Confusion Matrix:
- [[ 65   1   0   2  12  16   6]
- [  1 132  10   3   6   1   2]
- [ 19  32 135  35  17  27  35]
- [ 11   3  10 110   9   2  23]
- [  0   8   4   2  56   1   0]
- [ 13   1   1   3   1  36   3]
- [ 13   4   3   5  11  17  93]]
-Node Classification on random seed  3009 -> 0.603
-Confusion Matrix:
- [[ 79   2   3   7   3   8  12]
- [  5 127   2   3   3   4   3]
- [ 22  21 147  32  33  23  46]
- [ 15   8  16 100   1   3  11]
- [  1  14   7   3  48   2   4]
- [  5   2   2   1   1  41   6]
- [ 12   5  10  16   3  17  61]]
-Node Classification on random seed  3010 -> 0.588
-Confusion Matrix:
- [[ 56   0  11  13   1  20   8]
- [  7 139   3   2   4   4   4]
- [ 22  13 133  51   8  32  43]
- [ 16   6  20  88  12   8  11]
- [  3   8   3   1  50   6   2]
- [  0   2   2   1   3  43   7]
- [ 10   7   8  10   5  15  79]]
-Node Classification on random seed  3011 -> 0.63
-Confusion Matrix:
- [[ 62   3   2   7   4   9  20]
- [  2 140   6   2   3   3   2]
- [ 32  31 150  34  35  10  34]
- [  4   3  18 115   2   4  10]
- [  2  13   1   0  62   3   1]
- [  7   0   1   1   2  39   5]
- [  5   6  10  13  10  10  62]]
-Node Classification on random seed  3012 -> 0.628
-Confusion Matrix:
- [[ 72   3   3   3   6  17   3]
- [  6 118   6   2   3   5   0]
- [ 38  28 171  12  23  18  41]
- [ 10   7  16  98   5   3  11]
- [  1  13   5   0  56   1   4]
- [ 12   1   3   3   5  45   4]
- [ 18   3   3   3   4  20  68]]
-Node Classification on random seed  3013 -> 0.659
-Confusion Matrix:
- [[ 84   1   0   3   2  12   5]
- [  2 130   3   8   6   1   4]
- [ 25  19 141  41  22  29  36]
- [  9   0  13 117   1   5  16]
- [  1   5   3   3  53   2   3]
- [  6   1   1   5   1  53   6]
- [  7   4  18   6   2   4  81]]
-Node Classification on random seed  3014 -> 0.597
-Confusion Matrix:
- [[ 70   2   4   0   5  11   6]
- [  1 133   4   5   6   2   6]
- [ 21  21 125  39  30  33  40]
- [ 21   7  25  90  12   6  12]
- [  0   5   4   1  56   0   4]
- [  8   2   5   3   0  37   4]
- [ 13   8   9   4   4  10  86]]
-Node Classification on random seed  3015 -> 0.59
-Confusion Matrix:
- [[ 45   6   6   4   3   9  21]
- [  4 123   8   4   9   4   0]
- [ 16  17 137  36  38  22  45]
- [  6   5  12 113   7   9  20]
- [  2  10   5   1  57   0   1]
- [  5   1   1   0   1  50   6]
- [  5   7  12  10  19  13  65]]
-Node Classification on random seed  3016 -> 0.572
-Confusion Matrix:
- [[ 57   6   7  12   0   5  22]
- [  3 124   3   4   4   3   9]
- [ 29  25 116  47  35  20  57]
- [ 14   0  15  90   3   9  15]
- [  0   7   3   1  63   2   5]
- [  1   3   0   0   1  40   9]
- [ 13   1   7  10   2  16  82]]
-Node Classification on random seed  3017 -> 0.609
-Confusion Matrix:
- [[ 70   4   3   6   5  11   5]
- [  6 109   4   0  16   6   6]
- [ 30  30 133  25  16  37  50]
- [  5   6  17 111   5   4  11]
- [  0   5   1   1  69   0   1]
- [  7   3   0   3   0  42   7]
- [ 10   6   7   6  12  14  75]]
-Node Classification on random seed  3018 -> 0.627
-Confusion Matrix:
- [[ 68   4   8   5   5   2  17]
- [  2 135   6   1   8   2   3]
- [ 32  21 121  35  35  17  34]
- [  6   5  15 106   3   4  19]
- [  3  10   3   2  62   3   3]
- [  4   0   2   2   0  42  11]
- [  7   4   9   4   7  10  93]]
-Node Classification on random seed  3019 -> 0.622
-Confusion Matrix:
- [[ 80   0   3   4   1  12   8]
- [  8 104   8   3  10   0   5]
- [ 28  27 147  24  28  22  40]
- [ 10   6  20 111   3   4  12]
- [  3   4   4   1  60   3   3]
- [  4   3   2   1   0  36   6]
- [ 10   5  11   3  10  19  84]]
-Node Classification on random seed  3020 -> 0.575
-Confusion Matrix:
- [[ 53   9   0   6   2  15  16]
- [  9 122   3   2   7   3   5]
- [ 21  22 118  31  28  47  50]
- [  9   2  20  96   4   5  24]
- [  4   5   3   1  59   0   4]
- [  0   2   3   5   0  54   2]
- [ 19   4   2   6  12  13  73]]
-Node Classification on random seed  3021 -> 0.633
-Confusion Matrix:
- [[ 66   3   2   8   3   7  12]
- [  3 130   6   4   4   2   1]
- [ 20  28 135  25  32  31  47]
- [  9   7  11 114   2   6   9]
- [  0   8   4   3  64   0   3]
- [  5   1   0   0   0  41   8]
- [  9   8   6  10   7  13  83]]
-Node Classification on random seed  3022 -> 0.623
-Confusion Matrix:
- [[ 78   3   5   1   2   9  21]
- [  5 118   8   4  12   1   3]
- [ 32  18 122  14  32  20  56]
- [ 10   5  13 113   0   8  24]
- [  1   8   2   3  52   0   1]
- [  2   0   1   1   0  44   5]
- [ 11   4   5  15   4   8  96]]
-Node Classification on random seed  3023 -> 0.649
-Confusion Matrix:
- [[ 82   2   7   2   2   9   7]
- [  2 127   5   2  10   2   3]
- [ 34  21 157  26  28   8  35]
- [ 15   6  11 102   4   4  21]
- [  1   7   3   1  65   0   7]
- [  6   2   1   0   0  41   8]
- [ 16   3  13   9   6   2  75]]
-Node Classification on random seed  3024 -> 0.634
-Confusion Matrix:
- [[ 75   0   3   2   4  26   5]
- [  6 137   4   0   3   1   5]
- [ 17  26 155  40  13  19  42]
- [ 22   4  17  84   2  10  12]
- [  2   9   5   1  57   1   1]
- [  0   1   6   4   0  44   5]
- [ 12   1   8   5   7  15  82]]
-Node Classification on random seed  3025 -> 0.605
-Confusion Matrix:
- [[ 69   0   1   2   2  19   8]
- [  2 127   1   2   6   4   2]
- [ 30  20 127  52  32  31  32]
- [ 13   1  14  99   4   7  16]
- [  4   6   4   2  55   1   4]
- [  6   0   6   7   0  39   4]
- [ 16   3   7   4   5  15  89]]
-Node Classification on random seed  3026 -> 0.657
-Confusion Matrix:
- [[ 75   5   3   8   5   8   0]
- [  4 133   4   3   3   1   1]
- [ 16  15 158  47  28  16  24]
- [ 18  11  11  98   6  10  12]
- [  0  10   6   0  54   0   3]
- [  2   0   0   3   0  56   1]
- [ 16   2  18   9   3  11  83]]
-Node Classification on random seed  3027 -> 0.623
-Confusion Matrix:
- [[ 76   1   3   4   0  19   4]
- [  8 130  14   3   8   4   3]
- [ 24  24 161  23  25  28  30]
- [ 11   7  13  81  11  12   9]
- [  0   4   4   1  58   2   3]
- [  9   5   1   0   0  45   4]
- [ 19   5  13   0   6  13  72]]
-Node Classification on random seed  3028 -> 0.588
-Confusion Matrix:
- [[ 69   5   7   6   5  13   7]
- [ 16 124   9   1   4   2   8]
- [ 16  29 137  33  40  12  53]
- [  4  10  19  79  12  14  14]
- [  1   3   5   0  58   1   2]
- [  3   1   5   0   0  50   2]
- [ 10   5  11   5   5  14  71]]
-Node Classification on random seed  3029 -> 0.591
-Confusion Matrix:
- [[ 74   2   5   1  11   6   7]
- [  6 122   1   5  13   1   3]
- [ 23  14 131  40  39  32  37]
- [ 22   4  19  91  11   5   6]
- [  3   6   2   4  71   0   1]
- [ 17   1   0   0   2  36   5]
- [ 19   2  12   7   7   8  66]]
-Node Classification on random seed  3030 -> 0.603
-Confusion Matrix:
- [[ 89   4   8   7   4  13   8]
- [  0 106  13   3  21   0   6]
- [ 32  22 127  45  38  11  27]
- [  9   0  13 112   9   6   6]
- [  0   7   3   1  60   0   0]
- [  3   6   1   3   0  48   4]
- [  6   4  17  18   5  14  61]]
-Node Classification on random seed  3031 -> 0.619
-Confusion Matrix:
- [[ 58   6   9   6   5   4   6]
- [  2 131   4   0  10   0   5]
- [ 27  15 169  40  16  19  38]
- [ 11   4  37  82   9   6   3]
- [  1   6   2   3  55   1   7]
- [  9   1   1   2   0  45   9]
- [ 13   2  13   7   5  17  79]]
-Node Classification on random seed  3032 -> 0.626
-Confusion Matrix:
- [[ 82   3   5   6   2   8   5]
- [ 13 132   7   5   8   2   4]
- [ 15  11 144  46  41  20  24]
- [ 10   3   8 105   2  11   3]
- [  2   4   2   4  51   0   6]
- [  9   3   5   0   0  44   6]
- [ 12   2   7   9   6  35  68]]
-Node Classification on random seed  3033 -> 0.654
-Confusion Matrix:
- [[ 64   0   2   2   1  22  10]
- [  3 130   6   2   4   8   0]
- [ 24  19 138  26  28  34  32]
- [ 12   4  16 108   4   4  13]
- [  3   7   2   0  74   2   3]
- [  2   1   1   5   0  48   2]
- [  1   3   8   3   6  21  92]]
-Node Classification on random seed  3034 -> 0.59
-Confusion Matrix:
- [[ 57   4   9  10   3  23   6]
- [ 10 132   1   3   1   5   6]
- [ 32  20 150  23  14  30  49]
- [ 16   6  12  85   5   6  28]
- [  4  10   1   1  55   1   1]
- [  5   1   1   2   2  39   4]
- [ 15   4   4   2   9  21  72]]
-Node Classification on random seed  3035 -> 0.634
-Confusion Matrix:
- [[ 96   7   6   1   4   7   3]
- [  3 113   9   1  15   6   5]
- [ 22  17 141  18  31  16  37]
- [ 15   3  20  90  10   6  14]
- [  1   4   2   0  62   1   4]
- [  3   2   3   2   3  42   6]
- [ 19   7   5   8   6  14  90]]
-Node Classification on random seed  3036 -> 0.635
-Confusion Matrix:
- [[ 78   5   2   7   2   8  14]
- [  4 125   5   6   0   5   6]
- [ 33  22 141  43  20  24  32]
- [  7   2   9 105   3   8  15]
- [  0   7   6   4  54   3   2]
- [  7   1   0   2   0  49   5]
- [ 11   0   9   6   7  13  83]]
-Node Classification on random seed  3037 -> 0.628
-Confusion Matrix:
- [[ 61   2   7  11   4  15   7]
- [  7 121   6   6   4   5   3]
- [ 18  21 145  24  21  26  39]
- [  5   5  19 104   5   4  13]
- [  4   5   1   1  68   0   5]
- [  5   0   4   3   1  50   4]
- [ 10   7   6   6  19  14  79]]
-Node Classification on random seed  3038 -> 0.612
-Confusion Matrix:
- [[ 77   0   2  13   0   9   4]
- [  4 113   1  10  12   0   4]
- [ 14  44 145  25  20  15  38]
- [ 12   3  15 112   5   7  18]
- [  1   5   5   7  47   2   1]
- [  6   2   1   4   0  38  10]
- [ 17   3   2  20  13  14  80]]
-Node Classification on random seed  3039 -> 0.64
-Confusion Matrix:
- [[ 66   5   4   3  10   8   4]
- [  5 131   4   3   6   0   0]
- [ 12  31 140  39  38  19  29]
- [ 11   3  15 111   4   3   9]
- [  1   6   6   1  61   2   5]
- [  6   2   6   0   0  41   8]
- [ 11   7   7  11   4  12  90]]
-Node Classification on random seed  3040 -> 0.579
-Confusion Matrix:
- [[ 67   4   2  10   6   7   1]
- [  3 112   8   2  13   5   1]
- [ 52  25 130  28  33  25  37]
- [ 10   7  16 100   6  11   5]
- [  2   6   4   1  59   0   0]
- [  8   0   4   0   3  53   5]
- [ 20   4  11  19   8   9  58]]
-Node Classification on random seed  3041 -> 0.631
-Confusion Matrix:
- [[ 81   5   2   4   4   8   4]
- [  7 105   7   4  10   1   7]
- [ 24  25 171  16  31  26  21]
- [ 17   1  18  96   7   7  11]
- [  1   7  10   0  61   1   4]
- [  8   2   0   1   3  50   3]
- [ 10   3   9   8   6  26  67]]
-Node Classification on random seed  3042 -> 0.576
-Confusion Matrix:
- [[ 68   0  10   3   3  16  13]
- [  2 124   6   5   3   6   4]
- [ 26  32 118  54  15  34  28]
- [ 22   6  17  85   4  12  17]
- [  3   4   4   2  64   2   2]
- [  4   0   1   2   0  45  15]
- [  6   4   9   5   6  17  72]]
-Node Classification on random seed  3043 -> 0.583
-Confusion Matrix:
- [[ 56   6   3   3   5  11  18]
- [  3 121   6   1   8   4   7]
- [ 24  23 121  50  25  28  56]
- [  3   2  17 117   5   7  16]
- [  1   5   2   1  62   1   2]
- [  4   0   3   2   6  35   8]
- [  4   3   3  11  10  20  71]]
-Node Classification on random seed  3044 -> 0.644
-Confusion Matrix:
- [[ 68   3   7   8   4  15   5]
- [  4 137   4   6   3   1   5]
- [ 34  18 133  22  19  35  28]
- [  8   5  16 103   2   8  21]
- [  3  10   1   4  66   0   1]
- [  1   0   1   0   2  52   6]
- [  6   5   8   3   7  17  85]]
-Node Classification on random seed  3045 -> 0.618
-Confusion Matrix:
- [[ 71   1   1  12   4  17   7]
- [  5 109   5   4   6  11   6]
- [ 29  12 157  50  20  11  32]
- [ 11   2  11 117   4   7   4]
- [  2   9   5   4  55   0   1]
- [  8   4   1   5   0  32  10]
- [  9   6   4  18   9  15  77]]
-Node Classification on random seed  3046 -> 0.613
-Confusion Matrix:
- [[ 58   2   1   5   0  24  16]
- [  7 142   2   2   1   4   9]
- [ 28  23 131  27  16  38  40]
- [  6   8  20  96   1   5  15]
- [  2   4   8   2  50   3   5]
- [  5   0   0   3   0  49  12]
- [ 12   0  13   3   3  12  87]]
-Node Classification on random seed  3047 -> 0.648
-Confusion Matrix:
- [[ 68   1   3  14   6  11  11]
- [  2 123   9   2   6   3   8]
- [ 20  12 182  21  18  14  44]
- [ 15   7  15 110   2   6  13]
- [  1   9   2   6  48   0   1]
- [  5   0   9   4   0  36   2]
- [ 10   2   8   6   5  19  81]]
-Node Classification on random seed  3048 -> 0.581
-Confusion Matrix:
- [[ 71   1   3   4   8   7  14]
- [  7 115   9   2   6   2   6]
- [ 26  24 128  35  27  42  46]
- [ 17   3  11 100   6   3  13]
- [  1   9   6   1  62   3   0]
- [  9   3   0   2   2  46   1]
- [ 15   2  11  11   6  15  59]]
-Node Classification on random seed  3049 -> 0.634
-Confusion Matrix:
- [[ 71   8   3   9   6  14   9]
- [  3 117   4   4   8   0   6]
- [ 20  22 167  24  25  15  44]
- [ 15   2  17  92   8  14   6]
- [  1   8   0   2  47   2   3]
- [  2   0   0   3   0  53   4]
- [  6   4  11  12   3  19  87]]
-Node Classification on random seed  3050 -> 0.648
-Confusion Matrix:
- [[ 68   1   3   8   0  18   9]
- [  3 123  15   3  10   5   3]
- [ 20  20 185  45  19  14  26]
- [  7   3   8 100   8   7  13]
- [  1   7   3   0  61   3   2]
- [  1   1   1   4   1  39   7]
- [  9   3   4  11   2  24  72]]
-Node Classification on random seed  3051 -> 0.632
-Confusion Matrix:
- [[ 75   4   1   4   3  15   2]
- [  1 114   3   2   5   2   5]
- [ 20  36 146  35  30  22  29]
- [ 10   3  19 106   2  11  11]
- [  1   6   3   1  71   3   2]
- [  4   5   1   4   2  44   8]
- [  8   7   7   9   5  17  76]]
-Node Classification on random seed  3052 -> 0.638
-Confusion Matrix:
- [[ 77   2   2   2   2   4   9]
- [  6 139   6   3  13   0   3]
- [ 22  28 147  21  22  25  32]
- [ 16   3  26 106   2   6  11]
- [  3   4   5   2  55   2   3]
- [  5   0   0   4   0  41   5]
- [ 23   2  12   5   6  15  73]]
-Node Classification on random seed  3053 -> 0.608
-Confusion Matrix:
- [[ 66   0   7   5   4  13   6]
- [ 11 123   4   5  10   3   6]
- [ 19  23 138  59  26  24  35]
- [  7   1  10 113   3   8  15]
- [  8   4   3   2  65   1   4]
- [  2   1   2   2   5  43   1]
- [ 14   0   9   6   7  17  60]]
-Node Classification on random seed  3054 -> 0.597
-Confusion Matrix:
- [[ 74   5   5   5   4   7  11]
- [  9 119   2   3  12   1   7]
- [  7  40 119  33  30  29  43]
- [  8   4  21 108  10   6  13]
- [  1   8   4   2  65   2   2]
- [ 15   0   4   3   0  35   3]
- [ 13   5   3   3   0  20  77]]
-Node Classification on random seed  3055 -> 0.615
-Confusion Matrix:
- [[ 73   2   5   6   5  15   6]
- [  3 134   3   3   6   1  11]
- [ 15  13 143  35  30  23  35]
- [ 17   1  17 113   8   7  10]
- [  1   6   5   4  59   0   4]
- [  2   4   0   0   2  39   3]
- [  8   1  12  23   7  26  54]]
-Node Classification on random seed  3056 -> 0.576
-Confusion Matrix:
- [[ 71   0   6   3   8  18  11]
- [  8 125   4   0   8   2   4]
- [ 31  24 142  45  18  28  30]
- [ 39   1  16  73   9  10  10]
- [  0   2   5   4  58   4   3]
- [  7   1   2   1   2  40   6]
- [  7   3   9   6   6  23  67]]
-Node Classification on random seed  3057 -> 0.6
-Confusion Matrix:
- [[ 75   4   6   9   1   8  10]
- [  4 141  10   3   4   3   1]
- [ 38  12 130  32  19  38  31]
- [  5   7  12  89   0   7  27]
- [  2  15   3   0  50   4   0]
- [ 10   2   2   0   0  45   2]
- [ 21   2   7  14   6  19  70]]
-Node Classification on random seed  3058 -> 0.606
-Confusion Matrix:
- [[ 63   0   7   7   3  14   8]
- [  4 134   7   1  11   1   4]
- [ 21  19 137  33  24  24  57]
- [ 13   9  12 103   8   8   8]
- [  0   7   6   1  60   0   2]
- [  5   0   4   2   0  41   8]
- [ 12   2  19   6   5  12  68]]
-Node Classification on random seed  3059 -> 0.634
-Confusion Matrix:
- [[ 70   6   2   3   3  15   8]
- [  2 120   9   0   5   1   6]
- [ 28  20 163  42  13  27  26]
- [ 11   5  14 114   7   7   9]
- [  2   9   7   1  55   2   1]
- [  5   3   2   2   2  41   5]
- [ 14   6   6  10  10  10  71]]
-Node Classification on random seed  3060 -> 0.647
-Confusion Matrix:
- [[ 75   6  12   3   6   8   4]
- [  4 106   5   1  16   4   2]
- [ 23  14 180  25  27  22  27]
- [ 11   4  19  92   6   4  24]
- [  2   5   8   0  61   1   1]
- [  7   1   3   1   1  45   7]
- [ 12   2   6   3   4  12  88]]
-Node Classification on random seed  3061 -> 0.596
-Confusion Matrix:
- [[ 47   4   7   4   4  17  14]
- [ 11 113   4   3  23   4   4]
- [ 20  16 132  44  38  24  38]
- [  8   3  18 116   2   2  15]
- [  3   4   2   0  61   0   1]
- [  3   0   4   1   0  51   8]
- [ 12   3   5   3  15  13  76]]
-Node Classification on random seed  3062 -> 0.623
-Confusion Matrix:
- [[ 73   1   3   3   6  20   9]
- [  7 118   2   7  19   5   3]
- [ 27  24 155  28  44  18  25]
- [  6   1   6 110  16   5   8]
- [  1   7   1   2  59   0   5]
- [  7   1   1   2   1  48   4]
- [ 12   3   7   6   6  18  60]]
-Node Classification on random seed  3063 -> 0.558
-Confusion Matrix:
- [[ 64   6   5   6   6  11  11]
- [  1 123   9   1   7   5   4]
- [ 37  26 111  33  26  20  69]
- [  9   0  23  89   1   5  22]
- [  1   7   3   0  55   2   2]
- [  6   1   3   5   1  49   3]
- [  6   4  10  13   9  23  67]]
-Node Classification on random seed  3064 -> 0.613
-Confusion Matrix:
- [[ 74   1   9   5   3   5  12]
- [  3 129   9   0   6   2   5]
- [ 26  23 122  26  53  22  40]
- [ 12   3  19 109   7   4   9]
- [  3   1   6   2  53   2   1]
- [  6   2   2   3   2  46   7]
- [ 12   4   7  11   5   7  80]]
-Node Classification on random seed  3065 -> 0.559
-Confusion Matrix:
- [[ 60   2   3   7   7  12  18]
- [ 10 131   6   5   9   3   4]
- [ 35  30  80  33  39  27  42]
- [ 20   7  16  95   4   8  17]
- [  1   8   1   0  60   1   1]
- [  6   3   4   3   1  38   9]
- [  9   4   7   3   8   8  95]]
-Node Classification on random seed  3066 -> 0.64
-Confusion Matrix:
- [[ 75   4   3   3   2  12   5]
- [  6 130   4   8   1   2   1]
- [ 21  13 157  55  10  46  30]
- [  4   3  11 104   2  13   8]
- [  2   0   0   4  62   1   7]
- [  1   0   4   5   1  41   9]
- [ 13   4  12   7   6  17  71]]
-Node Classification on random seed  3067 -> 0.565
-Confusion Matrix:
- [[ 51   2  13   4   9  21   7]
- [  2 138   1   2   4   0   4]
- [ 33  21 120  42  20  21  55]
- [ 10   7  16 110   5   9  18]
- [  0   4   3   5  46   3   4]
- [  4   3   6   0   1  44   3]
- [ 14   5  26  13   2  13  56]]
-Node Classification on random seed  3068 -> 0.634
-Confusion Matrix:
- [[ 67   4   2   8   3  12  12]
- [  7 123  11   5   7   3   3]
- [ 33  19 152  33  13  22  37]
- [  7   3  21  97   7   6   4]
- [  3   4   5   2  65   0   1]
- [  5   1   3   1   0  47   5]
- [ 10   2   8  14   3  17  83]]
-Node Classification on random seed  3069 -> 0.623
-Confusion Matrix:
- [[ 62   2   6   6   3  14   7]
- [  6 120   2   3   5   4   0]
- [ 20  30 149  24  27  31  47]
- [  6   0  18 109  11  13  11]
- [  0   7   5   0  69   3   0]
- [  5   3   2   2   1  51   5]
- [  5   5   7  10   5  16  63]]
-Node Classification on random seed  3070 -> 0.65
-Confusion Matrix:
- [[ 63   1   4   5   2   6  22]
- [  7 135   3   2   7   4  11]
- [ 21  26 176  24  15  23  28]
- [ 16   2  20  94   3   0  13]
- [  2   8   1   2  68   0   4]
- [  7   3   0   0   0  42   8]
- [ 10   1  11  13  10   5  72]]
-Node Classification on random seed  3071 -> 0.592
-Confusion Matrix:
- [[ 59   3   4   5   2  21   6]
- [  6 140   3   0   4   5   3]
- [ 27  14 144  43  30  27  36]
- [ 11   2  16  93   0  10  25]
- [  2   6   7   5  52   1   3]
- [  2   2   9   1   0  35   9]
- [  5   2  12  13   5  21  69]]
-Node Classification on random seed  3072 -> 0.642
-Confusion Matrix:
- [[ 70   3   3   1   5  16   4]
- [  0 130   9   2   7   5   5]
- [ 17  20 179  30  19  22  27]
- [ 12   4  17  86   5   8  21]
- [  0  11   1   8  46   1   1]
- [  4   1   1   0   2  43   7]
- [ 15   6   3   2   7  26  88]]
-Node Classification on random seed  3073 -> 0.625
-Confusion Matrix:
- [[ 67   0   2   5   0  15  15]
- [  6 140   5   3   4   0   3]
- [ 28  27 148  30  18  28  37]
- [ 15   1  15  85   4   9  20]
- [  4  10   1   1  54   0   2]
- [  9   3   0   0   1  48   0]
- [ 19   6   9   1   4  15  83]]
-Node Classification on random seed  3074 -> 0.625
-Confusion Matrix:
- [[ 63   0   8   9   9   4  19]
- [  3 143   4   5   4   4   2]
- [ 27  11 145  35  34  16  37]
- [  5   2  26 108   0   7  10]
- [  1   7   4   2  61   4   0]
- [ 11   3   4   2   0  35   4]
- [  7   6  10  15   4  10  70]]
-Node Classification on random seed  3075 -> 0.631
-Confusion Matrix:
- [[ 64   0   5   5   5  12   7]
- [  0 122   4   2  23   4   2]
- [ 12   8 142  29  41  28  54]
- [  6   8  18  97   3   4   9]
- [  0   4   1   4  80   2   1]
- [  4   1   1   1   4  46   8]
- [ 17   2   2  14   7   7  80]]
-Node Classification on random seed  3076 -> 0.566
-Confusion Matrix:
- [[ 60   6   1   4   7   7   7]
- [ 11 129   3   3  13   4   1]
- [ 23  21 110  41  61  24  30]
- [  7   6  15 106  13   7   9]
- [  4   5   3   3  63   2   1]
- [  0   0   4   2   1  27  18]
- [ 22   8  12   4   9  12  71]]
-Node Classification on random seed  3077 -> 0.625
-Confusion Matrix:
- [[ 83   6   8   6   5   6   4]
- [  6 131   2   4   3   5  10]
- [ 30  33 131  43  20  26  25]
- [ 12   7  13 109   4   4   4]
- [  0   5   3   1  55   1   2]
- [  5   3   2   0   0  45   4]
- [ 15   7  18   6   3  14  71]]
-Node Classification on random seed  3078 -> 0.58
-Confusion Matrix:
- [[ 81   4   9   4   6   8   5]
- [  9 117   8   1   8   2  13]
- [ 48  37 140  33   9  16  33]
- [ 11   7  15  88   5   6  15]
- [  3   3   8   1  60   1   4]
- [  4   3   4   4   4  36   4]
- [  9   5  10   7  14  20  58]]
-Node Classification on random seed  3079 -> 0.638
-Confusion Matrix:
- [[ 77   7   4   2   6  10   1]
- [  1 141   4   4   4   1   4]
- [ 17  30 150  39  25  15  37]
- [ 11   5  16  81  11   8  14]
- [  1   6   3   4  56   1   2]
- [  5   5   1   0   0  58   4]
- [  8   2  16  10  10   8  75]]
-Node Classification on random seed  3080 -> 0.604
-Confusion Matrix:
- [[ 58   0   4   9   7  11  12]
- [  4 122   7   3  19   3   2]
- [ 20  17 131  29  58  27  45]
- [  7   5  14 105   1  11  20]
- [  2   4   3   1  68   0   0]
- [  2   0   1   2   0  49   3]
- [  7   4   7   6   6  13  71]]
-Node Classification on random seed  3081 -> 0.626
-Confusion Matrix:
- [[ 69   4   5   6   4   8  10]
- [  1 118   9   6  11   4   1]
- [ 11  19 152  33  26  20  50]
- [ 13   5  20 113   8   3   4]
- [  3   5   3   1  69   1   1]
- [  2   0   4   1   3  42  10]
- [  8   5   5  14  13  14  63]]
-Node Classification on random seed  3082 -> 0.634
-Confusion Matrix:
- [[ 76   3   7   5   4   9   4]
- [ 10 134   3   1   4   2   7]
- [ 20  15 153  27  36  23  29]
- [  9   7  10 103  16   6  12]
- [  6   1   4   1  63   1   3]
- [  8   0   2   0   0  36   4]
- [ 20   3  12   8   6  18  69]]
-Node Classification on random seed  3083 -> 0.615
-Confusion Matrix:
- [[ 84   2   2   5   6  11   4]
- [  7 130   6   2   8   0   6]
- [ 38  27 133  26  32  30  33]
- [  8   3  15 101   7   4  13]
- [  0  11   2   1  56   0   7]
- [  6   1   0   2   2  43   2]
- [ 14   3   8   4   7  20  68]]
-Node Classification on random seed  3084 -> 0.64
-Confusion Matrix:
- [[ 73   5   3   9   5   5   8]
- [  3 136   6   2  10   2   1]
- [ 18  18 139  38  32  25  40]
- [  5   1  18 107   9   8   6]
- [  1   9   2   0  58   3   1]
- [  9   1   1   3   1  41   2]
- [ 21   8   1   3   9   8  86]]
-Node Classification on random seed  3085 -> 0.617
-Confusion Matrix:
- [[ 67   3   6   5   7   3  16]
- [  1 118   3   4   8   3   9]
- [ 12  31 151  32  16  15  59]
- [  6   5  22 101   6   5  15]
- [  1  10   4   2  59   1   0]
- [  3   2   2   4   0  49  12]
- [ 10   4  16   7   3  10  72]]
-Node Classification on random seed  3086 -> 0.61
-Confusion Matrix:
- [[ 66   0   0   4   2  11  14]
- [  5 129   5   3   9   0   1]
- [ 24  40 137  36  27  26  37]
- [ 11   5  15 107   1   4  12]
- [  2   7   2   2  55   2   5]
- [  2   0   1   4   0  42   9]
- [ 20   4  11   6   6  15  74]]
-Node Classification on random seed  3087 -> 0.596
-Confusion Matrix:
- [[ 73   2   1   8   2  24   6]
- [  7 137   8   2  11   0   5]
- [ 24  16 141  40  17  27  35]
- [ 14   5  28  81  14  11  10]
- [  0   3   2   0  47   4   3]
- [  3   0   1   0   3  51   5]
- [ 22   3  10   3   5  20  66]]
-Node Classification on random seed  3088 -> 0.647
-Confusion Matrix:
- [[ 69   7   5   2   2  12   3]
- [  4 139   4   2   8   1   0]
- [ 31  19 144  33  35  17  32]
- [  6   5  19 108   2   9   8]
- [  0   3   1   1  65   4   0]
- [  3   1   5   0   1  53   1]
- [ 14   8   6   7   7  25  69]]
-Node Classification on random seed  3089 -> 0.618
-Confusion Matrix:
- [[ 69   2   2   3   2   8  11]
- [  2 133   3   4  13  10   1]
- [ 28  14 143  38  16  27  32]
- [ 12   5  11  97   6  16  13]
- [  2   7   8   3  56   1   2]
- [  2   3   4   2   3  48   5]
- [  5   5  11  18   5  17  72]]
-Node Classification on random seed  3090 -> 0.583
-Confusion Matrix:
- [[ 66   6   5   9   6  11   9]
- [  4 119   7   1  10   1   4]
- [ 25  22 128  44  36  23  25]
- [ 23   8   9 102  15   6  11]
- [  0   6   1   1  62   0   3]
- [ 15   4   3   2   1  42   2]
- [ 14   3   5   8   8  21  64]]
-Node Classification on random seed  3091 -> 0.628
-Confusion Matrix:
- [[ 66   3   6   3   2  15  10]
- [  2 121  17   2  10   1   2]
- [ 26  20 135  61  33  11  38]
- [  3   2  17 112   4   1  19]
- [  2   6   1   1  65   0   4]
- [  1   0   0   0   0  45  13]
- [ 12   2   3   5   7   7  84]]
-Node Classification on random seed  3092 -> 0.604
-Confusion Matrix:
- [[ 92   4   6   4   0  13   6]
- [  4 109  12   1   7   2   6]
- [ 28  16 143  32  34  13  45]
- [ 18   7  16  77   6   5  26]
- [  1   5   3   2  62   2   2]
- [  3   0   1   2   0  45   6]
- [  8   5   7   8  18  12  76]]
-Node Classification on random seed  3093 -> 0.607
-Confusion Matrix:
- [[ 61   0   1   3   3  21   6]
- [  7 121   7   4   6   4   5]
- [ 18  24 142  36  33  37  40]
- [ 10   5  13 102   6   4  10]
- [  2  10   1   1  65   1   5]
- [  6   3   3   1   1  49   5]
- [ 10   6   5   5   8  17  67]]
-Node Classification on random seed  3094 -> 0.617
-Confusion Matrix:
- [[ 84   0   2   5   4  17  14]
- [  3 128   7   2  19   3   4]
- [ 15  13 144  36  27  27  20]
- [  5   5  25 113   4   6   6]
- [  4   4   5   1  59   1   1]
- [  3   1   1   3   4  42   6]
- [  8   2   6   8  35  21  47]]
-Node Classification on random seed  3095 -> 0.603
-Confusion Matrix:
- [[ 53   0   5   4   1  19  11]
- [  8 125   6   2   6   1  11]
- [ 27  16 153  34  37  23  28]
- [ 12   3  15  95   6   7  13]
- [  1   7   4   1  48   1   4]
- [ 12   1   2   0   1  49   3]
- [  9   3   8   1  11  33  80]]
-Node Classification on random seed  3096 -> 0.615
-Confusion Matrix:
- [[ 65   5   7   6   7  17   7]
- [  5 146   3   5   5   1   4]
- [ 33  30 143  42  21  13  36]
- [ 13   2  13 103   8   4  15]
- [  0   5   4   1  54   1   4]
- [  5   0   0   1   0  47   8]
- [ 17   5   6   5   8  13  57]]
-Node Classification on random seed  3097 -> 0.597
-Confusion Matrix:
- [[ 76   3   3   2   4   6   7]
- [  3 107  17   2  18   1   3]
- [ 21  15 145  39  28  25  49]
- [ 17   4  10  91   9   3   9]
- [  2   6   5   2  60   2   3]
- [ 10   0   0  10   2  48   3]
- [ 19   3   8   6   7  17  70]]
-Node Classification on random seed  3098 -> 0.587
-Confusion Matrix:
- [[ 58   2   8   7   6  19  11]
- [  8 111   5   3   6   4   1]
- [ 34  25 143  39  37  17  30]
- [ 10   4  19 110   6   5  11]
- [  1   8   2   3  65   0   3]
- [ 13   0   1   3   0  25   9]
- [ 14   4   6   8   8  13  75]]
-Node Classification on random seed  3099 -> 0.61
-Confusion Matrix:
- [[ 71   0   5   5   2   5  15]
- [  2 122   1   6   2   0   5]
- [ 16  28 148  31  20  33  44]
- [  5   7  18 101  14  13  19]
- [  1   3   4   1  52   0   5]
- [  4   1   8   2   0  39   7]
- [  7   3  24   7   5  12  77]]
-Node Classification on random seed  3100 -> 0.62
-Confusion Matrix:
- [[ 65   1   9   9   2  12  13]
- [ 10 140   7   1   6   3   4]
- [ 19  30 126  32  52  25  29]
- [  4   0  18 113   3  10   6]
- [  1  11   1   3  60   1   1]
- [  4   1   5   1   0  41   5]
- [  6   2   8   5   7  13  75]]
-Node Classification on random seed  3101 -> 0.629
-Confusion Matrix:
- [[ 71   6   3   6   0  12  14]
- [  0 136   3   0   4   5   3]
- [ 12  25 160  21  24  51  32]
- [  5   5  16  89  11  11  17]
- [  0  13   2   2  58   0   3]
- [  7   4   3   5   1  51   1]
- [  9   3   7   7   1  17  64]]
-Node Classification on random seed  3102 -> 0.645
-Confusion Matrix:
- [[ 79   0   4   6   3  13   4]
- [  4 145   5   2   3   3   2]
- [ 17   9 143  38  25  15  48]
- [ 12   3   9  95   3   7  29]
- [  2   8   2   1  63   0   4]
- [ 11   2   0   0   1  47   3]
- [ 17   4  14   5   4  13  73]]
-Node Classification on random seed  3103 -> 0.625
-Confusion Matrix:
- [[ 61   1   5   6   7  14  15]
- [ 14 106   5   1  12   8   5]
- [ 28  20 156  20  23  22  38]
- [ 11   1  19 117   4   7  12]
- [  1   2   4   6  59   0   1]
- [  2   2   1   5   0  45   4]
- [  8   3   9   8   3  18  81]]
-Node Classification on random seed  3104 -> 0.595
-Confusion Matrix:
- [[ 72   6   4   3   3   6  17]
- [  1 116   5   0  11   4   5]
- [ 23  26 122  49  31  33  31]
- [  5   2  20 103  15   6   9]
- [  0   5   4   2  65   1   1]
- [  9   3   2   3   0  41   3]
- [  8  10  10   9   2  18  76]]
-Node Classification on random seed  3105 -> 0.589
-Confusion Matrix:
- [[ 65   4   1   2   7  16  20]
- [  2 116   3   0   9   5   5]
- [ 18  35 122  32  44  20  38]
- [ 11   7  13 104  13   9   7]
- [  1   4   1   3  60   5   2]
- [  7   0   2   1   0  45   4]
- [  7   4   3   9  13  24  77]]
-Node Classification on random seed  3106 -> 0.607
-Confusion Matrix:
- [[ 72   9   2  10   5  12  12]
- [  7 112  13   2   8   1   6]
- [ 28  22 164  24  15  33  35]
- [  8   6  11  95   5   9  15]
- [  2   5   1   5  66   0   5]
- [  3   2   2   0   0  31   8]
- [ 12   3  11  10  14  12  67]]
-Node Classification on random seed  3107 -> 0.596
-Confusion Matrix:
- [[ 63   4   9   3   1  16   5]
- [  7 116   2   0   8   2  11]
- [ 20  25 120  56  26  24  39]
- [ 12   1  12 119   2   8  15]
- [  1   7   2   4  61   0   6]
- [ 12   3   1   1   0  38   4]
- [ 19   1   9   8  10   8  79]]
-Node Classification on random seed  3108 -> 0.615
-Confusion Matrix:
- [[ 73   1   8   3   3   6   8]
- [  3 127  10   2   5   3   2]
- [ 34  20 138  32  29  25  34]
- [ 12   2  11 112   3  13  15]
- [  7   7   4   1  49   0   2]
- [  5   1   7   1   1  35   4]
- [ 16   4  16   7   5  13  81]]
-Node Classification on random seed  3109 -> 0.6
-Confusion Matrix:
- [[ 65   1   6   8   3  12  22]
- [  3 130   4   6   1   5   6]
- [ 29  19 170  33  11  33  26]
- [ 23   8  16  70   3   2  28]
- [  1   6   6   6  51   0   3]
- [  5   1   4   0   0  45   7]
- [  6   2  12   2   5  26  69]]
-Node Classification on random seed  3110 -> 0.618
-Confusion Matrix:
- [[ 65   5  10   5   2   9   3]
- [  9 119   6   4  24   3   4]
- [ 23  15 158  24  24  25  41]
- [ 23   0  21  92   1   4  17]
- [  1   2   1   1  60   3   5]
- [  4   1   4   3   0  47   3]
- [ 19   4   8  11   5   5  77]]
-Node Classification on random seed  3111 -> 0.631
-Confusion Matrix:
- [[ 73   4   2   8   2   7  11]
- [ 10 126   5   1  12   2   2]
- [ 20  14 161  58  15  31  17]
- [ 12   3  23 109   3   4   8]
- [  4  10   4   3  58   0   2]
- [  3   2   3   2   2  41   2]
- [ 13   5   8   6   7  19  63]]
-Node Classification on random seed  3112 -> 0.62
-Confusion Matrix:
- [[ 66  10   8   3   2  12   6]
- [  7 145   4   1   1   0   0]
- [ 32  31 143  49  20  16  25]
- [ 18   5  21  89   4   5  11]
- [  1  12   1   4  60   0   3]
- [  4   1   1   0   0  48   2]
- [  7   7  12   3   9  22  69]]
-Node Classification on random seed  3113 -> 0.612
-Confusion Matrix:
- [[ 60   5   4   6   0  25  20]
- [  6 128   5   2   8   8   1]
- [  7  21 153  24  25  30  46]
- [ 11   4  15 101   5  11   9]
- [  2   8   3   0  60   4   3]
- [  3   3   3   1   1  43   4]
- [ 11   3   9   4   6  22  67]]
-Node Classification on random seed  3114 -> 0.641
-Confusion Matrix:
- [[ 71   1   4   6   4  14  19]
- [  1 130   7   0   7   5   5]
- [ 22  20 147  16  30  17  48]
- [ 12   8  14  96   3   9  25]
- [  3   2   4   2  56   0   0]
- [  5   1   0   1   1  50   6]
- [ 12   1  12   3   1   8  91]]
-Node Classification on random seed  3115 -> 0.585
-Confusion Matrix:
- [[ 67   3   8   3   5  11  10]
- [  2 121   6   0  10   1   3]
- [ 40  21 137  34  37  16  48]
- [ 13   3  18  90   8   9  12]
- [  0   7   1   5  70   2   2]
- [  2   1   1   0   2  46   4]
- [ 18   4  10   8   6  21  54]]
-Node Classification on random seed  3116 -> 0.632
-Confusion Matrix:
- [[ 55   5   2   3  11  10  10]
- [  4 120   2   3  13   2   2]
- [ 33  15 136  30  36  31  45]
- [  7   4  12 122   4   7  10]
- [  0   5   4   1  63   2   1]
- [ 10   0   2   2   0  52   7]
- [  4   5   6   5   7   6  84]]
-Node Classification on random seed  3117 -> 0.62
-Confusion Matrix:
- [[ 65   0   4   3   5  21   7]
- [  5 120   8   7   6   2   0]
- [ 37  31 147  24  19  14  39]
- [ 13   4  12 101   8   5   8]
- [  0   6   6   0  67   1   4]
- [  3   2   4   0   1  38   8]
- [ 11   3   8  15   6  20  82]]
-Node Classification on random seed  3118 -> 0.604
-Confusion Matrix:
- [[ 74   8   5   4   2  13   2]
- [  5 122  10   2  11   2   2]
- [ 16  13 102  38  56  15  47]
- [ 13   8  14  89   6   8  22]
- [  2   5   1   1  72   4   2]
- [  1   3   2   0   1  56   6]
- [  7   6   9   4  11   9  89]]
-Node Classification on random seed  3119 -> 0.643
-Confusion Matrix:
- [[ 67   4   0   6   8  26   7]
- [  7 141   4   2   8   0   0]
- [ 12  23 155  31  25  21  31]
- [ 18   1  22  99   2   3   8]
- [  1   5   2   2  67   0   1]
- [  2   2   4   0   0  49   3]
- [ 14   4  11  12  14  11  65]]
-Node Classification on random seed  3120 -> 0.591
-Confusion Matrix:
- [[ 67   4   5   4   4  14  15]
- [  4 118   4   0   8   3   8]
- [ 25  37 125  29  16  35  44]
- [  8   4   8 113   2   7  10]
- [  1   9   5   1  62   1   1]
- [  2   4   0   6   2  47   5]
- [ 10   4  21  11  13  15  59]]
-Node Classification on random seed  3121 -> 0.618
-Confusion Matrix:
- [[ 80   1  12   1   4   9   4]
- [  1 123   6   1   9   1   4]
- [ 26  21 142  38  28  12  32]
- [ 32   7  15  83   7   3   8]
- [  3   9   5   1  62   0   5]
- [  4   3   8   1   0  45   4]
- [  8   5  19  13   3   9  83]]
-Node Classification on random seed  3122 -> 0.628
-Confusion Matrix:
- [[ 54   2   7  10   5   6  20]
- [  4 154   6   3   2   1   2]
- [ 13  35 166  38  13  21  36]
- [ 10   2  20  97   3   5   6]
- [  0  14   4   1  58   0   3]
- [  2   1   2   5   1  38   5]
- [  9   4  10  17   6  18  61]]
-Node Classification on random seed  3123 -> 0.659
-Confusion Matrix:
- [[ 79   2   2   3   2   3  15]
- [  3 121   2   2  12   1   0]
- [ 28  19 160  24  19  32  48]
- [  7   5  11 113   9   5  12]
- [  2   6  11   3  55   1   1]
- [  8   0   0   1   0  42   2]
- [ 19   4   6   2   4   5  89]]
-Node Classification on random seed  3124 -> 0.646
-Confusion Matrix:
- [[ 83   4   5   3   1  13   9]
- [  2 121   9   2   5   4   3]
- [ 22  14 166  33  15  24  47]
- [  8   2  24 107   3   4   1]
- [  2  14   4   1  44   1   2]
- [  7   5   1   1   2  51   3]
- [ 11   4   6  15   2  16  74]]
-Node Classification on random seed  3125 -> 0.614
-Confusion Matrix:
- [[ 75   0   2   4   5   9  15]
- [ 10 131   3   1  10   4   1]
- [ 28  32 144  55  22  14  35]
- [  9   5  13 111   3   5   9]
- [  2   6  11   1  59   0   2]
- [  2   1   3   6   1  33   5]
- [  8   5   7   9   6  17  61]]
-Node Classification on random seed  3126 -> 0.605
-Confusion Matrix:
- [[ 78   1   0  13   7   6  12]
- [  4 127   1   3  11   0   4]
- [ 44  27 126  21  41  25  41]
- [  3   5  15 107   5  12   8]
- [  0   3   7   0  62   0   1]
- [  8   2   2   1   1  43   3]
- [ 11   3   6  14  11  13  62]]
-Node Classification on random seed  3127 -> 0.609
-Confusion Matrix:
- [[ 88   4   7   2   6  12   4]
- [  6 131   3   3   5   1  10]
- [ 23  30 121  46  35  30  25]
- [  4   3  18  89   3   6  16]
- [  0   7   5   5  62   1   5]
- [  2   2   0   1   2  56   2]
- [  4   2   7  11   3  30  62]]
-Node Classification on random seed  3128 -> 0.613
-Confusion Matrix:
- [[ 78   4   9  13   7  13   8]
- [  5 127   3   1  11   5   5]
- [ 23   6 146  32  29  20  47]
- [ 15   6  14  94   4   6  14]
- [  0   6   3   3  57   0   4]
- [  8   0   1   1   0  36   5]
- [ 12   8  11   7   4  14  75]]
-Node Classification on random seed  3129 -> 0.608
-Confusion Matrix:
- [[ 67   6   5   8   7  13   9]
- [  5 124   3   7   4   4   8]
- [ 23  30 150  18  14  24  46]
- [ 11   1  18 107   7   2  21]
- [  0   3   8   2  59   2   1]
- [ 10   0   4   1   1  38   3]
- [ 13   3   5  14  10  18  63]]
-Node Classification on random seed  3130 -> 0.629
-Confusion Matrix:
- [[ 64   3   4   4   2  10  18]
- [  2 154   8   3   4   0   0]
- [ 20  28 132  29  31  22  32]
- [ 14   6  13  85   5   4  24]
- [  1   5   2   2  66   0   2]
- [  7   0   1   5   0  50   7]
- [ 15   8   5   7   6  12  78]]
-Node Classification on random seed  3131 -> 0.63
-Confusion Matrix:
- [[ 67   1  11   8   5   5   7]
- [  5 126   8   3   1   1   2]
- [ 18  29 160  39  21  18  27]
- [ 12   7  20 107   9   6  15]
- [  2   4   7   1  63   2   1]
- [  5   2   2   2   1  45   6]
- [ 13   4  14   8   8  10  62]]
-Node Classification on random seed  3132 -> 0.606
-Confusion Matrix:
- [[ 53   6   7  11   5  25   3]
- [  4 120   9   2  26   5   2]
- [ 20  12 149  39  19  33  30]
- [ 20   5   6  96   0   9   7]
- [  0   3   4   2  66   2   4]
- [  4   2   1   1   1  48   3]
- [ 16   3  11   8   5  19  74]]
-Node Classification on random seed  3133 -> 0.614
-Confusion Matrix:
- [[ 72   2   5   2   5   3  17]
- [  4 134   2   0   6   6   1]
- [ 27  27 152  36  30  22  40]
- [ 20   2  20  83  10   4   6]
- [  1   4   8   1  48   2   1]
- [ 13   0   3   5   0  43   5]
- [ 16   0  15   6   4   5  82]]
-Node Classification on random seed  3134 -> 0.605
-Confusion Matrix:
- [[ 69   3   1   4   2  16  14]
- [  5 130   3   0  12   3   4]
- [ 34  26 122  20  34  23  31]
- [ 12   2  18 106   5   8  12]
- [  0   9   3   1  65   1   2]
- [  2   1   1   5   4  51   5]
- [ 15   1   8  14  17  14  62]]
-Node Classification on random seed  3135 -> 0.605
-Confusion Matrix:
- [[ 51   2   5   6   9  14  20]
- [  3 131   4   2   6   6   5]
- [ 26  23 157  37  15  38  20]
- [ 24   5  16 100   4   5   6]
- [  1   5   3   2  59   2   7]
- [  6   2   0   1   2  43   3]
- [ 15   3  12   4   4  22  64]]
-Node Classification on random seed  3136 -> 0.626
-Confusion Matrix:
- [[ 66   0   4   5   3  10  10]
- [  3 117   6   4  15   5   5]
- [ 24   8 129  18  56  19  45]
- [  8  11  16 109   6   5  16]
- [  2   3   2   1  71   2   2]
- [  3   0   0   4   0  42   4]
- [ 14   2   2   7   9  15  92]]
-Node Classification on random seed  3137 -> 0.591
-Confusion Matrix:
- [[ 66   4  20   8   4   5  20]
- [  3 137  10   2   2   2   5]
- [ 20  25  96  35  49  17  58]
- [  5  11  14 124   6   6  11]
- [  0   7   2   1  54   3   2]
- [  2   0   7   1   0  39   7]
- [  3   1  15   5   4   7  75]]
-Node Classification on random seed  3138 -> 0.616
-Confusion Matrix:
- [[ 63   3   2   4   1  19   5]
- [  3 122   6   4   6   3   7]
- [ 35  19 146  27  22  29  40]
- [ 20   6   8  85  15   6   6]
- [  0   7   5   2  58   1   4]
- [  6   2   2   1   0  49   4]
- [ 12   7   8   4  10  13  93]]
-Node Classification on random seed  3139 -> 0.577
-Confusion Matrix:
- [[ 56   1  14   7   3  13   5]
- [  7 117   2   4  19   1   4]
- [ 37  22 128  26  20  27  53]
- [ 12   2   7 104  11   6  11]
- [  3   3   3   0  64   0  11]
- [  4   2   3   0   0  43  10]
- [  7   5  21   3  11  23  65]]
-Node Classification on random seed  3140 -> 0.616
-Confusion Matrix:
- [[ 69   6   2   4   6  15  11]
- [  9 123   9   1   7   2   7]
- [ 19  23 160  25  22  21  46]
- [ 17   1  15  89   2   5  18]
- [  2   6   5   4  56   0   4]
- [  3   0   4   0   1  55   6]
- [ 13   1   6   4  16  16  64]]
-Node Classification on random seed  3141 -> 0.598
-Confusion Matrix:
- [[ 67   0   2   4   2  14   9]
- [  5 133  10   4   6   4   5]
- [ 25  24 154  37  15  30  28]
- [ 20   4  39  66   9   6   5]
- [  0   5   2   3  55   4   5]
- [  2   1   2   1   0  59  10]
- [ 13   5  15   4   7  16  64]]
-Node Classification on random seed  3142 -> 0.628
-Confusion Matrix:
- [[ 63   6   6   1   3  15   6]
- [  3 123   3  12  10   5   4]
- [ 18  15 157  20  27  29  50]
- [  9   6  17 105   8   4  13]
- [  2   6   3   0  61   0   4]
- [  3   3   2   5   1  42   2]
- [ 11   5  11   7   1  16  77]]
-Node Classification on random seed  3143 -> 0.608
-Confusion Matrix:
- [[ 65   2   1   8   2  17  22]
- [  4 125  10   1   5   4   3]
- [ 15  13 138  22  29  23  52]
- [ 16   3  13  95   5  11  10]
- [  1   9   3   1  67   0   3]
- [  9   0   0   1   1  47   4]
- [ 15   5  12   9   5  23  71]]
-Node Classification on random seed  3144 -> 0.57
-Confusion Matrix:
- [[ 78   1   5   1   8   7  10]
- [  4 106   2   3   5   5   8]
- [ 30  30  93  28  59  22  59]
- [  7   3  17 104   8   4  17]
- [  0   5   1   1  63   1   5]
- [  8   1   3   3   1  47   6]
- [ 22   2   4   4   6  14  79]]
-Node Classification on random seed  3145 -> 0.65
-Confusion Matrix:
- [[ 78   1   1   2   1   7  15]
- [  4 136   6   4   5   1   3]
- [ 29  27 153  34  38  12  30]
- [  9   3  16  98   4   4  19]
- [  1   8   1   1  58   0   2]
- [  6   2   0   0   0  48   7]
- [ 13   5   6   4   6  13  79]]
-Node Classification on random seed  3146 -> 0.565
-Confusion Matrix:
- [[ 55   2   3   1   3  22  20]
- [  3 125   6  15   3   4   3]
- [ 23  14 108  47  30  31  63]
- [  7   2   8 104   8   6  20]
- [  1   4   4   3  54   2   1]
- [  9   0   1   4   1  53   2]
- [  7   6   3  20   5  18  66]]
-Node Classification on random seed  3147 -> 0.539
-Confusion Matrix:
- [[ 53   4  11  10  11  14  14]
- [  7 114   4   2  13   7   6]
- [ 18  31 110  66  35   9  52]
- [  7   4   7  88   8  19  10]
- [  1   8   0   0  49   0   3]
- [  2   1   1   3   3  42   8]
- [  7   4  16  17   8  10  83]]
-Node Classification on random seed  3148 -> 0.599
-Confusion Matrix:
- [[ 55   3   8  11   7  15  12]
- [  3 103   5   5  10   3   0]
- [ 22  19 154  25  38  26  48]
- [  8   2  13 102  12  14   9]
- [  0   8   5   1  68   0   2]
- [  4   3   2   3   1  40   4]
- [ 13   6   4   5   6  16  77]]
-Node Classification on random seed  3149 -> 0.643
-Confusion Matrix:
- [[ 61   2  10   0   1  15   8]
- [  6 130   5   2   2   1   4]
- [ 29  13 156  44  25  14  51]
- [ 12   6   9 116   2   2  15]
- [  1   8   3   0  59   2   5]
- [  2   2   2   2   1  48   3]
- [  8   7   6  11   0  16  73]]
-Node Classification on random seed  3150 -> 0.617
-Confusion Matrix:
- [[ 64   2   4   8   2  16  12]
- [  1 132  10   1   3   1   7]
- [ 16  16 136  41  21  15  63]
- [  7   3  11 114   7   4  18]
- [  2   4   4   0  52   3   5]
- [  0   1   5   2   1  44   5]
- [  7   3  17   6  10  19  75]]
-Node Classification on random seed  3151 -> 0.631
-Confusion Matrix:
- [[ 82   0   4   5   5   9   6]
- [  3 124   5  10  13   7   4]
- [ 22  15 137  42  24  10  55]
- [ 13   3   9 116  11   8   3]
- [  1   3   5   1  63   1   4]
- [  2   0   4   7   0  33   7]
- [  2   6   2  12   7  19  76]]
-Node Classification on random seed  3152 -> 0.549
-Confusion Matrix:
- [[ 67   1   8   6   6  21   3]
- [  2 121   5   4   7   9   4]
- [ 39  18  99  27  47  36  48]
- [ 17   7  19  97   3   5  12]
- [  1   6   1   2  67   1   2]
- [ 10   1   5   1   1  34   5]
- [  7   5  10   9   6  24  64]]
-Node Classification on random seed  3153 -> 0.621
-Confusion Matrix:
- [[ 70   3   2   2   7   4  11]
- [  2 127   5   4   3   1   1]
- [ 23  29 135  39  30  20  42]
- [  5   6  21 104   4   3  23]
- [  0  14   3   1  58   0   4]
- [ 10   3   1   0   2  49   6]
- [  9   6  14   4   7   5  78]]
-Node Classification on random seed  3154 -> 0.619
-Confusion Matrix:
- [[ 79   9   1   7   2   7  11]
- [  5 113   7   6  13   0   4]
- [ 32  15 160  23  15  20  35]
- [ 13   2  16 101   5  11  12]
- [  2   3   8   7  55   2   2]
- [  4   1   4   0   1  52   9]
- [ 16   4  16   5   4  22  59]]
-Node Classification on random seed  3155 -> 0.619
-Confusion Matrix:
- [[ 64   2   7   3   1  11   4]
- [  4 138   2   4   7   2   6]
- [ 24  22 125  37  21  28  55]
- [ 12   4   9 112   3  12  10]
- [  1  14   1   1  56   1   4]
- [  3   0   0   0   1  60   6]
- [ 14   3   6   6  10  20  64]]
-Node Classification on random seed  3156 -> 0.656
-Confusion Matrix:
- [[ 72   4   4   4   3   9  10]
- [  8 125   2   3   5   2   9]
- [ 18  19 149  33  20  16  48]
- [ 14   3  10 120   3   1   9]
- [  1   7   2   0  57   0   3]
- [  7   4   2   2   0  47   0]
- [ 20   8   5  11   4  11  86]]
-Node Classification on random seed  3157 -> 0.66
-Confusion Matrix:
- [[ 70   2   6   5   3  10   7]
- [  6 127   4   1  16   4   1]
- [ 19  13 158  22  25  22  38]
- [  8   6  21 108   5   7   9]
- [  2  10   6   2  67   0   1]
- [  4   2   2   4   0  38   3]
- [  4   8   9   6   3  14  92]]
-Node Classification on random seed  3158 -> 0.623
-Confusion Matrix:
- [[ 74   2   8   3   2   8  12]
- [ 10 120  15   0   8   4   3]
- [ 17  25 138  38  33  33  41]
- [  5   5  22  94   3  10   8]
- [  1   7   7   1  52   1   0]
- [  1   1   0   0   3  49   5]
- [  2   7   6   6   2  12  96]]
-Node Classification on random seed  3159 -> 0.605
-Confusion Matrix:
- [[ 59   4   6   9   9  15  12]
- [  3 144   2   2   3   5   4]
- [ 11  26 128  38  40  19  55]
- [ 12   6   8  92   5   3  17]
- [  0   7   4   1  59   2   2]
- [  2   0   0   1   0  53   4]
- [  7   3   9  17   8  14  70]]
-Node Classification on random seed  3160 -> 0.614
-Confusion Matrix:
- [[ 83   1   5   1   1  14   5]
- [  1 117  18   2   5   6   3]
- [ 17  24 135  45  16  30  37]
- [  3   6  18  95  10  11  14]
- [  4   7   0   5  58   0   1]
- [  6   5   0   3   2  54   2]
- [ 12   5   7   3   7  24  72]]
-Node Classification on random seed  3161 -> 0.64
-Confusion Matrix:
- [[ 81   3   3   0   1  16   9]
- [ 10 117   6   3  19   1   6]
- [ 21  38 152  16  13  14  52]
- [  5   4  10  95   3   8  14]
- [  2   4   2   4  54   0   5]
- [  3   3   3   0   1  44  11]
- [ 14   2   7   1   6  17  97]]
-Node Classification on random seed  3162 -> 0.614
-Confusion Matrix:
- [[ 71   6   1   9   3   8   9]
- [  2 148  10   1   3   0   1]
- [ 34  18 156  42  23  10  31]
- [ 17   5  20  85   4   3   4]
- [  0  14   5   5  53   2   2]
- [  5   2   1   4   1  40  14]
- [ 19   7   7  10   9  15  61]]
-Node Classification on random seed  3163 -> 0.604
-Confusion Matrix:
- [[ 78   3   1  10   6   8   8]
- [  9 109   2   3  16   3   2]
- [ 21  23 144  37  39  16  31]
- [  9  12  24  82  13   5   9]
- [  0   4   8   3  63   1   2]
- [ 10   0   3   0   1  44   6]
- [  8   2  13   6   3  16  84]]
-Node Classification on random seed  3164 -> 0.613
-Confusion Matrix:
- [[ 53   5   6   5   7  23  10]
- [  9 135   2   4   9   1   3]
- [ 23  14 148  16  28  21  47]
- [ 11   3  20  97   4   8  11]
- [  4   4   4   5  59   0   2]
- [  3   3   6   0   1  48   4]
- [  8   3  13   7   7  23  73]]
-Node Classification on random seed  3165 -> 0.654
-Confusion Matrix:
- [[ 79   0   3   3   4  13   7]
- [  4 119   2   0  17   0   4]
- [ 20  30 162  31  19  24  33]
- [ 15   4  22  94   2   5   7]
- [  1   5   2   1  69   1   1]
- [ 10   2   0   0   0  44   3]
- [  8   2  11   4  11  15  87]]
-Node Classification on random seed  3166 -> 0.622
-Confusion Matrix:
- [[ 62   1   6   5   3  12  11]
- [  1 118  12  10  11   5   4]
- [ 32  13 141  35  18  25  44]
- [ 23   4   6 111   3   6   7]
- [  0   9   3   2  68   1   3]
- [  6   3   1   0   2  44   5]
- [ 13   1   7   9   3  13  78]]
-Node Classification on random seed  3167 -> 0.642
-Confusion Matrix:
- [[ 82   1   3   8   4   5  13]
- [  6 113   3   0   9   2   1]
- [ 21  11 156  39  21  30  51]
- [  1   2  14 103   6   4  21]
- [  3   7   0   2  68   2   6]
- [  3   0   2   1   1  40   6]
- [ 12   2   8   5   8  14  80]]
-Node Classification on random seed  3168 -> 0.606
-Confusion Matrix:
- [[ 76   1   0  10   3  17   4]
- [  9 116  13   3   3   5   4]
- [ 44  31 151  23   9  24  45]
- [ 19   3  16  89   6   4  14]
- [  2   7  11   1  61   0   4]
- [  6   1   2   0   1  45   1]
- [ 19   7   4   3   6   9  68]]
-Node Classification on random seed  3169 -> 0.622
-Confusion Matrix:
- [[ 70   2   1  10   5  11   5]
- [  5 134   3   3   4   1  11]
- [ 37  30 141  37  12  14  37]
- [  5   2  11  99   5   5  15]
- [  2   8   5   1  62   3   4]
- [  9   1   4   2   0  39   6]
- [ 16   4  11  10   8  13  77]]
-Node Classification on random seed  3170 -> 0.623
-Confusion Matrix:
- [[ 67   1   5   7   6   9  10]
- [ 10 114   5   3   8   7   2]
- [ 34  22 173  25  27  19  38]
- [ 14   7  14 111   5   7  10]
- [  1   5   4   3  41   0   0]
- [  4   2   0   5   2  46   1]
- [ 17   3   7   1   8  19  71]]
-Node Classification on random seed  3171 -> 0.602
-Confusion Matrix:
- [[ 68   1   8   9   3   8  10]
- [  4 121   5   6   2   3   4]
- [ 26  27 116  67  37  19  29]
- [ 12   0  10 107   4   4   8]
- [  0  13   0   1  68   0   4]
- [  3   0   1   5   0  50  10]
- [ 22   1  11  10   5   6  72]]
-Node Classification on random seed  3172 -> 0.57
-Confusion Matrix:
- [[ 63  12   6   7   4   3  10]
- [  7 109   8   9  17   3   3]
- [ 36  20 117  33  56   5  42]
- [ 15   9   9 113  12   3   5]
- [  1  11   1   5  65   0   1]
- [  4   3   2   4   2  39   4]
- [  8   4   8  17   9  12  64]]
-Node Classification on random seed  3173 -> 0.631
-Confusion Matrix:
- [[ 57   2   6   3   4   8  14]
- [  8 126   1   1   8   0   1]
- [ 29  26 145  60  16  32  16]
- [  5   8  14 121   4   1  10]
- [  2   4   5   2  61   1   0]
- [  9   0   1   2   0  52   0]
- [ 12   4  15  20   6   9  69]]
-Node Classification on random seed  3174 -> 0.587
-Confusion Matrix:
- [[ 73   3   7   2   2  15  12]
- [  7 125  13   5   0   5   2]
- [ 33  13 122  39  31  31  35]
- [ 16   1  20  91   1   6  13]
- [  1   7   4   2  53   3   5]
- [  3   0   2   1   1  49  11]
- [  9   7  14   6  12  13  74]]
-Node Classification on random seed  3175 -> 0.583
-Confusion Matrix:
- [[ 67   2   4   5   5  18   4]
- [  4 111   6   8   3   7   3]
- [ 28  25 142  26  46  28  30]
- [  7   8  19  81  13   6  18]
- [  1   3   4   2  67   2   2]
- [  9   0   4   4   1  42   8]
- [  7   6   8   5  13  15  73]]
-Node Classification on random seed  3176 -> 0.598
-Confusion Matrix:
- [[ 67   2   3   8   2  10  17]
- [  5 116   4   0  11   2   2]
- [ 31  15 136  55  25  27  28]
- [ 18   5  10 108  13   7  10]
- [  1  10   2   0  61   0   0]
- [  2   0   3   1   1  44   4]
- [  8   3  12  11  18  16  66]]
-Node Classification on random seed  3177 -> 0.636
-Confusion Matrix:
- [[ 58   2   0   2   4  15  14]
- [  1 132   5   1   9   0   6]
- [ 19  25 154  21  43  24  38]
- [ 10   2  12 104   7   6  15]
- [  1   6   2   3  70   0   1]
- [  7   2   0   0   0  44   4]
- [ 12   1   6  10   8  20  74]]
-Node Classification on random seed  3178 -> 0.576
-Confusion Matrix:
- [[ 59   1   3   2   3  14  12]
- [  6 129   4   4   6   2   2]
- [ 49  34 125  43  21  18  39]
- [ 19   1  28  89   6   7  10]
- [  2  12   1   1  54   0   2]
- [  6   1   1   1   0  46   9]
- [ 12   3   5   9  13  12  74]]
-Node Classification on random seed  3179 -> 0.617
-Confusion Matrix:
- [[ 59   5  11   5   1  13  10]
- [  5 135   5   3   5   1   2]
- [ 11  27 135  28  46  31  25]
- [  4   5  15 120   2   6  10]
- [  2   6   3   2  54   1   2]
- [ 14   1   2   0   0  45   3]
- [ 15   4  15  13   8  16  69]]
-Node Classification on random seed  3180 -> 0.577
-Confusion Matrix:
- [[ 53   1   1   4   3  12  17]
- [ 12 138   5   2  12   1   3]
- [ 18  33  99  47  37  19  52]
- [ 19   2   8  84   3   9  12]
- [  2   9   2   1  79   1   4]
- [  5   0   8   0   1  42   8]
- [ 16   2   7   1  11  13  82]]
-Node Classification on random seed  3181 -> 0.614
-Confusion Matrix:
- [[ 57   4   2   6   1  20  10]
- [  4 128   3   3   3   7   5]
- [ 26  29 141  44  21  24  29]
- [ 15   5  12 104   3   9   7]
- [  6   6   5   8  69   0   4]
- [  6   1   2   1   0  37   4]
- [ 16   6   3   8   3  15  78]]
-Node Classification on random seed  3182 -> 0.647
-Confusion Matrix:
- [[ 76   4   5   7   2   6  21]
- [  3 130   8   1   3   2   5]
- [ 31  18 154  44  15  16  36]
- [ 21   6   9  97   4   5  11]
- [  3   5   3   0  62   2   1]
- [  8   1   1   1   0  37  11]
- [  8   3   4   3   8   8  91]]
-Node Classification on random seed  3183 -> 0.564
-Confusion Matrix:
- [[ 67   1   6  16   6  10   5]
- [  9 118   2   3  11   3   8]
- [ 25  12 100  30  69  34  41]
- [  5   6  12 109   3  14   9]
- [  1   6   2   1  58   0   3]
- [ 10   0   0   1   1  48   5]
- [ 18   2  22  10   7   7  64]]
-Node Classification on random seed  3184 -> 0.618
-Confusion Matrix:
- [[ 77   2   0   7   4   6  15]
- [  5 119   4   9  19   4   1]
- [ 29  13 147  35  31  10  47]
- [ 19   2  14 103   2  10   9]
- [  3   2   9   2  57   1   1]
- [  4   2   2   3   1  41   7]
- [  8   2   8   5   9  16  74]]
-Node Classification on random seed  3185 -> 0.62
-Confusion Matrix:
- [[ 72   4  10   3   4   5  10]
- [  2 145   4   2   2   1   3]
- [ 26  28 133  42   7  33  35]
- [ 15   7  21  94   2   2  18]
- [  2   2   8   0  62   1   3]
- [ 17   1   6   2   3  32   3]
- [ 17   1  11   3   4  10  82]]
-Node Classification on random seed  3186 -> 0.627
-Confusion Matrix:
- [[ 73   2   0   6   2  12  13]
- [  2 127   5   3   2  11   1]
- [ 32  23 138  42  37  13  35]
- [ 11   2  14 104   4   3  14]
- [  0   9   4   4  61   1   1]
- [  3   2   0   1   0  44   8]
- [ 11   3   7  14   4  12  80]]
-Node Classification on random seed  3187 -> 0.599
-Confusion Matrix:
- [[ 64   7  15   9   6   6  12]
- [ 12 115   7   4   9   1   1]
- [ 24  17 160  29  37  17  27]
- [ 14   2  29  96   7   8   3]
- [  3   6   2   1  65   2   1]
- [  9   0   3   0   1  34   2]
- [ 14   6   9   8   9  22  65]]
-Node Classification on random seed  3188 -> 0.618
-Confusion Matrix:
- [[ 54   3   0   7   6  17  17]
- [  2 136   7   1  10   3   1]
- [ 15  23 157  29  17  20  46]
- [  7   0   8 111   4  10  23]
- [  1   4   6   2  60   0   2]
- [  4   4   7   0   2  43   4]
- [  7   1  13   6  14  29  57]]
-Node Classification on random seed  3189 -> 0.624
-Confusion Matrix:
- [[ 68   2   9   5   4  10   4]
- [  4 132   1   1   5   5   8]
- [ 23  19 144  39  39  14  41]
- [  8   5  18 102  11   5   8]
- [  3   6   3   1  65   3   1]
- [  8   2   2   2   3  39   2]
- [  7   5  11  14   4  11  74]]
-Node Classification on random seed  3190 -> 0.641
-Confusion Matrix:
- [[ 64   2   2   8   3  14  11]
- [  2 138   5   1  12   5   5]
- [ 12  19 160  35  18  19  32]
- [  9   5  19  99  10   6  12]
- [  1   9   6   1  54   0   1]
- [  4   1   3   4   0  54   3]
- [ 15   8   7   3   9  18  72]]
-Node Classification on random seed  3191 -> 0.614
-Confusion Matrix:
- [[ 71   0   6   5   1  13   6]
- [  7 125   0   3   7  12   5]
- [ 41  21 135  32  25  31  25]
- [ 14   8  19  93   8  12   7]
- [  1   5   2   1  59   1   3]
- [  3   1   4   0   0  52   6]
- [  8   2   9   5   9  18  79]]
-Node Classification on random seed  3192 -> 0.612
-Confusion Matrix:
- [[ 83   5   5   3   1  11   3]
- [  4 126   9   2   5   0   3]
- [ 23  10 155  40  33  19  49]
- [ 10   2  13  89  17  10  10]
- [  2   5   2   6  46   3   0]
- [  6   2   2   1   1  48   4]
- [ 10   5   7   8   5  32  65]]
-Node Classification on random seed  3193 -> 0.641
-Confusion Matrix:
- [[ 68   3   6   5   5  14  13]
- [  2 146   5   4  10   0   6]
- [ 15  28 142  28  36  11  36]
- [  9   1  16 107  12   9  10]
- [  3   6   5   1  64   0   2]
- [  2   1   2   1   2  40   3]
- [  9   5   7   3   6  17  74]]
-Node Classification on random seed  3194 -> 0.611
-Confusion Matrix:
- [[ 57   5   6   9   6   9   8]
- [  4 129   8   6   2   1   1]
- [ 21  33 143  36  34  22  26]
- [ 18   7  14  96   4   7  13]
- [  4  10   5   0  62   1   3]
- [  2   1   0   3   1  54   6]
- [  8   3   6   3   6  27  70]]
-Node Classification on random seed  3195 -> 0.625
-Confusion Matrix:
- [[ 66   7   8  11   5   8   2]
- [  5 129  12   1   8   1   5]
- [ 34  17 163  37  16  23  26]
- [ 20   4   7  95   4   5  10]
- [  1   4   6   1  66   0   5]
- [ 11   2   4   4   1  36   2]
- [ 19   5   7   4   7  16  70]]
-Node Classification on random seed  3196 -> 0.597
-Confusion Matrix:
- [[ 65   2   3  10   4  23   1]
- [  5 131   4   1   8   2   1]
- [ 31  22 113  45  39  32  31]
- [ 13   2   8 123   3   9   7]
- [  1  10   4   3  64   0   1]
- [  5   5   3   5   3  36   7]
- [  6   5   3   7   2  27  65]]
-Node Classification on random seed  3197 -> 0.618
-Confusion Matrix:
- [[ 68   3   6   4   3  11  14]
- [ 10 154   7   3   1   4   3]
- [ 25  35 123  33  30  20  38]
- [ 17   3  14  99   6   4   7]
- [  2   7   5   4  62   0   4]
- [  9   2   1   1   0  39   4]
- [ 12   6  10   3   6   5  73]]
-Node Classification on random seed  3198 -> 0.618
-Confusion Matrix:
- [[ 68   1   1   4   5   4  20]
- [  3 122   4   2   4   1   3]
- [ 29  20 125  36  41  15  42]
- [ 19   3   9 107   1   4  13]
- [  4  11   1   0  57   2   4]
- [  2   1   0   2   1  52   4]
- [ 16   3   9  16   6  16  87]]
-Node Classification on random seed  3199 -> 0.63
-Confusion Matrix:
- [[ 73   5   2   7   1   9  15]
- [  2 140   5   1   6   9   3]
- [ 15  21 117  40  38  24  34]
- [ 13   3  12  95   3   2  21]
- [  3   7   3   2  60   1   5]
- [  3   2   1   3   0  52   6]
- [  4   3  10   7   5  14  93]]
-Node Classification on random seed  3200 -> 0.613
-Confusion Matrix:
- [[ 66   6   1   6   4  20   6]
- [  5 131   1   2   4   6   4]
- [ 29  25 138  44  36  15  27]
- [ 14   6  20 107   6   6  10]
- [  0   8   5   1  63   0   1]
- [  3   2   0   0   5  39   6]
- [ 11   3   5   9   2  23  69]]
-Node Classification on random seed  3201 -> 0.667
-Confusion Matrix:
- [[ 72   2   2  15   2  11  13]
- [  5 136   1   5   6   1   2]
- [ 17  33 159  21  16  21  35]
- [  7   4  14 127   5   3  16]
- [  1   6   5   2  55   2   1]
- [  3   2   2   2   0  43   9]
- [  9   3   6   3   9  11  75]]
-Node Classification on random seed  3202 -> 0.626
-Confusion Matrix:
- [[ 74   1   1   1   2   4  28]
- [  4 137   6   0   3   0   5]
- [ 21  39 134  41  30  16  44]
- [  5   3  11  91   7   7  14]
- [  0  10   0   1  60   1   4]
- [  0   1   2   0   1  54  10]
- [  7   2  12   7   8  15  76]]
-Node Classification on random seed  3203 -> 0.645
-Confusion Matrix:
- [[ 68   0   9   9   2   6   5]
- [ 10 132   3   3   4   2   1]
- [ 23  16 170  32  13  19  51]
- [  9   4  18 104   4   7   6]
- [  1   7   5   0  67   1   4]
- [  5   1   3   1   0  38   4]
- [ 23   7   9  15   6   7  66]]
-Node Classification on random seed  3204 -> 0.573
-Confusion Matrix:
- [[ 77   6   1   1   9   2  22]
- [  0 112   2   3   6   3   9]
- [ 23  11 145  34  40  30  31]
- [ 11   1  12  98   2   8  21]
- [  2  14   5   0  59   1   5]
- [  1   4   1   3   0  44   9]
- [  7   1   4  20  43  19  38]]
-Node Classification on random seed  3205 -> 0.602
-Confusion Matrix:
- [[ 65   6   5   3   2  16  14]
- [  3 126   2   2   3   1   2]
- [ 15  30 127  33  31  25  39]
- [ 12   6  10 105   3  15  26]
- [  3   6   3   3  60   1   2]
- [  5   0   4   1   2  43   4]
- [ 23   5   2   3   5  22  76]]
-Node Classification on random seed  3206 -> 0.617
-Confusion Matrix:
- [[ 72   4   0  10   5  13   9]
- [  7 127  10   2  12   0   1]
- [ 28  20 127  36  23  20  48]
- [  9   5  19 111   4   2  16]
- [  0   5   7   3  54   1   1]
- [  5   3   0   2   1  50   3]
- [ 20   2   5   4   4  14  76]]
-Node Classification on random seed  3207 -> 0.647
-Confusion Matrix:
- [[ 75   1   8   3   0  13   2]
- [  3 109   8   2  18   3   3]
- [ 35  18 175  30  26  20  35]
- [ 12   0   6 117   6   4  16]
- [  2   4   1   3  62   2   2]
- [  5   0   1   0   0  39   9]
- [ 10   2  15   0   6  19  70]]
-Node Classification on random seed  3208 -> 0.602
-Confusion Matrix:
- [[ 70   1   8   2   3  14  10]
- [  9 125   1   1   6   1   4]
- [ 23  31 143  34  27  12  53]
- [  9   4  28  87  10  10   7]
- [  2   6   2   0  57   2   0]
- [  5   3   2   3   1  50   4]
- [ 13  13   5   5   7  17  70]]
-Node Classification on random seed  3209 -> 0.627
-Confusion Matrix:
- [[ 74   4   9   7   5  15   3]
- [  8 115  13   7   3   3   1]
- [ 27  35 148  32  18  16  34]
- [  6   6   6 116   4   1  13]
- [  1   7   7   8  55   3   2]
- [ 10   4   0   1   0  38   1]
- [  9   4  16   5   3  16  81]]
-Node Classification on random seed  3210 -> 0.616
-Confusion Matrix:
- [[ 66   1   4   4   7  10   8]
- [  4 125   6   1   9   2   2]
- [ 23  15 148  47  33  22  35]
- [ 12   3  11 102   2   6   8]
- [  3   7   0   3  63   2   3]
- [ 10   1   0   2   1  53   5]
- [  8   4   8  10   6  36  59]]
-Node Classification on random seed  3211 -> 0.584
-Confusion Matrix:
- [[ 62   2   2   3   2  32  10]
- [  1 122   5   3   9   1   2]
- [ 22  17 124  65  41  33  20]
- [ 17   8  23  93   7   9  10]
- [  0   5   4   1  67   3   1]
- [  2   1   2   5   1  37   6]
- [  3   1  10  12   3  12  79]]
-Node Classification on random seed  3212 -> 0.651
-Confusion Matrix:
- [[ 72   3   2   5   3  13   5]
- [  4 130   4   0   6   2   7]
- [ 26  19 143  32  31  29  41]
- [ 13   2  11 110   1   3  15]
- [  3   6   1   0  65   2   2]
- [ 12   4   0   0   1  52   4]
- [ 11   5   6   3   3   9  79]]
-Node Classification on random seed  3213 -> 0.602
-Confusion Matrix:
- [[ 74   5  10   3   0  15   5]
- [  5 124   8   3   5   9   2]
- [ 15  19 139  55  23  22  40]
- [ 15   3  11  98   7   5  25]
- [  3   5   5   0  57   0   1]
- [  4   0   6   7   1  35   7]
- [ 12   3  10   3   6  15  75]]
-Node Classification on random seed  3214 -> 0.663
-Confusion Matrix:
- [[ 68   2  10  11   2   4  10]
- [  6 117  11   3   4   2   8]
- [ 16  25 188  23  18  13  50]
- [  6   3  17 117   8   2   6]
- [  2   4   3   1  57   0   4]
- [  4   3   4   1   0  40   4]
- [  7   3   9   6   5  17  76]]
-Node Classification on random seed  3215 -> 0.601
-Confusion Matrix:
- [[ 60   3   6   9   4   4  14]
- [ 10 110   8   8  14   4   4]
- [ 25  12 149  42  31  16  35]
- [ 21   2  13 100   5   5  13]
- [  0   3   2   6  72   0   6]
- [  7   0   2   1   3  41   5]
- [ 12   3   8  11  10  12  69]]
-Node Classification on random seed  3216 -> 0.638
-Confusion Matrix:
- [[ 91   3   4   3   2   9   5]
- [  5 121   4   1  12   3   5]
- [ 34  19 140  19  32  25  40]
- [  4   9  19 102   6   4  10]
- [  1   6   2   0  55   0   0]
- [  9   3   1   1   1  53   3]
- [  6   5   3   7   8  29  76]]
-Node Classification on random seed  3217 -> 0.622
-Confusion Matrix:
- [[ 76   1   4   0   7   8  11]
- [  1 130   7  11   2   5   2]
- [ 28  27 136  55  25  18  27]
- [  7   8  13 103   4   4  14]
- [  0   7   7   1  56   2   0]
- [  1   3   2   0   1  48   1]
- [ 14   4   6   6  13  21  73]]
-Node Classification on random seed  3218 -> 0.618
-Confusion Matrix:
- [[ 63   1   6  13   3  10  18]
- [  3 134   4   1  10   3   8]
- [ 30  21 161  21  23  27  39]
- [ 13   6  11  99   4   5  15]
- [  2   8   6   0  52   0   7]
- [  6   2   0   2   4  37   2]
- [  6   4   7   3   4  24  72]]
-Node Classification on random seed  3219 -> 0.613
-Confusion Matrix:
- [[ 88   4   3   2   4  11   8]
- [  6 134   8   3  18   0   2]
- [ 24  19 142  26  30  20  41]
- [ 20   5  19  88   6   4  12]
- [  2   5   5   2  57   2   0]
- [  5   2   4   2   1  38   3]
- [ 18   4   5   3  16  13  66]]
-Node Classification on random seed  3220 -> 0.628
-Confusion Matrix:
- [[ 64   3   1   8   6  11   7]
- [  7 114   6   3   3   2   5]
- [ 18  27 161  40  21  26  40]
- [ 23   6  16  88   6   4  16]
- [  0   6   3   2  67   1   1]
- [  7   1   3   1   0  54   2]
- [ 15   2   3   4   8   8  80]]
-Node Classification on random seed  3221 -> 0.636
-Confusion Matrix:
- [[ 79   4   0   5  10   6  11]
- [  8 132   6   3   6   5   5]
- [ 16  13 152  14  29  30  50]
- [ 19   1  15  85   7  16  17]
- [  2   6   4   1  60   0   4]
- [  1   0   4   1   3  47   4]
- [ 13   6   1   3   2  13  81]]
-Node Classification on random seed  3222 -> 0.595
-Confusion Matrix:
- [[ 73   0   1   3   4   7   7]
- [  5 116   5  20   3   4   2]
- [ 20  15 142  42  38  30  27]
- [ 17   2  15  86  17  11   8]
- [  0   5  10   4  54   1   1]
- [  6   1   3   6   2  41   0]
- [ 12   3   6  10  12  20  83]]
-Node Classification on random seed  3223 -> 0.634
-Confusion Matrix:
- [[ 63   1   4   9   7  11   5]
- [  2 126   2   4   9   3   0]
- [ 25  21 137  26  34  11  55]
- [ 23   4  14 110   7   6  12]
- [  1   4   2   2  62   0   2]
- [  4   1   2   0   0  47   3]
- [ 12   3   4   8   7  16  89]]
-Node Classification on random seed  3224 -> 0.605
-Confusion Matrix:
- [[ 53   3   9   6   6  17  14]
- [  3 126   7   3  14   2   8]
- [ 29  13 145  49  19  22  29]
- [  6   3  13 115   3   6   9]
- [  1   5   0   0  50   1   2]
- [  4   2  10   1   0  49   5]
- [ 10   6  21   5   9  20  67]]
-Node Classification on random seed  3225 -> 0.623
-Confusion Matrix:
- [[ 80   1   5   4   4  11  15]
- [ 11 128   3   7   8   6   4]
- [ 33  17 122  41  20  23  36]
- [  4   1   7 123   7   9   9]
- [  1   8   3   0  52   3   5]
- [  5   3   0   3   2  51   2]
- [  5   4   5  17   9  16  67]]
-Node Classification on random seed  3226 -> 0.615
-Confusion Matrix:
- [[ 65   0   1   8   1   9   2]
- [  8 136   1   0   6   2   9]
- [ 29  10 136  49  25  22  51]
- [  8   3  11 106   2   7   6]
- [  1  13   1   1  57   5   3]
- [  4   2   0   2   0  52   5]
- [ 11   9  10  13  12  23  63]]
-Node Classification on random seed  3227 -> 0.585
-Confusion Matrix:
- [[ 60   9  14   8   3   6  10]
- [  6 130   8   0   9   0   5]
- [ 22  19 144  29  39   7  42]
- [ 25  10  21  88   2   3  14]
- [  0   7   3   1  49   0   1]
- [ 11   3   2   4   2  46   4]
- [ 30   7   5   9   2  13  68]]
-Node Classification on random seed  3228 -> 0.557
-Confusion Matrix:
- [[ 53   4  14   3   9   7   7]
- [  7 104   5   4  12   6   3]
- [ 21  37 133  42  34  19  49]
- [ 19   9  12  96   1  10   8]
- [  0  13   1   0  57   0   6]
- [  7   2   1   0   0  47   1]
- [ 12   4  12  19   7  16  67]]
-Node Classification on random seed  3229 -> 0.657
-Confusion Matrix:
- [[ 81   1   2   5   1   8   9]
- [  1 144   7   3  14   1   0]
- [ 22  21 145  38  28  14  25]
- [  2   1  20  86   5  13  11]
- [  3   7   0   3  58   1   3]
- [  3   3   2   3   2  51   3]
- [ 17   6   7   3  13  12  92]]
-Node Classification on random seed  3230 -> 0.655
-Confusion Matrix:
- [[ 88   1   5   3   4   7   4]
- [  2 123   4   7  10   1   4]
- [ 21  17 176  22  21  19  34]
- [ 33   3  10  86   6  10   8]
- [  2   5   7   2  69   2   2]
- [  9   2   2   1   2  42   3]
- [ 14   2  11   7   6  10  71]]
-Node Classification on random seed  3231 -> 0.588
-Confusion Matrix:
- [[ 79   1   4   4   4   7  14]
- [  7 134   3   1   9   3  10]
- [ 25  23  97  71  26  22  35]
- [  7   7  11  99   3   6  19]
- [  2   9   2   4  59   1   3]
- [  8   1   1   3   0  37   3]
- [ 13   7   7   7   4  15  83]]
-Node Classification on random seed  3232 -> 0.559
-Confusion Matrix:
- [[ 74   5   9   8   4  12   5]
- [  6 131   2   1   9   0   3]
- [ 20  23 108  41  47  16  50]
- [ 20   3  21  73  11  14  17]
- [  1   9   1   1  55   3   4]
- [  1  10   1   1   6  45   6]
- [  9   2  11   5  10  13  73]]
-Node Classification on random seed  3233 -> 0.613
-Confusion Matrix:
- [[ 63   2   9  16   2  17  13]
- [  6 134   3   0   1   0   4]
- [ 32  18 143  26  21  11  40]
- [ 21   2  26 105   7   2   8]
- [  5   6   4   0  54   0   0]
- [  4   2   2   4   0  39   8]
- [ 26   3  11   7   4  14  75]]
-Node Classification on random seed  3234 -> 0.597
-Confusion Matrix:
- [[ 52   3   7   3   7  32   6]
- [  2 135   6   3   7   1   2]
- [ 10  21 149  25  33  23  51]
- [ 18   4  10 102   4  11   9]
- [  2  12   5   1  49   1   4]
- [  1   0   0   1   3  45   2]
- [ 11   3  11   7  14  27  65]]
-Node Classification on random seed  3235 -> 0.611
-Confusion Matrix:
- [[ 72   0   3   4   2  10  10]
- [  6 114   9   3   5   4   7]
- [ 26  47 141  37  17  13  33]
- [ 32   4  12  96   3   3  12]
- [  3   3   0   4  73   0   2]
- [  7   1   6   0   0  30   9]
- [ 18   4   6   4  10  10  85]]
-Node Classification on random seed  3236 -> 0.612
-Confusion Matrix:
- [[ 72   3   3   6   2  10  18]
- [  5 128   1   0   9   4  10]
- [ 24  32 137  22  34  16  45]
- [  5   4  21  91   6   7   9]
- [  2   8   1   1  69   2   0]
- [  6   1   1   3   3  34   5]
- [  8   6   5   9  20  11  81]]
-Node Classification on random seed  3237 -> 0.613
-Confusion Matrix:
- [[ 66   2   4   3   3  20  11]
- [ 10 114  13   5   7   0   1]
- [ 27  16 180  16  32  23  42]
- [ 11   1  12  79   5  11  22]
- [  1   9   5   2  51   1   1]
- [  5   1   8   3   0  51   4]
- [ 21   3   5   3   6  12  72]]
-Node Classification on random seed  3238 -> 0.609
-Confusion Matrix:
- [[ 72   1   2   5  11   5  14]
- [  4 129   3   0   9   4   6]
- [ 24  23 167  46  18  16  32]
- [  5   7  13  86   3   3  27]
- [  1   6   9   5  59   0   2]
- [  1   1   2   4   5  40   4]
- [ 11   1  13  17   9  19  56]]
-Node Classification on random seed  3239 -> 0.638
-Confusion Matrix:
- [[ 63  11   4   2   2  12  15]
- [  6 128   5   5   5   2   5]
- [ 19  33 142  28  38  19  32]
- [  7   4  18 108   2   6  15]
- [  0   2   6   2  67   1   2]
- [  3   0   2   0   0  47   3]
- [ 12   3   9   6   3  13  83]]
-Node Classification on random seed  3240 -> 0.602
-Confusion Matrix:
- [[ 59   3   8   6   3  18  16]
- [  8 127   5   1   5   1   4]
- [ 20  28 139  34  28  19  42]
- [ 12   5  23  93   3   4   8]
- [  2   7   0   3  64   1   4]
- [  4   2   2   2   0  43   5]
- [ 10   9  14   9   4  16  77]]
-Node Classification on random seed  3241 -> 0.596
-Confusion Matrix:
- [[ 69   3   2   2   1  15  13]
- [  2 139   0   1   6   5   5]
- [ 26  14 111  46  47  17  52]
- [  7   8  15 109   3   5  17]
- [  3   7   2   3  56   0   0]
- [  5   3   0   2   2  41  11]
- [ 15   3   6   3  11  16  71]]
-Node Classification on random seed  3242 -> 0.625
-Confusion Matrix:
- [[ 88   1   7   5   1   6  17]
- [  7 111  10   3   9   4   2]
- [ 14  19 136  30  35  15  38]
- [  7   3  17  97   8   6  27]
- [  6   2   5   4  58   3   0]
- [  8   2   0   0   0  46   9]
- [ 13   3   9   6   7   7  89]]
-Node Classification on random seed  3243 -> 0.614
-Confusion Matrix:
- [[ 78   9   5   7   7  16   4]
- [  2 107   2   2  14   1   6]
- [ 32  28 143  38  27  16  36]
- [ 11   8  13  99   6   7  14]
- [  0   6   3   0  73   3   5]
- [  2   2   4   1   0  38   7]
- [  6   5   7   5   8  11  76]]
-Node Classification on random seed  3244 -> 0.611
-Confusion Matrix:
- [[ 88   1   1   3   2   9   5]
- [  8 127   3   3   5   2   7]
- [ 32  19 126  37  44  20  41]
- [ 13   2  23  82   5   9  17]
- [  1   1   7   0  57   1   3]
- [  7   1   1   1   0  46   9]
- [ 12   1   5   4  13  11  85]]
-Node Classification on random seed  3245 -> 0.629
-Confusion Matrix:
- [[ 57   1   7   3   1  12  10]
- [  2 143   4   1   6   5   6]
- [ 17  27 143  40  46  15  29]
- [ 13   7  12 106   9   7  13]
- [  0   4   2   2  62   1   0]
- [  9   2   0   2   0  40   2]
- [  5   7  16   8   5  13  78]]
-Node Classification on random seed  3246 -> 0.612
-Confusion Matrix:
- [[ 82   3   4   0   2   9  10]
- [  5 102   6   5   8   2  13]
- [ 40  24 155  22  38  18  23]
- [  8   3  43  91   3   6   9]
- [  2   5   5   0  75   0   2]
- [  3   0   2   2   2  40   4]
- [ 17   3  12   8   6  11  67]]
-Node Classification on random seed  3247 -> 0.6
-Confusion Matrix:
- [[ 85   6   1   6   4   9   6]
- [  3 127   9   2  12   2   2]
- [ 30  23 125  42  27  29  29]
- [ 14   2  13 108   4   8  13]
- [  3   3   6   1  54   0   2]
- [ 11   0   0  11   2  35   9]
- [ 14   1   7  13  10  11  66]]
-Node Classification on random seed  3248 -> 0.655
-Confusion Matrix:
- [[ 71   2   4   6   3  16   3]
- [  8 123   2   6  16   0   1]
- [ 14  14 154  39  30  19  33]
- [  5   1  19 107   8   7  15]
- [  2   4   4   0  68   3   6]
- [  3   1   3   3   0  52   4]
- [  7   4   4   8   4  14  80]]
-Node Classification on random seed  3249 -> 0.605
-Confusion Matrix:
- [[ 63   3   3   2   1   7  16]
- [  4 118   7   2   8   4  14]
- [ 19  21 128  25  31  22  55]
- [  9   5  16 112   7   6  18]
- [  0   9   8   0  57   3   3]
- [  6   0   7   1   2  42  10]
- [  7   5   9   5   7   8  85]]
-Node Classification on random seed  3250 -> 0.587
-Confusion Matrix:
- [[ 70   1   6   5   4  19  14]
- [  6 115   4   1   6   1  13]
- [ 38  22 109  36  30  36  47]
- [ 13   0  18 111   3   7  13]
- [  5   2   3   0  57   1   2]
- [  2   1   2   2   1  52   3]
- [ 11   3  10   4   2  16  73]]
-Node Classification on random seed  3251 -> 0.609
-Confusion Matrix:
- [[ 90   0   1   6   4   3   3]
- [  4 129   5   3  11   4   4]
- [ 32  31 140  47  22  14  25]
- [ 13   4  21  88  20   6  15]
- [  3   2   3   4  50   0   1]
- [  6   2   8   1   2  36   2]
- [ 10   6  13   8  13   9  76]]
-Node Classification on random seed  3252 -> 0.614
-Confusion Matrix:
- [[ 65   1   5   6   3  10  16]
- [  0 126   6   2  13   0   9]
- [ 60  16 125  36  21  18  31]
- [  8   3  16 104   7   4  20]
- [  1   4   1   2  78   1   1]
- [  3   1   4   1   0  49   2]
- [ 12   3  16   4   6  13  67]]
-Node Classification on random seed  3253 -> 0.631
-Confusion Matrix:
- [[ 74   6   0   9   3  13  10]
- [  3 126   6   2   1   4   3]
- [ 28  31 153  26  18  18  43]
- [ 25   1  10  82   7  14  14]
- [  1   9   1   1  52   1   5]
- [  2   1   2   1   1  58   4]
- [  8   3   7   4   4  19  86]]
-Node Classification on random seed  3254 -> 0.624
-Confusion Matrix:
- [[ 65   4   1   3   9   6   8]
- [  4 139   5   2   9   1   7]
- [ 34  19 137  37  26  15  28]
- [ 15   6  13 102  17   8  11]
- [  0  10   5   0  65   0   1]
- [  6   1   6   0   2  42   8]
- [ 23   3   5   7   4   7  74]]
-Node Classification on random seed  3255 -> 0.615
-Confusion Matrix:
- [[ 53   8   7   5   1  13  13]
- [  2 128  11   4   6   1   3]
- [ 14  18 152  36  23  36  39]
- [ 17   3   5 121   4   7  10]
- [  0   9   6   0  54   1   3]
- [  3   3   8   2   9  27   8]
- [  7   7   9  10   6   8  80]]
-Node Classification on random seed  3256 -> 0.621
-Confusion Matrix:
- [[ 76   0   1   3   1  15  10]
- [ 15 120   6   5   7   8   1]
- [ 22  32 138  37  16  27  36]
- [ 13   1  14 112   4   6   8]
- [  3   4   4   3  54   0   1]
- [  9   6   0   5   4  41   5]
- [  5   1  13   8   4  16  80]]
-Node Classification on random seed  3257 -> 0.612
-Confusion Matrix:
- [[ 67   0  14   4   2   2  16]
- [  7 129   7  12  10   2   9]
- [ 20  24 136  34  26  15  44]
- [ 10   3  17  98   4   6  15]
- [  2   4   2   0  59   0   6]
- [  6   0   4   0   2  35   6]
- [ 14   1  14   6   9   9  88]]
-Node Classification on random seed  3258 -> 0.615
-Confusion Matrix:
- [[ 74   3   9   7   3  11   6]
- [  1 138   2   1   8   2   1]
- [ 39  17 143  24  36  28  35]
- [ 22   2  13  80   7   7  11]
- [  1  11   3   0  67   1   1]
- [ 11   0   3   2   1  52   3]
- [ 13   2  13   5   8  12  61]]
-Node Classification on random seed  3259 -> 0.592
-Confusion Matrix:
- [[ 82   2   0   2   4  15   8]
- [  5 118   7  11   1   2   6]
- [ 46  27 120  31  36  26  38]
- [ 10   6  11 113   4   8  13]
- [  4   4   4   0  58   1   5]
- [  9   0   1   2   1  39   7]
- [  9   2  10   3  10  17  62]]
-Node Classification on random seed  3260 -> 0.572
-Confusion Matrix:
- [[ 58   2   6   5   8  15  17]
- [  2 140   5   8   9   1   3]
- [ 19  20 107  54  22  27  56]
- [ 16   7  19  86   0  18  15]
- [  1   9   4   2  58   0   0]
- [  4   1   3   1   1  38  11]
- [  0   3   8   6  10  10  85]]
-Node Classification on random seed  3261 -> 0.563
-Confusion Matrix:
- [[ 67   2  12   7   8   6   3]
- [  3 138  10   4   4   2   3]
- [ 31  19 126  58  29  26  25]
- [  8   2  36  89   1   5  13]
- [  1   9   6   3  56   0   0]
- [  6   1   4   0   1  43   3]
- [ 13   0  23   7  30  13  44]]
-Node Classification on random seed  3262 -> 0.585
-Confusion Matrix:
- [[ 52   2   6   7   3  10  20]
- [  5 138  16   5   6   1   4]
- [ 19  17 134  30  42  12  37]
- [ 11   7  19  93   9   5  10]
- [  3   6   7   4  58   4   2]
- [  7   0   4   0   2  39   4]
- [ 17   8   7   7  19  11  71]]
-Node Classification on random seed  3263 -> 0.624
-Confusion Matrix:
- [[ 61   2   1   1   7  13  18]
- [  0 131   5   3   7   2   0]
- [ 16  27 144  29  33  16  55]
- [  5   3  19 123   3   3  11]
- [  2   4   3   1  65   1   0]
- [  2   1   1   0   3  40   6]
- [ 13   1  11  20  15  13  60]]
-Node Classification on random seed  3264 -> 0.66
-Confusion Matrix:
- [[ 71   1   4   3  10   8   7]
- [  3 125   7   3  10   7   4]
- [ 18  18 189  19  17  18  40]
- [  6   9  13  80  11   9  16]
- [  1   7   1   2  69   1   3]
- [ 10   4   5   1   2  34  11]
- [  7   2   9   3   2   8  92]]
-Node Classification on random seed  3265 -> 0.632
-Confusion Matrix:
- [[ 76   9   3   5   4   3  13]
- [  5 122   7   2   6   7   9]
- [ 35  14 152  21  16  22  49]
- [ 11   2  18 111   1   2   7]
- [  2   5   6   7  55   2   4]
- [  2   3   1   5   4  47   5]
- [  8   3   4   5  20  11  69]]
-Node Classification on random seed  3266 -> 0.619
-Confusion Matrix:
- [[ 62   3  11   3   4  13  14]
- [  4 150   6   1   4   5   4]
- [ 30  30 130  18  25  28  39]
- [  7   4  16 100   6   7  22]
- [  0   5   6   2  67   0   1]
- [  1   2   1   0   1  50   7]
- [ 12   5   6   6   5  17  60]]
-Node Classification on random seed  3267 -> 0.61
-Confusion Matrix:
- [[ 78   1   5   5   6  11   4]
- [  5 133  10   4   4   2   5]
- [ 18  22 131  40  33  29  35]
- [ 11   2  19 105   8   6   9]
- [  2   5   3   5  52   1   4]
- [  4   2   0   1   2  44   8]
- [  7   6  18  15   3  10  67]]
-Node Classification on random seed  3268 -> 0.648
-Confusion Matrix:
- [[ 67   2   5   5   3   4  11]
- [  8 159   1   0   4   0   6]
- [ 29  15 158  19  19  19  36]
- [ 17   1  10 100   9   5  22]
- [  0   6   5   0  65   3   5]
- [ 16   2   0   2   0  31   7]
- [ 19   6   5   1   5  20  68]]
-Node Classification on random seed  3269 -> 0.562
-Confusion Matrix:
- [[ 73   6   2   8   2   5   9]
- [  2 125   3   5   3   2   5]
- [ 25  36 117  37  28  12  53]
- [ 21   5  20  77  12   6  13]
- [  4  10   4   2  60   0   2]
- [ 12   5   1   9   0  35   4]
- [ 19   2  19  10   4  11  75]]
-Node Classification on random seed  3270 -> 0.584
-Confusion Matrix:
- [[ 69   2   7   7   8   6  13]
- [  5 129  11   0  11   2   1]
- [ 28  18 155  51  33  24  26]
- [ 23   1  16  70   7  10   6]
- [  0   9   5   5  61   0   0]
- [  2   2   1   9   4  52   5]
- [ 17   2  11   9   5  14  48]]
-Node Classification on random seed  3271 -> 0.619
-Confusion Matrix:
- [[ 65   2   4   0   6   8  15]
- [  3 122  10   6   9   1   5]
- [ 21  21 143  52  37  10  48]
- [ 14   7  18 102   9   3   5]
- [  2   6   2   3  63   0   2]
- [  3   1   2   0   0  41   6]
- [  9   3   6   5   5  12  83]]
-Node Classification on random seed  3272 -> 0.625
-Confusion Matrix:
- [[ 75   1   3   9   1   7  13]
- [ 12 137   1   2   3   3   8]
- [ 22  26 157  33  13  18  36]
- [ 18   8   8  95   6   3  15]
- [  5   5   9   0  57   3   4]
- [  7   1   4   1   3  37  11]
- [ 16   3  11   6   6  11  67]]
-Node Classification on random seed  3273 -> 0.652
-Confusion Matrix:
- [[ 79   2   3   3   1   7  18]
- [  9 125   7   4   7   2   7]
- [ 18  16 150  22  34  17  35]
- [  7   4  17 105   8   7  18]
- [  0   8   8   1  48   0   2]
- [ 10   3   0   0   0  46   5]
- [ 14   4   2   5   4   9  99]]
-Node Classification on random seed  3274 -> 0.617
-Confusion Matrix:
- [[ 65   3   6   2   2  25   2]
- [  5 118   6   1  14   1   9]
- [ 17  22 154  43  35  24  19]
- [  9   5   9 112   5   9  14]
- [  3   4   6   3  53   0   4]
- [  7   2   2   2   1  35   3]
- [  9   5  13   2   8  22  80]]
-Node Classification on random seed  3275 -> 0.618
-Confusion Matrix:
- [[ 69   2  10   9   4  14  15]
- [  5 119   9   0  11   0  13]
- [ 24  17 165  24  25  18  36]
- [  6   2  22  93   6   3   7]
- [  3   6   4   4  59   2   5]
- [  8   2   3   0   1  42   9]
- [  9   1   9   6  16  12  71]]
-Node Classification on random seed  3276 -> 0.646
-Confusion Matrix:
- [[ 68   2   2  13   4   9  10]
- [  4 133   4   4   0   5   3]
- [ 20  16 150  31  26  12  40]
- [ 11   4  10 121   4   4  18]
- [  0   7   4   2  49   1   5]
- [  6   0   5   7   1  47   5]
- [  9   2  11  11   5  17  78]]
-Node Classification on random seed  3277 -> 0.668
-Confusion Matrix:
- [[ 70   4   3   2   1   9   8]
- [  3 136   2   5   3   0   3]
- [ 16  29 163  16  30  28  43]
- [  4   4  13 111   4   6  24]
- [  1   7   5   0  58   0   1]
- [  6   1   1   0   0  41   7]
- [ 15   1   2  13   6   6  89]]
-Node Classification on random seed  3278 -> 0.603
-Confusion Matrix:
- [[ 66   5   4   7   1  15   9]
- [  5 125   5   2  16   0   6]
- [ 17  16 147  21  63  12  33]
- [ 15   1  24  80  19   8   6]
- [  3   3   2   3  66   0   5]
- [ 10   0   1   1   0  39   1]
- [ 13   3  12   7   3  20  80]]
-Node Classification on random seed  3279 -> 0.605
-Confusion Matrix:
- [[ 83   6   6  12   3   4  10]
- [  1 122   3   3  10   5   7]
- [ 24  25 125  42  30  22  46]
- [  5   2  20 103   4   8   9]
- [  1   3   3   1  59   4   1]
- [  5   1   0   0   1  50   6]
- [ 10   3  13  14  12  10  63]]
-Node Classification on random seed  3280 -> 0.598
-Confusion Matrix:
- [[ 66   1   3   9   7  15  10]
- [  5 124   4   2   7   1   6]
- [ 20  22 139  50  37  23  28]
- [ 15   6  21  95   2   1  12]
- [  0   9   3   4  54   3   3]
- [  9   0   3   1   2  42   2]
- [  7   3   9  10   4  23  78]]
-Node Classification on random seed  3281 -> 0.623
-Confusion Matrix:
- [[ 72   1  11   1   2   8   5]
- [  1 137  13   2   7   3   2]
- [ 24  27 118  30  29  21  60]
- [ 12   5  21  96   1   1  20]
- [  0   8   4   2  58   0   2]
- [  5   1   0   1   0  58   3]
- [ 11   8   8   3   4  10  84]]
-Node Classification on random seed  3282 -> 0.61
-Confusion Matrix:
- [[ 61   4  10   1   5   9   8]
- [  1 127   1   1  11   3   4]
- [ 15  25 143  36  30  14  51]
- [ 19   7  16 104   7   7  20]
- [  0   9   4   0  65   1   3]
- [  5   1   1   2   1  51   5]
- [ 14   6   6   4  13  10  59]]
-Node Classification on random seed  3283 -> 0.6
-Confusion Matrix:
- [[ 60   7   7   8   7   6   6]
- [ 13 138   9   3   4   1   6]
- [ 28  17 131  44  33  16  53]
- [ 18   9  16  93   8   2   7]
- [  0   7   2   0  61   3   2]
- [  5   0   4   3   1  40   5]
- [  6   5   7  10   3   9  77]]
-Node Classification on random seed  3284 -> 0.555
-Confusion Matrix:
- [[ 62   1   3   9   9  11  21]
- [  9 117   9   3   3   6   3]
- [ 60   9 121  40  44  24  27]
- [  5   0  11 113   3   6  12]
- [  2   7   1   3  58   0   1]
- [  8   2   0   2   1  37   4]
- [ 26   2  11   6  28  13  47]]
-Node Classification on random seed  3285 -> 0.581
-Confusion Matrix:
- [[ 57   1   8   4   3  11  14]
- [  9 128   3   0   5   1   6]
- [ 24  26 110  17  20  27  79]
- [ 10   6  11 115   6  10  19]
- [  2   8   3   1  61   2   2]
- [  4   2   9   2   1  39  10]
- [  7   2   9   1   5  29  71]]
-Node Classification on random seed  3286 -> 0.643
-Confusion Matrix:
- [[ 82   4   3   5   2   9  12]
- [  3 132   3   2   6   1  20]
- [ 18  27 156  25  21  25  30]
- [  8   4   8 101   2  12  16]
- [  1   5   3   6  61   1   3]
- [  3   1   0   3   2  40  13]
- [  8   3   2   9   7  21  71]]
-Node Classification on random seed  3287 -> 0.609
-Confusion Matrix:
- [[ 63   1   6  10   5  18  19]
- [  7 129   2   2   3   6   1]
- [ 14  31 125  29  27  32  36]
- [ 26   3   7 110   2  12   7]
- [  1   7   3   1  58   3   2]
- [  6   4   0   1   3  52   9]
- [  9  11  13   2   2   8  72]]
-Node Classification on random seed  3288 -> 0.621
-Confusion Matrix:
- [[ 57   1   3   6   2  22  11]
- [  1 123  10   2   9   1   5]
- [ 19  33 156  22  31  21  30]
- [  6   4  29  95   7   5  12]
- [  2   1   2   0  58   1   3]
- [  5   1   3   3   3  40   4]
- [  9   3  15   3   7  22  92]]
-Node Classification on random seed  3289 -> 0.605
-Confusion Matrix:
- [[ 64   0   6  11   5  10  11]
- [ 15 111   3   0   7   3  11]
- [ 27  13 130  29  29  23  58]
- [  5   3  15 113   3  17  11]
- [  2   5   1   1  69   2   2]
- [  1   0   9   1   0  46   3]
- [ 13   2   6  10   7  15  72]]
-Node Classification on random seed  3290 -> 0.624
-Confusion Matrix:
- [[ 83   0   2   4   5   3   2]
- [  4 119   7   3  15   5   6]
- [ 42  18 131  42  27  10  45]
- [  7   8  20 104   7   1  17]
- [  2   6   2   0  57   1   2]
- [  3   0   3   3   2  54   2]
- [ 12   2  11   8   7  10  76]]
-Node Classification on random seed  3291 -> 0.555
-Confusion Matrix:
- [[ 85   0   1   6   6   8  10]
- [  2 131   5   7  11   4   4]
- [ 34  18  82  33  62  25  51]
- [ 11   1  15  99  15   7   7]
- [  2   4   1   4  52   1   1]
- [  9   3   0   5   0  47  11]
- [  6   5   8  13   9  20  59]]
-Node Classification on random seed  3292 -> 0.607
-Confusion Matrix:
- [[ 72   2   2   4   4  10   3]
- [  2 125   4   5   7   4   8]
- [ 21  18 144  59  23  18  34]
- [  7   7  15 110   3   3  13]
- [  4   3   3   2  61   1   2]
- [ 15   1   4   0   2  41   6]
- [ 16   7  16  10   5  20  54]]
-Node Classification on random seed  3293 -> 0.641
-Confusion Matrix:
- [[ 76   1   6   8   8   9   0]
- [  2 129   4   3   8   2   4]
- [ 20   9 155  44  25  19  42]
- [ 19   3  14 104   3   4   9]
- [  0   4   7   0  56   1   1]
- [ 13   2   2   0   1  46   2]
- [ 15   3  11   8  12  11  75]]
-Node Classification on random seed  3294 -> 0.594
-Confusion Matrix:
- [[ 72   2   4   5   5  23  10]
- [  2 133   2   1   5   0   5]
- [ 24  24 128  36  23  27  34]
- [ 11   7  18  92   8   6  12]
- [  2  13   5   0  52   1   2]
- [  9   1   3   1   1  40   9]
- [  7   5  12   7   6  28  77]]
-Node Classification on random seed  3295 -> 0.615
-Confusion Matrix:
- [[ 72   6   4   3   5  11  10]
- [  4 119   9   3  14   4   1]
- [ 21  21 154  24  36  22  22]
- [ 13   5  37  85   8   7  11]
- [  1   7   6   0  66   0   1]
- [  5   3   1   0   1  48   7]
- [  9   3   5   8   8  19  71]]
-Node Classification on random seed  3296 -> 0.6
-Confusion Matrix:
- [[ 78   1   6   0   2   4  11]
- [  5 130   4   4   9   2   3]
- [ 29  17 114  61  19  18  46]
- [ 23   6  10 113   3   2  12]
- [  0   8   5   1  58   1   5]
- [  4   1   1   6   2  36   5]
- [ 17   7  14   6   7  13  71]]
-Node Classification on random seed  3297 -> 0.603
-Confusion Matrix:
- [[ 68   1   3  10   2  11   8]
- [  4 141   4   0   4   0   6]
- [ 26  27 129  29  35  21  39]
- [ 27   5  13  80   4   7  15]
- [  1   7   4   1  60   2   8]
- [  5   1   2   3   2  50   7]
- [ 10   3  14   8   2  16  75]]
-Node Classification on random seed  3298 -> 0.608
-Confusion Matrix:
- [[ 77   2   5   3   2   9  11]
- [  2 133   0   4   8   3   2]
- [ 24  31 105  40  47  26  35]
- [  7   6  20 109   2   8   6]
- [  2   5   1   1  68   2   3]
- [  8   3   1   5   0  36   2]
- [ 11   9   7  12   6  11  80]]
-Node Classification on random seed  3299 -> 0.631
-Confusion Matrix:
- [[ 80   8   4   6   2   9   3]
- [  7 128   2   5   5   7   1]
- [ 20  28 156  16  24  25  41]
- [ 21   4  21  79   6  14  15]
- [  2   5   5   0  63   0   3]
- [  7   3   2   4   2  56   3]
- [ 10   5   7   8   4   5  69]]
-Node Classification on random seed  3300 -> 0.603
-Confusion Matrix:
- [[ 73   0   2   2   1  18   3]
- [ 12 118   8   2   6   3   4]
- [ 43  14 124  49  27  30  38]
- [ 10   3  22 112   3   2   9]
- [  0   8   3   2  64   1   3]
- [  3   2   0   1   0  40   1]
- [ 16   8   3   8  10  17  72]]
-Node Classification on random seed  3301 -> 0.605
-Confusion Matrix:
- [[ 80   4   2   3   5  11   8]
- [  6 115   7   2  13   1   0]
- [ 21  23 159  40  42  21  27]
- [ 17   3  10  77  10   8  10]
- [  4   6   4   4  50   0   4]
- [  5   2   1   6   2  46   2]
- [ 19   1   7   5  14  15  78]]
-Node Classification on random seed  3302 -> 0.623
-Confusion Matrix:
- [[ 73   3   7   6   5   8   6]
- [  7 104  17   6  12   3   4]
- [ 11  23 150  36  39  18  40]
- [  6   4  10 123   1   5   6]
- [  1   1   2   6  67   0   3]
- [  5   3   3   4   2  41   5]
- [ 11   2   6  14  14  12  65]]
-Node Classification on random seed  3303 -> 0.573
-Confusion Matrix:
- [[ 76   3   4   3   6  10   1]
- [  3 136   3   6  12   0   6]
- [ 27  21 106  31  82  13  32]
- [ 17   5  13  83   9   6  21]
- [  2   8   2   0  66   0   2]
- [  6   3   2   6   2  42   5]
- [  8   9   9   4   8  17  64]]
-Node Classification on random seed  3304 -> 0.608
-Confusion Matrix:
- [[ 77   7   8   4   5  14   3]
- [ 10 137   6   3   4   3   3]
- [ 26  19 127  43  26  21  40]
- [ 15   0  13 101   1   5  17]
- [  1  10   4   0  60   2   1]
- [  8   0   3   1   0  48   4]
- [ 26   5   8   9   6   8  58]]
-Node Classification on random seed  3305 -> 0.641
-Confusion Matrix:
- [[ 64   2   2   2   4  20  10]
- [  7 124   6   1  16   4   3]
- [ 14  12 165  35  16  41  39]
- [  4   2  19  96   4  11   8]
- [  0   3  12   0  66   0   2]
- [  7   1   1   0   2  45   4]
- [ 17   1   7   6   5   9  81]]
-Node Classification on random seed  3306 -> 0.616
-Confusion Matrix:
- [[ 71   2   4   1   2  15   6]
- [ 11 122   9   6   6   1   3]
- [ 31  17 161  23  19  10  52]
- [ 14   9  18  85   7   6  15]
- [  0   6   5   2  64   1   3]
- [  9   2   3   1   2  47   4]
- [ 15   1  12  12   6  13  66]]
-Node Classification on random seed  3307 -> 0.665
-Confusion Matrix:
- [[ 70   2   2   3   8   7   9]
- [  7 134  10   0   6   4  10]
- [ 24  17 168  16  20  12  27]
- [ 19   6  13  92  10   7  17]
- [  3   3   3   1  73   1   2]
- [  6   0   5   1   1  35  13]
- [ 12   4   5   5   9   5  93]]
-Node Classification on random seed  3308 -> 0.59
-Confusion Matrix:
- [[ 53   6   8   2   1  16  10]
- [  3 125   2   3   5   2   2]
- [ 19  23 140  45  22  28  55]
- [ 12   5  14  90   6   7  22]
- [  0   6   4   2  63   2   4]
- [  0   2   6   3   1  33   8]
- [  7   7   8   5   7  20  86]]
-Node Classification on random seed  3309 -> 0.593
-Confusion Matrix:
- [[ 57   5   4   4   3  15  15]
- [  5 119   6   6   7   3   2]
- [ 26  17 126  45  24  18  43]
- [ 14   3  13 102   7   4  28]
- [  0   3   3   0  66   4   3]
- [  2   1   1   4   1  43   5]
- [ 16   1   8   9   8  21  80]]
-Node Classification on random seed  3310 -> 0.661
-Confusion Matrix:
- [[ 89   1   1   2   4  22   4]
- [  2 134   1   1   5   3   4]
- [ 23  12 137  36  26  26  39]
- [ 14   5  12 107   4   8  19]
- [  2   5   1   1  62   3   2]
- [  3   1   3   0   2  48   6]
- [  7   1   6   1   9  12  84]]
-Node Classification on random seed  3311 -> 0.583
-Confusion Matrix:
- [[ 69   2  15  10   4   3   4]
- [  6 124   5   9   8   0   4]
- [ 15  44 130  40  44  12  31]
- [ 11   6  25  93   4  14  13]
- [  0  12   3   2  52   0   2]
- [  6   2   4   3   0  42   4]
- [ 15   3  12   6   5   9  73]]
-Node Classification on random seed  3312 -> 0.636
-Confusion Matrix:
- [[ 90   2   6   4   2   7   8]
- [  2 130   2   2   6   1  10]
- [ 17  23 143  16  48  36  22]
- [  6   6  19  99   4  11  13]
- [  2   4   3   0  66   0   5]
- [  6   1   2   3   0  38   7]
- [ 10   6  10   5   8  19  70]]
-Node Classification on random seed  3313 -> 0.614
-Confusion Matrix:
- [[ 70   1   3   3   3  11  11]
- [  4 129   6   5   4   3   5]
- [ 24  24 138  42  24  22  56]
- [ 12   5  13  95   4   3  10]
- [  4   8   8   1  55   0   5]
- [  4   2   3   0   2  48   4]
- [ 10   5   8   5   9  10  79]]
-Node Classification on random seed  3314 -> 0.58
-Confusion Matrix:
- [[ 74   5   2   5   2  22   6]
- [  3 112   6   1  17   1   2]
- [ 24  33 128  38  31  20  42]
- [  6   1  17  98   3  14  23]
- [  2   6   4   1  62   2   4]
- [  7   2   8   1   0  40   1]
- [ 20   2  14   3   9  10  66]]
-Node Classification on random seed  3315 -> 0.63
-Confusion Matrix:
- [[ 62   2   5   8   8  17  20]
- [  4 141   3   2   3   3   5]
- [ 33  28 146  23  15  20  35]
- [  6   4   9  96   4   6  17]
- [  2  11   4   3  66   0   1]
- [  1   4   2   2   1  43   6]
- [ 17   5   9   4   4  14  76]]
-Node Classification on random seed  3316 -> 0.626
-Confusion Matrix:
- [[ 70   2   4   4   1  17  13]
- [ 11 122   9   5  13   3   2]
- [ 13  32 133  30  26  23  29]
- [ 15   4  14 107   9   5  14]
- [  2   4   3   1  63   2   1]
- [  2   3   7   4   1  44   2]
- [  9   7  10   5   4   9  87]]
-Node Classification on random seed  3317 -> 0.636
-Confusion Matrix:
- [[ 65   4   6   2   3  14  12]
- [  3 124   7   2   6   2   1]
- [ 25  16 158  29  35  27  32]
- [ 20   2  21  98   3   1   6]
- [  0   7   4   2  60   3   0]
- [  6   0   6   0   0  56   7]
- [  3   3  13   7  10  14  75]]
-Node Classification on random seed  3318 -> 0.616
-Confusion Matrix:
- [[ 74   1   5   1   3  14  10]
- [  7 118   8   6  12   4   2]
- [ 16  14 127  38  24  23  49]
- [ 11   0  20 100   6  10  15]
- [  1   4   4   1  56   1   2]
- [  5   0   2   1   2  53  10]
- [  5   5  14   7   6  15  88]]
-Node Classification on random seed  3319 -> 0.615
-Confusion Matrix:
- [[ 64   3  12   6   5  16   8]
- [  2 128   6   1   5   1   7]
- [ 23  18 163  32  22  29  27]
- [  9   4  15  94   6  14  17]
- [  2  14   1   1  52   1   7]
- [ 12   0   0   0   0  46   4]
- [ 21   4   9   6   4  11  68]]
-Node Classification on random seed  3320 -> 0.612
-Confusion Matrix:
- [[ 80   2   3   5   8  12   1]
- [  6 128   4   4   3   1   6]
- [ 25  23 148  43  15  24  44]
- [ 13  11   6  93  15   3  13]
- [  3   3   3   1  47   1   5]
- [  7   2   6   1   2  46   2]
- [ 15   5  12   7   8  15  70]]
-Node Classification on random seed  3321 -> 0.572
-Confusion Matrix:
- [[ 68   4  10   1   7  17  11]
- [  0 118  12   4  12   0   4]
- [ 27   8 119  54  34  17  53]
- [ 12   4  23  95   0   5  12]
- [  1   7   3   2  72   0   3]
- [  2   0   5   5   2  41   8]
- [  8   3  13  10   8  17  59]]
-Node Classification on random seed  3322 -> 0.616
-Confusion Matrix:
- [[ 87   2   5   4   3   5   1]
- [  5 128   6   4  15   4   5]
- [ 36  40 132  36  31  15  25]
- [ 10   6  21  94   3   3   8]
- [  0   6   4   2  62   1   4]
- [ 11   0   1   0   1  38   5]
- [ 22   1  10   7   7   9  75]]
-Node Classification on random seed  3323 -> 0.623
-Confusion Matrix:
- [[ 75   0   6   2   5  20   7]
- [  6 141   1   0   4   0   8]
- [ 33  17 129  50  16  27  43]
- [ 14   1   9  98   4   6  12]
- [  0   8   6   0  51   0   1]
- [  7   2   5   2   0  48   5]
- [ 10   1  15   6   6  12  81]]
-Node Classification on random seed  3324 -> 0.643
-Confusion Matrix:
- [[ 80   4   2   4   4  17   5]
- [  4 132   3   2   3   4   7]
- [ 32  13 151  30  26  22  38]
- [ 17   4  24 100   6   5   5]
- [  1   6   2   1  62   1   2]
- [  5   2   0   1   1  44   4]
- [ 17   4   8   5   4  12  74]]
-Node Classification on random seed  3325 -> 0.614
-Confusion Matrix:
- [[ 80   4   4   3   2  10   5]
- [  2 127   2   5   8   2   4]
- [ 22  31 123  60  28  21  32]
- [ 18   3  12 104  11   5   6]
- [  0   6   7   0  56   3   3]
- [  1   1   3   5   0  48   3]
- [ 11   2  20  11   4   6  76]]
-Node Classification on random seed  3326 -> 0.62
-Confusion Matrix:
- [[ 74   0   6   9   4  14   0]
- [  4 127   3   8   6   2   0]
- [ 16  26 153  44  28  30  23]
- [ 10   3  11  98   9  19   8]
- [  0   4   8   0  63   0   3]
- [  2   0   1   1   1  41   7]
- [  8   3  12  18  10  19  64]]
-Node Classification on random seed  3327 -> 0.598
-Confusion Matrix:
- [[ 71   2   3  10  10   6   2]
- [  0 137   6   6   6   1   1]
- [ 14  37 122  28  51  29  28]
- [ 15   7  19  96  11   8  11]
- [  0   4   2   3  59   0   3]
- [  3   1   1   3   0  51   3]
- [  9   3   5  11  12  28  62]]
-Node Classification on random seed  3328 -> 0.562
-Confusion Matrix:
- [[ 67   0  12  11   5   9   9]
- [  3 105   4   7   5   3  10]
- [ 30  18 132  23  42  15  52]
- [  8   5  25  97  20  11  19]
- [  1   3   3   3  56   1   2]
- [  6   0   4   1   1  47   1]
- [ 10   4  14   8   3  27  58]]
-Node Classification on random seed  3329 -> 0.624
-Confusion Matrix:
- [[ 63   7   2   8   2  13  11]
- [  3 123   2   6  17   4   1]
- [ 18  26 150  26  24  22  29]
- [ 12   6  17 101   6   7   9]
- [  2   3   6   6  67   0   1]
- [  8   0   0   0   1  53   2]
- [ 15   0   4  17   8  25  67]]
-Node Classification on random seed  3330 -> 0.605
-Confusion Matrix:
- [[ 63   4   1   2   1   8  21]
- [  3 142   6   7   3   3   7]
- [ 22  22 119  42  31  21  57]
- [  4   4  10 112   1   6  13]
- [  0   6   4   1  53   2   3]
- [ 10   0   1   1   2  37   4]
- [ 15   2  11   9   9  16  79]]
-Node Classification on random seed  3331 -> 0.566
-Confusion Matrix:
- [[ 59   2  12   9   1  16   8]
- [  1 119  10   2   2   3   6]
- [ 33  25 114  20  43  37  30]
- [  9   4  16 101  10   9  16]
- [  2   9   5   1  55   2   1]
- [  4   3   2   0   3  44   7]
- [ 18  10   5  15   9  14  74]]
-Node Classification on random seed  3332 -> 0.626
-Confusion Matrix:
- [[ 61   1   9   4   5  11  14]
- [  8 122   8   1   8   4   5]
- [ 20  21 174  23  27  23  37]
- [  9   6  22  88   7   3  15]
- [  0   4   4   2  63   2   2]
- [  3   0   4   2   1  49   2]
- [  7   2  13   6   6  23  69]]
-Node Classification on random seed  3333 -> 0.625
-Confusion Matrix:
- [[ 74   2   4   9   7   8   1]
- [  1 130   6   5   5   3   7]
- [ 23  22 148  38  19  26  34]
- [  7   9  19  88   5   8  12]
- [  1  13   0   0  56   1   0]
- [  5   4   2   6   0  50   3]
- [  8   2  11  17   7  15  79]]
-Node Classification on random seed  3334 -> 0.617
-Confusion Matrix:
- [[ 86   2   3   3   6  10   8]
- [  1 111  10   2  14   3   9]
- [ 15  17 158  27  31  22  31]
- [ 13   4  28  87   3  11  17]
- [  2   3   2   2  55   1   0]
- [  2   2   3   0   2  55  10]
- [ 12   4  11   8  10  19  65]]
-Node Classification on random seed  3335 -> 0.62
-Confusion Matrix:
- [[ 63   2   0   4   4  10  18]
- [  1 131   2   4   1   2   6]
- [ 30  17 151  13  19  41  25]
- [ 16   7  20  79  11   3  20]
- [  1  10   6   1  68   1   3]
- [ 10   0   3   0   0  51   6]
- [ 12   2   4   8  10  27  77]]
-Node Classification on random seed  3336 -> 0.562
-Confusion Matrix:
- [[ 67   1   3   7   1   8   9]
- [  5 112   8   6  10   6   1]
- [ 45  19 113  53  23  30  46]
- [ 12   1  23 101   2   6  16]
- [  3   5   1   3  59   2   1]
- [  8   1   1   8   4  33   2]
- [  9   3  10   9   7  20  77]]
-Node Classification on random seed  3337 -> 0.58
-Confusion Matrix:
- [[ 76   9   7   2   2  11   9]
- [  3 135   0   3   2   1   3]
- [ 28  18 107  46  36  15  70]
- [ 15   7  16  87   6   3  12]
- [  1  10   3   0  63   1   3]
- [  8   1   1   0   0  44   4]
- [ 23   4  10   4   6  17  68]]
-Node Classification on random seed  3338 -> 0.632
-Confusion Matrix:
- [[ 65   0   8   3   1   6  17]
- [  2 121   6   4  13   4   1]
- [  9  11 167  44  30  29  27]
- [ 12   4  24 102   4  11   7]
- [  1   9   3   2  66   0   3]
- [  9   0   3   1   1  43   6]
- [  8   6  18   3   1  17  68]]
-Node Classification on random seed  3339 -> 0.634
-Confusion Matrix:
- [[ 50   5   7   6   5  14   8]
- [  3 142   8   4   2   3   3]
- [ 23  14 147  32  29  28  32]
- [ 14   1  10 110   9   3  11]
- [  0  10   2   1  58   1   3]
- [  1   4   3   4   0  47   8]
- [  7   2   5   7   7  27  80]]
-Node Classification on random seed  3340 -> 0.649
-Confusion Matrix:
- [[ 73   1   7   4   2  10   5]
- [ 14 138   1   0   8   7   1]
- [ 33  19 140  41  14  17  32]
- [  8   0  18 115   2  10  15]
- [  1  11   3   3  65   0   2]
- [  7   1   3   1   1  50   0]
- [ 12   2   6  11   2  16  68]]
-Node Classification on random seed  3341 -> 0.591
-Confusion Matrix:
- [[ 70   3   1   2   4  12   7]
- [  3 158   3   1   6   4   2]
- [ 31  39  90  41  53  19  34]
- [ 13   2  10 105  19   3   8]
- [  3   7   1   4  62   1   2]
- [  6   1   6   0   0  41   4]
- [ 10   4   7  14   7  12  65]]
-Node Classification on random seed  3342 -> 0.602
-Confusion Matrix:
- [[ 59   2   6   4   4   7   9]
- [  0 122   9   2  10   2   2]
- [ 23  37 144  27  32  19  41]
- [ 15  13  16  92  11   2  14]
- [  2   5   1   0  63   1   3]
- [  6   0   2   2   0  37  12]
- [ 12   6   7  13   9  10  85]]
-Node Classification on random seed  3343 -> 0.628
-Confusion Matrix:
- [[ 84   4   1   2   6  11   8]
- [  4 132   4   4   5   0   2]
- [ 45  13 144  33  23  23  41]
- [ 19   4  13  98   0   4  15]
- [  5   7   4   0  56   0   4]
- [  3   3   2   0   4  34   6]
- [ 15   3   9   2   3  18  80]]
-Node Classification on random seed  3344 -> 0.669
-Confusion Matrix:
- [[ 80   1   8   5   4  13   5]
- [  0 127   5   5   8   1   3]
- [ 29  16 168  29  18  26  23]
- [ 11   4  10 108   6   6  13]
- [  0   6   4   0  59   1   2]
- [  5   1   2   2   3  45   4]
- [ 17   1  15   3   4  12  82]]
-Node Classification on random seed  3345 -> 0.615
-Confusion Matrix:
- [[ 69   5   8   1   3   9   7]
- [  6 136   4   1   6   5   4]
- [ 10  35 137  41  11  36  27]
- [ 13   5  12 105  11  16   5]
- [  2   7   5   1  57   0   3]
- [  6   2   0   6   0  43   8]
- [ 19   1   6   1   9  28  68]]
-Node Classification on random seed  3346 -> 0.61
-Confusion Matrix:
- [[ 62   3   9  11   1  15   4]
- [  6 135   1   7   4   5   0]
- [ 29  12 152  43  11  32  45]
- [ 12   4  12  87  11  12  14]
- [  2   3   5   2  65   3   3]
- [  6   0   1   2   1  47   3]
- [  8   4   8   6   2  28  62]]
-Node Classification on random seed  3347 -> 0.601
-Confusion Matrix:
- [[ 66   3   6   3   7  12   5]
- [  5 142   3   5   9   2   4]
- [ 26  23 116  32  32  24  53]
- [ 12   5  17  99   4   3  18]
- [  1   3   1   1  60   9   8]
- [ 13   0   2   1   0  43   7]
- [ 10   0   5   5   9  11  75]]
-Node Classification on random seed  3348 -> 0.634
-Confusion Matrix:
- [[ 65   5   1   3   4  10   8]
- [  5 127   6   4   5   6   2]
- [ 24  23 156  29  34  21  26]
- [ 10   5  12 124   2   2   9]
- [  3   5   5   6  50   0   6]
- [  7   2   3   0   6  37  12]
- [  7   7   8   7   7  19  75]]
-Node Classification on random seed  3349 -> 0.597
-Confusion Matrix:
- [[ 74   2   2   1   2  11  14]
- [ 11 121  10   2  14   0   5]
- [ 29  17 122  54  37  12  56]
- [ 10   3  11 107   3   7   6]
- [  2   7   2   0  61   1   3]
- [  1   0   4   1   3  46   9]
- [ 11   2  13   6   7  12  66]]
-Node Classification on random seed  3350 -> 0.597
-Confusion Matrix:
- [[ 69   4   5   5   4  14  14]
- [  7 123   5   2  11   2   2]
- [ 26  32 136  30  28  13  35]
- [  7  10  19 107   6   2  20]
- [  0   3   5   1  59   1   1]
- [  1   1   6   6   3  34   4]
- [  8   2  27   9   9  13  69]]
-Node Classification on random seed  3351 -> 0.58
-Confusion Matrix:
- [[ 56   0   7  14   8  10   6]
- [ 13 107   3   0  12   2   2]
- [ 18  12 136  49  28  37  49]
- [ 12   2  20 104   7   6   6]
- [  1   4   4   3  71   2   1]
- [  7   1   1   4   0  44   4]
- [ 14   2   6  19  12  12  62]]
-Node Classification on random seed  3352 -> 0.586
-Confusion Matrix:
- [[ 52   2  25   4   3  12   8]
- [  4 135   5  12   6   0   6]
- [ 16  26 127  55  17  28  41]
- [ 12   3  11  99   5   7  17]
- [  4  12   3   4  50   1   3]
- [  5   4   3   0   0  44   3]
- [ 13   6   8   5   6   9  79]]
-Node Classification on random seed  3353 -> 0.605
-Confusion Matrix:
- [[ 92   1   9   0   5  10   6]
- [  3 106   3   3  14   7   1]
- [ 33  23 143  56  28  16  27]
- [ 14  10  19  82   5   2   9]
- [  0   8   4   2  63   0   5]
- [ 10   0   0   1   1  55   4]
- [ 10   4  15  10   2  15  64]]
-Node Classification on random seed  3354 -> 0.609
-Confusion Matrix:
- [[ 77   0   3   4   2   1  14]
- [  6 120   5   2  19   0   8]
- [ 25  19 144  26  29  38  32]
- [  9   2  19  82   3   8  25]
- [  4   3   2   1  63   0   2]
- [  3   0   5   0   0  48   6]
- [ 13   1  14   8   7  23  75]]
-Node Classification on random seed  3355 -> 0.589
-Confusion Matrix:
- [[ 58   0   6   4   7   9  18]
- [  3 119  11   1   4   4   2]
- [ 26  17 124  40  24  30  50]
- [ 15   2  15 112   6  10   4]
- [  2  10   2   1  66   3   1]
- [  1   1   4   1   0  47   4]
- [ 13   2  13   6   7  32  63]]
-Node Classification on random seed  3356 -> 0.623
-Confusion Matrix:
- [[ 68   0   8   2   4  15  12]
- [  2 129  16   4   7   6   0]
- [ 15  31 138  26  30  17  38]
- [  7   5  12 123  12   5  13]
- [  1   7   7   1  59   1   2]
- [ 10   3   1   0   0  43   4]
- [  6   4  17   1   6  19  63]]
-Node Classification on random seed  3357 -> 0.618
-Confusion Matrix:
- [[ 68   0   2   6   3  11   6]
- [  9 138   6   1   6   3   3]
- [ 12  38 144  22  14  30  49]
- [ 17   7  10  90   1   6  17]
- [  0  10   6   4  56   1   7]
- [  2   1   1   3   1  58   4]
- [  7   4  14  12   4  22  64]]
-Node Classification on random seed  3358 -> 0.586
-Confusion Matrix:
- [[ 71   4   4  11   4   5   9]
- [  4 126   5   1   6   1  10]
- [ 23  23 134  62  34  15  28]
- [  8   9  27 104   4   2   8]
- [  0   8  11   2  47   2   2]
- [ 12   4   0   1   0  43   1]
- [ 16   6   8   9   8  17  61]]
-Node Classification on random seed  3359 -> 0.645
-Confusion Matrix:
- [[ 80   3   6   8   4   4   3]
- [  2 135   7   3   3   2   3]
- [ 18  16 162  39  26  13  38]
- [  4   3  26  95   6   6  16]
- [  0   6   6   3  57   0   5]
- [  7   0   2   1   1  44   5]
- [ 11   5   9   7   7  21  72]]
-Node Classification on random seed  3360 -> 0.642
-Confusion Matrix:
- [[ 47   4   3   3   1  17  17]
- [  3 138   3   1  13   4   3]
- [ 13  16 156  38  24  24  34]
- [ 15   4  11 109   7   5  10]
- [  0   7   3   4  61   1   2]
- [  7   0   1   2   1  45  12]
- [  3   2  11   7   4  18  86]]
-Node Classification on random seed  3361 -> 0.597
-Confusion Matrix:
- [[ 70   5   2   8   0  10   8]
- [  8 122   9   0  12   0   2]
- [ 31  34 140  21  18  29  39]
- [  5   8  22  89   6   4  20]
- [  4  11   4   3  44   1   0]
- [ 10   2   1   1   4  53   4]
- [ 21   2   7   8   4  15  79]]
-Node Classification on random seed  3362 -> 0.617
-Confusion Matrix:
- [[ 76   3   5  10   4   4   1]
- [  0 144   8   3   8   2   2]
- [ 25  22 138  34  15  31  42]
- [ 16   3  29  85  11   7  11]
- [  1   6   5   2  72   0   4]
- [  5   3   3   4   0  38   5]
- [  7   5   8  13   3  13  64]]
-Node Classification on random seed  3363 -> 0.567
-Confusion Matrix:
- [[ 71   4   2   4   6  12  18]
- [  4 124   8   2   6   7   3]
- [ 38  29 127  30  25  18  35]
- [ 12   1  33  87   7   8   3]
- [  4   6   3   2  58   3   2]
- [  4   3   2  11   3  41   4]
- [ 22   3  17   6  10  13  59]]
-Node Classification on random seed  3364 -> 0.634
-Confusion Matrix:
- [[ 84   6   5   2   1   8   7]
- [  6 131   6   4   6   3   2]
- [ 21  28 148  29  22  20  53]
- [  7  13  25  88   2   9  10]
- [  1   3   1   1  47   0   3]
- [  6   2   2   1   0  47   4]
- [ 11   2   4   8   6  16  89]]
-Node Classification on random seed  3365 -> 0.631
-Confusion Matrix:
- [[ 65   2   1  17   2   7  13]
- [  3 134   7   2   8   4   1]
- [ 39  21 146  29  21  16  29]
- [  6   3  20 107  13   6  10]
- [  2  10   1   2  60   0   1]
- [ 10   2   1   1   0  39   6]
- [ 13   2  12   8   9   9  80]]
-Node Classification on random seed  3366 -> 0.621
-Confusion Matrix:
- [[ 74   2   6   4   3  21   4]
- [  5 126  11   3  10   0   3]
- [ 18  17 143  41  14  27  30]
- [ 17   9  10  97   3   3  15]
- [  2   2   2   4  61   2   3]
- [  6   2   1   1   2  55   5]
- [ 22   3  10  11  14  11  65]]
-Node Classification on random seed  3367 -> 0.637
-Confusion Matrix:
- [[ 76   2   1   9   0  15   6]
- [  4 126   6   1  15   6   5]
- [ 14  18 139  39  31  14  29]
- [ 23   3   9  96   5   9  13]
- [  1  10   3   0  70   3   2]
- [  1   2   3   3   0  48   6]
- [ 11   3  15   9   4  10  82]]
-Node Classification on random seed  3368 -> 0.636
-Confusion Matrix:
- [[ 59   1   1   9   3   7  23]
- [  6 140   4   1  11   1   2]
- [ 10  28 167  25  28  17  47]
- [ 22   2  19  95   5   3  18]
- [  2   7   3   1  61   0   0]
- [  5   0   2   1   0  42  10]
- [ 13   3   5   6   0  13  72]]
-Node Classification on random seed  3369 -> 0.655
-Confusion Matrix:
- [[ 76   2   6   4   3  10  13]
- [  0 127   5   2   2   3  13]
- [ 16  30 146  43  20  13  29]
- [  8   3   7 128   8  11  16]
- [  0  10   2   0  57   3   3]
- [  2   3   3   2   1  48   6]
- [  6   2  15   3   5  12  73]]
-Node Classification on random seed  3370 -> 0.635
-Confusion Matrix:
- [[ 70   2   5   7   4   8  17]
- [ 10 105   5   4   8   3   2]
- [ 32  14 171  32  19  19  39]
- [ 10   4  18  94   3   2  15]
- [  0   7   2   0  68   1   1]
- [  5   1   1  10   0  41   7]
- [ 11   2   7   8   4  16  86]]
-Node Classification on random seed  3371 -> 0.629
-Confusion Matrix:
- [[ 76   7   2   4   1   7   3]
- [  5 118   2   0  15   2   2]
- [ 30  22 146  19  27  23  32]
- [ 11   4  21 108   5   6  14]
- [  2   7   4   3  65   0   2]
- [  5   3   4   0   1  53   4]
- [ 17   5   9   6  13  22  63]]
-Node Classification on random seed  3372 -> 0.605
-Confusion Matrix:
- [[ 53   5   6   4   3  11  16]
- [  6 132   7   1  10   8   4]
- [ 20  27 125  30  22  16  37]
- [ 11   9  17 102   5   7  12]
- [  1   3   3   1  81   0   3]
- [  5   4   2   1   1  37   9]
- [ 15   5  17  11   9  11  75]]
-Node Classification on random seed  3373 -> 0.619
-Confusion Matrix:
- [[ 73   3   3   6   0  17  18]
- [  7 116   4   2  10   3   2]
- [ 14  24 154  42  24  14  40]
- [  4   8  28 107   3   7  12]
- [  4   6   6   4  51   0   5]
- [  3   1   0   1   0  50   6]
- [  8   1   8   8   7  18  68]]
-Node Classification on random seed  3374 -> 0.633
-Confusion Matrix:
- [[ 58   7   2   3   5   3   9]
- [  4 139   6   2  15   4   2]
- [ 21  20 135  25  49  19  32]
- [ 15   3  15  97   9   4  12]
- [  2   5   1   3  64   0   2]
- [  7   1   3   0   0  55   6]
- [  7   5   8  10   7  14  85]]
-Node Classification on random seed  3375 -> 0.623
-Confusion Matrix:
- [[ 75   2   4   7   6   9  23]
- [  4 139   4   1   7   0   3]
- [ 23  24 157  22  27  14  34]
- [ 20   6  15  75   9  11  12]
- [  0   7   4   0  55   4   3]
- [  4   1   1   2   1  44   7]
- [  9   7   3   7  12  18  78]]
-Node Classification on random seed  3376 -> 0.612
-Confusion Matrix:
- [[ 72   6   6   4   3   9  23]
- [  0 119   7   3  12   3   5]
- [ 26  31 148  51  17  14  29]
- [ 14   4  20  96   2   5   9]
- [  0   8   5   2  63   1   3]
- [  7   1   2   2   0  48   6]
- [  9   4  11  11   3  10  66]]
-Node Classification on random seed  3377 -> 0.614
-Confusion Matrix:
- [[ 85   2   7   2   3   9   2]
- [  5 106   3   3  14   4   4]
- [ 25  19 140  45  30  19  35]
- [ 12   3  12 109   4  15   8]
- [  4   4   2   3  68   2   2]
- [  6   1   8   1   4  45   3]
- [ 14   0  14   5   7  21  61]]
-Node Classification on random seed  3378 -> 0.63
-Confusion Matrix:
- [[ 79   6   8   4   1   9   9]
- [  4 108   7   2  11   4  10]
- [ 24  35 146  27  18  31  32]
- [  9   1   8 122   5   4   9]
- [  0   3   4   1  61   2   4]
- [  4   1   1   7   0  52   2]
- [ 16   8   8   6   8  17  62]]
-Node Classification on random seed  3379 -> 0.577
-Confusion Matrix:
- [[ 72   1   2   6   4   8   7]
- [  6 112   6   2  18   8   4]
- [ 33  18 115  51  29  22  58]
- [  8   6  17  97   5   5  11]
- [  1   2   4   0  57   2   0]
- [  6   1   1   4   2  44   5]
- [ 13   7   6   1   6  27  80]]
-Node Classification on random seed  3380 -> 0.66
-Confusion Matrix:
- [[ 70   2   0   4   6  16   8]
- [  4 124   2   2  10   2   3]
- [ 26  19 153  24  25  20  34]
- [  9   3   8 122   2   8  12]
- [  2   6   6   0  68   7   1]
- [  1   1   1   0   5  42   7]
- [ 10   2  17   4   6  15  81]]
-Node Classification on random seed  3381 -> 0.616
-Confusion Matrix:
- [[ 66   5   7   2   3  12  19]
- [  3 123   8   2  10   0   4]
- [ 14  17 142  25  49  19  35]
- [ 22   2  19  97   7   5   9]
- [  1   6   1   2  58   0   3]
- [  5   3   0   0   0  55   7]
- [  7   4  16   3   6  22  75]]
-Node Classification on random seed  3382 -> 0.601
-Confusion Matrix:
- [[ 79   6  10   8   0   5   5]
- [  4 120  12  10  12   2   3]
- [ 25   8 140  42  28  17  39]
- [ 24   3  25  79   7   4   4]
- [  3   3   2   4  58   1   7]
- [ 10   1   2   0   1  55   5]
- [ 16   3   9   5  10  14  70]]
-Node Classification on random seed  3383 -> 0.573
-Confusion Matrix:
- [[ 66   2   3   4   2  26   5]
- [  2 117  10   4  17   2   3]
- [ 20  44 137  35  29  20  30]
- [  7   3  19  99   8  16  15]
- [  1  11   1   0  56   1   1]
- [  3   1   1   5   2  36   7]
- [  8   5   3  15  11  25  62]]
-Node Classification on random seed  3384 -> 0.601
-Confusion Matrix:
- [[ 64   2  14   5   3  15   2]
- [  7 142   1   5   5   2   2]
- [ 25  29 110  39  49  23  31]
- [  8   5  19 104   6   7  12]
- [  4   5   2   2  59   0   1]
- [ 12   1   5   2   0  44   2]
- [ 12   2   6   4   9  14  78]]
-Node Classification on random seed  3385 -> 0.627
-Confusion Matrix:
- [[ 69   0   2   9   8   8   4]
- [ 10 130  11   0   2   4   4]
- [ 32  23 155  25  22  22  41]
- [ 14   2  16  92   5  10  19]
- [  2   4   2   2  60   0   1]
- [  6   0   1   5   1  52   3]
- [ 21   2  10   5   2  13  69]]
-Node Classification on random seed  3386 -> 0.589
-Confusion Matrix:
- [[ 77   3   2   5   2   9   4]
- [  0 122   8   2  10   7   3]
- [ 50  16 151  39  26  19  23]
- [ 14   3  18  92  20   5  18]
- [  1  11   4   0  55   2   1]
- [  9   0   5   5   4  36   5]
- [ 12   4   8   6   4  24  56]]
-Node Classification on random seed  3387 -> 0.602
-Confusion Matrix:
- [[ 62   1   3   8   4   9  12]
- [  7 121   5   3  10  16   0]
- [ 33  16 148  36  18  26  46]
- [ 19   0  10 102   4   1  15]
- [  2   4   6   3  50   5   3]
- [  9   3   3  10   2  33   5]
- [ 11   1   6   6   6  11  86]]
-Node Classification on random seed  3388 -> 0.666
-Confusion Matrix:
- [[ 80   5   3   0   4  14   7]
- [  8 114   6   3   8   3   0]
- [ 22  19 173  23  12  22  30]
- [  7   6   8 121   2   6  12]
- [  1   5   9   2  59   1   0]
- [  2   2   1   1   0  46   3]
- [ 12   3   7  13  18  24  73]]
-Node Classification on random seed  3389 -> 0.599
-Confusion Matrix:
- [[ 56   1   0   8  14  12  10]
- [  7 113   3   3  12   0   4]
- [ 13  22 155  30  33  35  25]
- [ 23   2  31  86   8  10   9]
- [  1   5   3   1  54   2   2]
- [  6   1   6   0   1  52  10]
- [ 14   5   6   6   5  12  83]]
-Node Classification on random seed  3390 -> 0.603
-Confusion Matrix:
- [[ 63   3   5   2   1   9  17]
- [ 10 126   3   3  14   3   3]
- [ 16  36 128  40  25  19  32]
- [  7   4   7 126   6   8  11]
- [  2  11   4   7  54   1   1]
- [  6   2   5   2   0  46   4]
- [  5   5  13  13   6  26  60]]
-Node Classification on random seed  3391 -> 0.619
-Confusion Matrix:
- [[ 66   3   7   6   3  14   7]
- [  9 119  17   0   3   3   2]
- [ 16  20 143  26  37  25  45]
- [ 12   6  14  92   6  17   2]
- [  2   7   2   2  70   2   0]
- [  3   1   5   0   0  48   6]
- [  9   6   9  10   1  16  81]]
-Node Classification on random seed  3392 -> 0.604
-Confusion Matrix:
- [[ 45   3  15   2   3  13  11]
- [  2 119   5   3  12   0   4]
- [ 11  44 140  30  30  17  34]
- [ 11   9  18 115   3   9   6]
- [  1   5   3   3  61   1   2]
- [  1   2   3   1   3  58   6]
- [ 15   8  17   5   7  18  66]]
-Node Classification on random seed  3393 -> 0.625
-Confusion Matrix:
- [[ 69   9   9   0   5  10  12]
- [  4 128  10   2   3   5   2]
- [ 22  20 143  40  15  17  35]
- [ 11   2  22  97   2  10  20]
- [  2   3   1   0  69   4   3]
- [  9   1   0   4   0  42  10]
- [ 14   1  12   9   5  10  77]]
-Node Classification on random seed  3394 -> 0.565
-Confusion Matrix:
- [[ 47   3  11   8   3   8  13]
- [  8 137   7   3   9   1   1]
- [ 29  29 116  40  24  25  64]
- [ 10   4  13 102  14   7  10]
- [  0  10   3   2  57   0   5]
- [  6   0   5   4   0  34   6]
- [  8   4  11   6   8  13  72]]
-Node Classification on random seed  3395 -> 0.644
-Confusion Matrix:
- [[ 89   6   6   5   1   7   4]
- [  3 130   3   2   3   2   3]
- [ 28  10 152  33  21  23  34]
- [ 20   5  22  88   3   3  15]
- [  1   5   4   1  71   0   3]
- [ 11   1   1   1   1  47   1]
- [ 28   4   7   8   6  11  67]]
-Node Classification on random seed  3396 -> 0.592
-Confusion Matrix:
- [[ 63   5   3   5   2  17  28]
- [  7 114   4   3   8   3   2]
- [ 21  38 135  31  19  27  40]
- [ 10   7  11 104   3   4  13]
- [  0   4   1   8  52   1   3]
- [  0   2   4   0   0  56   7]
- [  7   6  19  10   6  19  68]]
-Node Classification on random seed  3397 -> 0.606
-Confusion Matrix:
- [[ 76   2   6   8   5   7  10]
- [ 11 137   5   5   4   0   4]
- [ 15  26 102  37  64  19  44]
- [  5   3  12 107   3   4   6]
- [  2   4   2   8  57   0   6]
- [  6   1   1   1   0  36  13]
- [ 14   3   4  11  11   2  91]]
-Node Classification on random seed  3398 -> 0.64
-Confusion Matrix:
- [[ 77   1   2  17   1  14   8]
- [  9 126   9   1   4   3   4]
- [ 23  21 166  29  17  19  26]
- [  7   2  19 101   6   5  18]
- [  2   3   6   2  60   1   3]
- [  3   0   4   2   0  49   3]
- [ 15   2   6  20  10  13  61]]
-Node Classification on random seed  3399 -> 0.626
-Confusion Matrix:
- [[ 67   5   2   6   4  18   8]
- [  1 138   5   1   5   3   1]
- [ 22  29 144  43  19  16  39]
- [  8   5  11 101   6   1  16]
- [  1   8   3   0  71   0   5]
- [  2   0   4   2   2  44  11]
- [  6   4  12  13  13  14  61]]
-Node Classification on random seed  3400 -> 0.585
-Confusion Matrix:
- [[ 93   4   0   4   4  18   5]
- [  4 120   2  10   4   6   4]
- [ 28  21 122  48  23  27  36]
- [ 23   4  23  84  11   6  11]
- [  0   7   4   6  57   1   0]
- [  5   0   2   3   5  40   4]
- [ 17   2  15   4   5   9  69]]
-Node Classification on random seed  3401 -> 0.618
-Confusion Matrix:
- [[ 78   4   2   2   3  14   3]
- [  6 106   6   2   6   1  13]
- [ 28  31 153  26  21  23  44]
- [ 12   4   8  97   3   6  21]
- [  2   9   5   2  55   2   3]
- [  9   0   0   2   0  45   3]
- [ 16   4  11   5   5  15  84]]
-Node Classification on random seed  3402 -> 0.639
-Confusion Matrix:
- [[ 72   2   2   4   1  24   8]
- [  1 128   4   0   8   3   6]
- [ 32  12 158  27  20  33  21]
- [ 16   5  19  98  11   3  10]
- [  1   6   3   0  59   0   2]
- [  6   3   9   3   1  44   2]
- [  7   3   6   7   9  21  80]]
-Node Classification on random seed  3403 -> 0.603
-Confusion Matrix:
- [[ 62   0   0  20   5  18  11]
- [  3 132   3   0   9   5   5]
- [ 22  20 139  28  40  17  39]
- [  5  10  27  97   3  10  14]
- [  1   8   3   3  50   3   1]
- [  2   4   1   2   4  39   5]
- [  7   4  10   8   7  10  84]]
-Node Classification on random seed  3404 -> 0.613
-Confusion Matrix:
- [[ 81   4   0   7   5   5   4]
- [  3 132   5   3   7   1   5]
- [ 37  41 134  38  23  20  13]
- [ 23   5  10  90   3   9  10]
- [  0  14   5   2  62   0   1]
- [  9   2   1   0   1  43   5]
- [ 20  10   9   8   7  12  71]]
-Node Classification on random seed  3405 -> 0.591
-Confusion Matrix:
- [[ 74   2   4   4   3   4  18]
- [ 10 113  10   8  11   0   4]
- [ 39  16 117  34  40   8  23]
- [ 25   1  23  90   8   3  10]
- [  1   7   5   2  68   0   2]
- [  9   0   2   1   3  47   6]
- [ 24   1   9  10   4  15  82]]
-Node Classification on random seed  3406 -> 0.612
-Confusion Matrix:
- [[ 69   3   2   5   6  16  15]
- [  6 129   2   0   7   2   2]
- [ 20  36 148  30  26  15  39]
- [ 13   5  18 101  11   7  10]
- [  1   4   6   0  57   0   2]
- [ 12   2   1   0   0  46   6]
- [ 10   8  17   7   4  12  62]]
-Node Classification on random seed  3407 -> 0.648
-Confusion Matrix:
- [[ 79   2   0   3   0   7  10]
- [  2 129   6   1   8   6   3]
- [ 20  26 160  27  15  29  38]
- [ 30   9   3  88  14   8   8]
- [  2   6   7   1  64   0   5]
- [  1   2   3   1   1  54   3]
- [  6   3  14   8   4  10  74]]
-Node Classification on random seed  3408 -> 0.611
-Confusion Matrix:
- [[ 56   4   6  11   4  13  10]
- [  3 114   3   2  11   4   4]
- [ 40  14 168  26  29  25  31]
- [ 19   3   9 108   2   4  15]
- [  1   6   4   1  58   0   4]
- [  8   2   7   2   0  43   1]
- [ 13   3  22   3   8  12  64]]
-Node Classification on random seed  3409 -> 0.65
-Confusion Matrix:
- [[ 77   1   5   3   3  17   8]
- [  7 129   5   2  11   9   4]
- [ 27  15 158  24  22  39  25]
- [  6   4  11 121   8   5   9]
- [  1   4   6   0  51   0   1]
- [  6   0   1   2   3  52   3]
- [ 15   0   6  10  10  12  62]]
-Node Classification on random seed  3410 -> 0.64
-Confusion Matrix:
- [[ 67   4   2   4   4  11   2]
- [  5 140   3   5   4   1   3]
- [ 28  29 156  26  12  33  46]
- [ 12   2   8  92   1  11  17]
- [  2   5   2   3  50   1   3]
- [  1   1   3   2   1  50   5]
- [ 11   3   7   7   9  21  85]]
-Node Classification on random seed  3411 -> 0.644
-Confusion Matrix:
- [[ 67   3   6   2   2   8   3]
- [  6 131   8   0  10   4   8]
- [ 34  12 132  39  30  32  22]
- [  3   2  13 122   4  10  10]
- [  5   3   5   2  55   0   7]
- [  4   0   3   0   1  55   3]
- [  7   1  20   5   2  17  82]]
-Node Classification on random seed  3412 -> 0.616
-Confusion Matrix:
- [[ 78   2   3   7   3   8  16]
- [  8 109   6   4   4   1   5]
- [ 24  22 161  51  23  10  40]
- [  2   4  24  93   2   6  13]
- [  4   6   4   2  60   0   4]
- [  8   1   3   0   1  47   8]
- [  6   3  18  10   9   9  68]]
-Node Classification on random seed  3413 -> 0.669
-Confusion Matrix:
- [[ 79   2   3   7   5   9   7]
- [  5 122  12   3   8   2   4]
- [ 24  23 151  33  19  32  21]
- [ 10   1   4 125   3   6  15]
- [  1   3   4   0  59   0   3]
- [  3   0   9   1   1  55   8]
- [  4   5   3   7   4  17  78]]
-Node Classification on random seed  3414 -> 0.66
-Confusion Matrix:
- [[ 74   4   3   7   4  12   5]
- [  4 139   4   9   3   2  10]
- [ 22  13 173  22  22  30  38]
- [  9   5  16  94   2   6   7]
- [  0   4   5   0  68   1   1]
- [  3   2   7   1   1  35   8]
- [  9   4   9   8   2  16  77]]
-Node Classification on random seed  3415 -> 0.615
-Confusion Matrix:
- [[ 69   1   7  14  18  12   5]
- [  8 132   8   3  11   5   4]
- [ 16  29 130  49  31  26  26]
- [ 10   1   9 108   2   7   9]
- [  1   7   2   1  55   0   1]
- [  8   2   0   1   3  40   3]
- [ 16   4   3   4   8  10  81]]
-Node Classification on random seed  3416 -> 0.579
-Confusion Matrix:
- [[ 63   5  10   4   6   4   7]
- [  2 127   6   0   3   4   3]
- [ 30  25 135  29  13  26  61]
- [ 43   2   8  82   5   8  11]
- [  0   6   8   3  64   0   4]
- [  7   2   0   2   0  38   8]
- [  9   5  16  13   5  18  70]]
-Node Classification on random seed  3417 -> 0.67
-Confusion Matrix:
- [[ 79   1   2   5   4   6   8]
- [  3 124   9  14   6   2   2]
- [ 18  16 159  23  25  22  31]
- [  9   2  16 116   5   5  19]
- [  2   4   6   3  53   1   1]
- [  6   0   2   2   0  48   5]
- [ 10   1   1  10   9  14  91]]
-Node Classification on random seed  3418 -> 0.61
-Confusion Matrix:
- [[ 80   1   4   5   3   5   9]
- [  5 132   8   2  12   0   3]
- [ 24  17 139  29  28  27  39]
- [ 14   4  17  92   2  14   6]
- [  2   4   5   7  66   3   2]
- [ 10   3   2   1   0  34   4]
- [ 21   8   6   4   5  25  67]]
-Node Classification on random seed  3419 -> 0.642
-Confusion Matrix:
- [[ 93  12   3   5   5   9  10]
- [  3 132   2   2   5   1   2]
- [ 19  28 142  28  25  18  36]
- [ 15   3  20  90   6   7   7]
- [  5  10   5   2  73   1   1]
- [  2   2   1   2   0  40   6]
- [ 12   4   6   7   5  16  72]]
-Node Classification on random seed  3420 -> 0.621
-Confusion Matrix:
- [[ 63   4   2   5   2  17   7]
- [  1 116   8   6   7   1  16]
- [ 20  16 150  32  34  25  35]
- [ 11   3  14 106   8   8  14]
- [  1   8   5   3  62   4   2]
- [  3   3   0   1   2  48   5]
- [ 13   2   3   4   8  16  76]]
-Node Classification on random seed  3421 -> 0.595
-Confusion Matrix:
- [[ 73   2   3   2   3  15  12]
- [  4 118   4   3   9   2   5]
- [ 33  22 119  55  30  25  30]
- [  8   1  16  91   5   7  21]
- [  1  10   1   0  52   1   3]
- [ 10   1   4   0   0  50   5]
- [ 17   7   8   2   3  15  92]]
-Node Classification on random seed  3422 -> 0.609
-Confusion Matrix:
- [[ 71   4   1   4   2  11  12]
- [ 29  97   8   3   9   2   9]
- [ 13  41 138  35  25  13  23]
- [ 13   3  13 119   4   2   8]
- [  1   6   5   2  69   0   2]
- [  6   3   2   3   0  42  12]
- [ 14   7  14  13   7   7  73]]
-Node Classification on random seed  3423 -> 0.631
-Confusion Matrix:
- [[ 77   5   2   3   5  19   8]
- [  2 128   5   4   2   2  11]
- [ 31  28 133  29  17  35  29]
- [ 11   4   9 114   7   9  15]
- [  2   4   4   1  53   0   2]
- [  4   4   3   0   0  52   1]
- [ 10   2   9   9   4  18  74]]
-Node Classification on random seed  3424 -> 0.651
-Confusion Matrix:
- [[ 83   2   2   8   2   5   7]
- [  7 120   6   4   6   7   5]
- [ 21  15 153  31  32  36  27]
- [  2   5  13 118   9   9  10]
- [  0   5   4   3  47   1   3]
- [  8   1   2   4   0  42   8]
- [  7   1   8   8   9   6  88]]
-Node Classification on random seed  3425 -> 0.631
-Confusion Matrix:
- [[ 71   5   2   1   1   9  10]
- [ 10 135   4   2   8   3   4]
- [ 24  24 149  48  19  27  37]
- [ 11   4  11 106   2   3  16]
- [  2   6   3   3  54   1   4]
- [  7   0   2   3   3  38   6]
- [ 15   4   6   9   4   6  78]]
-Node Classification on random seed  3426 -> 0.63
-Confusion Matrix:
- [[ 79   1   3   4   6   8   4]
- [  4 134   5   5   7   2   1]
- [ 31  31 149  34  27  37  19]
- [ 13   4  16  87   4   2  14]
- [  1   9   1   2  50   1   5]
- [  6   0   0   2   0  48   6]
- [ 18   3   3  15   6  10  83]]
-Node Classification on random seed  3427 -> 0.586
-Confusion Matrix:
- [[ 72   1  10   3   2  12  10]
- [  5 121   5   2   7   2   4]
- [ 38  16 110  34  52  22  35]
- [ 12   2  18  93   6   6  22]
- [  3   4   1   1  60   2   1]
- [  3   0   4   5   0  51   3]
- [ 19   6   6   3  10  17  79]]
-Node Classification on random seed  3428 -> 0.627
-Confusion Matrix:
- [[ 78   2   1   4   4  11  15]
- [  6 129   5   2  10   4   4]
- [ 24  17 153  27  25  29  44]
- [  7   4  13  98   7   9  22]
- [  1   5   3   2  60   0   4]
- [  9   0   0   0   2  43   5]
- [  8   1   8   5   6  18  66]]
-Node Classification on random seed  3429 -> 0.6
-Confusion Matrix:
- [[ 42   1   5   9   7  21  16]
- [  4 125   6   3   6   0   9]
- [ 23  23 131  19  28  34  40]
- [  8   4  19 117   2   8  23]
- [  1   1   4   1  71   0   2]
- [  9   2   2   2   0  40   4]
- [ 13   2   5  12   8  14  74]]
-Node Classification on random seed  3430 -> 0.608
-Confusion Matrix:
- [[ 86   0   2   8   2   4   3]
- [  4 125  17   7   6   2   3]
- [ 29  21 117  59  26  13  47]
- [ 12   0  19 109  10   3  13]
- [  2   8   2   3  56   1   3]
- [  6   0   2   2   0  33   5]
- [ 13   1   8   6   5  15  82]]
-Node Classification on random seed  3431 -> 0.6
-Confusion Matrix:
- [[ 64   2   8   7   5  10  21]
- [  7 133   9   2  10   1   0]
- [ 29  21 141  32  26  25  31]
- [ 23   2  14  97   6   5  10]
- [  0   9   9   2  63   0   0]
- [  2   0   4   2   0  41   9]
- [ 15   2  14   9   5  12  61]]
-Node Classification on random seed  3432 -> 0.631
-Confusion Matrix:
- [[ 83   1   0   1   3  15   8]
- [  5 114   7   2  11   2   4]
- [ 30  12 158  26  36  37  19]
- [ 11   3  11  94   7  10  18]
- [  1   8   1   2  69   0   1]
- [  8   1   1   6   2  48   1]
- [ 15   1   7   7   4  24  65]]
-Node Classification on random seed  3433 -> 0.637
-Confusion Matrix:
- [[ 66   1   5   3   3  21   6]
- [  5 120   5   4   8   4   6]
- [ 19  19 146  57  22  14  36]
- [  9   0  14 113  14   6   7]
- [  3   4   5   2  64   2   1]
- [  6   2   2   0   3  51   3]
- [  8   4   8   9   5   8  77]]
-Node Classification on random seed  3434 -> 0.572
-Confusion Matrix:
- [[ 77   1   3   4   4  12  16]
- [  1 114  10   1  16   7   3]
- [ 33  24 100  37  45  26  38]
- [ 11   3  16  92  20   0  11]
- [  0   4   3   0  69   0   7]
- [  3   1   2   6   2  46   2]
- [ 19   3   9   5   9  11  74]]
-Node Classification on random seed  3435 -> 0.592
-Confusion Matrix:
- [[ 67   2   5   2   4  14   8]
- [ 10 131   8   4   4   2   3]
- [ 25  45 136  34  24  16  37]
- [ 13   5  20  96   7   5  15]
- [  2   6   2   4  52   0   5]
- [  9   4   4   0   1  40   1]
- [ 13   3  12   7   5  18  70]]
-Node Classification on random seed  3436 -> 0.567
-Confusion Matrix:
- [[ 65   1   0   4  11  17  13]
- [  4 137   3   2   5   2  10]
- [ 51  38 124  37  29  27  31]
- [ 21   2  13  90   8   6   6]
- [  2   5   3   1  55   0   3]
- [  5   2   2   2   5  38   5]
- [ 12   2  10  12  11  10  58]]
-Node Classification on random seed  3437 -> 0.623
-Confusion Matrix:
- [[ 72   2   2   8   1  15  11]
- [  9 119   5   4   7   1   6]
- [ 23  21 133  34  23  23  41]
- [  9   1  21 120   3   3   9]
- [  2   7   3   2  58   3   2]
- [  3   4   6   1   0  44   8]
- [  6   1  23  10   9   5  77]]
-Node Classification on random seed  3438 -> 0.625
-Confusion Matrix:
- [[ 68   5   2  12   3  10  11]
- [  3 131   9   1   2   0   5]
- [ 20  30 141  26  17  18  54]
- [ 15   4  18 112   2   5  12]
- [  0   5   3   3  51   1   3]
- [  7   6   2   0   2  44   1]
- [ 14   3  22   6   1  12  78]]
-Node Classification on random seed  3439 -> 0.618
-Confusion Matrix:
- [[ 81   6   3   6   5  18   2]
- [  4 130  10   1   6   6   2]
- [ 31  26 136  35  22  31  42]
- [ 13   4  14  97   4  10   7]
- [  1   3   4   2  55   2   1]
- [  6   1   1   4   2  43   8]
- [ 13   3   1   5   3  14  76]]
-Node Classification on random seed  3440 -> 0.626
-Confusion Matrix:
- [[ 76   0   4   3   2  13   6]
- [  5 121   9   2   5   1   4]
- [ 26  25 134  39  30  28  22]
- [  8   1  16 111  11   7  15]
- [  1   2   3   4  63   1   2]
- [  6   2   1   1   0  51   7]
- [  9   5   6  15   9  18  70]]
-Node Classification on random seed  3441 -> 0.601
-Confusion Matrix:
- [[ 56   1   5   3   3   6  16]
- [  6 136   5   4   0   0   4]
- [ 17  21 134  64  17  19  48]
- [ 10   8  21 103   4  11  12]
- [  0   8   2   6  47   2   2]
- [  3   1   0   5   0  46   5]
- [ 15   4   8   7   9  17  79]]
-Node Classification on random seed  3442 -> 0.608
-Confusion Matrix:
- [[ 76   0   7   3   7  15  10]
- [  8 126   9   0   7   1   6]
- [ 34  18 131  37  30  28  32]
- [ 11   4   7 102  10   7  17]
- [  1   4   5   5  59   1   1]
- [  3   2   3   4   0  42   5]
- [ 16   3   7   7   7  10  72]]
-Node Classification on random seed  3443 -> 0.598
-Confusion Matrix:
- [[ 58   7   3   5   3  10  24]
- [  1 124   5   1   6   4   1]
- [ 25  31 134  36  31  31  30]
- [ 11   1  10 106   7   6  14]
- [  0   9   6   2  67   1   3]
- [  6   1   2   2   0  30  10]
- [  8   1   4  14  12  18  79]]
-Node Classification on random seed  3444 -> 0.601
-Confusion Matrix:
- [[ 70   3   4  11   5   7  10]
- [  9 128   7   3   2   3   3]
- [ 27  21 123  41  30  33  33]
- [  8   3  12 111   4   2  17]
- [  2   4   1   2  59   0   2]
- [  5   0   3   3   1  47   8]
- [ 13   5  10  16   8  18  63]]
-Node Classification on random seed  3445 -> 0.644
-Confusion Matrix:
- [[ 85   3   5   5   6   2  11]
- [  7 136   5   1   3   0   4]
- [ 16  20 129  49  30  25  34]
- [ 12   5  15 113   4   4   8]
- [  2  10   2   2  58   1   1]
- [  3   1   1   8   1  40   4]
- [ 14   1   5  10   5  11  83]]
-Node Classification on random seed  3446 -> 0.572
-Confusion Matrix:
- [[ 71   1   6   4   7  19   5]
- [  3 101  14   3   7   4   6]
- [ 29  19 121  64  22  21  33]
- [ 22   2  13  89   3   3  22]
- [  1   7   1   1  65   0   5]
- [  6   0   1   4   2  40   9]
- [ 14   4  12  15   4  10  85]]
-Node Classification on random seed  3447 -> 0.646
-Confusion Matrix:
- [[ 84   6   0   2   5  10   2]
- [  4 121  12   4  13   2   4]
- [ 22  16 163  22  30  15  39]
- [ 21   1  18  97   3   8   8]
- [  0   4   5   7  56   1   2]
- [  7   1   1   2   0  51   3]
- [ 26   3   7   4   4  10  74]]
-Node Classification on random seed  3448 -> 0.615
-Confusion Matrix:
- [[ 68   6   0  12   3  12  12]
- [  2 116   3  11   8   1   3]
- [ 25  34 130  35  41  16  39]
- [  9   1  15 103  11   4  12]
- [  0   3   1   1  69   0   3]
- [  1   1   5   5   1  52   5]
- [  4   6   4  12   7  11  77]]
-Node Classification on random seed  3449 -> 0.611
-Confusion Matrix:
- [[ 70   3   4   1   6  12   6]
- [  5 111   3   5  19   0   9]
- [ 33  29 143  31  16  28  27]
- [ 19   3  20  90   3   9   5]
- [  2   2   4   0  59   3   2]
- [ 10   3   1   2   1  54   1]
- [ 17   3  10   7   7  18  84]]
-Node Classification on random seed  3450 -> 0.603
-Confusion Matrix:
- [[ 47   6   4   5   3  16  26]
- [  5 126   5   2   6   5   3]
- [ 40  13 161  34  26  22  31]
- [ 14   4  10  99   4   6  12]
- [  1   7   4   0  58   0   2]
- [  4   0   3   1   0  41  17]
- [  9   2   8  10   9  18  71]]
-Node Classification on random seed  3451 -> 0.636
-Confusion Matrix:
- [[ 69   3   2   2   7   8  15]
- [  3 121   4   4   6   3   1]
- [ 32  24 148  47  23  19  30]
- [  4   1  21 110   4   4  14]
- [  1   7   8   0  52   0   1]
- [  8   2   2   4   1  49   2]
- [ 12   3   7   7   9   9  87]]
-Node Classification on random seed  3452 -> 0.553
-Confusion Matrix:
- [[ 70   2   6   3   7   7  15]
- [  3 125   3   0  12   1   9]
- [ 49  24  85  31  31  31  64]
- [ 20   5   8 110   9   5  15]
- [  1   8   6   1  57   2   5]
- [  6   1   2   1   0  44   8]
- [ 13   9  10   4   5   5  62]]
-Node Classification on random seed  3453 -> 0.635
-Confusion Matrix:
- [[ 73   1   7  10   4  15   6]
- [  1 136   4   4  16   3   6]
- [ 18  18 154  29  21  19  30]
- [  7   4  15  99   8   7  28]
- [  1   6   2   4  60   1   2]
- [  3   0   0   4   0  32  20]
- [  7   6   0  10   8  10  81]]
-Node Classification on random seed  3454 -> 0.644
-Confusion Matrix:
- [[ 74   4   1   6   1   3  25]
- [  0 130   3   2   7   0  12]
- [ 20  32 140  23  20  21  47]
- [  8   6  15 105   9   2  23]
- [  0   5   4   3  60   0   1]
- [  4   3   3   0   0  40   6]
- [ 14   3   4   7   4   5  95]]
-Node Classification on random seed  3455 -> 0.626
-Confusion Matrix:
- [[ 72   4   1   5   2  22   5]
- [  3 131   4   2  11   3   4]
- [ 21  24 137  40  18  26  39]
- [ 14   5  12 109   1   7  15]
- [  2   7   8   0  64   0   3]
- [  2   1   1   1   0  41   4]
- [ 18   8  10   1   7  13  72]]
-Node Classification on random seed  3456 -> 0.631
-Confusion Matrix:
- [[ 66   0  13   8   1   8   4]
- [  7 138   4   0   3   1   4]
- [ 29  20 152  39  27  19  35]
- [  6   3  19  99   3   7  16]
- [  2   6   4   3  51   1   1]
- [ 13   1   1   1   0  45   5]
- [ 14   5   8   8   6  14  80]]
-Node Classification on random seed  3457 -> 0.584
-Confusion Matrix:
- [[ 62   2   1  10  11  16  14]
- [  8 118   5   1  11   8   3]
- [ 17  23 117  24  56  10  56]
- [ 12   5  19 102  12   8  12]
- [  0   5   1   1  56   1   2]
- [  5   2   0   1   0  48   5]
- [ 14   2   2   6  14  11  81]]
-Node Classification on random seed  3458 -> 0.663
-Confusion Matrix:
- [[ 70   3   9   5   4  12   5]
- [  1 131   2   1   3   1   9]
- [ 20  19 169  24  15  20  48]
- [  4   5  15 114   3   6  14]
- [  2  10   3   2  50   0   3]
- [  1   1   2   0   1  53   6]
- [ 11   4  15  14   3  11  76]]
-Node Classification on random seed  3459 -> 0.614
-Confusion Matrix:
- [[ 78   5   2   1   1  13  10]
- [  3 128   7   6  14   2   4]
- [ 25  18 119  26  58  28  31]
- [ 11   3  11 108  10   6  11]
- [  4   2   2   3  63   3   5]
- [  5   0   1   0   0  44   7]
- [  8   4  15   2   4  15  74]]
-Node Classification on random seed  3460 -> 0.625
-Confusion Matrix:
- [[ 73   1   9   2   5  12  16]
- [  1 128   6   4   3   7   1]
- [ 14  22 126  36  40  28  30]
- [ 11   5  14  99   7   6   9]
- [  2   3   2   1  75   2   1]
- [  2   3   3   0   1  51   2]
- [ 13   5   6  10  11  19  73]]
-Node Classification on random seed  3461 -> 0.637
-Confusion Matrix:
- [[ 71   3   5   3   2  13  14]
- [  6 113  11   5   7   4   5]
- [ 15  21 157  30  37  15  32]
- [  8   0  21 121   3   9  15]
- [  3   8   3   1  56   0   1]
- [  9   0   1   0   0  37   6]
- [  4   1   7   1  12  22  82]]
-Node Classification on random seed  3462 -> 0.61
-Confusion Matrix:
- [[ 88   2   7   1   3   9   3]
- [  5 126   6   5   5   0   3]
- [ 33  49 134  38  20  17  21]
- [ 23   0  17 108   3   6  13]
- [  2   7   1   3  55   0   2]
- [  9   6   4   0   1  38   2]
- [ 20  10  16   1   4  13  61]]
-Node Classification on random seed  3463 -> 0.628
-Confusion Matrix:
- [[ 63   1   3   1   4  16  11]
- [ 10 117   4   3  10   9   3]
- [ 19  23 155  19  29  26  40]
- [ 15   8  19 101   4   2  17]
- [  0   5   2   1  62   1   4]
- [  2   3   7   1   4  49   6]
- [  9   3   3   6   8  11  81]]
-Node Classification on random seed  3464 -> 0.617
-Confusion Matrix:
- [[ 69   2   7  15   4   2  13]
- [  6 141   2   0   4   4   4]
- [ 18  24 144  54  26  15  41]
- [ 10   6  11  97   1   3   9]
- [  1   9  10   1  55   0   0]
- [  8   3   5   1   0  43   2]
- [ 20  10  11   5   7   9  68]]
-Node Classification on random seed  3465 -> 0.603
-Confusion Matrix:
- [[ 38   2   9   9   6  14  16]
- [  7 121   2   7   9   4   2]
- [ 20  16 136  34  28  30  36]
- [  9   4  13 113   2   4   8]
- [  0   9   7   4  73   1   4]
- [  2   0   0   3   1  47   4]
- [  5   4  12   6  20  24  75]]
-Node Classification on random seed  3466 -> 0.624
-Confusion Matrix:
- [[ 55   3   7  10   3   8  13]
- [ 10 127   3   3   8  10   4]
- [ 18  16 145  30  25  21  41]
- [  4   0  15 107   3   8  16]
- [  8  10   3   1  59   0   2]
- [  9   4   2   8   0  44   4]
- [ 15   2   5   4   9  11  87]]
-Node Classification on random seed  3467 -> 0.646
-Confusion Matrix:
- [[ 62   4   4  11   5   6   9]
- [  1 122   4   2  13   5   4]
- [ 15  22 153  38  17  18  31]
- [ 14   3  27  98   5   4  11]
- [  0   3   6   2  60   0   4]
- [ 13   1   0   2   0  57   5]
- [  7   0  14   8   3  13  94]]
-Node Classification on random seed  3468 -> 0.629
-Confusion Matrix:
- [[ 75   2   6   3   3   6   3]
- [  7 127   7   0   4   7   3]
- [ 20   9 173  45  31  21  29]
- [ 19   1  17  98   9   2  10]
- [  3  10   5   2  54   0   2]
- [  9   1   0   1   2  39   8]
- [ 16   3  11   9   5  20  63]]
-Node Classification on random seed  3469 -> 0.662
-Confusion Matrix:
- [[ 64   1  10   5   3  16  11]
- [  1 132   3   3   0   2   8]
- [ 30  23 154  30  12  22  46]
- [ 12   6   7 128   0   3  11]
- [  0   5   5   3  57   0   2]
- [  5   0   0   0   2  45   7]
- [  5   4  13   4   6  12  82]]
-Node Classification on random seed  3470 -> 0.64
-Confusion Matrix:
- [[ 57   1   4   6   6   2  17]
- [ 19 126   7   3   6   3   1]
- [ 24  22 150  37  28  13  43]
- [ 18   5   5 108   8   1  14]
- [  2   5   1   4  67   0   2]
- [  3   6   0   2   0  51   5]
- [ 11   1   3   6  10   6  81]]
-Node Classification on random seed  3471 -> 0.603
-Confusion Matrix:
- [[ 78   4   4   4   4   4  17]
- [  4 125   4   7   9   3   2]
- [ 38  15 112  32  33  16  40]
- [ 14   6  17 120   3   5   5]
- [  4   8   6   0  60   2   2]
- [  7   5   2   0   0  45   4]
- [ 12   6  20   7  12  10  63]]
-Node Classification on random seed  3472 -> 0.631
-Confusion Matrix:
- [[ 76   2   2   6   7   6   6]
- [  2 101  10   3  19   7   2]
- [ 28  17 164  24  35  13  25]
- [  8   3  19  98  11  11   9]
- [  2   8   0   0  73   1   3]
- [  1   0   1   5   2  41   5]
- [ 14   2   0  16  15  19  78]]
-Node Classification on random seed  3473 -> 0.607
-Confusion Matrix:
- [[ 56  10   5   4   8   9   7]
- [  8 129   1   3  11   1   3]
- [ 21  16 145  42  41  14  49]
- [  8   6   9  98   9   7  15]
- [  0   6   3   3  59   0   5]
- [  9   0   2   3   1  42  10]
- [ 11   2  10   2  10   9  78]]
-Node Classification on random seed  3474 -> 0.624
-Confusion Matrix:
- [[ 68   4   9   6   1  14  11]
- [  5 134   4   2   3   2   6]
- [ 19  10 145  45  14  34  37]
- [ 17   0  31  97   2   1  15]
- [  3   6   6   0  51   2   1]
- [  6   0   1   3   1  42  10]
- [  7   3   5   7   5  18  87]]
-Node Classification on random seed  3475 -> 0.637
-Confusion Matrix:
- [[ 61   2   2   8   1  15  14]
- [  2 147   4   4   5   0   2]
- [ 13  13 154  37  51  11  35]
- [ 21   6  17 102   4   7   5]
- [  0   8   2   1  57   1   1]
- [  2   3   2   2   0  46   3]
- [ 16   6   7   6  15   9  70]]
-Node Classification on random seed  3476 -> 0.594
-Confusion Matrix:
- [[ 56   1   2   5   8  12  18]
- [  0 117   9   3  11   6   1]
- [ 24  12 124  32  34  32  44]
- [ 11   2  17  99   2   6  11]
- [  8   4   3   1  60   0   8]
- [  5   2   1   4   1  41  16]
- [  7   4  16   6   7  10  97]]
-Node Classification on random seed  3477 -> 0.641
-Confusion Matrix:
- [[ 84   2   9   6   1  11   9]
- [  5 164   1   2   3   4   2]
- [ 17  18 134  30  14  42  29]
- [ 16  11  12 103   7   6   5]
- [  4   7   4   1  52   1   3]
- [  0   0   0   0   0  41  10]
- [ 21   4  10  14   4  14  63]]
-Node Classification on random seed  3478 -> 0.614
-Confusion Matrix:
- [[ 57   2   1  14   3  18  14]
- [  0 125   6   5   9   4   7]
- [ 17  20 153  36  18  36  34]
- [ 19   4  17  85   8   5  14]
- [  0   6   1   1  65   3   4]
- [  2   0   0   2   1  50   5]
- [  7   2  16   9   6  10  79]]
-Node Classification on random seed  3479 -> 0.655
-Confusion Matrix:
- [[ 69   2   3   7   4   2  15]
- [  1 153   9   3   7   3   3]
- [ 26  10 139  28  27   5  56]
- [ 10   9   8 123   6   4   8]
- [  1   4   2   3  53   0   3]
- [  8   1   3   2   0  39   6]
- [ 21   5   6   9   8   7  79]]
-Node Classification on random seed  3480 -> 0.585
-Confusion Matrix:
- [[ 57   2   7   5   4  19  13]
- [  1 120   7   3   4   2   1]
- [ 31  27 132  63  23  21  40]
- [  3   8  12  99   5   4  17]
- [  2   7   1   5  63   4   2]
- [ 12   3   1   1   1  32   6]
- [  7   6   5   4  17   9  82]]
-Node Classification on random seed  3481 -> 0.643
-Confusion Matrix:
- [[ 78   1  10   4   2  15   9]
- [  8 131  11   2  10   2   5]
- [ 27  20 144  19  25  21  36]
- [  7   4  17  90   8   4   8]
- [  4   4   5   1  63   0   6]
- [  5   1   1   1   1  56   6]
- [  7   3   6   8   8  15  81]]
-Node Classification on random seed  3482 -> 0.571
-Confusion Matrix:
- [[ 65   1   4  16   0  11   7]
- [  6 121   8   5   4   2   5]
- [ 35  16 126  37  29  22  46]
- [ 19   7  14  85   6  10  21]
- [  3   6   1   0  60   1   4]
- [  4   1   0   2   3  46  11]
- [ 21   1   5  20   7   8  68]]
-Node Classification on random seed  3483 -> 0.639
-Confusion Matrix:
- [[ 68   3   4   4   5  12  13]
- [  3 130   4   2  10   1   2]
- [ 19  19 130  55  31   8  36]
- [  6   5  10 126  15   8   9]
- [  0  10   1   1  64   0   1]
- [  5   1   2   0   3  36  10]
- [ 12   2  11   0   5  13  85]]
-Node Classification on random seed  3484 -> 0.585
-Confusion Matrix:
- [[ 76   0   7   6   5  16   9]
- [  3 127   7   7   5   1   5]
- [ 22  31 119  26  36  26  41]
- [ 19   3  18  86  11  13  13]
- [  0   4   1   4  49   4   6]
- [  4   1   1   2   0  38  15]
- [  7   3  12  10   3   8  90]]
-Node Classification on random seed  3485 -> 0.608
-Confusion Matrix:
- [[ 56   3   4   8  10  17  10]
- [  3 130   4   3  15   5   2]
- [ 26  16 142  18  25  30  47]
- [ 14   3  24  89   3   3  20]
- [  4   4   0   4  68   0   4]
- [  4   1   1   0   0  43   4]
- [ 10   2  15   4   8  14  80]]
-Node Classification on random seed  3486 -> 0.662
-Confusion Matrix:
- [[ 67   1   2   4   1  11  15]
- [ 13 136   3   2   8   0   1]
- [ 14  26 159  23  25  22  36]
- [ 14   1  14 120   5   2   8]
- [  0   2   2   0  68   1   2]
- [  1   1   6   3   0  49   2]
- [ 12   3  13   4  10  25  63]]
-Node Classification on random seed  3487 -> 0.621
-Confusion Matrix:
- [[ 68   2   0   3   3  14  13]
- [  1 133  12   4   6   1   8]
- [ 18  40 129  35  28  11  39]
- [ 14   5  20 107   7   3  10]
- [  0   7   0   1  57   4   6]
- [  4   3   0   1   0  43   8]
- [  4   6   9   6   2  21  84]]
-Node Classification on random seed  3488 -> 0.616
-Confusion Matrix:
- [[ 58   5   0   2   0   9  26]
- [  1 124   5   4  12   4   1]
- [ 37  21 144  28  26  20  54]
- [  5   7  11  92   6  10  13]
- [  2   7   4   0  58   1   0]
- [  5   0   3   1   3  45  11]
- [ 11   2   6   9   2  10  95]]
-Node Classification on random seed  3489 -> 0.592
-Confusion Matrix:
- [[ 64   4   2   6   4  18  21]
- [ 10 128  15   1   4   0   6]
- [ 18  27 146  28  37  30  36]
- [ 11   0  17  87   7   8  19]
- [  0   4   1   1  54   2   7]
- [  7   0   1   5   0  39   8]
- [ 12   2   5   2   9  13  74]]
-Node Classification on random seed  3490 -> 0.603
-Confusion Matrix:
- [[ 74   2   7  12   9  10  15]
- [  4 125  16   3   6   1   4]
- [ 16  15 147  34  29  23  44]
- [  9   3   6 109  10   6   9]
- [  0   6   4   4  54   0   1]
- [  8   0   1   3   0  37  10]
- [ 12   8   9  16   8  14  57]]
-Node Classification on random seed  3491 -> 0.642
-Confusion Matrix:
- [[ 77   2   4   6   3   8  12]
- [  1 132   4   0  17   4   3]
- [ 30  22 161  24  25   9  26]
- [ 10   6  10  81   9   5  37]
- [  3   8   2   1  68   0   1]
- [  2   2   1   1   3  46   4]
- [ 15   2  10   5  11  10  77]]
-Node Classification on random seed  3492 -> 0.602
-Confusion Matrix:
- [[ 69  19   1   3   4  14   7]
- [  0 114   4   2   9   3   9]
- [ 26  28 141  36  23  23  41]
- [  9   1  15 101   3   9  13]
- [  0   9   4   4  53   3   3]
- [  3   0   8   1   2  40   2]
- [ 12   2  15   6   3  19  84]]
-Node Classification on random seed  3493 -> 0.627
-Confusion Matrix:
- [[ 68   1   4   2   5  16   2]
- [  6 125   0   1   9   1   5]
- [ 33  15 147  32  21  23  36]
- [ 10   2  27  96   6   4  24]
- [  2   6   3   0  72   1   2]
- [  8   3   0   1   1  47   5]
- [ 22   2  13   7   5   7  72]]
-Node Classification on random seed  3494 -> 0.621
-Confusion Matrix:
- [[ 65   5   6   2   3   9  21]
- [  5 129   6   2   3   2   3]
- [ 21  21 138  38  36  16  32]
- [  6   2   4 104   4   5  17]
- [  3  14   4   1  62   1   1]
- [  3   2   5   0   1  50   7]
- [ 12  11  14  12   9  10  73]]
-Node Classification on random seed  3495 -> 0.611
-Confusion Matrix:
- [[ 81   2   2   4   3   6   6]
- [  1 116   3   1   5   7  15]
- [ 18  24 156  46  18  16  47]
- [ 22  11   9  90   2   4  21]
- [  0   7   3   1  67   2   2]
- [  4   0   2   2   0  34   6]
- [ 11   3  15  16   8  14  67]]
-Node Classification on random seed  3496 -> 0.596
-Confusion Matrix:
- [[ 63   2   9   3   4  14   3]
- [  5 131   8   1  12   3   4]
- [ 19  23 119  23  37  35  44]
- [  9   1  21 110   2   2  33]
- [  0  10   5   2  57   1   1]
- [  6   1   3   0   0  41   5]
- [ 17   3   4   6   6  17  75]]
-Node Classification on random seed  3497 -> 0.624
-Confusion Matrix:
- [[ 77   6   2   3   4   9   9]
- [  2 103   3   8   2   5   3]
- [ 29  17 161  28  21  17  47]
- [ 22   6   9 100   9  10  10]
- [  1   7   3   0  50   1   2]
- [  4   2   3   1   0  44  10]
- [  9   8  19   8   2  15  89]]
-Node Classification on random seed  3498 -> 0.621
-Confusion Matrix:
- [[ 71   2   9   1   2  18   4]
- [  3 139   6   2   7   1   2]
- [ 23  18 141  39  23  21  35]
- [ 16   7  17 106   6   8  13]
- [  2   4   4   2  61   1   1]
- [  4   3   3   3   0  44   3]
- [  8   2   8  12  18  18  59]]
-Node Classification on random seed  3499 -> 0.597
-Confusion Matrix:
- [[ 66   1   0   7   6  13  17]
- [  8 122   3   4  12   2   5]
- [ 39  16 129  26  30  15  61]
- [ 17   2  13 116   6   4   8]
- [  4   5   7   1  61   0   1]
- [  7   0   3   1   3  36   3]
- [ 15   4   6  12   6  10  67]]
-Node Classification on random seed  3500 -> 0.631
-Confusion Matrix:
- [[ 59   2   5  10   3   6  16]
- [  6 143  13   3   8   4   2]
- [ 22  16 143  37  29  10  39]
- [  9   3  11 118   3   3  12]
- [  0   5   4   2  58   1   6]
- [  2   4   3   2   0  40  11]
- [  8   5   8  18   2  16  70]]
-Node Classification on random seed  3501 -> 0.597
-Confusion Matrix:
- [[ 58   2   9  11   2  17  14]
- [  8 126   7   2   5   0   3]
- [ 20  23 135  30  25  22  54]
- [  9   2  19  99  12   2   9]
- [  0  13   6   2  60   2   1]
- [  5   1   1   6   0  45   3]
- [ 10   2   9  18   4  13  74]]
-Node Classification on random seed  3502 -> 0.639
-Confusion Matrix:
- [[ 71   1   1   5   3  18   4]
- [  0 149   9   6   5   3   4]
- [ 17  26 148  35  21  19  31]
- [ 19   5  15  93   4  10  13]
- [  0   8   9   0  55   2   1]
- [  5   1   1   2   0  51   5]
- [  6   7   6   9   6  19  72]]
-Node Classification on random seed  3503 -> 0.571
-Confusion Matrix:
- [[ 64   2   4   8   4  28   3]
- [  8 113   6  10  11   1   5]
- [ 27  30 122  48  19  16  42]
- [ 13   8  29  96   7   2   8]
- [  1   8   2   0  57   0   5]
- [  5   0   1   0   4  44   5]
- [ 17   3   8   8   9  14  75]]
-Node Classification on random seed  3504 -> 0.601
-Confusion Matrix:
- [[ 77   2   0   3   4  14  20]
- [  1 110   8   3   7   3   4]
- [ 20  14 122  54  41  26  34]
- [ 26   3   6 116   4   8  14]
- [  2   5   5   2  54   0   4]
- [  4   0   2   1   1  46   6]
- [ 12   2   6   4   6  18  76]]
-Node Classification on random seed  3505 -> 0.625
-Confusion Matrix:
- [[ 65   3   0   6   2  10  13]
- [  0 148   5   3   4   4   3]
- [ 19  16 140  50  26  13  35]
- [ 19   3  13  97  10   2  17]
- [  1   9   7   0  61   1   3]
- [ 12   3   0   3   0  49   2]
- [ 21   3   5  11   7  11  65]]
-Node Classification on random seed  3506 -> 0.607
-Confusion Matrix:
- [[ 79   1   4   3   4  11  13]
- [  6 129   7   2   6   5   5]
- [ 34  22 135  19  20  23  51]
- [  8   6  28  94   4   7   6]
- [  4   6   3   2  57   0   3]
- [  4   1   0   1   2  47  10]
- [ 15   7  17   5   6  12  66]]
-Node Classification on random seed  3507 -> 0.573
-Confusion Matrix:
- [[ 50   5  19   6   5  11  16]
- [  7 114  14   2  10   0   9]
- [ 22  17 119  23  50  18  52]
- [  5   3  20 103   7   8  15]
- [  1   5   3   0  60   0   3]
- [  1   3   4   2   5  36   7]
- [  6   5  14   5  10   9  91]]
-Node Classification on random seed  3508 -> 0.646
-Confusion Matrix:
- [[ 73   3   4   8   3   2  13]
- [ 11 136   4   4   0   3   2]
- [ 26  26 131  37  29  21  33]
- [  4  10   9 128   2   5  11]
- [  2   6   3   2  56   1   1]
- [  8   4   1   3   0  45   7]
- [ 12   4  10   3   9   8  77]]
-Node Classification on random seed  3509 -> 0.604
-Confusion Matrix:
- [[ 57   2   0   8   2  13   6]
- [  3 124   6   3   3   7   5]
- [ 37  24 160  11  17  22  45]
- [ 15  13  13  74  16   9  28]
- [  1   8   7   0  63   2   6]
- [  5   0   0   5   0  50   3]
- [ 13   7   5   5   3  18  76]]
-Node Classification on random seed  3510 -> 0.609
-Confusion Matrix:
- [[ 91   0   4   7   6  11  10]
- [  3 111   6   4  15   0   4]
- [ 27  21 133  44  33  18  32]
- [ 17   3  16 104   6   3  10]
- [  2   3   2   3  61   0   2]
- [ 11   1   2   2   3  38   3]
- [ 16   3  12   9   4  13  71]]
-Node Classification on random seed  3511 -> 0.637
-Confusion Matrix:
- [[ 74   2   4   8   6   7   2]
- [  4 139   8   6  10   1   1]
- [ 43  15 151  29  19  10  26]
- [ 22   6  12  94   2  14   2]
- [  1   8   3   4  71   0   1]
- [  5   2   5   2   4  42   5]
- [ 21   3  12   9   5  14  66]]
-Node Classification on random seed  3512 -> 0.588
-Confusion Matrix:
- [[ 70   2   1   2   4  12  13]
- [  0 136   3   7   4   2   3]
- [ 24  24 117  49  27  19  60]
- [ 10   3  23  81  13   5  25]
- [  2   7   3   0  68   0   3]
- [  4   0   5   6   0  40   8]
- [  2   2   8   6   3  18  76]]
-Node Classification on random seed  3513 -> 0.6
-Confusion Matrix:
- [[ 77   3  11   9   5   7   9]
- [ 10 112   3   5  14   6   0]
- [ 41  32 118  37  27  12  29]
- [  6   6  18 113  11   6   8]
- [  1   4   2   6  69   0   6]
- [  5   1   8   3   0  46   3]
- [ 17   1   4   6   5  13  65]]
-Node Classification on random seed  3514 -> 0.617
-Confusion Matrix:
- [[ 72   6   2  19   0   5   3]
- [  1 124   3   7  13   0   6]
- [ 11  19 133  33  39  37  39]
- [  7   4  17 110   2   6  17]
- [  1   2   2   5  64   0   3]
- [  4   2   0   6   0  38   7]
- [ 16   1   9   8   9  12  76]]
-Node Classification on random seed  3515 -> 0.647
-Confusion Matrix:
- [[ 52   3   9   3   2  20   6]
- [  6 124   1   6  19   2   5]
- [ 21  17 156  26  25  16  26]
- [  7   3  16 126   7   6  15]
- [  1   0   5   2  61   1   2]
- [  7   0   3   1   0  46   7]
- [ 23   4   3   4   8  15  82]]
-Node Classification on random seed  3516 -> 0.658
-Confusion Matrix:
- [[ 77   2   3   5   4  12  21]
- [  1 132   3   0   7   0   2]
- [ 17  17 145  37  20  29  43]
- [ 12   5  12 101   5   4  12]
- [  0   4   2   1  69   0   2]
- [  6   0   3   1   2  50   5]
- [ 11   4   5   5   1  17  84]]
-Node Classification on random seed  3517 -> 0.596
-Confusion Matrix:
- [[ 70   1   7   7   3   8   5]
- [  4 132   5   1  12   1  10]
- [ 18  32 123  31  18  41  29]
- [  6   3  24  89   7  10  24]
- [  1   6   3   6  57   3   1]
- [  4   8   5   2   0  43   3]
- [  8   5  12   6   7  17  82]]
-Node Classification on random seed  3518 -> 0.609
-Confusion Matrix:
- [[ 79   1   1  13   9   7   6]
- [  6 125   8   2  15   1   4]
- [ 17  21 130  38  22  31  44]
- [  9   4  11  97   5   5  12]
- [  1   4   2   0  65   1   7]
- [  5   2   3   7   1  37   7]
- [ 18   0   7   7  13  14  76]]
-Node Classification on random seed  3519 -> 0.634
-Confusion Matrix:
- [[ 84   9   2   3   4   9   3]
- [  4 126   4   5   9   3   8]
- [ 16  13 128  35  41  23  34]
- [ 18   3   8  99   8   6  16]
- [  1   6   5   0  72   0   2]
- [  8   2   0   4   1  37   8]
- [ 19   5   3   5   6   7  88]]
-Node Classification on random seed  3520 -> 0.602
-Confusion Matrix:
- [[ 66   5   4   4   2   3  17]
- [  5 120   5   3  11   1  10]
- [ 29  25 138  38  32  25  23]
- [ 20   9  13 103   0   4  10]
- [  3   3   5   0  62   0   2]
- [  7   1   4  11   0  34   8]
- [ 16   5  15   9   3   8  79]]
-Node Classification on random seed  3521 -> 0.643
-Confusion Matrix:
- [[ 82   2  14   2   8   2   5]
- [  2 136   2   1   6   1   5]
- [ 22  24 150  31  33  17  35]
- [ 15   2  16 101  10   2  11]
- [  1   7   2   0  59   0   5]
- [  6   2   1   0   3  44   5]
- [ 16   3   6   9  16   7  71]]
-Node Classification on random seed  3522 -> 0.613
-Confusion Matrix:
- [[ 78   4   1   4   3   6   8]
- [  4 112   4   1   7   0   1]
- [ 26  27 146  24  35  18  44]
- [  9   5  27  88   6   5  17]
- [  2   2   5   0  60   0   3]
- [  7   4   8   0   0  39   6]
- [ 19   6  10   3  20   6  90]]
-Node Classification on random seed  3523 -> 0.638
-Confusion Matrix:
- [[ 61   9   7   5   8  11  11]
- [  5 123   5   3   3   5   4]
- [ 27  14 157  23  27  28  47]
- [  4   3  11 107   2   5  12]
- [  1  10   3   0  62   3   1]
- [  6   1   3   2   0  44   5]
- [ 10   1   4  14   4  15  84]]
-Node Classification on random seed  3524 -> 0.623
-Confusion Matrix:
- [[ 83   2   4   6   3   9  10]
- [  4 116   7   3  12   1   5]
- [ 18  13 147  30  57  26  26]
- [  4   3  19 110   4   1  12]
- [  1   2   2   5  58   2   2]
- [  7   2   3   4   3  45   5]
- [  5   2  14  18   5  16  64]]
-Node Classification on random seed  3525 -> 0.64
-Confusion Matrix:
- [[ 82   2   0   5   4   7  15]
- [  7 131   5   6   6   1   3]
- [ 22  22 132  42  27  17  41]
- [  6   1  18  96   9   6   9]
- [  1   5   3   2  71   1   3]
- [  4   2   0   0   1  56   3]
- [ 10   4   8  11  12   9  72]]
-Node Classification on random seed  3526 -> 0.612
-Confusion Matrix:
- [[ 73   2   5   9   3  24   4]
- [  7 128   4   4   7   3   2]
- [ 13  26 145  43  32  13  43]
- [ 13   1   5 101   9   5  12]
- [  1   5   0   0  60   0   6]
- [  6   3   2   4   5  47   6]
- [  9   1   9  10   9  23  58]]
-Node Classification on random seed  3527 -> 0.609
-Confusion Matrix:
- [[ 71   2  17   3   3   1  15]
- [  8 127   3   2   7   5   4]
- [ 19  15 142  27  45  19  40]
- [ 18   3  14 105   3  10  10]
- [  2   5   1   4  53   1   2]
- [  6   1   3   8   2  37  10]
- [  8   3  13  10   2  17  74]]
-Node Classification on random seed  3528 -> 0.607
-Confusion Matrix:
- [[ 69  13   2   2   4  18   0]
- [ 11 101   6   1  15   6   3]
- [ 20  18 152  36  29  18  53]
- [ 10   0  17  93   6   8  13]
- [  5   3   5   0  60   0   2]
- [  6   1   4   1   0  45   3]
- [ 17   4   4   3   9  17  87]]
-Node Classification on random seed  3529 -> 0.636
-Confusion Matrix:
- [[ 63   2  10  11   4  11   7]
- [  6 139   3   2  10   0   3]
- [ 17  30 154  22  21  16  54]
- [ 10   7  16  95   6  10  12]
- [  1   7   3   0  54   0   1]
- [  3   0   1   0   1  52   7]
- [ 14   4   9  11   5   7  79]]
-Node Classification on random seed  3530 -> 0.596
-Confusion Matrix:
- [[ 78   4   0   7   2   8  16]
- [  5 122   3   7  11   1   1]
- [ 26  22 128  36  31  23  38]
- [ 17   3  22  71   4  14  15]
- [  1  10   4   0  62   2   5]
- [  3   0   0   2   0  52   9]
- [ 16   6   8   6   8   8  83]]
-Node Classification on random seed  3531 -> 0.639
-Confusion Matrix:
- [[ 52   1   3   8   3  14  18]
- [  3 122   2   7   9   0   0]
- [ 14  23 163  39  18  21  38]
- [ 15   4   9 115   5   5  17]
- [  2   9   5   4  55   0   5]
- [  7   0   2   1   2  48   5]
- [ 12   6   8   3   7   7  84]]
-Node Classification on random seed  3532 -> 0.6
-Confusion Matrix:
- [[ 72   0  19   6   3  13   9]
- [  5 125   9   1   6   4   4]
- [ 39  14 145  33  27  10  51]
- [ 21   0  22  93   7   9  17]
- [  1  11   2   5  51   0   2]
- [  7   3   0   1   1  42   4]
- [ 12   1   5   4   5   7  72]]
-Node Classification on random seed  3533 -> 0.641
-Confusion Matrix:
- [[ 75   1   4   3   5  19  15]
- [  3 113  15   1   8   2   1]
- [ 27  11 172  22  20  28  34]
- [ 14   3  15  95   4   5  12]
- [  2   9   6   2  54   2   5]
- [  4   0   2   1   4  47   2]
- [ 10   1   5   9   6  17  85]]
-Node Classification on random seed  3534 -> 0.617
-Confusion Matrix:
- [[ 66   5   5  15   2   8   7]
- [  4 120   1   1   6   7   5]
- [ 31  16 124  50  26  25  38]
- [  6   2   6 120   2   2  21]
- [  3   6   4   3  58   0   1]
- [  2   3   2   5   0  52   2]
- [ 16   0   2  11  16  16  77]]
-Node Classification on random seed  3535 -> 0.64
-Confusion Matrix:
- [[ 71   2   2   5   8  11  12]
- [  0 127   5   6  16   5   6]
- [ 19  24 140  30  17  18  40]
- [  7   1  16 105   7   8  12]
- [  3   7   3   2  51   1   3]
- [  3   0   3   2   0  62   8]
- [ 13   3   6   4   3  19  84]]
-Node Classification on random seed  3536 -> 0.612
-Confusion Matrix:
- [[ 66   7   1   5   4  19  12]
- [ 10 115   4   0   7   5   2]
- [ 31  31 153  27  20  18  41]
- [ 14   3  18 102   5   3  17]
- [  2   5   2   0  54   3   6]
- [  7   0   1   1   1  40   4]
- [ 16   2   5  11   6  12  82]]
-Node Classification on random seed  3537 -> 0.599
-Confusion Matrix:
- [[ 57   4   9   6   6   6   8]
- [  4 112   1   5  12   3   2]
- [ 19  21 145  50  42  18  41]
- [  7   3  17 109   6   4  12]
- [  1   6   3   4  59   0   1]
- [  4   2   3   2   2  36  16]
- [ 10   4  10   8   8  11  81]]
-Node Classification on random seed  3538 -> 0.636
-Confusion Matrix:
- [[ 72   1   8   5   1  18  15]
- [  0 122   4   4   8  10   2]
- [ 31  12 164  31  29  24  31]
- [ 10   8   4 109   1   4  16]
- [  1   7   1   3  52   2   1]
- [  4   2   3   7   2  47   3]
- [  4   3  17   7  13   7  70]]
-Node Classification on random seed  3539 -> 0.633
-Confusion Matrix:
- [[ 76   3   0   7   1   9   8]
- [  5 135   2   4   3   2   4]
- [ 53  20 131  29  27  13  27]
- [ 16   2  23 105  11   5   7]
- [  0   5   3   2  63   0   2]
- [  9   0   3   4   0  44  10]
- [ 16   2  13   4   5   8  79]]
-Node Classification on random seed  3540 -> 0.609
-Confusion Matrix:
- [[ 73   5   0   2   3  12   6]
- [  3 133   5   4  11   4   3]
- [ 15  12 124  48  20  39  49]
- [ 12   4  14  99   3   2  22]
- [  3   5  10   3  61   1   3]
- [  5   0   0   0   0  51   9]
- [ 15   2  12   8   8   9  68]]
-Node Classification on random seed  3541 -> 0.644
-Confusion Matrix:
- [[ 79   1   2   4   6   7   3]
- [  4 137   9   9   3   2   2]
- [ 24  17 160  49  23   7  47]
- [ 11   1   9 103   4   2  14]
- [  1   5   7   0  56   1   3]
- [ 13   0   3   3   1  31   3]
- [ 13   7   4  14   5  13  78]]
-Node Classification on random seed  3542 -> 0.611
-Confusion Matrix:
- [[ 68   3   5   2   6   9  14]
- [  1 133   5   7  11   1   3]
- [ 17  23 140  38  23  18  41]
- [ 15   1  17  92   6   6  14]
- [  3   5   4   2  60   1   4]
- [  4   3   7   3   0  45   3]
- [ 14   7  22  10   7   4  73]]
-Node Classification on random seed  3543 -> 0.623
-Confusion Matrix:
- [[ 63   0  14   2   1  13  10]
- [  6 132   8   4  10   0   5]
- [ 15  12 157  28  27  25  44]
- [  5   4  19  95   2   9  11]
- [  2   7   2   3  55   3   2]
- [  5   0   3   3   0  56   1]
- [  6   2  10  12  12  30  65]]
-Node Classification on random seed  3544 -> 0.557
-Confusion Matrix:
- [[ 67   1   3  14   5  10  20]
- [  9 101   3  11   4   2   6]
- [ 23  33 121  19  38  27  44]
- [ 10   2  18 108   8   6  17]
- [  2   6   5   6  50   3   1]
- [  7   1   4   6   0  40   5]
- [  7  11  16  17   5   8  70]]
-Node Classification on random seed  3545 -> 0.63
-Confusion Matrix:
- [[ 66   1   4   6   3  13   5]
- [ 22 123   7   1  15   2   1]
- [ 26  34 148  31  22  12  17]
- [ 14   4  17 112   5   3   7]
- [  2   7   4   3  57   0   3]
- [  6   2   2   0   1  57   4]
- [  9   2  14  17   9  13  67]]
-Node Classification on random seed  3546 -> 0.629
-Confusion Matrix:
- [[ 64   3   8   3   4  11  14]
- [  2 132   4   5   9   0   5]
- [ 16  27 132  40  22  27  38]
- [  6   5  11 122   5   7  12]
- [  2   7   2   3  48   0   2]
- [  8   2   2   5   0  50   2]
- [  5   0   5   9   8  25  81]]
-Node Classification on random seed  3547 -> 0.588
-Confusion Matrix:
- [[ 66  10   2   3   6  12  10]
- [  5 112   5   2  10   5   2]
- [ 29  28 137  36  24  26  43]
- [ 19   9  23  96   2   5  14]
- [  2   7   3   5  61   0   2]
- [  2   0   1   0   2  39   4]
- [  9   3   8  16   8  10  77]]
-Node Classification on random seed  3548 -> 0.631
-Confusion Matrix:
- [[ 74   0   6   7   3  12   7]
- [  4 120   3   1  10   6   5]
- [ 31   9 138  34  28  19  37]
- [  7   5  15  98   7   5  24]
- [  1   5   3   1  57   0   2]
- [  3   2   1   2   2  53   5]
- [ 12   6   8   8  11  12  91]]
-Node Classification on random seed  3549 -> 0.608
-Confusion Matrix:
- [[ 73   1   2   3   6  10  10]
- [  2 131   5   2   8   1   3]
- [ 19  17 123  36  37  33  45]
- [  7   5  19  96   1  12  26]
- [  2   6   2   1  68   1   2]
- [  7   2   5   0   7  33   4]
- [ 11   3   5  10   6   8  84]]
-Node Classification on random seed  3550 -> 0.624
-Confusion Matrix:
- [[ 60   5  12  12   5   3  12]
- [  1 133   4   5   3   1   4]
- [ 24  21 176  32  22  32  32]
- [ 12   1  15  98   3   8  17]
- [  2  10   6   0  53   0   7]
- [  6   5   4   2   4  31   3]
- [  9   3  16   1   3   9  73]]
-Node Classification on random seed  3551 -> 0.588
-Confusion Matrix:
- [[ 69   5   7   1   3  15  11]
- [  0 121   8   6   6  10   2]
- [ 31  42 117  42  38  30  40]
- [  7   6  22 104   5   6   9]
- [  2   5   1   0  55   0   2]
- [  4   1   0   0   2  45   6]
- [  2   2   7   5   8  13  77]]
-Node Classification on random seed  3552 -> 0.617
-Confusion Matrix:
- [[ 68   6   3   4   2   9  11]
- [  6 140   1   0   7   0   6]
- [ 27  28 127  47  36  17  39]
- [  9   2  11 103   2   5  10]
- [  1   5   0   2  65   2   5]
- [  3   1   2   1   2  41   7]
- [ 12   7   6  10  11  18  73]]
-Node Classification on random seed  3553 -> 0.631
-Confusion Matrix:
- [[ 75   3   1   3   5  11   6]
- [  6 127   4   0  11   3   0]
- [ 21  28 147  34  23  26  37]
- [ 11   2  17  96   8  10  11]
- [  2  11   6   1  54   2   2]
- [  8   3   3   0   1  43   1]
- [ 15   3   8   8   3  11  89]]
-Node Classification on random seed  3554 -> 0.615
-Confusion Matrix:
- [[ 62   3   2   6   4  11  15]
- [ 10 140   6   2   5   3   2]
- [ 28  23 147  40  14  15  43]
- [ 14   3  17 104   6  10   5]
- [  3  12   7   1  49   0   1]
- [  2   1   6   1   0  48   5]
- [  6   4  11  14   2  22  65]]
-Node Classification on random seed  3555 -> 0.581
-Confusion Matrix:
- [[ 72   2   1  10   1  13  10]
- [  3 134   4   4  11   5   3]
- [ 18  19 100  38  43  46  42]
- [  7   9  15  88   2  10  18]
- [  0   3   1   2  64   0   1]
- [ 12   0   7   2   4  39   3]
- [  5   4   5   7   6  23  84]]
-Node Classification on random seed  3556 -> 0.618
-Confusion Matrix:
- [[ 57   7   8  10   3  14   7]
- [  2 136   2   9  11   3   5]
- [ 24  24 171  18  23  21  30]
- [ 13   5  15  90   6   5  20]
- [  2   7   6   1  58   1   4]
- [  8   1   3   3   0  39   0]
- [ 10   4  16   7   3  21  67]]
-Node Classification on random seed  3557 -> 0.602
-Confusion Matrix:
- [[ 73   1   7   6   5  10   6]
- [  6 135   5   2  12   0   2]
- [ 25  34 150  22  32  23  38]
- [ 21   2  31  71   8   5   5]
- [  4   2   5   1  57   2   2]
- [  6   1   3   1   1  38   2]
- [  8  10   7   8   7  20  78]]
-Node Classification on random seed  3558 -> 0.599
-Confusion Matrix:
- [[ 72   1  14   2   6  14   3]
- [  1 129   9   2  17   0   6]
- [ 23  12 123  42  44  32  25]
- [ 15   4  10 116   8   5   9]
- [  0   8   6   1  53   0   2]
- [  4   2   4   0   2  55   5]
- [ 16   3   5   6  11  22  51]]
-Node Classification on random seed  3559 -> 0.603
-Confusion Matrix:
- [[ 71   4   2   6   6  17   7]
- [  4 123  10   6  12   1   6]
- [ 23  15 146  29  14  23  45]
- [ 10   4  15 112   5  13   6]
- [  1   1   4   6  56   0   6]
- [  6   0   2   8   1  33   0]
- [ 11   3  13  32   4  16  62]]
-Node Classification on random seed  3560 -> 0.6
-Confusion Matrix:
- [[ 58   1   6   1   3  16  13]
- [  7 133   2   6   7   2   7]
- [ 37  26 144  34  30  16  35]
- [ 11   0  20  90   4   3  17]
- [  2   6   5   2  65   0   3]
- [  9   2   2   0   0  48   5]
- [  9   3  22   5   4  17  62]]
-Node Classification on random seed  3561 -> 0.606
-Confusion Matrix:
- [[ 67   5   6   4   7   9  12]
- [  4 120   7   2  13   1   7]
- [ 18  31 138  20  25  34  37]
- [ 14   5  18  87  10   5  16]
- [  2   7   9   0  62   3   1]
- [  4   0   5   0   1  44   9]
- [ 12   6  13   0   7   5  88]]
-Node Classification on random seed  3562 -> 0.662
-Confusion Matrix:
- [[ 87   0   2   6   2   4   9]
- [  3 110   4   6   9   1   8]
- [ 16  10 150  29  34  20  41]
- [ 14   0  23 110   2   5  16]
- [  0   7   2   0  61   2   2]
- [  9   0   2   0   8  44   7]
- [  8   1  11   5   3   7 100]]
-Node Classification on random seed  3563 -> 0.631
-Confusion Matrix:
- [[ 83   1   2   4   6  10   8]
- [  4 140   4   2  14   1   2]
- [ 21  13 126  27  21  23  56]
- [  9   0  10 100  17   5  16]
- [  3   5   2   3  59   0   2]
- [  3   0   2   1   1  46   3]
- [ 25   5  12   4   7  15  77]]
-Node Classification on random seed  3564 -> 0.618
-Confusion Matrix:
- [[ 80   4   5   3   1   4   9]
- [  2 137   8   2   7   1   7]
- [ 30  21 134  44  51  20  22]
- [ 15   2  19 107   2   3   7]
- [  1   3   4   3  57   3   0]
- [  5   0   4   2   1  41   5]
- [ 10   3  13  16  12   8  62]]
-Node Classification on random seed  3565 -> 0.62
-Confusion Matrix:
- [[ 80   2   4  10   4   4   8]
- [  4 125   6   3   5   2   3]
- [ 35  16 131  38  47  22  38]
- [ 13   4  10 107   4   2  12]
- [  1   8   3   0  62   1   1]
- [  1   0   4   1   1  34  11]
- [ 12   2  13   5   9  11  81]]
-Node Classification on random seed  3566 -> 0.621
-Confusion Matrix:
- [[ 73   2   5   9   2  13   0]
- [  3 124   2   3  11   4   3]
- [ 30  32 148  22  42  12  29]
- [ 17   5  15 102   9   5   9]
- [  4   6   5   1  64   0   1]
- [  3   2   5   3   1  48   0]
- [ 17   8   8   7  10  14  62]]
-Node Classification on random seed  3567 -> 0.598
-Confusion Matrix:
- [[ 71   5   0   4   1  19  11]
- [  2 141   8   4   5   3   6]
- [ 28  22 120  34  31  19  58]
- [ 10   4   3 112   7   3  20]
- [  1   4   3   1  55   6   5]
- [ 10   0   3   1   0  35   2]
- [ 19   1  12  11   6  10  64]]
-Node Classification on random seed  3568 -> 0.601
-Confusion Matrix:
- [[ 61   4  12   6   1  12   4]
- [  7 132   4   5   6   3   3]
- [ 30  15 140  20  38  11  50]
- [ 17   1  16  90  14   7  14]
- [  0  12   2   2  61   0   2]
- [  6   2   1   2   3  48   3]
- [ 14   3  26   4   8   9  69]]
-Node Classification on random seed  3569 -> 0.613
-Confusion Matrix:
- [[ 65   4   4   5   3   9   8]
- [  4 132   5   0   4   1   1]
- [ 43  24 145  28  12  13  32]
- [ 21   3  32  87   5   3  21]
- [  4  11   4   0  62   1   2]
- [  4   2   2   3   1  36  10]
- [ 14  10  16   2   6  10  86]]
-Node Classification on random seed  3570 -> 0.572
-Confusion Matrix:
- [[ 69   0   6   5   6  16  12]
- [  6 134   4   1   6   5   4]
- [ 34  32 118  31  22  34  32]
- [ 34   5  19  72   3   9  17]
- [  2  10   1   2  62   1   1]
- [  6   2   1   2   1  51   4]
- [ 10   3  11   8   3  17  66]]
-Node Classification on random seed  3571 -> 0.616
-Confusion Matrix:
- [[ 68   2   2   9   3  23  12]
- [  2 123   5   4   4   1   3]
- [ 13  25 142  26  23  19  51]
- [ 14  12  14 106   4   3  14]
- [  2   6   4   3  56   1   4]
- [  1   1   2   2   2  49   5]
- [  6   9  13  15   6  14  72]]
-Node Classification on random seed  3572 -> 0.625
-Confusion Matrix:
- [[ 75   5   6   2   4  12   4]
- [  4 139   2   2   5   3   6]
- [ 17  29 153  45  18  29  34]
- [  5   5  12  89   8   4  16]
- [  1   5   6   1  66   3   3]
- [  9   1   4   0   2  32   8]
- [ 12   2  10   9   7  15  71]]
-Node Classification on random seed  3573 -> 0.627
-Confusion Matrix:
- [[ 63   1  10   4   4  14  14]
- [  2 121   9   2  14   6   2]
- [ 16  18 150  39  24  18  42]
- [  2   6  29 111   4   6  11]
- [  1   4   2   3  64   0   2]
- [  5   1   1   1   0  41   7]
- [  6   1  14   5   8  15  77]]
-Node Classification on random seed  3574 -> 0.593
-Confusion Matrix:
- [[ 46   0   2  14   9  19   8]
- [ 10 118   6   1  11   3   5]
- [ 17  13 122  34  46  25  38]
- [ 10   4  11  95   9   5  29]
- [  1   7   5   1  56   0   3]
- [  4   2   4   2   1  54   1]
- [ 13   5  10   2  10   7 102]]
-Node Classification on random seed  3575 -> 0.632
-Confusion Matrix:
- [[ 60   0   2   9   4  10  14]
- [  5 109   7   1  25   3   2]
- [ 33  12 152  36  18  26  27]
- [  4   4  20 125   7   5   9]
- [  2   5   3   2  66   1   1]
- [ 11   1   3   3   0  42   5]
- [ 14   4   4  10   6  10  78]]
-Node Classification on random seed  3576 -> 0.567
-Confusion Matrix:
- [[ 56   5  11   6   1  17  11]
- [  5 126   7   4   9   2   4]
- [ 16  29 109  36  30  15  60]
- [ 16   9   7 103   9   9  13]
- [  2   5   0   1  53   3   5]
- [  0   0   7   4   0  50  10]
- [ 14   9  15   9   4  14  70]]
-Node Classification on random seed  3577 -> 0.612
-Confusion Matrix:
- [[ 72   0  14   4   5  16   9]
- [  3 128   4   5   2   0   4]
- [ 20  28 127  30  39  28  36]
- [  9   8  10 107   2  11  18]
- [  0   6   1   6  51   0   2]
- [  5   1   0   1   0  45   4]
- [  8   7   8   9   9  16  82]]
-Node Classification on random seed  3578 -> 0.611
-Confusion Matrix:
- [[ 74   3   0   4   4  13  15]
- [  7 112  10  13   5   6   1]
- [ 14  22 126  50  49  16  36]
- [  8   1   9  95   5   6  19]
- [  1   3   2   4  67   0   2]
- [  3   4   1   2   2  51   7]
- [  2   6   5  10   7  12  86]]
-Node Classification on random seed  3579 -> 0.616
-Confusion Matrix:
- [[ 54   2   7   2   3  17  14]
- [  1 128   6   3  10   5   2]
- [ 47  17 147  46  17  18  29]
- [  8   4  17  96   3  10  24]
- [  0   4   3   1  72   0   1]
- [  1   4   3   5   3  47   2]
- [  8   2   7   7   8  13  72]]
-Node Classification on random seed  3580 -> 0.598
-Confusion Matrix:
- [[ 53   4   3   2   2  22  16]
- [  2 124   6   5   5   4   7]
- [ 24  22 124  46  20  27  39]
- [  5   3  23 107   7   4  11]
- [  1   5   7   2  66   2   2]
- [  5   2   1   3   1  48   7]
- [ 12   6   9   4   7  17  76]]
-Node Classification on random seed  3581 -> 0.618
-Confusion Matrix:
- [[ 65   5   6   2   5  13  13]
- [  4 130   5   3   5   0   5]
- [ 19  22 149  26  24  16  37]
- [ 10   4  17 109   6   5  11]
- [  2   5   3   3  66   1   1]
- [  9   5   1   3   2  36  12]
- [ 11   8  14  10  18  11  63]]
-Node Classification on random seed  3582 -> 0.635
-Confusion Matrix:
- [[ 85   2   2   2   7   4  12]
- [  6 121   1   3   6   4   1]
- [ 26  27 154  32  29  21  33]
- [ 22  10  11  93   1   2   4]
- [  3   5   5   2  63   4   2]
- [  4   2   3   2   1  40  10]
- [ 15   0   7  10   4  18  79]]
-Node Classification on random seed  3583 -> 0.625
-Confusion Matrix:
- [[ 69   2   2  10   5  10  11]
- [  2 118   4   2  23   1   2]
- [ 13  27 135  37  28  17  32]
- [ 13   4  25 107   7   3  12]
- [  7   2   4   3  55   0   1]
- [  3   1   0   3   1  59   1]
- [  8   6   6  19   6  12  82]]
-Node Classification on random seed  3584 -> 0.633
-Confusion Matrix:
- [[ 77   4   3   4   2  12   6]
- [  2 134   5   8   6   1   4]
- [ 32  21 156  18  19  27  39]
- [ 18   6   4 116   1   5  12]
- [  2   7   6   2  56   2   2]
- [  7   1   5   4   0  38   7]
- [  8   5   8  14   6  22  56]]
-Node Classification on random seed  3585 -> 0.591
-Confusion Matrix:
- [[ 86   3   6   4   6   7   9]
- [ 11 107   4   0  18   4   2]
- [ 13  12 105  26  76  31  30]
- [  8   3  20  97   4   5  17]
- [  1   3   2   1  80   0   4]
- [  7   2   0   2   0  42   2]
- [ 10   1  13  25   6  11  74]]
-Node Classification on random seed  3586 -> 0.593
-Confusion Matrix:
- [[ 53   3   5   5   1  11  20]
- [  1 100  16   3  17   5   7]
- [ 15  15 154  28  28  34  61]
- [ 13   1  19  94   4   9  15]
- [  1   2   2   1  67   0   1]
- [  3   0   3   2   1  45   9]
- [  8   2   7   4   3  22  80]]
-Node Classification on random seed  3587 -> 0.605
-Confusion Matrix:
- [[ 74   0   3   6   6  17   5]
- [  2 129   5   1  10   3   3]
- [ 34  33 114  23  22  36  36]
- [ 10   3  18 118   3   3  16]
- [  1   8   3   0  66   1   0]
- [  6   2   3   2   4  35   2]
- [ 16   4   4  10  12  19  69]]
-Node Classification on random seed  3588 -> 0.584
-Confusion Matrix:
- [[ 89   4   5   5   0   4  15]
- [  5 129   3   2   3   2   7]
- [ 27  14  96  51  70   9  33]
- [ 22   3  17 102   9   3   4]
- [  6   5   3   1  60   0   5]
- [  9   4   2   2   0  46   2]
- [ 15   9   6   9  12   9  62]]
-Node Classification on random seed  3589 -> 0.651
-Confusion Matrix:
- [[ 64   2   8   4   7  14   4]
- [  1 134   2   7   1   4   4]
- [ 23  25 144  36  29  18  26]
- [ 19   3  10 115   4   7   7]
- [  1   6   2   1  65   2   1]
- [  4   1   0   0   1  46   4]
- [ 10   5  13  12   6  15  83]]
-Node Classification on random seed  3590 -> 0.645
-Confusion Matrix:
- [[ 56   7  11   8   4  10  12]
- [  4 144   4   3   5   2   3]
- [ 28   7 153  40  23  18  30]
- [  4   3  13  95   7   5  27]
- [  5   6   2   2  61   2   2]
- [  2   0   0   3   0  56   9]
- [ 14   0  10   5   6   9  80]]
-Node Classification on random seed  3591 -> 0.65
-Confusion Matrix:
- [[ 79   2   3   3   3   8  11]
- [  5 141   3   2   3   2   7]
- [  9  22 152  30  46  12  42]
- [  7   5  12  98   5   3  19]
- [  1   8   4   2  49   1   2]
- [  5   2   5   2   1  40   4]
- [  7   3   7  12   7  13  91]]
-Node Classification on random seed  3592 -> 0.631
-Confusion Matrix:
- [[ 70   0   4  10   3  14  11]
- [  2 123   4   7  11   2   3]
- [ 12  24 138  35  41  23  29]
- [  8   1  15 132   3   5   2]
- [  0   3   6   1  56   0   4]
- [  8   1   1   5   5  41   8]
- [  7   3  14  12   3  19  71]]
-Node Classification on random seed  3593 -> 0.585
-Confusion Matrix:
- [[ 61   2   8   8   4  10   9]
- [  5 135   3   6   4   3   3]
- [ 14  27 124  59  32  23  47]
- [ 22   2  20  93   7   4  14]
- [  1   8   5   0  58   3   1]
- [  4   0   2   1   0  46   5]
- [ 23   2   6   7   5   6  68]]
-Node Classification on random seed  3594 -> 0.64
-Confusion Matrix:
- [[ 79   2  11   4   6   9   8]
- [  4 120  12   9   4   2   5]
- [ 17  27 154  26  22  28  36]
- [ 12   3  10 117   5   8   5]
- [  3   8   4   2  50   4   2]
- [  5   0   1   3   0  51   0]
- [ 10   5  10   8   5  15  69]]
-Node Classification on random seed  3595 -> 0.597
-Confusion Matrix:
- [[ 77   0   9   3   4   9   6]
- [  3 138   4   3   1   1   5]
- [ 21  23 134  40  25  15  40]
- [ 24   3  17  97   5   5  14]
- [  0   7   2   1  64   2   6]
- [ 18   2   1   6   1  37   8]
- [ 20   5  16   8   6  14  50]]
-Node Classification on random seed  3596 -> 0.638
-Confusion Matrix:
- [[ 70   2   9   7   9  12   8]
- [  6 128   5   4   2   3   7]
- [ 13  22 151  31  25  24  28]
- [  8   4  14 109   3   7   8]
- [  3   7   3   3  60   1   4]
- [  6   3   1   1   0  51   4]
- [  7   6  15   8   6  23  69]]
-Node Classification on random seed  3597 -> 0.645
-Confusion Matrix:
- [[ 75   3   6   5   4  15   5]
- [  2 139   7   2   7   0   6]
- [ 23  16 150  27  11  23  50]
- [  4   1  21  97   3   7  16]
- [  1   8   5   3  56   0   4]
- [  1   2   4   0   2  50   6]
- [  2   5  10  16   4  18  78]]
-Node Classification on random seed  3598 -> 0.608
-Confusion Matrix:
- [[ 72   7   5  11   3   3  18]
- [ 10 107   2   4  13   1   8]
- [ 21  20 138  39  36  27  35]
- [ 13   3  13 108   4   8   9]
- [  2   2   0   2  64   0   4]
- [  6   0   3   2   2  45   7]
- [  9   1   9   9   6  15  74]]
-Node Classification on random seed  3599 -> 0.647
-Confusion Matrix:
- [[ 65   5   3   4   6  11  14]
- [  7 146   5   1   0   1   3]
- [ 14  27 145  23  13  37  51]
- [  3   6  10 109   7  13  13]
- [  1  10   3   1  53   1   6]
- [  7   2   3   0   1  44   9]
- [  7   1  10   3   4   7  85]]
-Node Classification on random seed  3600 -> 0.638
-Confusion Matrix:
- [[ 67   8  15   8   2  12  10]
- [  1 139   3   3   5   1   6]
- [ 26   9 158  35  21  27  27]
- [  5   2  12 103   3  11  12]
- [  1   4   4   1  63   0   3]
- [  3   3   6   4   1  49   5]
- [  8   1  18  19   7  10  59]]
-Node Classification on random seed  3601 -> 0.623
-Confusion Matrix:
- [[ 61   1  17   8   3  14   9]
- [  5 133   6   3   8   1   6]
- [ 17  25 149  31  38  20  38]
- [  7   2  18 104   4   4   6]
- [  0   5   3   2  63   4   5]
- [  4   1  12   2   1  37  11]
- [  5   0  10   7   6   8  76]]
-Node Classification on random seed  3602 -> 0.62
-Confusion Matrix:
- [[ 63   2   1   7   2   8  17]
- [  1 128   6   7   3   2   3]
- [ 18  19 130  47  20  18  38]
- [ 12   7  23  92   6   5  13]
- [  5   6   3   4  73   2   2]
- [  3   2   3   1   2  55   3]
- [  9   2  20   4  10  14  79]]
-Node Classification on random seed  3603 -> 0.613
-Confusion Matrix:
- [[ 67   4   4   1   8   7  12]
- [  3 117   3   2  10   1   6]
- [ 25  29 129  33  36  21  39]
- [ 16  10  19 110   2   2  19]
- [  2   2   3   4  67   0   3]
- [  9   4   5   3   3  46   6]
- [ 14   3   2   1   4   7  77]]
-Node Classification on random seed  3604 -> 0.587
-Confusion Matrix:
- [[ 73   1   8   7   1  12   8]
- [ 13 116   5   2   3   1   3]
- [ 27  39 124  57  19  16  30]
- [  4   3  23 103   4   6  17]
- [  5  14   5   5  57   2   1]
- [  5   3   0   3   2  47   3]
- [  8   4   9  14   7  14  67]]
-Node Classification on random seed  3605 -> 0.618
-Confusion Matrix:
- [[ 73   2   1   7   4   7  11]
- [  7 126   3   1  13   3   8]
- [ 34  34 120  33  27  25  39]
- [  2   1  17 113   3   4   9]
- [  2   4   4   2  59   0   5]
- [  4   1   1   3   0  56   6]
- [ 12   2   4  13   7  17  71]]
-Node Classification on random seed  3606 -> 0.616
-Confusion Matrix:
- [[ 57   3  12   7   3  10   4]
- [  7 133   6   0   4   6   6]
- [ 19  21 126  41  35  17  48]
- [ 11   7  12 114   6   9   9]
- [  1   9   5   0  63   1   1]
- [  3   1   7   0   0  47  10]
- [  8   3   6  12   6   8  76]]
-Node Classification on random seed  3607 -> 0.601
-Confusion Matrix:
- [[ 69   4   1   9   6   5  10]
- [  7 119   1   7   5   0   4]
- [ 36  19 149  30  27   8  59]
- [ 15   8  15  86   5   8  13]
- [  1   7   4   4  58   0   2]
- [ 11   6   6   0   2  41   2]
- [ 11   9   6  12   4  10  79]]
-Node Classification on random seed  3608 -> 0.623
-Confusion Matrix:
- [[ 71   3   2  18   2   7   6]
- [  2 125   5   4   3   3   3]
- [ 18  20 147  50  25  20  42]
- [  8   5  13 104   3   5   8]
- [  2   8   5   5  61   1   2]
- [ 10   0   4   3   0  46   7]
- [ 14   7   6  12   6  10  69]]
-Node Classification on random seed  3609 -> 0.596
-Confusion Matrix:
- [[ 63   3   4  12   3  10  14]
- [  4 119   5   3   8   2   8]
- [ 33  20 130  53  26  19  54]
- [ 11   1  10  83   2   3  22]
- [  1   7   2   5  55   1   4]
- [ 10   2   0   3   0  53   3]
- [  7   0   8   1  11   9  93]]
-Node Classification on random seed  3610 -> 0.625
-Confusion Matrix:
- [[ 73   1   7   7   5  13   3]
- [  8 130   3   3   3   0   4]
- [ 22  16 164  23  53  18  46]
- [ 15   2  21  86   6   5  14]
- [  1   4   3   2  60   1   3]
- [  4   1   2   3   0  42   7]
- [ 20   7   5   7   4   3  70]]
-Node Classification on random seed  3611 -> 0.604
-Confusion Matrix:
- [[ 76   1  10   2   2   8  11]
- [  5 113   6   5  14   3  10]
- [ 21  29 131  35  28  20  43]
- [ 16   1  13 115   2   3  18]
- [  3   4   3   4  63   2   3]
- [  6   0   3   1   2  39   5]
- [ 13   2  17   1   6  15  67]]
-Node Classification on random seed  3612 -> 0.586
-Confusion Matrix:
- [[ 64   0   7  11   3  22  11]
- [  0 122   5   8  17   7   6]
- [ 20  20 112  34  22  31  51]
- [ 14   6  13 106   3   3  13]
- [  0   9   5   0  58   0   1]
- [  5   2   1   2   1  52   7]
- [  9   1  13  12   4  15  72]]
-Node Classification on random seed  3613 -> 0.639
-Confusion Matrix:
- [[ 82   2   5   5   3  10   2]
- [  5 122   8   4   7   1   4]
- [ 21  27 163  50  18  19  33]
- [  8   4  11 103   2   5  13]
- [  2   4   5   2  62   3   1]
- [  9   4   5   3   0  40   4]
- [ 16   3   7   8   3  15  67]]
-Node Classification on random seed  3614 -> 0.655
-Confusion Matrix:
- [[ 86   4   7   7   2   6   4]
- [  9 122   2   2   8   1   2]
- [ 16   8 160  37  21  27  39]
- [  9   4  13 115   5   5   9]
- [  0   6   6   0  57   0   4]
- [  7   1   4   0   0  47   0]
- [ 22   1   8  12  10  17  68]]
-Node Classification on random seed  3615 -> 0.617
-Confusion Matrix:
- [[ 68   4   4   3   4  12  16]
- [  3 137   4   1  13   3   1]
- [ 16  15 141  36  28  14  57]
- [ 11   2  22 100  18   4   7]
- [  0   6   5   1  65   0   1]
- [  6   1   8   1   2  37   4]
- [ 10   1  15   2  14   8  69]]
-Node Classification on random seed  3616 -> 0.587
-Confusion Matrix:
- [[ 76   1   4   4   4  19   4]
- [  4 128   6   0   4   6   2]
- [ 32  24 116  46  21  42  24]
- [ 13   2   4 119  12  16  13]
- [  2   6   9   0  49   3   1]
- [  5   1   1   2   0  45  11]
- [ 13   6   9   0  10  27  54]]
-Node Classification on random seed  3617 -> 0.637
-Confusion Matrix:
- [[ 68   6   6   6   3  13  13]
- [  9 136  11   0   1   0   6]
- [ 12  37 162  20  11  18  41]
- [  5   4  17 104   4   5  19]
- [  1  10   2   2  52   0   2]
- [  5   0   1   4   1  43   5]
- [ 16   5  17   6   4  15  72]]
-Node Classification on random seed  3618 -> 0.607
-Confusion Matrix:
- [[ 71   1   6   3   2  13   5]
- [  0 121   6   2   3   1   4]
- [ 12  28 158  62  31  18  29]
- [ 18   3  22  95   8   6  12]
- [  1  12   1   2  63   0   2]
- [  4   3   5   0   5  35   4]
- [ 13   1  11  19   4  11  64]]
-Node Classification on random seed  3619 -> 0.558
-Confusion Matrix:
- [[ 61   1   5   9  10  15  16]
- [  5 127   3   2   8   2   7]
- [ 18  19 107  59  43  39  34]
- [  9   5  11  97  10   9  14]
- [  1   6   0   2  56   0   1]
- [  6   0   6   2   2  39   8]
- [ 11   7  13   3   7  14  71]]
-Node Classification on random seed  3620 -> 0.634
-Confusion Matrix:
- [[ 76   2   2   2  10  12  10]
- [  5 129   6   5  11   4   3]
- [ 24  24 160  44  28  12  33]
- [  8   9   8 102   5   5  14]
- [  0   6   1   3  62   1   2]
- [  6   3   8   1   4  35   3]
- [ 11   4   5   9   4   9  70]]
-Node Classification on random seed  3621 -> 0.64
-Confusion Matrix:
- [[ 69   2   8   3   2   8  15]
- [  3 112  13   6  10   2   8]
- [ 13  20 152  55  19  18  31]
- [ 10   8   9 105   6   4   9]
- [  0   4   9   0  60   0   2]
- [  3   0   3   1   0  62   7]
- [  6   0  15   4  10  14  80]]
-Node Classification on random seed  3622 -> 0.595
-Confusion Matrix:
- [[ 64   6   5   9   4  18  14]
- [  2 117   6   5  13   3   5]
- [ 13  25 141  16  27  30  46]
- [  5   2  30  98   4   6  20]
- [  0   5   5   2  67   1   4]
- [  3   0   6   2   2  36   8]
- [ 12   8  10   7   4  12  72]]
-Node Classification on random seed  3623 -> 0.647
-Confusion Matrix:
- [[ 68   3   5  11   2   9   4]
- [  2 137   3   0   2   3   9]
- [ 22  20 151  19  36  13  47]
- [ 14   3  20 104   6   5  11]
- [  0   7   4   1  58   0   3]
- [  4   0   4   1   0  50   2]
- [ 13  11  10   9   7   8  79]]
-Node Classification on random seed  3624 -> 0.597
-Confusion Matrix:
- [[ 78   2   7   7   5  16   9]
- [  2 141   3   2   1   1  14]
- [ 21  37 126  49  27  26  25]
- [ 13   2  13  90   6  14   6]
- [  1  11   1   2  48   2   4]
- [ 16   1   3   1   0  42   6]
- [ 10   6  15   3   4   9  72]]
-Node Classification on random seed  3625 -> 0.569
-Confusion Matrix:
- [[ 65   5   9  12   5   8   7]
- [ 12 108   2  10   4   3   6]
- [ 25  23 125  28  24  19  50]
- [  8   6   9 109   6   5  19]
- [  1  10   6   3  52   0   4]
- [  6   1   7   0   3  31   8]
- [ 13   2   5   8  24  25  79]]
-Node Classification on random seed  3626 -> 0.609
-Confusion Matrix:
- [[ 78   5   8   1   3  11   6]
- [  5 130   8   0   2   3  10]
- [ 37  21 140  17  42  41  23]
- [ 11   5  20  92   2   7  10]
- [  2  12   4   3  49   4   4]
- [  4   2   1   0   1  40   5]
- [ 10   2  15   3   4  17  80]]
-Node Classification on random seed  3627 -> 0.63
-Confusion Matrix:
- [[ 74   1   4   7   2  12   4]
- [  4 131   6   3  17   6   3]
- [ 36  14 135  34  19  16  28]
- [ 16   2  12 108   8  10   6]
- [  2   6   7   2  64   2   2]
- [ 10   0   5   2   0  44   6]
- [ 19   2   9   9   4  13  74]]
-Node Classification on random seed  3628 -> 0.631
-Confusion Matrix:
- [[ 65   3   8   6   6   7   9]
- [  5 136   8   3   8   0   2]
- [ 17  24 151  17  21  28  47]
- [ 12   1   9  90   6   3  29]
- [  3   6   4   1  54   1   1]
- [ 10   3   4   2   0  49   4]
- [ 23   3   4   3  12   6  86]]
-Node Classification on random seed  3629 -> 0.645
-Confusion Matrix:
- [[ 71   4   3   5   9   7   8]
- [  3 135   7   1   6   4   1]
- [ 28  23 170  30  12  24  31]
- [  7   0  15  94  10   8  15]
- [  1   9   6   0  64   3   1]
- [  7   2   0   0   1  46   8]
- [ 21   2  13   4   5  11  65]]
-Node Classification on random seed  3630 -> 0.628
-Confusion Matrix:
- [[ 59   4   8   1   4  15  12]
- [  1 135   3   8   7   3   3]
- [ 26  26 154  37  20  26  44]
- [  9   6  16  96   1   5   9]
- [  0   4   5   3  60   0   2]
- [  6   4   4   0   1  40   3]
- [  7   4   9   6   3  17  84]]
-Node Classification on random seed  3631 -> 0.583
-Confusion Matrix:
- [[ 78   4   3  14  12   9   2]
- [  1 106   6   2  20   7   2]
- [ 29  21 164  34  21  10  33]
- [ 32   3  21  70   6  13  16]
- [  1   5   5   1  54   2   2]
- [  7   1   5   3   2  37   2]
- [ 23   2   8   4  10  13  74]]
-Node Classification on random seed  3632 -> 0.623
-Confusion Matrix:
- [[ 75   4   8   6   3  10  13]
- [  2 116  11   2   9   5   6]
- [ 18  12 150  38  18  22  53]
- [ 22   5  13  98   2   3  14]
- [  0   6   4   0  63   0   3]
- [  1   2   4   9   0  45   3]
- [ 10   5  10   0   2  19  76]]
-Node Classification on random seed  3633 -> 0.6
-Confusion Matrix:
- [[ 45   3   4   6   3  15  17]
- [  5 132   2   6  18   1   3]
- [ 29  30 150  29  19  23  47]
- [ 17   2  13  86   7   3  10]
- [  1   3   2   1  69   0   2]
- [  0   3   0   9   0  43  16]
- [ 11   3   5  10   8  14  75]]
-Node Classification on random seed  3634 -> 0.618
-Confusion Matrix:
- [[ 76   1   0   2   5   8  18]
- [  7 118   7   2   5   5   2]
- [ 16  52 130  30  39  15  26]
- [ 12  10  16 100   6   4  10]
- [  1   4   1   5  70   0   1]
- [  5   2   0   0   1  51   5]
- [ 20   3  12   5   5  14  73]]
-Node Classification on random seed  3635 -> 0.576
-Confusion Matrix:
- [[ 73   0   3   5   2   7  10]
- [ 14 126   4   1   8   1   6]
- [ 28  28 112  49  40  37  37]
- [ 10   2  43  82   3   1  11]
- [  3   5   4   1  63   1   3]
- [  6   0   1   4   1  43   4]
- [ 12   1   9   3   6  10  77]]
-Node Classification on random seed  3636 -> 0.621
-Confusion Matrix:
- [[ 77   3   2   2   2  10  23]
- [ 11 102   6   1   9   5   8]
- [ 41  11 139  25  30  24  41]
- [  6   3  10 117   6   6  13]
- [  2   2   2   4  62   1   1]
- [ 11   2   1   2   3  38   0]
- [ 17   1   6   6   9  11  86]]
-Node Classification on random seed  3637 -> 0.616
-Confusion Matrix:
- [[ 49   3   7   9   4  10  10]
- [  4 128   2   6  10   2   1]
- [ 31  20 159  38  29  18  29]
- [  4   5  18  99   4  11  13]
- [  3   7   4   2  69   0   2]
- [  6   1   5   1   2  46   5]
- [ 14   2   5   8  13  16  66]]
-Node Classification on random seed  3638 -> 0.646
-Confusion Matrix:
- [[ 93   6   6   2   4   8   3]
- [  4 118  12   1  11   2   3]
- [ 21  16 144  39  27  26  35]
- [ 10   5   8 109   2   7  15]
- [  1   3   2   0  70   2   5]
- [  7   0   0   0   1  49   4]
- [ 28   4   7   5   5   7  63]]
-Node Classification on random seed  3639 -> 0.595
-Confusion Matrix:
- [[ 68   5   4   3   1  22   3]
- [  4 134   4   7   4   3   1]
- [ 23  26 139  48  41  22  22]
- [ 11   5  31  71   8  10  14]
- [  0   5   2   2  66   0   1]
- [  1   3   1   2   2  42   5]
- [  8   7   9   9  12  14  75]]
-Node Classification on random seed  3640 -> 0.592
-Confusion Matrix:
- [[ 68   2   2   9   6  20   3]
- [  8 115   3   3   7   2   3]
- [ 18  13 129  55  29  21  34]
- [ 24   3  15  97   6   2  21]
- [  0   7   5   2  72   2   3]
- [  7   0   2   3   2  41   8]
- [ 14   1   6  16   6  15  70]]
-Node Classification on random seed  3641 -> 0.58
-Confusion Matrix:
- [[ 65   1   4   8   4  10  14]
- [  1 103   6   4   7  10   5]
- [ 26  22 132  50  34  31  33]
- [ 15   4  14  95  12   5  13]
- [  4   4   1   2  59   2   0]
- [ 10   0   4   2   2  52   2]
- [ 22   3  11   4   5   9  74]]
-Node Classification on random seed  3642 -> 0.587
-Confusion Matrix:
- [[ 68   2  10   2   9  14  18]
- [  6 119   6   1  13   1   4]
- [ 20  15 143  25  37  14  53]
- [ 22   5  12  91   3   6  13]
- [  2   8   1   3  61   0   1]
- [  5   1   3   5   3  31   6]
- [  5   4  20   5   9  21  74]]
-Node Classification on random seed  3643 -> 0.612
-Confusion Matrix:
- [[ 76   2   0   7   5  10   6]
- [  5 134   4   4   6   4   3]
- [ 36  15 114  45  23  31  35]
- [ 10   2  14  97   2   6  19]
- [  1  10   3   3  43   0   5]
- [ 10   0   2   0   1  67   1]
- [ 21   3   4   8   1  21  81]]
-Node Classification on random seed  3644 -> 0.623
-Confusion Matrix:
- [[ 58   1   1   3   6  14  15]
- [  8 142   2   3   3   4   4]
- [ 17  24 157  42  30  11  35]
- [ 15   5  12  91   4  13  12]
- [  0   8   3   0  52   1   4]
- [ 14   3   2   1   0  39   3]
- [ 11   2  10  10   6  15  84]]
-Node Classification on random seed  3645 -> 0.638
-Confusion Matrix:
- [[ 74  11   1   5   3  13   7]
- [  2 135   6   0   3   4   5]
- [ 17  39 146  32  13  30  31]
- [  9   6  12 102   4   6  12]
- [  1   9   6   0  62   1   0]
- [  6   1   0   2   1  50   5]
- [ 17   8   7  10   6  11  69]]
-Node Classification on random seed  3646 -> 0.572
-Confusion Matrix:
- [[ 61   9   6   3   4   9  13]
- [  7 119   2   3   8   8  11]
- [ 48  27 128  26  20  29  37]
- [ 13   5  17  91   8   1  10]
- [  0   2   3   1  61   4   1]
- [  6   1   2   3   1  41   3]
- [ 16   3  16   6   6  30  71]]
-Node Classification on random seed  3647 -> 0.593
-Confusion Matrix:
- [[ 55   2   7   3   9  11  18]
- [  7 122   3   6  11   6   3]
- [ 35  28 121  32  31  23  45]
- [ 12   4  13 104   5   5  18]
- [  1   8   3   4  56   0   1]
- [  8   0   0   3   0  47   7]
- [  8   4   7   2   6   8  88]]
-Node Classification on random seed  3648 -> 0.593
-Confusion Matrix:
- [[ 78   4   4   3   3  17   5]
- [  3 136   4   1  10   5   1]
- [ 32  21 123  38  33  31  31]
- [ 19   1  15 103   3  12  11]
- [  1  10   3   0  56   1   2]
- [  4   0   3   1   1  43   3]
- [ 11   3  17  14   9  17  54]]
-Node Classification on random seed  3649 -> 0.623
-Confusion Matrix:
- [[ 85   3   2   4   2  13   1]
- [  4 118   6   1   4   3   3]
- [ 19  25 123  39  31  20  42]
- [ 15   2  10 110   7   6   8]
- [  1   8   1   6  62   3   2]
- [  9   2   2   0   2  53   2]
- [ 16   4   5   8   9  27  72]]
-Node Classification on random seed  3650 -> 0.605
-Confusion Matrix:
- [[ 71   1   8   8   9   9  12]
- [  2 119   7   5  11   1   8]
- [ 19  25 134  30  37  29  28]
- [ 11   1  16 110   6   7  16]
- [  2   4   4   4  52   1   2]
- [  2   0   1   3   1  53   3]
- [  7   3  13  10  14  15  66]]
-Node Classification on random seed  3651 -> 0.62
-Confusion Matrix:
- [[ 78   1   3  11   3   7  21]
- [  6 127   9   1   2   3   6]
- [ 24  17 160  35  19  23  28]
- [  9   5  17  94   6   5  15]
- [  2   7   6   2  54   1   2]
- [ 13   2   3   3   0  43   5]
- [ 22   5  12   6   3  10  64]]
-Node Classification on random seed  3652 -> 0.625
-Confusion Matrix:
- [[ 74   2   6   1   6  11  15]
- [  5 138   3   2   3   6   5]
- [ 18  26 114  49  24  16  47]
- [ 12   2   5 124   7   7   6]
- [  1   8   3   1  61   3   4]
- [  8   0   3   2   0  52   0]
- [  6   3  11  13   4  21  62]]
-Node Classification on random seed  3653 -> 0.59
-Confusion Matrix:
- [[ 58   4   4   5   1  11  15]
- [  5 115   3   6   5   2   5]
- [ 28  32 134  42  17  23  42]
- [  8   3  17 106   2   4  15]
- [  3   8   6   5  51   0   4]
- [ 13   7   1   3   4  36   8]
- [ 19   2  11   6   4   7  90]]
-Node Classification on random seed  3654 -> 0.593
-Confusion Matrix:
- [[ 55   2   3  10   1  16  12]
- [  2 156   3   2   6   4   3]
- [ 33  32 136  49  22  11  45]
- [ 19   6  10  93   5   2  15]
- [  3   8   3   4  58   2   1]
- [  5   0   0   5   0  38   4]
- [ 10   5  10  10   7  17  57]]
-Node Classification on random seed  3655 -> 0.615
-Confusion Matrix:
- [[ 69   3   7   2   2  10   8]
- [  3 117   6   4   4   3   2]
- [ 20  28 161  34  25  22  40]
- [ 25   3  12  79   7   9  15]
- [  2  10   3   2  55   0   1]
- [  4   5   3   4   0  54   7]
- [  5   3  13   9   6  14  80]]
-Node Classification on random seed  3656 -> 0.597
-Confusion Matrix:
- [[ 67   2  14  11   3   6   5]
- [  6 119  11   3   7   1   2]
- [ 21  35 129  43  40  15  37]
- [ 16   4  13 106   5   2  16]
- [  3   6   5   1  61   1   1]
- [ 11   1   4   1   1  47   1]
- [ 17   4   4   8   7   9  68]]
-Node Classification on random seed  3657 -> 0.601
-Confusion Matrix:
- [[ 75   4   4   6   4  10   7]
- [  5 125   7   0  10   5   4]
- [ 24  51 132  32  19  22  43]
- [ 15   6  19  92   3   7  10]
- [  1  10   5   3  60   0   1]
- [  3   1   3   5   1  45   2]
- [ 13   2   8   8   2  14  72]]
-Node Classification on random seed  3658 -> 0.64
-Confusion Matrix:
- [[ 83   6   6   6   4   7   7]
- [  3 123   2   3  10   0  10]
- [ 25  15 148  28  36  26  25]
- [  5   3  17 109   3   5  10]
- [  2  14   2   5  57   0   2]
- [  3   1   3   1   0  40   7]
- [ 14   8  11   4  12   9  80]]
-Node Classification on random seed  3659 -> 0.585
-Confusion Matrix:
- [[ 64   5   1   9   4  13  15]
- [ 12 133   7   1   5   3   4]
- [ 23  25 135  26  16  30  58]
- [ 12   3  14 101   6   8  12]
- [  0   6   3   1  51   4   0]
- [ 16   1   1   3   1  24  15]
- [ 10   2   9  13   3  15  77]]
-Node Classification on random seed  3660 -> 0.601
-Confusion Matrix:
- [[ 76   0  10   7   7   8   4]
- [  5 139   5   5   8   5   3]
- [ 20  37 121  46  36  21  31]
- [ 12   8   8 100   9   3   9]
- [  1   7   2   1  62   0   1]
- [  9   5   1   3   2  47   3]
- [ 12   7  10   2  10  16  56]]
-Node Classification on random seed  3661 -> 0.628
-Confusion Matrix:
- [[ 77   1   3   5   6   9   6]
- [  3 147   5   3   9   1   2]
- [ 23  20 132  48  31  27  43]
- [ 15   6  17 111   3   4   8]
- [  2   6   1   2  55   2   2]
- [  6   1   4   0   0  45   1]
- [ 17   1   6   7   5  11  61]]
-Node Classification on random seed  3662 -> 0.61
-Confusion Matrix:
- [[ 61   2   2   3   0  23   8]
- [  5 146   5   4   3   1   3]
- [ 29  24 133  20  23  41  32]
- [ 12   7  18 102  13   3  11]
- [  0   6   5   2  47   2   2]
- [  5   1   8   5   0  47   3]
- [ 17   5   4  10   4  19  74]]
-Node Classification on random seed  3663 -> 0.606
-Confusion Matrix:
- [[ 57   1  11   3   4   9  19]
- [  1 132   4   0   7   3   7]
- [  9  22 129  22  58  20  51]
- [  7   7  14 110  10   8  18]
- [  3   7   3   1  59   2   3]
- [  2   1   0   2   0  35   6]
- [ 10   3  10   3   9  14  84]]
-Node Classification on random seed  3664 -> 0.608
-Confusion Matrix:
- [[ 76   9   3   6   3   6   4]
- [  5 123   7   4  15   2   0]
- [ 31  29 146  32  21  29  19]
- [ 29   4  19  90   2   1   4]
- [  0   7   9   4  54   1   2]
- [  9   2   0   1   0  42   6]
- [ 20   4  17   6   7  13  77]]
-Node Classification on random seed  3665 -> 0.557
-Confusion Matrix:
- [[ 64   2   3   8   3   9   9]
- [ 12 118   7   8   7   0   7]
- [ 22  27 108  49  38  46  41]
- [ 17   4   5 109   2  11  13]
- [  2   5   5   0  49   0   3]
- [  6   3   1   0   1  42   7]
- [ 13   4   5  14   8  16  67]]
-Node Classification on random seed  3666 -> 0.615
-Confusion Matrix:
- [[ 63   0  12   2  12   9   6]
- [  3 129   4   5   4  10   3]
- [ 10  20 165  31  31  21  47]
- [ 28   2  12  90   6   8  16]
- [  1   5   1   6  49   1  10]
- [  9   2   5   1   1  39   4]
- [  7   1  13   5   5   6  80]]
-Node Classification on random seed  3667 -> 0.66
-Confusion Matrix:
- [[ 70   7  14   3   4   7   8]
- [  4 133   7   4   4   3   5]
- [ 32  15 159  21  30   9  32]
- [ 17   1   9 118   3   3  14]
- [  2   4   5   1  56   1   2]
- [  5   2   3   1   0  41   6]
- [ 11   1  13   5   7  15  83]]
-Node Classification on random seed  3668 -> 0.57
-Confusion Matrix:
- [[ 71   7   2   3   6  14   4]
- [  7 133  11   1  12   2   4]
- [ 24  24 109  43  41  24  37]
- [ 15   4  19  86   7   8   5]
- [  3   7   2   1  67   0   1]
- [ 12   2   2   3   0  42   3]
- [ 15  10  13  10   6  16  62]]
-Node Classification on random seed  3669 -> 0.603
-Confusion Matrix:
- [[ 77   3   3   3   5  21   9]
- [  3 134   3   2  13   2   7]
- [ 21  28 127  43  27  40  21]
- [  3   1  16  92  11   7  14]
- [  5   4   1   1  56   1   3]
- [  3   1   1   1   1  36  13]
- [  9   5   8   5  11  18  81]]
-Node Classification on random seed  3670 -> 0.652
-Confusion Matrix:
- [[ 66   1   4   4   3   9  10]
- [  2 140   7   3   3   5   4]
- [ 22  20 147  34  32  33  32]
- [  7   3  12 119   2   9  13]
- [  1  10   1   3  59   1   2]
- [  4   2   0   0   1  45   8]
- [  5   3   1   8   8  16  76]]
-Node Classification on random seed  3671 -> 0.652
-Confusion Matrix:
- [[ 61   2   5   1   3  19  19]
- [  3 123   6   3   7  10   3]
- [ 15  26 156  29  17  22  35]
- [ 11   7  11 112   3   6   7]
- [  1   6   3   2  64   0   3]
- [  0   3   1   3   0  55   6]
- [  3   1  15   7   6  18  81]]
-Node Classification on random seed  3672 -> 0.603
-Confusion Matrix:
- [[ 52   5   2   8   4   9  24]
- [  5 128   3   0  21   1   2]
- [ 16  14 147  21  46  15  36]
- [ 12   3  13 103   5   9  19]
- [  0   8   4   1  59   2   0]
- [  7   1   0   2   3  51   9]
- [ 12   3  10   5  27  10  63]]
-Node Classification on random seed  3673 -> 0.647
-Confusion Matrix:
- [[ 88   3   1   2   5   7  13]
- [  1 131   5   1  11   2   4]
- [ 25  23 161  18  22  36  35]
- [ 10   6  22  87  11   6   7]
- [  0   5   5   0  55   0   0]
- [  2   1   7   0   0  50   2]
- [ 10   3   7   8  12  15  75]]
-Node Classification on random seed  3674 -> 0.609
-Confusion Matrix:
- [[ 79   3   9   4   1   6  20]
- [  5 128   5   1   7   7   0]
- [ 17  30 120  52  26  20  41]
- [ 24   3   5  91  11   2  10]
- [  5   6   3   3  60   1   0]
- [ 14   1   1   2   3  34   5]
- [ 10   4   4   4   4  12  97]]
-Node Classification on random seed  3675 -> 0.611
-Confusion Matrix:
- [[ 63   2   1   3   3  16  12]
- [  6 127   7   0   1   2   7]
- [ 23  22 147  40  15  29  25]
- [ 20   8  15 106   1   9  14]
- [  0  11   5   7  54   1   2]
- [  3   0   1   1   0  53   8]
- [ 14   7   4   5   5  34  61]]
-Node Classification on random seed  3676 -> 0.593
-Confusion Matrix:
- [[ 71   7   4   6   8   7   6]
- [  5 130   5   1   6   3   2]
- [ 26  11 129  65  32  24  28]
- [ 23  12  12  83   6   5  17]
- [  1   6   4   0  62   0   0]
- [ 10   2   2   2   6  36   7]
- [ 11   6   4   7  10   8  82]]
-Node Classification on random seed  3677 -> 0.632
-Confusion Matrix:
- [[ 71   8   0   6   1  11  14]
- [  4 137   9   0   3   1   7]
- [ 20  23 133  49  12  13  54]
- [ 14   4  14 115   7   3   5]
- [  0   8   3   3  63   0   3]
- [  5   0   1   6   2  33   4]
- [  9   3   7  11  10  11  80]]
-Node Classification on random seed  3678 -> 0.612
-Confusion Matrix:
- [[ 61   8   2   9   4  13   2]
- [  1 127   3   8   0   6   8]
- [ 13  41 146  40  30  23  42]
- [  8   9  13 125   4   3   2]
- [  0   4   8   1  43   1   6]
- [  4   5   0   4   0  46   5]
- [  6   7   8  12   6  19  64]]
-Node Classification on random seed  3679 -> 0.598
-Confusion Matrix:
- [[ 64   0   6   7   0  16   7]
- [  3 121   5   8   3   0   6]
- [ 23  29 148  26  26  32  39]
- [ 13   3  26  95   6  10  15]
- [  1  10   3   1  53   2   4]
- [  8   2   0   3   8  39   5]
- [ 10   3  10   8   6   9  78]]
-Node Classification on random seed  3680 -> 0.577
-Confusion Matrix:
- [[ 60   2   7  12   3   8   6]
- [  4 118   2   3  12   3   2]
- [ 27  17 143  42  39  28  37]
- [ 12  10  20 103   5   7  11]
- [  6   5   8   0  54   0   2]
- [  6   2   2   3   0  44   3]
- [ 16   5   8  10  14  14  55]]
-Node Classification on random seed  3681 -> 0.577
-Confusion Matrix:
- [[ 62   5   9   0   5  12  17]
- [  4 121   9   1  10   4   0]
- [ 14  22 140  47  42  28  28]
- [ 17   7  18  77   4   9  24]
- [  1   3   3   1  62   1   1]
- [ 11   0   3   1   0  47   3]
- [ 11   6   4  19   9  10  68]]
-Node Classification on random seed  3682 -> 0.59
-Confusion Matrix:
- [[ 58   0   4   7   8  18   7]
- [  2 138  11  10   4   0   1]
- [ 48  20 122  30  21  29  48]
- [  7   1  12 104   7   8  11]
- [  0  11   3   3  52   0   5]
- [  5   2   4   5   0  38   5]
- [  5   5  17  10   3  13  78]]
-Node Classification on random seed  3683 -> 0.611
-Confusion Matrix:
- [[ 49   1   6  13   1  16  18]
- [  1 148  11   1  10   1   3]
- [ 25  23 138  57  17  29  28]
- [  6   3  10 104   8   8  13]
- [  4   4   5   3  56   0   2]
- [  0   0   2   0   3  44   6]
- [  6   5   6   9  10  15  72]]
-Node Classification on random seed  3684 -> 0.637
-Confusion Matrix:
- [[ 67   7   2   3   6  11  10]
- [  5 121   5   4  14   0   7]
- [ 25  23 151  39  22  16  38]
- [ 13   3  28 103   4   5   7]
- [  0   3   2   3  70   0   4]
- [  6   2   0   0   0  48   5]
- [ 12   2   8   3   7   9  77]]
-Node Classification on random seed  3685 -> 0.594
-Confusion Matrix:
- [[ 59   2   1   8   5  21   6]
- [  3 135  11   5   5   4   3]
- [ 24  34 139  45  30  21  32]
- [ 18  10  16  94   8   9   8]
- [  1   8   4   4  62   1   1]
- [  4   1   1   2   0  29   6]
- [  6   4   6   6   9  13  76]]
-Node Classification on random seed  3686 -> 0.624
-Confusion Matrix:
- [[ 73   3   3   3   2  10  15]
- [  4 130  11   2   7   3   3]
- [ 30  13 146  28  16  17  55]
- [ 19   1  13 103   3   8  15]
- [  3  11   4   1  59   5   1]
- [  9   0   0   5   0  38  14]
- [ 21   4   5   1   3   5  75]]
-Node Classification on random seed  3687 -> 0.628
-Confusion Matrix:
- [[ 65   3  20   6   3  12   6]
- [  4 134   5   0   3   1   4]
- [ 20  20 148  37  24  14  49]
- [ 13   1  11 114   9   5  15]
- [  0  12   1   2  51   0   2]
- [  5   1   5   0   3  47   2]
- [  9   2  21   6   3  13  69]]
-Node Classification on random seed  3688 -> 0.62
-Confusion Matrix:
- [[ 76   1   8   3   4  11   7]
- [  4 130   6   5   9   4   2]
- [ 21  14 131  53  36  26  24]
- [  2   2  26 112   7   6  12]
- [  2   5   5   1  59   0   1]
- [  4   1   2   5   0  44   2]
- [  7   0  17  12   7  16  68]]
-Node Classification on random seed  3689 -> 0.6
-Confusion Matrix:
- [[ 61   4  10  10   5   6  17]
- [  7 128   6   2   5   0   5]
- [ 16  23 157  20  30  23  48]
- [ 15   2  25  91   5   6  10]
- [  7   1   5   3  43   1   0]
- [  7   3   3   5   0  37  12]
- [ 13   1   8   8  10  13  83]]
-Node Classification on random seed  3690 -> 0.636
-Confusion Matrix:
- [[ 79   2   4   9   1  11  11]
- [  3 133   3   2   7   3   2]
- [ 15  25 131  40  32  23  37]
- [  5   3   7 116   8   9   7]
- [  2   6   7   2  56   4   0]
- [  6   0   5   2   0  54   1]
- [  3   3  14   9  18  13  67]]
-Node Classification on random seed  3691 -> 0.625
-Confusion Matrix:
- [[ 81   3   3   6   1   3   7]
- [  3 125  11   3  11   7   4]
- [ 23  21 133  49  34  30  25]
- [  6   5  19 104   3   2  12]
- [  2   7   0   3  58   2   2]
- [  6   4   1   1   2  47   6]
- [ 14   3   8   9   2  12  77]]
-Node Classification on random seed  3692 -> 0.645
-Confusion Matrix:
- [[ 80   3   2   6   5  11   7]
- [  0 119   6   5   5   2  10]
- [ 24  14 180  25  12  18  43]
- [ 14   5  16  98  19   5   7]
- [  0  13   4   2  51   1   2]
- [  4   1   1   3   1  43   8]
- [ 12   6   3   5  13  12  74]]
-Node Classification on random seed  3693 -> 0.6
-Confusion Matrix:
- [[ 70   3   8   9   1  12  13]
- [  4 121   6   6   7   3   5]
- [ 24  25 114  50  20  21  37]
- [ 14   8   9 109   1  12   4]
- [  1   6   5   2  57   0   5]
- [  5   2   2   3   0  51   8]
- [ 19   6   6  10   7  11  78]]
-Node Classification on random seed  3694 -> 0.626
-Confusion Matrix:
- [[ 68   2   7   4  11  12  12]
- [  3 140   5   3   8   0   2]
- [ 21  13 132  28  20  18  49]
- [ 23   2   7 107   1   5  19]
- [  1   9   3   5  62   2   1]
- [  9   0   3   2   0  42   8]
- [ 11   5   4   6  16  14  75]]
-Node Classification on random seed  3695 -> 0.608
-Confusion Matrix:
- [[ 63   3   3   5   2  18  12]
- [  7 132   4   5  11   5   0]
- [ 33  22 146  30  26  30  25]
- [ 16   3  10 115   5   5   3]
- [  6   3   5   2  55   2   7]
- [  8   3   3   1   5  35   2]
- [ 12   6   5  10   3  26  62]]
-Node Classification on random seed  3696 -> 0.587
-Confusion Matrix:
- [[ 74   3   4  11   5   8  12]
- [  6 129   3   8   2   3   3]
- [ 36  27 133  33  26  31  26]
- [  9   5  23  92   6  11   7]
- [  1  10   5   0  55   1   5]
- [ 11   2   2   1   0  41   7]
- [  9   3  10   5   9  24  63]]
-Node Classification on random seed  3697 -> 0.636
-Confusion Matrix:
- [[ 73   3   0   6   3  13  20]
- [  4 135   3   2   4   3   4]
- [ 26  25 178  25  19   8  40]
- [  3   5  28  88   8   2   7]
- [  0   8   5   3  53   1   3]
- [  9   0   1   1   4  43   6]
- [ 16   4   1  16   5  20  66]]
-Node Classification on random seed  3698 -> 0.567
-Confusion Matrix:
- [[ 44   2  10   5   5  16  12]
- [  5 121   7   6   9   3   3]
- [ 25  25 148  48  23  30  33]
- [ 26   6  20  86   7   8  10]
- [  1   3   7   1  60   0   3]
- [ 13   1   2   2   0  38   5]
- [ 20   3   3   8   6  11  70]]
-Node Classification on random seed  3699 -> 0.579
-Confusion Matrix:
- [[ 69   6   4   6   0  10  15]
- [  6 108  17   1  15   3   6]
- [ 36  13 128  44  28  23  34]
- [ 18   7  18  97   2  12   3]
- [  0   5   2   0  56   0   0]
- [  6   2   4   2   3  47   3]
- [  6   5  13  17   8  18  74]]
-Node Classification on random seed  3700 -> 0.621
-Confusion Matrix:
- [[ 66   6   5   2   7  13   8]
- [  1 130   4   1   5   3   7]
- [ 12  36 145  43  28  27  34]
- [ 10   1  14  95   8   6   8]
- [  0   5   5   5  57   1   4]
- [  2   1   1   1   1  48   6]
- [  6   3  14   5   8  22  80]]
-Node Classification on random seed  3701 -> 0.622
-Confusion Matrix:
- [[ 70   4   1  11   4  20   8]
- [ 20 114  13   1  15   2   2]
- [ 48   7 161  23  23   7  30]
- [ 13   2  14 123   5   4   9]
- [  3   0   3   0  70   0   1]
- [ 17   5   1   3   2  30   5]
- [ 30   2   6   3   4   7  54]]
-Node Classification on random seed  3702 -> 0.612
-Confusion Matrix:
- [[ 65   1   3   7   3  13  14]
- [  7 131   7   4  10   2   5]
- [ 21  21 120  47  29  32  24]
- [ 18   5  10 112   6  11  16]
- [  1   5   1   6  58   0   4]
- [  3   2   0   1   1  42   4]
- [  3   4  12  13   5   7  84]]
-Node Classification on random seed  3703 -> 0.598
-Confusion Matrix:
- [[ 67   2   4   6   5  19  10]
- [  4 142   2   3  18   4   6]
- [ 31  10 107  30  37  43  33]
- [ 10   0  17  87   7   9  14]
- [  0   1   1   1  73   0   2]
- [  4   0   6   1   0  37   5]
- [ 12   3   9   4  18  11  85]]
-Node Classification on random seed  3704 -> 0.614
-Confusion Matrix:
- [[ 73   1   7   2   2   8  20]
- [  8 136   9   7   5   2   5]
- [ 33  24 126  34  21  13  37]
- [ 15  10  12 100   3   5  13]
- [  4  12   1   2  52   1   6]
- [  6   0   4   1   0  36   5]
- [ 10   2   9   6   5  16  91]]
-Node Classification on random seed  3705 -> 0.621
-Confusion Matrix:
- [[ 64   3  10   3   4  17  12]
- [  1 120   2   4   8   1   4]
- [ 20  12 171  29  18  24  37]
- [  5   2  17 108   4   5  23]
- [  2   3   5   4  47   0   3]
- [  5   0   6   4   0  43   4]
- [ 13   2  17  11   7  28  68]]
-Node Classification on random seed  3706 -> 0.6
-Confusion Matrix:
- [[ 70   0   7   5   7  11   7]
- [  3 133   9   2  13   8   3]
- [ 40  29 134  46  14  23  36]
- [  3   2  11  95   8   2  15]
- [  2   4   4   0  60   0   1]
- [ 10   0   4   5   0  39   4]
- [ 18   1  22   7   4  10  69]]
-Node Classification on random seed  3707 -> 0.66
-Confusion Matrix:
- [[ 75   1   2   7   2   7   7]
- [  4 127   5   0  10   5  14]
- [ 13  16 167  29  27  24  38]
- [ 11   8  15 101  10   2  14]
- [  2   3   5   1  63   1   2]
- [  8   0   4   1   0  46   1]
- [ 11   2  16   2   4   6  81]]
-Node Classification on random seed  3708 -> 0.609
-Confusion Matrix:
- [[ 72   4   3   9   1  12   2]
- [  7 134   6  12   8   5   6]
- [ 22   7 134  42  40  21  36]
- [ 13   4  18 101   1   5  10]
- [  1   5   0   3  53   2   2]
- [ 14   4   2   0   0  38   7]
- [ 13   1  12  12   7  12  77]]
-Node Classification on random seed  3709 -> 0.593
-Confusion Matrix:
- [[ 54  10   4   3  15  15   8]
- [  4 122   2   4   7   0   5]
- [ 21  38 147  26  36  19  28]
- [ 12   8  14  95  10   6  18]
- [  1   9   3   0  64   0   3]
- [  8   1   3   0   2  34  13]
- [ 10   3   9   6   6  17  77]]
-Node Classification on random seed  3710 -> 0.639
-Confusion Matrix:
- [[ 70   3   4   6   1   6  15]
- [  4 136   3   0  12   1   7]
- [ 19  26 163  23  17  22  48]
- [  7   9  14 102   6   2   7]
- [  0   3   7   3  54   0   3]
- [  6   4   0   0   2  37   3]
- [ 12   7  20   5   8  16  77]]
-Node Classification on random seed  3711 -> 0.595
-Confusion Matrix:
- [[ 64   1   9   4   1   8   8]
- [  6 128   5   5   7   1   6]
- [ 36  13 136  48  29  23  44]
- [  4   2  16  96   8  13  11]
- [  0   8   3   3  62   0   3]
- [  5   2   5   2   0  38   4]
- [ 21   3   4  14   5  15  71]]
-Node Classification on random seed  3712 -> 0.626
-Confusion Matrix:
- [[ 77   2   8   2   4   9  11]
- [  2 117  19   1   6   2   2]
- [ 25  18 151  23  26  26  37]
- [  8   4  17 102   3  10  16]
- [  2   3   3   3  73   1   2]
- [  1   2   4   1   2  42   3]
- [ 21   2  10   2  10  21  64]]
-Node Classification on random seed  3713 -> 0.589
-Confusion Matrix:
- [[ 49   7   2   1   8   8  14]
- [  4 139   3   4   9   5   7]
- [ 32  21 115  44  13  26  46]
- [  9   3  15 119  11   4  19]
- [  2  12   1   1  51   4   3]
- [  4   6   2   1   0  43   6]
- [ 12   2   8   0   9  23  73]]
-Node Classification on random seed  3714 -> 0.59
-Confusion Matrix:
- [[ 73   3   4   7   5  17  17]
- [  0 137   8   1  10   0   1]
- [ 32  37 125  28  31  42  32]
- [ 10   7  16  98   4   7   8]
- [  0   6   4   1  60   0   1]
- [  9   2   4   8   0  33   4]
- [  3   4  11  11   1  14  64]]
-Node Classification on random seed  3715 -> 0.609
-Confusion Matrix:
- [[ 66   2   7   7   2   9   8]
- [  2 130  12   5   9   2   9]
- [ 26  16 146  47  35  27  23]
- [ 13   7  10  84  16   6  18]
- [  0   5   4   3  61   0   2]
- [  5   3   1   1   0  49   9]
- [  5   3   7   4   9  12  73]]
-Node Classification on random seed  3716 -> 0.557
-Confusion Matrix:
- [[ 71   3   4   8   3   6   8]
- [  7 134   5   2  11   3   3]
- [ 19  18 123  38  39  31  43]
- [ 35   2  19  77   8  16   6]
- [  2   6   3   0  53   1   4]
- [ 13   2   4   2   7  36   1]
- [ 16   0  18   7   5  15  63]]
-Node Classification on random seed  3717 -> 0.595
-Confusion Matrix:
- [[ 68   2   2  10  10   9  14]
- [  6 127  15   1   7   1   3]
- [ 10  21 130  38  16  41  48]
- [ 14   6  23  91   6  11  15]
- [  1  12   1   0  65   1   0]
- [  8   2   0   2   0  37   2]
- [ 16   5   2  11   4   9  77]]
-Node Classification on random seed  3718 -> 0.619
-Confusion Matrix:
- [[ 66   3   2   5   4  14  18]
- [  5 138   4   6   7   1   5]
- [ 21  19 149  39  22  18  41]
- [ 13   4  19  81   6   6  13]
- [  0  13   2   1  53   0   2]
- [  4   2   6   1   0  47   6]
- [  8   6   8   7   5  15  85]]
-Node Classification on random seed  3719 -> 0.636
-Confusion Matrix:
- [[ 74   2   3   3   0  25  15]
- [  5 124   9   3  11   1   4]
- [ 23  14 161  30  30  21  35]
- [  8   1  13 117   4  11  13]
- [  4   7   1   4  47   1   4]
- [  0   2   5   1   1  52   0]
- [ 16   2   6   9   6  11  61]]
-Node Classification on random seed  3720 -> 0.579
-Confusion Matrix:
- [[ 59   3   9   2   5  15  11]
- [  3 109   2   9   8   2  10]
- [ 30  15 137  45  34  16  48]
- [ 15   2  15  87   7   8  23]
- [  1   2   4   3  65   2   0]
- [ 11   1   2   1   0  46   4]
- [  9   4  16   7   6  11  76]]
-Node Classification on random seed  3721 -> 0.616
-Confusion Matrix:
- [[ 82   2   4   7   1   4  14]
- [  5 135   6   2   3   1   4]
- [ 27  26 119  62  31   8  34]
- [  6   5   7 119   5   6   9]
- [  3   7   2   3  55   0   6]
- [  8   3   1   1   0  40   7]
- [ 14   3  10  15  11  11  66]]
-Node Classification on random seed  3722 -> 0.605
-Confusion Matrix:
- [[ 78   1   5   6   4  15  12]
- [  3 121   9   6  10   1   4]
- [ 22  18 133  48  31   8  50]
- [ 13   3   7 100   8  13  22]
- [  2   4   2   2  65   0   3]
- [  8   2   0   0   1  40   8]
- [  6   5   9   4   5  15  68]]
-Node Classification on random seed  3723 -> 0.608
-Confusion Matrix:
- [[ 66   1   1   9   6   9  20]
- [  3 112   3   5  17   1   2]
- [ 22  25 163  27  42  19  36]
- [  7   4  18 100   4   2   9]
- [  0   7   2   1  63   0   3]
- [ 17   1   4   3   1  29   4]
- [ 14   4   9   4   5  21  75]]
-Node Classification on random seed  3724 -> 0.612
-Confusion Matrix:
- [[ 77   3   2   1   2  12   2]
- [  6 126   3   3  14   1   2]
- [ 27  37 123  21  35  29  40]
- [  4  10  11 112   4  11  10]
- [  2   7   2   3  67   3   2]
- [  9   2   3   0   0  40   2]
- [ 17   3   4   8  17  14  67]]
-Node Classification on random seed  3725 -> 0.569
-Confusion Matrix:
- [[ 66   2   2  11   5  14  16]
- [  5 126   7  12   2   2   4]
- [ 19  28 138  42  18  23  43]
- [ 15   6  29  78  10  12  12]
- [  2   8   4   2  56   0   3]
- [  4   3   1   0   1  46   6]
- [  4   9   9  13   4  19  59]]
-Node Classification on random seed  3726 -> 0.625
-Confusion Matrix:
- [[ 57   5   9   2   1  12   9]
- [  7 119   7   3   8   2   9]
- [ 26  21 159  21  25  26  32]
- [ 11   8  22  97   6  14   9]
- [  0   6   5   4  53   0   2]
- [  8   1   1   0   0  41  12]
- [ 14   3   3   2   6  13  99]]
-Node Classification on random seed  3727 -> 0.616
-Confusion Matrix:
- [[ 79   5  11   3   3   7  12]
- [  2 124   6   0   4   7   9]
- [ 24  30 116  36  23  14  51]
- [ 10   6   4 121   6  10  14]
- [  0  11   3   3  52   0   1]
- [  3   2   3   0   0  49   5]
- [  9   4  15   6  10  12  75]]
-Node Classification on random seed  3728 -> 0.612
-Confusion Matrix:
- [[ 63   3   4   9   2   9   3]
- [  2 133   7   2   7   3   4]
- [ 35  15 116  33  35  31  34]
- [ 10   6  23 129   2   5  12]
- [  1   5   3   5  57   1   2]
- [  5   0   2   2   0  39  10]
- [ 12   2   6  11   6  19  75]]
-Node Classification on random seed  3729 -> 0.567
-Confusion Matrix:
- [[ 61   1   2   2   6   5  20]
- [  2 117   8   2  10   5   8]
- [ 24  19 120  36  44  18  56]
- [ 17   3   9 101  11   3  17]
- [  0   5   2   3  67   1   3]
- [  9   1   2   1   0  37   8]
- [ 19   6  17   3   6  19  64]]
-Node Classification on random seed  3730 -> 0.619
-Confusion Matrix:
- [[ 66   1  10   1   5  20   8]
- [  5 130   4   1   8   4   3]
- [ 22  16 154  29  25  15  46]
- [ 12   4  34  88   3   8  17]
- [  2   3   5   0  58   4   2]
- [  3   1   1   2   0  47   5]
- [ 18   4   6   3   5  16  76]]
-Node Classification on random seed  3731 -> 0.659
-Confusion Matrix:
- [[ 67   8   4   9   6   7  14]
- [  2 136   7   1  16   1   6]
- [ 13  18 153  44  24  20  29]
- [  2   6  12 123   3   5   9]
- [  2   3   4   2  57   1   1]
- [  4   1   0   2   0  43   4]
- [ 10   4  10   3   8  16  80]]
-Node Classification on random seed  3732 -> 0.633
-Confusion Matrix:
- [[ 57   3   3   7   9  18   8]
- [  7 108   2   2  17   2   9]
- [ 16  17 175  24  16  21  47]
- [ 11   1  20 101   7   4  10]
- [  1   7   5   2  59   1   1]
- [  6   1   1   1   1  51   5]
- [ 12   2   3   6   7  24  82]]
-Node Classification on random seed  3733 -> 0.615
-Confusion Matrix:
- [[ 57   8  11   4   2  12   5]
- [  4 121   3   7   5   3   6]
- [ 28  21 131  28  36  26  45]
- [  3   3  14 117  11   3  10]
- [  0   7   2   2  61   1   5]
- [  7   0   2   0   0  47   4]
- [ 12   5  10   8   5  17  81]]
-Node Classification on random seed  3734 -> 0.637
-Confusion Matrix:
- [[ 56   1   4   2   1  16  17]
- [  1 141  12   6   2   2   5]
- [ 17  14 169  29  23  13  42]
- [ 16  14  20  91   2   5  14]
- [  1  14   1   2  71   0   1]
- [  6   3   3   2   2  43   3]
- [  7   6   9   4   8  13  66]]
-Node Classification on random seed  3735 -> 0.612
-Confusion Matrix:
- [[ 65   4   7   5   8  10  18]
- [  7 127   3   6   7   0   6]
- [ 11  13 125  55  31  31  51]
- [ 11   1  12 109   4   6   8]
- [  2   6   3   0  66   2   3]
- [ 11   1   3   1   4  45   4]
- [  8   1   6   2   7   9  75]]
-Node Classification on random seed  3736 -> 0.609
-Confusion Matrix:
- [[ 62   4   5   6   4  14  22]
- [  3 135   7   4  10   7   1]
- [ 29  19 135  31  32  23  52]
- [ 10   4  11 112   3   6  10]
- [  0   7   1   1  59   1   1]
- [  3   1   3   0   3  49   9]
- [  8   2   8   5   5  16  57]]
-Node Classification on random seed  3737 -> 0.6
-Confusion Matrix:
- [[ 74   2   4   5   2  15  17]
- [  6 121  10   1   2   1  10]
- [ 37  29 124  37  35  25  29]
- [  7   6   6 103   2  16   7]
- [  0   2   5   2  67   0   8]
- [  3   4   1   3   1  38   8]
- [  9   3   8   8   9  15  73]]
-Node Classification on random seed  3738 -> 0.599
-Confusion Matrix:
- [[ 47   8  14   3   4  19   9]
- [  5 129   8   1   9   0   4]
- [ 17  24 132  33  54  13  39]
- [ 15   6   9 109   5   4  15]
- [  2   5   7   3  53   0   3]
- [  5   1  10   0   1  44   1]
- [  7   5   7   7   9  10  85]]
-Node Classification on random seed  3739 -> 0.61
-Confusion Matrix:
- [[ 70   2  13   4   5  13  14]
- [  7 126  10   4   2   1   3]
- [ 21  16 145  40  31  26  46]
- [  9   3  11  92   6   7  14]
- [  3   5   3   0  62   0   3]
- [ 14   2   2   0   0  40   7]
- [ 17   2   3   6   5  10  75]]
-Node Classification on random seed  3740 -> 0.637
-Confusion Matrix:
- [[ 87   1   5   2   3  13   8]
- [  9 139   2   1   4   3   3]
- [ 16  22 118  50  21  37  33]
- [ 16   3  12 100   2  10   8]
- [  2   8   3   2  65   0   3]
- [  7   0   0   3   0  40   8]
- [  7   3   7   6   5  15  88]]
-Node Classification on random seed  3741 -> 0.604
-Confusion Matrix:
- [[ 62   4   2  20   4   6  10]
- [  3 133   5   3   8   5   5]
- [ 15  17 145  31  50  21  30]
- [  3   6  13 106  12  12  11]
- [  1   6   4   1  48   1   3]
- [  2   2   3   4   2  39  11]
- [ 10   7  11   8   8  16  71]]
-Node Classification on random seed  3742 -> 0.589
-Confusion Matrix:
- [[ 71   4   2   2   4  13  18]
- [  5 101   0   2  24   0   5]
- [ 26  19 135  43  25  26  41]
- [ 10   7  11  99   5   5  10]
- [  0   5   1   2  68   0   8]
- [  5   1   4   0   0  48   5]
- [ 11   6   9  19  10  18  67]]
-Node Classification on random seed  3743 -> 0.629
-Confusion Matrix:
- [[ 70   5   0  13   7  10   9]
- [  2 125   6   5  14   3   0]
- [ 31  14 135  30  20  16  64]
- [  7   2   7 115   8   7  16]
- [  2   7   0   0  67   0   4]
- [ 10   3   5   0   4  39   1]
- [  9   6   0   4  12   8  78]]
-Node Classification on random seed  3744 -> 0.584
-Confusion Matrix:
- [[ 67   2  10   3   1  13  17]
- [  4 131   5   0   4   1   2]
- [ 18  24 107  52  28  27  50]
- [ 23   3  12  96   5  11   9]
- [  2   7   2   4  57   0   0]
- [  3   1   4   1   0  44   4]
- [ 12   3   7  19  12  11  82]]
-Node Classification on random seed  3745 -> 0.633
-Confusion Matrix:
- [[ 74   0   0   7   6   6  10]
- [  6 101   7   2   8   0  11]
- [ 31  21 170  32  27  17  39]
- [  5   6  19 100   4   1  16]
- [  1   7   4   2  51   0   5]
- [  5   1   2   3   1  48   5]
- [ 12   6  10  12   5   5  89]]
-Node Classification on random seed  3746 -> 0.595
-Confusion Matrix:
- [[ 74   0  13   9   3  20   5]
- [  6 125   8   3   3   4   8]
- [ 14  19 148  22  21  29  47]
- [ 14   6  18  83   1   8  18]
- [  1   8   7   2  59   0   3]
- [  3   3   6   3   2  47   3]
- [  7   5  15  10   6  22  59]]
-Node Classification on random seed  3747 -> 0.599
-Confusion Matrix:
- [[ 74   3   4   1   5  15   6]
- [  2 124   2   2   7   6   7]
- [ 23  16 139  39  26  26  38]
- [ 18   1  19  83  10  11  13]
- [  1   7   3   1  68   1   3]
- [  6   1   2   2   5  38   5]
- [ 11   1   8  23   5  16  73]]
-Node Classification on random seed  3748 -> 0.616
-Confusion Matrix:
- [[ 59   0   5   3   3  17   1]
- [  7 110   4   5   8   4   8]
- [ 28  19 151  36  27  22  45]
- [ 12   5   7 120   5   7   9]
- [  4   2   1   2  65   0   5]
- [ 12   1   2   5   1  47   4]
- [ 15   2  10  12   7  12  64]]
-Node Classification on random seed  3749 -> 0.617
-Confusion Matrix:
- [[ 71   1   0  13   5   5   8]
- [  6 128  16   3   4   2   3]
- [ 32  27 163  27  17  10  47]
- [  8   7   7  97  11   7  10]
- [  0   6   6   0  57   1   2]
- [ 11   0   2   7   1  32  11]
- [ 12   6  12  10   3  17  69]]
-Node Classification on random seed  3750 -> 0.622
-Confusion Matrix:
- [[ 72   6   9   6   2   9   8]
- [ 10 119  12   3   6   0   0]
- [ 27  23 169  16  27  21  35]
- [ 16   6  24  85   2   6  14]
- [  4   7   1   0  67   1   3]
- [  9   1   3   7   1  33   3]
- [ 12   2  11  12  10   3  77]]
-Node Classification on random seed  3751 -> 0.612
-Confusion Matrix:
- [[ 85   4   1   5   7  16   0]
- [ 10 118   2   2   3   4   5]
- [ 31  30 126  37  18  25  33]
- [ 14  11  19 102   5   4  10]
- [  0   6   3   3  59   0   3]
- [ 11   2   0   1   1  42   7]
- [ 19   5   5  12   5   9  80]]
-Node Classification on random seed  3752 -> 0.631
-Confusion Matrix:
- [[ 75   1   7   8   6  15   8]
- [  1 134   5   1  11   0   1]
- [ 20  19 145  48  10  31  24]
- [ 21   5  12 104   3   9  12]
- [  0   9   7   1  56   0   0]
- [  9   1   3   2   0  44   4]
- [  9   5   5  10  10  16  73]]
-Node Classification on random seed  3753 -> 0.596
-Confusion Matrix:
- [[ 68   0   3   6   4  18   6]
- [  5 118   1   3  13   2   4]
- [ 21  31 162  23  32  19  57]
- [ 11   5  19  77  10   7  13]
- [  2   7   3   2  59   2   4]
- [  4   4   0   5   1  39   4]
- [ 14   4  10   7   4  14  73]]
-Node Classification on random seed  3754 -> 0.598
-Confusion Matrix:
- [[ 68   7   3  10   1   6  21]
- [  5 138   7   4   3   9   1]
- [ 30  24 138  37  24  18  38]
- [ 12   5  21  90   6   6  17]
- [  2   5   6   3  57   1   1]
- [  9   0   3   1   0  35   8]
- [ 15   5  11   8   2   7  72]]
-Node Classification on random seed  3755 -> 0.611
-Confusion Matrix:
- [[ 77   3   6   4   3   9  12]
- [  3 132   8   0  18   0   1]
- [ 25  12 129  25  42  14  51]
- [  8   4  25  91   6   1  16]
- [  1   1   7   1  68   1   4]
- [  4   1   6   0   1  36  11]
- [ 11   3  11   9  12   9  78]]
-Node Classification on random seed  3756 -> 0.593
-Confusion Matrix:
- [[ 73   1   7   5   8  15  10]
- [  3 128   3   4   2   5   8]
- [ 27  28 133  47  21  36  20]
- [ 14   4  17  97   5   6  12]
- [  2   6   3   3  54   3   5]
- [ 13   1   1   4   0  34   6]
- [ 14   3   4  12   5  14  74]]
-Node Classification on random seed  3757 -> 0.578
-Confusion Matrix:
- [[ 73   4   3   6   8   9   9]
- [  9 120   9   2   9   1   5]
- [ 26  40 108  67  14  37  30]
- [ 10   8  14 112   1   4  12]
- [  3   5   6   1  57   1   1]
- [ 10   1   0   1   1  41   4]
- [  9   7   4   5   7  19  67]]
-Node Classification on random seed  3758 -> 0.61
-Confusion Matrix:
- [[ 67   2   3   3   3  12  14]
- [  4 124   3   9  12   2   5]
- [ 25  33 120  41  18  29  35]
- [  9   2  11 118  10   1  15]
- [  0   5   5   4  60   0   0]
- [  8   0   3   8   0  42   6]
- [ 14   4   3  10   8  11  79]]
-Node Classification on random seed  3759 -> 0.577
-Confusion Matrix:
- [[ 59   3   2   7  11  14  10]
- [  2 110   5   2  13   0   7]
- [ 22  33 128  31  42  23  41]
- [ 15   2  15  98   2   6  16]
- [  0   2   1   4  68   4   4]
- [  6   2   2   0   3  37  12]
- [ 10   8   9  11  10  11  77]]
-Node Classification on random seed  3760 -> 0.606
-Confusion Matrix:
- [[ 79   1   2   8   3  11   7]
- [  3 124   3   3   5   4   2]
- [ 23  22 135  23  31  32  44]
- [ 32  11  17  89   8   4   7]
- [  0   9   2   0  57   3   4]
- [  3   0   2   3   0  41   8]
- [  3   3  11  18   6  13  81]]
-Node Classification on random seed  3761 -> 0.633
-Confusion Matrix:
- [[ 64   1   2   6   1  27  15]
- [  5 125   6   1   5   5   6]
- [ 26  17 149  27  31  21  36]
- [  8   3  18 109   6   4  14]
- [  1   7   3   1  62   1   3]
- [  6   2   0   1   0  50   6]
- [  9   3   9   2   6  16  74]]
-Node Classification on random seed  3762 -> 0.625
-Confusion Matrix:
- [[ 74   4   1   8   4  10   9]
- [  4 128   4   1   7   3   6]
- [ 25  35 149  33  19  17  28]
- [ 10   9  22  88   9   8  11]
- [  2   8   4   5  63   2   1]
- [  5   0   3   3   0  49   6]
- [ 17   5  12   5   2   8  74]]
-Node Classification on random seed  3763 -> 0.638
-Confusion Matrix:
- [[ 71   6   8   1   5  14   2]
- [  7 118   4   1  10   5   8]
- [ 38  16 142  30  20  15  45]
- [ 11   2   9 133   6   8   6]
- [  0   4   2   1  50   1   3]
- [ 12   0   4   0   4  47   4]
- [ 13   0  14  12   1  10  77]]
-Node Classification on random seed  3764 -> 0.582
-Confusion Matrix:
- [[ 69   4   2   3   9   4  14]
- [  2 122   3  12   6   5   8]
- [ 19  25 134  45  28  26  39]
- [ 19   9  19  78  14   8  10]
- [  0   2   6   0  67   1   3]
- [  7   1   1   1   1  39   5]
- [ 13   1  14  10  12   7  73]]
-Node Classification on random seed  3765 -> 0.628
-Confusion Matrix:
- [[ 67   3   1  13   2   6   4]
- [  4 143   5   1   9   3   5]
- [ 22  22 152  24  24  19  44]
- [  9  14  22 100   2   8   5]
- [  0  11   2   1  49   0   2]
- [  6   4   2   2   2  40   6]
- [ 14   6  12  11   7  13  77]]
-Node Classification on random seed  3766 -> 0.6
-Confusion Matrix:
- [[ 77   1   5   4  10  16   3]
- [  2 116   4   6  21   6   3]
- [ 21  31 123  26  22  21  49]
- [ 21   3   7  96  13   6  14]
- [  0   4   2   2  68   0   2]
- [  4   0   6   1   4  49   1]
- [ 10   2  11   6   7  23  71]]
-Node Classification on random seed  3767 -> 0.626
-Confusion Matrix:
- [[ 60   2   2   4  13  12  16]
- [  9 121   7   3   6   2   7]
- [ 21  21 154  26  31  22  28]
- [  9   4  22  96   2   5  14]
- [  0   7   2   1  73   1   2]
- [ 10   1   0   2   1  46   7]
- [ 20   3   6   4  11   8  76]]
-Node Classification on random seed  3768 -> 0.603
-Confusion Matrix:
- [[ 64   3   8   2   3   9   7]
- [  2 123   1   0   9   2   5]
- [ 29  28 133  34  21  29  58]
- [ 14   2   8  96  16  10  11]
- [  1   5   2   5  63   4   2]
- [  8   1   3   0   0  47   7]
- [  2   2   6   6  10  22  77]]
-Node Classification on random seed  3769 -> 0.628
-Confusion Matrix:
- [[ 83   1  12   9   8   9   4]
- [  6 135   3   4   5   7   8]
- [ 24  21 132  28  22  20  45]
- [  8   0  10 111   5   3  12]
- [  0   6   7   1  53   3   2]
- [ 10   2   0   6   0  38   3]
- [ 12   2  15  13   8   8  76]]
-Node Classification on random seed  3770 -> 0.624
-Confusion Matrix:
- [[ 67   2   6   8   7  18   5]
- [  1 134   3   3   6   3   7]
- [ 17  25 141  47  21  20  30]
- [ 12   2  23 102   6   8  10]
- [  1   3   6   2  64   0   0]
- [  5   0   3   0   0  35   9]
- [ 13   1  13   7   6  17  81]]
-Node Classification on random seed  3771 -> 0.614
-Confusion Matrix:
- [[ 74   2   6   7   6  10  14]
- [  1 138   3   1  13   3   4]
- [ 14  20 140  43  20  16  54]
- [  9   4  13  98   5   3  22]
- [  1   4   4   3  60   0   3]
- [  4   1   3   2   1  46   3]
- [  9   8  15   9  10  13  58]]
-Node Classification on random seed  3772 -> 0.615
-Confusion Matrix:
- [[ 74   1   2  10   4   7  14]
- [  3 133   8   1   5   1   2]
- [ 22  21 138  30  52  19  40]
- [ 10   2  15 100   2   9  11]
- [  3   6   1   1  61   0   2]
- [  9   1   0   2   0  46   7]
- [  9   9   7   4  21  12  63]]
-Node Classification on random seed  3773 -> 0.659
-Confusion Matrix:
- [[ 60   3   9   5   3   7   6]
- [  2 134   2   3   5   1   7]
- [ 21  32 178  27  19  11  50]
- [  6   8  12  96   9   4   7]
- [  0   9   3   3  70   1   1]
- [  3   3   2   0   0  44   7]
- [ 10   4   6  10   8  12  77]]
-Node Classification on random seed  3774 -> 0.629
-Confusion Matrix:
- [[ 68   5   3  16   4  10   6]
- [  5 125   7   0   5   5   5]
- [ 14  35 176  44  14  16  40]
- [ 15   6  16 102   3   6   9]
- [  0   7   3   3  56   0   1]
- [  3   3   3   2   0  47   1]
- [ 13   3   9  16   1  14  55]]
-Node Classification on random seed  3775 -> 0.577
-Confusion Matrix:
- [[ 75   4   1   5   6  10   7]
- [  2 132   1   1   8   1   5]
- [ 31  26 118  52  27  17  54]
- [ 25   6  16  83   8   6   9]
- [  2   5   1   2  66   3   2]
- [  7   3   4   2   3  39   3]
- [ 10   3   4   8  10  23  64]]
-Node Classification on random seed  3776 -> 0.617
-Confusion Matrix:
- [[ 67   2  21   1   1  10   6]
- [  7 143   3   3   3   1   4]
- [ 23  29 151  36  31  10  39]
- [  7   7  21  84   6   9  16]
- [  4   7   1   2  56   3   2]
- [  4   2   2   1   0  39   3]
- [ 14   1  14  10   6  11  77]]
-Node Classification on random seed  3777 -> 0.616
-Confusion Matrix:
- [[ 64   1   8   4   3   7  15]
- [  5 139   5   3   6   4   2]
- [ 11  22 138  38  33  18  44]
- [ 13   8  17  97   3   9  14]
- [  0  13   7   2  54   0   1]
- [  2   5   3   0   1  47   8]
- [  7   3  12  11   5  11  77]]
-Node Classification on random seed  3778 -> 0.637
-Confusion Matrix:
- [[ 79   2   1   4   2   6  15]
- [  2 134   6   1  13   3   3]
- [ 30  18 140  33  36  28  38]
- [  6   3   7 111   6   8   7]
- [  1   2   2   1  75   1   3]
- [  2   2   0   0   4  30   9]
- [ 23   3  12   4   8   8  68]]
-Node Classification on random seed  3779 -> 0.614
-Confusion Matrix:
- [[ 61   5   2   5   1  19  13]
- [  3 128   7   1   8   2   4]
- [ 23  37 144  34  13  17  46]
- [  5   3  17 100   2   4  18]
- [  0  12   4   4  67   1   3]
- [  6   0   0   4   1  45   5]
- [ 13   5  10   2   5  22  69]]
-Node Classification on random seed  3780 -> 0.606
-Confusion Matrix:
- [[ 77   5   8   6   8   4   6]
- [  5 118   9   4  15   0   7]
- [ 30  15 135  36  20  12  41]
- [ 15   5  12 106   9   9  14]
- [  1   9   4   1  55   1   3]
- [  4   0   3   1   1  42   6]
- [ 12   3  14   1   8  27  73]]
-Node Classification on random seed  3781 -> 0.619
-Confusion Matrix:
- [[ 60   0   1  11  11  17   5]
- [  2 128   8   1   9  15   4]
- [ 19  17 136  24  28  30  35]
- [  8   4  11 112   4   5  12]
- [  1   8   1   3  62   0   3]
- [  8   0   1   6   1  53   0]
- [ 11   2   8  17   7  23  68]]
-Node Classification on random seed  3782 -> 0.609
-Confusion Matrix:
- [[ 78   1   2   6   3   8  12]
- [  4 120  11   2   6   6   7]
- [ 31  18 126  42  24  23  37]
- [ 19   3  20  96   5   6   8]
- [  0   5   5   1  64   1   4]
- [  6   1   3   2   0  48   3]
- [ 16   6  11   4   7  12  77]]
-Node Classification on random seed  3783 -> 0.61
-Confusion Matrix:
- [[ 59   5   4  13   1  20   3]
- [  6 125   6   2   8   1   4]
- [ 33  26 145  36  22  30  30]
- [  4   3  13 126   9   9  15]
- [  3   2  10   0  49   0   1]
- [  3   0   0   3   2  38   6]
- [ 14   2  12   9   5  15  68]]
-Node Classification on random seed  3784 -> 0.624
-Confusion Matrix:
- [[ 70   1   1   5   4  10  14]
- [  2 126   6   1   7   5   3]
- [ 26  32 128  23  46  14  40]
- [ 16   6  20  90   4   4  13]
- [  0   4   9   0  65   1   2]
- [  4   3   1   1   0  50   4]
- [  6   2   4   9   9  14  95]]
-Node Classification on random seed  3785 -> 0.614
-Confusion Matrix:
- [[ 76   4   3   4   3  10   6]
- [  3 143   3   0   4   2   3]
- [ 25  29 134  44  21  23  33]
- [ 15  10  17  91   1  10  12]
- [  1  11   0   2  60   1   2]
- [  4   5   9   0   0  43   1]
- [ 18   8  12   6   1  20  67]]
-Node Classification on random seed  3786 -> 0.582
-Confusion Matrix:
- [[ 52   6  15   3   1   5  16]
- [  2 136   4   2   8   1   7]
- [ 33  19 104  46  27  20  66]
- [  8   6  11 106   1   4  18]
- [  0   6   7   2  56   1   1]
- [  5   0   5   4   0  46   5]
- [ 16   4  12   8   3  10  82]]
-Node Classification on random seed  3787 -> 0.635
-Confusion Matrix:
- [[ 59   3  10  12   5  11   6]
- [  6 129   4   0  11   3   2]
- [ 15  19 162  24  24   9  44]
- [  4   9  16 100   7   8  18]
- [  1  10   4   0  63   2   2]
- [  1   2   2   8   0  46   2]
- [  9   4  24  13   4   7  76]]
-Node Classification on random seed  3788 -> 0.617
-Confusion Matrix:
- [[ 86   2   2   5   1   6  11]
- [  7 110   9   1  11   4   0]
- [ 43  20 137  36  33  16  35]
- [ 17   9  11 109   2   6   9]
- [  0   6   2   5  60   0   3]
- [  7   1   5   0   0  33   4]
- [ 15   4  10   6   9  10  82]]
-Node Classification on random seed  3789 -> 0.613
-Confusion Matrix:
- [[ 66   4   3   3   1  13  10]
- [  4 130   7   2  10   2   1]
- [ 18  25 119  49  21  39  21]
- [ 18   5  16  95   5  12  13]
- [  3   3   3   3  60   0   2]
- [  3   0   2   1   0  47  12]
- [ 20   6   8   2   8   9  96]]
-Node Classification on random seed  3790 -> 0.596
-Confusion Matrix:
- [[ 76   2   3   6   5   8   9]
- [  6 124   7   8   7   5   5]
- [ 25  21 133  19  46  33  46]
- [ 11   3  21  91  14   8   5]
- [  0   5   4   0  57   2   3]
- [  6   2   0   4   1  45   2]
- [ 17   3   5  10   9   8  70]]
-Node Classification on random seed  3791 -> 0.62
-Confusion Matrix:
- [[ 84   1   5  11   1   2  12]
- [  3 119   6   3  21   3   7]
- [ 16  20 147  24  30  17  53]
- [  6   3  12 106   7   8  22]
- [  1   5   1   1  66   1   1]
- [ 13   1   2   5   0  36   8]
- [ 12   8   7   5   6  10  62]]
-Node Classification on random seed  3792 -> 0.632
-Confusion Matrix:
- [[ 80   4   1   8   2  11   3]
- [  3 136   5   3   8   7   4]
- [ 27  25 138  31  12  23  39]
- [  8   5  15 100   2   5  21]
- [  0   6   5   1  73   4   0]
- [ 10   1   5   0   2  34   2]
- [ 16   4  10   5   9  16  71]]
-Node Classification on random seed  3793 -> 0.607
-Confusion Matrix:
- [[ 53   3  14   6   5  10  12]
- [  4 130   6   3   9   9   2]
- [ 24  16 144  14  17  44  39]
- [  4   4  27  95   3   8  19]
- [  6   2   4   1  70   4   4]
- [  5   0   3   1   1  46   4]
- [  4   3  14   4  12  19  69]]
-Node Classification on random seed  3794 -> 0.631
-Confusion Matrix:
- [[ 76   1   3   8   3  16   2]
- [  3 138   3   5   5   1   1]
- [ 21  26 146  31  37  21  27]
- [ 13   2  19 104   5   5   5]
- [  1   3   3   0  56   2   3]
- [ 11   1   1   1   2  47  10]
- [  7   6  13  12  13  17  64]]
-Node Classification on random seed  3795 -> 0.595
-Confusion Matrix:
- [[ 61   2   4   1  12  17   6]
- [  1 111   4   7  10   2   4]
- [ 15  18 138  38  34  32  44]
- [ 11   3  22  95   8   3  13]
- [  1   7   3   0  68   5   4]
- [  5   4   4   3   0  42   4]
- [ 18   0   9   9   5  13  80]]
-Node Classification on random seed  3796 -> 0.593
-Confusion Matrix:
- [[ 76   7   4   6   9  19   5]
- [ 11 117   7   0  12   3   4]
- [ 22  24 127  26  52  28  30]
- [ 15   3  14  98   3  10  13]
- [  1   8   5   3  50   0   1]
- [ 11   1   0   1   0  47   2]
- [ 18   3   5   3   5  13  78]]
-Node Classification on random seed  3797 -> 0.659
-Confusion Matrix:
- [[ 72   2   0  11   3   5   4]
- [  4 136   4   0   9   3   1]
- [ 28  25 146  38  24  21  24]
- [ 12   4  12 120   4  12   8]
- [  2   5   6   1  61   1   1]
- [  2   0   2   1   1  54   1]
- [ 16   3   2  13   8  18  70]]
-Node Classification on random seed  3798 -> 0.635
-Confusion Matrix:
- [[ 81   0   3   5   6  16   6]
- [ 10 124   0   1  17   2   2]
- [ 16  30 131  30  23  36  31]
- [ 11   4  13 103   2   7   9]
- [  1   4   2   6  59   1   4]
- [  6   1   0   1   1  52   5]
- [  9   5   6  10   7  16  85]]
-Node Classification on random seed  3799 -> 0.637
-Confusion Matrix:
- [[ 74   2   6   3   3  10   5]
- [  8 148   7   1   5   2   6]
- [ 28  27 146  24  19  33  19]
- [  6   5  18  79   6   8   3]
- [  1   5  13   1  70   0   1]
- [ 18   1   4   0   0  45   2]
- [  9  10   8   6   4  26  75]]
-Node Classification on random seed  3800 -> 0.622
-Confusion Matrix:
- [[ 69   3   0   2   4  13   7]
- [  3 129   3   0  18   4   5]
- [ 14  27 145  43  16  35  32]
- [  7   2  10 100  17   6  13]
- [  1   5   4   0  57   0   1]
- [  5   1   2   0   0  55   7]
- [  8   5  13  16   9  17  67]]
-Node Classification on random seed  3801 -> 0.602
-Confusion Matrix:
- [[ 68   4   6   5   2  13   8]
- [  3 125   6   4   8   4   6]
- [ 30  18 136  45  48  24  24]
- [ 14   2  10 104  10   5  11]
- [  1   6   1   2  58   1   1]
- [  6   0   5   2   2  46   1]
- [ 11   2  16   5   9  17  65]]
-Node Classification on random seed  3802 -> 0.591
-Confusion Matrix:
- [[ 60   2   9  11   7  11  10]
- [  8 142  10   1   6   2   1]
- [ 25  14 135  26  54  22  48]
- [ 13   2  17  89   4  10  10]
- [  0   4   2   0  51   1   2]
- [  9   0   2   0   0  49   3]
- [ 20   4   3   4  10  22  65]]
-Node Classification on random seed  3803 -> 0.622
-Confusion Matrix:
- [[ 64   3   1   3  10  22   9]
- [  4 120  14   1   5   6   4]
- [ 23  55 140  28  29  22  15]
- [ 11   7   4 122   8   5  15]
- [  0   4   4   5  49   2   1]
- [  4   1   2   2   0  47   2]
- [ 12   1   5   9   8  12  80]]
-Node Classification on random seed  3804 -> 0.624
-Confusion Matrix:
- [[ 63   0   5  16   8  11  13]
- [  2 120   4   4   2   2   7]
- [ 15  22 167  33  24  17  39]
- [ 10   2  19  97  12   2  11]
- [  2   9   6   1  55   2   0]
- [  5   3   0   4   2  45   9]
- [  9   4  10  16   6   8  77]]
-Node Classification on random seed  3805 -> 0.602
-Confusion Matrix:
- [[ 68   3   1  10   0  20   7]
- [  4 125   5   0  16   5   2]
- [ 31  29 112  28  21  32  38]
- [  4   8  15 129   6   8   5]
- [  0   8   5   1  58   2   0]
- [ 11   1   3   2   0  36   3]
- [ 11   5   4   8   9  27  74]]
-Node Classification on random seed  3806 -> 0.619
-Confusion Matrix:
- [[ 49   3   5   6   3  10  11]
- [  9 126   5   6   9   3   3]
- [ 27  13 173  27  35  13  34]
- [ 18   0  30  88  14   5  13]
- [  6   3   4   1  59   0   4]
- [  3   0   3   3   0  50   4]
- [  9   3   9   9   5  13  74]]
-Node Classification on random seed  3807 -> 0.616
-Confusion Matrix:
- [[ 65   3  11  10   5   9   4]
- [  1 116   5  11   4   0   5]
- [  8  21 160  54  21  21  48]
- [ 12   4  14 100   6   3   6]
- [  0   5   7   4  62   1   2]
- [  3   1   5   2   0  44   3]
- [  6   9  14   5   8  23  69]]
-Node Classification on random seed  3808 -> 0.623
-Confusion Matrix:
- [[ 54   2  12   1   3  13  24]
- [  3 118   3   2  22   1   7]
- [ 30  16 155  24  33  14  46]
- [  8   5  23 112   5   7   7]
- [  0   8   5   0  64   1   1]
- [  3   2   1   0   0  41   4]
- [  7   3   7  14   3   7  79]]
-Node Classification on random seed  3809 -> 0.564
-Confusion Matrix:
- [[ 60   2   8   3   4  12  15]
- [ 11 115   9   4   8   2   3]
- [ 28  24 135  45  45  10  37]
- [ 19   3  20  99   4   5  21]
- [  1   3   5   2  49   3   1]
- [ 14   0   4   3   1  36   8]
- [  8   6   7   6   8  14  70]]
-Node Classification on random seed  3810 -> 0.62
-Confusion Matrix:
- [[ 74   3   8   8   5   8   7]
- [  6 108   7   0  12   2   4]
- [ 23  20 169  24  23  32  39]
- [ 16   2  17  94   5   5   5]
- [  1   9   4   1  67   4   1]
- [  9   1   2   3   3  39   2]
- [ 19   4   6  10   5  15  69]]
-Node Classification on random seed  3811 -> 0.643
-Confusion Matrix:
- [[ 64   1  12   3   5   4   9]
- [  6 133  10   0   6   0   2]
- [ 25  26 166  22  33  14  30]
- [ 18   4  14 105   7   3  14]
- [  3   5   6   2  57   0   0]
- [  7   2   3   2   4  41   5]
- [ 11   6   7   6   6  14  77]]
-Node Classification on random seed  3812 -> 0.635
-Confusion Matrix:
- [[ 74   7  10   1   4   6   8]
- [  5 129   7   2   5   0   4]
- [ 18  14 153  31  30  16  40]
- [ 17   3   8 113   2   8   8]
- [  1  12   2   1  56   2   5]
- [ 14   2   0   1   0  39   6]
- [ 17   2  13  11  12  10  71]]
-Node Classification on random seed  3813 -> 0.573
-Confusion Matrix:
- [[ 52   2   9   3   1  15  15]
- [  5 111   8   4   2   0   4]
- [ 23  31 120  56  20  25  44]
- [  4   8   9 111   3  13  16]
- [  2   5   4   6  56   2   5]
- [  7   1   2   2   1  51   6]
- [ 12   2   5  22   6  17  72]]
-Node Classification on random seed  3814 -> 0.587
-Confusion Matrix:
- [[ 63   3   4   6   2   4   7]
- [ 10 122   3   4   9   5   3]
- [ 24  13 135  35  34  30  26]
- [ 12   3  25  87  13  11  18]
- [  1   7   6   3  65   4   1]
- [  5   0   6   4   2  42   2]
- [  9   3   9  20  12  15  73]]
-Node Classification on random seed  3815 -> 0.628
-Confusion Matrix:
- [[ 69   4   0   8   4   9   2]
- [  2 116   2   5   8   1   6]
- [ 33  38 138  27  19  12  43]
- [ 12   6  10 109   1   6   9]
- [  0   7   3   1  66   2   1]
- [ 14   1   5   1   0  54   8]
- [ 16   1   6  12  10  17  76]]
-Node Classification on random seed  3816 -> 0.624
-Confusion Matrix:
- [[ 70   0  11   3   3   6   9]
- [ 10 127   2   1   5   1  11]
- [ 36  20 154  36  28  23  27]
- [  9   8  16  98   5   5  14]
- [  2   3   4   1  55   3   2]
- [ 12   3   1   1   0  48   4]
- [ 16   3  14   5   4   9  72]]
-Node Classification on random seed  3817 -> 0.62
-Confusion Matrix:
- [[ 72   4   8   3   3  11  10]
- [  4 145   5   1   4   5   5]
- [ 37  16 128  34  18  30  42]
- [  6   2  22  92   6   7  11]
- [  1   4   6   1  66   1   1]
- [  9   3   1   3   2  44   2]
- [ 18   2   9   6   3  14  73]]
-Node Classification on random seed  3818 -> 0.584
-Confusion Matrix:
- [[ 64   1   6   2   3  17  16]
- [  1 139   6   2   9   3   5]
- [ 24  23 134  27  29  30  45]
- [ 27   8  11  78   4  18   9]
- [  1   4   2   0  66   1   0]
- [  4   0   1   1   0  46   6]
- [ 11   7  17  10   6  19  57]]
-Node Classification on random seed  3819 -> 0.594
-Confusion Matrix:
- [[ 69   4   1   5   5  15  13]
- [  2 108   2   5  10   0   8]
- [ 19  22 122  40  41  26  36]
- [ 16   8  14 106   3   8  13]
- [  2   5   2   1  70   2   2]
- [  2   2   1   0   4  47   3]
- [  5   1  14  18   8  18  72]]
-Node Classification on random seed  3820 -> 0.613
-Confusion Matrix:
- [[ 79   1   2   7   1   9   2]
- [  6 112  12   6   9  10   2]
- [ 40  17 140  43  17  20  31]
- [ 19   4  14 103  13   2   8]
- [  4   6   3   4  63   1   3]
- [  3   0   3   3   5  43   2]
- [ 10   2   7  11   7  18  73]]
-Node Classification on random seed  3821 -> 0.581
-Confusion Matrix:
- [[ 69   4   0   6   2  11   5]
- [  2 134   8   3   8   4   7]
- [ 35  20 143  24  19  22  50]
- [ 15   8  18  81   2   5  20]
- [  1   5   1   3  51   1   5]
- [  8   4   1   2   0  49   7]
- [ 19   4  11  16   7  26  54]]
-Node Classification on random seed  3822 -> 0.597
-Confusion Matrix:
- [[ 65   1  13   7   5  11  12]
- [  4 127   6   4  14   2   5]
- [ 37  21 131  20  38  13  48]
- [ 13  10   9 100   4   3  19]
- [  1   8   2   0  58   2   1]
- [  3   3   4   4   1  43   8]
- [  4   1  19   9   6   8  73]]
-Node Classification on random seed  3823 -> 0.602
-Confusion Matrix:
- [[ 70   3   1   9   2  18   8]
- [  1 126  11   4   1   3   2]
- [ 33  23 113  38  40  17  35]
- [ 15   3  17 110   4   5  16]
- [  1   6   4   0  66   1   2]
- [  2   1   6   0   1  44   3]
- [ 23   3  15   6   7   8  73]]
-Node Classification on random seed  3824 -> 0.559
-Confusion Matrix:
- [[ 63   2   4   8   3  14   7]
- [  8 130   2   0  10   3   2]
- [ 27  10 104  55  28  33  56]
- [ 11   8  24  79   3   9  22]
- [  3   5   1   2  68   0   3]
- [  5   2   0   2   0  45   6]
- [ 10   3  13  13   9  15  70]]
-Node Classification on random seed  3825 -> 0.606
-Confusion Matrix:
- [[ 75   4   4   4   5   9   5]
- [  1 126   7   1   5   3   7]
- [ 36  25 141  24  17  39  36]
- [ 19   5  18  94   4   5   5]
- [  1   3   6   1  63   1   3]
- [  6   1   1   3   0  48   2]
- [ 14   5  12   7  11  29  59]]
-Node Classification on random seed  3826 -> 0.658
-Confusion Matrix:
- [[ 89   3   1   1   3   8  15]
- [  3 143  11   3   4   2   3]
- [ 21  30 163  21  21   6  31]
- [ 17   8   9  85   6   4  17]
- [  1  12   6   0  69   0   2]
- [  9   1   2   2   0  41   7]
- [ 17   6  13   0   9   7  68]]
-Node Classification on random seed  3827 -> 0.659
-Confusion Matrix:
- [[ 76  11   7   8   4  16   3]
- [  4 122   5   0   3   2   1]
- [ 35  31 137  25  27  13  24]
- [  9   5   7 137   4   5  14]
- [  1   3   3   1  66   1   5]
- [  5   2   1   0   0  49   0]
- [ 18   2   6   7   5  18  72]]
-Node Classification on random seed  3828 -> 0.656
-Confusion Matrix:
- [[ 67   2   2   3   3   9  18]
- [  0 148   0   3   5   3   7]
- [ 17  30 161  26  21  29  32]
- [  5   6  19  99   0  17  14]
- [  1   3   3   3  67   1   3]
- [  3   0   5   0   2  46   6]
- [  8   3   7   6   7  12  68]]
-Node Classification on random seed  3829 -> 0.618
-Confusion Matrix:
- [[ 71   4   1  10   6   6   8]
- [  3 140   2   5   9   2   1]
- [ 17  19 141  48  30  16  35]
- [ 10   1  21  94   6  10  12]
- [  1   5   3   0  61   2   3]
- [  7   2   4   1   4  36   3]
- [ 15   8  11   0  15  16  75]]
-Node Classification on random seed  3830 -> 0.627
-Confusion Matrix:
- [[ 67   2   8   4   3  13   3]
- [  2 132   4   4   9   1   4]
- [ 22  20 148  35  31  31  26]
- [ 19   0  12 103   2   4  20]
- [  3   1   6   2  58   0   4]
- [  5   0   8   2   4  48   2]
- [  4   0  11  12   5  25  71]]
-Node Classification on random seed  3831 -> 0.59
-Confusion Matrix:
- [[ 73   7   2   2   1   9  17]
- [  6 126   3   0  21   0   7]
- [ 14  40 120  39  37  13  51]
- [ 15   2  21  95   7  13  14]
- [  3   5   2   0  58   1   2]
- [  6   3   0   0   0  51   5]
- [  6   6   6  11   6   7  67]]
-Node Classification on random seed  3832 -> 0.64
-Confusion Matrix:
- [[ 85   4   4   4   4   6   9]
- [  1 142   3   5   2   4   2]
- [ 28  16 143  39  33  21  29]
- [ 12   4  20 100   4  11   8]
- [  0   3   3   2  45   2   6]
- [  4   2   2   2   0  39   6]
- [ 16   6   9   7   7  10  86]]
-Node Classification on random seed  3833 -> 0.591
-Confusion Matrix:
- [[ 69   4   3   4  10  10   8]
- [  7 122   4   3   9   5   4]
- [ 32  39 118  47  24  27  31]
- [ 10   6  22 111   5   7   9]
- [  1   3   4   2  60   0   4]
- [ 10   2   3   1   1  40   2]
- [ 12   4   7   7   8   8  71]]
-Node Classification on random seed  3834 -> 0.628
-Confusion Matrix:
- [[ 80   3   1   5   4   8  15]
- [  2 125   4   0  10   1   1]
- [ 29   9 144  24  17  33  42]
- [  7   3  26  87   2   4  25]
- [  0   4   9   3  53   0   5]
- [  6   2   1   0   1  49   1]
- [  9   2  10   3  15  26  90]]
-Node Classification on random seed  3835 -> 0.632
-Confusion Matrix:
- [[ 62   6   2   4   3  13  11]
- [ 15 118   6   2   4   1   5]
- [ 27  21 163  33  10  20  30]
- [ 14   0  17  98   4   9  23]
- [  1   6   4   3  68   0   6]
- [  6   1   1   0   1  47  10]
- [ 14   2  13   2   6  12  76]]
-Node Classification on random seed  3836 -> 0.592
-Confusion Matrix:
- [[ 62   1   5   6   4  10  10]
- [  4 107   4   0  21   3   4]
- [ 27  19 171  14  31  28  46]
- [ 16   5  21  84  18   6  15]
- [  1   3   3   0  59   3   1]
- [  4   0   0   5   5  35   2]
- [ 13   2  12   5   4  27  74]]
-Node Classification on random seed  3837 -> 0.587
-Confusion Matrix:
- [[ 62   4   1   2   4   4  11]
- [  4 117   3   3  16   2   2]
- [ 27  31 149  27  34  21  45]
- [ 17  10  12  96   8   8  14]
- [  1  11   5   1  53   0   6]
- [  9   1   1   1   4  45   2]
- [ 15   5   8  12  12   9  65]]
-Node Classification on random seed  3838 -> 0.646
-Confusion Matrix:
- [[ 71   9   4   6   4   9  13]
- [  2 126   5   2  11   1   5]
- [ 20  26 149  26  14  28  42]
- [ 12   2  15 105   3   7  13]
- [  1   5   3   0  64   1   4]
- [  3   0   2   6   1  46   7]
- [  6   2   5   2  10  17  85]]
-Node Classification on random seed  3839 -> 0.567
-Confusion Matrix:
- [[ 61   8   1   3   1  16  10]
- [  1 138   3   2  15   1   8]
- [ 27  29 112  32  44  29  31]
- [ 24   6  26  86   5  14  15]
- [  2   7   2   2  60   2   3]
- [  2   1   0   2   1  48   4]
- [  5   6   5   6  15  17  62]]
-Node Classification on random seed  3840 -> 0.645
-Confusion Matrix:
- [[ 67   1   2   5   5   7   9]
- [  2 125  11   1   9   3   5]
- [ 32  15 161  27  20  34  41]
- [ 10   1  17 105   3   3  10]
- [  1   2   4   4  69   1   4]
- [  4   2   1   1   0  33   8]
- [ 19   3   8   6   2  12  85]]
-Node Classification on random seed  3841 -> 0.58
-Confusion Matrix:
- [[ 69   2   5   6   7   7  20]
- [  3 114   7   2   0   7   4]
- [ 24  27 144  47  25  35  35]
- [ 13   1  25  89   2   2  10]
- [  1   8   5   3  51   2   7]
- [  6   3   4   1   0  47   9]
- [ 11   3  21   5   3  12  66]]
-Node Classification on random seed  3842 -> 0.624
-Confusion Matrix:
- [[ 77   5  13   2   3   3  10]
- [  3 123   6   1  10   2   6]
- [ 32  28 146  34  21  10  39]
- [ 21   3  23 104   5   5  11]
- [  4   6   2   4  51   0   1]
- [  6   1   6   1   1  46   3]
- [ 16   2  12   8   5   2  77]]
-Node Classification on random seed  3843 -> 0.63
-Confusion Matrix:
- [[ 75   1   3   9   2   7   3]
- [  5 137   2   6   1   6  13]
- [ 33   9 134  41  15  26  27]
- [ 16   3  14 101   7   4  17]
- [  1   5  10   1  54   0  10]
- [  8   1   5   0   0  54   5]
- [ 17   2   5   4   3  23  75]]
-Node Classification on random seed  3844 -> 0.589
-Confusion Matrix:
- [[ 62   1   6   9   3   9   8]
- [  4 121  16   1  16   2   1]
- [ 39  17 124  58  31  24  25]
- [ 12   4  18 110   5   3   9]
- [  1   2   8   1  66   1   2]
- [  5   0   3   2   0  43   4]
- [ 17   3  10   6  11  14  63]]
-Node Classification on random seed  3845 -> 0.587
-Confusion Matrix:
- [[ 68   2   3   2   6  12  11]
- [  7 122   2   2  15   4   9]
- [ 21  20 118  38  49  30  40]
- [  6   9   8 106   8   8   8]
- [  1   5   5   5  69   0   2]
- [  4   2   6   0   6  26  19]
- [  3   6  13   2   6   8  78]]
-Node Classification on random seed  3846 -> 0.65
-Confusion Matrix:
- [[ 82   3   7   8   4  12   4]
- [  1 130   3   5   6   4   6]
- [ 22  27 154  27  11  21  36]
- [  7   2  21 100   5   6  13]
- [  1   9   2   1  67   1   1]
- [  4   1   1   3   3  51   1]
- [ 15   8  12  13   4   9  66]]
-Node Classification on random seed  3847 -> 0.593
-Confusion Matrix:
- [[ 79   4   1   5   9  14   9]
- [  6 133   0   6  14   2   1]
- [ 37  45 112  23  32  25  36]
- [ 12   6  17 104   2   2   6]
- [  1   8   0   1  55   0   3]
- [  7   0   3   1   4  38   9]
- [ 14   3   2  10  16  11  72]]
-Node Classification on random seed  3848 -> 0.63
-Confusion Matrix:
- [[ 64   6  10   7   6  13  10]
- [  3 133   1   4   6   1   2]
- [ 12  29 151  34  17  24  36]
- [  9   5  24 106   1   5  12]
- [  1   6   2   6  58   0   3]
- [  4   2   2   7   0  44   3]
- [ 14   8   9   9   4  13  74]]
-Node Classification on random seed  3849 -> 0.63
-Confusion Matrix:
- [[ 60   2   1  14   3   6  20]
- [  4 124   5   4   6   2   2]
- [ 16  28 142  41  35  33  22]
- [  3   6  17 114  11   4  10]
- [  0   4   1   3  75   0   3]
- [  5   2   0   2   0  36   5]
- [  9   2   7   4  11  17  79]]
-Node Classification on random seed  3850 -> 0.64
-Confusion Matrix:
- [[ 67   1   3   4   2   8  10]
- [  8 116   4   1  11   2   4]
- [ 18  21 171  31  30  26  27]
- [ 12   0  20 116   2   8  12]
- [  1   7   5   2  59   0   0]
- [  7   1   2   1   1  43   6]
- [ 15   2  13   9   6  17  68]]
-Node Classification on random seed  3851 -> 0.557
-Confusion Matrix:
- [[ 72   1   4   5   4   9   7]
- [  4 120   6   5   4   6   1]
- [ 31  40 107  39  37  48  39]
- [ 11   8  19  84   7   6  24]
- [  2   6   1   0  69   0   3]
- [  9   2   0   0   0  44   5]
- [  7   7   4   9   8  15  61]]
-Node Classification on random seed  3852 -> 0.598
-Confusion Matrix:
- [[ 60   5   7  14   2  19   9]
- [  6 130   3   2   6   2   7]
- [ 21  20 150  35  33  16  35]
- [  3   8  25  78  11   6   7]
- [  0  11   1   2  71   0   3]
- [  7   1   3   2   0  50  10]
- [ 14   6   4  18   8  10  59]]
-Node Classification on random seed  3853 -> 0.579
-Confusion Matrix:
- [[ 59   2   2   8   5  24  10]
- [  6 129   4   3   9   4   3]
- [ 26   6 112  57  36  21  47]
- [ 21   2   7 105   6   7   7]
- [  2   5   1   0  65   1   7]
- [  7   3   0   2   4  49   3]
- [ 18   3   3  19   6  14  60]]
-Node Classification on random seed  3854 -> 0.602
-Confusion Matrix:
- [[ 67   2  11   6   4  14  10]
- [  3 115   7   1  16   8   0]
- [ 14  31 135  48  34  33  27]
- [  4   4  20 103   4   6  16]
- [  1   3   3   0  64   0   2]
- [  3   0   0   1   2  53   2]
- [ 13   5   7   5  10  18  65]]
-Node Classification on random seed  3855 -> 0.622
-Confusion Matrix:
- [[ 59   1   3   8   2  12  15]
- [  3 128   4   5   4   1   4]
- [ 15  22 147  41  34  31  30]
- [  8   2   6  98  12  10  16]
- [  1   5   7   1  62   3   5]
- [  4   0   0   2   1  53   3]
- [  4   1  10  15   5  22  75]]
-Node Classification on random seed  3856 -> 0.626
-Confusion Matrix:
- [[ 68   3   4   6   0  19   6]
- [  3 131   3   3   2   7   4]
- [ 10  20 141  47  21  35  42]
- [ 11   3  12 112   3   2  16]
- [  0   5   4   3  56   5   6]
- [  7   2   1   0   0  45   5]
- [ 10   8   3  15   5  13  73]]
-Node Classification on random seed  3857 -> 0.597
-Confusion Matrix:
- [[ 76   3   0   7   4  16   7]
- [  3 116  12   4   8   6   2]
- [ 28  16 130  33  19  24  56]
- [ 24   2  14  92   3   4  15]
- [  1  12   4   1  57   2   2]
- [  8   0   2   1   0  52   9]
- [  9   1   7  13   5  16  74]]
-Node Classification on random seed  3858 -> 0.614
-Confusion Matrix:
- [[ 65   1   2  10   7  15  10]
- [  4 127   4   1   5   7   5]
- [ 20  16 145  42  12  24  55]
- [  7   7  12 112   7   7  10]
- [  1   8   8   0  69   1   2]
- [  2   0   6   0   0  33   7]
- [  6   4  11  17   3  20  63]]
-Node Classification on random seed  3859 -> 0.632
-Confusion Matrix:
- [[ 74   5   4   8   2   3   7]
- [  5 131  14   4  17   0   3]
- [ 16  18 122  36  32  22  46]
- [  1   2  11 121   6   4  17]
- [  5   5   6   0  64   0   0]
- [  7   0   5   0   2  45   5]
- [ 13   5   7   4  12   9  75]]
-Node Classification on random seed  3860 -> 0.629
-Confusion Matrix:
- [[ 82   3   3   9   1  10  16]
- [  1 122   4   2  11   5   5]
- [ 14  11 155  33  41  22  28]
- [  8   9  10 102   6   4  13]
- [  1   2   5   1  59   4   1]
- [  9   1   2   0   3  41   1]
- [  7   5   5  16  10  29  68]]
-Node Classification on random seed  3861 -> 0.586
-Confusion Matrix:
- [[ 61   7   2   3   0   9  14]
- [  8 110  14   9  11   7   3]
- [ 39  20 140  49  25  13  36]
- [ 14   5  26 109   3   7   7]
- [  2   1   5   4  57   0   1]
- [  6   3   1   1   1  38  10]
- [ 13   6  10   6   3  10  71]]
-Node Classification on random seed  3862 -> 0.598
-Confusion Matrix:
- [[ 69   2  12   3   6  11   8]
- [  5 141   4   3  14   2   4]
- [ 22  25 136  29  30  17  41]
- [ 21   3  12  78  21   3  16]
- [  6   6   1   2  58   1   2]
- [  5   1   3   0   0  50   8]
- [ 17   4  12   7   8   5  66]]
-Node Classification on random seed  3863 -> 0.592
-Confusion Matrix:
- [[ 83   4   3   2   5   7   7]
- [  5 131   5   4   2   1  11]
- [ 30  18 126  50  54  13  40]
- [ 11   2  26  77  14   4  20]
- [  3   3   1   0  66   0   1]
- [  5   0   2   0   2  48   8]
- [ 12   0  11   1  12   9  61]]
-Node Classification on random seed  3864 -> 0.59
-Confusion Matrix:
- [[ 61   2  17   6   2  13   8]
- [  3 120  12   1   7   2   4]
- [ 18  31 123  48  21  21  47]
- [  8   3  29  86  11   7   6]
- [  1   5  10   0  68   0   4]
- [  5   1   0   0   0  50   2]
- [ 15   7   5   6   6  16  82]]
-Node Classification on random seed  3865 -> 0.64
-Confusion Matrix:
- [[ 82   2   4   5   4   9  10]
- [  6 129   7   0   1   2   6]
- [ 20  29 158  25  27  17  49]
- [  9  10  23  89   3   5  14]
- [  2   3   2   2  65   2   5]
- [  8   3   2   1   1  37   5]
- [  7   4   8   3   6   9  80]]
-Node Classification on random seed  3866 -> 0.63
-Confusion Matrix:
- [[ 63   7   1   2   3  13  17]
- [  4 134   6   3   3   1   8]
- [ 30  19 155  37  23  33  25]
- [ 12   5  15  99   3   4  15]
- [  2  10   4   1  54   1   3]
- [  9   0   3   2   0  42   4]
- [ 10   2  10   1   2  17  83]]
-Node Classification on random seed  3867 -> 0.651
-Confusion Matrix:
- [[ 85   3   4   0   2  18   2]
- [  7 117   2   3  14   2   5]
- [ 18  16 174  40  22  23  34]
- [ 12   4   9 103   4   7  20]
- [  2   2   4   2  55   1   3]
- [  7   4   3   0   0  35   5]
- [ 11   2   8   7   2  15  82]]
-Node Classification on random seed  3868 -> 0.619
-Confusion Matrix:
- [[ 73   1   5   4   1   6  18]
- [  8  96   5   6  17   5   3]
- [ 21  24 153  46  24  17  29]
- [  7   4  15 117   3   6  15]
- [  2   5   2   4  60   0   3]
- [  8   0   3   0   2  51   2]
- [ 16   3   2  19   7  13  69]]
-Node Classification on random seed  3869 -> 0.568
-Confusion Matrix:
- [[ 60   4  12   2   7   6  23]
- [ 13 112   7   5   4   1   2]
- [ 31  31 142  39  40  18  27]
- [ 17  10  21  93   7   6   7]
- [  4   7   1   2  52   1   2]
- [  9   1   3   1   1  45   7]
- [  6   2  14  14   5  12  64]]
-Node Classification on random seed  3870 -> 0.605
-Confusion Matrix:
- [[ 73   2   9  13   4  17   6]
- [  1 110   2   4  17   1   6]
- [ 23  33 132  45  36  23  22]
- [  4   5  14 121   2   7  14]
- [  0   5   6   1  56   2   6]
- [  7   0   1   1   2  40   3]
- [ 14   2  11   6   8  10  73]]
-Node Classification on random seed  3871 -> 0.611
-Confusion Matrix:
- [[ 71   2   3   4   1  11   9]
- [  4 128   4   1   4   4   7]
- [ 26  27 124  45  22  41  29]
- [  7   3  25  93   2   8  10]
- [  5   3   1   1  73   0   7]
- [  4   2   4   1   0  48   7]
- [  8   3  10  10   5  19  74]]
-Node Classification on random seed  3872 -> 0.65
-Confusion Matrix:
- [[ 62   2   1   6   6  12  13]
- [  8 120   6   1  18   4   1]
- [ 25  22 161  21  20  23  32]
- [ 11   6  13 114   3   8  14]
- [  0   3   8   1  69   1   0]
- [  4   2   0   0   0  43   4]
- [ 13   3   6   9  10  10  81]]
-Node Classification on random seed  3873 -> 0.598
-Confusion Matrix:
- [[ 53   9   1   9   4  11  13]
- [  4 122   7   3  13   6   4]
- [ 23  30 144  45  33  12  35]
- [ 13   2  18  89  17   4   7]
- [  1   2   3   1  66   1   1]
- [  2   2   1   4   2  46   5]
- [  4   7  13  12   6  12  78]]
-Node Classification on random seed  3874 -> 0.593
-Confusion Matrix:
- [[ 62   0   4   9   8   7  13]
- [  4 109   3   2  12   1  10]
- [ 26  16 134  32  29  23  34]
- [ 11   2  28 126   8   6  13]
- [  1   4   1   2  55   0   1]
- [  9   2   4   7   0  43  10]
- [ 13   0   8  16   9  19  64]]
-Node Classification on random seed  3875 -> 0.69
-Confusion Matrix:
- [[ 71   0   4   6   4   8   4]
- [  4 121  10   0   7   1   7]
- [ 13  18 178  29  10  18  43]
- [  8   2  12 117   1   3  11]
- [  2   5   3   3  65   1   2]
- [  6   0   3   1   4  50   4]
- [ 11   0   8  11   7  16  88]]
-Node Classification on random seed  3876 -> 0.583
-Confusion Matrix:
- [[ 52   4   5   7   5  25  12]
- [  9 117   5   3   8   2   6]
- [ 30  23 157  31  29  25  27]
- [ 11   7  13 104  12   5  14]
- [  3   5   7   1  63   0   3]
- [  5   4   2   3   2  38   2]
- [ 13   1  11   8   8  21  52]]
-Node Classification on random seed  3877 -> 0.599
-Confusion Matrix:
- [[ 68   2   8   5   6  17  14]
- [  5 113   5   3   2   7  12]
- [ 26  13 159  27  18  41  34]
- [  7   3  23  92   8   7  14]
- [  1   5   3   3  41   1   2]
- [  1   7   3   0   0  55   2]
- [ 14   7   6   9   5  25  71]]
-Node Classification on random seed  3878 -> 0.62
-Confusion Matrix:
- [[ 69   5   5  12   6   5  10]
- [  1 118   2   3  12   1   6]
- [ 19  22 148  31  30  24  46]
- [  9   5  26  87   2   4  14]
- [  2   4   1   0  73   1   3]
- [ 10   1   3   2   0  43   2]
- [  8   1  11   8   9  14  82]]
-Node Classification on random seed  3879 -> 0.615
-Confusion Matrix:
- [[ 61   6   3   7   8  12  14]
- [  4 115   7   5  15   0   4]
- [ 24  17 143  46  36  15  35]
- [ 14   3   6  98  16  11   7]
- [  0   8   3   0  66   1   4]
- [  3   0   2   2   2  47   7]
- [  1   5   7   6   7  12  85]]
-Node Classification on random seed  3880 -> 0.669
-Confusion Matrix:
- [[ 73   6   7   2   5   7   5]
- [  1 143   2   1   5   0   2]
- [ 26  18 179  32   9  21  39]
- [  7   3  12  96  11   2  19]
- [  1   7   2   0  54   0   8]
- [  3   2   1   1   1  42   9]
- [ 11   3  12  12  14   2  82]]
-Node Classification on random seed  3881 -> 0.588
-Confusion Matrix:
- [[ 60   8   4   5   4  11   3]
- [  3 115   2   3   6   6   0]
- [ 41  31 123  48  26  28  25]
- [ 19   6  15 111   5   8   7]
- [  4   6   3   1  61   3   6]
- [  3   0   1   8   0  37   2]
- [ 13   1  13  11   4  19  81]]
-Node Classification on random seed  3882 -> 0.64
-Confusion Matrix:
- [[ 78   2   1   4   5  18   4]
- [  9 132   7   3   8   5   1]
- [ 30  19 152  27  20  20  36]
- [  9   4  17 112   5   4   6]
- [  2   5   4   1  62   1   2]
- [  8   1   1   3   1  41   5]
- [ 12   4  14   8   6  18  63]]
-Node Classification on random seed  3883 -> 0.621
-Confusion Matrix:
- [[ 66   4   5   2   4  27  13]
- [ 13 104   4   2   7   1   6]
- [ 23  12 152  19  24  25  33]
- [ 14   3  22  94   7  11  18]
- [  2   7   7   0  77   2   0]
- [  7   0   0   1   1  44  10]
- [  9   4   8   6   5  11  84]]
-Node Classification on random seed  3884 -> 0.604
-Confusion Matrix:
- [[ 69   3   3   8   1   8   8]
- [  8 115   6   3  18   4   3]
- [ 21  25 144  48  20  22  35]
- [ 11   3   7 110   6   4  18]
- [  3   4   4   1  60   3   3]
- [  4   4   1   6   1  34  13]
- [ 13   6   8   7   6  16  72]]
-Node Classification on random seed  3885 -> 0.607
-Confusion Matrix:
- [[ 77   2   7   5   2  18   9]
- [  8 108   2   1  13   4  10]
- [ 23  22 150  36  16  31  34]
- [  9   4  16 109   6  12  21]
- [  4   5   7   0  46   0   2]
- [  7   2   0   3   2  44   6]
- [  9   7   7   7   4  10  73]]
-Node Classification on random seed  3886 -> 0.641
-Confusion Matrix:
- [[ 72   8   2   2   5   3  16]
- [  8 120  11   1  10   7   5]
- [ 22  17 175  17  25  26  33]
- [  9   4  13 105   3   5  17]
- [  3   2   7   1  55   0   3]
- [  5   0   3   4   1  40  14]
- [ 13   5   9   2   7  11  74]]
-Node Classification on random seed  3887 -> 0.609
-Confusion Matrix:
- [[ 70   2   9   9   4  12   8]
- [  5 127   6   3   3   4   4]
- [ 33  17 161  31  24  34  19]
- [ 12   3  28  71   3   7  16]
- [  2   9  11   2  64   0   4]
- [  4   2   1   3   0  48   3]
- [ 17   1  10   2   7  17  68]]
-Node Classification on random seed  3888 -> 0.588
-Confusion Matrix:
- [[ 69   0  13   9   7  15   1]
- [  4 108   7   7  17   1   0]
- [ 28  19 131  33  52  26  41]
- [ 13   2  10 119   6  10   5]
- [  0   7   2   3  51   0   4]
- [  6   2   0   2   1  49   3]
- [ 11   5   9   4   6  21  61]]
-Node Classification on random seed  3889 -> 0.636
-Confusion Matrix:
- [[ 81   2   7   8   2  13   2]
- [  3 125   8   1  11   5   3]
- [ 20  11 127  40  30  26  26]
- [ 16   5  18 121   1   7  11]
- [  1   6   0   2  76   5   0]
- [  3   3   1   7   0  50   3]
- [ 15   2   7   5   8  20  56]]
-Node Classification on random seed  3890 -> 0.569
-Confusion Matrix:
- [[ 68   2   4   8   1  18  17]
- [  6 109  10   6  12   6   5]
- [ 28  30 140  46  26  37  24]
- [ 11   2   4 119   6   4   5]
- [  0   5   7   2  45   2   0]
- [  6   2   0   8   0  41   1]
- [ 11   0  14   7  15  33  47]]
-Node Classification on random seed  3891 -> 0.605
-Confusion Matrix:
- [[ 63   2   4   2   4  15  11]
- [ 12 105   8   1  16   5   8]
- [ 23  12 146  26  15  28  64]
- [ 11   3  13 104  10   7  21]
- [  0   3   6   1  55   0   4]
- [  4   2   0   1   4  45   4]
- [ 12   2   3   6   7  15  87]]
-Node Classification on random seed  3892 -> 0.628
-Confusion Matrix:
- [[ 74   1   9   2   5  13   4]
- [  6 143   4   1   8   0   2]
- [ 22  28 142  31  31  23  43]
- [ 24   2  13  83  12   5   8]
- [  0   5   2   0  64   4   6]
- [  2   0   2   2   0  44   3]
- [ 14   3   5   3   7  17  78]]
-Node Classification on random seed  3893 -> 0.594
-Confusion Matrix:
- [[ 65   2   4   4   5  13  14]
- [  0 118   8   8   4   1   5]
- [ 38  35 129  37  28  24  27]
- [ 22   3  13  83   4   4  23]
- [  2   5   0   2  66   1   3]
- [  3   3   2   5   0  51   3]
- [ 11   4   2  10  11  13  82]]
-Node Classification on random seed  3894 -> 0.637
-Confusion Matrix:
- [[ 78   2   3   0   8  15   9]
- [  4 116  10   1   2   2   3]
- [ 24  40 159  27  15  18  38]
- [  7   5  12 112   5   3  12]
- [  3  13   5   1  59   0   1]
- [  8   3   9   2   0  44   7]
- [ 19   2   8   0   7  10  69]]
-Node Classification on random seed  3895 -> 0.619
-Confusion Matrix:
- [[ 57   7   4   8   5  13  13]
- [  4 128   5   1   5   7   0]
- [ 28  11 151  30  31  33  38]
- [ 16   3  27  84   3   7  16]
- [  0   5   5   1  59   0   0]
- [  1   0   2   1   2  55   3]
- [ 11   1   9   4  10  11  85]]
-Node Classification on random seed  3896 -> 0.621
-Confusion Matrix:
- [[ 69   1   3   5   0   6  20]
- [  5 111  10   4   7   2   3]
- [ 31  21 162  21  26  17  41]
- [ 11   4  27  86   6   7   9]
- [  5   9   5   4  66   0   0]
- [  1   4   4   1   0  49   3]
- [ 16   2  17   4   5  12  78]]
-Node Classification on random seed  3897 -> 0.66
-Confusion Matrix:
- [[ 72   2   0  10   4   7  10]
- [  5 130   3   0   6   3   6]
- [ 23  20 163  22  25  26  27]
- [ 11   7  16 118   4   7  11]
- [  0   7   6   3  60   0   2]
- [ 11   0   3   0   0  47   5]
- [  6   1  14   2   8  17  70]]
-Node Classification on random seed  3898 -> 0.64
-Confusion Matrix:
- [[ 72   1   3   5   3  10   8]
- [  2 142   5   1   3   3   1]
- [ 12  19 143  33  32  21  39]
- [ 14   1  19  85   5  19  13]
- [  2   6   4   0  61   3   4]
- [  5   3   2   1   1  55   2]
- [  3   6  10  10   5  21  82]]
-Node Classification on random seed  3899 -> 0.605
-Confusion Matrix:
- [[ 65   4   3   8   3  12  12]
- [  0 116   3   2   9   0   4]
- [ 22  23 134  36  22  48  31]
- [  9   3  26 101   3   4  12]
- [  3  16   5   1  52   2   2]
- [  5   1   0   1   0  46   8]
- [  5   4   8  10   8  17  91]]
-Node Classification on random seed  3900 -> 0.619
-Confusion Matrix:
- [[ 67   3   5   6   4  11   7]
- [  5 124   6   2  16  12   1]
- [ 26  12 148  22  32  25  41]
- [  7   2  11 113   4   3  18]
- [  3   7   1   0  62   0   2]
- [  5   3   0   3   0  35  11]
- [ 14   4   2  11  21  13  70]]
-Node Classification on random seed  3901 -> 0.667
-Confusion Matrix:
- [[ 89   3   2   3   2   4  15]
- [  2 121   4   6   8   3   1]
- [ 17  17 161  30  21  25  28]
- [ 10   2   7 103   7  11  22]
- [  1   4   5   1  63   2   3]
- [  4   2   3   1   0  52   6]
- [ 17   3   9   7   4  11  78]]
-Node Classification on random seed  3902 -> 0.602
-Confusion Matrix:
- [[ 65   2   5   3   5  12   9]
- [  3 116  17   9   6   9   8]
- [ 21  14 156  18  28  15  58]
- [  5   5  30  91   6   4  19]
- [  3   4   7   1  53   1   3]
- [  5   3   4   2   0  49   1]
- [ 10   2  14   7   5  15  72]]
-Node Classification on random seed  3903 -> 0.612
-Confusion Matrix:
- [[ 74   2   0   4   4   7  24]
- [  2 138  14   1   3   3   3]
- [ 21  24 163  46  34  12  33]
- [ 10   3  21  92   3   3  12]
- [  1   6   3   4  61   1   5]
- [  7   5   1   1   1  40   4]
- [ 11   4   8   7  11  19  44]]
-Node Classification on random seed  3904 -> 0.656
-Confusion Matrix:
- [[ 88   2   5   5   3  10   5]
- [  1 134   1   1   9   2   5]
- [ 27  23 138  25  19  12  46]
- [ 20   7  19 100   6   2   6]
- [  0   6   3   1  60   0   4]
- [  5   1   1   2   0  55   4]
- [ 20   6   9   3   4  14  81]]
-Node Classification on random seed  3905 -> 0.6
-Confusion Matrix:
- [[ 57   2  14   7   6  13   8]
- [  3 128   2   3  13   8   2]
- [ 23  14 117  31  17  29  55]
- [ 21   4  13  95   4   4  16]
- [  3   4  10   0  62   1   2]
- [  8   3   1   0   1  47   3]
- [ 12   1  10   9  10  10  94]]
-Node Classification on random seed  3906 -> 0.636
-Confusion Matrix:
- [[ 88   2   7   4   2   6   7]
- [  1 114  14   0   5   3   7]
- [ 43  21 144  38  14  15  27]
- [  5   1  19 108  11   5  15]
- [  4   5   7   2  61   2   2]
- [  6   2   3   2   2  41   6]
- [ 16   3  16   5   5   4  80]]
-Node Classification on random seed  3907 -> 0.623
-Confusion Matrix:
- [[ 87   3   7   2   2   8  12]
- [  5 114  10   2   9   1   5]
- [ 32  30 151  29  22   9  33]
- [ 11   5  13  88   5   5  19]
- [  2   5   7   4  61   0   2]
- [  3   3   1   1   0  48  16]
- [  9   3  13   6  13  10  74]]
-Node Classification on random seed  3908 -> 0.648
-Confusion Matrix:
- [[ 81   7   1   1   3   7   5]
- [  1 120   8   2   9  11   6]
- [ 18  15 141  28  41  23  27]
- [ 15   2  15 102   7  12   9]
- [  3   3   2   0  71   0   0]
- [  4   3   1   0   0  69   8]
- [ 10   2  15   6   5  17  64]]
-Node Classification on random seed  3909 -> 0.644
-Confusion Matrix:
- [[ 79   1  13   1   6   4   8]
- [  7 122   4   5   6   2   7]
- [ 27  15 181  18  24  23  40]
- [  9   4  28  90   9   6  13]
- [  1   6   6   2  63   0   3]
- [  5   3   3   1   1  38   5]
- [  8   2  12   1   8   9  71]]
-Node Classification on random seed  3910 -> 0.621
-Confusion Matrix:
- [[ 71   1  11   8   3   9   9]
- [  7 111   6   5   5   3   6]
- [ 21  23 142  38  24  31  35]
- [  8   6   9 124   5  11   6]
- [  0   2   5   3  56   2   4]
- [  4   4   2   0   0  38   8]
- [ 13   3  14   3   2  20  79]]
-Node Classification on random seed  3911 -> 0.618
-Confusion Matrix:
- [[ 66   2   3   4   2  17  15]
- [  1 132   4   6   7   1   6]
- [ 29  23 153  58  16  17  35]
- [ 12   4   8 105   3   1   8]
- [  1  15   3   0  61   0   0]
- [  4   0   7   0   1  38   6]
- [  2   6  12  17   8  18  63]]
-Node Classification on random seed  3912 -> 0.607
-Confusion Matrix:
- [[ 84   7   4   3   5   4   5]
- [ 12 103   8   5   8   5   4]
- [ 29  17 166  25  30  19  26]
- [ 30   6  26  86  15   1  10]
- [  0   9   3   1  49   1   0]
- [  9   0   2   5   0  41   4]
- [ 16   3   9  15   4   8  78]]
-Node Classification on random seed  3913 -> 0.66
-Confusion Matrix:
- [[ 74   3   2   5   6   6   7]
- [  7 139   3   3   5   1   9]
- [ 26  16 153  35  15  12  38]
- [ 14   1  12 122   2   1  16]
- [  1   7   4   0  61   1   3]
- [  9   4   3   3   0  36   7]
- [ 13   4   3   9   3  21  75]]
-Node Classification on random seed  3914 -> 0.577
-Confusion Matrix:
- [[ 54   2  23   4   3  11   5]
- [  5 128   4   0   7   4   3]
- [ 40  30 115  24  20  25  43]
- [ 11   1  13 101   6  11  22]
- [  0  13   7   4  56   1   0]
- [  6   2   0   1   1  53   3]
- [ 19   3  11   7  10  18  70]]
-Node Classification on random seed  3915 -> 0.634
-Confusion Matrix:
- [[ 64   2   2   1   4  13  17]
- [  9 144   8   1   2   1   5]
- [ 25  21 134  40  19  22  43]
- [ 21   2   9 118   5   3  16]
- [  0   4   5   0  58   1   3]
- [ 10   0   0   2   0  50   8]
- [  4   0   9   8   4  17  66]]
-Node Classification on random seed  3916 -> 0.655
-Confusion Matrix:
- [[ 85   4   8   5   3  11   5]
- [  3 134   4   2   4   9   3]
- [ 23  15 146  28  19  30  39]
- [  8   4  11 109   4   6   9]
- [  1   5   7   4  56   2   2]
- [  7   1   5   1   1  49   0]
- [ 14   4  12   5   3  14  76]]
-Node Classification on random seed  3917 -> 0.59
-Confusion Matrix:
- [[ 74   5   3  10   4   9   4]
- [  2 130   6   3   5   2   5]
- [ 21  33 119  35  38  40  38]
- [  9   7  12 110   4   7  11]
- [  0   7   2   4  43   2   4]
- [  4   1   2   2   1  46   5]
- [  8   6  12  13   8  16  68]]
-Node Classification on random seed  3918 -> 0.571
-Confusion Matrix:
- [[ 56   5   4   6   2  13  20]
- [  7 135  10   3   6   3   0]
- [ 31  18 112  38  48  33  33]
- [ 20   4  10  89  13  19   8]
- [  1   8   2   1  54   1   3]
- [  3   1   1   0   3  47   7]
- [ 12   1   7   5   4  15  78]]
-Node Classification on random seed  3919 -> 0.649
-Confusion Matrix:
- [[ 73  11   3   3   5   8  10]
- [  6 112   8   3   4   0   7]
- [ 22  24 175  27  26  15  34]
- [ 14   8  11 116   3   6   7]
- [  1   5   1   1  67   1   6]
- [  4   1   4   0   3  37  16]
- [ 19   1  10   3   5   5  69]]
-Node Classification on random seed  3920 -> 0.611
-Confusion Matrix:
- [[ 77   2   6   3   4   2  18]
- [  3 122   9   5  10   0   8]
- [ 25  15 144  38  33  21  53]
- [ 11   6  13 110   6   1   7]
- [  0   8   3   0  57   0   4]
- [  8   2   3   2   2  35   5]
- [ 12   2  10  18   3   8  66]]
-Node Classification on random seed  3921 -> 0.602
-Confusion Matrix:
- [[ 70   3  10   4   7   8  14]
- [  5 116   4   1   4   1   7]
- [ 32  21 145  41  32  23  48]
- [  5   5  16  96   9   5  21]
- [  2   2   7   0  57   2   1]
- [  4   0   0   1   1  42   9]
- [ 15   5   5   2   7   9  76]]
-Node Classification on random seed  3922 -> 0.649
-Confusion Matrix:
- [[ 78   4   2  16   1   8   6]
- [  5 131   4   3  17   0   2]
- [ 18  17 158  18  22  25  42]
- [  6   3  16 111  13   2   4]
- [  0   3   8   2  71   0   4]
- [  3   5   8   2   3  35   2]
- [ 13   2   6  11  12  13  65]]
-Node Classification on random seed  3923 -> 0.555
-Confusion Matrix:
- [[ 73   0   7   4   7   9  17]
- [  1 100   3  11   9   3   0]
- [ 37  22 135  28  46  20  44]
- [ 29   2  15  76   6  13  13]
- [  1   7   8   5  55   3   3]
- [  3   2   3   1   2  45   6]
- [ 12   3  18   5   4  13  71]]
-Node Classification on random seed  3924 -> 0.581
-Confusion Matrix:
- [[ 82   0   1   4   2  20  10]
- [  2 135  10   1   4   1   1]
- [ 22  21 119  41  40  27  47]
- [ 19   5  10  93   3   6  16]
- [  0  10   0   5  55   1   2]
- [  6   1   6   0   1  41   3]
- [ 12   6  15   4  16  18  56]]
-Node Classification on random seed  3925 -> 0.618
-Confusion Matrix:
- [[ 81   3   3   5   3   4   6]
- [  6 123   4   0   8   2   8]
- [ 33  33 149  38  29  18  25]
- [ 10  11  29  91   5   8   7]
- [  2   6   1   5  57   1   4]
- [  3   3   7   0   1  46   6]
- [ 10   1   9   8   6  11  71]]
-Node Classification on random seed  3926 -> 0.618
-Confusion Matrix:
- [[ 81   1  12   2   2   7   5]
- [ 12 125   3   3   1   1   3]
- [ 16  30 133  49  21  25  43]
- [ 16   9   9 101   6  11  12]
- [  0   8   3   0  65   1   5]
- [  3   1   2   3   0  37   7]
- [  5   2  18   2   7  16  76]]
-Node Classification on random seed  3927 -> 0.618
-Confusion Matrix:
- [[ 64   2   0  12   3  15  18]
- [  5 119   4   0   8   2   7]
- [ 20  18 140  42  22  24  39]
- [  9   1  12 118   1   8  10]
- [  2   7   5   4  57   1   0]
- [  4   1   0   0   0  39  18]
- [ 14   1  16   6   5  16  81]]
-Node Classification on random seed  3928 -> 0.625
-Confusion Matrix:
- [[ 75   1   7   4   4  13   5]
- [  3 114   3   2   2   4  13]
- [ 17  22 153  36  22  20  52]
- [ 10   3  13 104   2   5  20]
- [  2   9   4   1  68   0   3]
- [  6   1   4   2   1  41   3]
- [ 14   4  11   9   6  12  70]]
-Node Classification on random seed  3929 -> 0.609
-Confusion Matrix:
- [[ 67   4   1   7   1  13  15]
- [  6 144   1   2   4   2   3]
- [ 20  31 132  59  27  16  18]
- [  5   3  15 112  10   7  18]
- [  5   9   1   4  43   2   3]
- [  4   1   1   0   1  42   5]
- [ 12   4   9   6  19  17  69]]
-Node Classification on random seed  3930 -> 0.563
-Confusion Matrix:
- [[ 55   8   5   5   3  11  15]
- [  2 119   5   0   5   3  18]
- [ 26  24 130  19  22  24  56]
- [ 24   5  25  74  11   8  19]
- [  0   7   4   0  66   2   2]
- [  7   0   0   0   0  40   5]
- [ 16   8   9   9   6  19  79]]
-Node Classification on random seed  3931 -> 0.522
-Confusion Matrix:
- [[ 49   3  20  10   6  13  12]
- [  2 114   9   7   6   7   4]
- [ 17  35 110  70  38  22  45]
- [  2   2  23  95   2   8  19]
- [  2   5   5   1  53   1   2]
- [  5   1   1   6   1  39   4]
- [ 12   5  13   6  10  16  62]]
-Node Classification on random seed  3932 -> 0.646
-Confusion Matrix:
- [[ 65   1   3   1  12   9   7]
- [ 13 126   3   1  10   6   5]
- [  6  19 169  37  34  25  35]
- [ 11   5  13  90   5   6  23]
- [  2   3   1   2  58   1   4]
- [  1   2   2   0   2  48   2]
- [  4   0   4   5   9  20  90]]
-Node Classification on random seed  3933 -> 0.631
-Confusion Matrix:
- [[ 76   4   1   7   2   6   5]
- [  5 123   5   5   3   2   4]
- [ 29  35 163  25  21  21  31]
- [ 10  10  19  96   1  12  10]
- [  3   9   2   1  60   0   3]
- [  8   3   1   2   0  45   6]
- [ 23   5   4   4   6  16  68]]
-Node Classification on random seed  3934 -> 0.624
-Confusion Matrix:
- [[ 85   2   1   2   4   7   6]
- [  5 119   6   5  16   1   7]
- [ 27   8 127  22  39  25  51]
- [  9   5  18 102   7  12   9]
- [  1   5   2   0  63   0   1]
- [  5   0   3   0   1  40   8]
- [ 22   7   7   5   5  10  88]]
-Node Classification on random seed  3935 -> 0.612
-Confusion Matrix:
- [[ 64   0   9  13   3  13   3]
- [  4 129   6   4  15   3   7]
- [ 14  13 147  37  24  34  40]
- [  7   4  14  97   9   9  16]
- [  2   2   3   3  70   1   3]
- [ 13   1   3   2   0  43   0]
- [ 11   4   6   6   1  26  62]]
-Node Classification on random seed  3936 -> 0.665
-Confusion Matrix:
- [[ 84   0   7   2   1   9  15]
- [  4 130   7   3   7   8   5]
- [ 13   9 164  23  19  18  34]
- [  8   4  22  97   5   9  10]
- [  2   4   7   2  57   0   2]
- [  5   0   0   3   2  48   5]
- [ 13   9   9  14   6  10  85]]
-Node Classification on random seed  3937 -> 0.592
-Confusion Matrix:
- [[ 67   2   1   7   5   8   9]
- [  4 122   4   1  10   4   1]
- [ 40  12 117  42  37  19  62]
- [ 15   7  10  98  10   3  10]
- [  2   4   2   0  70   0   6]
- [  5   2   3   1   0  47   1]
- [ 14   6   6   4  12  17  71]]
-Node Classification on random seed  3938 -> 0.633
-Confusion Matrix:
- [[ 85   4   7   7   1  16   7]
- [  8 130   4   1   1   4   8]
- [ 36  12 145  33  29  20  36]
- [  6   3  12 109   3  11  14]
- [  1   8   4   3  54   1   1]
- [  4   0   6   3   1  32   4]
- [ 13   2   5  10   4  14  78]]
-Node Classification on random seed  3939 -> 0.611
-Confusion Matrix:
- [[ 62   1   4   6   4  14   6]
- [  3 120   8   1  10   5   9]
- [ 18  20 140  55  21  23  38]
- [ 17   2  14 117   2   8  11]
- [  1   9   3   1  54   3   3]
- [  6   1   1   2   2  43   3]
- [  8   5   4   6   6  25  75]]
-Node Classification on random seed  3940 -> 0.62
-Confusion Matrix:
- [[ 76   8   6   8   0  12   4]
- [  1 136   1   7   4   4   5]
- [ 15  28 145  35  18  21  46]
- [ 12   7  12  89  16   3  24]
- [  0   3  10   3  50   0   1]
- [  4   0   1   2   0  50   6]
- [ 12   2   8  19   4   8  74]]
-Node Classification on random seed  3941 -> 0.596
-Confusion Matrix:
- [[ 70   4   3   1   5  18  14]
- [  4 120   6   5   8   8   3]
- [ 26  13 118  62  11  42  34]
- [ 16   1   4 109   2   5  15]
- [  2   6   7   1  70   1   2]
- [  8   2   1   0   0  43  10]
- [  7   4   8  11   9  15  66]]
-Node Classification on random seed  3942 -> 0.648
-Confusion Matrix:
- [[ 74   5   7   5   4   8   7]
- [  2 135   9   0   6   0   4]
- [ 18  22 146  38  42  12  35]
- [  6   2  19 100   9   2  11]
- [  0   8   2   0  66   1   1]
- [  5   1   1   4   0  42   7]
- [ 11   6  10   6   8   8  85]]
-Node Classification on random seed  3943 -> 0.598
-Confusion Matrix:
- [[ 66   5   2   4   3  12  12]
- [  7 122   8   4   4   4   4]
- [ 16  24 139  53  29  34  31]
- [ 18   3   9 102   1   3  10]
- [  0   6  10   4  67   1   1]
- [  5   3   0   3   0  44   5]
- [ 15   6   5   5   9  24  58]]
-Node Classification on random seed  3944 -> 0.635
-Confusion Matrix:
- [[ 72   0   2   7   2  12   8]
- [  9 142   3   4   4   3   3]
- [ 16  28 150  43  18  10  27]
- [ 10   4   8 120   6   2  10]
- [  1   5   4   1  59   0   2]
- [  5   6   1  12   3  30  17]
- [ 18   4   4  22   6  15  62]]
-Node Classification on random seed  3945 -> 0.593
-Confusion Matrix:
- [[ 79   2  11   3   3   4  10]
- [ 10 117   4   9  13   0   5]
- [ 38  24 136  23  29  16  27]
- [ 26   8   9  88   8   6   9]
- [  1   3   5   2  62   4   3]
- [  3   0  14   7   1  39   4]
- [ 14   4  14   6  10  15  72]]
-Node Classification on random seed  3946 -> 0.601
-Confusion Matrix:
- [[ 65   2   6   4   2  18  14]
- [  3 119   5   8   5   1   2]
- [ 26  29 152  28  37  12  32]
- [ 20   8  10 100   8   4  11]
- [  2   4   4   4  62   1   3]
- [  7   4   0   0   0  40   6]
- [ 10   8  10  19   4  18  63]]
-Node Classification on random seed  3947 -> 0.606
-Confusion Matrix:
- [[ 59   3  15  10   3  13   4]
- [  5 137   8   4   9   4   4]
- [ 30  26 153  24  16  34  24]
- [ 16   8  15 109   2   7  12]
- [  3   1   7   2  55   1   1]
- [ 12   0   7   1   3  39   3]
- [ 23   1   8   4   5  16  54]]
-Node Classification on random seed  3948 -> 0.641
-Confusion Matrix:
- [[ 73   3   5   6   2   9  11]
- [  4 128   4   3  14   2   4]
- [ 16  13 142  26  36  23  34]
- [  6   1  34  96   4   3  20]
- [  1   3   2   2  68   3   1]
- [  8   0   4   2   2  43   1]
- [  8   1   9   6   7  16  91]]
-Node Classification on random seed  3949 -> 0.633
-Confusion Matrix:
- [[ 66   1  13   4   4   9  10]
- [  6 123   7   8   5   0   8]
- [ 10  17 163  30  20  19  56]
- [  6   2  17 106   6   4  15]
- [  0   7   4   2  60   0   4]
- [  9   2   3   1   3  38   4]
- [ 12   3   9   8   2  17  77]]
-Node Classification on random seed  3950 -> 0.612
-Confusion Matrix:
- [[ 80   1   5   4   7   9   8]
- [  3 139   3   3   4   0   3]
- [ 14  30 128  56  30   7  43]
- [ 21   0  17 113   9   3   7]
- [  0  12   9   1  61   0   1]
- [ 15   6   1   0   0  28   6]
- [ 16   2   6   6  10  10  63]]
-Node Classification on random seed  3951 -> 0.675
-Confusion Matrix:
- [[ 63   4   3   5   4  13  15]
- [  7 128   8   2   4   1   5]
- [ 17  21 148  48  18  22  26]
- [  7   3   9 127   6   4  10]
- [  1   6   2   3  64   0   4]
- [  3   0   4   2   1  53   0]
- [  8   2  10   3   3  11  92]]
-Node Classification on random seed  3952 -> 0.593
-Confusion Matrix:
- [[ 55   7   4   7   3   4  20]
- [  4 125   6   5   3   0   5]
- [ 30  18 138  65  31   7  28]
- [ 20  10  13 112  11   2  15]
- [  2   8   1   6  42   1   1]
- [  8   0   6   1   1  47   5]
- [  8   3   7   9   5  17  74]]
-Node Classification on random seed  3953 -> 0.619
-Confusion Matrix:
- [[ 67   2   0   8   5  12   8]
- [  5 123   8   5  18   0   5]
- [ 36  19 159  28  32  20  25]
- [ 14  13   9  88  16   8   3]
- [  0  11   2   1  60   0   5]
- [  4   2   1   2   0  45   4]
- [  7   2   5  13   6  17  77]]
-Node Classification on random seed  3954 -> 0.617
-Confusion Matrix:
- [[ 82   6  13   2   5   9  10]
- [  2 137   0   1   5   5   7]
- [ 27  11 135  35  26  25  42]
- [ 14   4   9 103   5  10  10]
- [  2   8   4   2  43   2   7]
- [  7   2   4   1   1  39   5]
- [ 15   8   8   5   5  14  78]]
-Node Classification on random seed  3955 -> 0.586
-Confusion Matrix:
- [[ 66   0   2   9   4  10  11]
- [  5 125   5   5   5   2   3]
- [ 29  39 101  29  40  19  44]
- [ 14   6  13  88   8   2  13]
- [  1  13   2   3  62   1   5]
- [  4   1   1   0   0  64   3]
- [ 11   9   9   9   6  19  80]]
-Node Classification on random seed  3956 -> 0.65
-Confusion Matrix:
- [[ 78   3  12   1   3  16   1]
- [  2 131   6   1   3   4   3]
- [ 18  10 147  36  22  23  43]
- [  5   3  14  90  14   5  22]
- [  3   7   1   1  67   1   3]
- [  9   3   1   1   1  40   2]
- [ 12   4   8   3   9  11  97]]
-Node Classification on random seed  3957 -> 0.596
-Confusion Matrix:
- [[ 73  11   6   3   3  10   6]
- [  8 125   4   2   4   2   5]
- [ 29  20 144  48  14  23  17]
- [ 12   7  22  83  11  16  25]
- [  1   8   4   1  54   1   1]
- [  7   2   4   5   0  43   2]
- [ 14   4  19   4   8  11  74]]
-Node Classification on random seed  3958 -> 0.613
-Confusion Matrix:
- [[ 72   2   5   1   4  10  18]
- [  7 116   1   3  11   2   4]
- [ 34  11 158  29  42  12  30]
- [ 14   5  14 109  13   4  13]
- [  2  10   7   1  57   0   2]
- [  1   2   2   2   0  26   4]
- [ 15   3   8  17   5  17  75]]
-Node Classification on random seed  3959 -> 0.617
-Confusion Matrix:
- [[ 70   3   6   3   4  19   1]
- [ 12 126   8   0   3   2   2]
- [ 19  24 155  30  30  34  42]
- [ 10   7   6  97   2  14   5]
- [  2   5   3   4  55   0   3]
- [  5   2   1   4   1  44   4]
- [ 11   6   7   7   5  27  70]]
-Node Classification on random seed  3960 -> 0.624
-Confusion Matrix:
- [[ 58   1   4   3   2  15  14]
- [ 10 125   1   5   5   2   4]
- [ 16  30 136  32  32  18  40]
- [ 10  11  14 120   4  12  10]
- [  0   6   0   1  70   2   4]
- [  3   1   2   0   0  41   8]
- [ 18   4   7   2  11  12  74]]
-Node Classification on random seed  3961 -> 0.587
-Confusion Matrix:
- [[ 69   1   3   7   2  18   6]
- [  3 128  11   1   7   7   3]
- [ 19  42 107  49  29  29  32]
- [  3   5  13 110   4   5  16]
- [  1   8   8   2  44   1   4]
- [  3   6   2   2   2  53   5]
- [  8   7   6  13   3  17  76]]
-Node Classification on random seed  3962 -> 0.608
-Confusion Matrix:
- [[ 69   7   3   4   6  13   4]
- [  4 111   8   1  11   2   2]
- [ 27  25 131  31  25  16  58]
- [  9   2  12 109  10   7   9]
- [  1   7   2   3  66   1   5]
- [  4   1   6   3   1  41   4]
- [ 16  10   5   5   8  14  81]]
-Node Classification on random seed  3963 -> 0.613
-Confusion Matrix:
- [[ 54   4   4   9  14   7  11]
- [  2 127   1   3   2   6   2]
- [ 23  25 137  30  28  24  44]
- [  7   5  12 110   6   5  15]
- [  2  12   2   2  65   0   2]
- [  3   1   2   5   1  47   6]
- [ 11   2  16   5  11  15  73]]
-Node Classification on random seed  3964 -> 0.614
-Confusion Matrix:
- [[ 61   5   2   3   3   8  15]
- [ 11 138   1   1   9   1   5]
- [ 36  38 140  14  24  21  35]
- [ 14  13  12  93  12   8   9]
- [  6   6   4   2  50   1   1]
- [  4   0   0   2   2  57   6]
- [ 13   4  13   7   5  10  75]]
-Node Classification on random seed  3965 -> 0.612
-Confusion Matrix:
- [[ 80   0   5   6   4  12  11]
- [  6 126   3   5   1   4   9]
- [ 21  14 154  43  25  22  51]
- [ 12   1  14  93   9   6  22]
- [  1   9   2   4  46   1   2]
- [  7   2   0   0   3  38   6]
- [  8   3   5   7   4  18  75]]
-Node Classification on random seed  3966 -> 0.62
-Confusion Matrix:
- [[ 74   3   1   6   4   5  12]
- [  1 128  10   1   8   1   7]
- [ 23  10 130  27  24  29  54]
- [ 13   5  13 104   6   8  14]
- [  2   6   5   1  52   2   3]
- [  2   2   6   6   1  49   9]
- [ 10   3   7   9  12   9  83]]
-Node Classification on random seed  3967 -> 0.584
-Confusion Matrix:
- [[ 73   1   1   4   1  17  15]
- [  5 115  11   1   6   2   8]
- [ 34  10 129  37  37  19  56]
- [ 30   2  13  99   3  16   7]
- [  1   5   1   3  67   0   2]
- [ 13   0   4   1   1  38   4]
- [ 11   2  12   4   3  13  63]]
-Node Classification on random seed  3968 -> 0.617
-Confusion Matrix:
- [[ 76   0   1   4   1   9  11]
- [  4 124   3   5  13   1   8]
- [ 28  16 144  31  27  16  51]
- [ 12   3  10 105   1   9  18]
- [  1   4   3   2  55   1   3]
- [  2   0   3   1   2  52  10]
- [ 19   0   8  15  10  17  61]]
-Node Classification on random seed  3969 -> 0.63
-Confusion Matrix:
- [[ 75   3   1   5   4  19   5]
- [  6 118   3   9  10   6   4]
- [ 22  18 143  28  33  23  31]
- [ 11   3  14 111   8  15   5]
- [  0   3   3   1  67   0   2]
- [  5   0   0   0   3  46   6]
- [ 19   2   4   9   5  22  70]]
-Node Classification on random seed  3970 -> 0.648
-Confusion Matrix:
- [[ 72   1   3   3   2  11  10]
- [  0 127   5   2   7   3   6]
- [ 17  22 166  25  26  28  30]
- [ 13   7  12 103   4   2  12]
- [  3   2   3   1  65   2   3]
- [ 14   2   0   2   2  43   3]
- [ 22   1   7   5   8  21  72]]
-Node Classification on random seed  3971 -> 0.605
-Confusion Matrix:
- [[ 83   2   1   3   2  16   4]
- [  4 124   5   4  14   3   3]
- [ 21  13 123  38  47  24  36]
- [ 14   7   9 100  10   9  12]
- [  4   4   3   0  64   5   3]
- [  5   1   6   5   1  36   4]
- [ 14   2   2   7  12  16  75]]
-Node Classification on random seed  3972 -> 0.592
-Confusion Matrix:
- [[ 73   2   4   4   3  23   4]
- [  6 130   2   4   9   2   1]
- [ 27  30 141  31  37  28  38]
- [ 19   2   8  89  13   9   8]
- [  1   6   3   0  54   5   2]
- [  2   0   2   3   2  47   2]
- [ 17   4   8   9   9  19  58]]
-Node Classification on random seed  3973 -> 0.608
-Confusion Matrix:
- [[ 67   1   2   9   5  11   7]
- [  4 117   6   0   7   3   7]
- [ 35  23 143  41  15  12  38]
- [ 16   2  22  89   4   7  20]
- [  2  10   5   0  62   1   3]
- [  7   3   1   2   0  53   6]
- [ 13   7  13   6   7   9  77]]
-Node Classification on random seed  3974 -> 0.593
-Confusion Matrix:
- [[ 75   3   2   1   2  15   8]
- [ 18  99  12   3  12   0   5]
- [ 26  11 153  44  50  18  24]
- [ 16   3  13  95  15   9  11]
- [  1   2   4   0  59   0   4]
- [  4   2   6   0   1  43   8]
- [  8   1  17   4   7  17  69]]
-Node Classification on random seed  3975 -> 0.603
-Confusion Matrix:
- [[ 63   2   2  11   1  18   7]
- [  6 127   5   4   2   5   4]
- [ 16  18 149  32  32  10  60]
- [ 10   4  18  96   5   6  12]
- [  3   7   1   1  55   1   2]
- [  7   2   4   0   0  45   4]
- [ 18   2  22   5   5  23  68]]
-Node Classification on random seed  3976 -> 0.627
-Confusion Matrix:
- [[ 77   3   9   3   4   6   6]
- [  1 105  15   1   7   2   3]
- [ 14  14 158  35  44  17  37]
- [ 13   1  14 118   4   6  13]
- [  0   4   2   0  63   0   7]
- [  6   2   1   6   0  50   3]
- [  8   1  11  16   6  28  56]]
-Node Classification on random seed  3977 -> 0.599
-Confusion Matrix:
- [[ 58   3   6   3   7   9  11]
- [  3 139   6   4   8   0   3]
- [ 24  22 118  48  30  21  38]
- [  9   3  26  98   2   9  11]
- [  1  10   3   3  66   1   5]
- [  5   1   4   0   2  48   6]
- [ 10   2  13   6   4  19  72]]
-Node Classification on random seed  3978 -> 0.584
-Confusion Matrix:
- [[ 64   4   3  12   2   4  14]
- [  2 111  15   2   9   1  12]
- [ 31  23 115  39  30  21  50]
- [ 10   3  18 118   6   5  13]
- [  0   8   5   0  57   0   0]
- [ 10   0   2   3   0  41   3]
- [ 10   4   9  18   1  14  78]]
-Node Classification on random seed  3979 -> 0.623
-Confusion Matrix:
- [[ 78   2   5   6   4  12   7]
- [  1 123   5   6  10   5   7]
- [ 11  16 153  45  32  24  35]
- [  6   4  17  99   8   7  11]
- [  1   4   3   4  55   0   2]
- [  7   0   4   4   0  42   7]
- [  8   2   8   9   9  19  73]]
-Node Classification on random seed  3980 -> 0.609
-Confusion Matrix:
- [[ 70   4  12   4   1   6   8]
- [  6 121   9   4   4   3   7]
- [ 23  20 126  34  16  10  61]
- [ 19   5  18 100   6   5  16]
- [  1   8   2   0  63   1   2]
- [  2   2   3   2   0  50   9]
- [  4   5  17  12   9  11  79]]
-Node Classification on random seed  3981 -> 0.605
-Confusion Matrix:
- [[ 63   4   7   7   2   5   2]
- [  2 136  11   1   6   3   6]
- [ 34  21 138  24  32  17  40]
- [ 12  13  15  99   8   2  18]
- [  3   7   4   0  54   2   6]
- [  4   1   3   6   0  47   2]
- [ 24   2  12   4  10  13  68]]
-Node Classification on random seed  3982 -> 0.59
-Confusion Matrix:
- [[ 69   4   2   3   3  20   5]
- [  3 110   2   2  17   4  10]
- [ 23  21 131  40  30  19  46]
- [ 12   6  15  85   8  17  12]
- [  0   3   2   5  63   0   3]
- [  5   1   3   4   3  42   6]
- [ 10   5   7   9   9  11  90]]
-Node Classification on random seed  3983 -> 0.621
-Confusion Matrix:
- [[ 68   1   8   6   3  10   8]
- [  5 136   3   3   8   3   6]
- [ 23  32 139  17  19  37  41]
- [  7   4  15  90   7  11  20]
- [  1   5   0   0  70   2   1]
- [  6   2   6   0   1  52   4]
- [ 19   8   8   3   6  10  66]]
-Node Classification on random seed  3984 -> 0.581
-Confusion Matrix:
- [[ 64   5   6   2   6  21  15]
- [  4 138   5   4   4   5   0]
- [ 26  20 122  44  21  22  51]
- [ 11   5  14 100   6   2   3]
- [  0  15   5   4  56   1   4]
- [  7   0   6   2   5  35   6]
- [ 11   8  14   4   7  18  66]]
-Node Classification on random seed  3985 -> 0.602
-Confusion Matrix:
- [[ 73   6   8   6   2   8   5]
- [ 10 131   7   2  11   0   3]
- [ 20  31 138  21  39  36  21]
- [  7   6  13  94   7   7  10]
- [  2   6   4   4  57   0   1]
- [  4   1   7   1   1  45   0]
- [ 11   0  16  15  11  28  64]]
-Node Classification on random seed  3986 -> 0.583
-Confusion Matrix:
- [[ 72   2   6   1   6   9  10]
- [  3 118  11   2   9   8   2]
- [ 27  17 112  60  43  27  31]
- [ 14   5   4 109   4  10  23]
- [  1   7   1   2  64   3   3]
- [  6   1   0   0   0  51   4]
- [ 18   6   9   2   5  15  57]]
-Node Classification on random seed  3987 -> 0.62
-Confusion Matrix:
- [[ 90   8   1   9   2  10   4]
- [  5 129   1   4  10   1   5]
- [ 28  20 134  35  18  35  32]
- [ 14   5  13  96   5  11  14]
- [  1   6   7   0  57   0   1]
- [  4   1   1   2   4  39   2]
- [ 14   3   7  10   5  22  75]]
-Node Classification on random seed  3988 -> 0.595
-Confusion Matrix:
- [[ 69   0   2   2   8  14  12]
- [  6 127   3   5   5   6   4]
- [ 14  29 126  55  13  20  58]
- [ 15   3  16  99   2   6  24]
- [  0   4   2   4  60   3   4]
- [  5   0   1   2   0  43   7]
- [ 16   6   4   5   7  13  71]]
-Node Classification on random seed  3989 -> 0.606
-Confusion Matrix:
- [[ 67   2   5   7   9  11   9]
- [  5 129  10   1   8   2   7]
- [ 16  40 127  25  28  28  40]
- [  6   3  23  97   4   6  13]
- [  0   6   5   2  64   0   5]
- [  5   2   1   0   0  51   5]
- [  6   1   9  10   4  25  71]]
-Node Classification on random seed  3990 -> 0.598
-Confusion Matrix:
- [[ 66   7   7   8   4  16   1]
- [  4 139   2   2   5   0   1]
- [ 17  28 102  36  42  29  62]
- [  6   9  10 125   0   9   7]
- [  0  11   4   0  62   1   6]
- [  6   0   2   1   0  42   6]
- [ 10   1   3  11   9  19  62]]
-Node Classification on random seed  3991 -> 0.591
-Confusion Matrix:
- [[ 67   2   5   5   4   5   2]
- [  3 125   8   5   4   6   2]
- [ 15  15 108  95  36  26  30]
- [ 18   1  15 103   2   8   7]
- [  1   7   4   1  64   1   1]
- [  5   0   3   1   0  53   4]
- [ 11   5   4  15  11  16  71]]
-Node Classification on random seed  3992 -> 0.633
-Confusion Matrix:
- [[ 68   1   7   3   2  15   8]
- [  4 127   5   1   8   4   3]
- [ 16  13 158  26  41  33  32]
- [  6  10  26  83   3   9  11]
- [  2   3   5   4  73   0   2]
- [  3   0   3   3   0  48   1]
- [  9   0   9   7   3  26  76]]
-Node Classification on random seed  3993 -> 0.604
-Confusion Matrix:
- [[ 71   3  14   5   2  16   4]
- [  2 120   6   7   1   1   4]
- [ 21  22 155  36  24  21  36]
- [ 23   5  18  92   5   5  17]
- [  3   9   8   2  49   2   1]
- [  5   2   3   1   0  50   0]
- [ 14   4  16  12   2  14  67]]
-Node Classification on random seed  3994 -> 0.647
-Confusion Matrix:
- [[ 77   4   5   5   3  16   6]
- [  4 144   4   0   5   0   5]
- [ 18  34 144  43  16   8  26]
- [  7   5   9 117   4  11   9]
- [  3   5   3   3  62   0   0]
- [  8   2   2   0   3  39   4]
- [ 21   2  14   1  19  16  64]]
-Node Classification on random seed  3995 -> 0.629
-Confusion Matrix:
- [[ 63   2   3   8   4  14   7]
- [  0 117   2   4  17   7   7]
- [ 24  30 157  48  18  19  31]
- [  4   5  10 114   9   4   8]
- [  0   6   4   1  66   1   1]
- [  3   3   1   9   2  33   5]
- [  6   3  10   8   6  17  79]]
-Node Classification on random seed  3996 -> 0.578
-Confusion Matrix:
- [[ 68   1   0   5   4   8  16]
- [  5 105   1   6  19   0   1]
- [ 25  27 159  34  38  10  35]
- [ 22   8  15  84   4  13  23]
- [  3   2   3   2  57   1   4]
- [  6   1   0   4   0  35   8]
- [ 16   5   7  13  12  15  70]]
-Node Classification on random seed  3997 -> 0.623
-Confusion Matrix:
- [[ 69   3   2   7   3   5   7]
- [ 12 120  19   1   3   3   3]
- [ 29  19 163  39  17   7  44]
- [ 12   2  11 114  10   3  12]
- [  4   0   6   1  53   0   5]
- [ 12   0   0   0   1  47  10]
- [ 19   1  11   9  10  15  57]]
-Node Classification on random seed  3998 -> 0.615
-Confusion Matrix:
- [[ 53   7   4   7   3  13  17]
- [  1 145   4   5   9   3   7]
- [ 21  27 119  44  37  25  36]
- [ 13   4   4 120   1   6  13]
- [  0   7   3   1  57   2   3]
- [  3   0   0   1   0  46   7]
- [  9   2   6   8   5  17  75]]
-Node Classification on random seed  3999 -> 0.575
-Confusion Matrix:
- [[ 64   3  12   3   9  14  10]
- [  3 130   7   4   1   6   3]
- [ 20  35 128  40  22  34  57]
- [  4   6   7  86   4   7  24]
- [  3  10   7   0  57   1   5]
- [  8   0   0   2   1  31  15]
- [  3   2   5   6  10  12  79]]
-Node Classification on random seed  4000 -> 0.627
-Confusion Matrix:
- [[ 78   6   5  12   4  10   1]
- [  5 133   8   4   8   1   2]
- [ 17  23 131  24  27  36  49]
- [  5   9  11 104   4   9  14]
- [  2   2   2   2  54   3   1]
- [  7   0   5   1   1  52   3]
- [  8   1   7  13   4  17  75]]
-Node Classification on random seed  4001 -> 0.634
-Confusion Matrix:
- [[ 67   2   7   5   7  14   7]
- [  7 126   4   0   4   4   2]
- [ 31  37 159  21  14  18  56]
- [  7   1   9 104   2   9  14]
- [  3   5   6   0  56   1   2]
- [  3   1   4   0   3  55   9]
- [ 15   4  10   3   5  10  67]]
-Node Classification on random seed  4002 -> 0.579
-Confusion Matrix:
- [[ 63   1  10  10  14   9   6]
- [  3 126   6   1  10   2   6]
- [ 27  25 125  34  28  28  32]
- [ 14   3  18  94   8   6  20]
- [  1   5   9   3  49   1   2]
- [  9   2   3   3   2  45   1]
- [ 15   3   6  15  10  10  77]]
-Node Classification on random seed  4003 -> 0.626
-Confusion Matrix:
- [[ 59   0   5   4   4   5  11]
- [ 10 139   7   1   2   5   2]
- [ 17  21 159  35  27  17  52]
- [  2   2  18 101  10   8  10]
- [  2   3   3   5  55   1   3]
- [  3   2   4   2   0  50   5]
- [ 13   5  15  17   8   8  63]]
-Node Classification on random seed  4004 -> 0.645
-Confusion Matrix:
- [[ 75   0   5   4   3   6  17]
- [  2 126   7   4  15   4   7]
- [ 21  23 144  37  25  16  41]
- [ 11   2  11 105   9   8  15]
- [  1   2   1   1  61   2   3]
- [  5   3   2   2   1  53   4]
- [ 11   1   1   8   3  11  81]]
-Node Classification on random seed  4005 -> 0.617
-Confusion Matrix:
- [[ 83   2   3   7   7   4  16]
- [  2 122   6   3   5   5   2]
- [ 16  23 126  36  30  29  47]
- [  7   1  10 107   2   7  34]
- [  0   9   4   0  53   2   2]
- [ 16   1   1   0   2  36   9]
- [  7   2   8   5   1  10  90]]
-Node Classification on random seed  4006 -> 0.587
-Confusion Matrix:
- [[ 64   9   4   6   9  12   3]
- [  1 117  13   2   6   6   3]
- [ 18  36 137  34  23  38  31]
- [ 15   2  17  97   4   9  11]
- [  1   3   4   2  57   5   3]
- [  7   2   0   5   0  45  10]
- [ 14   2   8   7   8  20  70]]
-Node Classification on random seed  4007 -> 0.622
-Confusion Matrix:
- [[ 72   1   1   4   6   3  13]
- [  9 125   6   0   3   3   4]
- [ 31  21 162  26  26   7  51]
- [  3   2  17 102   5  10  11]
- [  3  13   9   3  53   1   8]
- [  3   2   0   1   2  35  10]
- [ 14   6  13  11   8   8  73]]
-Node Classification on random seed  4008 -> 0.617
-Confusion Matrix:
- [[ 75   3   3   9   4   9   8]
- [  4 118   6   4   8   6   5]
- [ 27  22 149  43  11  10  52]
- [ 10   1  18 108   5   5  17]
- [  1   6   4   1  61   2   4]
- [  4   5   5   2   1  38   3]
- [ 12   3   8   7  12  13  68]]
-Node Classification on random seed  4009 -> 0.638
-Confusion Matrix:
- [[ 70   4   2   0   2   7  16]
- [ 11 147   3   1   4   0   0]
- [ 11  29 140  29  17  38  40]
- [  8   6  10 102   2   6  21]
- [  0   7   4   5  57   1   2]
- [  5   4   2   0   3  46   1]
- [ 10   3   9  17   6  16  76]]
-Node Classification on random seed  4010 -> 0.632
-Confusion Matrix:
- [[ 71   3   3   0   2  11  13]
- [  2 150   0   1   7   2   2]
- [ 27  24 147  24  16  32  38]
- [ 13   6  24  89   7   9  10]
- [  0   4   2   6  54   2   2]
- [  8   2   4   0   0  51  11]
- [ 14   8   7   4   5  13  70]]
-Node Classification on random seed  4011 -> 0.605
-Confusion Matrix:
- [[ 79   4   1   8   5  16   4]
- [ 15 105   5   1  12   8   3]
- [ 31  10 141  30  18  31  56]
- [  8   6  10 114   2   7  17]
- [  1   3   6   1  58   0   1]
- [  6   2   2   5   0  38   4]
- [  9   4  12   7  10  14  70]]
-Node Classification on random seed  4012 -> 0.557
-Confusion Matrix:
- [[ 56   4   7   7   2  15  15]
- [  3 143   4   3   5   3   4]
- [ 16  50 106  27  22  26  46]
- [  2   9   7  83   6  13  29]
- [  0   7   8   1  56   0   4]
- [  5   1   9   0   0  43  10]
- [ 14  11  24   7   3  14  70]]
-Node Classification on random seed  4013 -> 0.588
-Confusion Matrix:
- [[ 76   4  10  12   7   8   7]
- [  3 142   6   0  10   2   1]
- [ 29  27 117  54  31  18  46]
- [ 10   9  14  90   3   6  13]
- [  3   9   3   0  55   0   1]
- [  2   0   3   0   0  41   3]
- [ 15   4  12  10   5  12  67]]
-Node Classification on random seed  4014 -> 0.616
-Confusion Matrix:
- [[ 63   4   3   1   3   9  15]
- [  7 130  14   1  10   3   5]
- [ 27  27 146  44  23  16  25]
- [ 14   8  11 115   8   7   8]
- [  1   5   2   6  47   1   4]
- [  7   3   1   0   0  52   1]
- [ 18   8   6   6   5  17  63]]
-Node Classification on random seed  4015 -> 0.596
-Confusion Matrix:
- [[ 76   7   1   8   3   8  14]
- [  8 132   4   3   8   3   5]
- [ 27  25 128  35  19  22  40]
- [ 11  10  19  97   8   7  13]
- [  2   8   2   1  52   0   1]
- [  5   0   0   2   5  41  14]
- [  6   4   6   8  17  15  70]]
-Node Classification on random seed  4016 -> 0.634
-Confusion Matrix:
- [[ 79   2   0   2   6  15   4]
- [  3 113   3   0   8   5   0]
- [ 31  29 146  19  28  25  42]
- [ 15   6   9 104   4   3  13]
- [  0   7   4   1  59   3   8]
- [  8   0   3   2   0  49   2]
- [ 18   3   0   4  13  18  84]]
-Node Classification on random seed  4017 -> 0.611
-Confusion Matrix:
- [[ 59   5   9   5   3  18  11]
- [  7 143   4   5   3   1   1]
- [ 15  29 120  49  29  23  52]
- [  8   1   7 103   9   4  17]
- [  0   7   0   1  49   1   0]
- [  3   1   0   8   0  49   8]
- [ 12   1   6   6   5  15  88]]
-Node Classification on random seed  4018 -> 0.608
-Confusion Matrix:
- [[ 66   1   4   8   4   4  14]
- [  6 109   5   7  12   5   2]
- [ 31  23 144  32  12  34  42]
- [ 15   3  18 102   2   3   8]
- [  2   1   3   2  71   1   2]
- [  9   0   2   5   1  42   9]
- [ 16   2  12   7   5  18  74]]
-Node Classification on random seed  4019 -> 0.596
-Confusion Matrix:
- [[ 51   0  10  10   2  19  17]
- [  3 117   7   4   4   3   2]
- [ 15  17 170  35  43  28  40]
- [  6   4  12 101   2   8  16]
- [  3   3   4   8  60   0   2]
- [  4   0   5   4   2  36  12]
- [  4   0  11  13   7  15  61]]
-Node Classification on random seed  4020 -> 0.641
-Confusion Matrix:
- [[ 77   0   4   2   4  13   8]
- [  3 118  10   1   9   2   3]
- [ 20  16 143  24  24  35  38]
- [ 20   5   7 112   7   2  12]
- [  4   3   3   1  57   1   2]
- [  5   0   2   3   1  51   7]
- [ 12   5   9   3   5  24  83]]
-Node Classification on random seed  4021 -> 0.599
-Confusion Matrix:
- [[ 82   5   4  10  10  11   2]
- [  7 111   3   2  14   4   2]
- [ 27  27 167  20  28  25  29]
- [ 13   1  14  91   5   2  17]
- [  3   3   4   2  57   0   8]
- [  8   3   0   6   2  40   0]
- [ 16   6  13  20   5  20  51]]
-Node Classification on random seed  4022 -> 0.579
-Confusion Matrix:
- [[ 70   7   3   9   1  14   7]
- [  3 116   5   9   6   4   8]
- [ 38  32 110  36  20  28  37]
- [ 13   3  19 111   3   6   8]
- [  1   6   3   0  63   3   2]
- [  9   2   2   4   0  29   6]
- [ 17   6   6  12   5  18  80]]
-Node Classification on random seed  4023 -> 0.615
-Confusion Matrix:
- [[ 63   3   5   2  14  12  10]
- [  4 125   5   1  12   2   6]
- [ 21  14 169  31  25  24  37]
- [  8   1  23  94   8   7  25]
- [  1   4   3   1  50   2   0]
- [  2   4   8   0   0  41   6]
- [ 15   5  11   3   6  14  73]]
-Node Classification on random seed  4024 -> 0.59
-Confusion Matrix:
- [[ 68   8   5   4   2  13  12]
- [  1 128  12   0  11   2   3]
- [ 31  27 120  40  41  28  38]
- [ 11   7   9 104   2   1  25]
- [  1   3   5   5  54   0   2]
- [  8   0   0   1   4  46   1]
- [ 15   7   3   2   8  12  70]]
-Node Classification on random seed  4025 -> 0.605
-Confusion Matrix:
- [[ 68   5   7   5   1   6  15]
- [  6 134  10   1   7   3   2]
- [ 32  15 118  42  33  19  50]
- [  8   6   9 112   6   5   9]
- [  2   4   3   1  63   0   6]
- [  9   1   3   1   0  37   9]
- [ 19   3  11   8   4   9  73]]
-Node Classification on random seed  4026 -> 0.613
-Confusion Matrix:
- [[ 51   6   9   9   3  10  21]
- [  3 126   4   5  12   1  13]
- [ 18  15 136  45  22  15  56]
- [ 12   4  18 103   1   4  12]
- [  4   4   2   1  64   2   4]
- [  6   0   5   3   1  40   7]
- [  2   1   4   2  12   9  93]]
-Node Classification on random seed  4027 -> 0.615
-Confusion Matrix:
- [[ 57   6   6   3   5  27   5]
- [  6 135   8   2  10   2   4]
- [ 28  17 143  35  25  35  25]
- [ 12   3  23 105   3   7  11]
- [  1   8   3   4  54   1   3]
- [  5   1   0   1   0  46   4]
- [ 11   3   5   5   7  15  75]]
-Node Classification on random seed  4028 -> 0.647
-Confusion Matrix:
- [[ 93   1   7   5   5   4   5]
- [  2 120   3   3  11   4   2]
- [ 19  21 150  32  45  15  23]
- [  7   4  13 101  10   7  12]
- [  3   9   1   1  60   1   1]
- [  2   0   5   0   4  49   8]
- [ 12   8   5  13   9  11  74]]
-Node Classification on random seed  4029 -> 0.657
-Confusion Matrix:
- [[ 76   1   3   0   4  11  16]
- [  2 136   2   2   9   6   2]
- [ 25  26 166  19  27  25  35]
- [  1   3  13 108   3   5  11]
- [  3  11   1   1  62   1   0]
- [  5   1   2   1   7  43   4]
- [  7   4  11   5   5  23  66]]
-Node Classification on random seed  4030 -> 0.63
-Confusion Matrix:
- [[ 67   1   8   2   0  21   9]
- [ 10 116   3   1  13   2   5]
- [ 21  22 179  22  27  31  36]
- [  6   5   7  97   2  14  18]
- [  2   2   8   2  58   2   0]
- [  5   0   3   2   1  34  13]
- [  9   2   6   5   8  14  79]]
-Node Classification on random seed  4031 -> 0.548
-Confusion Matrix:
- [[ 77   3   2   2   3   9  15]
- [  6 117   6   4   8   4   4]
- [ 44  16 101  40  33  28  33]
- [ 18   3  23  76  11   2  34]
- [  1   7   2   2  64   0   4]
- [  6   1   5   0   0  39  17]
- [ 19   0  14  10  11   2  74]]
-Node Classification on random seed  4032 -> 0.617
-Confusion Matrix:
- [[ 75   4   4   3   2   5  13]
- [  0 119   4   5   7   3  13]
- [ 20  18 153  31  20  20  46]
- [ 15  10  15 105   6   5  14]
- [  1  10   2   0  57   0   4]
- [  8   3   2   2   0  40  15]
- [  9   9   6   3  11  15  68]]
-Node Classification on random seed  4033 -> 0.631
-Confusion Matrix:
- [[ 85   2   7   4   2   8   5]
- [  3 124   2   2   6   1   6]
- [ 24  13 145  20  41  29  47]
- [  8   2  18 108  10  11  11]
- [  0   4   4   1  55   2   1]
- [  8   1   6   2   1  36   7]
- [ 10   4  10   6  10  10  78]]
-Node Classification on random seed  4034 -> 0.566
-Confusion Matrix:
- [[ 77   1   4   7   6   5  10]
- [  4 126   2   8   6   2   2]
- [ 36  20 115  37  44  19  45]
- [ 14   3  13  91  11  12  11]
- [  1   7   5   2  54   0   1]
- [  5   0   5   8   3  41   6]
- [ 13   4   9   8  20  15  62]]
-Node Classification on random seed  4035 -> 0.635
-Confusion Matrix:
- [[ 80   1   5   6   3  13   6]
- [  4 140  11   2   2   0   2]
- [ 21  26 118  41  29  34  22]
- [  2   6  20 100   3   9  11]
- [  0  11   4   3  54   0   2]
- [  3   5  10   0   1  48   0]
- [ 11   4   5   5   7  15  95]]
-Node Classification on random seed  4036 -> 0.576
-Confusion Matrix:
- [[ 65   4   5   6   1  14   9]
- [  4 128   4   6  14   5   2]
- [ 11  14  96  61  37  31  56]
- [  7   4  13 107   5   7  13]
- [  1   7   6   1  62   2   5]
- [  8   0   2   3   0  47   5]
- [ 12   3  21   2   7   6  71]]
-Node Classification on random seed  4037 -> 0.564
-Confusion Matrix:
- [[ 60   5  17   2   1  22   7]
- [  3 141   5   2   6   4   1]
- [ 15  25 112  71  37  31  32]
- [  4   2  18  98   5   5  11]
- [  3   4   4   6  51   1   3]
- [  4   1   3   1   3  37   6]
- [  7   2  17  10  15  15  65]]
-Node Classification on random seed  4038 -> 0.604
-Confusion Matrix:
- [[ 71   1   3   4   1  15   7]
- [  3 127   8   1   8   0   3]
- [ 39  15 137  44  38  16  30]
- [  8   6  12 121   6   6  13]
- [  3  12   6   0  49   2   2]
- [  4   3   1   2   0  27  22]
- [ 16   2  12   4  11   7  72]]
-Node Classification on random seed  4039 -> 0.639
-Confusion Matrix:
- [[ 65   7   0   6   4  19  10]
- [  3 123   5   2  15   3   3]
- [ 21  10 165  24  24  13  39]
- [ 15   4  16 116   5   8  18]
- [  1   4   2   2  67   0   1]
- [  3   0   3   2   0  43  11]
- [  8   1   4  10  12  23  60]]
-Node Classification on random seed  4040 -> 0.634
-Confusion Matrix:
- [[ 73   1   3   3   4  18   5]
- [  5 130   5   3   5   7   2]
- [ 21  25 156  31  16  18  42]
- [ 15   4  17 100   6   9  11]
- [  0   6   6   0  64   4   2]
- [  7   0   3   1   0  34   8]
- [ 13   2   4  10   2  22  77]]
-Node Classification on random seed  4041 -> 0.639
-Confusion Matrix:
- [[ 73   2   1   6   2  12   4]
- [ 10 137   8   3   5   1   4]
- [ 18  27 151  19  16  28  50]
- [  2  10  21 103   0  12  14]
- [  4   7   3   4  61   1   2]
- [  4   1   1   0   0  51   4]
- [  7   7  17   3   3  18  63]]
-Node Classification on random seed  4042 -> 0.613
-Confusion Matrix:
- [[ 54   3   9   4   5  11  13]
- [  3 132   5   2   4   1   4]
- [ 22  23 141  28  29  31  53]
- [ 12   3  11 112   3   7  17]
- [  0   6   4   2  56   0   1]
- [  1   0   1   3   1  48  10]
- [  4   4   9   9  15  14  70]]
-Node Classification on random seed  4043 -> 0.665
-Confusion Matrix:
- [[ 69   2   3   1   5  11  13]
- [  5 131   6   2  11   2   4]
- [ 34  20 187  20  10  25  25]
- [  9   5  12 107   7   4   7]
- [  4   6   4   0  58   0   3]
- [  6   1   2   4   1  38   8]
- [ 18   3   3   8  11  10  75]]
-Node Classification on random seed  4044 -> 0.567
-Confusion Matrix:
- [[ 66   2   3   6   2  13   6]
- [  4 121  12   1   9   1   7]
- [ 36  33 114  47  36  32  35]
- [  9   9  15  95   4  12   3]
- [  0   6   4   2  61   0   3]
- [  2   0  10   3   0  36   8]
- [  9   2   8  17   6  16  74]]
-Node Classification on random seed  4045 -> 0.634
-Confusion Matrix:
- [[ 68   2   1   6   3   7   5]
- [  8 124  10   3  14   1   7]
- [ 28  25 159  36  25  29  28]
- [ 10   6  10  99   4   5  12]
- [  2   3   5   1  60   1   0]
- [  7   0   2   1   1  49   2]
- [ 13   6  13   5   5  14  75]]
-Node Classification on random seed  4046 -> 0.59
-Confusion Matrix:
- [[ 71   0   4   1   4  23  10]
- [  4 127   6   2   8   4   2]
- [ 32  19 120  30  40  26  44]
- [ 13   2  17  84   2  13  22]
- [  2   4   3   1  66   0   5]
- [  1   1   3   0   2  45   3]
- [ 12   3  12   1  10  19  77]]
-Node Classification on random seed  4047 -> 0.628
-Confusion Matrix:
- [[ 75   4   0   8   2   9   9]
- [  3 128  10   5   7   2   2]
- [ 22  24 150  28  30  12  51]
- [  7   2  10  93   4   4  20]
- [  1   5   5   0  59   1   2]
- [  5   1   4   5   0  39   1]
- [ 14   3  10  17   8  15  84]]
-Node Classification on random seed  4048 -> 0.623
-Confusion Matrix:
- [[ 84   3   5   2   3   9   2]
- [  9 128   6   0  11   2   1]
- [ 14  20 143  64  32  14  14]
- [ 15   3  23 100   8   7   5]
- [  1   7   7   2  56   1   2]
- [  5   3   4   4   1  53   4]
- [ 14   2  12   6   9  21  59]]
-Node Classification on random seed  4049 -> 0.598
-Confusion Matrix:
- [[ 67   1   9   9   3   8  11]
- [  7 109  12   2  13   6   1]
- [ 32  29 118  37  26  28  31]
- [  4   7  10 103   5   4  24]
- [  9   0   1   4  71   1   2]
- [  7   2   3   0   2  46   4]
- [ 13   4   4   6   7  14  84]]
-Node Classification on random seed  4050 -> 0.6
-Confusion Matrix:
- [[ 66   1   0   2   3  12  13]
- [  4 131  11   1   6   2   3]
- [ 13  21 140  26  33  38  51]
- [  7   1  19 100  13   7  14]
- [  2  12   4   0  55   1   2]
- [ 13   1   4   1   0  42   0]
- [ 13   3   5  13  12  13  66]]
-Node Classification on random seed  4051 -> 0.625
-Confusion Matrix:
- [[ 68   2   8   4   3  21  10]
- [  2 136   2   2  12   0   0]
- [ 32  20 144  46  31  20  25]
- [ 12   3  18  84   8   9  11]
- [  2   6   2   2  64   1   4]
- [  3   1   0   0   1  47   3]
- [ 22   2   5   4   4  12  82]]
-Node Classification on random seed  4052 -> 0.622
-Confusion Matrix:
- [[ 62   0   7   3   5   2  17]
- [  3 132   7  11  18   1   6]
- [ 14  14 139  30  13  13  56]
- [ 18   5  15 111  13   3  11]
- [  0   2   5   3  61   0   4]
- [  6   1   2   1   3  36  11]
- [ 13   7   5  14   6  10  81]]
-Node Classification on random seed  4053 -> 0.609
-Confusion Matrix:
- [[ 66   4   9   9   4  13   3]
- [  3 132   3   3  13   4   2]
- [ 11  17 149  38  23  29  51]
- [  9   1  24 103   2   8  10]
- [  0  11   3   0  61   0   2]
- [  4   2   2   2   6  32   3]
- [  5   2   2  10  13  31  66]]
-Node Classification on random seed  4054 -> 0.614
-Confusion Matrix:
- [[ 70   3  10   5   9   3   4]
- [  5 123   4   3   6   2   4]
- [ 25  18 121  53  27  30  36]
- [  8   3  14 117   8   4   6]
- [  0   4   2   0  73   1   5]
- [  8   1   9   5   0  42   4]
- [ 10   6  14   6   9  12  68]]
-Node Classification on random seed  4055 -> 0.644
-Confusion Matrix:
- [[ 77   1  10   2   4   7  11]
- [  3 118  13   3   6   1  12]
- [ 22  18 168  22  31  25  19]
- [ 13   4  25  89   7   4  16]
- [  2   5   3   3  57   2   6]
- [  6   1   2   1   0  49   7]
- [ 12   3   9   3   2  10  86]]
-Node Classification on random seed  4056 -> 0.593
-Confusion Matrix:
- [[ 68   0  13   8   1   9   8]
- [  3 143   3   3   3   1   1]
- [ 30  23 110  37  25  27  58]
- [ 12   6  16 103   1   1  20]
- [  1   9   3   3  56   1   7]
- [  4   4   1   0   0  44   6]
- [ 10   7  19   5   8  10  69]]
-Node Classification on random seed  4057 -> 0.644
-Confusion Matrix:
- [[ 63   3   2   6   4  17  16]
- [  5 120   4   2  10   3   3]
- [ 13  17 176  33  25  33  26]
- [ 17   6   6 112   3   4  18]
- [  1   5   3   0  54   1   1]
- [  6   0   1   1   0  38  10]
- [  9   4  13   6   4  15  81]]
-Node Classification on random seed  4058 -> 0.628
-Confusion Matrix:
- [[ 77   2   8   4   1  11   2]
- [  1 144   6   5   5   3   2]
- [ 22  24 142  30  16  30  55]
- [ 12   5  12  93   5  11   7]
- [  0  11   1   0  52   5   5]
- [  4   2   2   0   0  50   6]
- [ 21   3  12   7   2  12  70]]
-Node Classification on random seed  4059 -> 0.629
-Confusion Matrix:
- [[ 81   1   2   5   4  12   2]
- [ 10 117   4   0  11   6   2]
- [ 23  18 156  34  27  26  35]
- [ 10   1  10  94   9   7  21]
- [  2   5   4   4  58   1   2]
- [  9   2   3   1   2  54   1]
- [ 19   1  15   7   4   9  69]]
-Node Classification on random seed  4060 -> 0.609
-Confusion Matrix:
- [[ 68   4   9   2   4  10  19]
- [  3 144   5   4   5   3   4]
- [ 22  33 117  47  20  30  32]
- [  7   3  12 107  10   5   9]
- [  0   8   1   3  67   2   1]
- [  6   2   1   0   2  29  10]
- [ 13   7  10   7   5  11  77]]
-Node Classification on random seed  4061 -> 0.635
-Confusion Matrix:
- [[ 83   1   5   6   1   8   5]
- [  5 123   5   1  11   1   8]
- [ 19  21 130  41  22  37  33]
- [ 13   5   5 110  10   5   7]
- [  0   3   1   1  68   2   7]
- [  6   3   2   0   2  45   6]
- [ 22   0   8  13   5   9  76]]
-Node Classification on random seed  4062 -> 0.644
-Confusion Matrix:
- [[ 72   1   1   7   0  12  15]
- [  7 125   4   2   2   0  13]
- [ 35  29 165  27  13  16  24]
- [ 16   8   5 109   4  14  16]
- [  1  14   2   0  52   0   2]
- [ 10   2   0   0   1  50   4]
- [ 18   7   1   2   6  15  71]]
-Node Classification on random seed  4063 -> 0.622
-Confusion Matrix:
- [[ 59   3   1   3   6  11  11]
- [  9 132   6   4   6   4   4]
- [ 23  16 147  29  20  26  53]
- [ 15   5  15 108   3   2  10]
- [  2  14   5   2  53   0   1]
- [  7   1   2   4   2  46   4]
- [  8   3   7   5   3  23  77]]
-Node Classification on random seed  4064 -> 0.631
-Confusion Matrix:
- [[ 76   9   4   3   2   6   7]
- [  6 119   2   3   9   5   2]
- [ 13  22 163  40  18  30  27]
- [  9   5  20  91   4   2  11]
- [  3  10  10   0  62   2   2]
- [ 10   4   3   3   1  43   7]
- [  4   4  11  10   5  21  77]]
-Node Classification on random seed  4065 -> 0.587
-Confusion Matrix:
- [[ 69   4   3   6   3  10  20]
- [  1 141   1   7   9   2   6]
- [ 23  23 115  51  37  29  30]
- [ 12   3  10  93   7  15   9]
- [  1   8   2   1  62   2   0]
- [  1   2   0   5   8  33   6]
- [  9   3  11   4   6  23  74]]
-Node Classification on random seed  4066 -> 0.649
-Confusion Matrix:
- [[ 70   4   2   2   2  15   8]
- [  5 125   3   1  11   0   8]
- [ 10  22 149  23  36  18  41]
- [  7   2  20 112   8   6  19]
- [  1   7   4   0  64   4   4]
- [  3   0   3   5   0  40   6]
- [  8   2   3   8   5  15  89]]
-Node Classification on random seed  4067 -> 0.687
-Confusion Matrix:
- [[ 66   7   6   2   3  15  10]
- [  5 140   4   0   7   0   2]
- [  8  19 170  20  26  14  43]
- [ 10   4  14 114   6   6  13]
- [  1   6   4   0  71   1   0]
- [  9   2   0   0   1  39   3]
- [ 10   3   5   5   7  12  87]]
-Node Classification on random seed  4068 -> 0.565
-Confusion Matrix:
- [[ 60   1   8   5   4   5  16]
- [  6 127   9   4   6   2   0]
- [ 51  27 116  38  30  26  25]
- [ 19   5  14 112  11   3   6]
- [  3   6   7   1  57   0   1]
- [ 10   0   5   2   1  41   2]
- [ 22   5  16   8  10  15  52]]
-Node Classification on random seed  4069 -> 0.623
-Confusion Matrix:
- [[ 82   5   6   5   2   5  15]
- [  9 135  12   1   4   3   4]
- [ 19  25 142  37  27  16  37]
- [  3   5  21  92   7  15  11]
- [  4   4   2   2  69   2   3]
- [  5   0   3   0   1  47   7]
- [  7   5  11   6   4  17  56]]
-Node Classification on random seed  4070 -> 0.638
-Confusion Matrix:
- [[ 70   2   2   4   2   9  10]
- [  6 123   3   1  12   1   4]
- [ 14  30 147  33  17  21  47]
- [ 12   7  16 118   2   5   7]
- [  1   5   7   6  68   1   1]
- [  3   0   3   4   0  48   7]
- [  5   6   7  15  12  12  64]]
-Node Classification on random seed  4071 -> 0.648
-Confusion Matrix:
- [[ 72   1   1   7   2   9   6]
- [  5 125   6   0   7   5   1]
- [ 28  16 153  25  19  23  47]
- [  9   2   8 113  10   5  24]
- [  0  10   5   1  70   1   2]
- [  8   3   4   0   0  44   7]
- [ 12   3   3   2   9  16  71]]
-Node Classification on random seed  4072 -> 0.631
-Confusion Matrix:
- [[ 73   3   1   5  10  12   7]
- [  3 138   8   2  10   6   3]
- [ 31  22 135  26  21  30  36]
- [  7   4   8 109   7   3  18]
- [  3   5   3   1  60   0   2]
- [  6   0   2   3   0  47   0]
- [ 13   6   6   3  11  22  69]]
-Node Classification on random seed  4073 -> 0.621
-Confusion Matrix:
- [[ 66   6   4   7   5   7  10]
- [  5 111  15   1   2  11   8]
- [ 18   9 144  24  65  17  37]
- [ 15   6  22 103   4   6   9]
- [  0   2   3   0  68   2   2]
- [  2   1   0   2   0  52   9]
- [ 13   1   5   4  11   9  77]]
-Node Classification on random seed  4074 -> 0.588
-Confusion Matrix:
- [[ 90   4   4   4   5   7  10]
- [  2  95   1   5  13   7   4]
- [ 15  26 129  33  50  44  34]
- [ 10   4  14  97   7   7   7]
- [  1   5   5   1  63   1   3]
- [  8   1   1   1   0  40   9]
- [  9   5   7   5   8  25  74]]
-Node Classification on random seed  4075 -> 0.566
-Confusion Matrix:
- [[ 60   7   4   8  11  19  14]
- [  5 113   5   0  11   2   2]
- [ 25  27 115  34  16  18  60]
- [ 12   3  14 100   5  15  17]
- [  0   4   7   0  66   0   1]
- [  6   1   2   2   3  41   3]
- [ 13   5  13   7  14  19  71]]
-Node Classification on random seed  4076 -> 0.644
-Confusion Matrix:
- [[ 78   3   4   1   6   7  16]
- [  2 131   6   1   4   2   2]
- [ 23  27 155  39  15  18  40]
- [ 15   5  14  97  10   3  14]
- [  0   6   4   0  58   1   2]
- [  5   4   4   0   0  45   3]
- [  8   5  10   6   6  15  80]]
-Node Classification on random seed  4077 -> 0.627
-Confusion Matrix:
- [[ 79   3   0   8   2  15   3]
- [  4 120   2   1  11   6   7]
- [ 26  16 134  26  25  42  48]
- [  5   1   6  95  11   7  14]
- [  4   8   4   1  61   5   5]
- [  1   0   3   5   0  54   8]
- [ 11   2   6   4   3  14  84]]
-Node Classification on random seed  4078 -> 0.628
-Confusion Matrix:
- [[ 67   3   8   3   2  10  19]
- [  6 125   8   0   9   2   4]
- [ 11  16 139  33  27  30  36]
- [ 25   7  20 103   3   7   6]
- [  2   7   4   1  69   0   3]
- [  1   3   3   3   2  42   2]
- [ 18   2   3   4   8  11  83]]
-Node Classification on random seed  4079 -> 0.627
-Confusion Matrix:
- [[ 65   2   3   6   6  15   8]
- [  5 132   8   4  13   5   4]
- [ 25  20 132  25  28  26  44]
- [ 13   3  22 103   2   1  12]
- [  1   6   1   3  59   1   3]
- [  5   0   1   0   0  46   8]
- [ 13   2   6   7   3  13  90]]
-Node Classification on random seed  4080 -> 0.603
-Confusion Matrix:
- [[ 49   3  11   8   4  15  10]
- [  3 127   4   5  15   5   1]
- [ 21  19 146  37  15  25  38]
- [ 11   5  40  98   3   5  11]
- [  0   6   0   3  59   1   6]
- [  6   3   5   1   1  53   2]
- [  6   5  10  10   3  15  71]]
-Node Classification on random seed  4081 -> 0.594
-Confusion Matrix:
- [[ 64   0   3  12   6  16  10]
- [  5 122   4   3  13   0   5]
- [ 25  13 142  29  25  30  50]
- [ 13   4  25  79  16   8  18]
- [  2   7   2   1  55   2   2]
- [  5   1   0   3   1  48   9]
- [ 14   6   6   0   8   4  84]]
-Node Classification on random seed  4082 -> 0.644
-Confusion Matrix:
- [[ 64   7   6   4   1   7   7]
- [  1 130   7   5   8   1   5]
- [ 30  15 164  30  24  22  43]
- [  9   0  13  97   6   5  11]
- [  0   7   2   0  67   1   3]
- [ 10   1   3   0   0  43   5]
- [ 15   6  14   7   8   7  79]]
-Node Classification on random seed  4083 -> 0.588
-Confusion Matrix:
- [[ 81   1   7   9   4   7   1]
- [  4 143   6   0   5   2   1]
- [ 39  28 123  39  21  28  49]
- [ 14   2  17  81   8   3  17]
- [  0   2   2   2  68   1   2]
- [ 18   2   2   3   1  32   4]
- [ 20   1  20   3   4  13  60]]
-Node Classification on random seed  4084 -> 0.581
-Confusion Matrix:
- [[ 56   5   5   6   4  15   5]
- [  9 122   3   1  14   2   6]
- [ 27  41 114  31  32  24  38]
- [ 14   5  13 105   2   7  11]
- [  1   6  10   3  62   0   3]
- [ 12   0  12   4   2  36   1]
- [ 18   6  10   5   1   5  86]]
-Node Classification on random seed  4085 -> 0.628
-Confusion Matrix:
- [[ 71   5   3   3   2  12   7]
- [  4 150   4   2   6   0   5]
- [ 28  17 131  47  22  31  29]
- [ 14   1  15 102   8  11   9]
- [  6  10   4   3  57   1   2]
- [  5   1   4   0   1  47   3]
- [ 10   3  12   2   0  20  70]]
-Node Classification on random seed  4086 -> 0.608
-Confusion Matrix:
- [[ 60   1   5   7   4  14   7]
- [  4 115  18   1   8   3   2]
- [ 44  15 123  26  39  20  39]
- [ 15   4  11 111   7   4   3]
- [  1   3   4   0  65   2   0]
- [  6   1   8   2   0  50   6]
- [ 18   4  12   7   7  10  84]]
-Node Classification on random seed  4087 -> 0.639
-Confusion Matrix:
- [[ 78   4   4   1   5  10   8]
- [  3 135   5   6   6   1   2]
- [ 29  18 132  39  22  17  51]
- [  7   5  16  98   4   8  16]
- [  0   7   2   3  64   3   4]
- [  8   1   3   0   0  41   3]
- [ 13   2   8   3   7   7  91]]
-Node Classification on random seed  4088 -> 0.602
-Confusion Matrix:
- [[ 54   4   6   8   0   8  16]
- [  3 142   5   5   4   1   4]
- [ 28  21 133  31  47  23  37]
- [ 14   4  23  91   5   3   9]
- [  5   5   3   2  61   1   2]
- [  0   4   0   4   7  40   7]
- [ 11   3   9   6   7  13  81]]
-Node Classification on random seed  4089 -> 0.6
-Confusion Matrix:
- [[ 61   4   6  10   2  14  12]
- [  8 135   6   2   5   3   5]
- [ 29  27 140  37  27  20  48]
- [ 14   5  19  97   3  10   4]
- [  2   5   2   1  57   0   4]
- [  7   2   1   5   1  37   2]
- [ 12   5   4   9   4  14  73]]
-Node Classification on random seed  4090 -> 0.588
-Confusion Matrix:
- [[ 61   6   4   3   6  11   5]
- [  9 125   3   2  10   2   9]
- [ 29  32 139  55  23  21  28]
- [ 12   1  16  84   4   9  19]
- [  1   8   2   2  50   0   1]
- [  5   0   0   6   0  61   4]
- [ 22   4  11   8   4  15  68]]
-Node Classification on random seed  4091 -> 0.62
-Confusion Matrix:
- [[ 69   4   5   5   6  12  10]
- [  7 117   6   8   2   0   2]
- [ 28  19 144  28  31  21  48]
- [ 11   8  14 110   5   9  11]
- [  0   7   3   2  57   1   2]
- [  7   1   0   0   2  43   2]
- [ 15   3   3   2  19  11  80]]
-Node Classification on random seed  4092 -> 0.597
-Confusion Matrix:
- [[ 59   7  12  11   2  10   8]
- [  3 140   9   4   3   0   1]
- [ 31  32 140  37  21  21  40]
- [ 15   4  14  86   6   5   7]
- [  4   3   5   3  53   1   4]
- [  9   0   5   6   1  52   5]
- [  8   2  17   7  10  10  67]]
-Node Classification on random seed  4093 -> 0.611
-Confusion Matrix:
- [[ 64   1   1   6   2  12  22]
- [  9 124   4   5   3   0   8]
- [ 26  17 128  54  35  24  27]
- [ 12   1  15 108   7   2  13]
- [  3   8   4   0  64   0   2]
- [  4   2   2   3   2  47   7]
- [ 12   3   9   4   5  13  76]]
-Node Classification on random seed  4094 -> 0.627
-Confusion Matrix:
- [[ 90   7   8   7   3  13   8]
- [  8 115   1   1  10   0   7]
- [ 24  12 129  38  18  23  43]
- [ 11   3  18 109   2   7  17]
- [  2   5   4   3  53   2   1]
- [  8   0   2   3   0  40   6]
- [  8   3   7  12   7  11  91]]
-Node Classification on random seed  4095 -> 0.632
-Confusion Matrix:
- [[ 82   1   2   9   1  14   5]
- [  2 141   5   0   6   2   6]
- [ 28  21 140  34  17  30  30]
- [ 26   2  12  84   6  10  18]
- [  3   4   7   6  52   0   2]
- [  4   0   0   1   2  53   5]
- [  6   4  10  10   7  10  80]]
-Node Classification on random seed  4096 -> 0.633
-Confusion Matrix:
- [[ 88   3   6   3   5   3   2]
- [  7 121   6   1   5   1   3]
- [ 22  31 159  14  25  23  30]
- [ 20   6  20  89  14  10  18]
- [  0   9   4   2  63   0   2]
- [  6   2   2   1   0  41   3]
- [ 14   7   7  12   4  14  72]]
-Node Classification on random seed  4097 -> 0.599
-Confusion Matrix:
- [[ 70   2   4   7   3  16  14]
- [ 12 122  10   1  12   5   1]
- [ 16  27 143  33  16  27  34]
- [  7   2  26  85   4  12  10]
- [  2   9   3   2  61   0   2]
- [  0  10   4   1   1  44   7]
- [ 12   4  10   7  10  16  74]]
-Node Classification on random seed  4098 -> 0.62
-Confusion Matrix:
- [[ 83   3   7   0   7  17   1]
- [  6 116   8   2   5   5   4]
- [ 34  18 139  27  28  23  36]
- [ 20   3  11 103   2  13  10]
- [  0   7   2   0  65   0   2]
- [  8   1   7   1   1  46   1]
- [ 16   3   5   1   8  27  68]]
-Node Classification on random seed  4099 -> 0.631
-Confusion Matrix:
- [[ 74   6   4   4   3  18  13]
- [  5 129   1   2   7   1   4]
- [ 28  22 161  33  28  20  29]
- [ 16   6  22 109   5   4   4]
- [  2   7   2   2  58   0   0]
- [  3   2   4   1   1  41   4]
- [ 13   8   5  11   7  12  59]]
-Node Classification on random seed  4100 -> 0.608
-Confusion Matrix:
- [[ 80   8   1   2   4   9  10]
- [  4 140   4   3   3   3   0]
- [ 13  39 145  45  22  28  38]
- [ 18   9  14  78   8  13  14]
- [  0   6   6   0  52   1   2]
- [  2   1   1   0   0  35  14]
- [ 13   7   9   4   5   9  78]]
-Node Classification on random seed  4101 -> 0.629
-Confusion Matrix:
- [[ 65   5   4   2   3   5  15]
- [  2 150   1   1   7   2   2]
- [ 35  24 129  38  16  17  29]
- [  9   5  19 119   2   8  15]
- [  0   9   7   3  55   1   4]
- [ 12   1   2   1   1  47   2]
- [ 24   4  14  10   2   8  64]]
-Node Classification on random seed  4102 -> 0.625
-Confusion Matrix:
- [[ 84   1   1   3   5   7   8]
- [ 10 114   2   4   8   2   6]
- [ 22  18 127  39  37  23  47]
- [ 11   3  14 105   4   4  21]
- [  0   2   5   0  66   1   2]
- [  1   4   5   0   1  45   6]
- [ 14   3   7   2   3  19  84]]
-Node Classification on random seed  4103 -> 0.622
-Confusion Matrix:
- [[ 73   4   8   6   5   7   6]
- [  0 119  10   3   7   4   5]
- [ 15  24 141  34  23  25  55]
- [  9   2  29  96  11   1   5]
- [  0  12   2   0  73   0   5]
- [  2   1   5   5   5  42   3]
- [  5   6   8   3   7  11  78]]
-Node Classification on random seed  4104 -> 0.619
-Confusion Matrix:
- [[ 69   1   7   6   7  13  12]
- [  2 134   4   1   9   4   2]
- [ 13  24 130  29  38  24  46]
- [ 16   3   9 107   5   7  12]
- [  3   3   1   1  69   0   3]
- [  6   1   0   4   2  42   8]
- [ 19   2   8   7   8  11  68]]
-Node Classification on random seed  4105 -> 0.614
-Confusion Matrix:
- [[ 66   2  10   8   2  15   4]
- [  3 131  10   3   4   2   1]
- [ 20  30 139  31  46  27  31]
- [ 11   2  11  93  14  10   9]
- [  0   6   1   1  69   0   4]
- [  1   1   5   3   3  46   0]
- [  3   8  10   5  11  18  70]]
-Node Classification on random seed  4106 -> 0.593
-Confusion Matrix:
- [[ 63   9   5   5   3   9  16]
- [  7 112   5   4  12   3   2]
- [ 18  12 139  29  28  29  60]
- [ 17   3  20  93   4   2  19]
- [  2   6   3   0  62   1   4]
- [  5   2   3   0   1  41   9]
- [ 10   4   6   7   9  14  83]]
-Node Classification on random seed  4107 -> 0.619
-Confusion Matrix:
- [[ 66   0   2   1   3  18   9]
- [  4 125   3   2   3   5   7]
- [  5  35 143  67  27  13  44]
- [ 10   1  11 130   4   6   4]
- [  1   8   3   0  57   0   1]
- [  8   1   3   0   0  53   0]
- [ 20   9   7  15   4  17  45]]
-Node Classification on random seed  4108 -> 0.646
-Confusion Matrix:
- [[ 70   3   0   2   4  12  12]
- [  3 132   3   2   4   3   1]
- [ 29  34 169  25  23  19  39]
- [ 14   4  14  96   4   6  10]
- [  0   7   2   1  58   1   2]
- [  6   2   2   2   1  50   2]
- [ 11   4  11   6   6  18  71]]
-Node Classification on random seed  4109 -> 0.577
-Confusion Matrix:
- [[ 68  11   0  11   5   2  13]
- [  8 138   8   3   6   0   1]
- [ 34  25 132  37  18  21  58]
- [ 15   0  17  93   1   4  10]
- [  2  14   3   2  52   1   3]
- [ 15   0   6   8   0  35   5]
- [ 13   2   9   2   9  21  59]]
-Node Classification on random seed  4110 -> 0.635
-Confusion Matrix:
- [[ 92   0   4   3   2   6   6]
- [  3 123   8   4   1  10   3]
- [ 29  26 143  31  14  16  47]
- [ 13   6  18  83   6  16   7]
- [  1   5   4   1  65   3   1]
- [  6   1   2   1   0  51   3]
- [  8   5   9   9   3  24  78]]
-Node Classification on random seed  4111 -> 0.676
-Confusion Matrix:
- [[ 88   1   8   6   2  11   4]
- [  5 136   1   5   6   3   2]
- [ 17  28 158  33  12  21  26]
- [  5   4  23 107   3   6  15]
- [  0   1   5   0  65   2   0]
- [  8   1   1   0   0  46   3]
- [ 11   4   9   7   7  18  76]]
-Node Classification on random seed  4112 -> 0.644
-Confusion Matrix:
- [[ 72   3   8   5   6  10   4]
- [  3 131  12   4   3   2   4]
- [ 22  21 156  32  16  25  26]
- [ 11   4  16 107   9   3   9]
- [  3   4   4   3  64   2   1]
- [  7   0   5   1   0  37   3]
- [ 17   5  10  10   5  18  77]]
-Node Classification on random seed  4113 -> 0.614
-Confusion Matrix:
- [[ 55   1   5   3   1   4  25]
- [  1 137   6   6   4   5   3]
- [ 17  21 148  59  14  36  33]
- [ 13   1  14 100   1   9  15]
- [  1   8   5   2  50   3   4]
- [  2   0   4   0   0  41   9]
- [ 10   1  16   6   4  14  83]]
-Node Classification on random seed  4114 -> 0.625
-Confusion Matrix:
- [[ 85   1   2   4   3  11   4]
- [  3 124   4   3   8   7   2]
- [ 30  18 152  48  24  18  27]
- [  9   5  17  92   4   6  31]
- [  1   5   0   6  53   0   3]
- [ 10   1   3   1   2  49   3]
- [ 15   0   3   5   5  23  70]]
-Node Classification on random seed  4115 -> 0.603
-Confusion Matrix:
- [[ 66   5   3  11   7   5   6]
- [  6 115   7   9  12   1  10]
- [ 33  26 136  37  28  18  31]
- [ 14   0  16 112   6   6  13]
- [  0   4   3   0  56   1   5]
- [  6   1   3   0   2  45   3]
- [ 14   2  13  11   6  13  73]]
-Node Classification on random seed  4116 -> 0.639
-Confusion Matrix:
- [[ 80   4   8   3   2   5   5]
- [  1 133   3   0   7   7   3]
- [ 25  37 174  26  15  20  35]
- [ 14   9  20 106   4   3   9]
- [  1  10   3   2  49   2   5]
- [  3   3   3   2   1  32   6]
- [ 22   4   8   5   7   9  65]]
-Node Classification on random seed  4117 -> 0.62
-Confusion Matrix:
- [[ 75   3   3   7   3  11   4]
- [  1 131   4   3   5   6   4]
- [ 26  33 141  19  30  27  39]
- [ 16   4  11 100   5  10  15]
- [  0   4   5   2  62   1   2]
- [  8   0   0   1   1  48   3]
- [ 16   2  12  13   8  13  63]]
-Node Classification on random seed  4118 -> 0.609
-Confusion Matrix:
- [[ 64   3   7   7   9  13  10]
- [  5 119  11   0  13   4   9]
- [ 21  15 161  26  18  16  50]
- [ 10   0  18 105   5   8  13]
- [  0   3   6   1  58   1   3]
- [  4   2   8   1   7  39   7]
- [ 17   3   9   7   8  13  63]]
-Node Classification on random seed  4119 -> 0.622
-Confusion Matrix:
- [[ 75   1   9   5   7   7   3]
- [  2 134  10   3   8   2   2]
- [ 24  20 149  35  31  25  40]
- [ 20   3  16  89   3   4  17]
- [  0   5   3   3  58   1   2]
- [  9   0   1   0   1  40   4]
- [ 12   6   7   4   7  16  77]]
-Node Classification on random seed  4120 -> 0.608
-Confusion Matrix:
- [[ 69   1   3   0   1  21  10]
- [  7 141   3   0   6   4   5]
- [ 20  12 119  48  25  31  44]
- [ 19   3  14  99   5   9   5]
- [  0  10   2   1  69   1   4]
- [  5   0   5   0   0  51   4]
- [ 17   2   6  18   2  19  60]]
-Node Classification on random seed  4121 -> 0.603
-Confusion Matrix:
- [[ 67   7  13   3   6  12   0]
- [  5 132   8   0   5   2   2]
- [ 26  24 133  41  34  21  48]
- [ 16   2  11 111  10   3   4]
- [  1  10   3   4  45   0   5]
- [ 10   0   1   0   1  43   7]
- [ 15   7  10   9   3   8  72]]
-Node Classification on random seed  4122 -> 0.572
-Confusion Matrix:
- [[ 59   2   3   6   3  10  10]
- [  9 110   6   3   5   3   8]
- [ 25  30 118  28  37  34  50]
- [ 14   0  15 101  11   6   9]
- [  1   8   4   1  60   3   2]
- [ 10   3   2   5   0  38   3]
- [  9   6   5  12  12  15  86]]
-Node Classification on random seed  4123 -> 0.61
-Confusion Matrix:
- [[ 64   4   5   7   3   7   5]
- [  2 121   4   2  18   2   3]
- [ 22  34 141  31  15  17  43]
- [  6   6  25  97   1   3  22]
- [  0   8   7   5  76   1   2]
- [  3   5   3   0   7  43   1]
- [ 16   4  14   5   6  16  68]]
-Node Classification on random seed  4124 -> 0.596
-Confusion Matrix:
- [[ 66   2   6   1   2  10   9]
- [ 11 112  12   0  21   7   7]
- [ 18  21 156  28  18  25  29]
- [ 10  11  10  91   7   4  24]
- [  1   6   3   3  65   1   3]
- [  7   8   2   0   1  34  11]
- [ 10   3   7   3  14  28  72]]
-Node Classification on random seed  4125 -> 0.581
-Confusion Matrix:
- [[ 63   0   7  12   4  11   7]
- [  4 125   5  12  11   2   8]
- [ 27  22 119  63  31   8  40]
- [ 21   2  10 100   9   8   5]
- [  0   5   2   4  59   3   7]
- [  0   2   9   3   3  44   3]
- [ 11   2   7  16   2  11  71]]
-Node Classification on random seed  4126 -> 0.611
-Confusion Matrix:
- [[ 51   7   4  10   0   7  24]
- [  4 146   1   6   8   0   3]
- [ 22  15 147  36  15  11  57]
- [ 12   6  15 104   2   8   8]
- [  2  13   7   3  47   1   2]
- [  2   6   2   0   1  45  10]
- [  5   6  12  15   6  15  71]]
-Node Classification on random seed  4127 -> 0.568
-Confusion Matrix:
- [[ 65   2   5   2   3  17  21]
- [  6 127   8  10   7   1   3]
- [ 15  14 129  63  27  29  24]
- [ 28   1  19  73  14   4  20]
- [  1   8   2   1  67   2   2]
- [ 13   1   1   0   3  38   1]
- [ 10   2  12   6   7  17  69]]
-Node Classification on random seed  4128 -> 0.601
-Confusion Matrix:
- [[ 62   1   4   5   4  20   3]
- [  8 131   3   1   8   1   4]
- [ 26  33 115  38  44  26  33]
- [  8   3  18 120   4   6   3]
- [  2  13   4   1  61   0   4]
- [  8   2   0   0   1  44   5]
- [  7   3  13   6   8  18  68]]
-Node Classification on random seed  4129 -> 0.637
-Confusion Matrix:
- [[ 70   5   1   0   2   5  18]
- [  2 122   4   0  13   1   7]
- [  8  14 172  26  25  25  48]
- [ 18   8   9  96  12   8  15]
- [  0   6   3   3  66   2   4]
- [ 10   4   0   2   0  36   3]
- [  9   6   8   6   5  18  75]]
-Node Classification on random seed  4130 -> 0.619
-Confusion Matrix:
- [[ 77   2   4   7   1  12  12]
- [  6 124  13   2   3   2   0]
- [ 24  29 140  17  24  19  51]
- [ 15   3  14 100   9   9  12]
- [  4  10   3   2  48   0   2]
- [  7   0   2   3   0  47   8]
- [ 14   4   4   8  11   9  83]]
-Node Classification on random seed  4131 -> 0.61
-Confusion Matrix:
- [[ 64   0   3   2   6  19  14]
- [  8 135   4   6   4   3   8]
- [ 22  20 122  43  33  28  39]
- [ 11   2   8 111   8   7  12]
- [  0   4   1   2  53   1   2]
- [  3   1   0   4   2  44  10]
- [  4   3  12   4   6  21  81]]
-Node Classification on random seed  4132 -> 0.624
-Confusion Matrix:
- [[ 62   2   4   2   2  23   9]
- [  4 117   6   1  13   1  12]
- [ 13  12 135  21  26  22  69]
- [  5   1  21 108   9   7  16]
- [  1   9   6   1  67   0   3]
- [  2   0   2   1   1  44   3]
- [  4   4   9   8   5  16  91]]
-Node Classification on random seed  4133 -> 0.606
-Confusion Matrix:
- [[ 57   1  11   6   4  14   8]
- [  3 141   9   2   1   6   4]
- [ 19  19 144  28  29  40  33]
- [ 15   6  25  98   0   5  10]
- [  1   9   3   2  53   1   3]
- [  0   2   6   3   7  48   4]
- [  9   1   9  11   7  18  65]]
-Node Classification on random seed  4134 -> 0.639
-Confusion Matrix:
- [[ 91   5   1   3   3  14   5]
- [  4 120   8   0   7   6   4]
- [ 28  23 151  16  35  13  31]
- [ 10   6  11 113   3   4   8]
- [  1   5   3   0  59   2   1]
- [  4   1   6   0   1  47   4]
- [ 21   7  10  12  14  21  58]]
-Node Classification on random seed  4135 -> 0.631
-Confusion Matrix:
- [[ 65   1   2  13   2  14   5]
- [ 13 137   6   5   1   0   4]
- [ 23  28 150  24  14  30  39]
- [ 11   4  14  97   3   6  14]
- [  0  14   3   3  63   0   3]
- [  8   1   0   7   0  45   6]
- [ 15   6   4   4   2  17  74]]
-Node Classification on random seed  4136 -> 0.582
-Confusion Matrix:
- [[ 61   1  10   3   7  13  21]
- [ 11 123   8   4   6   0   6]
- [ 22  14 114  23  48  41  30]
- [ 12   5   9  99  10   9   8]
- [  2   6   6   1  54   2   2]
- [ 16   1   0   1   1  44   5]
- [ 14   4   5   6  10  15  87]]
-Node Classification on random seed  4137 -> 0.582
-Confusion Matrix:
- [[ 60   5   4   5   3  18   4]
- [  8 118   9   1  10   5   1]
- [ 30  16 128  38  56  29  20]
- [ 12   9   8 101   9   6  15]
- [  4   4   2   0  71   1   2]
- [  5   1   3   0   0  35  13]
- [ 13   5   6   6  21  11  69]]
-Node Classification on random seed  4138 -> 0.631
-Confusion Matrix:
- [[ 61   3   8   7   2  11  17]
- [  1 141   5   4   3   4   4]
- [ 22  19 138  38   5  17  61]
- [  6   6  14 105   1   6   8]
- [  4  12   0   1  72   1   1]
- [ 14   1   5   1   1  38   3]
- [ 20   4   6   7   5  11  76]]
-Node Classification on random seed  4139 -> 0.593
-Confusion Matrix:
- [[ 58   3   6  13   3  15  19]
- [  3 129   0   2   6   1   6]
- [ 27  16 138  43  24  25  37]
- [  8   0  17 108   3  10  12]
- [  1   6   2   1  55   3   2]
- [  3   6   5   5   2  35   7]
- [ 11   3   6  11   6  28  70]]
-Node Classification on random seed  4140 -> 0.582
-Confusion Matrix:
- [[ 71   2   0   7   5  12  11]
- [  6 123   8   1  12   2   4]
- [ 20  28 115  67  20  22  41]
- [ 12   5  16 102   9   0   8]
- [  4   7   3   1  62   0   1]
- [  5   0   0   8   0  44   3]
- [  6   7   7  10  10  28  65]]
-Node Classification on random seed  4141 -> 0.622
-Confusion Matrix:
- [[ 71   9   9   3   3   8   6]
- [  6 134  14   4   8   2   8]
- [ 10  20 142  28  24  18  47]
- [  5   4  26  86   5   4   9]
- [  2   4   5   3  72   0   3]
- [  7   2   5   0   0  48   3]
- [ 12   3  18  12   8  11  69]]
-Node Classification on random seed  4142 -> 0.637
-Confusion Matrix:
- [[ 78   1   7   4   5  16   6]
- [  6 136   5   4   3   3   1]
- [ 19  18 127  50  19  22  45]
- [ 22   5   2 103   6   6   5]
- [  0   2   0   5  70   1   2]
- [  7   0   3   0   1  57   3]
- [ 10   3   3   9   6  28  66]]
-Node Classification on random seed  4143 -> 0.644
-Confusion Matrix:
- [[ 74   3   4   3   1  17  11]
- [  3 129  11   6  16   0   7]
- [ 19  25 167  28  14  28  17]
- [ 15   3  15  87   6   8  11]
- [  1   3  10   3  58   2   2]
- [  5   0   1   1   4  62   1]
- [ 10   2  14  11   5  10  67]]
-Node Classification on random seed  4144 -> 0.578
-Confusion Matrix:
- [[ 83   1   8   4   5   7   8]
- [  4 106  14   6   7   3   5]
- [ 17  15 126  66  40  21  31]
- [ 18   1   7  95  11  13   4]
- [  1   7   5   2  60   1   2]
- [  9   0   4   1   0  33  10]
- [ 23   1  13  10   7  10  75]]
-Node Classification on random seed  4145 -> 0.601
-Confusion Matrix:
- [[ 74   3   5   9   5  13  12]
- [  0 136   5   6  12   4   5]
- [ 21  35 129  45  21  21  45]
- [  7   3  10  94   6   2  10]
- [  2   6   0   0  50   0   6]
- [  6   1   3   1   2  49   7]
- [ 16   2  15   6   3  18  69]]
-Node Classification on random seed  4146 -> 0.599
-Confusion Matrix:
- [[ 68   1  10  11   2  11   5]
- [  2 127   2   3  13   3   9]
- [ 18  20 142  25  16  30  50]
- [  5   2  18  85   4  10  31]
- [  2   7   4   3  59   1   6]
- [ 15   3   3   3   2  41   6]
- [  6   5   9   3   7  15  77]]
-Node Classification on random seed  4147 -> 0.61
-Confusion Matrix:
- [[ 54   5   5   1   4  16  13]
- [  5 136   3   1   8   0   3]
- [ 13  21 146  49  28  19  43]
- [  6   2  20 104   6   8  21]
- [  2   6   2   0  59   0   5]
- [  6   0   4   3   0  43   5]
- [ 11   4   7   2  14  19  68]]
-Node Classification on random seed  4148 -> 0.603
-Confusion Matrix:
- [[ 62   1   6   6   2   8  17]
- [  3 128   3   2  12   2   3]
- [ 17  22 110  37  54  27  38]
- [  6   1  17 105   6  13   6]
- [  0   3   4   2  72   1   2]
- [  1   0   0   6   2  51   5]
- [  7   5   9  18  11  12  75]]
-Node Classification on random seed  4149 -> 0.635
-Confusion Matrix:
- [[ 67   4   3   5   3  13  12]
- [  4 135   3   2   7   1   8]
- [ 19  18 161  15  37  26  33]
- [  7   1  18 103   3   4  17]
- [  0  10   5   2  53   1   1]
- [  5   6   4   2   3  46   8]
- [  4   5   9   8   9  20  70]]
-Node Classification on random seed  4150 -> 0.624
-Confusion Matrix:
- [[ 64   3   2   9   8   7  11]
- [  5 122  13   2  12   0   3]
- [ 26   9 146  26  28   9  53]
- [ 11   3  10 105  10   6   9]
- [  3   7   6   1  47   1   2]
- [  5   4   2   0   2  56   6]
- [ 26   2   8   5   5  16  84]]
-Node Classification on random seed  4151 -> 0.574
-Confusion Matrix:
- [[ 78   1   3   5   4  12   2]
- [  3 115   6   0  17   2   3]
- [ 18  18 107  47  44  16  53]
- [ 14  12   8 109  11  11   9]
- [  0   4   7   0  64   1   1]
- [  3   0   0   2   0  39   8]
- [ 20   6  12  11  15  17  62]]
-Node Classification on random seed  4152 -> 0.623
-Confusion Matrix:
- [[ 78   3   0  10   7  15   6]
- [  3 133   7   0   5   1   1]
- [ 42  22 142  36  12  14  41]
- [ 10   5  19  99   3   7  14]
- [  1   6   4   2  59   3   3]
- [  7   3   7   2   1  47   6]
- [ 10   1  11  10   7  10  65]]
-Node Classification on random seed  4153 -> 0.656
-Confusion Matrix:
- [[ 74   3   2   2  11   4   5]
- [  2 131   5   1   8   2   4]
- [ 20  13 167  24  26  19  40]
- [  7   3  15 109  11   3  17]
- [  2   6   5   0  62   0   4]
- [  7   2   3   6   1  43   6]
- [ 12   1   9   9  10  14  70]]
-Node Classification on random seed  4154 -> 0.622
-Confusion Matrix:
- [[ 80   2   1   3   2  19   6]
- [  2 119  10   3   9   3   5]
- [ 29  18 134  31  35  24  29]
- [ 21   1   8 101  10   3  15]
- [  3   5   3   3  54   1   1]
- [  9   2   0   1   1  42  11]
- [ 10   6   3  13   6  11  92]]
-Node Classification on random seed  4155 -> 0.607
-Confusion Matrix:
- [[ 72   2   5   3   7  13   5]
- [  5 139   7   4   7   2   5]
- [ 18  20 139  26  33  33  43]
- [ 12   2  20  95   3   6  19]
- [  7  11   2   1  36   4   2]
- [ 11   5   0   0   2  41   9]
- [  8   2   4   2   6  17  85]]
-Node Classification on random seed  4156 -> 0.587
-Confusion Matrix:
- [[ 85   6   3   6   3   6   3]
- [  3 136   4   7   6   3   2]
- [ 35  33 111  39  22  23  46]
- [ 18   5  12  89   8   3  15]
- [  0   5   1   8  56   0   3]
- [ 12   2   3   1   0  34   8]
- [ 31   2   5   4   8   9  76]]
-Node Classification on random seed  4157 -> 0.637
-Confusion Matrix:
- [[ 56   1   6   6   3  13   7]
- [  3 146   7   1   3  12   4]
- [ 34  26 148  20  19  17  33]
- [  8   7  12 100  12   4  25]
- [  1   5   1   0  57   2   3]
- [  9   2   1   0   0  50   4]
- [ 11   5  12   6   8  10  80]]
-Node Classification on random seed  4158 -> 0.63
-Confusion Matrix:
- [[ 79   1   1   6   4  10   4]
- [  8 125   2   4   2   1  10]
- [ 33  34 133  25  24  23  40]
- [ 18   2  10 109   4   6  10]
- [  1   6   4   0  59   0   7]
- [  8   1   0   1   0  50   3]
- [ 20   4   5  12   7   9  75]]
-Node Classification on random seed  4159 -> 0.58
-Confusion Matrix:
- [[ 59   2   5   7   3  11  12]
- [  2 105   9   1  17   5   2]
- [ 29  27 120  49  24  42  43]
- [ 16   0  14 100   4   4  13]
- [  3   4   3   0  61   0   4]
- [  1   1   1   5   2  48   4]
- [ 15   6   8   5   4  13  87]]
-Node Classification on random seed  4160 -> 0.589
-Confusion Matrix:
- [[ 51   2   5  16   7   9  10]
- [  0 121   3   6  11   7   8]
- [  6  29 125  60  28  18  39]
- [  8   0   7 110  17   7  15]
- [  0   7   0   3  56   0   5]
- [  8   2   3   2   0  43   4]
- [  8   1  11  18   6  15  83]]
-Node Classification on random seed  4161 -> 0.609
-Confusion Matrix:
- [[ 60   3  12   6   2  10   7]
- [  9 112   9   6   5   3   7]
- [ 25  23 151  43  20  18  32]
- [ 19   1  20 115   4   5   8]
- [  3   3   7   3  47   0   3]
- [  8   0   2   1   1  42   1]
- [  7   9  10  12   6  18  82]]
-Node Classification on random seed  4162 -> 0.662
-Confusion Matrix:
- [[ 68   2   7   4   5   9   4]
- [  3 164   5   1   3   1   0]
- [ 22  26 143  46  26  23  27]
- [  4   3  21 103   6   5   7]
- [  1  10   2   0  63   2   5]
- [  7   0   0   3   0  51   1]
- [  6   5  11   4   5  16  70]]
-Node Classification on random seed  4163 -> 0.591
-Confusion Matrix:
- [[ 75   3   4   8   3  12  10]
- [  2 128   9   3  10   0   4]
- [ 18  10 110  60  28  23  56]
- [ 23   2  10  82  12   8  21]
- [  1   6   2   4  70   2   5]
- [  6   0   5   1   2  44   6]
- [ 13   1   6   3   2   5  82]]
-Node Classification on random seed  4164 -> 0.585
-Confusion Matrix:
- [[ 59   7   7   6   6   9  11]
- [  7 116  10   4   3   9   6]
- [ 40  26 143  23  27  38  27]
- [ 16   5  12  94   8   6   8]
- [  0   5  12   4  52   0   2]
- [  6   0   1   2   0  51   2]
- [ 11   2   9   8   2  28  70]]
-Node Classification on random seed  4165 -> 0.628
-Confusion Matrix:
- [[ 66   1   4   1   5  18  15]
- [  4 124   5   5   8   1   6]
- [ 27  17 156  26  23  25  43]
- [ 14   2  10 104   6  12   3]
- [  1   7   3   1  65   0   3]
- [  1   0   4   0   2  54   0]
- [ 13   3  12  10   7  24  59]]
-Node Classification on random seed  4166 -> 0.604
-Confusion Matrix:
- [[ 63   1   5   5   1   9  15]
- [ 10 131   5   7   9   4   3]
- [ 18  26 121  37  32  23  42]
- [  9   2  16 107  15   2   9]
- [  0   5   6   0  65   2   2]
- [  4   1   0   1   2  55   9]
- [ 16   4  10   7   3  19  62]]
-Node Classification on random seed  4167 -> 0.646
-Confusion Matrix:
- [[ 78   5   2   3   4   9   7]
- [  4 128  10   3   9   5   0]
- [ 22  18 155  41  21  27  27]
- [ 13   5  14 108   8   3  13]
- [  0   5   2   3  66   2   1]
- [  7   3   4   1   0  36   9]
- [ 17   1   7   5   4  10  75]]
-Node Classification on random seed  4168 -> 0.637
-Confusion Matrix:
- [[ 72   2  15   4   5   6   6]
- [  4 126  10   1  10   1   7]
- [ 17  26 149  31  22  21  42]
- [ 16   1  20 106   1  13  12]
- [  3   3   2   3  60   0   1]
- [  2   2   2   0   0  50   4]
- [ 13   2   7   3   5  18  74]]
-Node Classification on random seed  4169 -> 0.608
-Confusion Matrix:
- [[ 60   3  10  10   7  12  17]
- [  3 124   2   1  10   2   8]
- [ 20  22 127  20  43  21  46]
- [  8   6   9 118   2   6  14]
- [  0   9   2   2  56   1   2]
- [  4   0   1   3   0  36  13]
- [ 19   3   4  16   2   9  87]]
-Node Classification on random seed  4170 -> 0.6
-Confusion Matrix:
- [[ 73   4   1   7   3  14   5]
- [  7 118  15   3   6   7   2]
- [ 21  28 149  35  22  32  35]
- [  7  11  15  81  12   3  11]
- [  1   5   7   2  56   3   2]
- [  5   2   2   1   3  47   5]
- [  6   5  11  10   9  15  76]]
-Node Classification on random seed  4171 -> 0.651
-Confusion Matrix:
- [[ 61   3   1   4   1  13   8]
- [  4 128   9   4  11   2  13]
- [ 16  19 172  20  31  24  15]
- [  3   8  23  95   5   9  10]
- [  2   2   4   1  65   2   6]
- [  4   2   0   3   2  45   8]
- [ 16   0  10   9   9  13  85]]
-Node Classification on random seed  4172 -> 0.619
-Confusion Matrix:
- [[ 71   5   1  17   2  10  10]
- [ 10 147   4   1  11   3   4]
- [ 16  25 130  34  22  24  44]
- [ 14   4   9 102   5   8  14]
- [  0   6   4   4  56   0   1]
- [  2   1   5   1   0  41  10]
- [ 10   5   5   8   9  13  72]]
-Node Classification on random seed  4173 -> 0.592
-Confusion Matrix:
- [[ 67   1  10   7   5  17   4]
- [  4 133  13   2   5   3   1]
- [ 20  24 118  55  29  26  32]
- [  5   1  16 112   3  10  15]
- [  3   5   4   1  58   0   1]
- [  6   0   2   1   3  37   2]
- [ 15   5  12  12   7  21  67]]
-Node Classification on random seed  4174 -> 0.613
-Confusion Matrix:
- [[ 74   0   3   4   4  18   1]
- [  3 118  14   2   2   8   3]
- [ 28  26 138  20  26  35  36]
- [  8   5  29 100  10  10   5]
- [  2   3   4   0  75   2   2]
- [  6   0   0   3   0  41   2]
- [ 12   4  14  11   8  14  67]]
-Node Classification on random seed  4175 -> 0.618
-Confusion Matrix:
- [[ 73   0   2   0   1   5  11]
- [  6 129   4   3   8   3   3]
- [ 31  15 126  41  21  37  37]
- [ 26   5  14 114   2  10  12]
- [  3  10   5   4  57   1   1]
- [  8   0   2   0   0  46   4]
- [  7   3  13   3   7  14  73]]
-Node Classification on random seed  4176 -> 0.628
-Confusion Matrix:
- [[ 76   3   7   3   1   3   8]
- [  5 131   2   4   6   3   3]
- [ 30  23 167  33  17  23  38]
- [ 15   4  21 103   5   6   4]
- [  2  12   7   2  56   1   1]
- [  1   1   2   5   0  47   7]
- [ 14   5   8   9  13  15  48]]
-Node Classification on random seed  4177 -> 0.642
-Confusion Matrix:
- [[ 65   5   1   1   6   6  19]
- [  3 131   5   2   9   4   4]
- [ 15  30 136  36  24  19  32]
- [ 13   3   9 131   4   2  26]
- [  0   4   6   3  62   2   2]
- [  6   2   2   4   3  32   5]
- [  6   2   9   6   6  12  85]]
-Node Classification on random seed  4178 -> 0.621
-Confusion Matrix:
- [[ 61   1   3   3   2  10  13]
- [  8 122   3   3   9   4  11]
- [ 25  39 140  38  22  14  30]
- [  9   5  17 109  11   7  13]
- [  2   5   2   0  63   1   2]
- [  4   0   2   4   1  43   5]
- [  8   4   9   4  11  15  83]]
-Node Classification on random seed  4179 -> 0.601
-Confusion Matrix:
- [[ 52   5   7   8   6  21  12]
- [  3 132   7   4   0   4   6]
- [ 38  34 127  34  20  20  35]
- [ 12   3  14 104   5   9  12]
- [  0   8   3   1  52   2   5]
- [  2   0   2   4   1  48   5]
- [  9   0   7  11   9  11  86]]
-Node Classification on random seed  4180 -> 0.644
-Confusion Matrix:
- [[ 60   7   6   6   2  10  19]
- [  6 128   4   3  14   0   5]
- [ 21  16 153  42  30  16  23]
- [  8   5  25 106   5   1   9]
- [  5   5   6   2  66   1   2]
- [  1   5   2   0   0  49  10]
- [  3   2   9   8   4   8  82]]
-Node Classification on random seed  4181 -> 0.665
-Confusion Matrix:
- [[ 74   1   5   4   2  15   2]
- [  3 133   2   7   3   4   3]
- [ 28  21 153  32  21  17  45]
- [ 11   3   7 107   7   3  12]
- [  0   9   5   0  59   1   3]
- [  1   0   0   2   3  48   8]
- [  7   4   3   5   7  19  91]]
-Node Classification on random seed  4182 -> 0.639
-Confusion Matrix:
- [[ 64   1   2   9   2  11  18]
- [  5 141   3   4   2   1   5]
- [ 29  21 153  34  31  26  28]
- [ 13   2  17  91  10   2  11]
- [  3   8   2   0  52   0   0]
- [  3   2   5   3   0  57   4]
- [  2   2   5   8   6  21  81]]
-Node Classification on random seed  4183 -> 0.586
-Confusion Matrix:
- [[ 70   4   4   9   4  10  16]
- [  4 126   4   5  17   3   1]
- [ 44  27 128  31  30  18  35]
- [ 16   4   8  98  10   7  10]
- [  1   7   5   2  61   2   3]
- [ 14   0   6   0   1  30   3]
- [ 24   0   5  11   6   3  73]]
-Node Classification on random seed  4184 -> 0.583
-Confusion Matrix:
- [[ 76   3   7   6   5   8   5]
- [  2 136   6   1   3   0   6]
- [ 33  37 102  53  32  14  31]
- [ 22   6  15  89  13   4  17]
- [  1   8   2   2  55   0   1]
- [  2   2   6   2   4  39  14]
- [  4   6   7   8   3  16  86]]
-Node Classification on random seed  4185 -> 0.602
-Confusion Matrix:
- [[ 54   3   5   6   3  20   4]
- [  1 138   6   0   4   3   6]
- [ 33  26 132  45  22  27  30]
- [ 14   8  13 103   1  17   6]
- [  0   9   3   2  54   1  10]
- [  2   1   6   4   1  52   2]
- [ 17   4   4   8   3  18  69]]
-Node Classification on random seed  4186 -> 0.636
-Confusion Matrix:
- [[ 67   2   6  10   8   7   9]
- [  5 127  13   3   6   1   1]
- [ 23  32 171  34  25  18  24]
- [ 11   2  13  97   3   4   7]
- [  3   5   3   0  57   1   2]
- [ 10   0   5   4   4  45   2]
- [ 15   3  11   8   6  15  72]]
-Node Classification on random seed  4187 -> 0.616
-Confusion Matrix:
- [[ 64   4   3   7   6  15  15]
- [ 10 125   4   3   1   4   7]
- [ 23  25 148  38  13   8  52]
- [ 25   2  18  98   6   4   8]
- [  1  10   3   4  48   1   0]
- [  5   1   6   0   0  46   7]
- [  5   3   6   6   5  20  87]]
-Node Classification on random seed  4188 -> 0.617
-Confusion Matrix:
- [[ 64   3   0   3  10   9  17]
- [  6 124   2   1  19   1   4]
- [ 18  18 129  33  30  30  39]
- [  6   4  15 111  18   5  16]
- [  0   2   5   0  67   1   2]
- [  3   2   1   2   2  44   4]
- [  6   3  10   6  13  14  78]]
-Node Classification on random seed  4189 -> 0.603
-Confusion Matrix:
- [[ 62   1   6   8   6   8   9]
- [  3 129   6   4   9   6   2]
- [ 19  36 123  25  33  35  24]
- [  8   3  21  96  10   6  25]
- [  2   6   4   1  66   2   4]
- [  6   0   2   1   1  57   2]
- [ 10   7  10   4   4  18  70]]
-Node Classification on random seed  4190 -> 0.596
-Confusion Matrix:
- [[ 63   0   3   7   3  16   2]
- [  1 123  14   1   2   5   0]
- [ 30  18 141  28  25  30  51]
- [ 11   5  24  81   5   8  14]
- [  2   7   4   2  58   1   4]
- [  3   1   1   6   0  52   9]
- [ 16   4  12   8   7  14  78]]
-Node Classification on random seed  4191 -> 0.633
-Confusion Matrix:
- [[ 88   1   2   6   4   9  10]
- [  3 130   4   3   8   2   5]
- [ 31  15 141  24  24  22  42]
- [  5   9   9 107   4   8  14]
- [  2   8   5   2  44   0   4]
- [  7   0   2   2   0  55   4]
- [ 13   3   7  16   8  20  68]]
-Node Classification on random seed  4192 -> 0.609
-Confusion Matrix:
- [[ 77   1   1   3   2  18   8]
- [  9 128   7   2   8   2   9]
- [ 28  17 132  28  44  20  33]
- [ 11   9  12  88  14   3  22]
- [  1   4   3   2  69   3   2]
- [  6   0   0   1   6  37   3]
- [ 10   3   4   9   5  18  78]]
-Node Classification on random seed  4193 -> 0.633
-Confusion Matrix:
- [[ 67   5   3  12   4   5   9]
- [  5 129   1   3   5   1   2]
- [ 21  23 162  27  36  20  47]
- [  9   5  14 104  12   5  19]
- [  0   2   2   1  53   0   3]
- [  2   5   1   0   4  36   6]
- [ 14   4   4   8   3  15  82]]
-Node Classification on random seed  4194 -> 0.53
-Confusion Matrix:
- [[ 66   0   8   4   0  15   8]
- [  8 126  10   2  11   1   0]
- [ 38  25  94  42  54  18  46]
- [  6   3  16  96   3   8  14]
- [  4  11   1   1  55   1   0]
- [ 11   0   6   1   1  42   5]
- [ 17   4  21   9  28   9  51]]
-Node Classification on random seed  4195 -> 0.602
-Confusion Matrix:
- [[ 49   2   4   9   6  20   6]
- [  7 131   2   2   6   5   4]
- [ 23  18 138  33  13  26  50]
- [  7   8  19  92   7   9  39]
- [  1   4   2   1  59   0   0]
- [  2   1   0   2   3  48   1]
- [  9   4   3   5   6  29  85]]
-Node Classification on random seed  4196 -> 0.623
-Confusion Matrix:
- [[ 91   3  10   3   7   6   7]
- [  2 139   4   0   4   2   5]
- [ 29  12 134  26  24  21  42]
- [ 13   7  17  96  13   1  13]
- [  0  10   1   1  60   0   7]
- [ 16   2   3   0   2  42   9]
- [ 13   4   4   4   5  25  61]]
-Node Classification on random seed  4197 -> 0.588
-Confusion Matrix:
- [[ 47   1   5   3   2  19  16]
- [  3 126   3   1   7   3   5]
- [ 23  17 119  50  42  20  44]
- [  6   3  14 106   7   2  20]
- [  0   5   6   1  64   0   4]
- [  4   3   1   1   0  56   4]
- [ 11   7   7   7  13  22  70]]
-Node Classification on random seed  4198 -> 0.605
-Confusion Matrix:
- [[ 71   3  11   2   2   5   6]
- [  6 132   4   5   4   0   2]
- [ 19  26 135  37  39  21  47]
- [  7   4  15  83  18   6  16]
- [  1   4   2   1  63   1   6]
- [  6   0   6   4   1  43   3]
- [ 11   5  10   6   8  15  78]]
-Node Classification on random seed  4199 -> 0.652
-Confusion Matrix:
- [[ 67   4   0  10   8   5  23]
- [  1 122   5   3  10   1   5]
- [ 30  16 143  26  28  13  42]
- [  8   2   9 121   9   4   8]
- [  1   7   1   1  61   1   4]
- [  3   2   2   0   2  43  10]
- [  7   5  12   3   8   9  95]]
-Node Classification on random seed  4200 -> 0.601
-Confusion Matrix:
- [[ 58   2   1   8   4   7  13]
- [  3 117   4   6  11   2   5]
- [ 23  26 133  26  23  18  50]
- [ 25   4  14  99   6   7   9]
- [  0   3   2   2  72   0   5]
- [  5   2   1   3   1  48   7]
- [ 18   2   2  14   7  28  74]]
-Node Classification on random seed  4201 -> 0.612
-Confusion Matrix:
- [[ 65   2  11   2   3  17   8]
- [  9 123   2   1   9   7   4]
- [ 14  11 135  17  39  33  52]
- [ 12   6  17  96   1  13  12]
- [  4   6   3   0  56   1   1]
- [  8   0   1   1   1  52   3]
- [ 10   4  10  10   9  14  85]]
-Node Classification on random seed  4202 -> 0.631
-Confusion Matrix:
- [[ 62   6   4   5   2  18  10]
- [  5 129   4   1   9   1   6]
- [ 17  18 164  24  37  15  38]
- [ 11   6  13 106   6   8  12]
- [  0   7   8   1  52   0   1]
- [  8   1   5   4   3  43   4]
- [ 12   2   5   9  12  11  75]]
-Node Classification on random seed  4203 -> 0.604
-Confusion Matrix:
- [[ 70   2   6   6  10   7  15]
- [  8 107   6   5  10   3   3]
- [ 28  13 134  35  42   9  47]
- [  3   1  23 106   3   5  19]
- [  2   6   9   2  48   1   2]
- [  4   2   2   3   3  50   5]
- [ 10   4  11   4   5  12  89]]
-Node Classification on random seed  4204 -> 0.57
-Confusion Matrix:
- [[ 64   3   3  11   2  17   3]
- [  5 107   2   4  20   4   0]
- [ 35  16 124  46  31  30  41]
- [ 12   3  17 101  10   8  14]
- [  1   4   5   1  63   0   1]
- [  8   2   2   1   2  46   5]
- [  9   5   8  10  11  18  65]]
-Node Classification on random seed  4205 -> 0.658
-Confusion Matrix:
- [[ 75   6   3   3   5  12   6]
- [  5 130   5   0   6   2   4]
- [ 26  23 157  31  24  19  49]
- [  5   8  11 107   2   5  21]
- [  2   6   4   0  54   1   1]
- [  2   0   0   2   0  45   9]
- [  9   5   7   6   4   3  90]]
-Node Classification on random seed  4206 -> 0.636
-Confusion Matrix:
- [[ 71   1   8   4   3   8   6]
- [  5 141   7   2   9   5   3]
- [ 26  27 139  34  29  26  26]
- [  9   3  11 123   5   4   8]
- [  1   5   7   1  58   0   3]
- [  4   0   2   2   1  39  10]
- [ 14   1  14   4  16  10  65]]
-Node Classification on random seed  4207 -> 0.617
-Confusion Matrix:
- [[ 67   3   2   2   6  14   5]
- [  2 121   8   3  11   1   2]
- [ 26  11 147  30  43  14  45]
- [  1   4  29  99   0  22   6]
- [  1   2   2   5  66   1   0]
- [  4   3   0   0   0  48   5]
- [ 11   2   5  12  17  23  69]]
-Node Classification on random seed  4208 -> 0.665
-Confusion Matrix:
- [[ 76   4   2   1   7   5  13]
- [  6 141   3   1   3   4   1]
- [ 18  18 174  28  19  26  39]
- [ 11   3  21 101   6   9  13]
- [  2   7   3   3  60   1   4]
- [  2   3   1   2   1  40   6]
- [ 15   4   6   5   3   6  73]]
-Node Classification on random seed  4209 -> 0.592
-Confusion Matrix:
- [[ 64   4   5  13   8  13   5]
- [  4 119   5   2   7   4   1]
- [ 46  20 133  46  19  10  32]
- [  7   4  22 112   8   7   7]
- [  2   8   4   2  56   2   5]
- [  6   1   2   6   0  41   5]
- [  9   5   5  17  10  20  67]]
-Node Classification on random seed  4210 -> 0.639
-Confusion Matrix:
- [[ 63   0   9   3   2  12  12]
- [  2 150   6   5   2   2   4]
- [ 28  21 148  35  27  20  31]
- [  7   3   8 105  11  10  16]
- [  0   5   3   1  55   1   1]
- [  8   1   1   0   1  50   4]
- [  6   2  15   7  12  17  68]]
-Node Classification on random seed  4211 -> 0.63
-Confusion Matrix:
- [[ 75   3   4   1   2   9  10]
- [  1 128   8   3   7   1   3]
- [ 23  20 139  43  20  22  50]
- [ 20   4  23  82   7   6   7]
- [  2   3   0   2  58   0   3]
- [  3   4   1   0   2  47  10]
- [  3   5  12   7   2  14 101]]
-Node Classification on random seed  4212 -> 0.581
-Confusion Matrix:
- [[ 82   4   1   5   3  19   8]
- [  1 121   1  11   5   5   4]
- [ 18  26 132  55  27  37  21]
- [ 10   7  23  87  10   7  12]
- [  0   1   5   0  56  10   2]
- [  2   2   2   5   4  40   3]
- [  9   4  13  12   6  19  63]]
-Node Classification on random seed  4213 -> 0.649
-Confusion Matrix:
- [[ 85   3   3   4   7   4   9]
- [  1 124   6   5  22   1   3]
- [ 16  17 156  39  20  37  23]
- [ 12   5  15 103   4   5  15]
- [  0   6   2   3  60   0   2]
- [  7   3   0   0   2  46   3]
- [  4   2  14   3   5  19  75]]
-Node Classification on random seed  4214 -> 0.61
-Confusion Matrix:
- [[ 74   6   4   5   5   8   7]
- [  5 130   9   6  12   1   3]
- [ 25  20 127  33  34  21  40]
- [  6   3  18 113   7   8  11]
- [  3   4   4   1  60   0   1]
- [  1   2   1   3   2  50   5]
- [ 15   3   6  12  13  17  56]]
-Node Classification on random seed  4215 -> 0.605
-Confusion Matrix:
- [[ 86   2   3   5   2   6   9]
- [ 13 114   3   2   5   1   8]
- [ 19  14 141  42  38  16  36]
- [ 19   1  27  70   4   8  19]
- [  1   2   1   4  68   1   3]
- [ 11   0   3   0   1  34   8]
- [ 12   4   3   8  13  18  92]]
-Node Classification on random seed  4216 -> 0.601
-Confusion Matrix:
- [[ 68   3   4   1   7   6  14]
- [  7 116   5   3  17   4   7]
- [ 38  15 155  28  25  20  55]
- [ 12   0  17  92   1   6  17]
- [  1   4   5   0  55   2   5]
- [  9   1   0   2   1  35   9]
- [ 12   3   7  11   4  11  80]]
-Node Classification on random seed  4217 -> 0.605
-Confusion Matrix:
- [[ 75   1   2   4   8  13  11]
- [  0 122   6   4  10   0   4]
- [ 42  14 144  16  32  22  48]
- [ 11   2   8  76  25   7  18]
- [  1   7   7   1  59   0   1]
- [  9   5   3   2   0  40   4]
- [ 10   4   5   1  11  16  89]]
-Node Classification on random seed  4218 -> 0.601
-Confusion Matrix:
- [[ 59   3   1   4   2  12  22]
- [  1 129   7   5   5   3   5]
- [ 21  28 120  52  17  28  39]
- [  9   8   9 115   3  13  12]
- [  5   6   6   1  56   1   2]
- [  1   2   3   6   0  49   5]
- [  7   7  14  12   3   9  73]]
-Node Classification on random seed  4219 -> 0.582
-Confusion Matrix:
- [[ 64   1   1   7   7  18   6]
- [  3 139   5   4   5   3   1]
- [ 21  24 120  65  24  24  27]
- [ 14   3  19 100   8   9  15]
- [  1  14   6   1  55   2   2]
- [ 10   3   0   2   1  38   4]
- [ 16   2   8   7   8  17  66]]
-Node Classification on random seed  4220 -> 0.621
-Confusion Matrix:
- [[ 78   2   1   4   5  11  13]
- [  4 117   3   2   8   1   9]
- [ 20  27 145  35  21  24  40]
- [  8   2  12 110   5   9  10]
- [  0   6  13   0  59   0   3]
- [  3   0   1   5   0  45  12]
- [ 13   4   8  15   7  13  67]]
-Node Classification on random seed  4221 -> 0.624
-Confusion Matrix:
- [[ 53   3   6   6   2  15  15]
- [  3 132   2   0  11   3   6]
- [ 31  22 160  22  20  22  48]
- [ 15   1  14  92   5  11  15]
- [  1   1   5   2  61   2   0]
- [ 12   0   3   4   0  43   1]
- [ 19   4   3   2   8  11  83]]
-Node Classification on random seed  4222 -> 0.584
-Confusion Matrix:
- [[ 74   2   2   5   2  19  12]
- [  5 116   1   0  16   5   6]
- [ 23  24 130  34  30  36  38]
- [ 27   3  13  92   6   2  11]
- [  1   8   4   0  65   2   5]
- [  2   4   0   2   1  44   2]
- [  9   5   9   7   8  25  63]]
-Node Classification on random seed  4223 -> 0.621
-Confusion Matrix:
- [[ 69   4   3   3   7  20   3]
- [  0 123   5   6   6   4   4]
- [ 12  37 142  31  24  20  51]
- [  5   5  13  91   1   9  18]
- [  1   8   3   1  66   4   1]
- [  1   4   2   1   2  51   4]
- [  2   6   8   7  13  20  79]]
-Node Classification on random seed  4224 -> 0.604
-Confusion Matrix:
- [[ 70   2   4   5   6  12  18]
- [  1 126   4   1   6   1   5]
- [ 31  41 131  34  22  33  40]
- [ 10   2   9 101   4   6  15]
- [  0   7   2   3  58   2   3]
- [ 11   1   1   1   0  43   9]
- [ 14   5   8   7   2   8  75]]
-Node Classification on random seed  4225 -> 0.638
-Confusion Matrix:
- [[ 86   2   6   6   2   9   5]
- [  2 149   4   0   8   2   7]
- [ 29  40 132  34  31  20  32]
- [ 15   5  15  97   2   7  15]
- [  2   7   5   2  57   0   2]
- [  6   2   2   0   0  38   3]
- [  6   0   9   1   8   9  79]]
-Node Classification on random seed  4226 -> 0.648
-Confusion Matrix:
- [[ 54   4   2   5   4   9  12]
- [  2 126   5   3   7   4   5]
- [ 12  14 164  39  27  34  35]
- [ 11   2  14  90   8   3   7]
- [  0   6   4   2  71   3   2]
- [  3   1   2   8   2  51   7]
- [  2   1   8  15   6  12  92]]
-Node Classification on random seed  4227 -> 0.636
-Confusion Matrix:
- [[ 66   4   4   3   0  17   3]
- [  5 133   4   5  10   1   5]
- [ 25  30 146  38  12  19  37]
- [ 14   7  20  96   5   2  15]
- [  4   1   2   2  63   2   0]
- [  3   1   3   2   4  56   6]
- [  5   3  12   8  11  10  76]]
-Node Classification on random seed  4228 -> 0.633
-Confusion Matrix:
- [[ 68   7  10   3   0  11   8]
- [  4 130   4   2  10   1   3]
- [ 22  17 171  39  21  30  43]
- [  8   1  21  94   3   6  10]
- [  1   7   1   1  54   4   4]
- [  5   0   1   0   2  45   9]
- [  0   9  16   1   4  18  71]]
-Node Classification on random seed  4229 -> 0.592
-Confusion Matrix:
- [[ 61   4   4  13   2   6   9]
- [  4 124   7   3   6   8   5]
- [ 32  21 144  47  22  27  19]
- [ 19   4  14 103   2   7  14]
- [  0   5   4   0  59   2   7]
- [  5   1   4   3   2  41   6]
- [ 26   5  14   9   5  11  60]]
-Node Classification on random seed  4230 -> 0.592
-Confusion Matrix:
- [[ 74   1   3   4   1  13   6]
- [  2 114  11   3  15   8   6]
- [ 28  19 137  35  40  17  42]
- [ 22   2  15  94   2   7  16]
- [  3   5   2   1  53   1   1]
- [ 15   1   1   1   1  36   4]
- [ 23   1   7   5   7  11  84]]
-Node Classification on random seed  4231 -> 0.598
-Confusion Matrix:
- [[ 67   0   6   3   5   6  11]
- [  1 111  10   3  11   2   3]
- [ 28  33 132  34  38  16  30]
- [  8  10  24 110  11   4   8]
- [  1   9   3   4  60   0   1]
- [  8   1   6   1   2  33  13]
- [  5   6   7   8  15   7  85]]
-Node Classification on random seed  4232 -> 0.578
-Confusion Matrix:
- [[ 65   3   6   4   3  11  19]
- [  2 119   7   0  14   2   6]
- [ 24  13 110  47  41  19  59]
- [  9   5  15  99   0  10  13]
- [  3   5   5   1  76   1   4]
- [  0   3   0   4   0  41  10]
- [  9   4   5   8   9  19  68]]
-Node Classification on random seed  4233 -> 0.594
-Confusion Matrix:
- [[ 58   4   4   2   4  15  11]
- [  0 127   5   4   7   3   5]
- [ 38  28 137  39  33  19  42]
- [ 11   1  15 101  12  11   7]
- [  1   2   2   0  57   1   2]
- [  5   2   7   2   2  46   4]
- [ 15   4   9   7   9  12  68]]
-Node Classification on random seed  4234 -> 0.605
-Confusion Matrix:
- [[ 72   6  12   2   3  10   8]
- [  6 108   6   4   5   0   9]
- [ 26  17 152  35  33  13  42]
- [ 18  11  26  86   5   4  12]
- [  1   2   9   2  56   0   6]
- [  9   4   0   1   4  47   1]
- [ 13   5   5   5   6   9  84]]
-Node Classification on random seed  4235 -> 0.595
-Confusion Matrix:
- [[ 69   8   4   5   5   6  10]
- [  4 129  11   7   3   2  10]
- [ 29  11 131  52  21  17  45]
- [ 12   5   9  92   9   2  18]
- [  1   7   6   0  64   0   3]
- [ 10   4   5   4   5  27   6]
- [ 14   4   7  11   1  12  83]]
-Node Classification on random seed  4236 -> 0.641
-Confusion Matrix:
- [[ 84   1  10   5   4  21   7]
- [  1 120   5   0   9   4   5]
- [ 11  19 134  39  45  16  37]
- [  5   1  16 111  12   3   8]
- [  0   5   2   1  76   0   5]
- [  5   0   3   0   1  48   4]
- [  7   0  14   5  13  10  68]]
-Node Classification on random seed  4237 -> 0.566
-Confusion Matrix:
- [[ 50   6  10   5   4  12  10]
- [  2 121   6   3   8   6   4]
- [  9  15 134  37  37  20  64]
- [ 14   1  10  82  18  13  14]
- [  2  10   0   2  64   0   6]
- [  6   2   1   0   2  52   0]
- [  8   9  11   9  14  24  63]]
-Node Classification on random seed  4238 -> 0.587
-Confusion Matrix:
- [[ 74   3   3   8   2  14  10]
- [ 10 114  13   3   6   0   1]
- [ 33  26 108  26  37  25  47]
- [  1   5  13 111  11   7  12]
- [  1   2   7   3  52   4   3]
- [  5   0   3   5   0  46  10]
- [ 16   3  12   8   5  10  82]]
-Node Classification on random seed  4239 -> 0.609
-Confusion Matrix:
- [[ 68   4   4   4   2   8  19]
- [  7 133   5   3   6   7   4]
- [ 30  31 130  39  25  25  32]
- [  7   2  20 105   1   7  16]
- [  0  11   2   2  54   0   1]
- [  1   1   1   3   2  39   6]
- [  7   9   8   5   7  17  80]]
-Node Classification on random seed  4240 -> 0.635
-Confusion Matrix:
- [[ 78   6   2   1   8  10   5]
- [  3 146   1   0   6   2  12]
- [ 17  21 135  30  26  21  47]
- [ 13   4  22  99   8   3   9]
- [  0   9   0   1  56   1   6]
- [  6   1   0   5   2  41   2]
- [  7   4  11  12   3  18  80]]
-Node Classification on random seed  4241 -> 0.623
-Confusion Matrix:
- [[ 72   1   4   2   4  12   9]
- [  2 144   5   3   7   2   4]
- [ 18  24 135  27  29  28  38]
- [ 11   6  11  96  10  16  10]
- [  2   8   5   3  65   2   2]
- [  3   3   1   6   0  41   7]
- [  8   1  17   9   6  11  70]]
-Node Classification on random seed  4242 -> 0.637
-Confusion Matrix:
- [[ 99   1   1   5   1   5  10]
- [  5 127   4   1  11   1   4]
- [ 35  18 135  23  19  31  37]
- [ 10   5  16  97   4   8  16]
- [  7   8   5   1  52   3   1]
- [  8   1   0   0   0  55   4]
- [ 21   3  11   4   0  15  72]]
-Node Classification on random seed  4243 -> 0.587
-Confusion Matrix:
- [[ 57   3   6   5   4   7  13]
- [  9 129   2   2   6   1   2]
- [ 33  39 135  40  38  23  28]
- [ 14   1  21 105   3   4   6]
- [  1   7   3   4  61   1   1]
- [  4   3   6   4   1  36   1]
- [  9   3  17   4  13  21  64]]
-Node Classification on random seed  4244 -> 0.592
-Confusion Matrix:
- [[ 53  10   8  11   2  14   4]
- [  5 125   2   9   7   0   1]
- [ 31  12 137  29  15  35  67]
- [ 10   4   5 102  17   4  15]
- [  1   7   4   1  58   2   7]
- [  6   3   1   3   2  43   7]
- [ 13   2   2   8   2  20  74]]
-Node Classification on random seed  4245 -> 0.604
-Confusion Matrix:
- [[ 84   3   5   2   2  15  18]
- [  4 121   1   4  12  10   3]
- [ 19  25 121  35  40  29  33]
- [  6   5   9  99   5   3  18]
- [  4   8   4   0  57   0   0]
- [  8   3   0   1   3  47   3]
- [ 12   1   7   1  11  24  75]]
-Node Classification on random seed  4246 -> 0.615
-Confusion Matrix:
- [[ 74   3   4   3   4  10  10]
- [  3 125   6   1  11   1   3]
- [ 32  20 140  48  37  16  33]
- [  7   3  24 100   6   5   8]
- [  1  10   2   2  58   1   1]
- [  6   0   2   0   0  50   7]
- [ 10   6  13  13   6   7  68]]
-Node Classification on random seed  4247 -> 0.617
-Confusion Matrix:
- [[ 50   3   3  12   8   8  13]
- [  3 124   8   6  16   2   4]
- [ 16  24 155  39  27  15  33]
- [  9   3  20  87   7  11  10]
- [  0   8   4   4  70   1   2]
- [  4   1   0   3   0  47  12]
- [  8   4   9  10   9   4  84]]
-Node Classification on random seed  4248 -> 0.598
-Confusion Matrix:
- [[ 80   3   2   2   1   9   8]
- [  7 109  13   0  13   7   0]
- [ 23  45 151  19  22  14  40]
- [ 18   4  19  89   6   5  13]
- [  3   7   5   2  60   0   2]
- [  7   3   2   7   1  42   6]
- [ 17   2  13   7  13  12  67]]
-Node Classification on random seed  4249 -> 0.608
-Confusion Matrix:
- [[ 56   3   7   2   7  11  16]
- [ 10 107   7   2  12   3   2]
- [ 20  19 147  31  28  19  31]
- [ 12   4  19 107   9   3  14]
- [  1   7   3   5  60   0   0]
- [  2   1   4   2   2  48   8]
- [ 13   5   5  11  15  17  83]]
-Node Classification on random seed  4250 -> 0.556
-Confusion Matrix:
- [[ 56   3   7   8   2   8  17]
- [  6 129   1   3   3   3   4]
- [ 17  29 112  66  47  33  21]
- [  7   2  37 100   6   5  14]
- [  1   9   1   3  47   1   7]
- [  4   2   1   0   2  38   6]
- [ 15   3  10  11   7  12  74]]
-Node Classification on random seed  4251 -> 0.565
-Confusion Matrix:
- [[ 69   2  11  18   3   5   2]
- [  6 109  16   1  13   1   3]
- [ 23  22 117  31  31  30  49]
- [ 23   7  13 105   2  10   6]
- [  0   3  11   2  51   2   2]
- [ 15   1   4   2   0  42   3]
- [ 19   4  13  10   3  13  72]]
-Node Classification on random seed  4252 -> 0.606
-Confusion Matrix:
- [[ 72   2   8   5   9  11  10]
- [  3 140   3   6   2   6   0]
- [  8  31 133  68  21  11  34]
- [ 14   8  19  94   1   6  14]
- [  0   5   4   5  57   2   2]
- [  7   1   0   1   1  43  11]
- [ 13   5   6  14   4  13  67]]
-Node Classification on random seed  4253 -> 0.637
-Confusion Matrix:
- [[ 70   3   2   2   2  15  19]
- [  3 129   7   6   3   4   5]
- [ 18  34 137  36  37  14  23]
- [ 12   6  25  93   3   8  10]
- [  1   3   1   2  72   2   2]
- [  5   2   0   3   1  48   8]
- [  4   4   9   8   1  10  88]]
-Node Classification on random seed  4254 -> 0.621
-Confusion Matrix:
- [[ 61   1   9   5   3  15  16]
- [  3 132   2  11   6   5  10]
- [ 25  14 132  56  29  16  36]
- [  5   3   7 110   8   1   9]
- [  1   5   2   1  56   3   1]
- [  2   0   1   5   3  55   4]
- [ 13   2   4  14   7  16  75]]
-Node Classification on random seed  4255 -> 0.594
-Confusion Matrix:
- [[ 71   8   6   2   2   6  13]
- [  3 137   6   2   6   2   2]
- [ 29  22 126  60  18  18  50]
- [  8   2  17  96  11   5  13]
- [  3  16   2   3  50   0   4]
- [  9   0   3   1   3  30   8]
- [ 10   2   9   5   5  12  84]]
-Node Classification on random seed  4256 -> 0.639
-Confusion Matrix:
- [[ 68   4   6   5   4  17  14]
- [  2 132   6   1   6   2   1]
- [ 18  24 145  39  17  24  26]
- [ 15   1   6 106  14  12   9]
- [  1   5   3   4  72   0   1]
- [  1   3   8   3   1  47   1]
- [  9   1   9   6   9  23  69]]
-Node Classification on random seed  4257 -> 0.631
-Confusion Matrix:
- [[ 73   1   0   6   9  15   7]
- [  4 130   7   5  15   3   5]
- [ 20  18 148  20  32  19  44]
- [ 21   6  12 102  10   2  12]
- [  5   0   3   2  58   2   1]
- [  8   0   3   1   1  42   7]
- [  4   4   4   7  10  14  78]]
-Node Classification on random seed  4258 -> 0.637
-Confusion Matrix:
- [[ 72   1   4   3   6  10  11]
- [  6 126   6   4  12   1   1]
- [ 21  19 157  31  27  26  29]
- [  6   3  14  97  10  11  16]
- [  2   5   3   5  57   1   1]
- [ 13   0   0   1   1  47   5]
- [ 11   4   7   8   3  15  81]]
-Node Classification on random seed  4259 -> 0.57
-Confusion Matrix:
- [[ 74   0   1   5   8   8   6]
- [  7 109  14   3   3   3   9]
- [ 30  21 130  45  27  41  25]
- [ 16   5   3  91   5  16  24]
- [  2   9  10   1  50   1   1]
- [ 11   0   1   1   4  40   3]
- [ 18   2   8  10   9  14  76]]
-Node Classification on random seed  4260 -> 0.634
-Confusion Matrix:
- [[ 72   3   1  13   1   8  15]
- [  2 129   6   4  14   0   2]
- [ 19  29 140  47  23   9  46]
- [ 18   7   8  97   2   1  20]
- [  1   5   6   0  61   1   3]
- [  7   4   1   3   1  44   6]
- [  5   8   7   4   4   2  91]]
-Node Classification on random seed  4261 -> 0.618
-Confusion Matrix:
- [[ 70   2   3   6   6  10  16]
- [  6 138   5   0   5   0   2]
- [ 34  25 135  26  12  31  36]
- [ 22   3  19  83   8  11  12]
- [  1   3   4   1  65   0   0]
- [ 10   1   5   1   0  34   7]
- [ 18   3   6   5   5  12  93]]
-Node Classification on random seed  4262 -> 0.606
-Confusion Matrix:
- [[ 73   1   1   2   9  19   2]
- [  4 106   9   6  10   1   4]
- [ 39  28 139  20  27  31  38]
- [  9   2  13 100  15   4  16]
- [  0   3   7   0  63   4   6]
- [  3   0   2   0   0  47  12]
- [ 15   0  10   3  10   9  78]]
-Node Classification on random seed  4263 -> 0.631
-Confusion Matrix:
- [[ 79   1  13   0   0   9  11]
- [  1 112   8   2  11   7   0]
- [  7  32 171  27  20  38  36]
- [ 10   5  14  90   2  11  12]
- [  1  10   9   4  58   1   2]
- [  2   2   3   4   0  49   0]
- [  5   8  10   1   5  25  72]]
-Node Classification on random seed  4264 -> 0.578
-Confusion Matrix:
- [[ 75   1   4   3   5  10   6]
- [  6 119   7   4  17   3   1]
- [ 29  25 114  57  33  28  35]
- [ 14   1  11  87   6   1  10]
- [  0  10   7   2  57   2   2]
- [ 11   0   7   4   0  44   2]
- [  9   4  18   7   7  13  82]]
-Node Classification on random seed  4265 -> 0.601
-Confusion Matrix:
- [[ 61   1   1   9   4  15  15]
- [  7 111  11   7   7  10   4]
- [ 24   7 157  21  37  40  29]
- [ 13   1  25  99   4   5   8]
- [  4   3   3   2  61   0   6]
- [  9   1   0   3   1  46   3]
- [  7   0   6  13   8  25  66]]
-Node Classification on random seed  4266 -> 0.606
-Confusion Matrix:
- [[ 64   1   8   8   3  11  13]
- [  4 118   7   0   5   1   7]
- [ 15  17 167  28  23  29  37]
- [  4   3  18  95  12  13  11]
- [  2   3   5   1  67   0   5]
- [  2   0  10   2   0  36   8]
- [ 10   4  13   5   9  37  59]]
-Node Classification on random seed  4267 -> 0.584
-Confusion Matrix:
- [[ 73   3  16   3   6   9  10]
- [  5 116  14   3  10   6   5]
- [ 23  19 109  44  35  31  43]
- [ 12   4   8 101   6   9   9]
- [  1   7   2   0  62   1   2]
- [ 10   0   3   3   0  47   5]
- [ 19   2   9   3   9   7  76]]
-Node Classification on random seed  4268 -> 0.639
-Confusion Matrix:
- [[ 52   4   3  15   1   3  20]
- [  4 126   5   1  12   6   3]
- [ 20  16 174  21  27  21  45]
- [ 10   6  13  93   6  10  16]
- [  1   3   1   2  61   3   0]
- [  7   0   3   4   1  42   6]
- [ 12   2   3   8   5  12  91]]
-Node Classification on random seed  4269 -> 0.59
-Confusion Matrix:
- [[ 69   0   4   5   3   7  17]
- [  6 108   5   6  10   4   2]
- [ 26  25 138  35  26  21  43]
- [  7   6  28  94  11   5  16]
- [  3   6   2   3  65   0   4]
- [  9   2   3   2   0  44   5]
- [  7   4  14   7   3  18  72]]
-Node Classification on random seed  4270 -> 0.638
-Confusion Matrix:
- [[ 77   4   1   2   3  16   8]
- [  6 120  12   2   9   3   1]
- [ 26  23 146  38  27  19  23]
- [  8   4  17  95   8   8  14]
- [  2   8   5   1  65   0   2]
- [  4   0   2   0   1  48   7]
- [ 12   3  12   7  10   4  87]]
-Node Classification on random seed  4271 -> 0.603
-Confusion Matrix:
- [[ 59   3   8  12   2  16   9]
- [  6 123   1   4   6   4   7]
- [ 27  23 133  35  28  32  38]
- [  5   3  27 114   2   8   4]
- [  1   3   5   3  53   1   0]
- [  5   0   5   2   0  37   2]
- [ 12   2  13  10   7  16  84]]
-Node Classification on random seed  4272 -> 0.629
-Confusion Matrix:
- [[ 80   5   6   5   1  17   5]
- [  3 122  13   3   2   3   3]
- [ 23  19 141  50  29  31  29]
- [ 13   2  20  96   7   4  10]
- [  0   8   1   0  64   3   1]
- [  5   0   2   3   0  50   2]
- [  5   2   7   8   2  19  76]]
-Node Classification on random seed  4273 -> 0.649
-Confusion Matrix:
- [[ 80   1   8   5   5   9   4]
- [  7 134   3   3   7   4   4]
- [ 15  30 129  43  23  24  24]
- [  6   5  14 115   2   7   5]
- [  0   8   5   3  62   2   2]
- [ 11   1   1   2   1  48   2]
- [ 10   3   8   3   4  27  81]]
-Node Classification on random seed  4274 -> 0.626
-Confusion Matrix:
- [[ 58   7   3   4   0  21  20]
- [  4 131   5   6   3   2   4]
- [ 34  16 150  18  18  26  49]
- [ 17   7   7 115  13   6   8]
- [  0   9   1   1  55   1   2]
- [  5   1   3   2   3  44   4]
- [  9   0   9   8  11   7  73]]
-Node Classification on random seed  4275 -> 0.594
-Confusion Matrix:
- [[ 59   8   2   5   3  15   6]
- [  2 130   8   6  11   1   4]
- [ 30  32 100  40  34  23  42]
- [  6   5  12 107   8   7  17]
- [  1  13   2   1  62   4   1]
- [  4   2   3   2   0  54   4]
- [ 12   4   5   7   3  11  82]]
-Node Classification on random seed  4276 -> 0.606
-Confusion Matrix:
- [[ 77   3   3   6   4   7  11]
- [  4 139   5   5   3   5   4]
- [ 29  16 127  46  35  19  43]
- [ 20   4  11 100   2   9   7]
- [  3   5   0   1  61   0   4]
- [  8   1   4   2   1  34   5]
- [ 15   2   9   3  13  17  68]]
-Node Classification on random seed  4277 -> 0.611
-Confusion Matrix:
- [[ 66   4   5   7   4  14   5]
- [  7 138   4   2  10   1   8]
- [ 36  36 134  31  27  22  29]
- [  9   6  12  97   3  12   9]
- [  1   6   7   1  65   0   1]
- [  8   3   0   0   1  39   4]
- [ 13   3  12   9   2  15  72]]
-Node Classification on random seed  4278 -> 0.606
-Confusion Matrix:
- [[ 77   1   8   6   3  10   7]
- [  2 115   9   3   9   3   5]
- [ 18  35 144  54  25  21  39]
- [ 17   2   7 102   8   6  12]
- [  1   5   3   4  52   0   1]
- [  3   0   1   1   2  46   4]
- [ 13   4  10   9  11  12  70]]
-Node Classification on random seed  4279 -> 0.577
-Confusion Matrix:
- [[ 66   2   7   8   5  16   8]
- [  2 114   9   4  11   7   6]
- [ 24  17 152  42  30  28  38]
- [ 12   8  25  84  10  12  11]
- [  2   4   2   3  60   4   3]
- [  3   2   5   1   0  32   4]
- [  6   2  11   8   3  18  69]]
-Node Classification on random seed  4280 -> 0.588
-Confusion Matrix:
- [[ 79   3  14   3   5   9   6]
- [  5 132   9   0   1   9   7]
- [ 36  23 132  32  47   9  30]
- [ 10   1  19  94   7  16   9]
- [  1   5   6   2  47   1   0]
- [ 11   1   0   3   3  37  10]
- [ 22   4   5  10  13   5  67]]
-Node Classification on random seed  4281 -> 0.581
-Confusion Matrix:
- [[ 79   1   4   2   4   8   7]
- [ 11 118   5   1  12   1   3]
- [ 24  20 117  38  46  38  22]
- [ 16   3  19  79  15   8   9]
- [  7   6   2   1  64   2   2]
- [ 10   1   1   0   1  52   4]
- [  2   4  15   6   8  30  72]]
-Node Classification on random seed  4282 -> 0.604
-Confusion Matrix:
- [[ 72   1   4   4   4  13  10]
- [  3 111   6   2   6   8   4]
- [ 34  15 128  49  21  21  43]
- [ 12   3  22 103  11   4  13]
- [  1   9   4   1  56   1   0]
- [  4   0   2   4   0  53   6]
- [ 12   6   4   5  15   9  81]]
-Node Classification on random seed  4283 -> 0.674
-Confusion Matrix:
- [[ 64   2  12   3   3  10  10]
- [  4 131   4   3  12   1   4]
- [ 18  13 159  38  17  15  25]
- [ 14   2   8 121   8   1  15]
- [  6   3   8   3  64   0   4]
- [  4   0   2   0   3  38   9]
- [ 11   3   8   6   7   7  97]]
-Node Classification on random seed  4284 -> 0.643
-Confusion Matrix:
- [[ 77   2   3   4   1  17   5]
- [ 13 103   5   2   8   0   1]
- [ 23  35 171  24  18  23  39]
- [  5   3  27  93   4   4  11]
- [  1   5   2   1  62   2   3]
- [ 11   0   2   0   2  44   4]
- [ 18   5   8  10   2   4  93]]
-Node Classification on random seed  4285 -> 0.597
-Confusion Matrix:
- [[ 47   4  10  22   4   6  18]
- [  4 129   7   5   6   2   4]
- [ 19  24 127  36  21  29  44]
- [ 10   7  19  95  10   5  10]
- [  1   6   6   1  51   2   3]
- [  9   0   4   1   0  52   6]
- [  9   3   6  10   5   5  96]]
-Node Classification on random seed  4286 -> 0.61
-Confusion Matrix:
- [[ 65   6   3   6   4  12   3]
- [  3 133   1   1   7   1   7]
- [ 19  17 146  40  27  35  40]
- [ 15   3  17  96   6   5  12]
- [  1  12   7   7  53   0   2]
- [  4   0   2   4   1  42   9]
- [  8   4   4   7   8  20  75]]
-Node Classification on random seed  4287 -> 0.574
-Confusion Matrix:
- [[ 69   5   5   4   5  16   8]
- [ 11 107   6   6   6   3   1]
- [ 31  25 117  27  64  26  30]
- [ 15   1  18  83   4  11  12]
- [  4   4   4   6  64   0   0]
- [  5   0   1   0   0  46  11]
- [ 13   3  12   3   9  11  88]]
-Node Classification on random seed  4288 -> 0.619
-Confusion Matrix:
- [[ 60   4   2   8   3  13  24]
- [  5 127   2   2  10   5   5]
- [  9  19 142  27  38  27  43]
- [  6  12  11 105   6   6  11]
- [  0   5   2   3  62   0   3]
- [  2   2   2   1   1  35  14]
- [  4   3   4   9  15  13  88]]
-Node Classification on random seed  4289 -> 0.624
-Confusion Matrix:
- [[ 76   2   5   3   9   8  10]
- [  2 136   2   3  10   1   8]
- [ 37  27 134  31  24   8  60]
- [ 17   8  11  97   4   3  12]
- [  2   4   3   0  55   0   1]
- [  4   2   2   1   0  46   8]
- [ 11   2  11   2   6  12  80]]
-Node Classification on random seed  4290 -> 0.617
-Confusion Matrix:
- [[ 68   1   6   8   5   4   4]
- [  1 133   3   4  12   7   7]
- [ 25  15 122  42  28  36  36]
- [ 13   1  10 113  15   5  12]
- [  2   3   1   1  64   2   3]
- [  6   1   2   2   0  45   3]
- [ 15   4  15   3   7  13  72]]
-Node Classification on random seed  4291 -> 0.648
-Confusion Matrix:
- [[ 78   8   2   5   5   8   9]
- [  4 127   8   1   5   3   3]
- [ 43  34 154  23  14  23  31]
- [ 15   1  19  90   4   3  14]
- [  2   5   8   0  57   0   2]
- [  4   3   0   1   0  51   5]
- [ 14   5   7   2   2   7  91]]
-Node Classification on random seed  4292 -> 0.61
-Confusion Matrix:
- [[ 61   1   8  11   2   8  20]
- [  5 125   9   7   1   3   7]
- [ 42  20 147  30  27   9  28]
- [  8   0  24  86  17  11  13]
- [  1   3   5   3  57   0   2]
- [  9   1   3   6   2  46   3]
- [  3   4  10   8   9   7  88]]
-Node Classification on random seed  4293 -> 0.611
-Confusion Matrix:
- [[ 67   3   6  11   5   2   6]
- [  1 135   2   3  10   0   3]
- [ 21  30 139  24  28  29  52]
- [  7  13  14  91   5   8  21]
- [  1   6   0   2  66   0   3]
- [  0   1   1   2   1  36  19]
- [ 10   4   4  11  10  10  77]]
-Node Classification on random seed  4294 -> 0.624
-Confusion Matrix:
- [[ 60   0   2  13   2   6   9]
- [  2 147   7   4   3   5   3]
- [ 27   8 113  48  41  25  36]
- [  7   0  15 112   8   1  16]
- [  2   6   2   2  64   0   7]
- [  8   1   0   7   0  57   0]
- [ 15   0   7  20   4   7  71]]
-Node Classification on random seed  4295 -> 0.635
-Confusion Matrix:
- [[ 65   0   5   5   5  14   4]
- [  3 142   3   4   7   3   1]
- [ 39  15 144  45  24  28  32]
- [  9   0  21 102   1   3   7]
- [  1   5   5   1  56   0   1]
- [  6   0   5   1   2  49   2]
- [ 15   4   7   6   3  23  77]]
-Node Classification on random seed  4296 -> 0.584
-Confusion Matrix:
- [[ 60   3   4   5   4  11  16]
- [  4 132   5   0   9   1   1]
- [ 34  11 140  37  32  31  34]
- [ 16   6  13  86   3   6  16]
- [  5   6   3   2  67   0   6]
- [  7   1   3   2   7  32   3]
- [ 11   7  15   7  13  16  67]]
-Node Classification on random seed  4297 -> 0.613
-Confusion Matrix:
- [[ 79   2   5   8   7   4  13]
- [  3 127   8   2   9   2   6]
- [ 14  20 122  53  15  27  47]
- [ 11   1  17 106   4   5   6]
- [  1   4   7   0  57   0   5]
- [  4   2  13   5   5  38   2]
- [ 20   2  12   3   3  10  84]]
-Node Classification on random seed  4298 -> 0.641
-Confusion Matrix:
- [[ 70   2   5   4   5  10   7]
- [  8 139   3   4   5   1   3]
- [ 17  14 142  43  27  12  37]
- [ 10   5  16  97   5   5  29]
- [  0   8   4   2  75   0   2]
- [  6   1   2   4   1  40   3]
- [ 13   3   9   9   3  12  78]]
-Node Classification on random seed  4299 -> 0.626
-Confusion Matrix:
- [[ 61   1   5   0   4  15  25]
- [  6 140   3   4   3   2   4]
- [ 17  17 155  38  30  24  36]
- [  2   7  11 103  16   7  16]
- [  1   7   3   1  57   0   2]
- [ 11   0   2   2   1  32   6]
- [  9   2   6   4   7  17  78]]
-Node Classification on random seed  4300 -> 0.622
-Confusion Matrix:
- [[ 61   3   4   4   6  17  10]
- [  2 116   7   1   8   8  11]
- [ 16  16 153  42  20  28  38]
- [ 10   1  20  90   3   9  10]
- [  2   4   5   1  67   0   7]
- [  1   0   1   6   0  49   3]
- [ 12   1  14   8   6  13  86]]
-Node Classification on random seed  4301 -> 0.585
-Confusion Matrix:
- [[ 85   4   0   6   8   6   9]
- [  4 128   5   2   7   6   4]
- [ 26  46 115  38  29  18  40]
- [ 13   6  14 104   2   4  10]
- [  0   8   2   1  51   2   1]
- [  6   2   6   0   3  40  11]
- [ 13   8   8   6  20  11  62]]
-Node Classification on random seed  4302 -> 0.657
-Confusion Matrix:
- [[ 63   2   4   7   9   8   9]
- [  2 132  10   4   2   5   4]
- [ 34  17 158  28  13  30  44]
- [ 12   2  11 106   3   7  14]
- [  0   9   2   0  63   0   0]
- [  6   0   3   3   2  47   1]
- [  7   1   8   6   2  12  88]]
-Node Classification on random seed  4303 -> 0.637
-Confusion Matrix:
- [[ 79   5   5   3   0   6  13]
- [  2 126   7   1   5   7   6]
- [ 26  30 161  24  28  17  27]
- [ 10   6  18  95   7   1  19]
- [  1   7   4   1  63   2   4]
- [ 10   3   3   1   1  36   4]
- [ 10   0  12   4   9  14  77]]
-Node Classification on random seed  4304 -> 0.606
-Confusion Matrix:
- [[ 63   6   4   1   3  23  10]
- [  6 119   9   3   5   8   2]
- [ 19  21 130  47  20  21  38]
- [ 13   2  15 106   9   6   9]
- [  2   6   2   2  57   1   1]
- [  4   1   7   5   0  50   3]
- [ 12   1   8   8   6  25  81]]
-Node Classification on random seed  4305 -> 0.624
-Confusion Matrix:
- [[ 81   2   2   5   1  17   3]
- [  4  94  21   6   9   2   0]
- [ 28  18 149  50  29  24  22]
- [ 17   5  11 117   5   5   5]
- [  2   5   2   1  69   0   2]
- [  6   1   2   2   1  44   6]
- [  9   4   7  13   6  16  70]]
-Node Classification on random seed  4306 -> 0.597
-Confusion Matrix:
- [[ 59   5   4   0   5  18  20]
- [  4 129  11   5   6   5   8]
- [ 25  14 142  39  19  26  33]
- [ 17   1   9  86   6   2  27]
- [  1  11   3   2  63   0   4]
- [  8   1   6   0   2  35   7]
- [  5   7   6   3  10  18  83]]
-Node Classification on random seed  4307 -> 0.621
-Confusion Matrix:
- [[ 71   0   2   3   5   9  16]
- [  7 132   7   3   5   1   5]
- [ 30  20 133  31  23  19  52]
- [  7   5  12 106  12   6  19]
- [  3   9   3   0  64   0   2]
- [  2   4   2   4   0  41   3]
- [ 18   2   2   3   8  15  74]]
-Node Classification on random seed  4308 -> 0.609
-Confusion Matrix:
- [[ 57   5   6   6   3  13   9]
- [  5 143   4   1   3   0   0]
- [ 23  14 129  32  40  32  43]
- [ 10   3  11 109   3   6  13]
- [  3  11   3   1  58   0   2]
- [ 12   2   1   2   1  39   1]
- [ 20   5   6   8   6  22  74]]
-Node Classification on random seed  4309 -> 0.619
-Confusion Matrix:
- [[ 63   5   2   1   3  19   8]
- [  2 138   3   4  11   2   2]
- [ 45  24 130  23  30  26  42]
- [ 13   2  15  96   6   5  13]
- [  1   6   3   4  59   0   0]
- [  3   3   1   0   0  54   7]
- [  7   5  11   7   5  12  79]]
-Node Classification on random seed  4310 -> 0.597
-Confusion Matrix:
- [[ 68   1   4   3   5  16  12]
- [  7 116   8   3  12   3  13]
- [ 17   9 139  55  24  18  36]
- [ 16   4  10  99   6  13  11]
- [  1   3   1   6  57   0   4]
- [  5   1   2   3   0  49   7]
- [  9   4  16   8   9  18  69]]
-Node Classification on random seed  4311 -> 0.62
-Confusion Matrix:
- [[ 59   3   5   5   5  16  13]
- [  3 120   3   1   4   7   2]
- [ 22  18 154  17  26  31  52]
- [  5   1  16 102   5   5  17]
- [  2   7   2   1  58   2   0]
- [  7   1   0   0   0  52   9]
- [  3   8  12   6  19  19  75]]
-Node Classification on random seed  4312 -> 0.588
-Confusion Matrix:
- [[ 70   5   6   3   4  10  11]
- [  5 136   7   3   6   0   3]
- [ 22  30 115  56   9  32  36]
- [  6   3  18  98   6   9  15]
- [  2   5  14   2  63   2   0]
- [  7   0   4   1   2  37  11]
- [  8   6  14   8   8  13  69]]
-Node Classification on random seed  4313 -> 0.588
-Confusion Matrix:
- [[ 79   2   1   3   2   9   8]
- [  1 106   4   9   5   8   4]
- [ 29  35 107  35  36  17  59]
- [ 10   1  22 102   7   5  19]
- [  6  10   3   2  57   0   5]
- [  2   2   3   5   1  45   6]
- [  7   2   3   8   1  15  92]]
-Node Classification on random seed  4314 -> 0.604
-Confusion Matrix:
- [[ 73   2   6   1   3   8  16]
- [  8 138   3   4   7   3   3]
- [ 19  23 131  42  20  19  47]
- [ 19   4  11  92  15   2  14]
- [  2   3   6   1  63   2   2]
- [  8   0   7   5   0  35   6]
- [  9   3  15   3   9  16  72]]
-Node Classification on random seed  4315 -> 0.628
-Confusion Matrix:
- [[ 63   4   2  12   6   1  13]
- [  5 136   7   3  12   3   6]
- [ 20  17 159  37  25  13  47]
- [ 10   3  10 101   5  10   8]
- [  2   2   5   0  49   1   5]
- [ 17   0   4   1   1  42   7]
- [ 15   2   4  12   7   8  78]]
-Node Classification on random seed  4316 -> 0.619
-Confusion Matrix:
- [[ 72   2   5   1   6   9  10]
- [  7 125   1   0  11   7   4]
- [ 31  24 149  13  31  23  50]
- [ 16   9  13  89   2   7  14]
- [  0   5   4   1  76   1   4]
- [  9   2   2   1   0  40   5]
- [ 13   1  10   2   6  19  68]]
-Node Classification on random seed  4317 -> 0.63
-Confusion Matrix:
- [[ 72   0   8   7   3   8  10]
- [  9 124   8   3   5   1   2]
- [ 19  14 163  40  31  13  41]
- [  6   2  13  81   8   6  21]
- [  2   5   2   1  72   0   1]
- [  7   0   2   3   0  43   8]
- [ 20   2  16  13   9   1  75]]
-Node Classification on random seed  4318 -> 0.597
-Confusion Matrix:
- [[ 52   5   4   7   2  10  18]
- [ 12 118   9   1   4   1   7]
- [ 23  10 133  54  23  23  49]
- [  7  13  18 102   2  10  11]
- [  2   7   3   1  58   0   6]
- [  3   2   2   0   0  55   6]
- [  8   3   9   4   4  20  79]]
-Node Classification on random seed  4319 -> 0.662
-Confusion Matrix:
- [[ 65   3   3   5   5  11  10]
- [  7 133   7   3   2   3   6]
- [ 21  28 155  18  34  13  42]
- [ 16   2  13 126   6   3   6]
- [  2   7   2   0  52   1   5]
- [  5   0   5   1   0  41   8]
- [  4   7   7   4   7   6  90]]
-Node Classification on random seed  4320 -> 0.571
-Confusion Matrix:
- [[ 78   9   1  12   8  12   7]
- [ 10 113   8   3  10   3   4]
- [ 20  27 109  54  25  21  54]
- [  7   5  17  73   6   3  15]
- [  2   3   5   0  60   2   2]
- [  5   0   0   4   3  52   2]
- [ 16   7  14   3   3  17  86]]
-Node Classification on random seed  4321 -> 0.644
-Confusion Matrix:
- [[ 81   1   2   3   5   5   7]
- [  6 122   8   3   6   2   2]
- [ 39  10 159  32  17  27  39]
- [  7   4  14  94   7   9  18]
- [  1   5   0   0  77   1   5]
- [ 11   1   0   0   2  48   8]
- [ 20   2  10   8   3   6  63]]
-Node Classification on random seed  4322 -> 0.616
-Confusion Matrix:
- [[ 63   4   2   2   3  15   7]
- [  1 140   4   3   1   1   0]
- [ 33  25 133  44  25  30  19]
- [ 15   5  12 107   8   7  24]
- [  0   8   2   1  63   3   4]
- [ 11   2   3   1   1  38   3]
- [ 11   1  12   9   5  17  72]]
-Node Classification on random seed  4323 -> 0.629
-Confusion Matrix:
- [[ 76   4   8   3   4  10   8]
- [  3 133   6   2   7   2   3]
- [ 27  25 146  29  14  36  28]
- [  6   5  25 116   1   5  12]
- [  2   6   5   5  49   1   1]
- [  2   5   2   0   1  42   7]
- [  9   4  17   6   9  16  67]]
-Node Classification on random seed  4324 -> 0.627
-Confusion Matrix:
- [[ 72   1   7   3   6   8   7]
- [  4 132   4   2   8   4   1]
- [ 36  25 138  31  31  22  36]
- [  8   3  12 104  13   6  10]
- [  0   8   5   1  56   3   1]
- [  3   2   1   6   0  42   2]
- [ 10   2  15   8   5  13  83]]
-Node Classification on random seed  4325 -> 0.605
-Confusion Matrix:
- [[ 58   3  10   4   5  14  13]
- [  6 122   6   3  11   0   7]
- [ 19  18 145  33  26  19  49]
- [  7   8  17 102   2   4  16]
- [  1   7   8   0  62   0   2]
- [  4   3   0   2   4  36  13]
- [ 13   3   4   2  18  11  80]]
-Node Classification on random seed  4326 -> 0.61
-Confusion Matrix:
- [[ 63   1  10   5   4  11   9]
- [  2 116   4   0   7   2   8]
- [ 24  16 147  25  32  30  30]
- [ 11   5  11 114   8   6  14]
- [  1   5   1   2  62   1   7]
- [ 10   6   2   2   3  44   7]
- [ 23   3   3   9   5  25  64]]
-Node Classification on random seed  4327 -> 0.623
-Confusion Matrix:
- [[ 65   7   5   2   5  15   5]
- [  5 139   6   0   4   0   3]
- [ 12  28 159  35  40  12  29]
- [  7   6  17  87   7   2  14]
- [  1  14   5   4  51   1   1]
- [  7   2   2   1   5  51   1]
- [ 10   8  14  15   2  18  71]]
-Node Classification on random seed  4328 -> 0.538
-Confusion Matrix:
- [[ 55   3   2  13   4  16  22]
- [  2 116   4   6   9   5   2]
- [ 29  29 100  38  71  18  49]
- [  7   4  11 105   3  12  14]
- [  0   8   2   3  58   0   2]
- [  6   1   0   3   1  39   5]
- [ 11   3   7  14   4  19  65]]
-Node Classification on random seed  4329 -> 0.597
-Confusion Matrix:
- [[ 74   3   2   2   1  10  20]
- [  4 112   5   0  15   1   2]
- [ 28  22 129  26  26  27  60]
- [  6   9  16  90   3   3  23]
- [  3   5   4   2  54   2   3]
- [  0   2   2   1   2  40   9]
- [  6  10   7  13   6  12  98]]
-Node Classification on random seed  4330 -> 0.615
-Confusion Matrix:
- [[ 62   1   2   3   4  25  12]
- [  2 119   8   2  11   6   4]
- [ 19  25 138  25  26  26  35]
- [ 14   1  20 108   5   7  19]
- [  0   2   6   1  64   0   2]
- [  1   0   3   3   0  49   9]
- [ 11   2   4   5  14  20  75]]
-Node Classification on random seed  4331 -> 0.646
-Confusion Matrix:
- [[ 66   2   2   5   4   9   9]
- [  6 135   7   2  11   4   4]
- [ 32  25 149  24  18  24  35]
- [  6   0  15 101   6   7  14]
- [  2   5   4   0  65   0   2]
- [  5   0   2   3   0  55   2]
- [ 11   3  10   8   6  20  75]]
-Node Classification on random seed  4332 -> 0.611
-Confusion Matrix:
- [[ 70   1   3   9   2  11  17]
- [  3 120   7   9  16   1  10]
- [ 28  20 143  29  21  23  39]
- [ 11   3  16  93   4   7  12]
- [  1   4   5   3  69   0   4]
- [  5   2   5   1   1  51   2]
- [  9   1  12  11   4  17  65]]
-Node Classification on random seed  4333 -> 0.58
-Confusion Matrix:
- [[ 61   2   1   5   9  17   3]
- [  8 131   4   2   8   3   5]
- [ 30  16 130  20  20  52  44]
- [ 17   4  20  83   4  16  12]
- [  1   5   2   0  68   5   2]
- [  5   0   4   1   2  34   8]
- [ 21   3   6   2   6  25  73]]
-Node Classification on random seed  4334 -> 0.599
-Confusion Matrix:
- [[ 68   0   4   6   3  16   5]
- [  1 133   4   9   5  10   3]
- [ 14  39 138  33  21  42  24]
- [ 22   3  15  73   4  22   9]
- [  0   5   0   2  65   1   4]
- [  5   0   3   1   1  48  10]
- [ 10   4  12   7   7  15  74]]
-Node Classification on random seed  4335 -> 0.632
-Confusion Matrix:
- [[ 69   4   3   3   2  19   3]
- [ 18 122   5   2   6   2   2]
- [ 31  19 127  29  19  19  29]
- [ 17   8   6 108   4   7  22]
- [  2   5  13   2  64   0   1]
- [  4   0   2   2   0  45   3]
- [ 15   5   6   6   5  18  97]]
-Node Classification on random seed  4336 -> 0.574
-Confusion Matrix:
- [[ 79   4   0   8   5  12   5]
- [  6  97   8   1  20   3   1]
- [ 25  30 147  29  27  26  40]
- [ 41   6  24  79   4   5   6]
- [  3   2   5   0  59   0   2]
- [  8   0  13   0   0  35   2]
- [ 23   6  10   3   1  12  78]]
-Node Classification on random seed  4337 -> 0.614
-Confusion Matrix:
- [[ 77   3   2   0   6   8  14]
- [  1 115  10   2  11   3   5]
- [ 28  17 155  26  25  31  36]
- [  7   1   9 102   4  11  18]
- [  1  11   6   3  48   2   4]
- [  6   1   2   1   0  45   7]
- [ 14   4   8   8  11  19  72]]
-Node Classification on random seed  4338 -> 0.601
-Confusion Matrix:
- [[ 72   2   2   2  12  14   7]
- [  6 105  13   9   7   6   2]
- [ 29  21 142  34  34  18  37]
- [ 20   2   7 102   2  12  20]
- [  2   7   1   3  52   2   3]
- [ 10   0   0   1   0  51   5]
- [ 11   5   4   5  11  11  77]]
-Node Classification on random seed  4339 -> 0.645
-Confusion Matrix:
- [[ 70   2   4   3   1  15  17]
- [  5 138   2   1   8   0   3]
- [ 20  13 149  38  27  21  47]
- [ 11   2  16 105   4   9  13]
- [  0   5   2   3  59   2   2]
- [  2   2   1   3   0  46   7]
- [  5   3   8  12   4  12  78]]
-Node Classification on random seed  4340 -> 0.601
-Confusion Matrix:
- [[ 65   2  11   8   3  12   9]
- [ 12 131   5   1   4   2   4]
- [ 25  30 130  27  17  36  33]
- [ 19   5  11  90   1   8  20]
- [  0  11   5   2  57   4   6]
- [  7   3   1   2   0  56   3]
- [ 12   5   9   8   3  13  72]]
-Node Classification on random seed  4341 -> 0.588
-Confusion Matrix:
- [[ 78   1  12   3   4   7   9]
- [  3 121   7   6  20   1   3]
- [ 17  17 126  55  60  19  21]
- [ 17   0  12  99  18   3  17]
- [  0   6   3   2  72   0   3]
- [  4   0   5   0   3  36   3]
- [  8   3  17   5  10   8  56]]
-Node Classification on random seed  4342 -> 0.629
-Confusion Matrix:
- [[ 78   1   7   2   2  16   7]
- [  3 128   1   3   4   4   1]
- [ 31  49 143  30  21  19  26]
- [  4   2  23 113   6   7  16]
- [  1  10   2   4  52   2   1]
- [  7   1   0   2   0  46   1]
- [  9   6   8   8   5  19  69]]
-Node Classification on random seed  4343 -> 0.646
-Confusion Matrix:
- [[ 81   1   1   2   1  15   5]
- [  2 121   4   5   6   3   4]
- [ 33  20 142  38  24  16  42]
- [ 14   4  14 110   2   6  11]
- [  1  11   1   1  61   0   4]
- [  5   1   4   1   0  52   2]
- [  8   3   9   6   7  17  79]]
-Node Classification on random seed  4344 -> 0.624
-Confusion Matrix:
- [[ 69   2   4   3   4  15   7]
- [  1 146   2   1  10   0   4]
- [ 24  23 140  39  42  20  37]
- [ 13   7  10 109   8   2   4]
- [  0   7   6   6  53   1   3]
- [  4   0   4   0   0  41   1]
- [ 11   5   9  15  10  12  66]]
-Node Classification on random seed  4345 -> 0.605
-Confusion Matrix:
- [[ 65   1   9  15   2  18   0]
- [  5 118   9   5  11   9   2]
- [ 24   9 168  26  42  15  32]
- [ 10   7  15  92   7   6  21]
- [  1   2   6   0  55   4   1]
- [  3   0   6   1   0  42   6]
- [  5   1  12  24   6  17  65]]
-Node Classification on random seed  4346 -> 0.627
-Confusion Matrix:
- [[ 77   3  10   3   2  10   8]
- [  8 136  10   1   6   1   5]
- [  9  32 134  36  25  27  33]
- [ 10   6  13 104   2   9  14]
- [  0   2   5   6  67   1   3]
- [  4   0   1   0   1  41  12]
- [ 10   5  15   5   4  16  68]]
-Node Classification on random seed  4347 -> 0.591
-Confusion Matrix:
- [[ 63   1  10   6   4  13  13]
- [  2 128   5   2   5   1   6]
- [  6  23 135  64  16  24  45]
- [ 12   3  18  97   1   6  22]
- [  1  15   3   3  55   1   3]
- [  4   0   9   1   0  43   9]
- [  5   2   6   8   4  27  70]]
-Node Classification on random seed  4348 -> 0.631
-Confusion Matrix:
- [[ 82   4   4   8   4   8   9]
- [  7 118   2   2  12   0   2]
- [ 31  23 140  28  43  21  28]
- [  4   3  23  88  12   5  11]
- [  2  12   0   1  64   1   0]
- [  6   1   1   2   0  41   6]
- [ 16   4   4   3   5  11  98]]
-Node Classification on random seed  4349 -> 0.584
-Confusion Matrix:
- [[ 85   6   2   2   0  13  11]
- [  5 142   8   0   4   1   3]
- [ 25  25  96  42  45  15  52]
- [ 16   6  16  90   2   4  18]
- [  1  12   6   2  49   0   3]
- [  4   4   2   8   0  36   3]
- [  9   6   7  11   6  11  86]]
-Node Classification on random seed  4350 -> 0.555
-Confusion Matrix:
- [[ 65   1   3   4   8  18   4]
- [  0 125  10   4  12   3   7]
- [ 17  12 106  58  61  32  28]
- [ 14   1  27  94   6   6  17]
- [  1   6   0   0  56   1   5]
- [  3   0   1   0   1  46   3]
- [ 11   0   8  16   5  31  63]]
-Node Classification on random seed  4351 -> 0.613
-Confusion Matrix:
- [[ 77   3   2   7   8  17   6]
- [  2 132  12   4   9   1   6]
- [ 29  11 134  38  23  26  44]
- [ 12   3   6  98   7  19   8]
- [  0   8   4   3  54   0   3]
- [  4   1   1   3   0  50   0]
- [ 15   4   3   6  11  18  68]]
-Node Classification on random seed  4352 -> 0.626
-Confusion Matrix:
- [[ 74   3   5   4   2   8  10]
- [  5 123   5   1  13   2   7]
- [ 25  26 146  34  35  19  35]
- [  5   3  14  94   6   4   8]
- [  1   5   9   1  66   2   1]
- [  3   3   3   1   0  44   4]
- [ 17   8   8  12   7  10  79]]
-Node Classification on random seed  4353 -> 0.631
-Confusion Matrix:
- [[ 75   4   6   4   2   4  14]
- [  4 123  11   4   0   5   2]
- [ 29   9 150  48  40  18  40]
- [ 13   3  17 108   2   2  14]
- [  1   3   8   3  52   0   1]
- [  5   1   1   1   0  46  12]
- [ 11   1   9   5   5   7  77]]
-Node Classification on random seed  4354 -> 0.624
-Confusion Matrix:
- [[ 76   2   8   4   2   5   8]
- [  4 113  11   9   7   1   3]
- [ 31  18 142  33  51  14  32]
- [  3   3  11 117   6   5  16]
- [  2   6   2   2  64   1   4]
- [  8   1   4   4   0  52   3]
- [ 11   2  11  13   6   9  60]]
-Node Classification on random seed  4355 -> 0.61
-Confusion Matrix:
- [[ 50   3   6   3   4  15  21]
- [  1 135   6   4  10   4   3]
- [ 21  21 133  41  35  21  42]
- [  7   4  20  88   2   9   6]
- [  0   6   5   4  71   1   2]
- [  2   1   5   1   0  44   8]
- [  9   0   9   7   5  16  89]]
-Node Classification on random seed  4356 -> 0.653
-Confusion Matrix:
- [[ 78   1   5  18   5  10   7]
- [  2 127  12   0  11   2   7]
- [ 19  14 150  16  14  31  39]
- [ 15   7  11 118   6   4   3]
- [  0   8   9   0  61   0   3]
- [  3   1   1   3   3  50   6]
- [ 14   4  13   6   7   7  69]]
-Node Classification on random seed  4357 -> 0.6
-Confusion Matrix:
- [[ 71   3   4   3   7   7   9]
- [  5 114  13   0  12   6   5]
- [ 34  14 159  41  24  26  27]
- [ 27   5  13  75   5  11  14]
- [  4   4   0   5  56   1   4]
- [  4   0  10   2   1  52   8]
- [ 17   4   5   3   4   9  73]]
-Node Classification on random seed  4358 -> 0.603
-Confusion Matrix:
- [[ 59   0   8   6   9   6  15]
- [ 13 115   5   2   5   4   8]
- [ 27  12 126  27  46  25  45]
- [ 10   1  27  98   7   6  11]
- [  0   4   5   2  64   0   5]
- [  7   0   1   1   0  48   9]
- [  3   2   7   6   5  15  93]]
-Node Classification on random seed  4359 -> 0.569
-Confusion Matrix:
- [[ 73   5   6   3   3   3  16]
- [  4 100   2   0  28   5   8]
- [ 31  22 115  24  35  35  48]
- [ 13   4   9 107   8   7  16]
- [  2   9   2   2  50   1   2]
- [ 10   1   2   1   1  52   6]
- [ 19   6   4   6   6  16  72]]
-Node Classification on random seed  4360 -> 0.543
-Confusion Matrix:
- [[ 75   4   7   5   2   9  17]
- [  4 117   8   2  11   4   7]
- [ 39  27 108  26  37  23  37]
- [ 20   1  10  80  15  19   9]
- [  2   6   6   1  61   1   3]
- [  2   1   8   2   2  38   3]
- [ 19   4  26   5  10  13  64]]
-Node Classification on random seed  4361 -> 0.607
-Confusion Matrix:
- [[ 78   0   1   0  10  16  18]
- [  8 133   3   0   8   1   5]
- [ 16  16 125  32  62  25  22]
- [ 14   0  16  83  12   6  15]
- [  3   5   2   0  65   2   1]
- [  8   0   0   2   0  48   7]
- [ 12   7   8   3   9  18  75]]
-Node Classification on random seed  4362 -> 0.583
-Confusion Matrix:
- [[ 74   3   5   4   5  10  16]
- [  4 117  12   5   9   2   4]
- [ 31  25 151  51  31  19  35]
- [ 15   4  33  78   3   3  15]
- [  1   3   2   2  56   2   2]
- [  1   1   2   2   0  40  12]
- [  6   4   5   6  10  12  67]]
-Node Classification on random seed  4363 -> 0.593
-Confusion Matrix:
- [[ 65   2   5   3   9  16  18]
- [  5 113   7   0   6   4   2]
- [ 26  22 135  51  40  27  20]
- [ 12   0  15  98  10   7  11]
- [  2   8   7   0  62   1   3]
- [  4   2   1   1   4  47   6]
- [  5   3  12   4   5  21  73]]
-Node Classification on random seed  4364 -> 0.586
-Confusion Matrix:
- [[ 62   7   2   3   2   8  18]
- [  2 127   9  11   4   1   4]
- [ 23  30 145  40  18  26  29]
- [ 21   1  13  75   2   9  27]
- [  0   7   6   2  51   3   5]
- [ 10   0   5   3   5  40   8]
- [ 10   5  10  10   6   9  86]]
-Node Classification on random seed  4365 -> 0.627
-Confusion Matrix:
- [[ 54   5  14   6   4  12  17]
- [  1 126   5   3   4   1   1]
- [ 17  30 159  37  23  23  29]
- [ 11   5  16 111   1  10   4]
- [  0  11   3   1  62   1   4]
- [  9   3   5   1   1  35   2]
- [ 23   7   5   6   3   9  80]]
-Node Classification on random seed  4366 -> 0.641
-Confusion Matrix:
- [[ 77   2   2   5   0  14   5]
- [  2 121   4   2   8   5   1]
- [ 21  18 152  28  34  26  33]
- [ 16   5   3 109   5  18   8]
- [  4   5   1   0  67   0   8]
- [  1   3   2   2   0  49   8]
- [  8   6  16   5   3  22  66]]
-Node Classification on random seed  4367 -> 0.619
-Confusion Matrix:
- [[ 65  10   6   2  10   4  14]
- [  5 122   5   5  11   0   5]
- [ 18  22 131  43  26  13  53]
- [  5   2   9 120   8   6  22]
- [  0   5   4   2  62   0   0]
- [  9   1   4   3   0  43   2]
- [ 19   6   5   6   3   8  76]]
-Node Classification on random seed  4368 -> 0.623
-Confusion Matrix:
- [[ 82   1   4  12   8   8   4]
- [  5 108   9   1  16   1   4]
- [ 27  12 113  32  39  22  44]
- [  4   2  17 136   7   7   3]
- [  1   7   7   1  64   1   2]
- [  4   1   6   1   0  47  10]
- [ 19   2   7   4   9   6  73]]
-Node Classification on random seed  4369 -> 0.656
-Confusion Matrix:
- [[ 81   4   1   4   2  12   5]
- [  9 145   4   2   5   2   0]
- [ 29  13 158  53  12  13  31]
- [ 10   2  15 101   6  10  14]
- [  1   3   5   2  54   0   4]
- [  8   1   2   1   0  46   5]
- [ 17   1  15   3   3  15  71]]
-Node Classification on random seed  4370 -> 0.616
-Confusion Matrix:
- [[ 66   1   1   2   6   8  15]
- [  5 117   7   4   6   8   4]
- [ 19  18 152  35  24  15  58]
- [  7   5  17  93   4   5  16]
- [  0   7   6   3  56   0   5]
- [  8   3   3   0   2  49   3]
- [  8   5   2   5  13  21  83]]
-Node Classification on random seed  4371 -> 0.671
-Confusion Matrix:
- [[ 63   2   3   3   9  14  12]
- [  3 142   2   1   7   0   5]
- [  9  23 164  45  37  11  32]
- [  5   3  11 112   6   6   6]
- [  1   5   1   3  63   0   1]
- [  5   3   2   1   1  39   6]
- [ 10   2   9   4   7  13  88]]
-Node Classification on random seed  4372 -> 0.585
-Confusion Matrix:
- [[ 56   5   6   2   7  10  18]
- [  5 116   5   3  11   5   8]
- [ 31  22 111  26  40  22  57]
- [ 11   3   7 112  12   9  15]
- [  4   5   4   2  57   4   1]
- [  7   5   1   0   1  44   4]
- [  8   4   7   4   4  10  89]]
-Node Classification on random seed  4373 -> 0.64
-Confusion Matrix:
- [[ 69   2   8   8   4  12  10]
- [ 14 132  14   3   3   2   4]
- [ 12  30 165  24  16  14  39]
- [  7   1  16 103   9  11   8]
- [  3   4   7   4  52   1   1]
- [  4   2   1   6   1  41   3]
- [  9   4  16  10   4   9  78]]
-Node Classification on random seed  4374 -> 0.636
-Confusion Matrix:
- [[ 74   3   5   2   2   0  20]
- [  5 120  12   9  10   7   6]
- [ 22  11 150  61  15  15  34]
- [ 10   1  18 118   5   4  12]
- [  3   5   5   1  55   0   6]
- [  3   1   2   0   0  43   9]
- [ 16   0  14   1   3   6  76]]
-Node Classification on random seed  4375 -> 0.638
-Confusion Matrix:
- [[ 73   1   3   4   5  14  11]
- [  8 134  11   0   3   3   5]
- [ 23  29 148  35  19  15  40]
- [  3   1  18 103   3  16   7]
- [  0   9   2   1  56   0   3]
- [  3   3   1   1   0  45  11]
- [  6   3  11   7   9  15  79]]
-Node Classification on random seed  4376 -> 0.638
-Confusion Matrix:
- [[ 74   1   2   4   1   9  18]
- [  7 125   1   3   5   1   4]
- [ 16  14 142  36  33  19  40]
- [ 13   6  19 102   5   5  11]
- [  3   4   3   0  58   3   3]
- [  8   0   6   1   0  42  13]
- [  6   4  10   8   3  14  95]]
-Node Classification on random seed  4377 -> 0.617
-Confusion Matrix:
- [[ 77   1   3   7   2   9   4]
- [  5 149   3   1   3   0   4]
- [ 22  41 129  34  29  25  35]
- [  7   4  40  83   3   7   8]
- [  5   7   3   2  64   1   2]
- [  0   0   2   4   0  52   5]
- [  9   5   8   3   7  23  63]]
-Node Classification on random seed  4378 -> 0.581
-Confusion Matrix:
- [[ 78   5   2   3   2  27   6]
- [  6 121  12   4  12   3   0]
- [ 38  20 116  32  41  30  34]
- [ 13   4  13  93   6   2  11]
- [  1   7   3   0  60   4   4]
- [  4   0   2   1   1  46   7]
- [ 16   2   6   7   6  22  67]]
-Node Classification on random seed  4379 -> 0.598
-Confusion Matrix:
- [[ 80   2   9   4   6  12   9]
- [  6 132   2   0  14   2   5]
- [ 23  29 132  36  25  25  35]
- [ 16   1  20  99   8   4  10]
- [  1   3   3   1  71   0   1]
- [  6   1   2   1   5  38   2]
- [ 24   2  13  12   6  16  46]]
-Node Classification on random seed  4380 -> 0.589
-Confusion Matrix:
- [[ 67   3   5   9   2   6  11]
- [  4 137   7   6   6   0   5]
- [ 25  21 122  56  31  22  40]
- [ 11   4  18 103   4   6  10]
- [  2   8   0   2  57   1   5]
- [  5   0   1   8   3  31   2]
- [ 15   4   9   8   7  19  72]]
-Node Classification on random seed  4381 -> 0.638
-Confusion Matrix:
- [[ 68   1   1   3   4  13  18]
- [  1 126   1   4   8   2   5]
- [ 15  28 153  22  27  24  49]
- [  9   4  18 102   6   8  16]
- [  2   4   1   4  57   0   1]
- [  4   1   2   1   0  47   3]
- [  7   6   6   2  12  19  85]]
-Node Classification on random seed  4382 -> 0.591
-Confusion Matrix:
- [[ 65   1   0   8   6  12   3]
- [ 11 131   2  10   6   8   0]
- [ 26  36 124  41  16  32  35]
- [ 11   2  22 101   3  12  13]
- [  2   6   2   2  57   1   4]
- [  8   1   1   3   0  43   1]
- [ 15   3   6   8  11  19  70]]
-Node Classification on random seed  4383 -> 0.591
-Confusion Matrix:
- [[ 74   1   4   3   3   8  13]
- [ 11 116   6  14  11   3   4]
- [ 33  15 135  40  42  10  51]
- [  8  11  14  92  14   4   9]
- [  1   3   0   2  56   1   3]
- [  6   0   2   1   0  37   5]
- [ 14   3  11   8  10   7  81]]
-Node Classification on random seed  4384 -> 0.642
-Confusion Matrix:
- [[ 71   2   0   2   5  11   8]
- [  8 123   7   3   8   3   2]
- [ 24  19 149  30  32  11  51]
- [ 15   2   9 113   3   2  14]
- [  1   6   2   1  58   1   4]
- [  2   2   2   0   1  60   7]
- [  6   6   4  18  12  12  68]]
-Node Classification on random seed  4385 -> 0.625
-Confusion Matrix:
- [[ 61   1   3   7   2   9  26]
- [  2 127   5   2   6   1   8]
- [ 38  22 146  15  19  20  39]
- [  8   5  11 105  10   6  14]
- [  1  11   6   1  60   0   1]
- [  7   1   1   2   2  45   6]
- [  4   5  12   9   5  22  81]]
-Node Classification on random seed  4386 -> 0.613
-Confusion Matrix:
- [[ 65   3  12   3   5  12   9]
- [  1 124   5   1   1   0   2]
- [ 16  27 149  53  17  32  44]
- [ 18   1  17 103   3   0  16]
- [  0   6   9   2  53   1   2]
- [  5   3   3   0   2  51   1]
- [  5  12  13   3   6  16  68]]
-Node Classification on random seed  4387 -> 0.614
-Confusion Matrix:
- [[ 81   5   1   9   3  13  13]
- [  2 119   5   3   9   3  14]
- [ 20  14 147  39  27  20  37]
- [ 21   4  14  84   3   2  11]
- [  0   6   4   2  54   0   4]
- [  8   2   2   2   1  50   4]
- [ 16   3  12  12   7   9  79]]
-Node Classification on random seed  4388 -> 0.619
-Confusion Matrix:
- [[ 73   1   3   4   7  14   5]
- [  2 114   9   3  14   2   3]
- [ 32  21 164  23  23  21  33]
- [ 14   4  21  95  13   6   6]
- [  1   5   4   1  56   0   2]
- [  7   1   2   0   3  46   8]
- [ 15   3  16   8   7  14  71]]
-Node Classification on random seed  4389 -> 0.62
-Confusion Matrix:
- [[ 75   2   2   2   3  17   5]
- [  3 117   6   6   5   3   3]
- [ 33  22 136  44  16  23  42]
- [  7   3   6 106   4   8  16]
- [  0  12   3   2  62   0   2]
- [  5   1  12   3   0  38  11]
- [ 16   5   5   3   4  15  86]]
-Node Classification on random seed  4390 -> 0.628
-Confusion Matrix:
- [[ 63   5  11  10   1  10  15]
- [  5 132   5   0   7   6   6]
- [ 25  25 169  31  19  10  46]
- [  2   4  25  93   2   8  16]
- [  4   3   3   0  53   0   1]
- [  2   3   4   2   0  47   7]
- [ 16   5  13   2   6   7  71]]
-Node Classification on random seed  4391 -> 0.656
-Confusion Matrix:
- [[ 63   4   4   4   5   5  22]
- [  8 143   8   4   6   4   6]
- [ 12  21 146  20  39  10  47]
- [ 10   2  11 108   1   6  16]
- [  0   5   2   1  71   2   1]
- [  2   0   2   1   1  44  11]
- [  4   2  10  14   7   4  81]]
-Node Classification on random seed  4392 -> 0.618
-Confusion Matrix:
- [[ 86   5   1   2   2   9  16]
- [ 10 119   7   2   6   3   8]
- [ 31  30 140  29  17  24  47]
- [  7   2  10 104   5   5  14]
- [  2   6   3   1  45   0   3]
- [ 10   3   1   1   2  48   1]
- [ 15   7   3   3   9  20  76]]
-Node Classification on random seed  4393 -> 0.637
-Confusion Matrix:
- [[ 74   4   1   2   6   7  14]
- [  8 116   6   0  13   7   3]
- [ 10  18 136  29  19  23  61]
- [  7   2   7 124   6   3  21]
- [  0   4   2   4  57   2   2]
- [  7   1   2   3   1  53   9]
- [ 13   3   7  10   6  10  77]]
-Node Classification on random seed  4394 -> 0.662
-Confusion Matrix:
- [[ 62   2   7   3   4  14  13]
- [  8 129   6   3   7   4   6]
- [ 20  18 166  30  15  13  26]
- [  8   8  15 112   4   3  17]
- [  6   4   4   1  57   2   2]
- [  6   0   1   1   2  46  10]
- [ 13   9   9   2   4   8  90]]
-Node Classification on random seed  4395 -> 0.613
-Confusion Matrix:
- [[ 66   5   3  13   4   5  18]
- [  4 127  10   7   3   2   6]
- [ 15  16 124  23  37  35  42]
- [  9   3  30  94   4   1  21]
- [  4   6   1   3  65   0   1]
- [  1   1   1   2   2  53   7]
- [  7   6   7   4   6  12  84]]
-Node Classification on random seed  4396 -> 0.583
-Confusion Matrix:
- [[ 62   2   4   8   7  10   6]
- [  8 130   6   1  11   0   6]
- [ 23  39 119  33  41  21  54]
- [ 16   4   9  90   2   5  23]
- [  1   3   3   1  58   2   1]
- [  3   0   2   5   3  43   4]
- [ 12   1  14   1   6  16  81]]
-Node Classification on random seed  4397 -> 0.624
-Confusion Matrix:
- [[ 56   4   6  11   3  14  14]
- [  0 141   5   2   8   6   2]
- [ 17  15 160  31  24  30  23]
- [  6   5  12  97   7  10  11]
- [  1   6   4   0  62   0   5]
- [  4   4   7   4   3  37   2]
- [  9   9   7   9  13  23  71]]
-Node Classification on random seed  4398 -> 0.591
-Confusion Matrix:
- [[ 65  12   2  10   2   8   7]
- [  3 129   7   3   4   2   1]
- [ 28  28 121  57  29  24  35]
- [  7  13  17  90   1   9  11]
- [  1   8   2   7  52   0   3]
- [  5   1   2   3   2  48   4]
- [  8   3   6  11  13  10  86]]
-Node Classification on random seed  4399 -> 0.617
-Confusion Matrix:
- [[ 76  10   4   3   1  10   5]
- [  2 142   5   4  10   2   6]
- [ 23  15 109  58  31  12  55]
- [  8   5  15 110   8   8  12]
- [  0   5   3   1  50   0   2]
- [  4   1   3   2   0  49   6]
- [  4   3   7   6   8  16  81]]
-Node Classification on random seed  4400 -> 0.596
-Confusion Matrix:
- [[ 56   1   8   5   3  13  20]
- [  9 139   3   0   9   5   1]
- [ 26  27 129  37  23  29  33]
- [ 14   3  12 105   6   4  16]
- [  1   9   2   2  52   2   1]
- [  7   0   1   2   6  37  11]
- [  8   2   8   2  21  12  78]]
-Node Classification on random seed  4401 -> 0.606
-Confusion Matrix:
- [[ 71   0   6   3   6  14   9]
- [  2 122   3   1   5   3  10]
- [ 20  16 131  52  38  15  49]
- [  0   6  17 107   7   6  16]
- [  0   5   0   2  60   1   4]
- [  7   3   2   5   1  48   3]
- [ 19   3   6   3  11  15  67]]
-Node Classification on random seed  4402 -> 0.613
-Confusion Matrix:
- [[ 69   7   2   5   1  14  13]
- [  2 137   6   1   8   2   3]
- [ 21  43 119  36  41  11  44]
- [  8   9  14 103   6   2  10]
- [  0   7   3   0  62   3   3]
- [  5   2   4   2   0  34   5]
- [  6   4  11   1   6  16  89]]
-Node Classification on random seed  4403 -> 0.588
-Confusion Matrix:
- [[ 70   4   6   9   4  13  15]
- [  4 109   4   1  16   2   2]
- [ 17  38 134  23  52  20  45]
- [ 13   4  23 102   0   4  12]
- [  2   5   4   2  67   3   2]
- [  2   1   3   1   1  44   2]
- [ 16   5   3   7   7  15  62]]
-Node Classification on random seed  4404 -> 0.632
-Confusion Matrix:
- [[ 67   3   5   2   2  16  10]
- [  9 133   5   1   3   5   8]
- [ 14  14 138  33  23  27  52]
- [ 10   2  18 108   7   5  15]
- [  0   9   2   1  56   3   3]
- [  0   1   1   4   1  50   2]
- [ 13   1   8  10  10  10  80]]
-Node Classification on random seed  4405 -> 0.578
-Confusion Matrix:
- [[ 62   5   3   2   5  13   8]
- [  6 133   4   3   7   1   2]
- [ 29  29 100  33  43  32  35]
- [ 14  11  15 101  13   7  12]
- [  4   6   0   1  56   3   1]
- [ 15   1   4   1   0  43   2]
- [ 20   5  13   1   6   7  83]]
-Node Classification on random seed  4406 -> 0.59
-Confusion Matrix:
- [[ 70   6   5   3  14   4   8]
- [  2 136   3   7   6   1   6]
- [ 21  16 124  51  39  11  49]
- [ 26   2  10 102   4   3  17]
- [  0   7   2   2  64   2   1]
- [  8   5   1   0   7  30   6]
- [  6   8   8  17   8   8  64]]
-Node Classification on random seed  4407 -> 0.593
-Confusion Matrix:
- [[ 72   6   2   5   5  12   2]
- [  1 131   8   3   8   0   9]
- [ 25  20 117  27  41  21  51]
- [ 29   1  20  88  19   4   7]
- [  0  10   2   1  66   0   5]
- [  0   3   1   1   1  42   7]
- [  5   3  11   9   9  13  77]]
-Node Classification on random seed  4408 -> 0.613
-Confusion Matrix:
- [[ 72   2   2   9   3   9   6]
- [  3 134   4   2  13   3   5]
- [ 23  28 122  42  41  19  35]
- [ 18   3  11 113   3   4  10]
- [  1   4   1   1  61   1   3]
- [  4   0   2   2   1  44   2]
- [ 18   1   4  16   7  21  67]]
-Node Classification on random seed  4409 -> 0.659
-Confusion Matrix:
- [[ 71   1   6   4   4   5  13]
- [  5 143   3   1   5   0   6]
- [ 20  19 158  36  17  26  40]
- [  5   6  25 104   4   4   8]
- [  2   6   4   0  58   1   3]
- [  9   1   1   3   1  51   4]
- [ 22   3   5   2   4   7  74]]
-Node Classification on random seed  4410 -> 0.667
-Confusion Matrix:
- [[ 83   2   8   2   2   7  12]
- [  5 123   2   5   9   7   4]
- [ 14  13 175  42  15  25  30]
- [ 13   6   8  99   7   5  15]
- [  1   7  11   0  51   0   3]
- [  5   4   2   1   0  53   6]
- [  4   2   7   3   6  13  83]]
-Node Classification on random seed  4411 -> 0.624
-Confusion Matrix:
- [[ 65   7   5   8   2  19   3]
- [  7 128   5   4  13   1   4]
- [ 27  15 138  29  24  26  40]
- [ 10   3  21  91  15   4   5]
- [  0   8   2   2  63   0   1]
- [  4   5   0   1   0  52   6]
- [ 11   3  12   5   6  13  87]]
-Node Classification on random seed  4412 -> 0.577
-Confusion Matrix:
- [[ 64   5  12  10   5  13   8]
- [  6 129   5   0   4   3  12]
- [ 44  11 109  53  27  10  44]
- [ 11   7  12 102   5   7   9]
- [  2  13   9   0  52   1   3]
- [ 12   3   1   1   1  43   1]
- [ 16   2  11   2   7  15  78]]
-Node Classification on random seed  4413 -> 0.649
-Confusion Matrix:
- [[ 72   1   1   2   4   5  11]
- [  2 144  10   0   9   2   1]
- [ 42  19 139  26  17  21  51]
- [ 11   2  16 103   6   3  23]
- [  2   5   2   2  62   0   1]
- [  5   2   0   0   0  41  11]
- [  8   5   3   4   7   9  88]]
-Node Classification on random seed  4414 -> 0.617
-Confusion Matrix:
- [[ 75   3   3   5   5  11   9]
- [  5 119   9   2   7   4   2]
- [ 32  21 131  25  19  28  38]
- [  5   7  21 105   5   4  20]
- [  1   5   3   1  68   2   7]
- [  4   1   2   1   0  42   8]
- [ 14   2   8  13   8  13  77]]
-Node Classification on random seed  4415 -> 0.644
-Confusion Matrix:
- [[ 63   1   3   6   4  12   9]
- [  6 121   9   0  12   5   5]
- [ 11   8 148  33  45  23  32]
- [ 17   0  17 120   4   5   8]
- [  1   4   1   2  54   3   3]
- [  8   3   2   3   1  58   3]
- [  6   7  13   5   2  14  80]]
-Node Classification on random seed  4416 -> 0.623
-Confusion Matrix:
- [[ 67   3  10   3   2  10  12]
- [  5 143  16   3   8   2   6]
- [ 17  23 140  34  27  26  32]
- [ 12   2  20  77  11   7  18]
- [  1   6   4   1  55   4   4]
- [  0   1   1   2   0  59   7]
- [  7   5   5   5   4  11  82]]
-Node Classification on random seed  4417 -> 0.587
-Confusion Matrix:
- [[ 70   1   2  11   4  14   9]
- [  2 119   7   2   8   4   5]
- [ 36  20 123  35  23  39  42]
- [ 13   7  16  94   6   6   6]
- [  2   7   5   6  56   1   3]
- [  5   1   1   1   4  51   6]
- [ 10   4   3  16   6  14  74]]
-Node Classification on random seed  4418 -> 0.578
-Confusion Matrix:
- [[ 61   4   8   3   5  16   7]
- [  7 130   7   2   4   6   2]
- [ 24  22 120  53  36  23  35]
- [ 23   4   9  99   7   6  11]
- [  0  11   3   3  59   0   4]
- [  7   1   7   0   3  39   6]
- [  6   1  13  10   9  14  70]]
-Node Classification on random seed  4419 -> 0.628
-Confusion Matrix:
- [[ 65   3   3  10   8  14   6]
- [  2 129   8   2   8   2   9]
- [ 15  21 130  26  44  12  42]
- [  6   7  11 119   7   6   9]
- [  1   7   6   1  59   0   5]
- [  2   2   2   4   0  46   8]
- [ 10   2   9  20   4   8  80]]
-Node Classification on random seed  4420 -> 0.603
-Confusion Matrix:
- [[ 65   6   5   5   6  18   4]
- [  4 117  10   4   5   3   6]
- [ 26  36 137  41  17  26  44]
- [ 11   3  12 105   8   0  13]
- [  0   9   3   0  53   1   6]
- [  3   1   4   4   2  48   4]
- [  5   2   9  11  12   8  78]]
-Node Classification on random seed  4421 -> 0.631
-Confusion Matrix:
- [[ 66   8   1   6   3  17  20]
- [  5 139   2   2   2   4   3]
- [ 26  13 141  30  24  25  52]
- [ 10   1  14 103   1   9   6]
- [  0   9   1   3  54   1   4]
- [  0   0   0   0   0  57   6]
- [ 10   7   7   7   1  29  71]]
-Node Classification on random seed  4422 -> 0.637
-Confusion Matrix:
- [[ 74   4   2  10   2   9   4]
- [  4 122   8   0  12   0   2]
- [ 26  13 170  32  34  13  43]
- [  8   0  14 108  11  11   8]
- [  2   8   7   0  47   2   2]
- [  3   1   0   2   1  41   6]
- [ 13   0   6  21   8  11  75]]
-Node Classification on random seed  4423 -> 0.605
-Confusion Matrix:
- [[ 81   3   2   7   5   9   2]
- [  9 130   9   2   9   1   2]
- [ 26  29 130  33  45  12  45]
- [ 10   5  10  94   6   3  17]
- [  1   5   3   1  60   0   1]
- [ 12   1   1   0   1  43   9]
- [ 20   6   9   2  11  11  67]]
-Node Classification on random seed  4424 -> 0.628
-Confusion Matrix:
- [[ 64   8   0  10   7   9  16]
- [  4 124   4   1  13   1   7]
- [ 31  11 139  21  34  18  34]
- [ 12   4  13 114   5   8   9]
- [  2   6   3   2  71   2   3]
- [ 10   0   3   3   1  39   7]
- [ 13   1  12  10   3  11  77]]
-Node Classification on random seed  4425 -> 0.653
-Confusion Matrix:
- [[ 79   1  10   5   4   5   8]
- [  7 113   8   1  12   2   2]
- [ 35   8 150  29  24  29  30]
- [ 10   4  12 123   2   3  10]
- [  0   9   3   2  67   0   2]
- [  4   2   1   0   2  46   0]
- [ 10   2   7  11   7  24  75]]
-Node Classification on random seed  4426 -> 0.645
-Confusion Matrix:
- [[ 66   2   8   2   3  11  10]
- [ 11 136   3   1   3   0   1]
- [ 24  20 173  34  24  18  39]
- [ 11   3  15  93   0   3  16]
- [  5   9   8   0  56   0   0]
- [  6   1   3   0   3  45   2]
- [ 16  12   7   6   5  10  76]]
-Node Classification on random seed  4427 -> 0.57
-Confusion Matrix:
- [[ 77   1   3   8   3   5  14]
- [  7 115  17   2  14   4   1]
- [ 27  30 127  34  41  18  38]
- [  9   1  13 105   4   5  16]
- [  5   1   6   3  55   0   3]
- [  7   0   5   0   2  45   7]
- [ 10   4  21   7  21  13  46]]
-Node Classification on random seed  4428 -> 0.595
-Confusion Matrix:
- [[ 63   3   9   5   3  15   6]
- [  3 124   7   4  10   3  14]
- [ 17  44 124  32  26  23  39]
- [ 11   7  15  97   1  10   7]
- [  0   6   1   1  65   1   7]
- [  5   2   3   0   2  49  10]
- [  6   5  13   7   6  16  73]]
-Node Classification on random seed  4429 -> 0.599
-Confusion Matrix:
- [[ 84   0   0   4   7  17   5]
- [  2 119   6   3  12   4   4]
- [ 33  10 130  41  14  31  39]
- [ 15   7  21 103   4  11   5]
- [  3   9   4   4  53   0   4]
- [  8   2   1   1   1  40   4]
- [ 16   3   8   5   9  24  70]]
-Node Classification on random seed  4430 -> 0.642
-Confusion Matrix:
- [[ 81   0   4   2   2   7   9]
- [  5 117   5   4   5   3  10]
- [ 23  25 158  33  33  17  25]
- [  9   8  15 111   5   7   9]
- [  1   5   3   0  54   8   2]
- [  4   2   7   1   0  48   4]
- [  4   5  11  12  11  13  73]]
-Node Classification on random seed  4431 -> 0.642
-Confusion Matrix:
- [[ 73   4   2   9   2  10  15]
- [  6 142   4   3   3   4   1]
- [ 11  21 138  27  27  24  54]
- [  5   8  16 107   8   6  13]
- [  2   6   4   2  59   3   3]
- [  0   0   0   4   2  45   5]
- [  7   3   5  10   9  10  78]]
-Node Classification on random seed  4432 -> 0.636
-Confusion Matrix:
- [[ 78   0   4   5   2  18  15]
- [  6 122   6   0   5   3   0]
- [ 41  18 157  21  29  11  21]
- [  9   4  15 109   5   8  14]
- [  2   1   8   5  57   1   2]
- [  7   0   6   6   1  45   6]
- [ 19   3   9   4   2  22  68]]
-Node Classification on random seed  4433 -> 0.588
-Confusion Matrix:
- [[ 58   2   8   4   0  19  17]
- [  6 132   3   2   8   2   9]
- [ 19  19 139  27  33  23  39]
- [ 15  10  19  75  17   3  20]
- [  1   6   3   2  57   3   0]
- [  6   2   0   1   1  42  12]
- [ 10   6   6   8   5  16  85]]
-Node Classification on random seed  4434 -> 0.636
-Confusion Matrix:
- [[ 67   3   3   5   6  11  16]
- [  6 132   4   1   5   2   2]
- [ 22  16 140  40  45  16  32]
- [ 11   5  12 109   6   2   7]
- [  1  12   0   0  59   1   1]
- [ 13   1   1   2   4  39   6]
- [ 12   6   5   3   6  12  90]]
-Node Classification on random seed  4435 -> 0.655
-Confusion Matrix:
- [[ 73   2   2   2   6  13  19]
- [  2 132   4   6   5   1   6]
- [ 17  27 166  20  21  16  38]
- [ 13   7  18  92   4   3  13]
- [  0  12   4   3  64   0   2]
- [  5   2   2   0   3  50   3]
- [ 14   3   8  11   1   7  78]]
-Node Classification on random seed  4436 -> 0.6
-Confusion Matrix:
- [[ 69   4   0   1   5  19   9]
- [  3 141  10   4   8   4   3]
- [ 17  17 144  38  20  25  43]
- [ 32  11  16  76   5   7  17]
- [  1   5   3   2  55   4   8]
- [  2   2   2   0   0  38   5]
- [ 11   2   9   4   4  18  77]]
-Node Classification on random seed  4437 -> 0.605
-Confusion Matrix:
- [[ 61   3   4   8   9  12   7]
- [  2 130   6   2   8   2   3]
- [ 33  25 143  50  25  18  25]
- [  8   5   7 112  14   4   6]
- [  2  10   3   5  47   1   4]
- [  8   1   1   0   1  46   7]
- [ 21   3  12  12   8  10  66]]
-Node Classification on random seed  4438 -> 0.641
-Confusion Matrix:
- [[ 71   4   1   7   3  13   9]
- [ 10 114   9   2  12   0   5]
- [ 14  10 156  34  17  21  50]
- [ 11   1  13 125   4   3  15]
- [  2   7   4   1  57   3   3]
- [  2   3   2   1   2  47   8]
- [ 10   1   8  10  10  14  71]]
-Node Classification on random seed  4439 -> 0.629
-Confusion Matrix:
- [[ 71   2   7   3   1   7  11]
- [ 17 117   5   0   7   1   8]
- [ 25  19 121  38  36  34  22]
- [ 18   3  11 109   3   2  15]
- [  7   5   3   1  73   2   2]
- [  2   0   1   1   0  55   3]
- [ 18   4   3   2   9  13  83]]
-Node Classification on random seed  4440 -> 0.62
-Confusion Matrix:
- [[ 71   2   3   9   6  11   8]
- [ 11 122   6   6   4   7   2]
- [ 42  11 111  30  27  37  39]
- [ 13   1  15 124   2   3  12]
- [  1   4   4   1  65   1   6]
- [  5   2   2   2   1  50   5]
- [ 10   4  10   2   5   8  77]]
-Node Classification on random seed  4441 -> 0.64
-Confusion Matrix:
- [[ 78   2   1   4   4  13  16]
- [  3 137   5   4   9   4   1]
- [ 20  25 137  31  25  12  43]
- [ 12   7  18 102   6   2  10]
- [  2   5   5   1  57   1   3]
- [  3   0   0   7   2  48   5]
- [ 12   2  13   2   1  19  81]]
-Node Classification on random seed  4442 -> 0.61
-Confusion Matrix:
- [[ 65   1   6   6   3   9  17]
- [  4 131   9   0   2   5   3]
- [ 25  20 134  40  21  40  28]
- [ 18   3  14  96   4   8  13]
- [  1   4   7   0  61   0   2]
- [  4   3   4   1   1  44   6]
- [ 12   3   7  11   6  19  79]]
-Node Classification on random seed  4443 -> 0.643
-Confusion Matrix:
- [[ 80   1   4  12   6  11   2]
- [  1 114  11   4   7   3   2]
- [ 34  10 151  35  29  22  40]
- [ 11   2  19 111   6   4   9]
- [  0   5   3   0  57   0   3]
- [  5   1   3   2   0  42   4]
- [ 12   3   6   2  12  11  88]]
-Node Classification on random seed  4444 -> 0.625
-Confusion Matrix:
- [[ 83   2   2   1   5   5  16]
- [  7 126   4   3   5   5   3]
- [ 22  17 147  39  28  15  46]
- [  9   6  12  87   3   7  22]
- [  1   8   2   1  54   2   2]
- [  7   3   1   2   0  48   6]
- [ 14   5  11   2  12  12  80]]
-Node Classification on random seed  4445 -> 0.618
-Confusion Matrix:
- [[ 63  13   9   4   9   8  10]
- [  1 149   9   0   9  10   6]
- [ 21   8 146  33  15  37  31]
- [ 13   2  20 102   8   5  10]
- [  1   4   7   1  56   1   2]
- [  6   1   3   0   0  37   6]
- [ 11   3   6   5   9  25  65]]
-Node Classification on random seed  4446 -> 0.673
-Confusion Matrix:
- [[ 63   3   4   5   4  12   5]
- [  3 140   3   3   5   2   6]
- [  9  21 172  25  22  25  45]
- [  9   3  25 105   3  12  12]
- [  1   4   1   3  64   0   1]
- [  1   1   1   0   2  43   7]
- [  4   3   2  10   9  11  86]]
-Node Classification on random seed  4447 -> 0.607
-Confusion Matrix:
- [[ 62   1  17  18   5  11   3]
- [  5 128   5   1  12   5   4]
- [ 15  26 125  31  23  22  32]
- [  4   6  14 111   6  11   6]
- [  2   3   6   5  63   2   4]
- [  8   0   3   4   0  46   3]
- [ 22   5   9  16   8  10  72]]
-Node Classification on random seed  4448 -> 0.627
-Confusion Matrix:
- [[ 76   1   3   2   7  12  15]
- [  2 119   5   1   3   1  11]
- [ 17  13 175  36  26  18  37]
- [  7   2  20  86  16  10  18]
- [  3   5   5   1  62   1   1]
- [  9   2   3   1   1  43   2]
- [ 14   5  10   4  10  13  66]]
-Node Classification on random seed  4449 -> 0.631
-Confusion Matrix:
- [[ 82   1   4   4   3  10  17]
- [  8 122  11   2  18   0   3]
- [ 18  22 156  38  19  33  21]
- [ 14   5  10 108   1   3   5]
- [  4   5   9   1  60   2   2]
- [  9   4   7   0   2  43   1]
- [  9   1   9   4   4  26  60]]
-Node Classification on random seed  4450 -> 0.633
-Confusion Matrix:
- [[ 75   2   9   3   3   6  18]
- [  5 130   2   1  13   0   7]
- [ 26  14 144  31  24  16  55]
- [ 11   2   8 106  13   6  16]
- [  2   3   3   0  56   1   3]
- [ 12   4   0   3   0  47   3]
- [  7   3   9  12   1  10  75]]
-Node Classification on random seed  4451 -> 0.66
-Confusion Matrix:
- [[ 73   1   5   2   6   6  19]
- [  2 138   4   3   8   0   8]
- [ 17  25 167  36  31  15  29]
- [  8   1  11  97   8  10  16]
- [  0   8   4   0  63   1   1]
- [  9   1   1   1   2  45   5]
- [ 11   5   3   6   6   5  77]]
-Node Classification on random seed  4452 -> 0.59
-Confusion Matrix:
- [[ 57   4   9   9   4  21   4]
- [  4 129   4   2  10   0   1]
- [ 31  27 152  32  25  23  36]
- [ 10   4  16 111   3   2  10]
- [  3  10   3   2  48   2   2]
- [  5   1   1   1   0  47   5]
- [ 17   3   4  22  23  15  46]]
-Node Classification on random seed  4453 -> 0.642
-Confusion Matrix:
- [[ 76   4   4   5   3  10   2]
- [  1 132   1   3   2   3   2]
- [ 30  18 141  45  26  16  42]
- [ 20   3  10 122   3   8   7]
- [  2  10   5   0  56   2   1]
- [  4   4   3   0   0  39   8]
- [ 16   4  10   8  10   3  76]]
-Node Classification on random seed  4454 -> 0.597
-Confusion Matrix:
- [[ 67   2   9   6   3  12   7]
- [  6 131   5   7   3   2   4]
- [ 16  25 145  29  19  25  41]
- [ 22   8  14  97   1   7  11]
- [  0   6   6   6  49   1   2]
- [  7   4   2   4   0  43   6]
- [ 20   5   7  16   4  23  65]]
-Node Classification on random seed  4455 -> 0.608
-Confusion Matrix:
- [[ 64   2   6   4   4  11   8]
- [  9 125   9   2   8   2   6]
- [ 29  25 133  43  18  21  37]
- [ 18   3  14  97  10   4  11]
- [  2   4   2   1  70   0   2]
- [ 10   0   6   0   1  43   4]
- [ 15   4  12   4   6  15  76]]
-Node Classification on random seed  4456 -> 0.628
-Confusion Matrix:
- [[ 67   3   7   1   4   7  11]
- [  8 119   2   4   6  13   4]
- [ 21  28 143  28  15  33  33]
- [ 10   8  15 113   2   5  15]
- [  0   8   2   8  54   0   2]
- [  9   0   0   1   0  42   5]
- [  9   4   9   4   8  20  90]]
-Node Classification on random seed  4457 -> 0.633
-Confusion Matrix:
- [[ 85   0   4   6   2   5  11]
- [  1 130  12   2   5   3   6]
- [ 27  12 125  45  37  14  43]
- [  6   4   7 104  10   2  16]
- [  3  12   4   3  62   0   0]
- [ 11   2   1   2   0  47   8]
- [ 14   3   3   6   8   7  80]]
-Node Classification on random seed  4458 -> 0.587
-Confusion Matrix:
- [[ 56   1   7   3  12   7  10]
- [  2 108   8   5  20  10   3]
- [ 33   9 138  42  20  17  56]
- [ 11   6  30  89   2   5  13]
- [  1   5   2   0  68   0   1]
- [  4   0   5   1   0  43   1]
- [  8   3  12  10  17  11  85]]
-Node Classification on random seed  4459 -> 0.619
-Confusion Matrix:
- [[ 71   3  15   3   2   5  10]
- [  4 134   9   1  11   5   2]
- [ 26  27 137  25  27  22  37]
- [ 14   2  10  93   5  10  16]
- [  0   4   1   5  61   2   0]
- [  6   0   7   4   1  43   4]
- [ 16   4   6  13   7  10  80]]
-Node Classification on random seed  4460 -> 0.582
-Confusion Matrix:
- [[ 70   4   0   9   0  12  11]
- [  3 112   6   7   6  15   8]
- [ 20  27 132  42  32  29  37]
- [  8  11  23  89   6   9  11]
- [  3  10   2   3  53   1   3]
- [  1   1   3   0   0  43  12]
- [  2   6  11   7   9   8  83]]
-Node Classification on random seed  4461 -> 0.63
-Confusion Matrix:
- [[ 65   4   5   5   3  16   5]
- [  7 139   5   0   4   2   2]
- [ 27  28 143  27  19  28  33]
- [ 14   9  17  99   7   9  10]
- [  1   2   7   0  62   0   1]
- [  6   1   3   2   1  58   5]
- [ 10   7   8   5  10  15  64]]
-Node Classification on random seed  4462 -> 0.609
-Confusion Matrix:
- [[ 59   7   9   3   3  11  17]
- [  5 123  10   8   1   3   4]
- [ 30  31 156  43  19  19  34]
- [  9   5   9 101  14   7  16]
- [  2   2   4   3  51   0   3]
- [  9   0   0   3   1  43   3]
- [ 10   6   8   7   6   7  76]]
-Node Classification on random seed  4463 -> 0.577
-Confusion Matrix:
- [[ 65   4   8   5   4   4  12]
- [  4 129   5   5   3   9   2]
- [ 22  25 115  55  22  18  34]
- [ 24   4   8 107   3   7  13]
- [  1   6   3   3  57   4   2]
- [  8   4  14   8   0  33   4]
- [ 19   5  11   4  10  17  71]]
-Node Classification on random seed  4464 -> 0.605
-Confusion Matrix:
- [[ 66   1   5   8   7  18  13]
- [  4 118   4   3   8   2   3]
- [ 19  22 131  37  43  22  35]
- [ 23   3   9 107   3  12  11]
- [  1   4   1   1  61   1   2]
- [  5   2   1   1   1  52   4]
- [  6   5   6   7  16  16  70]]
-Node Classification on random seed  4465 -> 0.617
-Confusion Matrix:
- [[ 60   5   6  11   3   9  13]
- [  3 118   9   2   7   2   2]
- [ 15  26 151  35  49  13  32]
- [  1   8  13 112   5  12  11]
- [  2   3   8   2  63   0   0]
- [ 14   2   4   1   0  45   3]
- [  7   2   9  17   6  11  68]]
-Node Classification on random seed  4466 -> 0.585
-Confusion Matrix:
- [[ 65   2   6   7   9  15  10]
- [  2 125   7   1   3   2   1]
- [ 34  23 129  37  44  23  23]
- [ 18   4  14 120   4   8   7]
- [  0   5   9   8  53   1   1]
- [  8   0  10   1   2  26   4]
- [  6   6  15  13   6  16  67]]
-Node Classification on random seed  4467 -> 0.616
-Confusion Matrix:
- [[ 60  11   9   4   5   6  17]
- [  3 144   6   1  13   2   2]
- [ 18  21 121  33  41  21  41]
- [  7   0  14 108   3   5  13]
- [  1   6   0   3  70   1   2]
- [  4   2   1   1   8  34   5]
- [  5   4  11   9   8  17  79]]
-Node Classification on random seed  4468 -> 0.615
-Confusion Matrix:
- [[ 72   4   2   8   6  13   7]
- [  7 122   6   0   9   2   5]
- [ 17  45 134  34  26  16  45]
- [  3   3  12  97   3   6  16]
- [  1   9   3   2  61   1   3]
- [  3   2   5   2   1  51   7]
- [ 11   5  13   3   9  10  78]]
-Node Classification on random seed  4469 -> 0.624
-Confusion Matrix:
- [[ 80   1   2   2   2  12   5]
- [ 14 120   8   2   4   2   8]
- [ 33  21 146  48  21  10  34]
- [ 17   1  19 114   2   4   6]
- [  2  10   6   3  52   0   3]
- [  8   0   1   1   1  31   9]
- [ 18   8   6   5   6  11  81]]
-Node Classification on random seed  4470 -> 0.583
-Confusion Matrix:
- [[ 72   1   2   6   4  21   6]
- [ 10 101   7   3  13   5  17]
- [ 26  31 114  32  58  23  16]
- [ 14   4  11 109   4   2  12]
- [  0   4   1   2  69   1   2]
- [  6   2   1   1   1  40   6]
- [ 16   1  27   0   7  11  78]]
-Node Classification on random seed  4471 -> 0.604
-Confusion Matrix:
- [[ 72   1   7   5   7   5  15]
- [  1 144  12   0   2   0   4]
- [ 18  29 128  41  40  21  30]
- [ 13   4  19  80   6   8   6]
- [  0   7   4   2  67   1   2]
- [  8   1   1   0   0  43   5]
- [ 14   1   8  11  11  26  70]]
-Node Classification on random seed  4472 -> 0.594
-Confusion Matrix:
- [[ 81   4   1  11   4  10   8]
- [  7 121   0   1  13   2   3]
- [ 37  16 122  46  25  25  54]
- [ 20   5   5  83   5   8  20]
- [  1  14   2   0  61   1   1]
- [  1   2   0   7   0  45   7]
- [  7   8   0  11   2  12  81]]
-Node Classification on random seed  4473 -> 0.648
-Confusion Matrix:
- [[ 70   2   2   2   2   9  18]
- [  1 156   5   1   1   0   2]
- [ 13  37 136  18  17  35  44]
- [  6   5  11 111   2  13  15]
- [  4   6   9   2  49   1   1]
- [ 10   1   3   0   0  52   3]
- [  7   4   7   2  10  21  74]]
-Node Classification on random seed  4474 -> 0.608
-Confusion Matrix:
- [[ 79   2   3   2   1  14   8]
- [  5 120   6   2   2   0   2]
- [ 52  22 128  37  27  24  35]
- [  6   5  19 102   4   3  15]
- [  2  12   0   0  57   2   4]
- [ 10   1   4   0   0  48   2]
- [ 21   6  11   5   7   9  74]]
-Node Classification on random seed  4475 -> 0.615
-Confusion Matrix:
- [[ 56   5   8   5   3   7  20]
- [  3 132   7   3   2   2   3]
- [ 27  30 156  29  36  23  19]
- [ 13   1  13 103   9   5  11]
- [  1   6   5   0  47   0   2]
- [  3   3   2   2   2  50   9]
- [ 13   3  15   6  19  10  71]]
-Node Classification on random seed  4476 -> 0.627
-Confusion Matrix:
- [[ 81   1   1   4   1   9   6]
- [  3 127   3   9  14   3   5]
- [ 25  15 147  38  39  19  38]
- [ 17   1  10  89   2  13  17]
- [  3   5   2   0  59   2   4]
- [  5   1   2   0   0  44   7]
- [ 12   2   4   4   5  22  80]]
-Node Classification on random seed  4477 -> 0.631
-Confusion Matrix:
- [[ 60  10   3   2   3  14   5]
- [  4 128   5   3   7   0   8]
- [ 26  25 134  33  22  39  27]
- [ 15   5  12 109   5   5   5]
- [  0   6   4   1  66   3   5]
- [  1   1   3   0   2  52   5]
- [ 10   2  17   6   6  14  82]]
-Node Classification on random seed  4478 -> 0.654
-Confusion Matrix:
- [[ 76   0   2   5   6  16  23]
- [  3 134   3   0   2   4   3]
- [ 21  32 142  31   9  12  45]
- [  5  10  16  97  10   4   9]
- [  3  10   3   0  60   0   1]
- [  2   1   0   1   0  56  10]
- [ 13   3  11   6   3   8  89]]
-Node Classification on random seed  4479 -> 0.628
-Confusion Matrix:
- [[ 62   5   0   9   3  13  17]
- [  0 108   6   2   4   3  11]
- [ 11  38 154  30  13  21  52]
- [  3  11  19 101   3  10  14]
- [  1  12   3   3  54   1   2]
- [  1   3   1   0   1  46   6]
- [ 10   4   3   8   6   9 103]]
-Node Classification on random seed  4480 -> 0.572
-Confusion Matrix:
- [[ 76   1   8   3   5   6   5]
- [  5 141   2   0   5   1   9]
- [ 22  21 104  32  67  39  30]
- [ 20   3   5  91  17   5  16]
- [  1   6   4   3  61   2   3]
- [  5   0   7   4   2  48   5]
- [ 13   0   6  12   5  23  51]]
-Node Classification on random seed  4481 -> 0.619
-Confusion Matrix:
- [[ 62   1   7   3   6   5  15]
- [  7 140   6   1   2   1   3]
- [ 39  31 137  30  11  19  29]
- [ 17   2  11 103   5  21  12]
- [  2   9   4   0  62   2   4]
- [  7   3   7   3   0  36  15]
- [ 14   2  19   3   2   1  79]]
-Node Classification on random seed  4482 -> 0.593
-Confusion Matrix:
- [[ 81   5   2   5   5  12   7]
- [  6 127   4   5   7   1   3]
- [ 39  17 115  42  39  26  25]
- [ 16   4  14  90   7   6  10]
- [  3   3   4   3  60   1   0]
- [  3   0   1   8   0  45   9]
- [ 23   3  13   3   6  17  75]]
-Node Classification on random seed  4483 -> 0.637
-Confusion Matrix:
- [[ 59   2   4  12   5   7  15]
- [  1 147   9   3   8   1   2]
- [ 25  24 159  28  25  14  40]
- [  8   2  14 115   4   1  11]
- [  0   5   2   3  53   0   2]
- [  6   1   1   0   6  40   4]
- [ 13   3  10   3  20  19  64]]
-Node Classification on random seed  4484 -> 0.628
-Confusion Matrix:
- [[ 64   5   2  10   1  18  11]
- [  3 127   3   8   7   0   4]
- [ 26  15 150  33  23  31  33]
- [  9   4  13 110   5   6  11]
- [  0  10   3   3  64   1   1]
- [  2   0   2   3   2  38   8]
- [  3   4   5  12   7  25  75]]
-Node Classification on random seed  4485 -> 0.587
-Confusion Matrix:
- [[ 69   3   7   6   2  12   6]
- [  7 132   1   0   9   7   3]
- [ 32  33 128  27  20  41  32]
- [  6   7  18 108   4  14   8]
- [  1   5   5   1  56   5   2]
- [  5   4   0   1   0  44   3]
- [ 13   6  15   7  13  22  50]]
-Node Classification on random seed  4486 -> 0.625
-Confusion Matrix:
- [[ 55   3   4   7  11   7  11]
- [  2 108   9   1   8   1   4]
- [ 32  22 158  20  22  27  48]
- [ 17   4  14 102   6   9  10]
- [  2   5   2   1  64   0   3]
- [  6   1   2   0   1  52   4]
- [ 10   3  10  11   5  10  86]]
-Node Classification on random seed  4487 -> 0.626
-Confusion Matrix:
- [[ 54   1   7   0   8  19   6]
- [  1 127   8   2  10   3   6]
- [ 21  17 164  35  19  28  31]
- [ 10  12   9  95   8  12   3]
- [  1   8   1   1  57   4   6]
- [  1   0   0   6   8  50   0]
- [  4   6  14  11   3  24  79]]
-Node Classification on random seed  4488 -> 0.634
-Confusion Matrix:
- [[ 87   1   4   1   0  11   7]
- [  3 132  11   2   3   5   9]
- [ 21  17 153  29  13  10  52]
- [ 22   5  20  99   3   5  16]
- [  3   8   5   5  50   0   4]
- [  7   1   2   1   1  36   6]
- [ 28   2   7   4   8   4  77]]
-Node Classification on random seed  4489 -> 0.574
-Confusion Matrix:
- [[ 60   5   3   5   6  20  10]
- [  7 139   7   5   6   0   7]
- [ 24  22 120  38  38  18  36]
- [ 16   3  18  92   6  12  13]
- [  1   5   3   2  58   1   0]
- [  3   3   3   1   0  40   6]
- [ 23   8  11   9  10  12  65]]
-Node Classification on random seed  4490 -> 0.629
-Confusion Matrix:
- [[ 69   0   2   4   1  10   9]
- [  8 115   7   3  10   6   2]
- [ 46   6 165  35  16  24  38]
- [ 12   1  14  99   6   5  12]
- [  1   6   3   3  66   2   0]
- [  7   0   1   3   2  48   1]
- [ 16   5   4  13   8  19  67]]
-Node Classification on random seed  4491 -> 0.637
-Confusion Matrix:
- [[ 77   2   5   3   3   7  10]
- [  4 142   0   1  21   1   6]
- [ 17  25 134  21  23  28  32]
- [ 14   3  18 116   6   7   4]
- [  0   6   7   0  53   4   2]
- [ 11   1   1   3   0  48   2]
- [ 19   2   6   9  14  15  67]]
-Node Classification on random seed  4492 -> 0.633
-Confusion Matrix:
- [[ 83   2   5   8   4   7   1]
- [  6 130   5   1   4   1   3]
- [ 37  19 139  30  31  17  40]
- [ 19   5  12 108   2   7   7]
- [  0   2   2   6  70   0   4]
- [  8   2   1   0   0  31   4]
- [ 15   5   8  22   5  10  72]]
-Node Classification on random seed  4493 -> 0.559
-Confusion Matrix:
- [[ 72   2   4   4   6  10   9]
- [  7 125   3   1   9   1   2]
- [ 29  26  93  78  29  18  52]
- [ 20   5  13  96   7   3   9]
- [  0   6   4   3  57   1   3]
- [ 12   2   2   1   1  43   2]
- [ 14   2  14  13   2  12  73]]
-Node Classification on random seed  4494 -> 0.635
-Confusion Matrix:
- [[ 68   1   3   9   6  21   2]
- [  7 134   3  13   5   3   4]
- [ 24  13 158  38  18  14  40]
- [ 11   1  23  93   6   8  11]
- [  0   5   2   4  54   2   2]
- [  7   0   1   1   1  46  11]
- [ 11   3   3   9   7  12  82]]
-Node Classification on random seed  4495 -> 0.627
-Confusion Matrix:
- [[ 79   2   3   1   2  12   3]
- [  6 116  10   3   8   6   2]
- [ 28  21 150  20  26  36  41]
- [  8   3  15 113   3   9  13]
- [  0   6   4   0  63   0   2]
- [  9   0   2   0   0  39   4]
- [ 23   4   9   8   4  17  67]]
-Node Classification on random seed  4496 -> 0.581
-Confusion Matrix:
- [[ 61   6   5   4   4  11   5]
- [  6  94   3   4  19   2   1]
- [ 26  14 161  37  32  25  42]
- [ 17   8   9  95   9   8   9]
- [  0   6   6   2  63   1   2]
- [ 13   1   3   1   0  53   3]
- [ 27   3   7  12   6  20  54]]
-Node Classification on random seed  4497 -> 0.596
-Confusion Matrix:
- [[ 62   3   8   7   2  13   8]
- [  4 115   5   4   3  10   2]
- [ 14  15 137  47  40  20  51]
- [ 14   4   6 112   4   9  12]
- [  3   7   4   3  64   0   2]
- [  6   2   6   0   0  47   5]
- [  7   4  15   4   5  26  59]]
-Node Classification on random seed  4498 -> 0.588
-Confusion Matrix:
- [[ 71   3   6   7   9  13  10]
- [  4 125   3   0  11   3   6]
- [ 29  36 133  38  24  28  30]
- [  9   4  26  93   1  12   8]
- [  1   8   3   1  51   1   0]
- [ 10   0   4   1   1  42   4]
- [ 15   4   8  11   6  14  73]]
-Node Classification on random seed  4499 -> 0.655
-Confusion Matrix:
- [[ 60   2   4   8   8   7  10]
- [  6 115   6   1   5   1  11]
- [ 19  22 159  20  13  38  35]
- [ 15   3  14  96   2   2  17]
- [  1   3   4   1  79   1   2]
- [  8   2   3   2   2  51   0]
- [ 11   4  11   7   3  11  95]]
-Node Classification on random seed  4500 -> 0.653
-Confusion Matrix:
- [[ 72   0   1   4   6   8   7]
- [  3 153   6   2   6   4   3]
- [ 23  24 160  30  25  20  32]
- [  2   3  24 104   6   9  11]
- [  0   3   2   3  60   1   3]
- [  9   3   6   1   0  39   5]
- [ 12   7   5   1   7  20  65]]
-Node Classification on random seed  4501 -> 0.646
-Confusion Matrix:
- [[ 71   1   9   8   4  17   1]
- [  3 138   4   0   5   6   4]
- [ 24  17 149  23  23  25  49]
- [  9   4   8 103   1  14  12]
- [  0   9   5   0  61   0   4]
- [  5   1   1   3   0  50  10]
- [  5   1   4   8   7  20  74]]
-Node Classification on random seed  4502 -> 0.619
-Confusion Matrix:
- [[ 82   2   6   3   1  11  12]
- [  0 128   5   3   3   6   1]
- [ 33  18 138  66  28  16  33]
- [ 15   7  14 103   1   0  13]
- [  4   8   5   2  46   2   2]
- [  8   0   1   0   0  42   5]
- [ 15   3   7   4   7  11  80]]
-Node Classification on random seed  4503 -> 0.633
-Confusion Matrix:
- [[ 70   7   5   4   3  12  12]
- [  4 135   3   1  11   2   0]
- [ 15  43 140  26  25  26  33]
- [  3   5  26  87   3   7  15]
- [  0   2   4   2  71   1   2]
- [  4   2   4   2   3  44   7]
- [  4   7   6   3  12  11  86]]
-Node Classification on random seed  4504 -> 0.572
-Confusion Matrix:
- [[ 68   1   6  15   7   8   8]
- [  6 121   5   1   5   4   5]
- [ 27  22 113  58  30  21  35]
- [  8   3  20 105   6   5  16]
- [  6   7   4   1  53   3   4]
- [  5   0   2   3   0  50   7]
- [ 21   7  12   7   5  12  62]]
-Node Classification on random seed  4505 -> 0.6
-Confusion Matrix:
- [[ 78   1   4   3   2  18   7]
- [  5 120   7   5   9  15   2]
- [ 18  14 146  33  37  28  30]
- [ 14   1  13  96  13  13  14]
- [  0   4   0   1  47   1   0]
- [  4   0   2   7   1  49   2]
- [ 11   1  13  17   5  25  64]]
-Node Classification on random seed  4506 -> 0.61
-Confusion Matrix:
- [[ 52   1   9  13   3  17  16]
- [  6 120   7   6   6   5   5]
- [ 20  17 144  39  22  10  47]
- [ 10   1  10 107  10   7  13]
- [  0   8   4   1  61   1   2]
- [  2   1   0   1   2  41   7]
- [ 11   2   2   8  16  22  85]]
-Node Classification on random seed  4507 -> 0.674
-Confusion Matrix:
- [[ 78   2   7   4   3  15   6]
- [  5 143   3   1   9   0   6]
- [ 15  15 154  36  17  20  42]
- [ 11   1  10 112   2   5  12]
- [  1   7   7   1  58   0   1]
- [  0   2   4   0   0  48   7]
- [  6   2   9   8   9  15  81]]
-Node Classification on random seed  4508 -> 0.642
-Confusion Matrix:
- [[ 96   0   5   5   2  11   5]
- [  7 117   9   0   4   4   5]
- [ 25  21 143  35  25  17  40]
- [ 14   3  25 105   4   3  10]
- [  2   9   4   1  67   0   0]
- [  7   0   4   2   1  36  14]
- [  9   3  11   1   8   3  78]]
-Node Classification on random seed  4509 -> 0.555
-Confusion Matrix:
- [[ 64   3   6  10   1   7   5]
- [  8 134   6   0   6   7   9]
- [ 22  31  98  22  54  35  37]
- [  8   4  20 100   7   8  11]
- [  1   8   5   5  61   1   4]
- [  5   4   6   2   0  33   6]
- [ 14   3  16  17  10  11  65]]
-Node Classification on random seed  4510 -> 0.564
-Confusion Matrix:
- [[ 83   4   5  10   4   6   8]
- [  6 113   8   2   6   2  10]
- [ 29  23 113  26  27  41  40]
- [ 15  10  10  99   3  12  18]
- [  4   6   0   1  58   5   3]
- [  9   1   1   5   2  37   5]
- [ 21   5   9  17   4  13  61]]
-Node Classification on random seed  4511 -> 0.606
-Confusion Matrix:
- [[ 77   1  14   3   4  14   2]
- [  1 129   2  10   8   3   5]
- [ 35  14 134  34  35  24  45]
- [ 18   2   6 108   5   6  16]
- [  1   6   4   4  50   1   2]
- [  3   0   2   1   3  40   2]
- [  6   7  14   4   3  24  68]]
-Node Classification on random seed  4512 -> 0.635
-Confusion Matrix:
- [[ 73   9   0   4   2  11   2]
- [  4 107  11   7   9   3   7]
- [ 31  18 137  33  15  22  57]
- [ 12   2  12 123   1   9   6]
- [  1   5   6   3  55   1   4]
- [  3   0   3   1   1  62   1]
- [ 11   5   8   4   5  16  78]]
-Node Classification on random seed  4513 -> 0.594
-Confusion Matrix:
- [[ 77   3   3   3   1  10  15]
- [  5 118  10   4  12   3   7]
- [ 26  17 134  25  25  39  60]
- [ 16  12  18  88   2   5  12]
- [  2   4   0   0  57   1   5]
- [  3   0   2   3   0  42   6]
- [ 17   2   3  10   6   9  78]]
-Node Classification on random seed  4514 -> 0.641
-Confusion Matrix:
- [[ 72   2   5   4   3  17  11]
- [  4 125   4   5   8   1   3]
- [ 25  12 139  45  22  18  41]
- [ 11   5   8 105   3   8  16]
- [  1   5   3   2  59   0   5]
- [  6   2   0   2   1  47   5]
- [  7   6   8   6   2  17  94]]
-Node Classification on random seed  4515 -> 0.639
-Confusion Matrix:
- [[ 64   4   3   6   3  20   7]
- [  2 138   5   3   6   4   1]
- [ 20  26 154  43  27  13  37]
- [  5   4  29  99   3   5  11]
- [  0   7   2   1  64   0   3]
- [  5   2   2   0   3  40   2]
- [  6   1   6   6   5  23  80]]
-Node Classification on random seed  4516 -> 0.638
-Confusion Matrix:
- [[ 73   1   2   3   4  12  14]
- [  4 124   4   5   7   0   2]
- [ 26  29 135  37  20  24  25]
- [ 14   1  18  97   2   4  24]
- [  0   6   1   2  69   2   1]
- [  4   1   2   0   0  47   3]
- [ 13   4   9  15   9   8  93]]
-Node Classification on random seed  4517 -> 0.632
-Confusion Matrix:
- [[ 78   4   3   5   3   5   6]
- [  7 110   5   6  12   0   4]
- [ 21  43 141  38  19  20  39]
- [  5   9  11 105   3   1  22]
- [  0   6   6   2  68   0   4]
- [  6   0   0   3   2  42   3]
- [ 11   6   8   1   2  17  88]]
-Node Classification on random seed  4518 -> 0.662
-Confusion Matrix:
- [[ 72   5   1   6   4  18   1]
- [  8 139   5   2   2   2   1]
- [ 18  20 143  27  19  12  49]
- [  7   2   7 115   2   6   7]
- [  3  10   3   4  72   0   2]
- [  3   3   1   1   3  50   3]
- [  8   8  14   5   6  30  71]]
-Node Classification on random seed  4519 -> 0.61
-Confusion Matrix:
- [[ 72   3   2   1   2  10  19]
- [  6 119  11   4   2   0   8]
- [  7  12 137  64  32  25  48]
- [ 17   2  11 104   2   7  12]
- [  5   2   5   3  61   1   5]
- [  6   2   1   1   0  44   4]
- [ 10   5  13   4   7   9  73]]
-Node Classification on random seed  4520 -> 0.589
-Confusion Matrix:
- [[ 54   5  18   9   5  12   1]
- [  2 116  16   3  11   5   2]
- [ 31  22 145  43  32  15  31]
- [  7   6  10 109   5   9  16]
- [  1   3   6   2  55   0   6]
- [  5   1  14   1   1  45   4]
- [ 13   2   9   0   4  23  65]]
-Node Classification on random seed  4521 -> 0.647
-Confusion Matrix:
- [[ 78   3   6   2   2  12   9]
- [  6 128  12   1   5   1   2]
- [ 24  22 146  22  36   8  39]
- [  9   5  25  96   9   8   8]
- [  1   6   5   3  68   1   1]
- [  1   2   5   2   0  39   8]
- [  8   3   7   4   8  12  92]]
-Node Classification on random seed  4522 -> 0.617
-Confusion Matrix:
- [[ 81   1   7   3   5   4  10]
- [  8 121   5   0  16   0   4]
- [ 27  26 135  40  30  17  26]
- [ 14   3  20 108   2   5   8]
- [  3   4   5   1  61   1   3]
- [ 11   2   5   0   3  35   4]
- [ 22   4   8   7   7  12  76]]
-Node Classification on random seed  4523 -> 0.628
-Confusion Matrix:
- [[ 69   4   4   7   6  11   6]
- [  7 141   7   1   9   0  12]
- [ 25  18 154  31  28  14  45]
- [  9  14   9  88   4   7  12]
- [  2   6   3   0  67   2   2]
- [  5   1   2   2   7  43   1]
- [ 14   4  10   4   5  12  66]]
-Node Classification on random seed  4524 -> 0.636
-Confusion Matrix:
- [[ 81   4   0   8   3   8  15]
- [  0 122   5   0  11   4   9]
- [ 29  17 159  12  18  17  61]
- [ 10   6  23 107   4   6  14]
- [  1   4   6   0  47   0   4]
- [ 10   2   2   3   1  43   5]
- [ 15   4   4   5   5   9  77]]
-Node Classification on random seed  4525 -> 0.587
-Confusion Matrix:
- [[ 69   2   8  12   0  13   8]
- [  3 110  15   2   3   6  11]
- [ 18   8 141  37  41  22  52]
- [ 12   1  27 102   4   7  10]
- [  0   4   6   5  44   1   3]
- [  6   1   1   1   0  44   5]
- [ 11   0   7   9   6  25  77]]
-Node Classification on random seed  4526 -> 0.589
-Confusion Matrix:
- [[ 83   0   2   4   2   5   7]
- [ 18 124   6   0   1   5   2]
- [ 28  28 132  56  22  11  45]
- [ 26   2  17 107   1   0   7]
- [  2   7   7   5  54   0   2]
- [  9   1   2   4   0  36   2]
- [ 24   3   9  17   6  16  53]]
-Node Classification on random seed  4527 -> 0.623
-Confusion Matrix:
- [[ 85   3   1  14   2  11   9]
- [  8 118   4   3   3   3   2]
- [ 36  19 137  33  11  28  53]
- [  8   4   4  94  11   7  17]
- [  3   5   4   2  55   1   2]
- [  9   0   0   1   2  41  10]
- [ 23   5   4   3   3   6  93]]
-Node Classification on random seed  4528 -> 0.592
-Confusion Matrix:
- [[ 60   3   1   7   8  17  10]
- [  2 103  11   1  13   0   3]
- [ 28   7 143  37  29  21  48]
- [ 23   3   5  86  11   8  12]
- [  1  11   3   1  68   2   3]
- [  4   1   4   2   2  51   5]
- [ 16   4  13   9   7  12  81]]
-Node Classification on random seed  4529 -> 0.598
-Confusion Matrix:
- [[ 67   3   4   1   3   5  18]
- [  5 118   8   2  14   6   0]
- [ 24  39 141  25  34  21  32]
- [ 11   6   9 107   2   3  28]
- [  0   6   7   2  56   1   0]
- [  3   3   1   0   3  45  10]
- [ 17   7   6   3  18  12  64]]
-Node Classification on random seed  4530 -> 0.614
-Confusion Matrix:
- [[ 84   2   3   8   1  12   1]
- [  9 124   9   2   6   2   2]
- [ 29  31 134  31  32  32  20]
- [ 14   8   8 104   2  13  11]
- [  0  10   2   2  64   1   1]
- [  7   2   3   2   0  45   1]
- [  8   2  13  20   6  18  59]]
-Node Classification on random seed  4531 -> 0.639
-Confusion Matrix:
- [[ 73  11   3   8   2   6  10]
- [  5 126   5   1   1   3   5]
- [ 38  11 140  35  34  16  39]
- [  7   8  12 108   8   4  11]
- [  2   4   6   0  60   0   6]
- [  3   2   2   2   0  46   3]
- [ 15   2   7  13   2   9  86]]
-Node Classification on random seed  4532 -> 0.608
-Confusion Matrix:
- [[ 55   4   4   9   6   6  17]
- [  6 138   7   2   8   0   1]
- [ 19  25 131  37  40  22  42]
- [  8  11  13 103   5  10  12]
- [  1   8   2   0  62   0   1]
- [  4   2   4   5   1  42   4]
- [  7   4  13   5  10   7  77]]
-Node Classification on random seed  4533 -> 0.611
-Confusion Matrix:
- [[ 66   2   3   0   6  21   7]
- [  3 127   3   2   4   0   4]
- [ 14  21 140  40  37  21  53]
- [ 16   1  16 106   3  11   8]
- [  1   9   0   5  44   1   2]
- [  2   2   0   3   1  48   7]
- [ 12   7   8  10   9  14  80]]
-Node Classification on random seed  4534 -> 0.603
-Confusion Matrix:
- [[ 56   2   8   2   5  10  14]
- [  1 123   5   6  13   3   7]
- [ 23  17 145  71  17  21  30]
- [ 19   4  13 113  14   3   6]
- [  0   5   3   0  62   0   1]
- [  1   2   0   1   0  44   4]
- [  9   2   9  20   9  17  60]]
-Node Classification on random seed  4535 -> 0.635
-Confusion Matrix:
- [[ 82   0   4   2   2  13   9]
- [  2 134  10   2   7   0   1]
- [ 19  20 140  23  24  31  47]
- [  3   2  14  97   4   8  19]
- [  0  14   4   1  62   0   2]
- [  3   2   3   2   0  52   3]
- [  3   5  12   8  10  27  68]]
-Node Classification on random seed  4536 -> 0.581
-Confusion Matrix:
- [[ 65   3   5   4  11   7  12]
- [ 21 101   2   2  12   4   5]
- [ 25  12 131  45  23  34  39]
- [ 10   2  18 101  11   9  20]
- [  1   9   5   2  56   0   0]
- [  4   9   4   2   0  37   4]
- [ 17   0   3   6   4  13  90]]
-Node Classification on random seed  4537 -> 0.609
-Confusion Matrix:
- [[ 49   5   9   8   7  16  14]
- [ 10 123   7   4   7   2   3]
- [ 26  25 141  23  33  22  42]
- [  8   9   9 116   4   5  12]
- [  0   7   3   0  66   0   2]
- [  3   1   8   2   1  41   9]
- [  9   4   8  11   2  11  73]]
-Node Classification on random seed  4538 -> 0.635
-Confusion Matrix:
- [[ 81   0  11   4   1   5   6]
- [ 10 125   5   3   5   1   4]
- [ 26  21 135  37  28  17  42]
- [ 14   4   7 117   4   7  12]
- [  4   7   3   0  63   1   2]
- [  5   2   2   3   0  44   7]
- [ 17   2   9   7   8  12  70]]
-Node Classification on random seed  4539 -> 0.583
-Confusion Matrix:
- [[ 77   4   7   2  10  14   9]
- [  5 139  12   2   6   2   5]
- [ 23  27  97  33  33  19  54]
- [  8   8   7 101  12   5  15]
- [  3   8   1   3  65   0   6]
- [  8   0   2   2   3  28  11]
- [ 15   1   7  11   5   9  76]]
-Node Classification on random seed  4540 -> 0.61
-Confusion Matrix:
- [[ 77   2   4   6   5  10   8]
- [  2  98   9   7   8   5   5]
- [ 22  20 129  34  54  21  32]
- [  3   2  19 113   3   7  15]
- [  5   3   1   4  69   0   1]
- [  2   0   1   1   3  48   2]
- [ 16   5   5  23   6   9  76]]
-Node Classification on random seed  4541 -> 0.638
-Confusion Matrix:
- [[ 70   3  14   9   5   9  15]
- [ 12 131   5   0   9   1   1]
- [ 20  16 180  24  25  15  28]
- [ 25  11  12  95   4   4  21]
- [  4   3   4   5  53   1   5]
- [  2   0   3   0   0  37   5]
- [ 21   0   5   6   3   7  72]]
-Node Classification on random seed  4542 -> 0.608
-Confusion Matrix:
- [[ 70   3   1   6   7   6  14]
- [  3 121  10   1   8   3   5]
- [ 30  15 145  43  17  16  42]
- [ 11   3  12  95   6   6  14]
- [  0   6   8   0  67   2   2]
- [  5   0   0   2  10  37  11]
- [ 15   3  11  12   4  19  73]]
-Node Classification on random seed  4543 -> 0.623
-Confusion Matrix:
- [[ 86   2   1   4   2   6   8]
- [  6 134   5   3  13   3   1]
- [ 20  24 147  30  27  18  35]
- [ 12   2  18 102   2   8  21]
- [  5   6   7   3  48   2   0]
- [ 10   0   1   8   1  36   7]
- [ 13   2  10   9   6  16  70]]
-Node Classification on random seed  4544 -> 0.601
-Confusion Matrix:
- [[ 71   4   3   2   9  17  18]
- [  7 125   5   1   9   3   6]
- [ 25  17 160  28  17  26  48]
- [ 11   3  19  73   0  15  17]
- [  7   5   8   5  51   4   1]
- [  1   0   2   1   1  47   2]
- [ 11   5   8   3  13  12  74]]
-Node Classification on random seed  4545 -> 0.63
-Confusion Matrix:
- [[ 71   4   4   2   6  12   5]
- [  1 135   5   2  10   2   2]
- [ 25  10 158  33  20  31  17]
- [ 18   5  25  71   8  11  17]
- [  2  15   4   0  55   3   1]
- [  7   0   3   0   0  51   4]
- [  6   1   7  10  21  11  89]]
-Node Classification on random seed  4546 -> 0.619
-Confusion Matrix:
- [[ 74   1   2   4   2  12   5]
- [  4 127   7   4   3   7   3]
- [ 29  10 146  41  20  11  56]
- [ 18   6  17 102   2   5  18]
- [  0   5   8   1  53   2   4]
- [  8   6   5   0   1  35   7]
- [ 20   2  13   4   2   6  82]]
-Node Classification on random seed  4547 -> 0.596
-Confusion Matrix:
- [[ 51   1   3  10  12  25   6]
- [  5 137   1   2   7   4   4]
- [ 26  25 152  25  23  23  41]
- [  8   5  21  93   8  15  16]
- [  3   5   4   3  57   1   3]
- [  5   0   1   2   1  49   5]
- [ 16   3  13   6   7  10  57]]
-Node Classification on random seed  4548 -> 0.614
-Confusion Matrix:
- [[ 47  11   4   4   1  12  13]
- [  2 133  15   3   7   2   1]
- [ 45  29 131  29  35  19  29]
- [ 13   1  11 113   4   2   6]
- [  1   4   4   6  71   1   4]
- [  8   0   1   4   0  43   4]
- [ 10   7  12   7   5  10  76]]
-Node Classification on random seed  4549 -> 0.626
-Confusion Matrix:
- [[ 68   0   5   6   3  12   3]
- [  7 137   3   4   8   1   3]
- [ 19  31 130  27  43  22  44]
- [  7   3  15 103   3   4  16]
- [  0   4   3   4  64   1   3]
- [  3   0   4   4   0  47   3]
- [  7   3  12   7   6  21  77]]
-Node Classification on random seed  4550 -> 0.637
-Confusion Matrix:
- [[ 82   1   6   3   7   8   5]
- [  0 112  11   1  14   1   7]
- [  9  25 143  24  29  19  55]
- [ 18   2  10 128   1   5   8]
- [  2   4   9   1  63   0   4]
- [ 10   0   2   0   1  36  11]
- [  2   3  13  14   6  12  73]]
-Node Classification on random seed  4551 -> 0.608
-Confusion Matrix:
- [[ 65   4   5   2   9  19  12]
- [  1 102  16   4  14   8  11]
- [ 27  15 153  30  23  18  36]
- [  2   0  16  92  14  14  26]
- [  1   2   6   2  62   1   2]
- [  4   1   2   4   0  44   5]
- [  1   4   6   8  10   7  90]]
-Node Classification on random seed  4552 -> 0.599
-Confusion Matrix:
- [[ 74   5   2   1   2   9  14]
- [  8 107   3   4  12   5   1]
- [ 16  27 142  39  33  29  53]
- [ 20   4  15  95   1   9   3]
- [  1   2   2   1  67   3   6]
- [  5   2   1   1   2  51   0]
- [ 13   7   5   9   5  21  63]]
-Node Classification on random seed  4553 -> 0.612
-Confusion Matrix:
- [[ 70   0  18   6   1  14  14]
- [ 13 139   7   0  10   5   5]
- [ 26  22 147  25  12  21  41]
- [  8   9  22  87   5  11  20]
- [  1   5   3   2  56   0   0]
- [  3   1   5   2   0  28  21]
- [  3   2  17   4   2   2  85]]
-Node Classification on random seed  4554 -> 0.625
-Confusion Matrix:
- [[ 81   1   2   2   2  13   7]
- [  2 113  17   4  10   4   2]
- [ 36  16 150  43  26  18  25]
- [ 20   4  26 104   1   4   5]
- [  0   9   1   3  67   0   0]
- [  7   2   1   4   1  36   6]
- [ 14   4   9   3   4  17  74]]
-Node Classification on random seed  4555 -> 0.601
-Confusion Matrix:
- [[ 61   9   1   6   0  25   3]
- [  3 121   5   1   3   4   2]
- [ 28  26 148  45  25  33  23]
- [  6   5  18 114   8   7   6]
- [  7   8   0   4  60   3   1]
- [  8   0   5   2   7  36   6]
- [  8   2   6   6  15  19  61]]
-Node Classification on random seed  4556 -> 0.631
-Confusion Matrix:
- [[ 68   0   6   9   3   9  10]
- [  4 131   6   5   5   5   4]
- [ 15  26 124  20  22  39  35]
- [  7   0  18  97   7  11  13]
- [  2   3  10   2  78   1   1]
- [  2   0   0   2   0  50  14]
- [ 13   4   6   8  10  12  83]]
-Node Classification on random seed  4557 -> 0.617
-Confusion Matrix:
- [[ 57   5   1  11   4  15  11]
- [ 10 125   8   0   7   0   8]
- [ 20  19 156  39  28  18  37]
- [  6   4  27 102   2   4  14]
- [  1   4   7   1  63   0   5]
- [  5   3   2   1   0  40   5]
- [ 17   4  10   4   1  15  74]]
-Node Classification on random seed  4558 -> 0.564
-Confusion Matrix:
- [[ 74   2   8  12   3  10   5]
- [  8 137   3   0   4   2   7]
- [ 21  29 110  30  65  20  48]
- [ 10  11  10  99   4   8   7]
- [  0   8   2   0  55   1   5]
- [ 12   2   0   2   0  43   6]
- [ 14   5   9  15  12  16  46]]
-Node Classification on random seed  4559 -> 0.61
-Confusion Matrix:
- [[ 69   0   2  12   4  13  12]
- [ 10 121   6   1   6   6   1]
- [ 21  30 144  40  33  24  27]
- [ 16   4  12 104   3   6  11]
- [  2   3   2   0  64   1   1]
- [  6   1   4   7   3  36   5]
- [ 14   1   6  15  11   8  72]]
-Node Classification on random seed  4560 -> 0.63
-Confusion Matrix:
- [[ 72   4   5   7   2  11   6]
- [  2 119   6   3   8   4   8]
- [ 30  18 157  16  33  21  30]
- [  8   7  20 104   6   5  14]
- [  3   2  12   3  57   0   0]
- [  5   1   2   1   2  48   3]
- [ 11   6  14   6   2  23  73]]
-Node Classification on random seed  4561 -> 0.597
-Confusion Matrix:
- [[ 68   2   1  11   9  14  12]
- [  3 135   0   1   3   3   9]
- [ 21  21 127  28  29  25  47]
- [  9   0  21  97   5   8  16]
- [  0   8   3   1  60   0   2]
- [  8   0   0   3   0  44   9]
- [ 15   7   6  17   9  17  66]]
-Node Classification on random seed  4562 -> 0.63
-Confusion Matrix:
- [[ 70   9   3   4   4  15   9]
- [  2 149   8   4   2   3   2]
- [ 13  28 131  36  26  18  48]
- [  6   8  11 112   6   4  16]
- [  1   4   6   2  49   3   4]
- [  5   3   1   0   3  49   9]
- [ 11   4   6   6   6  11  70]]
-Node Classification on random seed  4563 -> 0.64
-Confusion Matrix:
- [[ 89   7   3   5   2   9   4]
- [  2 137   2   2  15   0   2]
- [ 18  35 163  29  20  18  44]
- [  7   7  15  95   3   9   5]
- [  3  10   1   1  52   0   1]
- [  2   3   1   2   1  50   2]
- [ 19   5  14   5   2  25  54]]
-Node Classification on random seed  4564 -> 0.611
-Confusion Matrix:
- [[ 82   1   8   4   5   7   9]
- [ 10 114   2   6  14   4   3]
- [ 13  22 142  18  41  22  35]
- [  8   6  13 102  10  13  14]
- [  2   4   4   2  52   1   1]
- [ 11   1   5   0   2  43  10]
- [ 17   9  15   4   6   7  76]]
-Node Classification on random seed  4565 -> 0.606
-Confusion Matrix:
- [[ 65   3   2   6   4  12   7]
- [  5 138   3   2   9   3   5]
- [ 34  15 128  30  46  34  34]
- [  5   8  15  90   2   5  18]
- [  5   9   3   2  61   1   2]
- [  4   0   6   1   1  48   5]
- [  8   4   6   5   8  17  76]]
-Node Classification on random seed  4566 -> 0.614
-Confusion Matrix:
- [[ 64   2  10   2   0  15  16]
- [  1 102   7   4   8   8   2]
- [ 31  14 136  43  28  18  48]
- [  8   9  11 122   2   7  11]
- [  4   5   2   4  60   0   5]
- [  7   0   2   1   0  49   3]
- [  6   1   8   9   4  20  81]]
-Node Classification on random seed  4567 -> 0.616
-Confusion Matrix:
- [[ 64   1   9   3   9  11   1]
- [  2 137   4   1   7   1   2]
- [ 29  30 143  27  40  12  40]
- [ 18   6  11  99   8   6  13]
- [  1  13   0   2  62   2   1]
- [  2   2   2   3   2  46   3]
- [ 13   3   9   3   6  26  65]]
-Node Classification on random seed  4568 -> 0.622
-Confusion Matrix:
- [[ 71   4  10  10   7   9   3]
- [  2 129   9   4   8   0   2]
- [ 10  20 135  31  40  22  49]
- [ 16   8  12  98   4   2  11]
- [  1   7   2   0  67   1   4]
- [  9   0   1   3   0  46   4]
- [  8   4   6  19   4  12  76]]
-Node Classification on random seed  4569 -> 0.609
-Confusion Matrix:
- [[ 54   2   1   8   2  14  19]
- [  4 100   7   3   9   9   5]
- [ 24  19 143  30  34  19  34]
- [ 12   3   8 104   5   3  25]
- [  4   7   3   2  65   0   5]
- [  5   1   0   1   2  38  10]
- [ 13   0   5   5  13  16 105]]
-Node Classification on random seed  4570 -> 0.652
-Confusion Matrix:
- [[ 94   2   6   3   1   7   5]
- [  5 132   6   0   5   2   5]
- [ 27  22 144  36  37  14  39]
- [  6   2  15 111   3   7  17]
- [  0   7   3   0  59   1   7]
- [  2   2   3   2   0  45   4]
- [ 17   2   9   8   0   9  67]]
-Node Classification on random seed  4571 -> 0.582
-Confusion Matrix:
- [[ 61  10   3  10   6  12   5]
- [  5 125   4   1  12   5   6]
- [ 24  14 133  29  33  36  40]
- [ 11   4  13 110   5   3  11]
- [  1   8   1   2  60   2  10]
- [  8   1   1   2   3  34   9]
- [ 12   0  16   8  21  11  59]]
-Node Classification on random seed  4572 -> 0.609
-Confusion Matrix:
- [[ 70   7   3   6   4   6   6]
- [  4 138   1   3   6   1   7]
- [ 30  25 124  20  22  25  50]
- [ 13  11  13  96  12   9   7]
- [  1  15   2   1  66   1   3]
- [ 11   2   3   0   0  35   4]
- [ 18   0   5   6   3  25  80]]
-Node Classification on random seed  4573 -> 0.612
-Confusion Matrix:
- [[ 67   4   4   2   4  14  11]
- [ 10 118  13   2   7   7   0]
- [ 20  27 151  52  15  17  45]
- [ 12   8  10 105   2   6  19]
- [  0   7   5   1  65   2   3]
- [  9   3   0   1   0  36   6]
- [ 12   4   7   4   3  10  70]]
-Node Classification on random seed  4574 -> 0.628
-Confusion Matrix:
- [[ 78   3   8   1   1   8  12]
- [  3 138   3   4   2   0   6]
- [ 27  22 139  37  26  23  39]
- [ 19   5  13  89   9   8  16]
- [  2   9   4   0  59   1   0]
- [  3   0   3   2   0  36   6]
- [ 13   2  19   1   4   8  89]]
-Node Classification on random seed  4575 -> 0.595
-Confusion Matrix:
- [[ 68   1   3   3   3  16  14]
- [  3 117   4   4   7   5   6]
- [ 15  17  85  56  64  28  46]
- [  7   3  11 108   3   4  21]
- [  1   3   0   1  69   5   1]
- [  7   0   1   4   0  49   2]
- [  4   1   7   4   7  13  99]]
-Node Classification on random seed  4576 -> 0.651
-Confusion Matrix:
- [[ 85   3   1   2   2   3  18]
- [  4 137   3   3   8   4   3]
- [ 15  26 141  22  22  18  45]
- [ 13   2  23 103   5   1  11]
- [  1   9   3   1  58   0   0]
- [  6   4   3   2   2  44   7]
- [ 14   4  12   3   9  12  83]]
-Node Classification on random seed  4577 -> 0.629
-Confusion Matrix:
- [[ 57   8   2   6   1   5  10]
- [  8 142   6   4   7   1   4]
- [ 22  24 161  39  27  22  25]
- [ 15   0  14 109  10   6   8]
- [  3   2   2   1  57   0   2]
- [  9   1   2   8   0  43   5]
- [ 13   4  11  20   4  10  60]]
-Node Classification on random seed  4578 -> 0.649
-Confusion Matrix:
- [[ 65   0   4   9   3  12   3]
- [  4 133   2   2   6   3   3]
- [ 31  13 150  31  18  20  54]
- [  8   2  22 106   3   5  11]
- [  3   8   6   1  62   1   4]
- [  6   4   2   0   0  51   6]
- [ 17   1  10   4   4   5  82]]
-Node Classification on random seed  4579 -> 0.659
-Confusion Matrix:
- [[ 82   5   2   4   3   9  10]
- [  5 119  11   2   7   1   7]
- [ 17  18 166  25  31  19  35]
- [ 14   5  21 109   4   4   3]
- [  2   7   4   2  60   0   2]
- [  2   0   3   1   0  45   6]
- [ 14   4   6   5   5  16  78]]
-Node Classification on random seed  4580 -> 0.593
-Confusion Matrix:
- [[ 78   1   3   2   3  18  12]
- [  4 124   3  10   5   4   6]
- [ 19  20 121  66  41  20  36]
- [  8   0  15  95   8   7  16]
- [  1   1   3   3  63   4   0]
- [  5   2   0   0   0  42   4]
- [  8   3  11   5   7  23  70]]
-Node Classification on random seed  4581 -> 0.59
-Confusion Matrix:
- [[ 66   6   4   4   4  16   5]
- [ 14 125   3   4  14   2   7]
- [ 20  16 144  39  22  24  44]
- [ 14   5  26  77  12  10  15]
- [  5   1   3   0  54   0   1]
- [  6   1   1   0   0  54   2]
- [ 16   3   3  18   8  12  70]]
-Node Classification on random seed  4582 -> 0.594
-Confusion Matrix:
- [[ 73   3   8   3   2  12   8]
- [  8 122   3   2   1   0   2]
- [ 20  19 139  57  13  16  60]
- [ 12   1  19  96   2   8  25]
- [  3   9   4   2  51   3   1]
- [  2   2   2   0   4  46   6]
- [ 12   4   8   7   7  26  67]]
-Node Classification on random seed  4583 -> 0.642
-Confusion Matrix:
- [[ 61   4   4   1   5  11   5]
- [  5 120   4   1  22   1   5]
- [ 16  17 158  29  19  29  47]
- [  7   4  18 112   2   8   6]
- [  0   5   5   2  61   0   5]
- [  0   0   3   1   4  58   5]
- [ 19   3   7   3   6  20  72]]
-Node Classification on random seed  4584 -> 0.595
-Confusion Matrix:
- [[ 61   4   5   5  10  20  16]
- [  2 142   6   2   5   5   2]
- [ 29  14 120  38  53   7  33]
- [ 11   9  26  93   9   3   7]
- [  0   9   0   5  62   1   1]
- [  5   2   2   0   0  39  13]
- [  7   4  13   2   4  16  78]]
-Node Classification on random seed  4585 -> 0.591
-Confusion Matrix:
- [[ 78   1   4   2   5   8  12]
- [  3 116   7   0  14   3   4]
- [ 29  18 116  51  25  31  47]
- [  7   3  21 105   2  12  12]
- [  0  10   6   2  62   3   1]
- [  4   0   1   1   2  50   3]
- [  6   5   7  13  11  13  64]]
-Node Classification on random seed  4586 -> 0.616
-Confusion Matrix:
- [[ 65   3   5   3   4  10   6]
- [  2 144   7   2   9   0   5]
- [ 21  22 149  48  20  17  43]
- [ 11   1  29  83   3   8  19]
- [  1   2   5   2  58   2   2]
- [  3   2   4   1   0  43   9]
- [  9   0  15   2   8  19  74]]
-Node Classification on random seed  4587 -> 0.613
-Confusion Matrix:
- [[ 67   3   5   6   4  15   7]
- [  3 125   1   4  11   8   5]
- [ 21  19 146  29  43  13  36]
- [  7   5  15 110  12   2  10]
- [  4   2   4   4  61   1   1]
- [  4   1   1   5   0  45   6]
- [  9   4   8  20  11  18  59]]
-Node Classification on random seed  4588 -> 0.596
-Confusion Matrix:
- [[ 63   2   4   6   2  15   8]
- [  4 113  12   5  10   2  10]
- [ 23  15 150  40  22  23  40]
- [ 11   1  12 106   6   3  17]
- [  1   6   3   3  56   2   2]
- [  7   0   2   2   0  42   6]
- [  9   5  18   9  10  26  66]]
-Node Classification on random seed  4589 -> 0.582
-Confusion Matrix:
- [[ 76   3   4   1   1   5   9]
- [ 11 119   4   8  12   3   5]
- [ 33  14 120  60  33  17  47]
- [ 11   2  16  97   4   7  15]
- [  2   7   2   0  49   1   3]
- [  7   2   0   2   0  51   6]
- [ 15   5   6   7   4  24  70]]
-Node Classification on random seed  4590 -> 0.637
-Confusion Matrix:
- [[ 88   1   0   4   1  13  14]
- [  6 137   4   2   6   3   1]
- [ 41  20 132  37  20  36  28]
- [ 15   5  12 112   2   6   7]
- [  4   4   2   2  53   0   2]
- [  2   1   4   1   0  53   2]
- [ 19   1   8   6   2  19  62]]
-Node Classification on random seed  4591 -> 0.577
-Confusion Matrix:
- [[ 33   1   4  16   2  16  18]
- [  4 132   8   1   7   3   6]
- [ 18  35 141  36  12  49  45]
- [  5   4  22  97   2  10  18]
- [  1   7   4   4  48   1   2]
- [  4   1   1   1   3  47  11]
- [  5   3   4   4  11  14  79]]
-Node Classification on random seed  4592 -> 0.655
-Confusion Matrix:
- [[ 70   6   1  10   3  12   6]
- [  1 117   6   4   8   2   4]
- [ 10  20 176  29  18  23  25]
- [  6   8  29  91   5  11  15]
- [  2   4   2   2  65   3   1]
- [  1   3   2   3   0  48   4]
- [ 13   5   4   5   9  20  88]]
-Node Classification on random seed  4593 -> 0.606
-Confusion Matrix:
- [[ 74   1  11   8   1  12   6]
- [  4 134   8   0   5   2   4]
- [ 33  23 113  24  23  35  44]
- [  7   4  19 101   9   6   6]
- [  0   9   1   1  67   1   2]
- [  3   5   5   1   4  44   4]
- [  8   7  17   9   6  16  73]]
-Node Classification on random seed  4594 -> 0.61
-Confusion Matrix:
- [[ 76   1   5   8  10  15  11]
- [  1 123   7   0  16   3   7]
- [ 19  26 129  34  30  20  48]
- [ 15   3  16 101   3   6   8]
- [  0   3   4   1  56   1   1]
- [  3   2   0   4   3  48   3]
- [  7   3   6  12   7  18  77]]
-Node Classification on random seed  4595 -> 0.599
-Confusion Matrix:
- [[ 71   4   7   5   3  10   6]
- [  5 140   5   4   2   4   6]
- [ 14  24 129  31  27  33  59]
- [ 21   3  20  79   3  12  14]
- [  1   6   1   0  68   2   5]
- [  2   1   2   0   2  40   5]
- [  6   2  10   7   5  22  72]]
-Node Classification on random seed  4596 -> 0.601
-Confusion Matrix:
- [[ 64   0   4  14   2   5  11]
- [  2 128   7   3   6   2   5]
- [ 16  20 155  32  35  27  44]
- [  4   3  21 103   6   7  25]
- [  2   3   7   1  52   0   3]
- [  6   2   3   2   0  35   7]
- [ 14   1   9   3  22  13  64]]
-Node Classification on random seed  4597 -> 0.585
-Confusion Matrix:
- [[ 64   4   5  10   3   6  10]
- [  7 120   2   7   5   4   1]
- [ 39  34 115  42  23  16  47]
- [ 11   2  12 106  14   7  10]
- [  1   7   8   0  63   2   3]
- [  5   1   1   1   0  40   6]
- [ 16   4   6  12   8  13  77]]
-Node Classification on random seed  4598 -> 0.624
-Confusion Matrix:
- [[ 65   1  10   6   4   7  15]
- [  4 131   7   2   7   0   8]
- [ 20  27 151  31  28  14  47]
- [ 10   2  20  99   5   9  21]
- [  0  10   1   2  60   0   3]
- [  4   0   3   2   0  45   6]
- [  9   2  15   4   5   5  73]]
-Node Classification on random seed  4599 -> 0.61
-Confusion Matrix:
- [[ 76   0   4   2   3  11   7]
- [ 11 128   6   3   9   2   6]
- [ 31  12 129  39  43  19  37]
- [ 13   3   9  97   4   6  13]
- [  0   2   4   2  60   2   4]
- [  4   6   4   2   2  40   7]
- [ 15   4   8   6   6  19  80]]
-Node Classification on random seed  4600 -> 0.582
-Confusion Matrix:
- [[ 76   4   0   5   0   6  10]
- [  8 126   5   3   4   2   3]
- [ 39  37 111  42  24  27  36]
- [ 18  10  14  93   3  10   6]
- [  0   4   5   0  64   0   3]
- [  7   2   3   2   0  46   7]
- [ 21   4  15   5   5  19  66]]
-Node Classification on random seed  4601 -> 0.599
-Confusion Matrix:
- [[ 60   1   9   9   5  22   3]
- [  8 122   4   4   6   9   4]
- [ 27  11 130  34  31  30  48]
- [ 14   5  17 105   6  11   9]
- [  2   9   3   0  57   1   1]
- [  1   2   0   1   1  54   1]
- [  5   5   6   4  10  22  71]]
-Node Classification on random seed  4602 -> 0.641
-Confusion Matrix:
- [[ 74   4   7   4   1   6  11]
- [  9 134   5   2   3   2   2]
- [ 30  14 151  29  26  42  26]
- [ 11   5  11 114   5   2   9]
- [  4   7   5   2  53   0   1]
- [  5   2   1   1   2  40   2]
- [ 12   1  13  13   4  18  75]]
-Node Classification on random seed  4603 -> 0.617
-Confusion Matrix:
- [[ 63   7   6   4   4  10  14]
- [ 11 135   3   1   7   0   6]
- [ 22  22 145  26  13  35  49]
- [  4   9  25  89   8   7  15]
- [  2   1   6   1  52   4   0]
- [  6   0   0   3   2  45   6]
- [  3   3  15   4   2  17  88]]
-Node Classification on random seed  4604 -> 0.586
-Confusion Matrix:
- [[ 72   7   8   7   3   7  12]
- [  6 123  12   0   7   2   2]
- [ 16  28 112  46  18  22  35]
- [  9  10  27 121   3   4   6]
- [  1  14   5   0  52   0   1]
- [ 10   3   4   2   3  35   4]
- [ 13  11  16   9   3  18  71]]
-Node Classification on random seed  4605 -> 0.578
-Confusion Matrix:
- [[ 76   3   7   1   6   9  14]
- [  2 121  12  10   2   0   3]
- [ 23  24 128  28  37  32  33]
- [ 11   9  26  83   9   1  23]
- [  2   9   3   5  55   3   4]
- [  3   1   4   3   0  41   4]
- [ 13   2  10   9   5  17  74]]
-Node Classification on random seed  4606 -> 0.612
-Confusion Matrix:
- [[ 75   1   4   6   2   9  10]
- [  3 122   2   4  14   4   3]
- [ 22  18 144  41  28  23  46]
- [  7   3   8 109   9   8  13]
- [  2   1   6   1  60   1   1]
- [  5   1   3   3   0  44   8]
- [  9   2   3  18   8  28  58]]
-Node Classification on random seed  4607 -> 0.656
-Confusion Matrix:
- [[ 69   1   3   5   0   9  19]
- [  2 121   4   4   5   5   5]
- [ 30  18 149  26  17  18  35]
- [  7   6  21 106   6  12   8]
- [  0   7   4   2  59   3   0]
- [  2   0   1   5   0  65   9]
- [ 12   2   9   3   4  15  87]]
-Node Classification on random seed  4608 -> 0.655
-Confusion Matrix:
- [[ 61   4   5   5   9   9  11]
- [  4 130   8   3   3   9   5]
- [ 23  12 195  21  14  10  52]
- [  4   6  17  99   3   3  19]
- [  1   9   7   3  56   0   3]
- [  0   6   2   0   0  49   6]
- [  9   3  12   0   8  17  65]]
-Node Classification on random seed  4609 -> 0.66
-Confusion Matrix:
- [[ 84   3   5   2   0   7  10]
- [  3 135   4   1  10   2   6]
- [ 15  13 163  11  28  18  46]
- [ 10   4  21  97   8   6  16]
- [  0  11   5   1  61   1   7]
- [ 12   1   0   1   0  48   6]
- [ 10   3   7   5   6  15  72]]
-Node Classification on random seed  4610 -> 0.61
-Confusion Matrix:
- [[ 87   0   3   8   7   7   5]
- [  2 127   7   2   6   2   4]
- [ 19  26 129  35  31  29  21]
- [  9   3  24 108   7   4  13]
- [  1   5   3   1  65   2   1]
- [  3   1   1   1   0  40   6]
- [ 21   3  11  23  10  23  54]]
-Node Classification on random seed  4611 -> 0.58
-Confusion Matrix:
- [[ 65   8   6   2   6  19   4]
- [  4 115   7   5   2   7   6]
- [ 17  23 134  56  23  16  34]
- [ 31   1  11  96   9  10   5]
- [  2   5   4   2  72   0   1]
- [ 10   2   9   4   2  33   4]
- [ 12   3  10  13   5  20  65]]
-Node Classification on random seed  4612 -> 0.626
-Confusion Matrix:
- [[ 57   4  11   8   1   2  11]
- [  6 131   7   3   9   1   3]
- [ 24  20 162  36  16  29  23]
- [ 16   3  27  97   6   4   8]
- [  0   5   7   2  65   0   1]
- [  8   0   2   5   0  42   8]
- [ 11   6   7  14   3  17  72]]
-Node Classification on random seed  4613 -> 0.631
-Confusion Matrix:
- [[ 73   2   1  10   3   4  13]
- [  7 139   3   0   7   0   5]
- [ 24  18 136  17  38  20  53]
- [  8   7  27 114   3   5  10]
- [  0   5   2   1  68   1   1]
- [  4   2   4   5   0  44   7]
- [  5   1   5  21   8  12  57]]
-Node Classification on random seed  4614 -> 0.62
-Confusion Matrix:
- [[ 64   3   4   4   4  13  11]
- [  6 142   2   3  11   2   2]
- [ 32  22 148  25  21  35  40]
- [ 20   4  16  90   4   5  17]
- [  1   7   3   1  62   2   3]
- [  8   0   4   0   1  35   6]
- [  8   1   9   5   4  11  79]]
-Node Classification on random seed  4615 -> 0.579
-Confusion Matrix:
- [[ 60   1   7   7   4  11   7]
- [  1 118   7   4  11   4   2]
- [ 20  27 121  54  43   8  34]
- [  4   6  20  95   7  11  22]
- [  0   4   4   2  66   0   4]
- [  8   2   2   1   3  46  11]
- [ 15   7  12  10   6   8  73]]
-Node Classification on random seed  4616 -> 0.572
-Confusion Matrix:
- [[ 64   8   2   1   1  20   9]
- [  2 141   4   5   5   4   1]
- [ 32  16 121  45  27  18  51]
- [ 21  10   6  85   6  14  19]
- [  2  14   2   5  50   0   1]
- [  6   4   9   0   0  47   6]
- [ 17   4   9   4   8  10  64]]
-Node Classification on random seed  4617 -> 0.639
-Confusion Matrix:
- [[ 79   3   3  11   1   4   7]
- [  3 124   7   3  20   0   0]
- [ 20  14 158  29  22  25  34]
- [  8   3  16 109   4   5  24]
- [  3   3   4   3  52   0   2]
- [  9   0   1   1   1  44   7]
- [ 23   0   7   5   7  19  73]]
-Node Classification on random seed  4618 -> 0.64
-Confusion Matrix:
- [[ 83   5   2   9   6   7  18]
- [  4 125   5   5   5   0   8]
- [ 25  17 144  29  19  16  38]
- [ 12   3  11 116   3   8   8]
- [  1  11   2   0  50   3   3]
- [ 10   4   4   1   1  43   6]
- [ 15   6   6   6   5  13  79]]
-Node Classification on random seed  4619 -> 0.594
-Confusion Matrix:
- [[ 69   2   1   8   1   8   9]
- [  2 126   6   1   7   4   7]
- [ 19  24 121  35  62  27  45]
- [ 10   0  18  96   5   7  14]
- [  1   5   6   1  54   1   2]
- [  2   1   1   2   1  53   4]
- [  9   3  15  10  10  10  75]]
-Node Classification on random seed  4620 -> 0.62
-Confusion Matrix:
- [[ 71   1   6   9   4  12   4]
- [  2 120   9   4   9   5   1]
- [ 38   6 153  18  28  24  44]
- [ 10   4  18 101  12   5  15]
- [  3   6   6   1  51   0   7]
- [  4   0   0   0   3  55  11]
- [ 12   2   7   9   8  13  69]]
-Node Classification on random seed  4621 -> 0.598
-Confusion Matrix:
- [[ 67   1   3   8   5  14   7]
- [ 10 103   4   7   4   6   9]
- [ 27  14 135  41  36  15  27]
- [ 17   4  16 110  12   8   9]
- [  0   6   3   3  73   1   2]
- [ 10   2   1   0   0  48  11]
- [ 13   3  11  17   4  11  62]]
-Node Classification on random seed  4622 -> 0.631
-Confusion Matrix:
- [[ 61  11   3   5   4   4  14]
- [  4 126   7   4   6   0  10]
- [ 26  23 151  34  28  13  27]
- [  5   6  30  96   5   4   5]
- [  0  11   1   3  67   1   2]
- [  9   0   4   0   1  52   7]
- [ 10   1  19   5   6  11  78]]
-Node Classification on random seed  4623 -> 0.615
-Confusion Matrix:
- [[ 72   6   4   4   4   8   4]
- [  5 127   0   1  15   3  16]
- [ 25  23 150  26  21  36  22]
- [  9   4  23  96   5  10  12]
- [  2   2   4   1  59   3   1]
- [  7   2   3   2   0  41   2]
- [ 16   1  15  13   8  17  70]]
-Node Classification on random seed  4624 -> 0.6
-Confusion Matrix:
- [[ 60   9   6   4   3  17   8]
- [  9 130   5   0   7   2   4]
- [ 21  22 137  42  25  20  55]
- [ 13  11  13 107   2   7  24]
- [  5   7   1   1  50   1   5]
- [  2   1   4   0   2  41   1]
- [ 12   5   4   1   7  12  75]]
-Node Classification on random seed  4625 -> 0.595
-Confusion Matrix:
- [[ 88   1   0   3   5   7  13]
- [  5 120   4   6   4   7   1]
- [ 14  15 108  60  40  21  55]
- [ 18   0   8 106   8   5  12]
- [  2   7   4   3  52   2   1]
- [ 17   0   0   2   2  33   7]
- [ 15   4   7   5   3  12  88]]
-Node Classification on random seed  4626 -> 0.63
-Confusion Matrix:
- [[ 76   4  10   4   1  13   6]
- [  3 111   5   3   6   1   4]
- [ 17  12 146  34  30  26  56]
- [ 17   0  10 107   6   6  17]
- [  3   8   4   3  55   1   4]
- [  5   0   0   2   0  52   2]
- [  8   3  10   7   4  15  83]]
-Node Classification on random seed  4627 -> 0.584
-Confusion Matrix:
- [[ 59   2   7   7   4   7  15]
- [  7 115   4   7  12   7   7]
- [ 19  15 121  48  56  26  39]
- [  7   4   6  96  10   6  12]
- [  4   3   3   0  75   1   0]
- [  6   0   6   0   2  49   1]
- [ 12   5   7   5  16  11  69]]
-Node Classification on random seed  4628 -> 0.62
-Confusion Matrix:
- [[ 79   2   1   3   3   8   7]
- [  4 129   6   6   2   1   1]
- [ 32  23 142  27  29  20  39]
- [ 13   5  14  93   7   9  11]
- [  0   7   2   0  62   2   3]
- [  7   3   1   1   0  49   7]
- [ 23   5  11  15  10  10  66]]
-Node Classification on random seed  4629 -> 0.606
-Confusion Matrix:
- [[ 80   3   1   0   5   8   4]
- [  7 115   9   2  11  10   3]
- [ 28  36 138  26  21  28  46]
- [ 10   1  24  95   4  12   7]
- [  1   4   3   7  65   3   2]
- [  1   3   4   0   1  36  10]
- [  4   5   6   4  13  17  77]]
-Node Classification on random seed  4630 -> 0.563
-Confusion Matrix:
- [[ 58   4   4   8   4   7   2]
- [  8 121   4   7   7   6   4]
- [ 28  18 140  49  24  28  29]
- [ 31   1  21  85  10  11   5]
- [  1  11   2   3  61   0   2]
- [  3   1   6   5   4  45   1]
- [ 25   3  16  10   5  19  53]]
-Node Classification on random seed  4631 -> 0.664
-Confusion Matrix:
- [[ 80   2   4   8   4   5  12]
- [  1 132   3   3  11   4   6]
- [ 30  27 150  30  18  15  42]
- [ 15   2  14 115   6   5  10]
- [  1   4   2   0  69   0   1]
- [  0   0   2   3   0  41   5]
- [  8   3   8   8   7   7  77]]
-Node Classification on random seed  4632 -> 0.578
-Confusion Matrix:
- [[ 57   3   4   4   3  14  16]
- [  4 130  12   7   6   2   2]
- [ 29  16 115  41  44  25  39]
- [  8   5  13  95  11   8  16]
- [  2   6   4   3  56   1   4]
- [  3   3   1   0   3  55   4]
- [ 16   3  11   7   4  15  70]]
-Node Classification on random seed  4633 -> 0.622
-Confusion Matrix:
- [[ 75   2   7   2   0   9  22]
- [  2 133   6   4  11   1  12]
- [ 33  25 133  37  25  16  31]
- [ 12   1  10 129   2   4   9]
- [  2   6   5   3  57   1   3]
- [  7   0   7   0   1  40   2]
- [ 11   4   6   6   9  22  55]]
-Node Classification on random seed  4634 -> 0.58
-Confusion Matrix:
- [[ 61   1   3  10   4  16  15]
- [  7 127   3   7   9   9   3]
- [ 31  15 155  29  25  33  27]
- [ 30   5  19  65   3   4  11]
- [  4   6   0   0  68   1   4]
- [ 13   2   3   5   3  34   5]
- [ 16   5   5   7   8  14  70]]
-Node Classification on random seed  4635 -> 0.59
-Confusion Matrix:
- [[ 71   4   2   8   7  12   5]
- [ 13 115   3   4   9   6   8]
- [ 17  20 138  18  33  17  63]
- [  8  10  20 106   0   5   7]
- [  1   8   1   1  47   0   3]
- [  6   6   8   0   0  46   7]
- [ 19   2  10  13   9  17  67]]
-Node Classification on random seed  4636 -> 0.623
-Confusion Matrix:
- [[ 67   1   2   7   4  14  22]
- [  0 134  13   1   4   4   5]
- [ 40  15 162  25  14  27  30]
- [  8   4  13  83   7   8  27]
- [  1  11   4   1  62   0   3]
- [  2   2   5   4   1  33   5]
- [  2   2  16   8   6   9  82]]
-Node Classification on random seed  4637 -> 0.655
-Confusion Matrix:
- [[ 78   5   6   4   5  16   4]
- [  3 134   7   1   5   0   4]
- [ 25  12 168  32  21  16  41]
- [ 12   4   8 105   1   6  12]
- [  0   6   9   0  48   0   3]
- [  8   0   5   1   1  51   3]
- [ 11   5   4   5   9  25  71]]
-Node Classification on random seed  4638 -> 0.625
-Confusion Matrix:
- [[ 62   2   3   6   6  10   6]
- [  4 127   1   5   4   5   3]
- [ 28   8 150  31  39  17  43]
- [ 12   2  18 103   2   8  16]
- [  2   3   3   6  68   0   2]
- [  5   2   1   7   2  41   6]
- [  7   4   3   8  13  22  74]]
-Node Classification on random seed  4639 -> 0.618
-Confusion Matrix:
- [[ 79   3   2   4   3   6  17]
- [  7 125   6   2   7   4   1]
- [ 25  16 135  30  22  22  52]
- [ 10   3  14 105   5  10  23]
- [  1   6   4   0  50   1   6]
- [  4   3   2   1   1  49  10]
- [ 17   2   8   5   4  13  75]]
-Node Classification on random seed  4640 -> 0.586
-Confusion Matrix:
- [[ 71   5   3   4   1   8  10]
- [  6 121   3   2  12   4   2]
- [ 26  35 131  27  25  19  51]
- [  8   7  18  86  12   8  13]
- [  4  10   4   1  61   0   3]
- [ 12   7   6   1   0  45   7]
- [ 11   1   8  11   3  16  71]]
-Node Classification on random seed  4641 -> 0.627
-Confusion Matrix:
- [[ 69   3   1   4   7   9  11]
- [  3 130   8   3  12   1   0]
- [ 25  19 132  24  50  23  25]
- [ 12   1  20 119   5   5  15]
- [  2   6   3   0  69   1   2]
- [  1   0   0   0   1  44   6]
- [ 11   8   8   6   8  24  64]]
-Node Classification on random seed  4642 -> 0.583
-Confusion Matrix:
- [[ 74   6   1   4   2  10  12]
- [  3 125   4   2   8   0  10]
- [ 26  22 115  25  55  27  58]
- [ 19   8  15  88   4   2  17]
- [  1   8   4   1  54   0   6]
- [  3   4   5   0   0  38   7]
- [ 10   2   5   8   4   9  89]]
-Node Classification on random seed  4643 -> 0.611
-Confusion Matrix:
- [[ 64   2   6   5   4  27   5]
- [  5 121   6   2  15   6   3]
- [ 13  19 147  36  27  28  45]
- [  8   4   7 106   6  13  10]
- [  1   5   5   4  52   1   1]
- [  5   0   3   3   2  54   1]
- [  9   3  10   6   7  21  67]]
-Node Classification on random seed  4644 -> 0.627
-Confusion Matrix:
- [[ 79   4  13   3   1   9   4]
- [  7 121   4   1   6   4   1]
- [ 24  30 141  23  32  15  59]
- [  4   6  11 113   5   6  14]
- [  1   4   2   1  49   2   3]
- [  4   2   4   2   0  48   6]
- [  2   5  17   7   6  19  76]]
-Node Classification on random seed  4645 -> 0.603
-Confusion Matrix:
- [[ 60   3   3   2   3  15  18]
- [  4 135   5   3   4   1   3]
- [ 34  22 137  25  38  24  39]
- [ 16   3  13  94   5   8  17]
- [  2   9   0   3  53   1   3]
- [  2   3   1   1   0  49   2]
- [  2   8  14   3   9  26  75]]
-Node Classification on random seed  4646 -> 0.596
-Confusion Matrix:
- [[ 64   4   5   8   5  12   6]
- [  6 133   7   3  13   0   9]
- [ 19  12 141  44  34  29  35]
- [ 16   0  24  87   8  11   6]
- [  2   2   6   1  61   3   0]
- [  5   2   6   1   3  38   4]
- [ 14   3   3  11   8  14  72]]
-Node Classification on random seed  4647 -> 0.583
-Confusion Matrix:
- [[ 80   2   3   5   1  19   6]
- [  4 123   8   8   3   4   7]
- [ 37  25 116  42  18  30  41]
- [ 23   5  14  95  10   7  10]
- [  0   4   0   2  58   2   6]
- [ 12   2   2   0   0  49   1]
- [ 12   3  11   7   6  15  62]]
-Node Classification on random seed  4648 -> 0.62
-Confusion Matrix:
- [[ 88   1   4   4   3   5   4]
- [  2 136   4   1   3   4   2]
- [ 21  22 125  31  28  23  52]
- [ 18   4  19  84   7   9  18]
- [  0   8   1   4  61   2   2]
- [  7   1   2   1   4  42   9]
- [ 20   2  12   3   7   6  84]]
-Node Classification on random seed  4649 -> 0.59
-Confusion Matrix:
- [[ 79   1   1   4   1  10   5]
- [  5 123   9   3   1   3   8]
- [ 31  51 122  28  23  24  45]
- [ 14   5  15  99   3   8  14]
- [  2  10   4   3  57   2   1]
- [  7   5   4   2   0  40   3]
- [ 18   1  12   6   7  11  70]]
-Node Classification on random seed  4650 -> 0.618
-Confusion Matrix:
- [[ 65   4   8   5   5  11   4]
- [  3 130   3   0   9   4   5]
- [ 16  27 114  41  32  43  32]
- [ 10   5  12 120   9  10   5]
- [  0   5   2   1  55   0   1]
- [  7   1   4   0   1  44   9]
- [  9   0  16   4   4  15  90]]
-Node Classification on random seed  4651 -> 0.592
-Confusion Matrix:
- [[ 71   2   2   5   5  18   7]
- [  1 124   6   8   3   3   7]
- [ 22  25 120  58  26  22  46]
- [ 17   5   8 114   6   8  21]
- [  3   4   4   0  46   3   2]
- [  2   0   2   1   0  54   7]
- [  7   0   5  13   8  16  63]]
-Node Classification on random seed  4652 -> 0.643
-Confusion Matrix:
- [[ 68   4   3   4   4   5  10]
- [  9 132   6   3   4   0   6]
- [ 15  29 152  47  23  23  44]
- [ 14   2  11  95   2   6   6]
- [  1   7   3   2  71   1   1]
- [  5   2   2   0   0  41   6]
- [ 14   6   9   3   5  10  84]]
-Node Classification on random seed  4653 -> 0.587
-Confusion Matrix:
- [[ 74   3   4  12   4   9   7]
- [ 13 133   7   4   8   0   5]
- [ 11  33 132  48  52  17  20]
- [ 12   1  12  94  10   7  15]
- [  2   5   0   4  56   0   1]
- [  5   4   1   5   1  34   6]
- [ 11   3  12  16   8  15  64]]
-Node Classification on random seed  4654 -> 0.636
-Confusion Matrix:
- [[ 87   1   4   7   5   2   7]
- [  7 125   2   1   5   0   5]
- [ 21  26 131  42  31  24  31]
- [  6   3  20 127   1   3  14]
- [  1  17   0   5  56   1   2]
- [ 12   0   0   1   1  32   4]
- [ 18   2   0  16   6  10  78]]
-Node Classification on random seed  4655 -> 0.625
-Confusion Matrix:
- [[ 69   4   2   7   8  10   8]
- [  4 127   3   1  13   1   5]
- [ 18  19 163  22  18  27  60]
- [ 11   5  20  92   3   7   9]
- [  3   3   5   2  59   2   4]
- [ 12   0   3   1   1  45   5]
- [ 10   5   3   2   4  25  70]]
-Node Classification on random seed  4656 -> 0.627
-Confusion Matrix:
- [[ 81   7   3   2   4  11   6]
- [  5 128   4   3  12   2   6]
- [ 24  30 165  19  30  24  38]
- [ 10   8  12  89   4  11  13]
- [  0   8   1   4  57   2   3]
- [  8   1   1   1   0  41   7]
- [ 17   5   2   3   5  17  66]]
-Node Classification on random seed  4657 -> 0.584
-Confusion Matrix:
- [[ 72   1   4   4   2  16   8]
- [  1 123   2   4  10   0   7]
- [ 35  15 127  27  36  28  43]
- [ 25   4   9  87   6   7  15]
- [  1   8   8   2  59   2   2]
- [  7   3   7   5   1  38   4]
- [ 10   3  12  10   0  22  78]]
-Node Classification on random seed  4658 -> 0.641
-Confusion Matrix:
- [[ 67   1   6   1   5  13  22]
- [  5 115   1   1   8   4   7]
- [ 24  16 146  31  25  13  50]
- [  9   1  23 115   0   3  14]
- [  4   3   6   1  67   1   3]
- [  9   0   1   6   0  35   7]
- [  8   3   7   4   7   6  96]]
-Node Classification on random seed  4659 -> 0.611
-Confusion Matrix:
- [[ 76   4   6  12   2   9  11]
- [  3 126  10   0   8   5   4]
- [ 20  28 147  30  28  14  41]
- [ 14   4  13  90  11   4  15]
- [  3   7   1   2  54   1   2]
- [  6   2   1   2   2  36   8]
- [ 20  11   1   8   5  11  82]]
-Node Classification on random seed  4660 -> 0.603
-Confusion Matrix:
- [[ 67   3   8   4   6   7   9]
- [  4 131   4   1  12   1   3]
- [ 28  22 149  29  31  21  41]
- [ 10   4  13  96  16   7  13]
- [  0   4   5   2  67   2   0]
- [ 10   5   0   1   2  34  10]
- [ 18   4   8   8  10  11  59]]
-Node Classification on random seed  4661 -> 0.649
-Confusion Matrix:
- [[ 81   4   5   2   6   9  11]
- [  2 115   3   3   8   7   6]
- [ 27  17 173  21  29  21  34]
- [ 12   6  12 108   7   4  15]
- [  1   5   4   1  67   1   6]
- [  7   1   4   3   1  40   4]
- [  6   5   7   5   5  14  65]]
-Node Classification on random seed  4662 -> 0.638
-Confusion Matrix:
- [[ 76   3   0   4   6   7   4]
- [  3 123   4   4  15   8   3]
- [ 20  19 158  39  26  22  34]
- [  8  10  12 111   7   3  10]
- [  0   4   4   0  62   0   1]
- [ 10   2   1   4   0  50   4]
- [ 11   8   4   8  13  17  58]]
-Node Classification on random seed  4663 -> 0.637
-Confusion Matrix:
- [[ 77   0   6   2   5  11   4]
- [  3 128   8   2   9   2   7]
- [ 26  17 138  33  25  19  55]
- [ 13   2   8 115   4   5  12]
- [  1   9   2   2  53   2   2]
- [  3   0   2   6   1  50   6]
- [  5   2   4   8   9  21  76]]
-Node Classification on random seed  4664 -> 0.614
-Confusion Matrix:
- [[ 70   1   2   7   1  23  14]
- [  3 127   9   4   3   1   6]
- [ 31  17 135  34  11  26  55]
- [  2   3  14 111   9  14   9]
- [  3  11   5   0  49   0   3]
- [  5   1   1   0   0  46   4]
- [ 11   4   4  19   0  16  76]]
-Node Classification on random seed  4665 -> 0.603
-Confusion Matrix:
- [[ 70   4   0   5   5  21   3]
- [  3 119   6   8   4   1   3]
- [ 21  16 129  36  51  15  41]
- [  9   4  11  90  11  13   9]
- [  0   5   5   1  70   3   0]
- [  6   2   1   2   1  42  11]
- [ 15   5  10   2   8  20  83]]
-Node Classification on random seed  4666 -> 0.647
-Confusion Matrix:
- [[ 70   1   1   8   7  12  14]
- [ 11 139   3   2   7   0   1]
- [ 21  17 137  30  18  28  38]
- [  4   1  17 120   2   3  11]
- [  3   7   3   9  55   0   3]
- [  2   3   3   1   4  52   6]
- [ 17   4   8   9   5   9  74]]
-Node Classification on random seed  4667 -> 0.619
-Confusion Matrix:
- [[ 74   4   6   4   4  12   6]
- [  4 126  10   4   4   0   2]
- [ 38  19 163  37  23  12  40]
- [  7   4  18  97   2   7  18]
- [  1  11   2   1  59   0   3]
- [  6   1   2   0   2  39   4]
- [ 11   4  20   3  11  14  61]]
-Node Classification on random seed  4668 -> 0.589
-Confusion Matrix:
- [[ 39   3   2  13   4  26  10]
- [ 16 137   5   1   5   4   0]
- [ 18  22 114  37  60  21  43]
- [  7   1  26 105   8   4   9]
- [  1   6   6   4  47   2   1]
- [  0   4   0   1   1  50   6]
- [  6   2   5   4   4  13  97]]
-Node Classification on random seed  4669 -> 0.622
-Confusion Matrix:
- [[ 61   6   8   8   3  11   3]
- [  8 122   9   1  14   4   3]
- [ 19  15 160  43  15  39  28]
- [  2   2  21  99   4   3  21]
- [  0   4   6   2  60   4   4]
- [  9   3   3   1   0  41   5]
- [  9   1   3   6  10  18  79]]
-Node Classification on random seed  4670 -> 0.578
-Confusion Matrix:
- [[ 77   3   8   2   2   6  14]
- [  8 101  10   0  13   5   2]
- [ 34  32 125  30  45  15  32]
- [ 10   3  11 112   4   4  11]
- [  3   7   4   4  56   1   2]
- [  6   2   3   0   3  50   5]
- [  8  14  12  22   6  16  57]]
-Node Classification on random seed  4671 -> 0.619
-Confusion Matrix:
- [[ 75   7   7   5   2  10   2]
- [  1 119   4   0   3   8   4]
- [ 27  12 127  40  47  24  35]
- [ 16  11  13 111   4  10   3]
- [  3   9   4   0  66   2   1]
- [  4   3   1   2   0  58   1]
- [ 13   4  10   6   7  16  63]]
-Node Classification on random seed  4672 -> 0.615
-Confusion Matrix:
- [[ 92   1   1   9   2   7   7]
- [  4 104   2   3  15  11   5]
- [ 30  18 159  38  17  22  41]
- [ 18   4  15  79   8   6  12]
- [  1   2   8   3  65   0   2]
- [  2   1   3   9   1  49   4]
- [ 12   7  11   5   7  11  67]]
-Node Classification on random seed  4673 -> 0.619
-Confusion Matrix:
- [[ 55   5   3  10   1  15  16]
- [  3 122   7   4  15   6   3]
- [ 18  27 179  30  21  22  31]
- [  5   7  19  99   2   5   6]
- [  1   5   7   7  66   0   1]
- [  8   5   1   3   0  33   3]
- [ 16   4   6  13   6  14  65]]
-Node Classification on random seed  4674 -> 0.631
-Confusion Matrix:
- [[ 54   3   1  12   3  20  12]
- [  4 129   2   6   3   3   5]
- [ 31  25 152  35  21  25  24]
- [  9   7  15 100   5   3  19]
- [  1   3   5   3  66   1   1]
- [  8   4   1   4   0  47   2]
- [ 10   3   5  10   5  10  83]]
-Node Classification on random seed  4675 -> 0.598
-Confusion Matrix:
- [[ 74   4   6  11   2  11   9]
- [  3 138  10   1   3   2   4]
- [ 23  21 152  27  25  14  40]
- [ 20   9  13  75  17  11  10]
- [  1   8   2   0  44   6   0]
- [  6   1   4   1   2  37   8]
- [ 18  10   4  10   7  18  78]]
-Node Classification on random seed  4676 -> 0.597
-Confusion Matrix:
- [[ 74   6   4  11   6   7   7]
- [  3 108  17   1  10   3   3]
- [ 27  24 123  27  26  28  56]
- [ 10   9   6 103   6   7  18]
- [  0   5   4   1  58   0   2]
- [  7   0   2   3   1  43   8]
- [ 18   2   3   6   7  12  88]]
-Node Classification on random seed  4677 -> 0.614
-Confusion Matrix:
- [[ 73   6   4   3   2   6   8]
- [  3 138   2   6   5   2   2]
- [ 21  29 141  22  22  16  49]
- [  4   6  23  92   7   5  26]
- [  2  11   3   4  57   0   7]
- [  6   1   3   4   1  43   4]
- [  9  10   9   1  11  21  70]]
-Node Classification on random seed  4678 -> 0.588
-Confusion Matrix:
- [[ 80   1   0   9   3   8   8]
- [  8 107  11   3  10  10   1]
- [ 36  19 145  26  42  15  36]
- [  8  11  11 111   4   3  19]
- [  1   4   9   1  55   0   3]
- [ 11   0   2   2   2  27   9]
- [ 16   1  16  12  17   4  63]]
-Node Classification on random seed  4679 -> 0.597
-Confusion Matrix:
- [[ 76   1   1   3   2  14   7]
- [  2 132  19   3   3   7   0]
- [ 21  27 130  49  19  25  33]
- [ 15  10  16  86  10  13  13]
- [  1   6  10   0  50   0   1]
- [  9   1   2   3   0  46   4]
- [ 10   6  15   3   6  13  77]]
-Node Classification on random seed  4680 -> 0.612
-Confusion Matrix:
- [[ 57   6  18   5   3  11   9]
- [  1 127   2   2  10   1  12]
- [ 23  16 134  53  22  22  35]
- [ 16   8   6 113   6   4  10]
- [  0   4   3   3  63   0   3]
- [  2   4   5   3   6  37   7]
- [  3   4  21   6   2  11  81]]
-Node Classification on random seed  4681 -> 0.621
-Confusion Matrix:
- [[ 69   2   6   3   2  15   5]
- [  2 146   4   1   6   3   2]
- [ 22  29 155  30  22  22  45]
- [ 10   0  15  88   8   5  29]
- [  2  10   5   2  46   1   0]
- [  3   2   3   0   3  41   3]
- [  5   2  18   6   9  17  76]]
-Node Classification on random seed  4682 -> 0.59
-Confusion Matrix:
- [[ 48   6   5   4   5  26  11]
- [  3 129   6   0   7   4   2]
- [ 30  24 147  31  15  28  43]
- [ 18   4  12  93  12  12  17]
- [  0   8   2   1  56   1   4]
- [  7   2   2   0   1  51   4]
- [  7   6  12   9   4  15  66]]
-Node Classification on random seed  4683 -> 0.63
-Confusion Matrix:
- [[ 89   0   1   9   3   8  10]
- [  2 143   2   4   7   3   3]
- [ 15  22 145  48  29  16  34]
- [  9   7  10  83   6  16  13]
- [  1   5   4   1  58   0   4]
- [  5   2  13   2   1  38   1]
- [  7   7   4  11   9  16  74]]
-Node Classification on random seed  4684 -> 0.664
-Confusion Matrix:
- [[ 95   5   1   2   5   6   8]
- [  2 148   6   1   2   3   2]
- [ 33  16 125  50  19  16  38]
- [ 11   4  14 117   4   6   7]
- [  1   5   4   1  59   1   4]
- [  5   0   2   2   1  44   8]
- [ 10   0   5   7  10   9  76]]
-Node Classification on random seed  4685 -> 0.611
-Confusion Matrix:
- [[ 70   2   3   9   2  19   4]
- [  4 124  10   3   7   3   6]
- [ 24  26 143  50  11  31  36]
- [  7   2   5 113   7   6   9]
- [  6   2   7   2  53   0   2]
- [  7   1   1   6   1  37   6]
- [ 15   2   9   9   3  24  71]]
-Node Classification on random seed  4686 -> 0.633
-Confusion Matrix:
- [[ 70   4   3   3   2  11  12]
- [ 10 107   7   5  11   7   3]
- [ 22  23 148  28  36   9  51]
- [  6   8  13 107   8   4   9]
- [  0   4   4   1  67   0   1]
- [  8   4   2   0   0  43   3]
- [  7   1  16   6   7   8  91]]
-Node Classification on random seed  4687 -> 0.644
-Confusion Matrix:
- [[ 72   4   3   1   6  13   7]
- [  2 145   7   1   2   3   6]
- [ 24  28 129  42  24   7  46]
- [ 15   1  14 101   4   4  16]
- [  0   8   4   0  69   3   4]
- [  9   1   1   3   0  42   5]
- [  4   3   7   3   4  17  86]]
-Node Classification on random seed  4688 -> 0.618
-Confusion Matrix:
- [[ 64   4  10   7   3   4   4]
- [  4 114   9   0   9   6   3]
- [ 26  24 147  31  31  23  33]
- [ 13   3  10 118  11   7  19]
- [  3   4   2   2  60   1   9]
- [  6   0   2   0   2  49   2]
- [ 18   4   9   8   9   7  66]]
-Node Classification on random seed  4689 -> 0.626
-Confusion Matrix:
- [[ 78   2   2   3   5   9   6]
- [  3 129   4   0  10   5   8]
- [ 17  22 137  41  25  23  37]
- [  2   3  16 104   2   5  20]
- [  1   7   5   2  66   1   1]
- [  7   1   1   3   3  50   3]
- [ 15   5   7   6  14  22  62]]
-Node Classification on random seed  4690 -> 0.624
-Confusion Matrix:
- [[ 62   2   1   2   9  12   8]
- [  4 117   5   1   9   5   3]
- [ 24  25 169  26  26  22  53]
- [  9   3  20 104   4   7  16]
- [  0   1   2   0  64   0   2]
- [  4   0   5   1   2  36   5]
- [ 19   2   8   7  10  12  72]]
-Node Classification on random seed  4691 -> 0.644
-Confusion Matrix:
- [[ 79   9   6   6   4  17   2]
- [  2 144   0   1   7   1   6]
- [ 16  17 146  42  22  17  38]
- [  8   1  12 106   1  16   9]
- [  3   8   5   0  62   1   0]
- [ 12   4   1   2   0  41   5]
- [ 11   9   4   9   3  19  66]]
-Node Classification on random seed  4692 -> 0.653
-Confusion Matrix:
- [[ 68   2   4   6   3   5  12]
- [  7 119   4   3   6   0   8]
- [ 28  33 149  27  40  13  38]
- [  7   3  11 120   3   1  14]
- [  0   7   1   2  58   1   4]
- [  3   1   3   0   4  48   6]
- [  8   1   5   7   8   8  91]]
-Node Classification on random seed  4693 -> 0.609
-Confusion Matrix:
- [[ 85   2   5   6   2  19   2]
- [ 10 116   2   3   9   1   3]
- [ 27  26 108  42  23  24  37]
- [ 12   3  11  93  14  16  13]
- [  0   4   3   2  67   0   1]
- [  4   1   1   2   0  46   8]
- [ 13   4   4   7   7  18  94]]
-Node Classification on random seed  4694 -> 0.628
-Confusion Matrix:
- [[ 72   1   3   3   7  15  11]
- [  4 125  12   0  13   1   1]
- [ 11  23 172  29  23  10  42]
- [ 24   0  13  73  14  10  16]
- [  0   6   2   2  55   2   4]
- [  5   2   2   1   1  48   5]
- [ 12   3   8  11   5  15  83]]
-Node Classification on random seed  4695 -> 0.646
-Confusion Matrix:
- [[ 73   3   5   4   3  17   7]
- [ 16 119   6   2   5   4   3]
- [ 20   8 184  14  21  24  40]
- [  8   2  24 100   1  11  13]
- [  1   4   3   5  61   2   2]
- [  4   2   1   6   1  43   2]
- [ 12   0  12   7   7  22  66]]
-Node Classification on random seed  4696 -> 0.593
-Confusion Matrix:
- [[ 74   3   5   1   5  17   7]
- [  3 132   6   3  11   3   8]
- [  8  20 126  38  43  39  42]
- [ 16   5  25  85   9   4   6]
- [  0   4   6   7  50   1   2]
- [  7   0   0   3   3  40   3]
- [  9   2   6   5   8  14  86]]
-Node Classification on random seed  4697 -> 0.585
-Confusion Matrix:
- [[ 65   4   5   7   2  12   8]
- [  4 132  11   0   7   0   3]
- [ 34  28 120  41  34  25  32]
- [ 16   4  14 103   5   3   9]
- [  2  10   4   0  58   0   2]
- [ 11   2   9   3   1  38   5]
- [ 10  12   9  10   4  13  69]]
-Node Classification on random seed  4698 -> 0.608
-Confusion Matrix:
- [[ 64   6   0   6   5  18   8]
- [  9 115   4   7   3   8   5]
- [ 39   6 136  43  18  19  39]
- [  8   1  10 118   7   8  24]
- [  3   3   4   2  64   1   1]
- [  3   1   4   0   1  40   8]
- [ 13   2   8   4  12  21  71]]
-Node Classification on random seed  4699 -> 0.613
-Confusion Matrix:
- [[ 70   2   4   6   3   8  12]
- [  3 136   9   4   3   2   6]
- [ 39  39 133  32  15  10  35]
- [ 22   3  23 101   1   5  14]
- [  0   9   5   0  47   5   3]
- [  1   1   2   0   1  46   6]
- [ 16   6  15   3   7   7  80]]
-Node Classification on random seed  4700 -> 0.615
-Confusion Matrix:
- [[ 72   3   4   7   7  11   7]
- [  8 127  10   2  10   4   4]
- [ 27  26 130  48  29  18  24]
- [ 11   1  13 111  11   8   6]
- [  3   4   2   2  53   1   0]
- [  7   3   5   3   0  43   5]
- [ 14   4  12   5   3  13  79]]
-Node Classification on random seed  4701 -> 0.604
-Confusion Matrix:
- [[ 73   0  11   1   1  16   2]
- [  3 127   7   1   4   3   2]
- [ 24  19 147  24  24  40  42]
- [ 14   3  26 110   8  13  16]
- [  1   7   4   1  50   0   1]
- [ 10   3   4   3   0  38   6]
- [  8   3   8   5   7  21  59]]
-Node Classification on random seed  4702 -> 0.567
-Confusion Matrix:
- [[ 85   4   5   1   2   7   6]
- [ 13 115   2   3   6   0   0]
- [ 25  45  81  61  41  22  30]
- [ 15   8  25  89   2   7  20]
- [  3   7   1   2  72   0   1]
- [  3   4   3   2   0  53   2]
- [  8   6  12  10   6  13  72]]
-Node Classification on random seed  4703 -> 0.635
-Confusion Matrix:
- [[ 74   1   3   5   8  17  10]
- [  0 116  10   9   5   5   2]
- [  5  29 159  29  52   6  32]
- [ 17   6  23  86   3   3   7]
- [  0   3   5   0  80   2   2]
- [  7   3   4   1   1  44   7]
- [  6   2   9   6  10  10  76]]
-Node Classification on random seed  4704 -> 0.652
-Confusion Matrix:
- [[ 81   1   1   0   5   5  11]
- [  1 117   9   1  17   4   6]
- [ 23   9 155  30  35  14  45]
- [  9   2   3 117  15   5  17]
- [  0   6   4   0  66   1   4]
- [  5   1   3   1   1  38   4]
- [ 15   4   5   2  17   7  78]]
-Node Classification on random seed  4705 -> 0.621
-Confusion Matrix:
- [[ 64   1   3   4   4  18  12]
- [  5 120   5   1   4   4   3]
- [ 25  27 153  26  26  21  36]
- [ 13   6  14  98   4   6  19]
- [  2   9   2   0  63   5   1]
- [  2   0   0   5   0  46  11]
- [ 10   7   8  10   8  12  77]]
-Node Classification on random seed  4706 -> 0.608
-Confusion Matrix:
- [[ 69   0   7   5   0   6  19]
- [  7 119   9   4   3   1   4]
- [ 20  10 115  30  50  31  43]
- [ 13   5  23 107   5   5  11]
- [  1  12   3   1  59   2   2]
- [  1   1   2   4   0  44   9]
- [  2   5   5  16   4  11  95]]
-Node Classification on random seed  4707 -> 0.651
-Confusion Matrix:
- [[ 81   2   8   1   7   4   3]
- [ 11 125   6   0   8   0   4]
- [ 18  22 179  25  29   5  39]
- [ 12   1  11 100   6   5  17]
- [  4   7   5   0  54   1   4]
- [  4   5  11   1   2  38   8]
- [  5   4  10   9   7  18  74]]
-Node Classification on random seed  4708 -> 0.612
-Confusion Matrix:
- [[ 80   0   5   3   1   9  16]
- [  4 127   5   1   6   0   7]
- [ 25  26 119  40  34  21  40]
- [  9   0   8 121   6   3  14]
- [  0  13   3   2  56   3   2]
- [  6   2   3   3   0  35  16]
- [  9   3  10  12   4  14  74]]
-Node Classification on random seed  4709 -> 0.623
-Confusion Matrix:
- [[ 63   3   8  11   9   7  10]
- [  4 137   5   3   3   6   3]
- [ 15  22 130  32  29  20  49]
- [ 12   6  16 107   5   3   4]
- [  1   9   4   3  59   0   1]
- [  5   1   3   3   1  47   8]
- [  8   3  17   9   5  11  80]]
-Node Classification on random seed  4710 -> 0.607
-Confusion Matrix:
- [[ 66   1   3   9   6   6  10]
- [  5 125   4   1  10   5   1]
- [ 36  19 128  21  25  21  55]
- [ 13   8  12 102   7  15  10]
- [  1   6   2   1  65   0   3]
- [  2   1   5   2   1  49   3]
- [  9   3   4  17   9  21  72]]
-Node Classification on random seed  4711 -> 0.573
-Confusion Matrix:
- [[ 62   2   3   1   2  14   7]
- [  4 128   4   4   2   1   4]
- [ 22  25 123  58  18  19  60]
- [ 19   2  14  84  16  19  11]
- [  0   6   2   2  70   2   2]
- [  3   0   3   7   2  44   6]
- [ 10   2  17  10   9  13  62]]
-Node Classification on random seed  4712 -> 0.628
-Confusion Matrix:
- [[ 73   2   9   6   5   9  14]
- [  2 128  10   1   5   1   2]
- [ 27  19 139  23  36  22  43]
- [  9   6  20 103   3   3  14]
- [  0   6   1   2  60   5   4]
- [  8   2   1   1   1  52   5]
- [ 11   3   7   8   8   8  73]]
-Node Classification on random seed  4713 -> 0.594
-Confusion Matrix:
- [[ 73   2   5   3   8  11  12]
- [  5 129  12  10   9   2   3]
- [ 30   7 149  45  21  21  54]
- [ 20   6  21  93   5   4  11]
- [  0   3   3   0  56   0   3]
- [  7   3   4   5   0  37   5]
- [ 15   2  10   3   5  11  57]]
-Node Classification on random seed  4714 -> 0.637
-Confusion Matrix:
- [[ 78   3   2   6   4   7  17]
- [  5 111  13   3  11   2   7]
- [ 24  15 181  40  20  11  27]
- [  7   8  16 101   8   8  12]
- [  1   4   5   1  56   0   3]
- [  6   3   2   1   0  50   9]
- [ 12   6   7  13   5   9  60]]
-Node Classification on random seed  4715 -> 0.656
-Confusion Matrix:
- [[ 66   6   3   6   3  13  10]
- [  8 122   6   1   9   9   3]
- [ 17  13 183  33  18  15  32]
- [  5   4  14 115   6   4  13]
- [  2   3   4   0  57   0   2]
- [  4   6   4   4   2  42   4]
- [ 17   2  13   4   9  13  71]]
-Node Classification on random seed  4716 -> 0.611
-Confusion Matrix:
- [[ 64   4   5   4   6  16   5]
- [  3 126   4   7   8   1  10]
- [ 28  37 137  24  23  17  38]
- [ 15  10   6  97   4   8  16]
- [  2   9   5   0  60   1   8]
- [  6   1   2   2   0  46   2]
- [ 14   7   5   4   4  18  81]]
-Node Classification on random seed  4717 -> 0.604
-Confusion Matrix:
- [[ 59   1  13   5  15  13   2]
- [  7 150   3   2   9   5   5]
- [ 39  20 120  22  36  26  41]
- [ 15   4  11 100   6   9   7]
- [  0   4   5   1  61   1   2]
- [  4   1   6   3   2  39   2]
- [ 12   2   5   3   9  18  75]]
-Node Classification on random seed  4718 -> 0.624
-Confusion Matrix:
- [[ 64   4   1   2   5   7  12]
- [  7 115  18   9   7   4   1]
- [ 22  21 128  37  25  35  45]
- [ 11   9   7 111   7  11   7]
- [  0   4   4   0  76   0   5]
- [  3   0   1   2   1  47   3]
- [  2   4  11   8   3  11  83]]
-Node Classification on random seed  4719 -> 0.575
-Confusion Matrix:
- [[ 64   2   9   2   7  13  15]
- [  4 117   5   1  16   2   4]
- [ 19  11 118  22  52  19  53]
- [ 17   2  13 105   8   5  17]
- [  2   3   4   1  62   3   3]
- [ 10   4   2   2   0  46   6]
- [ 14   3  13  15  11  11  63]]
-Node Classification on random seed  4720 -> 0.592
-Confusion Matrix:
- [[ 57   5  11   3   5  25   4]
- [  1 149   2   2   4   7   6]
- [ 12  21 143  45  28  19  33]
- [  7   7  23  77   7  12  16]
- [  1   8   5   1  63   1   1]
- [  6   2   0   3   0  40   6]
- [ 11   2  16  17   7  16  63]]
-Node Classification on random seed  4721 -> 0.605
-Confusion Matrix:
- [[ 83   2   1   6   2  15  12]
- [  3 116   7   2   9   4   2]
- [ 15  17 131  29  41  34  49]
- [ 10   7   3 103  11   6  15]
- [  3   5   5   3  55   6   2]
- [  9   2   0   0   2  41   3]
- [ 10   3   5   4  17  14  76]]
-Node Classification on random seed  4722 -> 0.598
-Confusion Matrix:
- [[ 71   4   4  14   4  12   7]
- [  3 127   0  11   4   6   1]
- [ 28  34 123  36  24  32  25]
- [  4   3  15 105  11   7  12]
- [  3   4   2   4  63   1   4]
- [  9   2   2   4   0  49   0]
- [ 13   3   8  20   3  19  60]]
-Node Classification on random seed  4723 -> 0.621
-Confusion Matrix:
- [[ 68   1   8  15   3  22   3]
- [  4 145  11   6   8   1   2]
- [ 21  15 125  44  12  21  44]
- [  5   1  17 110   7   3   7]
- [  4   3   1   7  58   6   3]
- [  3   2   5   0   2  55   3]
- [  6   5   5  20   4  19  60]]
-Node Classification on random seed  4724 -> 0.643
-Confusion Matrix:
- [[ 81   1   5   6   2   9  16]
- [  5 124   5   1  10   3   8]
- [ 17  18 143  48  22  15  40]
- [ 10   5  11 110   2   9  10]
- [  0   2   5   3  61   2   3]
- [  7   0   3   1   0  44   9]
- [  6   5   4   6  10  13  80]]
-Node Classification on random seed  4725 -> 0.632
-Confusion Matrix:
- [[ 70   1   9   4   7  14  17]
- [  1 111   5   3   7   1   2]
- [ 25  27 163  27  35  24  25]
- [  7   3   4 105   4   8   8]
- [  0   9   4   0  57   3   1]
- [  6   1  10   2   0  41   3]
- [  7   4  15   7  11  17  85]]
-Node Classification on random seed  4726 -> 0.621
-Confusion Matrix:
- [[ 75   2   4   5   5  13   5]
- [  2 131   0   3   9  10   4]
- [ 21  19 127  52  35  16  38]
- [ 14   4  13 115   8   3   4]
- [  1   7   7   1  56   0   2]
- [  3   2   6   6   0  38  10]
- [ 12   2  14   3   8   6  79]]
-Node Classification on random seed  4727 -> 0.638
-Confusion Matrix:
- [[ 71   4   0   8   2  12   1]
- [  7 122   5   3  18   5   1]
- [ 22  25 156  25  29  20  39]
- [  1   3  18 109   5   4   5]
- [  1   9   6   1  55   1   3]
- [  9   1   2   1   0  53   2]
- [ 20   3   8   3  10  20  72]]
-Node Classification on random seed  4728 -> 0.608
-Confusion Matrix:
- [[ 63   3   5   9   1  14  12]
- [  3 132   3   5   3   1   1]
- [ 16  19 134  31  25  48  51]
- [ 15   1  15 100   6   9  16]
- [  1   7   3   5  64   1   0]
- [  9   0   1   5   1  43   3]
- [  8   2  11   8   4  11  72]]
-Node Classification on random seed  4729 -> 0.615
-Confusion Matrix:
- [[ 67   2  11   3   4  13   4]
- [  4 115   6   5   8   6   5]
- [ 29  13 154  30  19  31  33]
- [  3   1  23 104  11   1  25]
- [  1   4   8   3  67   1   4]
- [  7   1   3   2   1  26   7]
- [ 15   7   9   3   3  16  82]]
-Node Classification on random seed  4730 -> 0.611
-Confusion Matrix:
- [[ 60   1   0   3   4  16  15]
- [  4 125  12   5   4   4   7]
- [ 15  20 142  36  31  19  48]
- [  4   5  12 115   6   8  10]
- [  3   5   6   6  54   2   1]
- [  2   0   0   1   2  48   7]
- [ 11   4   9  11   8  22  67]]
-Node Classification on random seed  4731 -> 0.61
-Confusion Matrix:
- [[ 58   1   3  10   9  16   7]
- [  3 128   3   2   9   5   5]
- [ 32  30 150  35  16  31  33]
- [  7   1  15 105   9  19   6]
- [  0   5   1   0  64   1   1]
- [  6   0   2   1   1  37   7]
- [ 15   3   9   7   5  19  68]]
-Node Classification on random seed  4732 -> 0.61
-Confusion Matrix:
- [[ 60   2   4  10   5  14   5]
- [  7 118   5   1   7   8   5]
- [ 30  15 140  34  38  24  32]
- [ 12   1   8 116   7   1  16]
- [  3   5   4   2  57   2   1]
- [  8   1   0   3   3  46   2]
- [ 13   3  15  10  12  12  73]]
-Node Classification on random seed  4733 -> 0.604
-Confusion Matrix:
- [[ 74   1   4   3   2  11  10]
- [ 11 115   7   4  15  10   1]
- [ 22  30 145  36  24  27  27]
- [ 13   4  11  94  10  16  14]
- [  2   3   5   1  56   3   2]
- [  2   0   1   2   0  51   5]
- [ 15   3   5   1  15  18  69]]
-Node Classification on random seed  4734 -> 0.586
-Confusion Matrix:
- [[ 63   3   3   5   4  10  15]
- [  5 116   5   2   9   8   6]
- [ 17  21 147  43  28  13  50]
- [ 28   6  23  82   4   8  14]
- [  0   4   4   5  53   2   5]
- [  3   0   4   1   2  48   7]
- [ 16   3  16   2   2   8  77]]
-Node Classification on random seed  4735 -> 0.612
-Confusion Matrix:
- [[ 67   3   4  10  11   7  16]
- [  7 118   2   3   3   2   5]
- [ 33  32 115  33  29  27  45]
- [ 11   2   7 128   3   4  11]
- [  3   2   4   5  62   0   0]
- [  8   0   1   3   1  42   2]
- [ 11   0  12   7   4  15  80]]
-Node Classification on random seed  4736 -> 0.607
-Confusion Matrix:
- [[ 67   4   2   5   5  16   3]
- [  3 128   5   1  10  11   4]
- [ 21  24 140  21  29  23  43]
- [ 21   6  16  88   3   6  18]
- [  1   3   1   3  64   3   2]
- [  8   1   3   0   4  36  10]
- [  9   5   6  10  13  11  84]]
-Node Classification on random seed  4737 -> 0.631
-Confusion Matrix:
- [[ 76   3   2  10   1   9   1]
- [  1 120  10   5  14   5   6]
- [ 26  15 149  31  41  15  28]
- [ 13   3  13 108   2   8   9]
- [  3   6   1   0  69   1   3]
- [ 11   0   5   1   1  47   2]
- [ 18   4  12  11   9  10  62]]
-Node Classification on random seed  4738 -> 0.581
-Confusion Matrix:
- [[ 66   4   7   3   3   7  11]
- [ 12 113   6   4   8   4   6]
- [ 26  39 123  23  30  44  35]
- [ 11   4  16  98  10   3  17]
- [  0   9   3   4  54   1   0]
- [  7   2   2   2   1  48   5]
- [ 14   4  12   6   8   6  79]]
-Node Classification on random seed  4739 -> 0.62
-Confusion Matrix:
- [[ 76   2   2   3   1   9   9]
- [  8 143   4   0   9   4   1]
- [ 14  25 142  32  36  21  40]
- [ 24   3  17  90   9   6  14]
- [  3   5   4   2  53   2   3]
- [  6   2   3   0   0  51   6]
- [ 10   6   7   4   9  15  65]]
-Node Classification on random seed  4740 -> 0.604
-Confusion Matrix:
- [[ 64   1   4   7   5  11  11]
- [  8 135  12   0  19   0   9]
- [ 30  10 166  31  28  31  18]
- [ 26   2  10  86   3   3   9]
- [  5   7   5   1  54   0   7]
- [  5   0   5   1   0  39   3]
- [ 13   3  14  12   8  19  60]]
-Node Classification on random seed  4741 -> 0.606
-Confusion Matrix:
- [[ 79   2   2   6   1  15   5]
- [  4 120   3   0   2   2   5]
- [ 13  37 146  44  13  18  43]
- [ 18   7  24  91   5   2  15]
- [  1  10   0   0  62   1   2]
- [  4   3   3   2   5  46   5]
- [ 11   9  16   4  10  22  62]]
-Node Classification on random seed  4742 -> 0.628
-Confusion Matrix:
- [[ 71   4   1   1   4  13   7]
- [  5 128   8   1   6   2   2]
- [ 30  21 166  25  26  15  52]
- [ 11   1  18  90   4   6  26]
- [  2   7   4   1  53   1   4]
- [  5   3   0   1   0  45  10]
- [ 10   8   7   0   6  14  75]]
-Node Classification on random seed  4743 -> 0.59
-Confusion Matrix:
- [[ 69   4   5  14   1  12   6]
- [  5 110   5   7   2   1   3]
- [ 28  31 116  59  36  11  38]
- [  4   6  17 118   6   4  13]
- [  4   8   4   4  57   0   2]
- [  4   0   1   3   0  48   7]
- [ 16   3   9   3   9  15  72]]
-Node Classification on random seed  4744 -> 0.65
-Confusion Matrix:
- [[ 76   1   2   2   4  20  12]
- [  5 125   3   2   6   9   3]
- [ 28   7 164  39   9  27  37]
- [ 11   2   9 105  10   7   9]
- [  0   6   3   1  58   2   1]
- [  7   0   4   0   1  47   6]
- [ 11   3  13  10   5  13  75]]
-Node Classification on random seed  4745 -> 0.607
-Confusion Matrix:
- [[ 78   1   3   1   6   6   2]
- [  3 114   6   3  10   3   3]
- [ 26  20 146  22  41  34  40]
- [ 11   5  18  82  14  15   8]
- [  1   4   2   2  71   1   2]
- [  7   1   0   3   0  46   5]
- [  8  10  19   6   5  16  70]]
-Node Classification on random seed  4746 -> 0.649
-Confusion Matrix:
- [[ 69   4   6   5   7  15   8]
- [  2 123   6   6   9   3   1]
- [ 17  28 160  25  22  24  23]
- [  8   3  20 108   2   7  21]
- [  1   4   3   3  66   1   5]
- [  5   1   0   0   2  41   8]
- [  9   2   8   6   7  14  82]]
-Node Classification on random seed  4747 -> 0.589
-Confusion Matrix:
- [[ 68   1   2   3   2  17   6]
- [  1 120   5   2  12  11   0]
- [ 50  18 112  37  41  26  27]
- [ 14   2  15  94   5   7  15]
- [  1   8   2   0  65   1   3]
- [  4   1   3   1   0  59   2]
- [ 18   3   7  10   5  23  71]]
-Node Classification on random seed  4748 -> 0.611
-Confusion Matrix:
- [[ 77   4   4   3   1  14  14]
- [  8 119   8   4   5   2   6]
- [ 21  18 122  41  31  16  52]
- [ 11   4  15 119   7   4  11]
- [  2   6   7   1  46   4   3]
- [ 12   0   2   0   2  43   5]
- [ 12   4   4   8   3  10  85]]
-Node Classification on random seed  4749 -> 0.649
-Confusion Matrix:
- [[ 65   5   3   4   4   8  11]
- [  5 134   4   3  11   1   4]
- [ 19  33 163  34  19  24  27]
- [  6   7  10 121   1   6  20]
- [  1   6   3   4  65   0   3]
- [  3   1   7   0   2  39   2]
- [  7  11   8   8   4  12  62]]
-Node Classification on random seed  4750 -> 0.635
-Confusion Matrix:
- [[ 70   3   5   8   4   7  19]
- [  3 128   6   5  12   4   4]
- [ 30  17 152  42  26  13  23]
- [  5   1  15 115   7   6  21]
- [  0   4   3   2  53   0   5]
- [  3   0   1   3   2  41   7]
- [  7   2   8   7  11  14  76]]
-Node Classification on random seed  4751 -> 0.585
-Confusion Matrix:
- [[ 74   3   2  10   3  14  10]
- [  2 130   6   3  13   3   2]
- [ 20  18 117  31  25  34  35]
- [  3   7  21  86   7   9  23]
- [  5   8   2   2  60   2   1]
- [  6   0   1   4   0  40  18]
- [ 14   2   6  10   8  22  78]]
-Node Classification on random seed  4752 -> 0.614
-Confusion Matrix:
- [[ 64   5   5   1   2  18   1]
- [  4 140   6   1   5   7   3]
- [ 11  14 149  42  49  25  32]
- [  7   8  18 102   9  12   2]
- [  0   8   4   4  60   0   0]
- [  2   4   3   6   0  41   1]
- [ 16   3   3   8  22  15  58]]
-Node Classification on random seed  4753 -> 0.624
-Confusion Matrix:
- [[ 59   5   4   2   4  11   8]
- [  7 136   3   5   5   2   5]
- [ 16  23 137  27  32  28  51]
- [ 13   4   7 108   6   6  10]
- [  1  10   2   0  61   2   2]
- [  4   3   7   0   0  41   2]
- [ 10   3   7   7   5  27  82]]
-Node Classification on random seed  4754 -> 0.634
-Confusion Matrix:
- [[ 67   3   8   5   1  10   6]
- [  2 125  12   4   4   0   5]
- [ 19  18 167  27  16  17  48]
- [ 18   5  20  96   2   1  17]
- [  1   6   5   0  63   1   2]
- [  3   2   7   4   0  37   5]
- [  7   7   9   8   9  22  79]]
-Node Classification on random seed  4755 -> 0.599
-Confusion Matrix:
- [[ 77   3   9   4   2  12   2]
- [  0 130   8   2   3   0   7]
- [ 25  23 112  33  14  29  65]
- [ 15   5  17 120   4   6   8]
- [  2   8   5   0  68   0   5]
- [  3   0   4   1   4  33   3]
- [  9   6  12  10   5  28  59]]
-Node Classification on random seed  4756 -> 0.619
-Confusion Matrix:
- [[ 74   1  13   3   0  10   4]
- [  4 135   8   2   8   1   2]
- [ 25  23 126  50  23  16  46]
- [  4   3  16 112   5  10   7]
- [  3   3   3   0  57   0   1]
- [  4   0   8   4   0  42   3]
- [  8   5  18   8   8  21  73]]
-Node Classification on random seed  4757 -> 0.609
-Confusion Matrix:
- [[ 65   1  12   2   4  11   8]
- [  5 129   5   9   5   2   4]
- [ 33  17 113  26  36  35  43]
- [  9   4   9  94  14   6  14]
- [  1   5   6   2  65   0   1]
- [  2   1   5   2   1  56   5]
- [ 11   1   9   2  10  13  87]]
-Node Classification on random seed  4758 -> 0.611
-Confusion Matrix:
- [[ 72   6   4   2   2  11   8]
- [  7 136   1   4   8   0  11]
- [ 29  19 136  16  31  10  47]
- [ 12   8  16  98   8   2  17]
- [  1   7   5   1  54   5   3]
- [  3   3   5  11   2  40   8]
- [ 10   7   5   6  10  18  75]]
-Node Classification on random seed  4759 -> 0.614
-Confusion Matrix:
- [[ 69   1   7   2   5  11   7]
- [  6 126   5   0   3   6   2]
- [ 39  26 114  47  19  22  35]
- [ 16   1  12 117   8   4   8]
- [  3   9   2   2  70   1   2]
- [  7   4   1   1   0  41   5]
- [ 14   4  12  10   9   8  77]]
-Node Classification on random seed  4760 -> 0.634
-Confusion Matrix:
- [[ 76   3   2   4   2   9   8]
- [  1 128   4   1   8   0  11]
- [ 24   9 143  51  20  22  40]
- [ 14   5  10 106  12   5   8]
- [  1   5   3   1  58   0   4]
- [ 12   1   2   5   0  33   3]
- [ 20   4   7   9   3  13  90]]
-Node Classification on random seed  4761 -> 0.616
-Confusion Matrix:
- [[ 68   2   6   4   6   6   8]
- [  1 129   2   3  17   7   3]
- [ 17  18 138  42  36  23  32]
- [ 14   8  12 106   2   9  11]
- [  1   6   4   5  53   0   0]
- [  6   2   2   2   0  48   7]
- [ 13   4   9  12   7  15  74]]
-Node Classification on random seed  4762 -> 0.61
-Confusion Matrix:
- [[ 60   1   8   4   3  17  12]
- [  7 119   4   7   4   1   4]
- [ 21  18 163  22  45  18  32]
- [ 15   5   9  90  13   5  24]
- [  1   8   3   2  55   0   2]
- [  8   6   5   0   3  41   5]
- [ 12   1  18   5   1  11  82]]
-Node Classification on random seed  4763 -> 0.63
-Confusion Matrix:
- [[ 79   3   4   4   1  13   4]
- [  4 128  10   2  11   2  10]
- [ 12  23 156  52  21  19  32]
- [ 11   5  12  87  10  10   5]
- [  1   3   6   2  56   1   3]
- [  1   2   2   0   0  48   3]
- [ 11   5   6   8  10  26  76]]
-Node Classification on random seed  4764 -> 0.62
-Confusion Matrix:
- [[ 79   1   2   7   2   4   1]
- [  0 125   7   3  10   1   9]
- [ 14  24 116  54  43  18  34]
- [ 12   7   9 114   6   1  13]
- [  3   8   1   1  61   0   6]
- [  9   0   5   2   0  43   8]
- [ 11   4   7  11   8  14  82]]
-Node Classification on random seed  4765 -> 0.595
-Confusion Matrix:
- [[ 67   2   2   5   2   8   7]
- [  3 117  14   2   2   4   1]
- [ 26  38 134  45  19  35  30]
- [ 11   4  13 115   2   4  16]
- [  0  10   8   1  59   3   4]
- [  5   2   2   2   0  38   8]
- [  8   7  10  11  12  17  65]]
-Node Classification on random seed  4766 -> 0.638
-Confusion Matrix:
- [[ 78   1   2   0   1  13   5]
- [ 10 129   8   4   8   1   7]
- [ 28  18 158  25  19  22  53]
- [  7   4  17 100   3   6  14]
- [  1   7   3   3  56   1   5]
- [  6   2   1   5   2  37   8]
- [ 11   1   8   9   2  11  80]]
-Node Classification on random seed  4767 -> 0.607
-Confusion Matrix:
- [[ 72   2   7   0   5  13  12]
- [  3 126   8   2  12   2   3]
- [ 16  20 140  62  17  22  24]
- [  9   4  14 109   8   6  16]
- [  1   5  10   6  57   1   0]
- [  6   4   3   3   0  42   8]
- [ 16   3  10  15   6   9  61]]
-Node Classification on random seed  4768 -> 0.636
-Confusion Matrix:
- [[ 73   1   1   1   2   9  15]
- [  6 124   6   3   6   0   2]
- [ 32  12 161  33  36   8  52]
- [ 22   5  15  89   7   5  12]
- [  3   1   7   2  54   0   2]
- [  8   1   1   4   1  53   3]
- [  5   5   6   7   7  10  82]]
-Node Classification on random seed  4769 -> 0.615
-Confusion Matrix:
- [[ 92   5   3   2   7   5   6]
- [  4 109   3   0   9  11   1]
- [ 23  22 157  33  14  46  33]
- [  9   8  16  97   3  10  13]
- [  1   1  10   1  46   2   3]
- [ 10   0   1   0   2  36   2]
- [ 14   2   9  11   4  26  78]]
-Node Classification on random seed  4770 -> 0.597
-Confusion Matrix:
- [[ 66   4   5   7   3  12  10]
- [  6 131   7   4  19   0   2]
- [ 27  22 139  63  14  10  31]
- [ 22   2  16 102   4   6   8]
- [  1   6   5   3  53   0   3]
- [  5   1   5   2   1  34   7]
- [ 17   1  19   7   6  10  72]]
-Node Classification on random seed  4771 -> 0.632
-Confusion Matrix:
- [[ 58   2   3   1   5  15  17]
- [  3 136   5   0   6   3   2]
- [ 27  20 161  33  28  18  25]
- [ 20   2  11  98   4   6  18]
- [  1   4   5   7  63   0   2]
- [  7   4   1   0   1  38   8]
- [ 11   7   5  13  11   7  78]]
-Node Classification on random seed  4772 -> 0.6
-Confusion Matrix:
- [[ 78   1   4   5   7   6  11]
- [  1 129   4   3   8   1   4]
- [ 24  19 110  42  33  32  50]
- [ 11   6  10 107   5   4  19]
- [  0   7   3   1  70   0   3]
- [  6   2   4  13   0  36   6]
- [  8   1  13   2   4  17  70]]
-Node Classification on random seed  4773 -> 0.644
-Confusion Matrix:
- [[ 67   2   4  12   4  12   5]
- [  5 131   2   5   1   5   1]
- [ 20  30 134  55  10  21  42]
- [  8   3   2 123   5  12   9]
- [  1   8   3   4  60   4   4]
- [  5   1   0   2   0  36   6]
- [ 16   4   4   6   5   8  93]]
-Node Classification on random seed  4774 -> 0.637
-Confusion Matrix:
- [[ 74   0   3   3   6   5  19]
- [  0 126   2   2  10   2   2]
- [ 23  26 144  29  31  13  45]
- [ 15   4  17 112   7   3  19]
- [  3   6   4   4  58   2   2]
- [  4   2   0   1   3  49   3]
- [ 12   5   7   8   8   3  74]]
-Node Classification on random seed  4775 -> 0.596
-Confusion Matrix:
- [[ 62   5   6   2   6  14  11]
- [  5 126  12   6   6   0   1]
- [ 29  20 141  34  31  20  45]
- [ 13   2  16 102   8  10  14]
- [  1   3   4   2  54   1   5]
- [ 11   0   3   0   4  47   3]
- [ 14   2   8   9   7  11  64]]
-Node Classification on random seed  4776 -> 0.671
-Confusion Matrix:
- [[ 63   0   7   1   5  21   7]
- [  2 139   1   1  12   1   3]
- [ 11  14 181  27  24  27  38]
- [  8   2  10 110   5   7  11]
- [  0   6   4   0  67   0   1]
- [  2   1   0   3   0  44   9]
- [ 11   4   6  16   4  17  67]]
-Node Classification on random seed  4777 -> 0.621
-Confusion Matrix:
- [[ 92   1   4   4   5   3   6]
- [  6 126   2   8   8   3   3]
- [ 35  11 113  37  56  26  38]
- [  7   2  10 106   7   9   7]
- [  0   5   3   4  61   2   2]
- [  7   0   0   2   0  48   3]
- [  8   1  12  14   8  10  75]]
-Node Classification on random seed  4778 -> 0.626
-Confusion Matrix:
- [[ 74   3   4   8   3  10   6]
- [  7 128   4   1   8   9   4]
- [ 26  13 119  39  35  13  51]
- [ 15   1  11 122   3   6  11]
- [  0   4   5   0  51   2   6]
- [  3   2   1   3   1  34   7]
- [  7   3   5  18   4  12  98]]
-Node Classification on random seed  4779 -> 0.606
-Confusion Matrix:
- [[ 77   5   2   3   5  10  24]
- [  3 140   8   0   6   3  10]
- [ 25  23 133  31  22  26  47]
- [ 17   2  22  90   2   7  12]
- [  3   5   6   1  60   0   1]
- [  7   2   3   1   1  37   5]
- [ 11   5   4   5   8  11  69]]
-Node Classification on random seed  4780 -> 0.635
-Confusion Matrix:
- [[ 63   3   4   3   7   7  13]
- [  9 132   2   5   4   4   1]
- [ 31  21 168  24  20  25  36]
- [  9   3  21  99   7   6   9]
- [  1   5   3   1  67   1   2]
- [  4   2   1   2   4  39   4]
- [ 13   4  16   7   5  16  67]]
-Node Classification on random seed  4781 -> 0.61
-Confusion Matrix:
- [[ 73   1   2   7   6   8  14]
- [ 11 145   1   3   7   1   3]
- [ 29  13 140  35  30  22  31]
- [ 13   2  29  83   9   8  14]
- [  2   2   7   6  54   0   4]
- [  7   1   2   4   2  42   2]
- [ 14   4   7  11   2  14  73]]
-Node Classification on random seed  4782 -> 0.64
-Confusion Matrix:
- [[ 61   8   5   3   6   7  15]
- [  5 130   7   3  10   1   5]
- [ 16  31 173  38  26  22  23]
- [ 10   6  21  88   7   7  10]
- [  1   4   2   2  63   0   1]
- [  0   4   1   2   2  46   5]
- [ 12   4  10   3   8   7  79]]
-Node Classification on random seed  4783 -> 0.666
-Confusion Matrix:
- [[ 72   9   2   1   2   7  11]
- [  1 143   7   1   7   0   4]
- [ 22  19 165  44  24  30  22]
- [  3   8  12  97   6   8  16]
- [  3   9   3   1  51   1   1]
- [  1   1   2   1   0  51   4]
- [ 13   3   3   5   4  13  87]]
-Node Classification on random seed  4784 -> 0.621
-Confusion Matrix:
- [[ 58   2   2  13   4  10  15]
- [  3 130   3   5   1   1   2]
- [ 20  25 150  45  26  14  45]
- [ 17   5   7 107   2   5  13]
- [  1   5   6   5  66   1   2]
- [ 11   0   4   2   0  38   4]
- [ 14   5   6   8   7  13  72]]
-Node Classification on random seed  4785 -> 0.602
-Confusion Matrix:
- [[ 68   3   5   3   5  11  19]
- [  1 109   7   3   4   2   9]
- [ 29  28 146  27  14  32  41]
- [ 11   1  25 111   4   5  15]
- [  2   4   2   0  58   0   5]
- [  5   2   2   0   0  40   7]
- [ 10   5  16   7  10  17  70]]
-Node Classification on random seed  4786 -> 0.614
-Confusion Matrix:
- [[ 85   2   8  11   5   9   4]
- [  4 131   3   0   6   2   6]
- [ 20  38 144  35  29  10  37]
- [ 24   8  14  67   4   2  28]
- [  1   8   3   2  64   1   3]
- [  6   0   1   1   1  39   9]
- [ 15   4   6   5   5   6  84]]
-Node Classification on random seed  4787 -> 0.618
-Confusion Matrix:
- [[ 81   2  13   1   4  22   7]
- [  2  98   5   2  13   4   5]
- [ 24  16 160  48  21  22  42]
- [  6   2  20  89   3   8  16]
- [  0   4   8   0  60   1   2]
- [  4   7   0   1   6  40   2]
- [  5   4   4   2   4  20  90]]
-Node Classification on random seed  4788 -> 0.613
-Confusion Matrix:
- [[ 73   3   5   6   1  13  11]
- [  5 128   6   2   4   4   5]
- [ 18  14 117  48  50  28  36]
- [  6   2  22 108   5   8   2]
- [  0   8   2   3  56   1   6]
- [  6   0   3   3   0  46   5]
- [  4   0   9  14   4  15  85]]
-Node Classification on random seed  4789 -> 0.604
-Confusion Matrix:
- [[ 62   3   6   7   2  15  12]
- [ 10 124   7   1   2   1   2]
- [ 33  36 150  21  26  13  44]
- [ 18   3  14  91  10   5  12]
- [  2  10   4   1  48   1   2]
- [  5   2   0   2   1  45   6]
- [ 15  10   6   5   4  17  84]]
-Node Classification on random seed  4790 -> 0.64
-Confusion Matrix:
- [[ 64   3   2   3   3  13   8]
- [  4 120   3   2   6   3   2]
- [ 25  19 168  32  13  36  26]
- [  3   1  14 101   4  19  14]
- [  4   9   2   4  63   1   3]
- [  7   0   1   1   1  46  10]
- [ 25   8  12   3   0  11  78]]
-Node Classification on random seed  4791 -> 0.646
-Confusion Matrix:
- [[ 66   3  10   4   3  17   3]
- [  2 118   5   2   6   2   3]
- [ 25  19 174  31  15  18  42]
- [ 14   4  16 114   0   5  12]
- [  2   5   4   1  53   0   2]
- [  5   1   5   1   3  45   1]
- [ 20   6   7  16   5   9  76]]
-Node Classification on random seed  4792 -> 0.57
-Confusion Matrix:
- [[ 65   5   3   4  15  15  13]
- [  6 112   6   3   8   3   9]
- [ 15  26 127  35  23  19  49]
- [ 12   9  13  96   3   6  18]
- [  5   5   6   2  62   1   1]
- [  4   0   1   3   0  43  10]
- [ 15   6  23  10   7  13  65]]
-Node Classification on random seed  4793 -> 0.637
-Confusion Matrix:
- [[ 69   4   9   0   2  13  10]
- [  2 144   4   2   3   1   4]
- [ 27  29 160  34   9  34  23]
- [  7   2  22 101   6   8   5]
- [  0   7   3   4  54   2   6]
- [  7   4   1   1   4  33   2]
- [  7  10   8   9   6  22  76]]
-Node Classification on random seed  4794 -> 0.587
-Confusion Matrix:
- [[ 73   8   8   2   6  11   6]
- [  2 132   0   4   5   6   5]
- [ 24  32 117  39  40  27  29]
- [ 15   7   2 104  11  10   8]
- [  0  11   3   0  54   0   6]
- [  9   1   1   3   1  43   5]
- [ 26   3   6  14  10   7  64]]
-Node Classification on random seed  4795 -> 0.617
-Confusion Matrix:
- [[ 87   2   3   4   2   1   2]
- [  5 143   3   2   7   3   3]
- [ 39  35 129  24  31  11  43]
- [ 22   2  15  94   8   7  10]
- [  3   7   4   3  56   0   3]
- [  8   3   5   3   0  38   1]
- [ 24   2   8   6   3  16  70]]
-Node Classification on random seed  4796 -> 0.636
-Confusion Matrix:
- [[ 69   1  12   7   3  15   6]
- [  3 144   4   1   9   3   1]
- [ 19  22 169  41  20  10  31]
- [ 13   4  22  92   0   6  12]
- [  2   8   3   2  48   3   1]
- [  4   2   6   2   0  47   3]
- [ 11   6   7  10   6  23  67]]
-Node Classification on random seed  4797 -> 0.591
-Confusion Matrix:
- [[ 66   4   3   5   8  11   8]
- [  4 141   1   6   7   2   4]
- [ 21  26 118  49  25  16  49]
- [ 10   2  21  99  12   5  11]
- [  2   6   6   2  44   0   7]
- [  4   2   7   0   1  53   6]
- [ 13   5  17   8   7   6  70]]
-Node Classification on random seed  4798 -> 0.639
-Confusion Matrix:
- [[ 66   5   7   6   3   9   4]
- [  3 125   9   3   2   4   1]
- [ 19  26 148  32  26  22  32]
- [ 14   0  20 121   5   6  14]
- [  2   5   4   1  61   0   4]
- [ 10   0   2   3   0  40   5]
- [  9   6   5   8   7  18  78]]
-Node Classification on random seed  4799 -> 0.652
-Confusion Matrix:
- [[ 66   2   3   5   1   9   4]
- [  5 125   9   4  10   2   0]
- [ 23  15 171  25  34  25  24]
- [ 15   7  11 117   9   5   5]
- [  2  10   1   2  71   0   1]
- [  4   2   2   6   4  46   3]
- [ 16   9   4  14   3  13  56]]
-Node Classification on random seed  4800 -> 0.612
-Confusion Matrix:
- [[ 68   2   8   8   4  23   6]
- [  5 116   5   1  10   1  13]
- [ 19  23 131  30  25  25  42]
- [ 15   8  12 116   3   9   9]
- [  0   7   2   4  62   0   2]
- [  5   0   2   0   1  44   8]
- [  2   7   4  18  12   8  75]]
-Node Classification on random seed  4801 -> 0.649
-Confusion Matrix:
- [[ 64   5   3   8   6   4   9]
- [ 11 133   1   1   5   0   5]
- [ 10  36 140  22  42  22  39]
- [ 10   3   9 124   6   4   7]
- [  0  10   1   1  61   0   0]
- [  6  10   0   0   2  35  10]
- [  4   3   4  11   7  14  92]]
-Node Classification on random seed  4802 -> 0.627
-Confusion Matrix:
- [[ 74   2   3   5  10   9   3]
- [  2 123   6   1  19   2   4]
- [ 27  16 153  27  45  23  24]
- [ 18   6  33  89   2   6   9]
- [  4   1   3   0  67   0   2]
- [  2   0   1   3   3  52   1]
- [ 12   3   6   8   7  15  69]]
-Node Classification on random seed  4803 -> 0.607
-Confusion Matrix:
- [[ 79   4   5   6   8  14  11]
- [  4 134   9   1   6   0   2]
- [ 29  16 121  54  45  14  34]
- [  6   2  15 113   2   3  16]
- [  0   3   2   4  54   1   4]
- [ 12   0   2   3   1  42   3]
- [ 12   4   1  18   7  10  64]]
-Node Classification on random seed  4804 -> 0.588
-Confusion Matrix:
- [[ 69   4   6   7   4  23   4]
- [  1 128   5  17   5   2   2]
- [ 23  19 124  38  22  30  50]
- [ 12   2  33  97  10   8   8]
- [  2   7   2   0  57   0   1]
- [  5   0   0   3   0  50   4]
- [  7   0  16   5   9  16  63]]
-Node Classification on random seed  4805 -> 0.59
-Confusion Matrix:
- [[ 68   7   7   4   5  10  13]
- [  5 135   3   2   7   3   6]
- [ 20  21 119  28  37  10  63]
- [ 12   6  14  98   7   3   8]
- [  0   6   2   0  65   0   2]
- [ 14   3   2   3   2  41   3]
- [ 14   4  10   4  29  11  64]]
-Node Classification on random seed  4806 -> 0.611
-Confusion Matrix:
- [[ 76   7  12   7   2   8   9]
- [  6 122   7   0   1   2   2]
- [ 16  22 155  44  23  22  42]
- [ 12  10   9 101   7   4  15]
- [  4  13   2   1  48   0   6]
- [  5   3   1   3   3  41   7]
- [ 20   4   3  10  11   4  68]]
-Node Classification on random seed  4807 -> 0.607
-Confusion Matrix:
- [[ 66   2   7   6   4   7  19]
- [  4 122   7   3   8   6   1]
- [ 27  18 135  19  26  26  51]
- [  1   4  23 102   3   9  17]
- [  0   9   0   3  65   3   0]
- [  7   2   3   2   1  50   6]
- [ 13   3   2   6  25  10  67]]
-Node Classification on random seed  4808 -> 0.617
-Confusion Matrix:
- [[ 74   5   5   0   0  11  13]
- [  3 115  15   7  11   3   1]
- [ 23  12 156  46  20  12  31]
- [ 15   7  27  96   5   8   3]
- [  1   5   3   1  63   1   3]
- [  8   3   2   0   0  49   2]
- [ 18   7  12   9   5  20  64]]
-Node Classification on random seed  4809 -> 0.604
-Confusion Matrix:
- [[ 79   3   5   4   6   9  12]
- [  4 123   1   0  13   3   5]
- [ 23  15 141  25  19  18  61]
- [  9   5   9  92  12  11  20]
- [  2   7   3   4  55   4  11]
- [  8   3   6   0   1  42   4]
- [  7   5  14   1   5  19  72]]
-Node Classification on random seed  4810 -> 0.638
-Confusion Matrix:
- [[ 66   5   7   4   3  14  15]
- [  6 126  10   0   6   0   1]
- [ 28  26 141  37  22  17  35]
- [  7   3   8 107   2   6  12]
- [  0   8   7   2  66   0   2]
- [  5   0   1   2   1  49   8]
- [ 18   2   7   3  13   9  83]]
-Node Classification on random seed  4811 -> 0.582
-Confusion Matrix:
- [[ 61   5   4   3   2  24  17]
- [  3 114   5   5   5   6   0]
- [ 20  33 134  37  15  28  37]
- [ 11   9   9 100   5  10  16]
- [  1   7   6   2  56   1   2]
- [  1   5   4   6   0  47   3]
- [ 14   9   9   5  13  21  70]]
-Node Classification on random seed  4812 -> 0.639
-Confusion Matrix:
- [[ 82   3   7   3   2   7  14]
- [  4 121   4   1   8   2   6]
- [ 33  12 135  47  15  17  45]
- [ 19   1   6 108   2  11  14]
- [  3   3   5   3  60   1   1]
- [  3   0   0   0   2  43   5]
- [ 20   2  17   5   1   7  90]]
-Node Classification on random seed  4813 -> 0.62
-Confusion Matrix:
- [[ 77   1   3   4   5  18  12]
- [  7 134   3   2   6   5   2]
- [ 16  22 147  29  17  48  26]
- [ 10   5  40  87   4   6   7]
- [  1   6   6   1  54   1   1]
- [  8   1   2   2   2  52   0]
- [ 10   2  10   5   9  15  69]]
-Node Classification on random seed  4814 -> 0.601
-Confusion Matrix:
- [[ 72   4   4  11   6  11   2]
- [  6 116   9   3   9   2   9]
- [ 24  11 134  52  36  28  37]
- [ 14   1  11 106   4  11   7]
- [  3   6   1   3  56   1   2]
- [  7   1   1   1   0  44   2]
- [ 19   2   7   7   5  19  73]]
-Node Classification on random seed  4815 -> 0.593
-Confusion Matrix:
- [[ 67   1   4   8   5  15   5]
- [  7 118   5   2  13   4   4]
- [ 29  16 119  41  28  29  51]
- [ 25   6  14  93   1   8  15]
- [  0   7   3   0  69   0   2]
- [  7   0   2   1   1  44   6]
- [ 11   2   5   2   5  17  83]]
-Node Classification on random seed  4816 -> 0.631
-Confusion Matrix:
- [[ 74   1   8   2   6  12   7]
- [  0 146   4   2   1   3   4]
- [ 21  35 129  40  20  30  42]
- [ 24   7   9  95   6   8   6]
- [  1   3   8   0  61   1   1]
- [  2   1   1   0   2  40   4]
- [  8   2   9   4   7  17  86]]
-Node Classification on random seed  4817 -> 0.621
-Confusion Matrix:
- [[ 77   2   5   8   4   8   1]
- [  6 124   6   3   3   7   2]
- [ 21  11 136  33  34  28  37]
- [ 14   6  19 112   6   3  11]
- [  1   9   2   3  55   1   5]
- [ 11   1   2   0   2  44   4]
- [ 27   0   9   4   6  14  73]]
-Node Classification on random seed  4818 -> 0.644
-Confusion Matrix:
- [[ 74   8   2   3  10  11   4]
- [  2 143   4   3   6   1   5]
- [ 16  30 142  42  24  27  35]
- [ 11   7  20 102   6   3   4]
- [  0  12   3   1  61   1   1]
- [  4   0   3   1   1  45   4]
- [  9   6   7   4   5  10  77]]
-Node Classification on random seed  4819 -> 0.615
-Confusion Matrix:
- [[ 56   4   3   7   3  18  15]
- [  6 130   4   2   4   0   4]
- [ 22  33 145  47   8  27  45]
- [  5   3  13 101   4  18  18]
- [  1   5   3   2  57   1   2]
- [  4   0   3   1   2  46   2]
- [  7   5   5  10   5  14  80]]
-Node Classification on random seed  4820 -> 0.628
-Confusion Matrix:
- [[ 79   3   4   6   5  12  10]
- [  1 141   4   1   4   4   8]
- [ 25  21 140  49  15  15  38]
- [  7   4  18  99   5   4  14]
- [  2   3   7   2  59   0   4]
- [  8   2   3   4   0  32   5]
- [ 10   4  11  10   2  18  78]]
-Node Classification on random seed  4821 -> 0.599
-Confusion Matrix:
- [[ 58   5   4   3   6  17  15]
- [  6 126   4   3   5   0   5]
- [ 14  21 143  36  39  21  51]
- [  2   4  20  95   7   3  18]
- [  2   7   4   3  57   1   1]
- [  3   1   1   3   4  41  12]
- [ 13   7   7  10   8   5  79]]
-Node Classification on random seed  4822 -> 0.592
-Confusion Matrix:
- [[ 73   0   2   4   0   7  19]
- [  6 124   7   3  10   7   4]
- [ 38  15 137  29  23  22  61]
- [  7   5  15  99   3   7  21]
- [  1   7   4   1  51   0   4]
- [ 10   0   3   0   1  41   7]
- [ 16   5   9   9   8   8  67]]
-Node Classification on random seed  4823 -> 0.601
-Confusion Matrix:
- [[ 70   2   4   5   7  12   6]
- [ 13 124   5   2   1   2   5]
- [ 34  37 110  30  37  25  38]
- [ 16   5  14 105   7   6  15]
- [  0   8   3   1  63   0   1]
- [  6   0   2   3   0  49   5]
- [ 13   1  11   5   4   8  80]]
-Node Classification on random seed  4824 -> 0.623
-Confusion Matrix:
- [[ 77   2   7   4   3   1   9]
- [  5 141   4   4  16   2   3]
- [ 30  19 125  24  45  18  42]
- [  8   7  12 100   8   4  18]
- [  3   3   4   1  69   0   2]
- [  3   0   0   1   1  50   8]
- [ 24   2   6   8   6  10  61]]
-Node Classification on random seed  4825 -> 0.608
-Confusion Matrix:
- [[ 63   7   4   0   5   7  18]
- [  1 119  13   6   7   7   2]
- [ 28   9 140  33  28  22  47]
- [ 16   1  20 103   6   7  15]
- [  2   8   2   1  62   0   2]
- [  6   0   3   2   1  42   5]
- [ 11   2   3   5  12  18  79]]
-Node Classification on random seed  4826 -> 0.585
-Confusion Matrix:
- [[ 48   1   7  17   5  24  10]
- [ 11 112   3   3   5   2   7]
- [ 22  26 131  57  35  13  32]
- [  4   1  13 120   2   5   7]
- [  4   6   9   3  53   0   2]
- [  0   1   6   2   0  51   6]
- [  8   4  12  14   6  20  70]]
-Node Classification on random seed  4827 -> 0.618
-Confusion Matrix:
- [[ 87   1   3  12   5  11  12]
- [  3 127   5   2  11   2   2]
- [ 38  18 123  33  13  21  49]
- [ 20   5   8 100  10   3  12]
- [  0   5   7   3  69   0   0]
- [  9   0   4   4   1  29   9]
- [ 14   0  13   5   3   6  83]]
-Node Classification on random seed  4828 -> 0.619
-Confusion Matrix:
- [[ 66   1   1   1   5  12  17]
- [  4 119  10   2  15   2   3]
- [ 32  18 144  39  36  21  33]
- [  7   1  15 109   3  13   7]
- [  2   5   1   3  62   0   1]
- [  8   2   0   0   1  39   2]
- [ 12   5  13  10   7  11  80]]
-Node Classification on random seed  4829 -> 0.625
-Confusion Matrix:
- [[ 62   1  10   4   4   6   5]
- [  2 143   6   3   8   3   3]
- [ 33  14 131  41  17  25  43]
- [ 10   5  11  98   7   7  18]
- [  3   4   9   1  56   1   2]
- [  2   2   2   4   0  46   4]
- [ 10   0   7  17   8  13  89]]
-Node Classification on random seed  4830 -> 0.606
-Confusion Matrix:
- [[ 63   0   0   4   1  16  11]
- [  5 121   4   1   7   8   7]
- [ 30  25 123  40  24  18  39]
- [ 10   6  12 111   9   8   6]
- [  2   7   2   2  63   2   0]
- [  7   4   1   2   3  56   1]
- [ 14   3   9  11   6  27  69]]
-Node Classification on random seed  4831 -> 0.653
-Confusion Matrix:
- [[ 68   1  10   2   7   8   8]
- [  4 133   6   0   6   2   7]
- [ 13  12 173  30  21  28  33]
- [  7   0  23  89   6  23  16]
- [  0   7   4   1  58   1   3]
- [  3   1   1   1   0  56   4]
- [ 11   1   9   6   2  19  76]]
-Node Classification on random seed  4832 -> 0.608
-Confusion Matrix:
- [[ 77   1   2   6   4  13   4]
- [  5 119   9   2  19   3   6]
- [ 18  15 163  39  23  20  44]
- [  9   0  32  76  13   5  12]
- [  1   5   3   0  60   0   4]
- [  5   3   2   1   1  42   7]
- [ 18   2  20   4   2  10  71]]
-Node Classification on random seed  4833 -> 0.581
-Confusion Matrix:
- [[ 80   2   5   2   6  18   5]
- [  7 122   4   8   7   5   7]
- [ 22  24 127  36  33  29  34]
- [ 19   3  10  88  14  10  13]
- [  1   7   1   0  55   0   3]
- [  9   3   5   0   4  38   5]
- [ 10   5   6   9   3  25  71]]
-Node Classification on random seed  4834 -> 0.636
-Confusion Matrix:
- [[ 76   2   2   4   3  11   7]
- [  4 140   3   0  10   4   4]
- [ 29  19 135  50  33  28  16]
- [ 11  10   7 118   4   4  12]
- [  1   8   3   0  57   1   1]
- [  4   2   2   0   0  49   5]
- [ 13   5   7  10   4  21  61]]
-Node Classification on random seed  4835 -> 0.616
-Confusion Matrix:
- [[ 81   3  10   1   2   8   7]
- [  8 122  13   3   4   0   9]
- [ 24  15 143  46  41  16  34]
- [  7   5  14  95  10   6  23]
- [  2   3   5   1  59   2   0]
- [  6   2   2   0   0  38   8]
- [ 12   5   5  10   2  10  78]]
-Node Classification on random seed  4836 -> 0.615
-Confusion Matrix:
- [[ 75   1   1   8   5   6  24]
- [  4 116   1   4  12   6   7]
- [ 40  13 143  25  21  21  47]
- [  7   2  13 109   4   6   7]
- [  1   5   5   0  59   0   2]
- [  4   1   4   2   1  44   5]
- [ 19   5  21   7   6  12  69]]
-Node Classification on random seed  4837 -> 0.618
-Confusion Matrix:
- [[ 73   0   2   8   1  10  13]
- [  2 122   5   4   6   0   2]
- [ 25  36 133  40  19  11  58]
- [ 10   3  13 109   4   6  14]
- [  2   8   0   1  53   4   3]
- [  2   0   3   1   2  58   7]
- [ 15   2   8  13  11   8  70]]
-Node Classification on random seed  4838 -> 0.614
-Confusion Matrix:
- [[ 77   0   6   8   5  15   7]
- [  5 107   3   4   6   5   4]
- [ 46  17 144  41  25  15  24]
- [ 14   2  14 108   4   6  12]
- [  3   6   7   1  59   1   2]
- [  5   1   7   1   0  47   2]
- [ 14   1  13   5  11  18  72]]
-Node Classification on random seed  4839 -> 0.592
-Confusion Matrix:
- [[ 77   3   3   0   4   5   4]
- [  6 119   3   4   8   8   4]
- [ 20  22 123  48  41  26  42]
- [ 10   2  21 102   3  11   8]
- [  0   9   1   3  62   3   2]
- [ 10   0   1   1   2  47   3]
- [ 19   5   7  12  10  14  62]]
-Node Classification on random seed  4840 -> 0.562
-Confusion Matrix:
- [[ 45   1   2  15   4  11  26]
- [  1 104   4   8  19   4   8]
- [ 13  21 128  37  59  16  51]
- [ 17   2  14 106   3  15   5]
- [  2   3   0   0  65   2   3]
- [  8   2   3  10   1  35   6]
- [ 10   2   6   9   7   8  79]]
-Node Classification on random seed  4841 -> 0.632
-Confusion Matrix:
- [[ 73   0   6   3   3   7   9]
- [  1 129   6   3   9   2   7]
- [ 19  40 171  24  17  25  29]
- [ 18  13  13  90   2   5  15]
- [  2   6   3   2  63   2   2]
- [  4   0   2   0   1  46  10]
- [ 12   4   7   8  11  16  60]]
-Node Classification on random seed  4842 -> 0.589
-Confusion Matrix:
- [[ 65   1   6   2   9  25   6]
- [  3 121   6   7  12   3   3]
- [ 21  19 138  50  26  43  17]
- [ 12   6  14  91  10  12   8]
- [  2   5   3   3  60   1   1]
- [  4   0   2   1   1  37   6]
- [ 19   6   9   6   9  12  77]]
-Node Classification on random seed  4843 -> 0.607
-Confusion Matrix:
- [[ 77   3   2   5   3   8   5]
- [  4 112  14   1  12   4   3]
- [ 28  29 139  31  51  15  33]
- [ 17   0  13  98   7   8   9]
- [  0   5   4   0  74   1   0]
- [  9   2   1   2   1  53   3]
- [ 16   3   6  16  13   6  54]]
-Node Classification on random seed  4844 -> 0.609
-Confusion Matrix:
- [[ 65   5   1   1   5  15  13]
- [  5 145   2   0   2   3   9]
- [ 18  32 128  48  25  25  41]
- [  5   1  11  95   8   7  21]
- [  1  12   0   4  60   2   4]
- [  4   1   0   2   3  36   9]
- [  7   3   7  10   9  10  80]]
-Node Classification on random seed  4845 -> 0.625
-Confusion Matrix:
- [[ 78   3   1   5   1   6   9]
- [  3 136  10   4   1   0   1]
- [ 26  32 135  22  16  24  46]
- [  8   3  19  94  13   5  18]
- [  2  11   2   2  56   0   5]
- [ 13   2   2   0   2  42   8]
- [ 18   5  10   4   3  10  84]]
-Node Classification on random seed  4846 -> 0.652
-Confusion Matrix:
- [[ 85   1   3   6   2  10   9]
- [  2 136   7   1  10   5   1]
- [ 20  23 165  22  22  22  20]
- [ 17   9  17  85   3   7  13]
- [  0   9   4   5  63   0   2]
- [  3   2   3   0   2  49   2]
- [ 15   7  10   4   8  20  69]]
-Node Classification on random seed  4847 -> 0.623
-Confusion Matrix:
- [[ 74   7   7   6   2  10  13]
- [  2 129   5   1   4   3   0]
- [ 21  31 127  24  46  11  32]
- [ 27   3  17 110   8   8   8]
- [  2   2   2   0  62   1   1]
- [ 13   2   3   2   2  42   5]
- [ 10   5   8   4   5  14  79]]
-Node Classification on random seed  4848 -> 0.674
-Confusion Matrix:
- [[ 57   9   6   2   2   7  14]
- [ 11 128   5   4   9   0   1]
- [ 19  23 186  22  17  14  34]
- [  7   2  17 112   4   5  10]
- [  1   4   6   1  72   0   1]
- [  3   2   4   0   2  51   4]
- [ 13   5   5   5  16  10  68]]
-Node Classification on random seed  4849 -> 0.623
-Confusion Matrix:
- [[ 74   3   4   5   3   3   6]
- [  9 129   3   0   5   2   3]
- [ 33  21 159  51  22   9  38]
- [ 24   5  18  87   2   7  10]
- [  0  15   5   0  61   0   3]
- [  3   0   7   3  10  35   2]
- [ 14   5  11   4   4   5  78]]
-Node Classification on random seed  4850 -> 0.63
-Confusion Matrix:
- [[ 68   2  10   5   2  15   5]
- [  2 139   2   5   2   0   5]
- [ 18  30 132  38  22  32  42]
- [  4   7  15 110   5   6  12]
- [  1   7   7   1  53   0   1]
- [  4   0   1   3   2  47   7]
- [ 10   1   9   3  10  17  81]]
-Node Classification on random seed  4851 -> 0.597
-Confusion Matrix:
- [[ 52   3   7   6   3   8  14]
- [  3 127   3   1  15   3   3]
- [ 28  29 138  35  28  36  33]
- [ 15   6  21  93   3   6  15]
- [  2   5   4   0  70   2   2]
- [  1   2   3   2   0  45   3]
- [  8   3  17   5   7  13  72]]
-Node Classification on random seed  4852 -> 0.604
-Confusion Matrix:
- [[ 79   1   2   5   4  12  10]
- [  5 106   3   4  13   3   6]
- [ 26  27 133  33  21  19  43]
- [ 16   5  10 116   3   3  12]
- [  1   4   3   0  52   2   2]
- [ 16   2   1   0   0  50   3]
- [ 27   8   7   6  11  17  68]]
-Node Classification on random seed  4853 -> 0.607
-Confusion Matrix:
- [[ 66   2   2   4   2  22   6]
- [  8 133   2   2  13   4   2]
- [ 19  13 125  29  54  28  34]
- [  4   5  16  99  10  17  10]
- [  2   2   2   2  69   0   3]
- [  4   3   2   1   0  52   4]
- [ 10   4  11   5   9  21  63]]
-Node Classification on random seed  4854 -> 0.621
-Confusion Matrix:
- [[ 71   1   6   1   3   8  21]
- [  2 126   3   2   7   1   2]
- [ 37  26 137  32  22  18  34]
- [  7   5  23  99   3   4  16]
- [  3   5   2   2  64   2   3]
- [  6   2   3   0   2  52   9]
- [ 21   4  12   7   4   8  72]]
-Node Classification on random seed  4855 -> 0.668
-Confusion Matrix:
- [[ 79   2   6   4   8   4   7]
- [  2 126   8   3   3   1   8]
- [ 18  22 160  30  28   9  46]
- [  6   3  18  94   8   3  10]
- [  1   9   5   0  74   1   2]
- [  7   2   2   1   0  46   2]
- [  9   8   8   3   5  10  89]]
-Node Classification on random seed  4856 -> 0.621
-Confusion Matrix:
- [[ 67   7   0  12   7   8  12]
- [  8 119   4   3   1   2   3]
- [ 29  15 141  50  23  15  36]
- [  7   6  15 106  12   8   7]
- [  1  10   4   0  53   2   4]
- [  5   0   0   3   1  53   9]
- [ 13   4   7  15   7   4  82]]
-Node Classification on random seed  4857 -> 0.615
-Confusion Matrix:
- [[ 58   4   0   7   3  14  14]
- [  5 139   7   1   4   4   5]
- [ 32  36 158  20  16  11  38]
- [  7   8  21  91   1   3  19]
- [  0   6   4   1  63   0   2]
- [  3   3   4   1   2  51   4]
- [  6  11   8   6  31  13  55]]
-Node Classification on random seed  4858 -> 0.548
-Confusion Matrix:
- [[ 42   1   7  18   4  12  19]
- [  6 104  12   1  14   5  10]
- [ 21  24 144  41  26  34  37]
- [  5   1  15  92   3   8  27]
- [  1   8   5   3  63   1   3]
- [  9   0   3   2   3  41   3]
- [ 11   4   9   4  13  19  62]]
-Node Classification on random seed  4859 -> 0.605
-Confusion Matrix:
- [[ 72   2  10   0   2   8  16]
- [  6 117   8   1   8   2   3]
- [ 23  21 148  37  32  26  38]
- [ 19   4  15  81  10   2  22]
- [  2   4   4   0  69   0   4]
- [  5   2   3   5   1  46   4]
- [ 10   3   6   2   8  17  72]]
-Node Classification on random seed  4860 -> 0.614
-Confusion Matrix:
- [[ 63   4   3   1   4   5  17]
- [  2 123  11   2   9   0   4]
- [ 29  23 156  40  27  29  20]
- [  8   5  15 100   9  10  13]
- [  0   9   4   1  51   0   4]
- [  7   3   1   4   1  41   5]
- [ 16   6   8   2  10  15  80]]
-Node Classification on random seed  4861 -> 0.582
-Confusion Matrix:
- [[ 73   2   8   6   2  13  10]
- [  4 117   1   0  12   4   4]
- [ 23  15 125  40  51  26  33]
- [ 18   3  19  83   3   3  11]
- [  2   8   2   1  65   2   3]
- [ 12   1   3   0   0  39  15]
- [  8   7   9   5  13  16  80]]
-Node Classification on random seed  4862 -> 0.635
-Confusion Matrix:
- [[ 55   2   4  11   1  16   8]
- [  0 133   3   1  11   2   1]
- [ 26  24 149  34  23  36  28]
- [ 16   3  10 114   4  14   6]
- [  0  10   2   0  64   1   3]
- [  3   4   3   1   0  54   1]
- [ 11   6   9   8   7  12  66]]
-Node Classification on random seed  4863 -> 0.626
-Confusion Matrix:
- [[ 67   2   5   5   7  13  12]
- [  4 134   8   1   4   0   3]
- [ 26  13 158  50  31  14  23]
- [ 14   2  10  97   7  11  10]
- [  3   7   2   5  54   0   0]
- [ 11   1   2   1   0  45   3]
- [ 19   3  11   5   9  17  71]]
-Node Classification on random seed  4864 -> 0.638
-Confusion Matrix:
- [[ 70   1   2   7   4  12  13]
- [  2 119   8   2   4   1   6]
- [ 21  18 154  30  27  22  35]
- [ 10   8  13 105   8   4   8]
- [  0   7   5   0  57   4   3]
- [  0   1   1   0   0  49   7]
- [ 21   1  15   5  11  15  84]]
-Node Classification on random seed  4865 -> 0.609
-Confusion Matrix:
- [[ 57   3   8  11   3  14  14]
- [  3 125   5   3   9   1  11]
- [ 26  16 133  25  29  18  41]
- [ 10   5  24  99   5   8  16]
- [  2   6   2   2  72   1   2]
- [  4   2   5   1   2  40   3]
- [ 15   1  10   5   6  14  83]]
-Node Classification on random seed  4866 -> 0.63
-Confusion Matrix:
- [[ 77   2   0   4   3  13  11]
- [  1 134  16   0   4   3   3]
- [ 27  29 139  35  21  13  36]
- [ 13   1  11 103   4   5  22]
- [  1   5   3   0  59   2   3]
- [  5   2   2   0   2  46  11]
- [  9   0   9   8  21  10  72]]
-Node Classification on random seed  4867 -> 0.625
-Confusion Matrix:
- [[ 73   3   3   6   4   9  13]
- [  4 126   1   4   1   1   4]
- [ 34  18 140  39  24  16  44]
- [ 10   3   8 113   4   9  14]
- [  2   6   4   0  61   0   9]
- [  7   4   1   0   1  48   5]
- [ 10   7   5   9   5  24  64]]
-Node Classification on random seed  4868 -> 0.622
-Confusion Matrix:
- [[ 74   3   5   6   4  11  10]
- [  7 119   7   1   4   3   3]
- [ 31  26 145  37  16  21  38]
- [ 11   9  13 111   2   7  11]
- [  3   5  11   4  59   0   1]
- [  8   2   2   2   1  44   5]
- [ 11   2   2   5   6  22  70]]
-Node Classification on random seed  4869 -> 0.608
-Confusion Matrix:
- [[ 57   3   2  15   7   5  20]
- [  0 112   5   1  14   2   7]
- [ 15  17 140  32  50  13  41]
- [  3   7  24 115   5   5  14]
- [  1   6   3   3  59   0   2]
- [ 12   2   1   3   0  35  13]
- [  8   2   7  10   2  10  90]]
-Node Classification on random seed  4870 -> 0.627
-Confusion Matrix:
- [[ 78   2  10   6   1  11   6]
- [  2 127   4   0   9   4   7]
- [ 26  15 158  21  13  36  47]
- [ 13   3  11  97   0   8  22]
- [  2  12   6   2  52   0   0]
- [  5   4   1   1   0  52   2]
- [  8   7   6  10  13  17  63]]
-Node Classification on random seed  4871 -> 0.599
-Confusion Matrix:
- [[ 68   4   8   5   3  13  15]
- [  1 132   4   2  10   0   2]
- [ 20  27 133  59  28  13  33]
- [  9   6  16 100  11   4   9]
- [  1   8   4   2  64   0   1]
- [ 12   1   2   2   4  33   4]
- [ 17   1   7   6   8  19  69]]
-Node Classification on random seed  4872 -> 0.653
-Confusion Matrix:
- [[ 76   1   3   3   4  15  14]
- [  9 118   5   1  14   1   1]
- [ 25  18 165  32  24  16  42]
- [ 10   4  13 115   6   0  11]
- [  3   2   3   0  77   0   0]
- [  6   2   5   3   1  30   9]
- [ 12   4   5   3  10   7  72]]
-Node Classification on random seed  4873 -> 0.631
-Confusion Matrix:
- [[ 78   4   3   1   4  14   4]
- [  5 115   4   6   9   0   5]
- [ 21  19 135  54  41  22  21]
- [ 18   8   5 114   4   3   8]
- [  3   9   4   2  53   1   2]
- [  6   0   2   2   1  50   9]
- [  7   3   4   8   9  14  86]]
-Node Classification on random seed  4874 -> 0.667
-Confusion Matrix:
- [[ 87   1   6   2   4  10   9]
- [  6 136   4   2  12   7   4]
- [ 19  12 164  33  15  31  37]
- [ 21   4   8  96   4   1  13]
- [  1   3   3   1  61   3   3]
- [  8   1   2   0   0  43   6]
- [  5   0   4   8   9  11  80]]
-Node Classification on random seed  4875 -> 0.613
-Confusion Matrix:
- [[ 59   0   9   1   5   8   8]
- [  6 116   6   3  11   5   7]
- [ 34  24 119  28  30  28  58]
- [  5   4  11 119   6   7   9]
- [  2   6   3   1  66   0   1]
- [  2   2   1   1   1  46  10]
- [ 10   3   7   2   7  15  88]]
-Node Classification on random seed  4876 -> 0.618
-Confusion Matrix:
- [[ 62  11   6   3   5  10   7]
- [  3 129   8   3  11   2   4]
- [ 22  17 144  41  18  19  43]
- [  8   4  16 114   3  12  13]
- [  2   7   4   0  55   2   5]
- [  0   2   3   5   1  36   6]
- [ 13   2   6   8   6  21  78]]
-Node Classification on random seed  4877 -> 0.623
-Confusion Matrix:
- [[ 85   3   8   5   3   7   3]
- [  3 135   5   8   8   0   4]
- [ 27  16 146  45  37  19  34]
- [ 10   4  15 108   1   1  13]
- [  4   4   3   3  55   1   3]
- [  2   1   4   1   1  37   3]
- [  9   4  15  15  12  13  57]]
-Node Classification on random seed  4878 -> 0.616
-Confusion Matrix:
- [[ 70   2   3   3   3  10  14]
- [  4 134   4   4   8   4   5]
- [ 24  33 140  33  25  29  28]
- [  5   0  17  90   6   9  13]
- [  3  11   3   1  55   1   5]
- [  6   1   3   1   0  47   6]
- [  5   6  11   4   7  24  80]]
-Node Classification on random seed  4879 -> 0.663
-Confusion Matrix:
- [[ 72   8   4   7   5  10   3]
- [  3 132   3   6   8   0   4]
- [ 21  20 171  40   9  23  28]
- [ 12   4  13 108   1   8   7]
- [  0   8   4   3  62   0   2]
- [  7   1   0   3   3  37   5]
- [ 13   2   6  15   2  16  81]]
-Node Classification on random seed  4880 -> 0.634
-Confusion Matrix:
- [[ 73   0   3   3   1  17   9]
- [  3 120   3   0   8   5   1]
- [ 17  27 146  52  22  31  34]
- [  7   3  15 111   5   4  13]
- [  1   9   3   0  53   2   1]
- [  7   2   1   0   1  57   7]
- [  5   5  12   3   9  15  74]]
-Node Classification on random seed  4881 -> 0.599
-Confusion Matrix:
- [[ 65   1   0   2   5   7  23]
- [  5 129   1   4   4   2   5]
- [ 34  17 129  37  20  23  53]
- [ 11   3  11 103   2   2  18]
- [  2   7   4   2  59   0   1]
- [  6   0   0   0   2  54   9]
- [ 19   5  12   6  13  23  60]]
-Node Classification on random seed  4882 -> 0.601
-Confusion Matrix:
- [[ 65   3   3   8   3  10  12]
- [  6 128   3   2  15   6   4]
- [ 13  24 150  32  31  26  43]
- [ 12   3  18  96   7   7  18]
- [  1   6   4   3  48   3   0]
- [  3   2   3   1   2  44   6]
- [  5   3   4  12   6  26  70]]
-Node Classification on random seed  4883 -> 0.637
-Confusion Matrix:
- [[ 71   9   1   6   3  11   7]
- [  7 133   0   0  13   1   4]
- [ 30  17 120  28  24  30  26]
- [ 12   3  13 130   5   5  15]
- [  1   9   5   4  59   0   2]
- [  8   4   4   2   2  46   1]
- [ 14   5   8   4   6  14  78]]
-Node Classification on random seed  4884 -> 0.623
-Confusion Matrix:
- [[ 67   1   4   7   4  11   8]
- [  4 126   8   6   4   1   7]
- [ 22  13 149  37  31  17  50]
- [ 21   5  14  95   4   6  15]
- [  1   9   4   1  55   1   4]
- [  4   0   2   0   0  58   5]
- [  8   4   7   5   6  16  73]]
-Node Classification on random seed  4885 -> 0.607
-Confusion Matrix:
- [[ 51   0   5   5   5  14   3]
- [  5 130   2   5   5   1   4]
- [ 18  38 124  27  43  27  46]
- [  4   4   6 109   6   9  20]
- [  0   8   3   0  64   0   4]
- [  5   1   1   8   3  50   6]
- [  9   3   8  13  10   9  79]]
-Node Classification on random seed  4886 -> 0.571
-Confusion Matrix:
- [[ 61   1   3   2   6  12   8]
- [  8 136   1   4   2   2   4]
- [ 27  23 133  32  53  27  30]
- [ 25   4  15  72  19   6  13]
- [  1   7   2   1  62   2   0]
- [  9   3   3   1   1  39   9]
- [ 14   4  14   3  14  14  68]]
-Node Classification on random seed  4887 -> 0.599
-Confusion Matrix:
- [[ 53   6   5   1   1  20  13]
- [  5 136   2   6  13   4   3]
- [ 21  16 142  32  37  15  45]
- [  8   8  31  79  11   1  13]
- [  0   8   9   3  60   0   1]
- [  9   1   2   1   1  54   2]
- [ 13   6   5   4   6  13  75]]
-Node Classification on random seed  4888 -> 0.595
-Confusion Matrix:
- [[ 62   0  12  11   5  12   5]
- [  2 140   7   1  12   3   6]
- [ 27  21 148  26  38  22  41]
- [ 24   6   7  75  14   5  19]
- [  1   4   2   3  61   5   4]
- [  1   3   1   8   0  38   4]
- [ 11   0   7   3  12  10  71]]
-Node Classification on random seed  4889 -> 0.638
-Confusion Matrix:
- [[ 75   3   6   4   0  14   5]
- [  9 118   3   2   6   6   8]
- [ 17  22 156  39  28  33  27]
- [  1   8  16 119   1   9   7]
- [  1   6   6   4  45   0  10]
- [  5   1   5   0   0  53   1]
- [ 10   3  11  10   2  13  72]]
-Node Classification on random seed  4890 -> 0.607
-Confusion Matrix:
- [[ 69   3   4   4   1  15  12]
- [  4 119   9   4   8   2   4]
- [ 23  30 145  37  25  15  48]
- [  9   6   8 108   7  10  14]
- [  0   9   8   1  52   2   0]
- [  0   2   2   3   1  42   2]
- [ 17   6  12   5   7  14  72]]
-Node Classification on random seed  4891 -> 0.633
-Confusion Matrix:
- [[ 72   4  10   8   2  12   5]
- [  4 111   6   2   8   3   8]
- [ 20  17 163  27  27  26  42]
- [ 11   1   7 110   6   6  15]
- [  2   5   4   2  45   0   5]
- [  3   0   2   1   1  54   6]
- [ 10   4   6  14  14  11  78]]
-Node Classification on random seed  4892 -> 0.62
-Confusion Matrix:
- [[ 81   4   4   3   1  17  12]
- [  6 121   8   2   1   2  12]
- [ 13  17 144  33  34  34  39]
- [ 12   5  18  98  10   2  11]
- [  1  11   4   0  52   2   3]
- [  3   1   3   1   0  38   6]
- [  3   3   9   5  11  14  86]]
-Node Classification on random seed  4893 -> 0.597
-Confusion Matrix:
- [[ 64   5   0   4   1  15  22]
- [  0 120   2   7  13   2  12]
- [ 15  11 133  45  18  23  62]
- [ 10   3  14  97  10  10  22]
- [  0   3   4   1  55   2   1]
- [  8   0   0   2   0  45   6]
- [  7   6   4   2  11  20  83]]
-Node Classification on random seed  4894 -> 0.625
-Confusion Matrix:
- [[ 76   3   2   6   4  22   6]
- [  3 135   4   2   1   4   5]
- [ 14  26 140  39  16  19  48]
- [ 22   3  18  93   4   6  15]
- [  3  10   2   1  70   0   1]
- [  8   2   3   0   2  34   7]
- [ 15   3   5   6   0  15  77]]
-Node Classification on random seed  4895 -> 0.623
-Confusion Matrix:
- [[ 65   2   6   6   4  13  16]
- [  3 130   8   1   6   0   6]
- [ 20  21 143  31  41  27  39]
- [ 14   3   8 115   1   2   4]
- [  1  10   4   5  55   2   0]
- [  6   0   2   1   1  44   5]
- [  2   5  17   8  12  14  71]]
-Node Classification on random seed  4896 -> 0.642
-Confusion Matrix:
- [[ 61   3   3   3   3  13  12]
- [  6 120  10   4   5   1   5]
- [ 20  25 163  34  20  26  25]
- [  6   3  27 111   0   5  10]
- [  1  10   5   0  55   1   5]
- [  5   1   1   4   3  53   3]
- [ 14   1   7   9   2  17  79]]
-Node Classification on random seed  4897 -> 0.594
-Confusion Matrix:
- [[ 66   2   8   2   5  19   6]
- [  3 135   7   8   7   3   6]
- [ 33  41 126  24  21  31  32]
- [ 15   3  11  80   7   7  14]
- [  1   5   2   1  71   2   2]
- [  1   4   6   8   5  30   2]
- [ 13   4   4  10   2  19  86]]
-Node Classification on random seed  4898 -> 0.534
-Confusion Matrix:
- [[ 64   1   8   4   6  11  14]
- [ 10 114   5   2   5   4   1]
- [ 37  35 122  34  29  27  35]
- [ 29   7  20  80  14   4  25]
- [  4   6   1   3  59   0   2]
- [ 11   2   2   1   5  35   2]
- [ 25   3  13   5   8   6  60]]
-Node Classification on random seed  4899 -> 0.614
-Confusion Matrix:
- [[ 80   6   3   7   2  12   6]
- [  6 118   5   8  12   7   5]
- [ 30  12 137  26  27  16  52]
- [  6   2  13  98   8   7  19]
- [  3   8   5   0  56   2   5]
- [  2   0   1   3   1  39   4]
- [ 16   2   4   3   7  23  86]]
-Node Classification on random seed  4900 -> 0.616
-Confusion Matrix:
- [[ 80   1   4   3   2  11   9]
- [ 11 111   5   1   8   6   7]
- [ 21  14 156  35  20  27  51]
- [  9   8  11  78  15  13  15]
- [  2   1   3   0  57   1   2]
- [  6   0   1   4   0  43   2]
- [ 24   4   8   7   5   7  91]]
-Node Classification on random seed  4901 -> 0.653
-Confusion Matrix:
- [[ 68   4   1  17   2   7   6]
- [  0 126   6   1   6   4   5]
- [ 22  17 161  29  32  18  50]
- [  5   5   6 119   7   5  12]
- [  1   7   2   0  52   1   2]
- [  5   2   1   3   1  48   3]
- [  8   1   8   9  10  16  79]]
-Node Classification on random seed  4902 -> 0.616
-Confusion Matrix:
- [[ 64   2   9   5   2  20   5]
- [  1 142   5   5   6   3   6]
- [ 20  15 154  30  31  25  33]
- [ 22   7  13  96   3   5  12]
- [  1   9   5   2  49   5   1]
- [  7   3   2   1   1  48   4]
- [ 13   4   7  11  11  12  63]]
-Node Classification on random seed  4903 -> 0.549
-Confusion Matrix:
- [[ 72   8   1   3   7   7  14]
- [ 16 101  21   2  12   0   3]
- [ 30  41 102  32  44  15  38]
- [ 13   7  10  93  14   7  13]
- [  2   5   3   0  62   0   3]
- [  3   3   1   2   4  45   6]
- [ 15  11   5  12  12   6  74]]
-Node Classification on random seed  4904 -> 0.635
-Confusion Matrix:
- [[ 80   6   3   4   2  11   7]
- [  2 124   5   6   4   8   0]
- [ 21  23 140  49  17  20  38]
- [  7   4  17 108   1   8   6]
- [  2   7   5   1  66   3   1]
- [  4   0   2   3   3  39   1]
- [  7   4  15  15   7  16  78]]
-Node Classification on random seed  4905 -> 0.624
-Confusion Matrix:
- [[ 69   1   4   7   1  17   8]
- [  7 115   5   2   9   3   3]
- [ 36  19 132  45  26  22  35]
- [  9   4  15 112   0   6   7]
- [  3   5   1   2  73   1   0]
- [  3   0   8   5   3  38   1]
- [  5   0  18   4   9  17  85]]
-Node Classification on random seed  4906 -> 0.595
-Confusion Matrix:
- [[ 63   3   3   7   4  18  15]
- [  6 129  15   0   2   5   5]
- [ 17  24 125  38  31  25  30]
- [ 19   4  14 100   7   8  13]
- [  0   9   3   1  57   1   3]
- [  6   2   1   0   6  37   4]
- [  7   8   7  10   7  17  84]]
-Node Classification on random seed  4907 -> 0.561
-Confusion Matrix:
- [[ 62   0  14   5  11  14   5]
- [  6 105  17   2  13   6   5]
- [ 21  12 129  33  38  33  37]
- [ 16   1  14 100   8  11  14]
- [  1   1   7   7  55   1   1]
- [  7   0   2   0   1  45   6]
- [  8   5  22  18   6  10  65]]
-Node Classification on random seed  4908 -> 0.579
-Confusion Matrix:
- [[ 61   1   6  14   6   9  13]
- [  3 114   3   4  11   5   4]
- [ 25  38 108  55  28  11  39]
- [  6   8  21 105   3  10   6]
- [  3   8   6   3  56   0   2]
- [  3   2   2   2   0  47  16]
- [  6   2  11   7  10   9  88]]
-Node Classification on random seed  4909 -> 0.604
-Confusion Matrix:
- [[ 76   5   4   0   5  13   6]
- [  5 118   5   1   8   7  10]
- [ 35  12 141  58  16  37  20]
- [ 11   0   2 105   4  11  18]
- [  1   9   7   2  52   0   2]
- [ 12   1   5   2   3  37   5]
- [ 14   7   6   1  10  16  75]]
-Node Classification on random seed  4910 -> 0.583
-Confusion Matrix:
- [[ 71   1   3   7   6  13  10]
- [  2 129   7   5   9   5   2]
- [ 30  25 130  41  16  24  41]
- [ 26   5  29  74   3   5  12]
- [  0  10   7   0  62   1   6]
- [  2   2   2   4   1  47   4]
- [  7   9   8   5   3  19  70]]
-Node Classification on random seed  4911 -> 0.592
-Confusion Matrix:
- [[ 75   4   5   6   2   5  19]
- [  1 134   9   3   7   2  11]
- [ 33  23 132  31  24  16  48]
- [ 13   4  23  90   5   6   8]
- [  1   7   4   1  61   1   1]
- [  5   5   4   4   0  51   6]
- [ 11   0  16  12   9  13  49]]
-Node Classification on random seed  4912 -> 0.619
-Confusion Matrix:
- [[ 65   6   6   5   3  10  23]
- [  1 137   5   2   2   3   3]
- [ 27  15 163  23  35  13  40]
- [ 12   3  24 102   3   7  17]
- [  1  11   5   0  57   1   2]
- [  9   2   2   2   2  27   5]
- [ 11   5  11   5   9  10  68]]
-Node Classification on random seed  4913 -> 0.593
-Confusion Matrix:
- [[ 68   0   6   6   7  14   3]
- [ 10 117   7   4  16   2   7]
- [ 20  13 144  35  36  23  49]
- [ 13   4  18  76  10   9  17]
- [  2   4   1   1  62   0   5]
- [  5   2   3   2   3  42   7]
- [  8   0  11   6   4  14  84]]
-Node Classification on random seed  4914 -> 0.592
-Confusion Matrix:
- [[ 61   2   7   7   1   7  23]
- [  5 122   1   4   2   2   3]
- [ 34  35 147  33  24  17  37]
- [ 15   7  25  91   7   2  20]
- [  2  10   3   2  49   2   1]
- [  8   3   5   1   0  44   2]
- [ 17   1  12   7   4   8  78]]
-Node Classification on random seed  4915 -> 0.61
-Confusion Matrix:
- [[ 70   1   2   5   3  20   6]
- [  2 141   5   4   4   2   3]
- [ 20  23 132  44  26  10  49]
- [ 15   6   6  95   5   5  21]
- [  0  14   5   1  40   2   1]
- [ 12   2   0   0   0  55   4]
- [ 11   5  10  10   8  18  77]]
-Node Classification on random seed  4916 -> 0.636
-Confusion Matrix:
- [[ 65   1  10   5   1  14  11]
- [  4 120   4   0   7   2   2]
- [ 39  20 144  34  32   9  42]
- [  9   5  18 116   4   4  16]
- [  3   5   2   0  66   1   3]
- [  3   3   2   0   2  45   7]
- [  3   1   9   6  13   8  80]]
-Node Classification on random seed  4917 -> 0.609
-Confusion Matrix:
- [[ 66   5  17   4   5  24   5]
- [  6 126   0   5  10   5   3]
- [ 32  34 135  33  28  29  24]
- [  5   6  15  99  11   5   7]
- [  2   8   5   1  58   0   3]
- [  1   0   1   1   1  52   1]
- [  5   1  12   4   7  20  73]]
-Node Classification on random seed  4918 -> 0.605
-Confusion Matrix:
- [[ 69   1   5   4   5  14  13]
- [  6 135   5   1   8   2   3]
- [ 26  35 139  21  30  28  26]
- [  9   7  29  86   5   6   5]
- [  1  11   1   2  62   2   2]
- [  8   1   3   0   1  43   3]
- [ 15   4   4  12  11  20  71]]
-Node Classification on random seed  4919 -> 0.619
-Confusion Matrix:
- [[ 81   0   3   1   2  13  14]
- [  3 129   3   3   4   7   4]
- [ 14  22 144  39  33  19  41]
- [ 10   2   9  96   3   5  19]
- [  4   8   3   2  60   1   2]
- [  4   1   0   2   6  39   9]
- [ 14   3  11   4   9  25  70]]
-Node Classification on random seed  4920 -> 0.638
-Confusion Matrix:
- [[ 63   2   3   7   4  13  13]
- [  5 151   5   0  10   1   2]
- [ 14  37 154  23  16  31  35]
- [ 21   4  14  98   5   2  15]
- [  0   5   6   1  61   3   4]
- [  5   1   7   2   2  29   7]
- [  5   2   8   5   5  12  82]]
-Node Classification on random seed  4921 -> 0.602
-Confusion Matrix:
- [[ 78   8   4   7   7   9   7]
- [  2 113   4   7   4   7   1]
- [ 36  40 120  33  23  28  42]
- [ 14   2  16 114   6   2  14]
- [  1   6   2   2  60   1   2]
- [  7   0   1   0   2  46   4]
- [ 18   4   4   6   5  10  71]]
-Node Classification on random seed  4922 -> 0.583
-Confusion Matrix:
- [[ 57   2   0  15   4  14   8]
- [  5  95   9   1  25   4   3]
- [ 17  10 160  29  28  31  62]
- [ 14   3  19 104   4   2  10]
- [  3   3   5   4  57   2   2]
- [  3   0   4   5   2  41   9]
- [  9   3   8  11   7  18  69]]
-Node Classification on random seed  4923 -> 0.62
-Confusion Matrix:
- [[ 73   3   3   9   6   9  17]
- [  4 130   6   4   3   1   4]
- [ 24  20 148  37  33  16  22]
- [  9   3  20 107   5   4  18]
- [  0   6   4   1  56   0   2]
- [  6   2   2   4   5  27   8]
- [  9   5   7  17   8  14  79]]
-Node Classification on random seed  4924 -> 0.594
-Confusion Matrix:
- [[ 70   1   5   5   5  18   3]
- [  7 118   7   3   9   6   2]
- [ 40  24 126  50  21  21  35]
- [ 10   2  11 105  12   8  12]
- [  3   5   2   1  56   1   1]
- [  3   0   2   2   3  49   7]
- [ 13   0  15   7   5  19  70]]
-Node Classification on random seed  4925 -> 0.622
-Confusion Matrix:
- [[ 71   5   3   3   1  10   8]
- [  4 125   7   1  10   1   3]
- [ 18  29 149  41  29  24  32]
- [ 13   5   9  98   9   6   3]
- [  5  10   5   0  69   2   4]
- [  0   4   5   0   2  38   5]
- [  5   8   8   9   7  25  72]]
-Node Classification on random seed  4926 -> 0.63
-Confusion Matrix:
- [[ 80   1   2   5   6  18   8]
- [  6 122   2   4  15   3   6]
- [ 21  17 142  31  14  39  38]
- [  6   0  10 107   6   5   9]
- [  1   5   5   2  51   4   3]
- [  8   0   2   3   3  40   9]
- [  9   5   9   4   8  18  88]]
-Node Classification on random seed  4927 -> 0.622
-Confusion Matrix:
- [[ 57   5   7   4   4  19   8]
- [  4 144   7   2   6   0   6]
- [ 20  32 125  22  17  27  53]
- [ 13   0  11 114  10   5  12]
- [  1   6   5   0  58   2   1]
- [  2   2   1   0   0  46   8]
- [ 14   6   8   9   6  13  78]]
-Node Classification on random seed  4928 -> 0.641
-Confusion Matrix:
- [[ 76   2   3   4   6  15   8]
- [  1 125   5   3   6   1   3]
- [ 30  17 135  48  21  24  39]
- [ 22   1   4 113   4   5   5]
- [  1   6   6   2  47   2   4]
- [  4   0   2   7   0  59   1]
- [ 11   6   9   2   4  15  86]]
-Node Classification on random seed  4929 -> 0.625
-Confusion Matrix:
- [[ 87   1   5   3   6   6   6]
- [  7 136   3   5  13   3   4]
- [ 27  23 108  39  29  17  36]
- [ 16   3  14 118   7   1  14]
- [  1   4   1   2  57   0   2]
- [  7   0   2   1   3  43   6]
- [ 21   2   7   3  13  12  76]]
-Node Classification on random seed  4930 -> 0.592
-Confusion Matrix:
- [[ 73   3  13   4   2   8   9]
- [  1 113  13   2   9   5   3]
- [ 34  24 136  36  28  30  38]
- [ 21   2  17  99   4   5   6]
- [  3   8   5   0  60   0   1]
- [  9   0   4   0   0  44   3]
- [ 14   2  16   4   9  13  67]]
-Node Classification on random seed  4931 -> 0.662
-Confusion Matrix:
- [[ 74   2   5   9   4  11   2]
- [  3 142   4   3   7   2   0]
- [ 28  21 148  41  23  14  35]
- [ 12   4   7  99   8   8  17]
- [  1   6   5   0  58   0   2]
- [  6   0   0   0   1  51   4]
- [ 11   2   1   5  15   9  90]]
-Node Classification on random seed  4932 -> 0.61
-Confusion Matrix:
- [[ 70   2   9  11   1   6  14]
- [  1 146   1   3   1   1   7]
- [ 33  29 112  39  19  27  38]
- [  4   5   9 109   1  17  19]
- [  2  10   4   3  49   2   4]
- [  4   1   3   1   0  46   7]
- [  7   3  11   6  14  11  78]]
-Node Classification on random seed  4933 -> 0.589
-Confusion Matrix:
- [[ 79   2  14   2   1  11   2]
- [  3 124   8   9   5   2   8]
- [ 22  30 127  34  32  30  37]
- [ 20   3  20  89   2  10  12]
- [  5   5   1   6  49   1   4]
- [  5   0   3   6   0  40   0]
- [  6   9   2  12   2  25  81]]
-Node Classification on random seed  4934 -> 0.63
-Confusion Matrix:
- [[ 63   3  10  14   3   5   3]
- [  5 140  12   1   3   4   2]
- [ 23  32 140  37  25  19  25]
- [ 10   7  11 104   5   3  11]
- [  1   3   4   0  63   1   4]
- [  5   0   2   1   2  49  11]
- [ 14   8  11  11   6  13  71]]
-Node Classification on random seed  4935 -> 0.607
-Confusion Matrix:
- [[ 58   0   3  15   4  10   5]
- [  3 122  10   2  17   2   9]
- [ 23   9 147  35  21  30  36]
- [  6   6  22 103  12   6   6]
- [  1   8   5   2  63   2   2]
- [  8   1   5   6   0  47   4]
- [  4   2  16  13   4  18  67]]
-Node Classification on random seed  4936 -> 0.646
-Confusion Matrix:
- [[ 85   4   1   4   0   6  11]
- [  3 133   3   4   6   3   2]
- [ 19  22 156  56  19  13  31]
- [ 13   4  19  95   4   4  14]
- [  5   7   2   3  66   2   0]
- [  2   1   2   0   1  46  11]
- [  8   2  11  11   4  17  65]]
-Node Classification on random seed  4937 -> 0.595
-Confusion Matrix:
- [[ 56   1   5  13   6   2  20]
- [ 10 103  15   3   8   1   5]
- [ 11  17 124  48  57  18  38]
- [ 10   6  15 108   2   3  10]
- [  0   8   1   2  57   2   0]
- [  7   4   1   0   1  55   8]
- [ 10   9   8   5  10   5  92]]
-Node Classification on random seed  4938 -> 0.592
-Confusion Matrix:
- [[ 76   3   7   4   4  18   4]
- [  1 125   5   2   9   2   1]
- [ 21  24 117  58  19  10  43]
- [ 16  11  16  89   4  24  17]
- [  0   4   2   1  54   2   2]
- [  8   1   0   0   0  54   8]
- [ 12   6   9   1   6  23  77]]
-Node Classification on random seed  4939 -> 0.625
-Confusion Matrix:
- [[ 73   1   5   2   3  21   4]
- [  3 132   3   8   5   0   2]
- [ 30  17 139  44  23  25  24]
- [  9   5   8 115  11  13  11]
- [  0   3   3   4  55   2   2]
- [  1   2   2   1   0  44   4]
- [ 11   5  19   5  12  22  67]]
-Node Classification on random seed  4940 -> 0.619
-Confusion Matrix:
- [[ 68   2   3   9   4  10  20]
- [  3 127   9   1  12   4   8]
- [ 38  16 129  26  40  24  30]
- [  7   5  16 105   2   3  13]
- [  1   4   2   2  76   0   3]
- [  5   0   2   2   0  48   4]
- [  5   2   9  11   7  17  66]]
-Node Classification on random seed  4941 -> 0.623
-Confusion Matrix:
- [[ 64   3   2   6   3  12  19]
- [  7 122   4   2  12   1   1]
- [ 30  14 154  32  37  19  45]
- [ 12   4  21  92   1   4   8]
- [  2   5   5   2  53   0   2]
- [  6   1   5   1   0  57   4]
- [ 13   3   8   4   8   9  81]]
-Node Classification on random seed  4942 -> 0.555
-Confusion Matrix:
- [[ 80   3   1   8   6   5  13]
- [  7 115   7   3   8   3   3]
- [ 24  20  85  49  77  17  46]
- [  5   4  22  92   5   7   7]
- [  1   4   2   1  65   1   3]
- [  8   2   6   0   0  39   5]
- [ 13   5   9   8  12  15  79]]
-Node Classification on random seed  4943 -> 0.614
-Confusion Matrix:
- [[ 69   1   5   7  10   7   2]
- [  4 130   3   2  11   1   3]
- [ 29  29 152  44  15  29  22]
- [ 19   2  10 102   1  10  10]
- [  0   6   6   0  60   2   2]
- [  7   8   3   5   1  37   7]
- [ 26   3  10   6   6  12  64]]
-Node Classification on random seed  4944 -> 0.613
-Confusion Matrix:
- [[ 71   7   4   3   5  17   7]
- [  5 124   6   1   3   4   3]
- [ 13  20 143  49  21  34  37]
- [  8  13  27  78   5   4  13]
- [  4   7   6   1  61   0   1]
- [  2   0   2   2   1  57   2]
- [  7   7   8   4   6  18  79]]
-Node Classification on random seed  4945 -> 0.617
-Confusion Matrix:
- [[ 83   1   6   8   3  12   5]
- [  0 141   9   4   8   2   3]
- [ 21  23 124  43  19  27  34]
- [  5   3  13  95  12   4  19]
- [  0   4   0   2  70   4   4]
- [ 10   2   4   3   3  34   2]
- [ 18   4   9   5   9  16  70]]
-Node Classification on random seed  4946 -> 0.65
-Confusion Matrix:
- [[ 92   4   3   2   0   7   2]
- [  9 131   5   2   6   5   2]
- [ 24  23 159  19  35  42  35]
- [  4   4  11  92   4   3  14]
- [  1   5   3   2  56   3   1]
- [  7   0   1   0   0  35   7]
- [ 19   6   5   6   8  11  85]]
-Node Classification on random seed  4947 -> 0.573
-Confusion Matrix:
- [[ 76   2   9   3   7   8  13]
- [  9 112   3   3  14   5   3]
- [ 28  14 146  31  35  35  22]
- [ 10   2  25  89   4  12  20]
- [  1   3   5   4  50   2   4]
- [ 13   1   1   1   2  37   6]
- [ 10   3   7   6   6  35  63]]
-Node Classification on random seed  4948 -> 0.563
-Confusion Matrix:
- [[ 72   6   9   4   3  21   8]
- [  4 103   7   1   7   2   5]
- [ 35  20 112  43  48  29  31]
- [ 12   5  15 100   5   6  13]
- [  0   8   1   4  60   1   1]
- [  7   2   5   0   0  46   5]
- [ 21   3  11   6   7  16  70]]
-Node Classification on random seed  4949 -> 0.616
-Confusion Matrix:
- [[ 74   4   1   4   2   4  17]
- [  4 111   2   4  12   5   2]
- [ 23  29 144  40  28  32  24]
- [ 14   6   8  99   3   4  23]
- [  0   6   2   4  66   0   1]
- [ 10   2   6   0   0  41   9]
- [ 16   4   6   9   8   6  81]]
-Node Classification on random seed  4950 -> 0.63
-Confusion Matrix:
- [[ 51   3   3   9   9  17  17]
- [  3 112   4   3  12   6   3]
- [ 23  36 158  23  31  21  26]
- [  5   3  11 112   7   4  12]
- [  2   6   3   0  66   2   5]
- [  7   1   0   0   1  50   3]
- [ 11   1   9   2   8  18  81]]
-Node Classification on random seed  4951 -> 0.635
-Confusion Matrix:
- [[ 60   1  12   4   1  13  13]
- [  7 126   3   0   2   3   4]
- [ 36  22 166  24  10  26  37]
- [ 14   8  11 111   1   8  14]
- [  0  12   2   2  58   3   2]
- [  3   3   2   0   0  45   5]
- [ 16   2  16   5   6  12  69]]
-Node Classification on random seed  4952 -> 0.633
-Confusion Matrix:
- [[ 87   0   4   9   6  11   8]
- [  4 125   9   2   3   6   2]
- [ 28  11 152  33  30  20  42]
- [  9   7  11  94   4   3  14]
- [  1  11   8   2  62   0   2]
- [  8   0   2   1   0  35   4]
- [ 13   3   5   5  17   9  78]]
-Node Classification on random seed  4953 -> 0.564
-Confusion Matrix:
- [[ 66   8   6   2   5  10  20]
- [  1 109   4   6   8   1   5]
- [ 23  24 130  38  26  14  52]
- [ 13   1  11  91   4   7  32]
- [  0   9   2   3  58   0   7]
- [  9   4   2   2   0  47   4]
- [  7   8   7   9  24  18  63]]
-Node Classification on random seed  4954 -> 0.57
-Confusion Matrix:
- [[ 70  12   3   4   7  11  12]
- [  6 135   4   6   6   2   3]
- [ 28  28 119  30  43  26  45]
- [ 15   8  14 101   4   7   4]
- [  0  10   5   2  51   0   0]
- [ 14   2   3   1   1  33   2]
- [ 12   3  11   7  14  15  61]]
-Node Classification on random seed  4955 -> 0.604
-Confusion Matrix:
- [[ 76   4   4   8   5  13  11]
- [  9 125   8   2   8   4   2]
- [ 24  28 122  25  37  28  39]
- [  8   6  10  96   1   7  28]
- [  1   7   4   1  69   2   3]
- [  4   3   2   0   1  46   3]
- [ 11   4   6  11   4  10  70]]
-Node Classification on random seed  4956 -> 0.611
-Confusion Matrix:
- [[ 73   3   6   6   6   9   6]
- [  3 123   3   5   5   4   1]
- [ 22  16 151  46  36  11  26]
- [ 11   2  33  96   7   6   9]
- [  3   7   8   5  57   1   1]
- [  9   1   7   1   1  49   2]
- [ 16   3   5  16   7  14  62]]
-Node Classification on random seed  4957 -> 0.606
-Confusion Matrix:
- [[ 69   4   4   4   2  15  18]
- [  3 112   6   1   2   5   6]
- [ 21  37 128  48  19  21  46]
- [ 13   5  10  97   6   6  10]
- [  0   9   7   1  61   0   2]
- [  7   1   5   4   0  46   2]
- [  6   4  10  12   4   8  93]]
-Node Classification on random seed  4958 -> 0.598
-Confusion Matrix:
- [[ 53   4  15   8   7   8   5]
- [  1 130   4   2   7   0   7]
- [ 37  25 138  40  19  36  36]
- [ 11   8  20  95   5   8  14]
- [  2   9   4   1  65   0   3]
- [  9   1   6   0   2  48   1]
- [  3   4  14   2   2  12  69]]
-Node Classification on random seed  4959 -> 0.617
-Confusion Matrix:
- [[ 65   2   7  10   5  11   5]
- [  4 125   9   7   8   6   5]
- [ 24  15 152  19  54  24  28]
- [ 12   3  23  99   7   6   4]
- [  0   1   4   2  68   0   1]
- [  6   1   1   3   1  40   9]
- [  3   3  10  12  13  15  68]]
-Node Classification on random seed  4960 -> 0.579
-Confusion Matrix:
- [[ 67   3   5   1   2  23   8]
- [  6 118   7   4   6   0   2]
- [ 17  32 109  46  31  34  50]
- [ 20   3  13 100   4   9  10]
- [  0   7   3   7  58   1   1]
- [ 10   4   2   1   0  43   4]
- [  8   3  15   3   2  14  84]]
-Node Classification on random seed  4961 -> 0.603
-Confusion Matrix:
- [[ 84   5   0   3   2   9   7]
- [  9 125   4   3   4   2   4]
- [ 27  25 101  30  57  21  35]
- [ 15   6  17  87  14   2  12]
- [  1   4   1   3  63   0   2]
- [  6   1   0   0   1  53   5]
- [  8   7   5  17   8  15  90]]
-Node Classification on random seed  4962 -> 0.62
-Confusion Matrix:
- [[ 68   1   0   0   3  15  10]
- [  3 124   8   3   7   4   4]
- [ 19  25 143  49  20  24  35]
- [  7   6  19 106   5   8  10]
- [  2   6   6   4  64   1   5]
- [  2   1   4   0   0  40   8]
- [  2   8  15   6   5  20  75]]
-Node Classification on random seed  4963 -> 0.653
-Confusion Matrix:
- [[ 88   3   5   2   2   5   8]
- [ 10 116   5   2   6   1   5]
- [ 21  19 168  39  17  26  30]
- [ 11   4  14  99   5   7  19]
- [  2   6   7   0  57   0   4]
- [  4   0   3   0   2  43   7]
- [ 14   2   6   1   3  20  82]]
-Node Classification on random seed  4964 -> 0.616
-Confusion Matrix:
- [[ 65   1  13   9   2  13  14]
- [  4 128   5   1   8   0   5]
- [ 35  25 134  51  18  22  27]
- [  7   8  19 106   3   5  11]
- [  4   5   6   1  50   0   1]
- [  3   1   5   2   0  47   5]
- [ 13   3   5  13   5   6  86]]
-Node Classification on random seed  4965 -> 0.624
-Confusion Matrix:
- [[ 83   5   1   4   4   6  11]
- [  7 120   1   2   3   0   3]
- [ 39  21 138  38  28  13  47]
- [ 15   1  15  97  10   3  12]
- [  1   7   3   1  64   0   1]
- [  8   0   2   1   1  48   5]
- [ 22   8  13   3   5   6  74]]
-Node Classification on random seed  4966 -> 0.571
-Confusion Matrix:
- [[ 84   1   7   5  12  15   4]
- [  4 125   5   4   3   3   2]
- [ 25  17 129  48  37  22  48]
- [  9   4  23  75  11  14  11]
- [  1   7   3   6  50   1   3]
- [  3   0   2   4   3  42   4]
- [ 17   5   5   4  10  17  66]]
-Node Classification on random seed  4967 -> 0.645
-Confusion Matrix:
- [[ 69   3   1   6   3   9  13]
- [  1 135   1   5   3   5   3]
- [ 23  29 152  16  23  15  61]
- [  6   3  25  90   5  10  24]
- [  0   6   4   1  66   2   5]
- [  8   0   3   0   0  41   9]
- [  4   2   2   4   4   8  92]]
-Node Classification on random seed  4968 -> 0.578
-Confusion Matrix:
- [[ 72   6   5   3   2   8  15]
- [  5 112   4   1   6   6   5]
- [ 23  39 101  39  56  16  36]
- [  9   8  16  95   4   9   9]
- [  3   7   2   0  65   0   3]
- [  7   2   4   3   0  51   3]
- [  5   9   5  11  18  10  82]]
-Node Classification on random seed  4969 -> 0.629
-Confusion Matrix:
- [[ 72   1   2   4   3   9  15]
- [  5 135   3   3   8   1   4]
- [ 23  19 164  23  22  17  43]
- [ 14   8  17 102   2  10  12]
- [  1  11   0   3  57   0   3]
- [  7   1   2   5   0  33  14]
- [ 13   3  17  10   2  11  66]]
-Node Classification on random seed  4970 -> 0.615
-Confusion Matrix:
- [[ 66   5   2   5   4  16   4]
- [  2 139   2   2   9   4   3]
- [ 12  30 147  44  25  28  23]
- [ 15   5  22  88   7   4  18]
- [  0   5   4   0  58   5   4]
- [  5   1   1   1   1  45   3]
- [  6   5  17   7   8  21  72]]
-Node Classification on random seed  4971 -> 0.652
-Confusion Matrix:
- [[ 68   0  12   6   3  10   7]
- [  3 123   9   1   7   3   5]
- [ 24  14 176  30  19  22  36]
- [  6   1  22 106   6   6  16]
- [  2   4   6   2  53   0   8]
- [  4   0   3   0   0  47   5]
- [  9   4  12   6   1  14  79]]
-Node Classification on random seed  4972 -> 0.621
-Confusion Matrix:
- [[ 64   0   2   3   3  18  20]
- [ 10 132  11   2   4   5   4]
- [ 17  20 130  53  21  24  42]
- [  7   5  10 103   2   6   8]
- [  2   5   7   4  63   1   2]
- [  4   0   1   1   2  55   9]
- [  6   5   2   9   2  20  74]]
-Node Classification on random seed  4973 -> 0.619
-Confusion Matrix:
- [[ 93   0   0   3   8  10   4]
- [  2 121   2   5  11   1   8]
- [ 23  25 132  25  31  17  48]
- [ 14   4  31  93   4  10  11]
- [  1   9   1   6  62   1   1]
- [  1   2   1   2   0  44   3]
- [ 10   1   4   8   7  26  74]]
-Node Classification on random seed  4974 -> 0.604
-Confusion Matrix:
- [[ 76   5   3   3   6   6  20]
- [  5 137   2   2  11   3   7]
- [ 24  26 125  40  30  26  29]
- [ 16   3  12 104   5  10   7]
- [  3   8   4   1  55   1   3]
- [  6   1   2   2   3  38   6]
- [ 15   4  13   5   6  12  69]]
-Node Classification on random seed  4975 -> 0.593
-Confusion Matrix:
- [[ 52   5   2   6   2  21  13]
- [  4 136   5   1  14   2   3]
- [ 20  21 125  36  34  27  46]
- [ 18   4   6 100   2   3  26]
- [  1   4   3   3  70   0   1]
- [  5   1   2   0   5  42   6]
- [  6   0   6   7  14  22  68]]
-Node Classification on random seed  4976 -> 0.61
-Confusion Matrix:
- [[ 71   9   2   8   2   4  10]
- [  6 120   5   0  18   2   4]
- [ 44  25 135  25  35  23  17]
- [  9   3  19  98   6   5  16]
- [  1   4   3   3  62   1   3]
- [  5   1   4   1   2  48   6]
- [ 21  10   7   6   5  10  76]]
-Node Classification on random seed  4977 -> 0.632
-Confusion Matrix:
- [[ 80   2   7   5   2   6   8]
- [  4 136   2   4   6   1   4]
- [ 29  18 132  52  21  16  29]
- [ 10   1  15 104   9  10  12]
- [  0   4   2   2  60   1   4]
- [  4   0   9   5   0  44   4]
- [ 10   0   7  22   7  14  76]]
-Node Classification on random seed  4978 -> 0.579
-Confusion Matrix:
- [[ 49   3   7   7   4  16  30]
- [  3 122   8   3   1   5   3]
- [ 25  17 124  35  43  25  42]
- [  4   5  18 104   2   5  19]
- [  1   7   4   3  64   0   3]
- [  2   2  10   1   0  36  11]
- [ 13   3  10   4   4  13  80]]
-Node Classification on random seed  4979 -> 0.655
-Confusion Matrix:
- [[ 72   4   3   4   6   4  20]
- [  8 125   2   3   8   1   2]
- [ 19  19 163  35  18  16  36]
- [ 10   2  19 105   4  11   7]
- [  2   9   2   2  58   0   5]
- [  4   3   0   1   1  43   4]
- [ 14   5   8  10   5   9  89]]
-Node Classification on random seed  4980 -> 0.621
-Confusion Matrix:
- [[ 77   4   2   4   7   4  21]
- [  9 111   9   1   7   3   6]
- [ 19  12 153  23  34  22  56]
- [ 12  10  17 101   2   3  10]
- [  2   6   4   3  58   2   3]
- [  2   2   2   0   0  45   5]
- [ 10   5   8   7   5  16  76]]
-Node Classification on random seed  4981 -> 0.567
-Confusion Matrix:
- [[ 78   5   3   5   7   8   8]
- [  4 111   8   6  12   2   7]
- [ 28  12 135  63  22  29  30]
- [ 13   2  13  88   4  12  17]
- [  0   2   6   2  52   0   3]
- [ 10   2   8   1   0  41   9]
- [ 12   4  13  12   7  22  62]]
-Node Classification on random seed  4982 -> 0.596
-Confusion Matrix:
- [[ 65   2  12   3   4  13   6]
- [ 10 124   9   3   6   3   5]
- [ 41  29 110  39  33   8  50]
- [ 10   3  10 105   4   5  14]
- [  2   5   1   3  59   1   3]
- [  5   1   2   2   5  46   2]
- [ 14   3   7   1   6  19  87]]
-Node Classification on random seed  4983 -> 0.625
-Confusion Matrix:
- [[ 65   7   1   3   3   9  10]
- [  9 121   2   5  11   4  10]
- [ 15  19 144  35  35  32  41]
- [ 17   4  13  97   6   7   7]
- [  0   4   4   0  60   0   1]
- [  7   0   2   3   2  47   3]
- [  5   5  10   5   4  15  91]]
-Node Classification on random seed  4984 -> 0.657
-Confusion Matrix:
- [[ 85   7   2   2   3   5  13]
- [  4 141   6   0   3   2   5]
- [ 12  26 177  26  13  44  28]
- [  6   4  22  93   5   2  22]
- [  1  11   4   2  45   2   1]
- [  1   2   2   1   0  41   6]
- [  6   9   6   5   2  20  75]]
-Node Classification on random seed  4985 -> 0.605
-Confusion Matrix:
- [[ 59   7   3   6   6   8  11]
- [  7 138   5   5   9   4   2]
- [ 33  13 126  47  17  23  51]
- [  8   9  14 106   3   3  17]
- [  4   5   1   2  57   4   1]
- [  4   2   0   4   0  38   6]
- [ 11   4   7  13   4  12  81]]
-Node Classification on random seed  4986 -> 0.601
-Confusion Matrix:
- [[ 84   3   7   7   4   6   3]
- [  5 113   5   5  10   0   2]
- [ 34  17 138  30  31  25  43]
- [ 23   5  19  90  10   5   7]
- [  2  12   2   4  50   1   0]
- [  4   1   5   3   0  52   1]
- [ 17   4  16   4   4  13  74]]
-Node Classification on random seed  4987 -> 0.605
-Confusion Matrix:
- [[ 74   1   4   4  10  15  10]
- [  6  99   3  10   5   3   5]
- [ 25  13 149  39  25  16  43]
- [ 19   2  15 101  14  12   8]
- [  3   2   2   0  66   0   1]
- [ 11   2   1   0   2  40   5]
- [  9   2  11  10  13  14  76]]
-Node Classification on random seed  4988 -> 0.622
-Confusion Matrix:
- [[ 59   2  10   9   4  18   7]
- [  4 121   8   3   5   1   5]
- [ 19  22 166  38  30  21  30]
- [  7  10  10  98   5   3  20]
- [  2   1   1   1  63   0   2]
- [  2   2   1   2   3  41   8]
- [ 13   6  13  13   3  14  74]]
-Node Classification on random seed  4989 -> 0.582
-Confusion Matrix:
- [[ 81   3   4   3   6  13   9]
- [  6 113  11   2  14   0   1]
- [ 24  22 126  35  36  29  41]
- [  9   7  19  80   7  16  25]
- [  0   5   1   5  65   0   3]
- [  4   0   1   0   1  52   3]
- [ 13   4   5   2  10  19  65]]
-Node Classification on random seed  4990 -> 0.613
-Confusion Matrix:
- [[ 75   3   4   3   4  11  11]
- [  3 128   6   2   8   3   5]
- [ 20  29 124  27  23  33  51]
- [ 14   4  10 111   1  11  13]
- [  3   4   7   1  51   0   1]
- [  5   3   3   1   1  39   5]
- [  8  10   8   3   9  16  85]]
-Node Classification on random seed  4991 -> 0.632
-Confusion Matrix:
- [[ 78   2   8   2   3   6  11]
- [  5 137   3   5  11   0   3]
- [ 32  18 120  37  34  13  44]
- [  7   0  14 105  20   5   8]
- [  1   4   4   1  64   0   3]
- [  5   0   2   0   0  43   7]
- [  7   4   5  14  12   8  85]]
-Node Classification on random seed  4992 -> 0.62
-Confusion Matrix:
- [[ 79  11   0   8   3  12  10]
- [  4 113   2   2  11   6   1]
- [ 24  14 126  38  23  23  51]
- [ 18   1  14 104   9   4  13]
- [  1   6   4   0  70   0   1]
- [  8   1   1   0   0  42   5]
- [ 12   2   9   4  12  12  86]]
-Node Classification on random seed  4993 -> 0.566
-Confusion Matrix:
- [[ 70   3   8   2   8   7   8]
- [  2 130   8   1  14   7   5]
- [ 34  31 128  25  70  21  19]
- [ 13   5  17  87  13   6  15]
- [  0   8   2   0  53   1   4]
- [  8   1   2   3   0  44   6]
- [ 13   3  16   2  12  11  54]]
-Node Classification on random seed  4994 -> 0.635
-Confusion Matrix:
- [[ 78   0   7   1   3  13   7]
- [  6 124   5   1  11   3   6]
- [ 29  17 157  19  32  16  37]
- [ 15   2  18  98   7   4  10]
- [  0   5   6   2  62   1   2]
- [  5   0   5   1   1  45  10]
- [ 13   2  16   6  11  10  71]]
-Node Classification on random seed  4995 -> 0.614
-Confusion Matrix:
- [[ 68   1   5  14   6   9  10]
- [  3 126   5   1   2   5   5]
- [ 14  25 146  36  25  22  54]
- [ 20   5  13  95   4   5  10]
- [  1  13   3   2  66   0   4]
- [ 10   1   0   1   0  39   4]
- [  9   2  10  12   2  13  74]]
-Node Classification on random seed  4996 -> 0.605
-Confusion Matrix:
- [[ 72   3   0   5   3  14   3]
- [ 10 110   7   5   7   5   5]
- [ 31  27 138  29  18  13  44]
- [ 13   1  16 103  13   5  12]
- [  3   4   3   1  70   0   5]
- [  9   1   2   8   1  24  10]
- [ 18   6  11   9   7   8  88]]
-Node Classification on random seed  4997 -> 0.645
-Confusion Matrix:
- [[ 72   6   4   8   1   9  10]
- [  5 140  11   2   4   0   5]
- [ 12  25 156  34  27  12  38]
- [ 11   6  20 107   2   2  11]
- [  2   4   4   0  60   0   6]
- [  6   5   5   1   8  36   4]
- [  5   5   4   3   8  20  74]]
-Node Classification on random seed  4998 -> 0.62
-Confusion Matrix:
- [[ 75   1   3   2   3  12   4]
- [  2 120   7   2   4   1   5]
- [ 14  28 137  38  29  18  45]
- [ 14   0  17  99   9  11   8]
- [  2  15   3   2  51   0   1]
- [  3   5   2   0   0  57   6]
- [ 11   5  18   2   8  20  81]]
-Node Classification on random seed  4999 -> 0.634
-Confusion Matrix:
- [[ 58   8   4   4   3  18  16]
- [  4 142   4   2   4   4   4]
- [  6  24 139  18  31  21  57]
- [  3   5  19 116   6   6   7]
- [  1   9   3   2  63   1   2]
- [  2   1   2   4   0  38  10]
- [ 10   4  10   6  10  11  78]]
-Node Classification on random seed  5000 -> 0.63
-Confusion Matrix:
- [[ 73   4   1  12   5  10   8]
- [  4 123   6   1  10   0   2]
- [ 15  16 160  49  30  23  51]
- [  5   2  16 100   6   5  16]
- [  3   4   3   3  55   0   0]
- [  2   0   1   3   0  41   6]
- [ 12   5   6   7   9   9  78]]
-Node Classification on random seed  5001 -> 0.549
-Confusion Matrix:
- [[ 67   4   6   7   4   8  15]
- [  4 148   5   1   8   1   3]
- [ 35  25  68  68  40  30  36]
- [ 20   4   8  92   9   6  16]
- [  1   9   5   2  55   3   3]
- [ 11   0   1   2   0  41   7]
- [  9   0  17   5   6   7  78]]
-Node Classification on random seed  5002 -> 0.616
-Confusion Matrix:
- [[ 79   5   2   4   1   8   6]
- [  2 124   7   7  10   2   5]
- [ 33  19 142  32  28  16  41]
- [ 12   6  22 101   6   8  11]
- [  1   2   3   4  61   2   1]
- [  7   3   3   0   0  40   8]
- [ 26   7  10   2   7   5  69]]
-Node Classification on random seed  5003 -> 0.58
-Confusion Matrix:
- [[ 78   0  16   2   3   9   3]
- [ 13 119   5   3   1   2   2]
- [ 34  28 111  65  17  19  33]
- [ 12   7   8  87   3   4  31]
- [  0   6   4   4  63   1   0]
- [ 10   1   2   3   7  44   6]
- [ 21   4  14   2   4  11  78]]
-Node Classification on random seed  5004 -> 0.617
-Confusion Matrix:
- [[ 60   4   5   6   4  15   5]
- [  7 132   7   2  10   4   3]
- [ 29  14 123  25  33  28  61]
- [  9   6  15 112   5   3   6]
- [  1   2   2   2  69   1   2]
- [  4   1   3   4   1  48   3]
- [ 14   2   5  15   2  13  73]]
-Node Classification on random seed  5005 -> 0.615
-Confusion Matrix:
- [[ 73   5   3   5   2  16  11]
- [  2 119  16   1  16   3   0]
- [ 42  27 131  29  33  16  32]
- [  9   6  13  97   3   6   9]
- [  0   3   2   2  60   3   5]
- [  0   2   0   3   2  50   6]
- [  7   5   5  12  12  11  85]]
-Node Classification on random seed  5006 -> 0.575
-Confusion Matrix:
- [[ 61   1   5   4   8  11  11]
- [  7 127   6   1   3   3  10]
- [ 18  37  94  48  31  40  27]
- [ 15  10   9 104   6   5  12]
- [  1   8   3   4  65   1   4]
- [  6   0   2   6   0  56   6]
- [ 10   5  11   9   5  16  68]]
-Node Classification on random seed  5007 -> 0.606
-Confusion Matrix:
- [[ 73   1   2   5   5  16   8]
- [  3 118   5   4  15   2   7]
- [ 18  14 134  44  15  31  49]
- [ 16   2   7 102   5  15  15]
- [  0   3   6   2  67   1   3]
- [  0   3   2   5   3  45   7]
- [  3   4   6  11  12  19  67]]
-Node Classification on random seed  5008 -> 0.635
-Confusion Matrix:
- [[ 68   1   3  11   5  15  10]
- [  2 120   4   6   8   1   6]
- [ 17  24 156  33  28  21  44]
- [  5   6  20 114   2   6  18]
- [  2   8   4   1  59   0   3]
- [  4   2   2   3   2  36   3]
- [  5   2  12   3   4   9  82]]
-Node Classification on random seed  5009 -> 0.629
-Confusion Matrix:
- [[ 74   1   5   4   5  14  20]
- [  2 133   5   5   6   1  10]
- [ 15  17 140  30  20  23  37]
- [ 16   0  16 114   4   5  11]
- [  2   7   9   2  55   1   2]
- [  3   6   3   1   1  39   5]
- [ 10   6  16   4   4  17  74]]
-Node Classification on random seed  5010 -> 0.644
-Confusion Matrix:
- [[ 75   0   7   6   6  10   2]
- [  6 114   4   3   6   2   6]
- [ 24  18 150  39  34  18  37]
- [  5   5   9 108  13   3  13]
- [  2  11   4   4  59   1   1]
- [  4   2   3   3   0  50   4]
- [  6   1   7   4   7  16  88]]
-Node Classification on random seed  5011 -> 0.639
-Confusion Matrix:
- [[ 88   3   3   6   2  11   5]
- [  5 132   5   1  16   3   3]
- [ 32  36 130  18  23  20  40]
- [  9   2  22  99   1   2  12]
- [  3   4   0   0  62   2   0]
- [  3   2   3   1   0  44   8]
- [ 10   5   7   9   5  19  84]]
-Node Classification on random seed  5012 -> 0.617
-Confusion Matrix:
- [[ 74   1   0   2   3   8   7]
- [  3 119   9   5   9   0   5]
- [ 23  22 151  30  23  12  55]
- [ 18   4  21 100   5   3  29]
- [  3   6   5   0  65   1   3]
- [  4   2   2   1   0  44   8]
- [  6   6  15   1  11  12  64]]
-Node Classification on random seed  5013 -> 0.6
-Confusion Matrix:
- [[ 79   0   3   2   1  15  15]
- [  3 121  15   8   6   5   3]
- [ 19  12 134  50  20  53  40]
- [ 12   2  12  94   1   4  14]
- [  2   3   2   2  51   3   5]
- [  3   1   9   1   0  44   4]
- [ 13   1  11   4   3  18  77]]
-Node Classification on random seed  5014 -> 0.667
-Confusion Matrix:
- [[ 65   1   6   6   1   9  13]
- [  3 135   4   0   8   4   8]
- [ 36  14 168  35  22  14  17]
- [  4   1  14 117   6   2  15]
- [  3   8   4   1  59   1   1]
- [  4   2   2   3   2  51   3]
- [ 14   7   6  11   6  12  72]]
-Node Classification on random seed  5015 -> 0.574
-Confusion Matrix:
- [[ 70   4   5   3   1   7  15]
- [  6 130   3   5   5   6   4]
- [ 28  21 134  41  29  20  39]
- [ 14   1  12  92  14  12  23]
- [  3   3   3   2  56   1   1]
- [ 11   0   2   1   2  48   2]
- [ 17   6   6  21   2  25  44]]
-Node Classification on random seed  5016 -> 0.633
-Confusion Matrix:
- [[ 65   0   3   9   1  12  18]
- [  8 135  10   6   5   0   1]
- [ 11   8 150  29  21  25  25]
- [ 14   2  24 118   7   4   7]
- [  2   5   5   2  70   1   2]
- [  6   1   2   3   3  39   6]
- [  2   4  13  17  15  28  56]]
-Node Classification on random seed  5017 -> 0.607
-Confusion Matrix:
- [[ 47   1   3   8   4  15  18]
- [  6 152   7   3  13   0   3]
- [ 22  19 147  24  26  30  48]
- [ 17   4  11  88  14   4  15]
- [  1   5   1   1  56   1   2]
- [ 10   1   2   0   2  36   6]
- [ 16   2   5   9   7   7  81]]
-Node Classification on random seed  5018 -> 0.561
-Confusion Matrix:
- [[ 47   1   7   7  10  15   9]
- [  6 119  17   3  12   3   8]
- [ 31  18 124  38  61  14  25]
- [  9  10  19 103   3   6  14]
- [  0   0  11   3  63   1   2]
- [  2   3   2   1   1  42   4]
- [  9   6   7   7  22  12  63]]
-Node Classification on random seed  5019 -> 0.634
-Confusion Matrix:
- [[ 72   2   1   7   3   9  12]
- [  1 115   7   8   8   1  11]
- [ 22  26 146  51  22  31  28]
- [  9   3   7 120   6   7   8]
- [  0   8   6   4  47   0   4]
- [  2   0   2   5   1  57   5]
- [  2   4  12   5   6  10  77]]
-Node Classification on random seed  5020 -> 0.611
-Confusion Matrix:
- [[ 54   4   7   8   3  15  14]
- [  2 142  10   3   3   3   3]
- [ 24  20 120  57  31  15  27]
- [ 10   5  15 108   3   4  17]
- [  1  13   0   3  64   0   1]
- [  4   3   5   6   2  42   1]
- [  9   1   8   8  11  10  81]]
-Node Classification on random seed  5021 -> 0.63
-Confusion Matrix:
- [[ 80   2   7   1   2  11   6]
- [  3 127   6   3   6   5   8]
- [ 27  24 129  38  16  26  32]
- [ 13   3  21 107   4   6  14]
- [  1  10   1   0  62   0   6]
- [  7   1   5   1   1  48   2]
- [  5   4  16   4   9  13  77]]
-Node Classification on random seed  5022 -> 0.581
-Confusion Matrix:
- [[ 58   7   3   3   5  12  15]
- [  2 120   5   9   4   4   2]
- [ 27  20 132  31  25  26  67]
- [ 10   6  12  98   3   6  20]
- [  1   8   4   0  70   2   4]
- [  2   1   2  10   1  34   5]
- [  6   6   1  14  14  14  69]]
-Node Classification on random seed  5023 -> 0.665
-Confusion Matrix:
- [[ 83   0   7   2   2   9   5]
- [  2 142   4   5   2   0   8]
- [ 19  25 146  45  25  10  26]
- [  4   3  18 102  10   2  16]
- [  1  10   2   4  64   0   0]
- [  4   3   4   0   1  53   5]
- [ 17   5   3   6   2  19  75]]
-Node Classification on random seed  5024 -> 0.628
-Confusion Matrix:
- [[ 66   4   2   5   5   6  20]
- [  1 132   5   1  11   6   5]
- [  8  22 157  25  20  17  48]
- [  1   6  25  98   2   9  22]
- [  0   7   5   1  61   2   2]
- [  5   0   5   1   3  34  14]
- [  9   4   9   2  16  11  80]]
-Node Classification on random seed  5025 -> 0.622
-Confusion Matrix:
- [[ 62   6   5  14   0   9   6]
- [  4 137   5   2   6   0   5]
- [ 12  33 147  45  21  22  31]
- [  7   5  20  98   5   4  20]
- [  4   4   5   1  60   1   1]
- [ 12   1   1   0   3  52   3]
- [  7   7   8   5  10  18  66]]
-Node Classification on random seed  5026 -> 0.651
-Confusion Matrix:
- [[ 65   5   1   7   4  13  11]
- [  9 128   6   1   3   3   5]
- [ 13   5 153  19  20  37  48]
- [  4   4  10 121  15   9  15]
- [  3   4  11   1  58   0   1]
- [  5   2   0   0   1  45   9]
- [ 13   1  11   2  10   8  81]]
-Node Classification on random seed  5027 -> 0.594
-Confusion Matrix:
- [[ 53   5   6   8   5  12   3]
- [  4 139   7   1   3   8   2]
- [ 15  26 117  51  30  19  35]
- [ 12   6  15 103   6   9  11]
- [  1   9   4   3  59   0   5]
- [  2   2  12   0   2  45   8]
- [ 10   5  16   8   8  12  78]]
-Node Classification on random seed  5028 -> 0.627
-Confusion Matrix:
- [[ 72   5   2   5   6  11  14]
- [ 11 113   1   0  10   1   4]
- [ 19  19 164  32  22  18  43]
- [  8   7  22 100   7   9  10]
- [  0   9   2   1  66   1   4]
- [  7   0   1   2   0  47   5]
- [ 14   3   5  19   7   7  65]]
-Node Classification on random seed  5029 -> 0.623
-Confusion Matrix:
- [[ 77   3   4   3   3   9   7]
- [  4 125   3   3  14   4   1]
- [ 37  28 113  37  27  23  43]
- [  4   2  10 112   1   6  19]
- [  4   9   0   4  64   1   2]
- [  5   2   3   2   1  45   4]
- [ 15   1   9   6   5   9  87]]
-Node Classification on random seed  5030 -> 0.623
-Confusion Matrix:
- [[ 76   1   4   1   2  13  18]
- [  5 118   8   2   6   3   4]
- [ 19  30 158  25  17  23  43]
- [ 16   2  24  89  15   2   9]
- [  0   8   2   2  61   1   2]
- [  3   2   3   2   0  36  17]
- [ 14   2   4   4   6  13  85]]
-Node Classification on random seed  5031 -> 0.646
-Confusion Matrix:
- [[ 73   5   0   1   8  11   7]
- [  3 138   2   1   7   6   3]
- [ 30   9 159  42  27  16  29]
- [ 14   3  22  92   5   5  20]
- [  1   6   7   0  51   1   2]
- [  7   0   4   3   0  33   4]
- [ 11   2   6   8   2  14 100]]
-Node Classification on random seed  5032 -> 0.591
-Confusion Matrix:
- [[ 71   1   8  11   4  22   6]
- [ 12 130   6   5   5   3   1]
- [ 28  26 121  51  10  37  25]
- [ 10   6  18  94   4   6  18]
- [  1   9   3   3  46   2   0]
- [  4   0   0   4   0  41   7]
- [  6   1  12   8   5  21  88]]
-Node Classification on random seed  5033 -> 0.631
-Confusion Matrix:
- [[ 82   3   8   2   4  14   9]
- [  7 113   5   1  10   2   9]
- [ 13  13 164  23  45  27  37]
- [  8   5  17  93   2   7  12]
- [  2   8   8   0  59   0   1]
- [  5   1   2   1   0  49   6]
- [  7   5   9  11   9  11  71]]
-Node Classification on random seed  5034 -> 0.65
-Confusion Matrix:
- [[ 66   7   7   0   6  16   6]
- [  2 140   9   2   7   4   3]
- [ 21  25 147  21  16  23  31]
- [ 13   4  11  90   4   8  13]
- [  2   8   2   0  74   0   2]
- [  8   5   1   0   0  58   2]
- [ 15   6  15   4   3  18  75]]
-Node Classification on random seed  5035 -> 0.646
-Confusion Matrix:
- [[ 77   0   3   1   2   5  13]
- [  3 130   6   3  16   0   2]
- [  8  17 148  47  30  24  20]
- [ 14   4  14 115   2   4   8]
- [  1   5  11   1  58   1   1]
- [  5   3   2   2   0  46   8]
- [  9   4  17   6  12  20  72]]
-Node Classification on random seed  5036 -> 0.604
-Confusion Matrix:
- [[ 82   5   3   6   5  11   5]
- [  3 119   9   0   3   4   3]
- [ 10  28 138  48  30  15  39]
- [ 16   8  14  95   8  13  14]
- [  1   7   4   1  67   0   2]
- [  8   1   9   4   0  37   3]
- [ 16   2   6  11   6  15  66]]
-Node Classification on random seed  5037 -> 0.57
-Confusion Matrix:
- [[ 68   2   4   1   9   4  16]
- [  4 110   7   1  10   3   6]
- [ 24  33 109  28  61  27  46]
- [ 10   5  16  87   2   7  24]
- [  0   9   2   1  62   2   3]
- [  3   0   5   2   2  59   4]
- [ 14   2   7   5   7  12  75]]
-Node Classification on random seed  5038 -> 0.621
-Confusion Matrix:
- [[ 70   1   3   9   2  14  13]
- [  7 120   6   3  10   0   3]
- [ 27  28 151  27  22  26  32]
- [  8   1  22 105   6   5  16]
- [  3   2   5   2  61   1   2]
- [  7   0   1   3   2  50   7]
- [  7   3   9  14   5  15  64]]
-Node Classification on random seed  5039 -> 0.669
-Confusion Matrix:
- [[ 59   0   9  10   1  16  11]
- [  9 115   7   3   4   0   5]
- [ 18  24 184  21  21  22  27]
- [  9   4   8 106   1   9  23]
- [  1   5   3   1  69   2   0]
- [  1   1   3   3   0  50   2]
- [  0   0  12   5  13  17  86]]
-Node Classification on random seed  5040 -> 0.594
-Confusion Matrix:
- [[ 79   0   1   9   6  20  12]
- [ 12 112  13   2  10   6   4]
- [ 23  21 133  56  24  25  29]
- [ 14   0  15 100   4   7   9]
- [  1  10   3   2  57   1   0]
- [  8   0   1   3   0  42   6]
- [  7   4   7   8   8  15  71]]
-Node Classification on random seed  5041 -> 0.649
-Confusion Matrix:
- [[ 81   2   4   3   2  12   7]
- [  5 134   5   4   4   3   1]
- [ 28  35 137  26  22  17  28]
- [ 15   8   9  91   4   3  16]
- [  9   7   8   1  59   1   0]
- [  7   2   1   0   1  50   7]
- [  9   4  13   4   8   6  97]]
-Node Classification on random seed  5042 -> 0.628
-Confusion Matrix:
- [[ 67   1   2   0   3  10  12]
- [  4 129   2   0   7   5   6]
- [ 27  21 129  20  48  24  35]
- [  4   5  14 101   6   7  15]
- [  2  11   1   4  55   0   1]
- [  3   4   1   0   0  63   3]
- [  3   4   8  11  19  19  84]]
-Node Classification on random seed  5043 -> 0.627
-Confusion Matrix:
- [[ 77   1   5  13   0   5   5]
- [  3 120  10   3   4   3   5]
- [ 17  31 138  22  41  19  39]
- [  8   6  19 120   4   4   6]
- [  1   9   2   0  60   5   4]
- [  8   0   1   0   1  46   4]
- [ 13   6   5  10   7  24  66]]
-Node Classification on random seed  5044 -> 0.655
-Confusion Matrix:
- [[ 69   5   3   5   3   7   9]
- [  3 112   4   5  12   6   4]
- [ 44  11 166  34  16  20  31]
- [ 12   7   5 119   3   5   8]
- [  0   5   5   2  68   0   5]
- [  6   0   3   1   3  54   3]
- [ 12   2   5   8   5  18  67]]
-Node Classification on random seed  5045 -> 0.617
-Confusion Matrix:
- [[ 69   0   4   7   5   6   6]
- [  5 139   9   6   7   3   0]
- [ 21  15 151  45  18  31  45]
- [ 22   4  12  93   1  11  13]
- [  3   5   3   2  57   0   3]
- [  1   1   1   0   6  48   3]
- [ 16   7   9   6   5  16  60]]
-Node Classification on random seed  5046 -> 0.607
-Confusion Matrix:
- [[ 80   1   1   2   0  15   5]
- [  1 123   3   9   5   5   2]
- [ 26  29 109  73  15  20  33]
- [ 14   3  18 113   6   5   7]
- [  4   4   8   2  54   2   2]
- [  6   0   2   2   4  44   5]
- [  9   2   9   9   9  16  84]]
-Node Classification on random seed  5047 -> 0.599
-Confusion Matrix:
- [[ 51  10   5  11   0  15  17]
- [  5 129   2   1   2   3   5]
- [ 18  40 135  30  17  24  44]
- [  7   3  20 116   1   5  14]
- [  2   5   7   4  59   5   6]
- [  7   1   5   2   0  34   5]
- [ 19   5   6   6   4  13  75]]
-Node Classification on random seed  5048 -> 0.596
-Confusion Matrix:
- [[ 81   1   1   4   4  14   6]
- [  6 130   4   1  12   7   9]
- [ 28  21 129  43  27  15  35]
- [  4   5  23  85   3   9  31]
- [  2   5   1   0  55   1   1]
- [  6   2   3   5   0  42   7]
- [ 10   1  12   9   4  22  74]]
-Node Classification on random seed  5049 -> 0.652
-Confusion Matrix:
- [[ 95   3   1   6   4   1   2]
- [  1 137   0   4   5   3   7]
- [ 14  30 144  29  22  24  44]
- [ 14   5  20  92   5   8  13]
- [  0   6   5   0  65   0   6]
- [ 10   0   0   6   0  38   8]
- [  7   5   9   6   4  11  81]]
-Node Classification on random seed  5050 -> 0.603
-Confusion Matrix:
- [[ 61   6   0  10   6   9  10]
- [  3 127   2   3  11   5  12]
- [ 30  28 131  48  21   9  38]
- [  6   8  15 116  10   1   7]
- [  1  10   3   1  54   0   5]
- [  6   2   8   2   0  40   2]
- [  9   4  13   4  15  14  74]]
-Node Classification on random seed  5051 -> 0.63
-Confusion Matrix:
- [[ 55   1   7   5   5  19  11]
- [  2 131   3   1   8   4  16]
- [ 25  14 139  26  22  34  35]
- [  5   6  14 108   6   9  22]
- [  3   3   5   2  54   3   3]
- [  7   0   1   1   1  51   8]
- [  8   2   9   2   2  10  92]]
-Node Classification on random seed  5052 -> 0.624
-Confusion Matrix:
- [[ 64   3   8  10   1   7   6]
- [  7 121   6   3   7   2   5]
- [ 19  23 136  35  31  26  43]
- [  7   3   9 115   7   4  16]
- [  0   9   1   0  61   1   1]
- [  3   3   5   3   1  52   5]
- [ 11   9  14   8  10   4  75]]
-Node Classification on random seed  5053 -> 0.597
-Confusion Matrix:
- [[ 66   2   6   5   3   7  14]
- [  7 136   5   5   2   5   2]
- [ 20  24 148  30  25  28  44]
- [  9  10  21  98   5   5  10]
- [  3   7   5   2  53   1   4]
- [  6   0   3   4   2  37   5]
- [  8   3  12   8  17  19  59]]
-Node Classification on random seed  5054 -> 0.607
-Confusion Matrix:
- [[ 82   3   4   8   3  16   6]
- [  3 126   6   3  17   4   4]
- [ 21  22 149  44  24  22  38]
- [ 19   6  10  91   6  12   6]
- [  0   8   2   2  44   0   5]
- [  3   1   1   3   0  49   4]
- [ 12   5  11   4   5  20  66]]
-Node Classification on random seed  5055 -> 0.592
-Confusion Matrix:
- [[ 66   2   1   3   8   7  10]
- [  5 116   6   2   8   3   1]
- [ 45  16 117  34  13  28  56]
- [ 12   4   8 106  12  10  15]
- [  1   4  13   0  55   2   3]
- [  5   1   5   1   0  52   4]
- [  8   2  11   7   7  25  80]]
-Node Classification on random seed  5056 -> 0.622
-Confusion Matrix:
- [[ 81   1  10   7   6   5   6]
- [  3 130   7   5   8   5   2]
- [ 24  14 111  38  26  14  50]
- [  6   0  24 119   0   4  11]
- [  1   8   2   3  56   4   1]
- [  9   0   3   0   0  51   3]
- [  8   7  12  18   5  18  74]]
-Node Classification on random seed  5057 -> 0.651
-Confusion Matrix:
- [[ 59   1   2   1   3   7  18]
- [  4 138   7   3   3   5   5]
- [ 10  16 172  28  21  15  34]
- [ 22   2  14  97  13   2  20]
- [  0  16   2   0  60   1   4]
- [  6   2   3   2   0  39  13]
- [ 10   2  14   4   8   6  86]]
-Node Classification on random seed  5058 -> 0.627
-Confusion Matrix:
- [[ 78   3   3   5   2  20   3]
- [  9 123   2   2   9   4   2]
- [ 14  20 164  31  29  28  39]
- [ 32   5  16  73   5   5  11]
- [  0   6   1   3  60   0   1]
- [  4   4   3   0   0  50   6]
- [  6   4   6   1   9  20  79]]
-Node Classification on random seed  5059 -> 0.628
-Confusion Matrix:
- [[ 72   3   5   5   1  11   9]
- [  4 124  13   2   9   0   4]
- [ 19  13 153  27  37  20  44]
- [  5   2  17  93   5   8  32]
- [  1   3   3   0  63   2   3]
- [  6   3   4   1   0  40   3]
- [  6   3  10   8   8  13  83]]
-Node Classification on random seed  5060 -> 0.624
-Confusion Matrix:
- [[ 84  10   6   5   7   7   9]
- [  2 110   9   4   9   6   5]
- [ 22  21 125  38  18  34  34]
- [  7   6   8 102   5   5  15]
- [  0  11   5   0  70   0   3]
- [ 12   2   4   1   4  49   1]
- [ 13   3   3   2   6  14  84]]
-Node Classification on random seed  5061 -> 0.635
-Confusion Matrix:
- [[ 74   1   4   2   2  24  12]
- [  1 138   3   4   9   7   5]
- [ 18  11 147  29  12  33  43]
- [ 18   2  16  98   3  10  11]
- [  1   6   5   1  62   0   3]
- [  7   3   0   3   0  44   4]
- [ 13   1  13   7   5  13  72]]
-Node Classification on random seed  5062 -> 0.638
-Confusion Matrix:
- [[ 79   1   2   5   3   7  13]
- [  3 105   8   4   5   2   2]
- [ 27  31 156  23  28  21  24]
- [  8   5  21 112   6  14   7]
- [  1   4   5   2  65   0   0]
- [  6   0   2   0   0  48  12]
- [ 21   5  15   2   6  11  73]]
-Node Classification on random seed  5063 -> 0.629
-Confusion Matrix:
- [[ 77   2   1   4   3  11  10]
- [  6 129   4   1   4   2  10]
- [ 30  18 160  25  18  31  30]
- [ 15   3  17  90  10  15   9]
- [  1  11   5   1  50   3   2]
- [ 14   0   0   4   0  44   3]
- [ 11   2   7   0   4  24  79]]
-Node Classification on random seed  5064 -> 0.638
-Confusion Matrix:
- [[ 71   1   0   7   5  10  26]
- [  5 112   7   7  15   3   3]
- [ 18  16 152  42  44   9  37]
- [ 11   3  11 102   2   3   7]
- [  0   3   2   0  66   1   0]
- [  4   2   1   1   1  52   3]
- [ 10   2  16   9   7   8  83]]
-Node Classification on random seed  5065 -> 0.61
-Confusion Matrix:
- [[ 67   3   3   5   3  13  11]
- [  8 124   7   6   4   3   2]
- [ 24  23 131  26  44  30  23]
- [  6   1  23 110   6   6  11]
- [  1   8  10   0  58   0   3]
- [  6   0   2   2   0  44   5]
- [ 10   2  13   4  17  16  76]]
-Node Classification on random seed  5066 -> 0.585
-Confusion Matrix:
- [[ 70   1   4   5   3  10   5]
- [  6 128  10   7   2   3   3]
- [ 38  19  99  54  23  33  42]
- [ 14   2  10 113   2   1  24]
- [  1   6   4   1  48   0   3]
- [  4   3   3   0   4  46   9]
- [ 11   5  10  11   4  15  81]]
-Node Classification on random seed  5067 -> 0.643
-Confusion Matrix:
- [[ 75   1   2  11   3   6   4]
- [  4 132   5   6   4   4   2]
- [ 20  17 145  31  11  29  33]
- [ 17   1  21 104   5   6   9]
- [  0   8   6   1  59   0   3]
- [  3   4   3   3   3  48   4]
- [ 17   7  12   9   7  15  80]]
-Node Classification on random seed  5068 -> 0.629
-Confusion Matrix:
- [[ 59   3   7  14  12  11   5]
- [  2 116   2   0  11   5   7]
- [ 16  30 156  28  39  12  28]
- [  8   0  16  95   8  13  24]
- [  0   8   2   2  57   0   0]
- [  5   0   2   1   1  52   5]
- [  9   4   8   6   5  12  94]]
-Node Classification on random seed  5069 -> 0.647
-Confusion Matrix:
- [[ 80   0   9   5   3   2   3]
- [  2 134   5   1  11   3   5]
- [ 29  42 147  42  12  25  18]
- [  9   1  23 122   2   4   8]
- [  2   9   3   0  61   0   1]
- [  5   3   3   3   1  39   3]
- [ 20   3  10   5   7  11  64]]
-Node Classification on random seed  5070 -> 0.596
-Confusion Matrix:
- [[ 80   4   2  11   5   6   2]
- [ 19 123  13   2  11   0   4]
- [ 22  24 140  27  19  25  65]
- [ 15  10  13  75   9   5  12]
- [  0   7   3   2  54   0   5]
- [ 14   1   2   0   0  48   5]
- [ 11   1   5   8   7   8  76]]
-Node Classification on random seed  5071 -> 0.606
-Confusion Matrix:
- [[ 67   1  22   3   4   9   9]
- [  6 117   3   2   7   2  11]
- [ 25  17 129  39  39  20  46]
- [  9   5  14 114   0   4  16]
- [  5   4   1   0  51   1   5]
- [  7   1   2   2   0  54   4]
- [ 14   3   9   5   8  10  74]]
-Node Classification on random seed  5072 -> 0.646
-Confusion Matrix:
- [[ 59   5   6   9   2  12  11]
- [  5 111   3   3   6   3   2]
- [ 30  16 138  17  25  26  51]
- [  3   7   8 122   4   9  11]
- [  1   3   1   1  74   1   0]
- [  9   0   2   1   1  49   7]
- [ 13   5   5  11   3  16  93]]
-Node Classification on random seed  5073 -> 0.61
-Confusion Matrix:
- [[ 56   2   4   6   5  16   6]
- [  0 125   3   6   3   5   3]
- [ 19  24 147  61   9  23  38]
- [ 20   6  19  92   3   6   8]
- [  0   4   9   3  62   0   1]
- [ 15   1   2   0   1  44   3]
- [ 10   4   9   5   8  20  84]]
-Node Classification on random seed  5074 -> 0.669
-Confusion Matrix:
- [[ 73   4   2  11   4   7   5]
- [  4 135   6   0   7   1   5]
- [ 22  22 166  36   8  19  26]
- [  7   3  14 101   2  11  11]
- [  2  10  12   0  62   3   2]
- [  5   2   3   3   0  45   6]
- [ 14   3   8   5   1  15  87]]
-Node Classification on random seed  5075 -> 0.586
-Confusion Matrix:
- [[ 64   1  11   5   7   9   8]
- [  9 122   5   5   2   2   2]
- [ 29  16 131  38  41  15  33]
- [ 23   3  31  91   9   3  14]
- [  2   3   4   0  59   0   1]
- [  6   0   5   4   0  57   0]
- [ 15   2  18  10   8  15  62]]
-Node Classification on random seed  5076 -> 0.585
-Confusion Matrix:
- [[ 64   6   2   6  14   4  27]
- [  1 120   4   5   8   4   2]
- [ 40  16 140  43  38  19  27]
- [ 21   5  14  97   8   6  12]
- [  0   6   3   4  62   0   3]
- [  5   2   5   0   1  43   4]
- [ 20   2  10   4  11   3  59]]
-Node Classification on random seed  5077 -> 0.63
-Confusion Matrix:
- [[ 75   3   0   7   5  12   7]
- [  1 127   5   0   6   3   5]
- [ 13  29 155  30  26  24  41]
- [ 13   2  10 107   6   4   9]
- [  1   5   4   6  62   0   6]
- [  6   0   3   2   0  36   3]
- [ 13   7  10  11   8  24  68]]
-Node Classification on random seed  5078 -> 0.636
-Confusion Matrix:
- [[ 57   1  10   3   1  10  13]
- [  4 121  11   2   8   1   6]
- [ 17  17 167  37  30  19  31]
- [ 17   2  28  87   4   9   9]
- [  2   5   5   1  74   0   1]
- [  2   0   2   2   2  50   4]
- [  7   1   3   7   6  24  80]]
-Node Classification on random seed  5079 -> 0.59
-Confusion Matrix:
- [[ 64   4   3   1   1  19  12]
- [  2 115   7   5   8   2   3]
- [ 24  17 122  47  20  47  35]
- [  6   6  16 112   6   7  13]
- [  0   5   5   2  62   2   3]
- [  7   1   3   2   2  43   6]
- [ 12   6  13   8   9  13  72]]
-Node Classification on random seed  5080 -> 0.639
-Confusion Matrix:
- [[ 94   2   2   6   6  11   2]
- [  5 134   2   4   6   5   4]
- [ 17  12 134  22  34  25  48]
- [ 20   1  18  82   9   9  24]
- [  0   5   2   3  56   2   1]
- [  3   1   0   3   0  49   5]
- [  3   6   4  12   5  12  90]]
-Node Classification on random seed  5081 -> 0.573
-Confusion Matrix:
- [[ 66   0   3   9   3  12  11]
- [  3 106   2   2  11   1   8]
- [ 17  12 158  43  23  24  58]
- [  5   2  31  84   7  13  13]
- [  2   3   2   4  60   1   4]
- [  5   1   3   4   0  53   2]
- [ 15   2   8  15  11  32  46]]
-Node Classification on random seed  5082 -> 0.662
-Confusion Matrix:
- [[ 81   2   4   4   5  13  10]
- [  7 115   4   4   4   0   3]
- [ 26  16 165  17  26  22  36]
- [ 16   2  12 103   3   2  15]
- [  2   7   5   1  58   1   0]
- [  9   1   4   1   0  49   4]
- [  8   1  15   5   4  17  91]]
-Node Classification on random seed  5083 -> 0.613
-Confusion Matrix:
- [[ 73   2   8   7   5   7  10]
- [  6 116   3   3   6   3   1]
- [ 27  23 135  23  21  30  45]
- [ 13   4  16 116   7   5  10]
- [  1   7   7   0  57   3   2]
- [ 13   0   4   1   1  46   5]
- [ 17   3   7   5  10  16  70]]
-Node Classification on random seed  5084 -> 0.617
-Confusion Matrix:
- [[ 63   3   2   3   6  18  12]
- [  1 122   4   1  10   3   4]
- [ 18  20 164  15  27  27  47]
- [  7   1  12  91   3  18  17]
- [  3   9   7   5  62   0   2]
- [  0   2   6   2   0  52   3]
- [  6   6   9   7  17  20  63]]
-Node Classification on random seed  5085 -> 0.584
-Confusion Matrix:
- [[ 57   1  14   5   4  22   9]
- [  3 116   7   2  10   1   6]
- [ 25  13 131  47  24  35  38]
- [  4   7  15  89   2   7  28]
- [  2   5   2   4  64   4   3]
- [  3   1   5   0   3  61   2]
- [  1   1  17   4  11  19  66]]
-Node Classification on random seed  5086 -> 0.624
-Confusion Matrix:
- [[ 72   5   6   6   4  16   6]
- [  4 133   8   2   8   1   1]
- [ 15  24 154  36  14  26  36]
- [ 21   0  10 104   3   6  11]
- [  3   7   5   2  49   0   6]
- [  8   1   2   0   1  42   3]
- [ 19   3  15   5   8  19  70]]
-Node Classification on random seed  5087 -> 0.612
-Confusion Matrix:
- [[ 69   2   4  10   4  13  13]
- [ 11 113   4   2   8   6   3]
- [ 33  21 130  50  20  19  34]
- [ 11   4  17 110   4   8  11]
- [  4   7   2   2  61   0   1]
- [  7   3   0   3   0  36   4]
- [ 15   5   5   4   5   9  93]]
-Node Classification on random seed  5088 -> 0.588
-Confusion Matrix:
- [[ 68   4   9   5   2  18   6]
- [  3 136   5   1   4   1   8]
- [ 20  27 124  36  24  46  36]
- [ 10   8  13 104   4  12  16]
- [  4   8   6   2  45   0   1]
- [  6   0   0   0   0  42   1]
- [  7   4  16   3  11  25  69]]
-Node Classification on random seed  5089 -> 0.609
-Confusion Matrix:
- [[ 63   3   8   5   2  16  12]
- [  5 130   4   0  21   1   1]
- [ 18  24 155  36  18  18  44]
- [ 17   2  24  87   4   5  20]
- [  0   6   5   0  56   0   3]
- [  5   0   5   2   0  38   3]
- [ 15   1  10   9   7  12  80]]
-Node Classification on random seed  5090 -> 0.598
-Confusion Matrix:
- [[ 62   5  13  10   4   6  22]
- [  9 101  12   6   5   1   3]
- [ 26  17 137  46  36  21  35]
- [  8   1   5 108   5   2  24]
- [  2   8   2   1  59   1   1]
- [  4   2   2   4   0  36  10]
- [  9   3   7  11   7   6  95]]
-Node Classification on random seed  5091 -> 0.63
-Confusion Matrix:
- [[ 81   1   2  11   6   6  10]
- [  7 131  13   6   5   5   3]
- [ 25   5 135  47  27  28  38]
- [ 19   4  12 105   1   4  12]
- [  1   4   5   1  56   0   4]
- [  8   1   4   6   1  37   6]
- [ 11   1   2   5   4   9  85]]
-Node Classification on random seed  5092 -> 0.668
-Confusion Matrix:
- [[ 89   4   3   1   2   1  10]
- [ 11 131   6   4   4   7   2]
- [ 26  24 148  18  15  20  46]
- [ 19   8  11 104   4   1  19]
- [  3   3   1   1  57   5   1]
- [  1   2   1   0   0  46   8]
- [ 17   2   5   2   7   7  93]]
-Node Classification on random seed  5093 -> 0.623
-Confusion Matrix:
- [[ 66   3   7  15   0  11   4]
- [  5 123  11   1   3   3   6]
- [ 20  24 141  26  26  10  56]
- [ 17   5  13  92   6   6   8]
- [  2   5   4   5  68   2   3]
- [  1   1   4   4   1  45   5]
- [ 14   6   4   6  12  12  88]]
-Node Classification on random seed  5094 -> 0.625
-Confusion Matrix:
- [[ 77   4   3   8   3  18   5]
- [  2 124   2   3  12   2   4]
- [ 19  26 159  39  24  26  47]
- [  5   2  16  95   4   5  13]
- [  0   3   1   1  58   0   8]
- [  4   0   2   2   8  40   6]
- [  9   2   9   8   5  15  72]]
-Node Classification on random seed  5095 -> 0.593
-Confusion Matrix:
- [[ 60   6  11   1   5  11  17]
- [  5 123   8   1  12   1   8]
- [ 33  41 146  32  25  27  20]
- [ 13   3  24  85   4   4  16]
- [  0   7   5   0  63   2   1]
- [  5   1   2   1   1  45   2]
- [ 14   4   8   4   6  16  71]]
-Node Classification on random seed  5096 -> 0.624
-Confusion Matrix:
- [[ 66   4   1   2   6  16   5]
- [  4 140   5   2  15   8   1]
- [ 27  32 109  23  29  18  39]
- [ 19   2  10 117   6   5  12]
- [  2  11   5   3  62   0   4]
- [  0   1   0   0   2  57   7]
- [ 12   5   9   3   8  13  73]]
-Node Classification on random seed  5097 -> 0.606
-Confusion Matrix:
- [[ 68   4  11   1   6  13  10]
- [  4 134   9   7   4   6   4]
- [ 25  21 130  33  37  18  35]
- [ 17   1   9  85   8  15  14]
- [  0   9   3   6  63   1   3]
- [  3   0   1   1   1  44   4]
- [  4   1  10   5  13  17  82]]
-Node Classification on random seed  5098 -> 0.594
-Confusion Matrix:
- [[ 81   3   7   2   9  12   7]
- [  2 104   2   4  12   2  12]
- [ 18  18 137  24  21  37  52]
- [ 19   2  14 103   8  17  15]
- [  5   5   3   0  60   1   6]
- [  2   1   1   2   0  40   2]
- [ 22   3   7   2   6  19  69]]
-Node Classification on random seed  5099 -> 0.612
-Confusion Matrix:
- [[ 58   2   3  12   1   7  10]
- [  4 120   7   4   9   2   0]
- [ 35  13 150  34  45  30  30]
- [  9   5   5 109   5   4  14]
- [  2   7   3   1  66   1   3]
- [  4   0   3   2   2  41  10]
- [ 18   1  22   6   4   9  68]]
-Node Classification on random seed  5100 -> 0.614
-Confusion Matrix:
- [[ 62   2   0   9   1  13  17]
- [  2 117   5   1  11   4   6]
- [ 25  14 153  51  18  22  41]
- [  3   9  14 114   1   4  16]
- [  2   5   6   1  57   0   2]
- [  3   2   5   6   0  49   2]
- [ 14   4  13   9   8  15  62]]
-Node Classification on random seed  5101 -> 0.6
-Confusion Matrix:
- [[ 64   0   7   5   8  15   5]
- [ 11 138   6   2   5   6   4]
- [ 16  26 130  30  32  26  38]
- [ 10   7  27  97   3   5   9]
- [  3   3   7   2  50   1   3]
- [  5   1   1   5   0  52   8]
- [ 12   5   7   9   8  17  69]]
-Node Classification on random seed  5102 -> 0.613
-Confusion Matrix:
- [[ 71   3   3   5   4  14  10]
- [  5 122   1   1  12   2   3]
- [ 23  21 138  28  49  24  31]
- [  7   4  19 112   6   5   9]
- [  2   9   3   0  61   0   1]
- [  6   1   4   3   1  45   3]
- [ 13   5  12   8   9  18  64]]
-Node Classification on random seed  5103 -> 0.592
-Confusion Matrix:
- [[ 53   0   4   1   5  20  25]
- [  3 133   3   0  15   2   6]
- [ 22  15 107  58  19  32  46]
- [ 14   2   5  92  10  10  12]
- [  0   7   2   2  77   0   1]
- [  2   0   2   1   1  52  10]
- [ 15   4   8   8   5  11  78]]
-Node Classification on random seed  5104 -> 0.585
-Confusion Matrix:
- [[ 74   2   3   7   9   7   9]
- [  2 109   2   1  18   2   3]
- [ 34  30 130  25  31  15  52]
- [ 31   4  14  89  12   4  12]
- [  0   3   9   0  57   0   2]
- [  4   3   1   4   0  45  10]
- [ 11   5   2  13   9  10  81]]
-Node Classification on random seed  5105 -> 0.573
-Confusion Matrix:
- [[ 63   1   7   4   4  19  13]
- [  9 115   0   8   6   2   3]
- [ 20  36 135  46  25  16  46]
- [ 25   6  21  84  14   5   6]
- [  1   4   2   5  57   1   5]
- [  0   5   2   1   0  50   5]
- [  4   2  11  15   4  18  69]]
-Node Classification on random seed  5106 -> 0.582
-Confusion Matrix:
- [[ 68   3   4   2   6  17   5]
- [  2 117   4   3  27  11   2]
- [ 31  17 124  36  24  39  22]
- [  7   6  16 105  18   6   8]
- [  4   8   1   2  55   1   2]
- [  5   0   3   3   1  39   8]
- [ 15   3  14   2  10  20  74]]
-Node Classification on random seed  5107 -> 0.632
-Confusion Matrix:
- [[ 56   2   5   5   3   6  21]
- [  3 131   5   5   5   0   3]
- [ 23  23 149  37  23  21  41]
- [ 17   0  14 103   5   7  19]
- [  2  11   6   0  71   2   2]
- [  4   0   2   3   2  34   7]
- [  7   4   6   6   4   7  88]]
-Node Classification on random seed  5108 -> 0.602
-Confusion Matrix:
- [[ 66   2   6   5   4  16   7]
- [  6 126   9   8  10   1   2]
- [ 15  17 142  54  28  20  50]
- [ 15   5  10 108   4   6  12]
- [  0   4   2   2  57   0   5]
- [  4   2   2   7   2  44   1]
- [  8   8   8  13   4  14  59]]
-Node Classification on random seed  5109 -> 0.62
-Confusion Matrix:
- [[ 65   3  12   7   1   9   6]
- [  3 157   4   0   1   3   3]
- [ 30  36 144  26  21  25  31]
- [ 14   5  22  92   3   7  13]
- [  3  12   4   2  53   1   3]
- [  7   0   3   0   0  39   3]
- [ 23   5   6   4   9  10  70]]
-Node Classification on random seed  5110 -> 0.623
-Confusion Matrix:
- [[ 57   4   5   6   3   5  19]
- [  2 143   4   4   2   3  14]
- [ 31  18 138  31  26  14  29]
- [ 21   5  11  93   5   7  19]
- [  0   2   6   2  61   0   5]
- [  3   0   0   3   2  54   3]
- [ 11   4  12   8   8  20  77]]
-Node Classification on random seed  5111 -> 0.609
-Confusion Matrix:
- [[ 82   1   2   4   1  17   8]
- [  6 110   9   3  10   5   3]
- [ 31  25 129  25  28  17  44]
- [ 14   2  23 101   3   3  20]
- [  6   7   4   1  58   0   3]
- [  3   0   3   4   0  45   5]
- [ 10   6   4  13   6  12  84]]
-Node Classification on random seed  5112 -> 0.59
-Confusion Matrix:
- [[ 58   1   8   7   7   2  11]
- [  9 113   6   5   9   2   7]
- [ 29  13 153  42  24  27  35]
- [  9   4  23 102   9   8  12]
- [  2   7   3   0  62   1   2]
- [  4   2   2   3   0  39  10]
- [ 12   4   6  24   6  13  63]]
-Node Classification on random seed  5113 -> 0.6
-Confusion Matrix:
- [[ 69   3   5  10   5   9  15]
- [  3 108  17   4   2   7   2]
- [ 21  18 146  39  39  20  34]
- [ 13   3  16  93   4   5  24]
- [  2   6   5   2  60   0   1]
- [  4   1   1   2   2  45   2]
- [  4   1  14   7   5  23  79]]
-Node Classification on random seed  5114 -> 0.612
-Confusion Matrix:
- [[ 76   0   5   0   2   8  15]
- [  3 122   4   1   8   1   3]
- [ 17  13 130  52  19  32  59]
- [ 11   2  14 105   7   0  12]
- [  3   5   7   0  67   0   1]
- [  9   3   4   2   0  42   6]
- [  8   3  15   7  11  16  70]]
-Node Classification on random seed  5115 -> 0.599
-Confusion Matrix:
- [[ 59   2  13   3   6  17  17]
- [  8 134   7   3  11   2   3]
- [ 10  29 109  35  47  32  36]
- [  6   3  25 107   4   5  10]
- [  1   5   1   2  65   0   1]
- [  1   1   2   0   1  48   5]
- [  3   3   9   7   6  19  77]]
-Node Classification on random seed  5116 -> 0.63
-Confusion Matrix:
- [[ 72   5   6   5   2  12  10]
- [  3 127  17   5   9   2   6]
- [ 20  19 144  20  51  10  35]
- [ 13   5  25 109   1   1  12]
- [  2   2   3   2  61   1   2]
- [  1   1   2   5   0  39  15]
- [ 10   3   5   9   5   8  78]]
-Node Classification on random seed  5117 -> 0.617
-Confusion Matrix:
- [[ 62   3   6  15   2  15   9]
- [  1 136  14   3   5   1   3]
- [ 15  12 128  44  39  26  46]
- [  6   0  17 118   4   4   6]
- [  0  10   2   2  51   1   3]
- [  1   1   1   1   0  48   0]
- [ 15   4   8  13   2  23  74]]
-Node Classification on random seed  5118 -> 0.573
-Confusion Matrix:
- [[ 81   3   6   5   5  12   1]
- [ 14 111   3   4   7   3   6]
- [ 23  36 127  58  27  22  26]
- [  2   3  26 107   5   5  14]
- [  3   6   9   4  44   0   2]
- [ 11   0   2   3   0  42   8]
- [ 19   5   8   9   3  19  61]]
-Node Classification on random seed  5119 -> 0.621
-Confusion Matrix:
- [[ 56   2   4   7   6  16  11]
- [  3 118  10   3   5   3   3]
- [ 30  18 160  34  18  20  30]
- [ 20   2  20 112   3   7   5]
- [  3   6   4   2  55   3   3]
- [  5   2   4   0   1  44   4]
- [ 15   4  16   4   6  17  76]]
-Node Classification on random seed  5120 -> 0.633
-Confusion Matrix:
- [[ 74   3   5   4   3  18  11]
- [  5 121   5   4  10   3   2]
- [ 22  26 133  25  27  21  37]
- [ 17   9  16 109   7   6   9]
- [  2   8   5   1  61   1   2]
- [  6   1   4   1   2  49   2]
- [  1   2   9   2   6  17  86]]
-Node Classification on random seed  5121 -> 0.627
-Confusion Matrix:
- [[ 71  12   2   5   1  15   8]
- [  4 111   6   2   9   4   7]
- [ 27  16 154  33  30  19  31]
- [ 19   5   9 101  11   7   9]
- [  1   5   3   2  63   5   2]
- [  0   4   2   3   0  53   8]
- [  6   2   7   5   7  20  74]]
-Node Classification on random seed  5122 -> 0.618
-Confusion Matrix:
- [[ 66   2   8   0   1  11  15]
- [  3 120  10   5   7   0  10]
- [ 25  23 150  24  18  26  38]
- [ 12   7  16  96   4   9  23]
- [  1   3   3   3  57   0   4]
- [  5   3  10   0   1  46   8]
- [  7   5   8   4   6  14  83]]
-Node Classification on random seed  5123 -> 0.646
-Confusion Matrix:
- [[ 67   6   4   4   2  12  13]
- [  7 127   8   7   9   1   2]
- [ 18  10 152  22  35  21  32]
- [ 12   3   9 127   8   5  10]
- [  1   8   2   1  54   2   0]
- [  6   2   2   0   1  46   3]
- [ 16   5   9  15   5  16  73]]
-Node Classification on random seed  5124 -> 0.618
-Confusion Matrix:
- [[ 76   0   7   3  12   7   7]
- [  4 128   0   9  23   2   7]
- [ 30  29 139  25  29  22  30]
- [  8   1  19  97   8   4  16]
- [  0   9   4   2  62   1   4]
- [  3   1   4   1   1  39   6]
- [ 10   3  11  10   3   7  77]]
-Node Classification on random seed  5125 -> 0.614
-Confusion Matrix:
- [[ 70   2  12   4   7  14   9]
- [  6 138   2   0   7   2   7]
- [ 24  32 138  33  30  16  34]
- [ 13   4  16  94   9   4  13]
- [  5   4   2   1  52   3   3]
- [  6   3   4   1   3  41   1]
- [ 11   4  12   2   8  13  81]]
-Node Classification on random seed  5126 -> 0.581
-Confusion Matrix:
- [[ 72   2   4   6   2  11  12]
- [  4 117   9   0  11   3   3]
- [ 23  39 101  53  25  26  41]
- [  7   7  16 117   5  11   7]
- [  4   4   3   3  50   1   6]
- [  5   0   2   0   3  48   1]
- [ 14   5   6   2  11  22  76]]
-Node Classification on random seed  5127 -> 0.598
-Confusion Matrix:
- [[ 64   5   1   8   4   4  16]
- [  8 129   8   0   8   7   3]
- [ 37  24 134  37  19  15  40]
- [ 18   6  17  84   3  17   9]
- [  1   8   5   1  68   1   1]
- [ 11   1   0   3   1  39   3]
- [ 10   2  14  10   6  10  80]]
-Node Classification on random seed  5128 -> 0.626
-Confusion Matrix:
- [[ 65   5   8   5   2   9  14]
- [  3 128   7   4   9   3   3]
- [ 30  28 143  42  14  34  22]
- [ 10   2  22 115   3   5  10]
- [  1   8   1   4  57   0   3]
- [  6   2   0   1   0  52   2]
- [ 11   3   9   6   4  19  66]]
-Node Classification on random seed  5129 -> 0.605
-Confusion Matrix:
- [[ 76   7   2   2   3   8   7]
- [  5 125   3   3   7   4   4]
- [ 18  18 149  55  28  18  39]
- [ 11  11  14  91  12   7   8]
- [  2   9   4   3  58   0   4]
- [  7   1   1   1   1  42   5]
- [  6  11  12  10   8  16  64]]
-Node Classification on random seed  5130 -> 0.608
-Confusion Matrix:
- [[ 70   4   8   2   5  11   5]
- [  2 137   4   1  13   2   4]
- [ 31  18 130  44  34  27  29]
- [ 13   2  11  99  15  10   7]
- [  2   5   4   3  66   0   2]
- [  5   3   0   3   0  39   2]
- [ 12   3   4   6   9  27  67]]
-Node Classification on random seed  5131 -> 0.586
-Confusion Matrix:
- [[ 55   2   1  11   4   9  11]
- [  8  97   7   1   6   5   6]
- [ 29  14 129  51  30  33  38]
- [  8   3  12 126  10   1   8]
- [  1  10   4   0  48   3   2]
- [ 16   1   0   0   2  41   4]
- [ 20   1  18   3   4  17  90]]
-Node Classification on random seed  5132 -> 0.634
-Confusion Matrix:
- [[ 82   4   5   1   3  11   5]
- [  4 141   3   1  13   7   5]
- [ 24  21 135  48  13   8  50]
- [  9   6   6 102   5   3  18]
- [  1   6   6   4  53   0   5]
- [ 12   0   0   1   0  48   1]
- [  8   2   6  12   6  23  73]]
-Node Classification on random seed  5133 -> 0.666
-Confusion Matrix:
- [[ 69   2   3   2   3  24   8]
- [  2 134   4   2   4   2   1]
- [ 18  24 175  28  18  19  39]
- [  9   9  10 100   5   7  14]
- [  0   8   4   2  64   0   3]
- [  4   0   1   3   3  54   7]
- [  6   1   5  10   4  16  70]]
-Node Classification on random seed  5134 -> 0.629
-Confusion Matrix:
- [[ 79   5   5   3   2   4   9]
- [  1 127   6   2   4   2   5]
- [ 36  18 161  42  26  15  37]
- [ 10   3  23 103  11  11  11]
- [  2   7   1   1  50   2   1]
- [  3   1   4   1   0  40   4]
- [ 14   3  15   5   6  10  69]]
-Node Classification on random seed  5135 -> 0.635
-Confusion Matrix:
- [[ 84   0   4   2   4   4  13]
- [  2 137   7   2  12   3   2]
- [ 16  20 148  15  34  28  46]
- [ 11   4  15 105   5   2  21]
- [  0   7   5   2  62   3   2]
- [  4   0   2   6   1  30   7]
- [  7   6  12   3  20   6  69]]
-Node Classification on random seed  5136 -> 0.59
-Confusion Matrix:
- [[ 80   1   5   2   8  14   3]
- [  3 139   9   7   5   3   0]
- [ 21  34 121  45  58  19  23]
- [ 20   8  17  82   6   5  10]
- [  1   8   2   3  47   1   0]
- [  4   2   1   2   1  45   4]
- [ 12   2   9   7   7  18  76]]
-Node Classification on random seed  5137 -> 0.605
-Confusion Matrix:
- [[ 61   1   4  10   4  13  10]
- [ 10 133   3   5   2   6   8]
- [ 27  17 153  51  24  16  34]
- [ 15   9  18  84   6   5   4]
- [  5   4   1   2  65   1   5]
- [  4   1   1   2   1  47   3]
- [ 17   3  11   8   3  21  62]]
-Node Classification on random seed  5138 -> 0.63
-Confusion Matrix:
- [[ 69   1   4   4   1  19   9]
- [  5 117   6   2  19   5   7]
- [ 24  20 154  29  15  26  41]
- [ 15   2   8 120   1   8  15]
- [  2   3   2   0  63   0   5]
- [  2   1   3   6   1  41   7]
- [  7   5   4   8   7  21  66]]
-Node Classification on random seed  5139 -> 0.611
-Confusion Matrix:
- [[ 55   2   6   4   5   7  10]
- [ 10 118   4   4   6   3   7]
- [ 23  37 150  30  17  23  49]
- [  8   7  11 113   4   5  13]
- [  6   4   5   1  59   2   1]
- [  3   2   2   6   2  47   3]
- [  8   8  10   6   6  19  69]]
-Node Classification on random seed  5140 -> 0.589
-Confusion Matrix:
- [[ 75   3  12   5   3  14   6]
- [  4 114   2   4   9   1   1]
- [ 35  20 116  45  52   8  43]
- [  6   2  19 110   6   4  13]
- [  0   3   3   1  69   1   5]
- [  8   3   3   0   0  38   5]
- [ 22   3   7   6   5  19  67]]
-Node Classification on random seed  5141 -> 0.593
-Confusion Matrix:
- [[ 71   2   9   2   2  11  13]
- [  7 111   9   2  17   6   2]
- [ 37  16 148  17  24  16  42]
- [ 34   1  21  86   7   4   6]
- [  2  11   9   0  56   0   1]
- [  9   1   2   2   1  44   0]
- [ 14   3  11  11   8  15  77]]
-Node Classification on random seed  5142 -> 0.611
-Confusion Matrix:
- [[ 54   2   9   5   3   8   9]
- [  3 139   8   0  14   4   6]
- [ 26  13 136  32  29  34  44]
- [  6   1  19 108   3   9  11]
- [  4   5   2   1  64   0   1]
- [ 12   2   4   1   2  38   3]
- [  4   2  11  11   3  23  72]]
-Node Classification on random seed  5143 -> 0.63
-Confusion Matrix:
- [[ 74   3   7   3   2  13  10]
- [  0 134   8   1   3   1   8]
- [ 14  27 142  42  36  26  38]
- [  5   7  19 100   5   8  12]
- [  0   5   2   2  52   1   1]
- [  3   4   5   0   5  43   1]
- [  1   3   6   2   9  22  85]]
-Node Classification on random seed  5144 -> 0.611
-Confusion Matrix:
- [[ 88   2   5   1   2  17   8]
- [  8 117   6   1   3   1   9]
- [ 25  11 135  50  18  29  43]
- [ 11   1  27  90   7  16   7]
- [  1   4   5   1  55   0   5]
- [  3   1   4   3   0  53   2]
- [ 12   1  10   9   5  15  73]]
-Node Classification on random seed  5145 -> 0.599
-Confusion Matrix:
- [[ 82   8   7   1   4  12   7]
- [  3 131   7   7   3   5   5]
- [ 19  24 138  42   7  36  39]
- [ 18   5   6  94   2  16   6]
- [  5   7   8   2  62   2   3]
- [  7   0   1   8   0  31   9]
- [  8   4  13  13   3  19  61]]
-Node Classification on random seed  5146 -> 0.623
-Confusion Matrix:
- [[ 85   2   5   8   6   8   9]
- [  7 136   5   3   6   5   4]
- [ 22  29 131  43  27  30  27]
- [ 11   2  16 108   1   5  11]
- [  4  10   1   0  59   2   4]
- [  3   3   5   0   1  39   3]
- [  9   0  13   6   1  20  65]]
-Node Classification on random seed  5147 -> 0.617
-Confusion Matrix:
- [[ 55   3   2   8   2   9  17]
- [  6 134   4   2   5   5   8]
- [ 29  16 139  20  31  23  65]
- [  5   2  22 106   1   4  16]
- [  3   6   6   1  55   2   2]
- [  3   0   0   1   0  50   5]
- [ 16   3   9   7   4  10  78]]
-Node Classification on random seed  5148 -> 0.623
-Confusion Matrix:
- [[ 72   6   2   2   4  12   2]
- [  4 136   5   8   8   7   2]
- [ 21  26 145  36  19  18  45]
- [ 13   6  10 105   4  12  19]
- [  2  11   1   0  51   0   2]
- [  1   0   0   2   4  48   9]
- [  9   3   7   8  12  15  66]]
-Node Classification on random seed  5149 -> 0.626
-Confusion Matrix:
- [[ 77   3   5   4  10  19  12]
- [  1 123   3   4   7   4   2]
- [ 24  25 148  33  18  23  22]
- [  8   7  12  98  10   5  16]
- [  2   7   4   1  63   1   3]
- [  2   1   3   1   1  49   5]
- [ 10   2  12   7  14  21  68]]
-Node Classification on random seed  5150 -> 0.596
-Confusion Matrix:
- [[ 68   2  11   4   3  12   2]
- [  6 129   3   3   9   6   8]
- [ 22  20 114  44  44  25  39]
- [  9   3  17  89   6   9  14]
- [  1   3  14   1  61   0   2]
- [  5   0   3   1   0  42   2]
- [ 14   5  10   5   1  16  93]]
-Node Classification on random seed  5151 -> 0.616
-Confusion Matrix:
- [[ 64   5   3   6   3  12  12]
- [  6 121   3   1  11   5   7]
- [ 14  26 134  47  24  29  39]
- [  4   1  15 111   1   5  15]
- [  1   4   5   3  60   1   1]
- [  3   1   3   3   0  41  14]
- [  9   1   8  11   8  14  85]]
-Node Classification on random seed  5152 -> 0.557
-Confusion Matrix:
- [[ 47   5   3   3   7  13  10]
- [  3 129  11   1  22   4   5]
- [ 37  20 130  40  39  20  35]
- [ 15  10  18  97   9   5   6]
- [  0   4   1   2  62   0   1]
- [  3   0   2   1   0  45   5]
- [  6   9   6  16  23  23  47]]
-Node Classification on random seed  5153 -> 0.607
-Confusion Matrix:
- [[ 63   7   4   8   3  21   3]
- [  6 126   4   3   8   3   4]
- [ 33  13 168  23  14  25  44]
- [  3  16  11  79   6   5  24]
- [  1  11   8   2  64   0   1]
- [  4   4   1   0   0  40   4]
- [ 17   6   8  11   6  18  67]]
-Node Classification on random seed  5154 -> 0.602
-Confusion Matrix:
- [[ 62   2   4   1   3  14  17]
- [  8 121   2   2   6   1  10]
- [ 26  27 146  30  25  13  48]
- [  7   4  14 103  15   3  11]
- [  1   9   3   1  63   1   1]
- [  6   3   4   3   0  39   9]
- [  8   4   7  28   7  10  68]]
-Node Classification on random seed  5155 -> 0.607
-Confusion Matrix:
- [[ 65   1   3   4   6  15   4]
- [  9 108   8   0  13   4   2]
- [ 39  25 150  33  27  21  30]
- [  9   3  11 116   2   7  17]
- [  1   8   6   1  57   0   2]
- [  6   1   2   4   0  46   7]
- [ 14   6  16   6   5  15  65]]
-Node Classification on random seed  5156 -> 0.635
-Confusion Matrix:
- [[ 63   1   8   4   4  13  24]
- [ 11 129   4   5   5   0   3]
- [ 17  19 149  32  16  27  35]
- [  7   4   7 120   5   5  16]
- [  3   7   4   1  64   2   2]
- [  7   3   1   4   1  40   3]
- [ 12   1   5   6  11  20  70]]
-Node Classification on random seed  5157 -> 0.6
-Confusion Matrix:
- [[ 60   4   1   4   4  18  17]
- [  4 123   1   2   8   5   3]
- [ 17  34 119  32  21  38  51]
- [ 10   2  11 106   5  11  12]
- [  5   7   3   2  53   1   0]
- [  4   2   1   7   1  47   1]
- [ 13   7   4   4   5  18  92]]
-Node Classification on random seed  5158 -> 0.655
-Confusion Matrix:
- [[ 84   4   5   3   5   5  15]
- [  2 130   2   3  15   1   2]
- [ 19  21 156  24  40  29  24]
- [ 11   4   9 103   3   3  13]
- [  2   5   1   3  67   0   0]
- [  4   1   2   3   2  33   8]
- [ 14   3   8   4  12  11  82]]
-Node Classification on random seed  5159 -> 0.615
-Confusion Matrix:
- [[ 76   3   4  16   4   4   4]
- [  5 127   4   4  10   2   2]
- [ 27  12 156  47  24  12  37]
- [ 23   5  16  94   4   9  17]
- [  1   8   3   2  53   0   3]
- [  3   1   2   3   1  43  10]
- [ 16   5   4   9   8  11  66]]
-Node Classification on random seed  5160 -> 0.577
-Confusion Matrix:
- [[ 78   1   5   6   2  18   8]
- [  7 116   6   2   8   3   7]
- [ 16  28 112  35  75  16  27]
- [ 13   5  19 109   3   5  28]
- [  1   4   1   0  58   3   1]
- [  3   1   6   3   1  45   2]
- [ 12   1   4   7  10  20  59]]
-Node Classification on random seed  5161 -> 0.646
-Confusion Matrix:
- [[ 65   4   3   1   1  11  13]
- [  3 122   8  10   6   1   2]
- [ 22  19 179  37  22  15  25]
- [ 17   2  13  98   9  11  12]
- [  1   7   7   2  66   1   2]
- [  5   1   1   0   2  46   4]
- [ 19   5   2   6   5  17  70]]
-Node Classification on random seed  5162 -> 0.633
-Confusion Matrix:
- [[ 62   2   1   3   5  11  14]
- [  1 119   4   8   4   2   6]
- [ 34  10 158  47  14  30  30]
- [ 13   4  18  99   6   3  15]
- [  3   8   7   0  59   1   2]
- [  2   1   2   0   1  56  10]
- [  5   2   8  13   3  14  80]]
-Node Classification on random seed  5163 -> 0.619
-Confusion Matrix:
- [[ 76   4   4   7   5  11   4]
- [  8 122   9   3   5   1   2]
- [ 22  28 143  38  30  25  36]
- [  9   4  14 103   0   6  13]
- [  1   5   4   0  64   0   5]
- [  7   0   1   5   1  36   3]
- [ 15   6   5   5   9  21  75]]
-Node Classification on random seed  5164 -> 0.584
-Confusion Matrix:
- [[ 67   2   3   6   7  12  12]
- [  3 125  12   1   4   3   6]
- [ 14  15 106  41  46  25  70]
- [ 11   4  11 103   7   6  18]
- [  0   5   4   3  56   0   1]
- [  4   3   3   5   4  40   7]
- [  6   4   2   4   6  16  87]]
-Node Classification on random seed  5165 -> 0.607
-Confusion Matrix:
- [[ 75   0   3  10   5   7  15]
- [  6 125   7   3   2   4   5]
- [ 17  25 132  40  19  38  45]
- [  6   5  17  90   4   4  15]
- [  1   6   4   5  62   0   3]
- [  3   4   3   2   2  42   7]
- [  6   5  10   7   8  15  81]]
-Node Classification on random seed  5166 -> 0.619
-Confusion Matrix:
- [[ 70   3  10   5   3   5   9]
- [  2 127   3   1   4   0   3]
- [ 19  29 162  25  22  18  63]
- [ 16   6  18  97   1   6   8]
- [  4   8   5   2  50   1   4]
- [  3   3   2   4   2  40   5]
- [ 18   2  10   5   5  19  73]]
-Node Classification on random seed  5167 -> 0.624
-Confusion Matrix:
- [[ 67   1   3   8   3  24   7]
- [  2 153   7   3   2   3   2]
- [ 25  26 143  38  15  28  35]
- [ 14   5   6 101   8  11  13]
- [  2   7   4   0  57   3   0]
- [  6   3   1   3   0  37   2]
- [ 12   4   4   6   3  27  66]]
-Node Classification on random seed  5168 -> 0.625
-Confusion Matrix:
- [[ 86   3   2   2   3  15   5]
- [  4 124   4   3  16   5   4]
- [ 19  37 119  33  24  21  31]
- [ 29   2  10  98   2   2  28]
- [  0   6   5   0  70   0   3]
- [  4   3   4   0   0  48   5]
- [ 14   3   3   3   3  15  80]]
-Node Classification on random seed  5169 -> 0.573
-Confusion Matrix:
- [[ 88   3   3  14   2   6   4]
- [  6 119   7   2   7   2   3]
- [ 27  29 120  17  24  44  43]
- [  8   7  34  89   3  12  11]
- [  1  12   3   1  40   2   3]
- [ 10   2   1   2   0  46   1]
- [ 12   5  10   8  16  20  71]]
-Node Classification on random seed  5170 -> 0.565
-Confusion Matrix:
- [[ 60   3   2   4   3  25  15]
- [  0 134   5   3   8   9   1]
- [ 17  22 145  47  34  22  44]
- [ 11   5  12  95  15   5   8]
- [  3   7   5   2  57   0   0]
- [  6   3   1   1   1  36   6]
- [ 12   7  13  13  23  12  38]]
-Node Classification on random seed  5171 -> 0.628
-Confusion Matrix:
- [[ 78   2   5   6   3  11   4]
- [  6 116   6   7  12   1   4]
- [ 23  28 131  30  22  15  44]
- [ 15   9  13 117   5   6   4]
- [  2   9   2   4  68   3   1]
- [  6   4   3   2   0  40   3]
- [ 15   4   5  13   3  12  78]]
-Node Classification on random seed  5172 -> 0.604
-Confusion Matrix:
- [[ 75   2   5  13   9   7   3]
- [  1 110   9   4  14   3   6]
- [ 32  14 159  36  20  18  48]
- [ 24   5  19  91   2   2   8]
- [  0   3   5   0  71   0   8]
- [  4   2   9   1   0  40   9]
- [ 17   3  11   9   5   6  58]]
-Node Classification on random seed  5173 -> 0.579
-Confusion Matrix:
- [[ 75   2   3   8   2  11   8]
- [  3 108   5   4   8   6   6]
- [ 28  46 106  57  26  19  41]
- [ 11   3   8 116   3   4  13]
- [  1  17   3   4  50   0   4]
- [  4   2   5   4   0  46   4]
- [  6   5   7  14   7   9  78]]
-Node Classification on random seed  5174 -> 0.654
-Confusion Matrix:
- [[ 83   2   1   3   1   1  24]
- [  7 124   9   1  11   0   4]
- [ 14  14 172  29  30  17  34]
- [  9   6  18  98   7   6  10]
- [  5   7   5   1  64   0   2]
- [  9   1   2   1   0  35   6]
- [  8   8   8  10   8   7  78]]
-Node Classification on random seed  5175 -> 0.6
-Confusion Matrix:
- [[ 74   7   2   7   3   9  15]
- [  5 114   2   7   8   2   4]
- [ 30  19 135  43  21  21  42]
- [ 16   6  23  95  11   9  10]
- [  2   6   6   1  64   1   2]
- [  6   0   1   0   0  46   6]
- [ 12   3  12   4   8   8  72]]
-Node Classification on random seed  5176 -> 0.657
-Confusion Matrix:
- [[ 64   2   4   3   2  19  17]
- [  3 126   3   5   3   5   4]
- [ 15  11 164  27  27  21  28]
- [ 14   4   8 110   9  10   7]
- [  2   6   4   1  66   0   2]
- [  1   1   3   0   3  47  10]
- [  7   4   7  11   3  27  80]]
-Node Classification on random seed  5177 -> 0.577
-Confusion Matrix:
- [[ 56  11   4   6   3  15  15]
- [  6 131   2   1   7   5   7]
- [ 17  35  95  44  42  19  37]
- [ 14   4  11 120   9   9  11]
- [  5   4   1   2  60   0   4]
- [  2   0   3   0   1  45   5]
- [ 12   4  18   8  13   7  70]]
-Node Classification on random seed  5178 -> 0.546
-Confusion Matrix:
- [[ 61   1   2   3   7  20   6]
- [  4 122  10   1   8   3   2]
- [ 13  16 107  46  72  38  29]
- [  9   2  28  88   7  14   6]
- [  0   5   4   1  59   2   1]
- [  9   1   2   4   1  39   2]
- [ 10   3   8  10  11  33  70]]
-Node Classification on random seed  5179 -> 0.646
-Confusion Matrix:
- [[ 77   3   2   5   3  13   6]
- [  4 123   1   5  13   6   3]
- [ 22  18 167  31  27  16  27]
- [ 16   4  20 104   4   3   8]
- [  0   5   2   2  60   0   3]
- [  6   5   5   2   2  39   3]
- [ 18   4   9   8   5  15  76]]
-Node Classification on random seed  5180 -> 0.627
-Confusion Matrix:
- [[ 62   7   9   5   4  11  10]
- [  3 131   3   2   4   3   2]
- [ 20  10 149  31  23  17  51]
- [ 17   5  11 119   6   2  13]
- [  0   7   5   0  58   3   0]
- [ 10   3   0   3   1  36   3]
- [ 19   9  15  12   4  10  72]]
-Node Classification on random seed  5181 -> 0.605
-Confusion Matrix:
- [[ 88   1   1   9   3   9   7]
- [  1 129   4   5   3   5   7]
- [ 16  34 115  50  18  28  33]
- [ 17   3  20 104  10   4  19]
- [  1   6   3   3  53   4   1]
- [ 10   1   2   1   1  41  11]
- [ 13   2   9   3   4  13  75]]
-Node Classification on random seed  5182 -> 0.616
-Confusion Matrix:
- [[ 66   4   8   4   1   4  15]
- [  1 149   4   0  10   1   4]
- [ 35  29 136  38  13  14  51]
- [  9   5  14  94   7  10  17]
- [  5  12   2   2  49   0   1]
- [  3   5   2   0   0  41   4]
- [  9   8  16   6   4   7  81]]
-Node Classification on random seed  5183 -> 0.625
-Confusion Matrix:
- [[ 69   5   5   5   5  11  10]
- [ 10 118   6   2  12   7   0]
- [ 19  13 145  21  36  29  39]
- [ 10   6  20  96   7  12  13]
- [  0   4   2   0  75   0   1]
- [  5   0   3   2   1  41   4]
- [ 17   4  10   4   5  10  81]]
-Node Classification on random seed  5184 -> 0.659
-Confusion Matrix:
- [[ 82   1   6   2   0   6   9]
- [  0 122   2   3  10   3   3]
- [ 31  16 152  47  17  24  22]
- [ 17   2  14 108   2   3  10]
- [  1  11   6   2  64   0   1]
- [  2   0   1   5   1  46   4]
- [  9   4  17   6   6  15  85]]
-Node Classification on random seed  5185 -> 0.624
-Confusion Matrix:
- [[ 60   3   4   5   6  17   6]
- [  3 127   8   2   9   0   4]
- [ 24  24 146  56  19  10  39]
- [  9   1  20 104  20   8   7]
- [  2   2   3   2  52   1   2]
- [  3   0   2   2   1  50   5]
- [  9   2  12   8   5  11  85]]
-Node Classification on random seed  5186 -> 0.601
-Confusion Matrix:
- [[ 81   3   5   4   0  13  10]
- [  5 116   0   2  11   3  11]
- [ 12   7 108  40  45  39  37]
- [  7   7  18 125   5   4   6]
- [  1   6   4   0  61   0   2]
- [  8   2   3   3   0  44   7]
- [ 11   2  11  23  11  11  66]]
-Node Classification on random seed  5187 -> 0.593
-Confusion Matrix:
- [[ 54   2  10  10   6  16  11]
- [  6 109  12   5  11   3   5]
- [ 31  17 139  29  28  20  49]
- [ 12   2  13 101   8   7  12]
- [  1   1   5   1  70   2   6]
- [  2   0   4   1   2  47   3]
- [  7   3   9  22   7   6  73]]
-Node Classification on random seed  5188 -> 0.61
-Confusion Matrix:
- [[ 56   2   2   5   3  12  13]
- [  7 131   3   8   9  10   5]
- [ 25  21 148  23  28  19  43]
- [ 20   5  10  94   9  11  14]
- [  2   6   3   4  61   2   2]
- [  2   4   2   1   1  45   5]
- [ 13   3   9   6   6  12  75]]
-Node Classification on random seed  5189 -> 0.6
-Confusion Matrix:
- [[ 71   4   4   5   4   8   8]
- [  5 131   1   5  15   5   9]
- [ 33  12 129  33  32   7  59]
- [ 11   5  14  94   9  10  11]
- [  2   6   3   1  71   0   5]
- [  4   1   6   0   1  41   4]
- [ 17   3   6  16   6  10  63]]
-Node Classification on random seed  5190 -> 0.611
-Confusion Matrix:
- [[ 78   2   2   6   5  10   4]
- [ 12 118  10   1   6   4   2]
- [ 19  31 122  29  38  34  43]
- [ 10   3  10 112   5   4  14]
- [  1   8   0   0  60   3   4]
- [  2   1   1   2   0  53   4]
- [ 11   2  24   8   6   8  68]]
-Node Classification on random seed  5191 -> 0.609
-Confusion Matrix:
- [[ 71   2   1   6   1  10  15]
- [  3 138   4   2   3   9   2]
- [ 24  28 143  56  25  28  35]
- [ 14   8  15  94   4   7   7]
- [  2   6   1   0  55   1   2]
- [  2   0   5   2   0  40   5]
- [ 15   2   9   6   8  16  68]]
-Node Classification on random seed  5192 -> 0.571
-Confusion Matrix:
- [[ 56   3   5   5   3  12  16]
- [ 15 101  15   1  10   5   7]
- [ 19  19 141  39  30  18  60]
- [  4  13  17 103   4   8  19]
- [  3   4   3   2  55   1   2]
- [ 13   0   1   1   0  40   3]
- [ 11   4  10   4  10  10  75]]
-Node Classification on random seed  5193 -> 0.608
-Confusion Matrix:
- [[ 53   5   2   2   2  17  20]
- [  4 125   3   1   9   1   3]
- [ 25  32 141  48  14  25  35]
- [ 15   3  11 106   4   6  19]
- [  0   5   5   2  65   0   1]
- [  3   2   2  14   1  43   2]
- [ 14   3  16   4   4   8  75]]
-Node Classification on random seed  5194 -> 0.638
-Confusion Matrix:
- [[ 66   4   6   5   3   7   3]
- [  1 131   4   3   7   5   4]
- [ 16  12 161  39  17  36  25]
- [  8   2  17 123   7  11  15]
- [  1  12   3   0  62   0   5]
- [  5   5   1   1   0  38   3]
- [ 15   2  20   9   6  17  57]]
-Node Classification on random seed  5195 -> 0.658
-Confusion Matrix:
- [[ 84   3   0   6   3  11   3]
- [  2 118  13   7   3   6   1]
- [ 26  21 169  20  21  19  37]
- [ 13   4  13  95   2  10  13]
- [  1   8   3   0  65   0   3]
- [  6   0   0   4   1  53   2]
- [ 26   3   2   3   9  14  74]]
-Node Classification on random seed  5196 -> 0.582
-Confusion Matrix:
- [[ 74   0   2   8   4  10  11]
- [  3 124   6   3  12   2   6]
- [ 35  30  99  54  30  28  33]
- [ 16   6  12  99  11   6  15]
- [  1   8   3   2  52   1   2]
- [  2   0   4   6   0  43   8]
- [  6   1   5   4  11  11  91]]
-Node Classification on random seed  5197 -> 0.619
-Confusion Matrix:
- [[ 71   5   3   5   2   8  11]
- [  8 135   5   1   8   5   2]
- [ 27  23 155  33  28  21  36]
- [ 20   2   7  91   8   7  17]
- [  1  10   4   0  62   1   4]
- [  8   2   1   2   0  35   7]
- [  7   2  11   4   7  18  70]]
-Node Classification on random seed  5198 -> 0.639
-Confusion Matrix:
- [[ 76   2   2   2   4   9  21]
- [  2 137   6   2   6   2   4]
- [ 26  28 139  18  16  21  49]
- [  9   4  13 124   5   5   9]
- [  2  10   3   2  57   0   6]
- [  6   0   0   3   7  39   5]
- [  7   3  14   8   5  15  67]]
-Node Classification on random seed  5199 -> 0.55
-Confusion Matrix:
- [[ 73   5   2   7   5  17   9]
- [  9 131   2   7   6   4   5]
- [ 30  35  93  21  52  20  53]
- [ 16   3  27  92   5   7  13]
- [  2   2   0   0  61   2   5]
- [ 12   0   3   3   0  47   4]
- [ 21   0   5  11   4  16  53]]
-Node Classification on random seed  5200 -> 0.628
-Confusion Matrix:
- [[ 68   1   0   6   2   7  14]
- [  2 118  11   5   5  11   2]
- [ 28  15 139  42  17  28  39]
- [ 13   6  19 107   4   4  12]
- [  3   8   1   1  60   1   2]
- [  6   2   0   0   0  53   4]
- [  8   3   9  12   4  15  83]]
-Node Classification on random seed  5201 -> 0.635
-Confusion Matrix:
- [[ 69   3   1   6   4   9  17]
- [  2 117   8   0   7   3  10]
- [ 41  15 149  27  17  24  40]
- [ 12   4  18 111   6   3   4]
- [  2   8   4   1  55   0   4]
- [  9   0   0   1   0  46   2]
- [ 14   5   6  13   6   9  88]]
-Node Classification on random seed  5202 -> 0.595
-Confusion Matrix:
- [[ 50   0   0   9   4  22  18]
- [  6 118   8   3  15   7  11]
- [ 22  23 153  31  27  19  38]
- [ 10   1   7  96  11   6  24]
- [  2  15   4   0  61   0   2]
- [  3   0   0   1   2  47   6]
- [  5   7   1   5  13  17  70]]
-Node Classification on random seed  5203 -> 0.65
-Confusion Matrix:
- [[ 84   2   1  10   2  14   1]
- [  4 125   6   5  10   2   4]
- [ 28  22 171  27  17  19  40]
- [  3   3  23  91   4   1  14]
- [  0   5   4   3  47   0   8]
- [  6   1   2   1   0  55   7]
- [ 17   3   2   7   9  13  77]]
-Node Classification on random seed  5204 -> 0.636
-Confusion Matrix:
- [[ 79   4   0   3   2  11   9]
- [  6 132   2   6   2   3   4]
- [ 13  42 149  41  18  11  39]
- [ 11   3   6 124   8   6   8]
- [  1  10   9   1  52   1   0]
- [  5   7   2   3   3  37   7]
- [ 15   4  19   6   1  12  63]]
-Node Classification on random seed  5205 -> 0.63
-Confusion Matrix:
- [[ 76   2   0   7   0   8  11]
- [  5 141   4   0   4   3   3]
- [ 25  23 143  30  27   9  46]
- [  8   3  20 100   3   2  14]
- [  1  14   5   2  60   0   1]
- [  8   1   7   0   8  43   5]
- [ 17  10   5   4  15  10  67]]
-Node Classification on random seed  5206 -> 0.642
-Confusion Matrix:
- [[ 74   3   2   4   1   7  13]
- [  0 127  10   0  14   1   3]
- [ 26  30 158  32  33  29  18]
- [ 13   8   8 121   2   3   7]
- [  3   2   5   1  48   1   5]
- [  8   1   0   1   2  46   1]
- [ 15   6   8  10   7  15  68]]
-Node Classification on random seed  5207 -> 0.606
-Confusion Matrix:
- [[ 60  10   4   3   3  18  14]
- [  2 123   6   8   5   5   0]
- [ 25  26 142  35  27  23  31]
- [ 14   4   9 102   5   7  22]
- [  0  12   1   2  63   0   2]
- [  6   0   4   2   0  44   4]
- [ 18   6   5   5   7  14  72]]
-Node Classification on random seed  5208 -> 0.617
-Confusion Matrix:
- [[ 69   3  13   5   6   6   9]
- [  7 145  10   1   6   2   2]
- [ 21  11 143  30  24  25  32]
- [  8   5  24 106   4   8  15]
- [  3   3   8   3  52   0   2]
- [  7   0   4   2   2  41   4]
- [ 16   4  20   5  11  12  61]]
-Node Classification on random seed  5209 -> 0.576
-Confusion Matrix:
- [[ 60   7   1  13   5   8  16]
- [  3 121   6   1   6   1   6]
- [ 42  26 115  35  26  34  26]
- [ 18   3  17  98   1   8  17]
- [  1   7   3   5  66   3   2]
- [  9   8   1   0   2  43   5]
- [ 14   4  11   0   9  14  73]]
-Node Classification on random seed  5210 -> 0.616
-Confusion Matrix:
- [[ 70   1  13   2   6  10  10]
- [  4 129   8   4   5   3  10]
- [ 14  11 136  46  39  14  39]
- [ 13   5  17  83   8   2  23]
- [  2   5   4   0  66   2   5]
- [  7   1   2   2   0  44   6]
- [  9   4  10   4   3  11  88]]
-Node Classification on random seed  5211 -> 0.603
-Confusion Matrix:
- [[ 62   2  15   4   2  13   6]
- [  8 134   3   1  11   0   1]
- [ 21  21 151  45  24  27  45]
- [  4   3  14 105   1   5  17]
- [  6  10   6   1  60   0   1]
- [  4   3   2   0   1  23  16]
- [ 12   5   7   8  15   7  68]]
-Node Classification on random seed  5212 -> 0.582
-Confusion Matrix:
- [[ 68   2   5   9   3  14   3]
- [  1 145  11   3   5   7   2]
- [ 23  13 125  52  32  33  24]
- [ 19   3  12 101   5  11   9]
- [  0   4   4   2  60   0   5]
- [  5   2   2  11   5  36   2]
- [ 10   2   5  22   9  27  47]]
-Node Classification on random seed  5213 -> 0.651
-Confusion Matrix:
- [[ 59   1   7   9   4  10  21]
- [  2 118   7   1  12   4   3]
- [ 29  14 185  20  22  17  44]
- [  7   8  17  98   3   3   8]
- [  2   4   5   0  60   1   1]
- [  3   1   1   2   0  53   2]
- [ 15   4   8   8   7  12  78]]
-Node Classification on random seed  5214 -> 0.609
-Confusion Matrix:
- [[ 79   3   4   8   6  22   1]
- [  5 128   3   4  10   2   5]
- [ 16   7 155  33  43  29  40]
- [ 18   5  20  78   4   9   5]
- [  0   8   5   5  54   1   3]
- [  1   0   4   3   0  52   2]
- [  6   3   5  12  12  19  63]]
-Node Classification on random seed  5215 -> 0.64
-Confusion Matrix:
- [[ 66   2   8  10   7   4  19]
- [  0 118   7   3   9   2   1]
- [ 17  21 162  23  30  20  29]
- [ 10   8   9 107   4   7  14]
- [  1  13   6   7  61   1   1]
- [  2   1   2   0   2  49  10]
- [  4   2  14   3  13  14  77]]
-Node Classification on random seed  5216 -> 0.649
-Confusion Matrix:
- [[ 86   3   3   3   1  11   2]
- [  3 134   5   1   9   4   2]
- [ 32  25 142  35  14  10  52]
- [ 17   5   3 101   4  11  11]
- [  3   8   6   0  60   2   2]
- [  4   1   5   1   1  55   3]
- [ 15   1   6   9   8  10  71]]
-Node Classification on random seed  5217 -> 0.591
-Confusion Matrix:
- [[ 64   1   6   8   8  10  13]
- [  2 138   4   7   6   4   5]
- [ 23  24 108  38  42  34  31]
- [  7   7  10 106   3   7  12]
- [  0   5   2   4  69   0   3]
- [  5   2   5   0   3  42   6]
- [ 17   2  12  16   7   8  64]]
-Node Classification on random seed  5218 -> 0.653
-Confusion Matrix:
- [[ 67   6   7   4  11  12   3]
- [  2 142   5   5   5   2   2]
- [ 18  22 145  26  29  18  36]
- [ 10   4  10 114   4   1   8]
- [  1  13   1   3  77   1   0]
- [  5   4   2   2   1  43   4]
- [ 18   9   2   7  11  13  65]]
-Node Classification on random seed  5219 -> 0.631
-Confusion Matrix:
- [[ 64   3   4   2   6  13  12]
- [  5 117   8   0   7   5  12]
- [ 16  19 156  26  17  23  47]
- [  6   8  15 114   5   8  19]
- [  0  10   6   2  57   0   5]
- [  5   3   4   2   4  39   3]
- [  7   3   6   4   3  16  84]]
-Node Classification on random seed  5220 -> 0.603
-Confusion Matrix:
- [[ 80   2   2   4   6  14   4]
- [  2 125   5   7  14   1   3]
- [ 28  29 140  26  26  28  46]
- [  9   5  19  85  14  10  10]
- [  1   3   2   3  58   1   2]
- [  2   1   2   2   0  51   5]
- [ 11   5   0  11  13  19  64]]
-Node Classification on random seed  5221 -> 0.573
-Confusion Matrix:
- [[ 63   0   7  11   1  14   6]
- [ 10 126   8   3   8   4   2]
- [ 27  33 126  29  52  23  29]
- [  6   4  17  84  16  18   9]
- [  0   8   1   1  58   2   6]
- [  4   0   0   5   0  52   4]
- [  7   7  11  14   5  15  64]]
-Node Classification on random seed  5222 -> 0.614
-Confusion Matrix:
- [[ 59   2   6   5   5  18  13]
- [  0 107  15   2  13   4   3]
- [ 13  24 138  30  35  31  26]
- [ 18   5  10 106  11   4  10]
- [  0   9   8   1  66   1   1]
- [  4   1   2   0   1  54   2]
- [ 12   5   4   2   7  23  84]]
-Node Classification on random seed  5223 -> 0.607
-Confusion Matrix:
- [[ 89   2   4   0   3   3   7]
- [  3 127  12   4   2   2   3]
- [ 23  34 133  53  23  21  47]
- [  6   4  13  94   5   6  14]
- [  7   6   5   2  56   0   0]
- [  7   3   5   1   0  30   9]
- [ 23   4   9   4   5   9  78]]
-Node Classification on random seed  5224 -> 0.588
-Confusion Matrix:
- [[ 70   0   3   7   6  19   6]
- [ 10 117   8   2   6   2   1]
- [ 33  24 124  37  44  33  26]
- [  9   4   7  96  18  10   2]
- [  9   6   2   2  57   2   3]
- [  3   0   3   6   0  50   2]
- [ 13   4   4   8  14  14  74]]
-Node Classification on random seed  5225 -> 0.624
-Confusion Matrix:
- [[ 61   4   2   7   4  16  14]
- [  4 133   5   5   7   4   3]
- [ 25  20 125  47  37  13  33]
- [ 20   5   8 107   7   6   9]
- [  2   5   4   1  55   0   0]
- [  7   3   0   2   0  50   3]
- [ 11   5   3   3   7  15  93]]
-Node Classification on random seed  5226 -> 0.632
-Confusion Matrix:
- [[ 61   4   2   4   3  16  12]
- [  3 128   4   2   4   3   6]
- [ 18  16 164  35  16  11  55]
- [ 13   3  23  91   2   7  13]
- [  1  10   4   0  65   1   2]
- [  9   1   2   0   4  45   6]
- [ 14   3   6   9   7  14  78]]
-Node Classification on random seed  5227 -> 0.657
-Confusion Matrix:
- [[ 72   1   1   5   3   7   7]
- [  1 134   7   1   9   0   5]
- [ 26  21 151  26  32  22  43]
- [  3   2  25 101   4   6  11]
- [  1   9   4   0  69   2   1]
- [ 10   3   0   1   2  39   4]
- [ 11   6   9   2   4   6  91]]
-Node Classification on random seed  5228 -> 0.584
-Confusion Matrix:
- [[ 65   3   2   6   8  14   7]
- [  3 119   9   4  14   2   2]
- [ 25  38 123  22  23  28  40]
- [ 11   3  15  95   7   6  15]
- [  0   6   3   1  75   0   1]
- [  6   1   2   0   4  49   8]
- [ 14   4  17   7  24  11  58]]
-Node Classification on random seed  5229 -> 0.635
-Confusion Matrix:
- [[ 80   7   0   8   2   6   8]
- [  8 128   4   6  10   2   1]
- [ 21  24 156  41  23  13  35]
- [ 10   6  18  92   5   5  18]
- [  0   7   1   0  75   1   1]
- [ 10   2   4   2   0  41   3]
- [  8   7  12   5   8  13  63]]
-Node Classification on random seed  5230 -> 0.673
-Confusion Matrix:
- [[ 85   1   3  13   3  10  10]
- [  3 110  12   4   8   0   4]
- [ 20  23 178  12  21  19  39]
- [  6   1  14 114   0   4  19]
- [  3   4   5   1  59   1   5]
- [  7   6   1   2   0  46   5]
- [  7   2  10   4   4  11  81]]
-Node Classification on random seed  5231 -> 0.628
-Confusion Matrix:
- [[ 75   2   4   1   3  11   9]
- [  2 136   4   3   9   3   5]
- [ 28  26 105  57  37  10  34]
- [  9   5  14 110  11   9   9]
- [  0   3   2   1  72   0   4]
- [  5   2   1   4   2  57   1]
- [ 15   2   8   4   6   7  73]]
-Node Classification on random seed  5232 -> 0.574
-Confusion Matrix:
- [[ 60   5   3  10   1   9   5]
- [  6 129  13   0   7   9   1]
- [ 30  32 124  33  38  23  22]
- [ 12   5  11  90  10   7  18]
- [  0   5   8   0  73   0   2]
- [  5   2   4   2   1  41   3]
- [ 15   5   7   9  26  22  57]]
-Node Classification on random seed  5233 -> 0.62
-Confusion Matrix:
- [[ 77   2   2   3  11   8  11]
- [ 10 115   5   2  16   4   3]
- [ 15  21 163  44  23  18  35]
- [ 10   1  23  99   6   6  20]
- [  3   2   7   2  57   0   2]
- [  9   0   1   2   4  35   6]
- [ 13   2  11   0   5  12  74]]
-Node Classification on random seed  5234 -> 0.589
-Confusion Matrix:
- [[ 62   3   1  13   6  19   9]
- [  5 124   9   2  11   0   9]
- [ 31  12 134  36  21  38  35]
- [ 19   1  16  99   5   4  23]
- [  1   5   5   0  61   0   2]
- [  6   0   3   4   0  35   5]
- [ 14   2  11  13   2  10  74]]
-Node Classification on random seed  5235 -> 0.604
-Confusion Matrix:
- [[ 67   6   3   6   2  11  16]
- [ 11 123   1   4   3   2   9]
- [ 25  17 147  46  20  25  37]
- [ 11   7  15  98   4   5  11]
- [  0  13   3   2  57   1   1]
- [  7   0   4   7   3  45   2]
- [ 15   3   9   9   3  17  67]]
-Node Classification on random seed  5236 -> 0.608
-Confusion Matrix:
- [[ 75   3   0   3   2  10   5]
- [  5 130   3   1   6   3   2]
- [ 20  37 132  14  30  30  41]
- [ 18  11  27  77   8   3  16]
- [  3   6   6   2  55   0   2]
- [ 11   0   2   2   2  49   5]
- [ 14   4  13   2   6  14  90]]
-Node Classification on random seed  5237 -> 0.594
-Confusion Matrix:
- [[ 56   0   8   9  10   9  10]
- [  7 128   8   6  10   2   6]
- [ 17  15 123  36  36  32  29]
- [  9   2  14 114   9   9   3]
- [  2   5   6   5  61   2   4]
- [  6   1   1   4   2  45   5]
- [  8   1  13  15  12  18  67]]
-Node Classification on random seed  5238 -> 0.612
-Confusion Matrix:
- [[ 73   1   2   7   4  13   7]
- [  5 127   6   0   4   8   7]
- [ 22  18 120  53  22  31  40]
- [ 20   7  17  98   4   4   8]
- [  2   6   0   1  68   0   2]
- [  2   0   2   4   0  52   5]
- [ 10   1   6  10   6  21  74]]
-Node Classification on random seed  5239 -> 0.591
-Confusion Matrix:
- [[ 70   7   3   9   2   7   7]
- [  6 101   3   1  23   1   0]
- [ 28  15 147  32  41  35  30]
- [ 10   6  17 104   8   7  10]
- [  0   5   4   1  60   2   0]
- [ 10   2   1   4   0  54   2]
- [ 16   2  18   9   7  18  55]]
-Node Classification on random seed  5240 -> 0.642
-Confusion Matrix:
- [[ 64   1   3   2   4  17  16]
- [  9 122  12   2   6   2   7]
- [  9  31 170  26  22  24  33]
- [ 22   5  10  96   7   8  11]
- [  0   2   8   0  63   1   0]
- [  5   4   0   1   1  47   7]
- [  5   2  10   9   3  11  80]]
-Node Classification on random seed  5241 -> 0.582
-Confusion Matrix:
- [[ 66   3   4  10  10   6  13]
- [  1 120   3   8  21   2   5]
- [ 25  19 122  58  13  33  44]
- [ 12   2   9  98   8   6  22]
- [  1   3   7   2  68   1   2]
- [  5   1   2   8   0  35   1]
- [ 11   7  11   5   4  10  73]]
-Node Classification on random seed  5242 -> 0.647
-Confusion Matrix:
- [[ 89   7   3   2   2   3   6]
- [  5 135   3   4   5   1   6]
- [ 19  22 164  22  20  21  43]
- [  7   4  21  80   7   2  21]
- [  0  17   2   0  53   1   0]
- [  7   2   5   2   0  44   4]
- [ 14   7  18   2   7   9  82]]
-Node Classification on random seed  5243 -> 0.617
-Confusion Matrix:
- [[ 81   2   8   5   7   8   6]
- [  3 115   3   3  17  13   3]
- [ 20  30 143  35  26  22  43]
- [  4   5  15 106   3   2   9]
- [  0   6   1   4  55   3   1]
- [  9   0   3   0   2  45   3]
- [ 14   7  12   6   7  13  72]]
-Node Classification on random seed  5244 -> 0.594
-Confusion Matrix:
- [[ 67   2   5   9   5   9  12]
- [  3 114   5   1   9   3  10]
- [ 29  22 139  21  35  18  39]
- [ 11   3  23  97   4  15  18]
- [  1   7   9   0  62   1   4]
- [  0   3   4   2   1  39   4]
- [ 14   3  17   6   2  17  76]]
-Node Classification on random seed  5245 -> 0.645
-Confusion Matrix:
- [[ 64   1   4   2   4  14  14]
- [  6 119   4   3  10   1  17]
- [ 21  15 167  30  26  24  24]
- [ 11   0  19 129   8   2  14]
- [  3   5   7   4  56   0   2]
- [  5   0   2   1   1  41   8]
- [ 18   3   5   2   2  13  69]]
-Node Classification on random seed  5246 -> 0.611
-Confusion Matrix:
- [[ 56   1  14   0   5  15   4]
- [  3 129   8   4  10   2   6]
- [ 28  15 134  23  22  30  41]
- [  9   2  18  98   4   4  31]
- [  0   4   5   4  71   0   2]
- [  1   0  15   4   1  37   1]
- [ 10   2  20   1   8  12  86]]
-Node Classification on random seed  5247 -> 0.598
-Confusion Matrix:
- [[ 62   1   5   6   5  17  13]
- [  3 125  10   2  16   2   4]
- [ 30  21 114  39  18  27  50]
- [ 12   4   9 115   9   9   8]
- [  3   3   5   0  57   0   2]
- [  2   3   2   2   2  62   0]
- [ 20   2   3  16   3  14  63]]
-Node Classification on random seed  5248 -> 0.588
-Confusion Matrix:
- [[ 70   2   1   9   1   4  29]
- [  3 132   4   5   5   0  13]
- [ 24  21 127  51  35   9  57]
- [ 12   3  17 103   2   3  12]
- [  0   4   3   1  60   0   3]
- [  9   1   1   2   1  28  10]
- [ 11   0  12  12   6  14  68]]
-Node Classification on random seed  5249 -> 0.611
-Confusion Matrix:
- [[ 77   2   1   5   2  16   6]
- [  4 134   7   7   4   8   3]
- [ 19  30 146  19  29  23  28]
- [ 13   4  28  97   9   6  23]
- [  1   6   5   0  65   1   1]
- [  9   0   1   2   1  40   4]
- [ 16   7  10   3   8  18  52]]
-Node Classification on random seed  5250 -> 0.62
-Confusion Matrix:
- [[ 62   6   2   2   5  17   9]
- [ 11 122   3   4  13   1   3]
- [ 12  16 149  44  17  20  48]
- [ 20   1  23  87   6   4  18]
- [  2   7   7   0  64   0   2]
- [  6   3   1   2   0  58  12]
- [  7   1   4   6   8   7  78]]
-Node Classification on random seed  5251 -> 0.618
-Confusion Matrix:
- [[ 66   3   5   2   2  24  12]
- [  3 140   8   2   9   2   6]
- [ 34  18 136  31  17  28  31]
- [ 10   1  26 102   6   7  15]
- [  0   6   2   1  52   2   2]
- [  1   1   1   0   4  52  11]
- [  5   1  13   3  15  12  70]]
-Node Classification on random seed  5252 -> 0.651
-Confusion Matrix:
- [[ 67   1   9   3   5  11   4]
- [  3 125   2   1   6   8  10]
- [ 20  22 166  31   8  43  16]
- [ 12   5  22 106   8   4  11]
- [  0  15   3   0  59   2   1]
- [  3   1   2   3   1  54   7]
- [  5   1   6   7   6  21  74]]
-Node Classification on random seed  5253 -> 0.588
-Confusion Matrix:
- [[ 68   1   3   9   4  26   5]
- [  0 102   5   8  17   4   7]
- [ 16  10 141  44  33  31  43]
- [ 15   2  17  91   7   9  24]
- [  2   1   7   1  64   1   2]
- [  1   4   1   1   0  54   2]
- [  4   3  13   2   8  19  68]]
-Node Classification on random seed  5254 -> 0.603
-Confusion Matrix:
- [[ 60   8   5   4   6  16   9]
- [  4 125   1   2  15   1   3]
- [ 20  17 134  32  30  30  50]
- [ 14   4  10 101  10   4   8]
- [  3   5   2   0  68   1   5]
- [  2   0   4   4   0  52   6]
- [ 11   6  11  10  13  11  63]]
-Node Classification on random seed  5255 -> 0.585
-Confusion Matrix:
- [[ 67   3   8   7   6   7  16]
- [  1 129   6   1  14   2   3]
- [ 23  12 117  29  53  40  50]
- [  5   5  11  97  10   9  16]
- [  1  11   3   0  53   0   2]
- [  8   1   3   2   1  46   8]
- [  4   4  11   3   6  10  76]]
-Node Classification on random seed  5256 -> 0.637
-Confusion Matrix:
- [[ 67   6   0   4   0  13  16]
- [  8 126   9   5   6   1   6]
- [ 27  15 153  38  44   7  36]
- [  7   3   9 107   3  11   6]
- [  0   7   6   0  70   1   3]
- [  2   0   3   1   0  45   7]
- [  9   2   7   4  17  14  69]]
-Node Classification on random seed  5257 -> 0.632
-Confusion Matrix:
- [[ 76   4   2   3   1  11   7]
- [  1 134   5   2  15   4   3]
- [ 20  22 141  26  32  27  37]
- [  9   5  25 103   2   6  11]
- [  1   5   7   5  58   0   4]
- [  1   1   2   1   0  42   1]
- [  6   5  14   9   9  17  78]]
-Node Classification on random seed  5258 -> 0.606
-Confusion Matrix:
- [[ 84   7   3   1   2  11   8]
- [  4 133   0   2  14   2   4]
- [ 12  30 142  19  21  28  39]
- [ 11   2  21  76  11  11  29]
- [  0   6   2   0  66   1   5]
- [  7   0   1   2   0  41   7]
- [ 17   5   9   6  12  22  64]]
-Node Classification on random seed  5259 -> 0.576
-Confusion Matrix:
- [[ 69   3   9   7   7   4  13]
- [  6 125   3   2  10  10   1]
- [ 24  28 124  62  24  26  33]
- [ 12   2  23  95   2   3  10]
- [  2   9   7   0  51   2   2]
- [  9   0   1   4   0  38   6]
- [  8   5  13  17   6   9  74]]
-Node Classification on random seed  5260 -> 0.589
-Confusion Matrix:
- [[ 46   9   6   3   4  18  15]
- [  4 137   6   2   5   0   7]
- [ 17  26 134  46  33  25  47]
- [ 13   6  13  92   2  14  10]
- [  0   6   5   7  56   1   2]
- [  3   1   4   1   2  41  10]
- [  5   7   5   7   5   9  83]]
-Node Classification on random seed  5261 -> 0.623
-Confusion Matrix:
- [[ 72   3   5   3   8  12   3]
- [  1 139   3   5   6   1   2]
- [ 20  22 145  24  34  33  31]
- [  8   7  15  98  11   3  22]
- [  2  10   5   4  61   2   0]
- [  5   1   1   3   1  46   7]
- [ 13   4  10   6   8  13  62]]
-Node Classification on random seed  5262 -> 0.647
-Confusion Matrix:
- [[ 63   2   3   3   5  11  12]
- [  1 121   4   1  22   0   3]
- [ 23  17 175  12  30  14  48]
- [  9   1  29  87   7   6  25]
- [  1   1   4   2  62   0   0]
- [ 10   1   2   2   1  41   7]
- [ 14   3   5   3   7   2  98]]
-Node Classification on random seed  5263 -> 0.609
-Confusion Matrix:
- [[ 61   2  10   3   4  10  22]
- [  5 111   5   1   5   3   1]
- [ 22  18 155  31  36  32  23]
- [  8   5  14 113   8   2  22]
- [  2   5   3   1  64   1   1]
- [  5   2   4   1   1  36   8]
- [ 14   3  17   5  13  13  69]]
-Node Classification on random seed  5264 -> 0.62
-Confusion Matrix:
- [[ 78   3   2   4   3  17   5]
- [  2 117   3   4  16   3   5]
- [ 27  26 127  55  21  22  41]
- [ 12   1  11 108   8   5   8]
- [  0   2   3   4  56   1   5]
- [  3   0   1   1   1  61   2]
- [ 13   2   8   5   7  18  73]]
-Node Classification on random seed  5265 -> 0.593
-Confusion Matrix:
- [[ 58   4  19   1   5  12   6]
- [  3 128   2   1   2   4   3]
- [ 23  24 145  35  39  22  60]
- [ 10   7  13  95   8   7   8]
- [  1   6   1   1  62   0   7]
- [  4   2   4   0   0  42   8]
- [ 14   6   5   9   7  14  63]]
-Node Classification on random seed  5266 -> 0.609
-Confusion Matrix:
- [[ 90   2   7   6   1   5   4]
- [  3 133   1   3   2   1   6]
- [ 18  38 109  55  34  22  38]
- [ 21   5  14 102   3  10   8]
- [  0   8   6   0  55   0   0]
- [  3   3   4   3   1  44   7]
- [  8   5  10  11   6   9  76]]
-Node Classification on random seed  5267 -> 0.617
-Confusion Matrix:
- [[ 56   1   4   6   6  11  11]
- [  1 125   3   3   9   1   8]
- [ 40  17 157  16  25  24  32]
- [ 11   1  13  83   5  24  11]
- [  2   8   5   0  60   1   1]
- [  4   2  12   0   0  51   3]
- [ 10   1  13   3  12  23  85]]
-Node Classification on random seed  5268 -> 0.621
-Confusion Matrix:
- [[ 88   4   7   5   0  12   3]
- [  5 126   9   1   5   8   3]
- [ 40   8 130  36  27  20  31]
- [  9   5  23  89   9   3  19]
- [  1   3   8   0  65   2   4]
- [  3   0   5   3   3  52   1]
- [ 11   4   6  14   6  13  71]]
-Node Classification on random seed  5269 -> 0.619
-Confusion Matrix:
- [[ 95   4   1   7   2  10   3]
- [  3 123   7  10  16   1   1]
- [ 15  24 144  33  29  26  37]
- [ 16  11  15  87   1   8  13]
- [  1   2   0   2  47   0   3]
- [  7   3   5   0   2  41   3]
- [ 17   2   8   4   6  23  82]]
-Node Classification on random seed  5270 -> 0.64
-Confusion Matrix:
- [[ 61   3   4   4   3  16  11]
- [  7 127   3   3   9   2   3]
- [ 37  19 156  23  31  19  27]
- [ 13   4  15 112   0   8  12]
- [  4   7   2   0  55   3   3]
- [  2   2   1   0   1  39   7]
- [ 14   4  11   1   7  15  90]]
-Node Classification on random seed  5271 -> 0.583
-Confusion Matrix:
- [[ 64   5   4   1   8  11  11]
- [  3 121  11   6   6   0  12]
- [ 30  19 117  31  23  30  60]
- [ 17   2  17 100   4   4  11]
- [  0   9  10   4  52   2   0]
- [  2   1   0   1   2  45   9]
- [ 15   7   6  10   4   9  84]]
-Node Classification on random seed  5272 -> 0.642
-Confusion Matrix:
- [[ 66   2   0   8   8   9  11]
- [  5 128   3   1  16   9   3]
- [ 14  18 152  20  32  22  36]
- [  3   6  20 115  10   4  14]
- [  1   3   4   0  66   1   3]
- [  8   0   0   2   0  42   3]
- [ 12   5   5   9   5  23  73]]
-Node Classification on random seed  5273 -> 0.636
-Confusion Matrix:
- [[ 66   5   1   3   7  18   9]
- [  2 122   8   4  11   4   3]
- [ 29  14 159  32  14  30  39]
- [  5   3  21 102   7   1  18]
- [  1   7   3   2  64   1   2]
- [ 11   1   2   0   0  42   4]
- [ 12   2   8   4   7   9  81]]
-Node Classification on random seed  5274 -> 0.629
-Confusion Matrix:
- [[ 78   2   4   2   4  15   8]
- [  3 143   7   3   1   3   2]
- [ 22  26 138  46  28  18  29]
- [ 24   0  11  98   6   6   8]
- [  1  11   5   1  52   1   0]
- [  7   3   0   1   0  56   7]
- [ 18   5   7   5   5  16  64]]
-Node Classification on random seed  5275 -> 0.613
-Confusion Matrix:
- [[ 61   0   4   4   4  13  10]
- [  5 120   5   7   2   4   5]
- [ 20  10 135  51  26  23  48]
- [  6   3   8 107   8   8  14]
- [  0  18   5   0  62   2   1]
- [ 10   2   4   1   1  43   5]
- [  8   3  12   3  10  14  85]]
-Node Classification on random seed  5276 -> 0.634
-Confusion Matrix:
- [[ 82   5   5   4   4  18   4]
- [  7 129   4   0   6   1   3]
- [ 17  19 136  53  34  13  40]
- [ 11   7  13 105   7   6   8]
- [  1   8   1   4  56   0   3]
- [  3   4   1   0   3  53   4]
- [ 16   4   8   2   4  11  73]]
-Node Classification on random seed  5277 -> 0.661
-Confusion Matrix:
- [[ 78   0   1   6   7  15   6]
- [  0 124   7   5   5   1   5]
- [ 28  13 154  20  28  24  28]
- [ 18   1  17 119   5   6   8]
- [  1  12   3   3  65   1   2]
- [  2   1   2   4   0  39   8]
- [  7   1  10   5  10  13  82]]
-Node Classification on random seed  5278 -> 0.649
-Confusion Matrix:
- [[ 66   3   2   4   4   9   9]
- [  3 124   6   1  20   3   1]
- [ 17  22 178  45  20  11  42]
- [  9   7  18 104   2   2  12]
- [  3   6   4   2  58   0   3]
- [  7   0   5   1   0  44   2]
- [  8   3  11   8   5  11  75]]
-Node Classification on random seed  5279 -> 0.64
-Confusion Matrix:
- [[ 61   2   3   3   5  24   5]
- [  3 122   3   2  11   6   6]
- [ 11  15 164  37  17  25  45]
- [ 20   1  11 117   1   7  10]
- [  2   3   5   6  55   0   2]
- [  9   0   0   1   0  40   7]
- [ 13   4  18   3   4  10  81]]
-Node Classification on random seed  5280 -> 0.591
-Confusion Matrix:
- [[ 76   1   4   4   4   9   2]
- [  7 118  10   3   5   5   7]
- [ 22  29 146  22  28  38  28]
- [ 22   4  21  93  10  12   7]
- [  2  10   3   1  58   0   0]
- [  7   0   3   4   3  43   5]
- [ 12   4  15   5  16  15  57]]
-Node Classification on random seed  5281 -> 0.621
-Confusion Matrix:
- [[ 62   1   7   5   1   8   9]
- [  7 119  10   0  13   1   8]
- [ 23  15 152  34  34  11  47]
- [  4   4  12 101  11   3  31]
- [  1   2   4   0  66   0   3]
- [  7   3   3   1   2  44   3]
- [ 10   4   7   7  12  11  77]]
-Node Classification on random seed  5282 -> 0.585
-Confusion Matrix:
- [[ 66   0   4   3   1  17  15]
- [  2 123  14   1  10   7   5]
- [ 33  16 101  50  11  27  50]
- [ 12  11  18  98  11  10  11]
- [  0   7   7   0  59   1   4]
- [ 12   1   1   1   0  57   5]
- [  6   5   5   3   7  11  81]]
-Node Classification on random seed  5283 -> 0.566
-Confusion Matrix:
- [[ 54   5   4  14   3  15  15]
- [  1 123   9   1   8  10   4]
- [ 25  12 113  36  35  21  46]
- [  8   2   8 102   5   7  26]
- [  3   8   2   1  63   1   5]
- [  4   3   5   1   2  41  16]
- [ 13   2  16   6  15  11  70]]
-Node Classification on random seed  5284 -> 0.604
-Confusion Matrix:
- [[ 82   1   7   6   7   6   4]
- [  3 110   5   3   4   6   4]
- [ 28  23 117  40  38  34  25]
- [ 18   5  11 111   6   6   7]
- [  0  10   3   1  59   2   1]
- [ 11   1   1   5   0  50   2]
- [ 10   7   3  17   2  23  75]]
-Node Classification on random seed  5285 -> 0.652
-Confusion Matrix:
- [[ 92   0   8   3   0  15   9]
- [  0 135   6   4   1   1   6]
- [ 26  18 146  38  22  20  39]
- [ 12   2  10 102  12   5  13]
- [  1   5   3   1  55   2   2]
- [  2   0   3   4   1  51   6]
- [ 14   3   9   5   8   9  71]]
-Node Classification on random seed  5286 -> 0.626
-Confusion Matrix:
- [[ 85   6   0   1   2  22   4]
- [  4 122   2   1   6   6   3]
- [ 32  25 146  19  20  29  33]
- [ 12   8  17  95   9   3  17]
- [  1  10   1   3  52   3   4]
- [  6   0   2   0   1  51   9]
- [ 10   5   3   7   7  21  75]]
-Node Classification on random seed  5287 -> 0.613
-Confusion Matrix:
- [[ 68   1   1   7   4   9  12]
- [  7 120   7   3   4   2   3]
- [ 17  23 141  43  37  14  40]
- [ 12   5   9 109   7   8  11]
- [  0  10   3   1  56   1   2]
- [  3   1  14   1   2  43   9]
- [ 10   1   5   9  14  15  76]]
-Node Classification on random seed  5288 -> 0.607
-Confusion Matrix:
- [[ 57   7   5   3   2  16  18]
- [  6 126   4   3  13   2   3]
- [ 21  30 142  34  30  27  25]
- [  5   2  26  88   5  10  12]
- [  2   3   3   6  64   1   2]
- [  5   1   1   0   2  53   4]
- [ 16   2   6   4  12  14  77]]
-Node Classification on random seed  5289 -> 0.643
-Confusion Matrix:
- [[ 67   2   5  10   4  15   7]
- [  3 137   5   1   4   1   4]
- [ 25  22 170  30  12  28  29]
- [  9   9  21 101   5   2  17]
- [  3   6   3   1  56   0   3]
- [  3   0   5   4   0  41   3]
- [ 14   2   6   9   4  21  71]]
-Node Classification on random seed  5290 -> 0.6
-Confusion Matrix:
- [[ 82   6   4   2   2  12   2]
- [  1 121   5   2   1   5   8]
- [ 20  22 142  49  15  20  39]
- [ 22   5  14  73   7  13  23]
- [  2  13   2   3  60   0   6]
- [  6   4   2   4   0  43   2]
- [  8   5  15  11   2  16  79]]
-Node Classification on random seed  5291 -> 0.625
-Confusion Matrix:
- [[ 80   7   5   3   6  13   2]
- [  2 137   2   0  12   3   6]
- [ 26  34 119  27  30  14  42]
- [  9   2  17 100  10   3  16]
- [  1  10   6   1  67   0   0]
- [  6   2   0   0   1  40   5]
- [  9   3   7   7   8  18  82]]
-Node Classification on random seed  5292 -> 0.601
-Confusion Matrix:
- [[ 75   1   7   1   3  14  10]
- [  5 114   8   5   4   3   6]
- [ 24  37 131  35  23  29  33]
- [ 13   2  16 104   1  11   7]
- [  1   8   1   1  56   1   1]
- [  8   0   7   2   0  38   4]
- [ 21   0  15  11   3  17  83]]
-Node Classification on random seed  5293 -> 0.621
-Confusion Matrix:
- [[ 63   3   7   1   3   9  12]
- [  7 128  11   3   9   5  16]
- [ 22  19 133  45  33  29  32]
- [  2   5   8 110   4   3   7]
- [  1   2   1   1  68   0   6]
- [  3   3   5   0   0  52   5]
- [ 12   1  10   8  10  16  67]]
-Node Classification on random seed  5294 -> 0.591
-Confusion Matrix:
- [[ 65   3   5   1   0  19   5]
- [  6 128   7   1   5   6  11]
- [ 35  12 112  29  31  46  27]
- [ 15   1  12  98  11   7  11]
- [  1   5   5   3  54   3   5]
- [  3   1   3   2   2  60   0]
- [ 17   3  12  10   4  24  74]]
-Node Classification on random seed  5295 -> 0.616
-Confusion Matrix:
- [[ 80   4   8   3   2  11   5]
- [  4 118   7   3   2   0   6]
- [ 22  22 133  35  37  18  46]
- [  5   5  12 105  11   8  18]
- [  2  12   5   0  60   1   3]
- [  0   3   1   0   2  57   1]
- [ 15   7   8  10  12   8  63]]
-Node Classification on random seed  5296 -> 0.612
-Confusion Matrix:
- [[ 62   1   5   9   3   9  16]
- [  5 122   8   0  14   2   8]
- [ 26  13 151  22  28  37  32]
- [  3   4  26  98   3  10   8]
- [  3   9   8   2  58   0   1]
- [  3   2   4   0   2  44   3]
- [  8   4  16   9   8  14  77]]
-Node Classification on random seed  5297 -> 0.605
-Confusion Matrix:
- [[ 83   8   3  13   4  12   5]
- [  4 120   1   2  12   2   5]
- [ 30  14 137  41  24  18  39]
- [ 19   2  20  96   5   3  11]
- [  0   6   5   0  62   1   3]
- [ 11   2   4   0   2  43   8]
- [ 11   0   6   8  17  14  64]]
-Node Classification on random seed  5298 -> 0.62
-Confusion Matrix:
- [[ 68   1   1   3   3  13   8]
- [  2 138   5   1   8   2   3]
- [ 29  38 135  34  20  26  32]
- [ 13   9  17  96  10   4   9]
- [  1   4  10   3  67   1   3]
- [  3   7   1   1   0  30  11]
- [  5   4   5   7   8  15  86]]
-Node Classification on random seed  5299 -> 0.575
-Confusion Matrix:
- [[ 62   8   7   5   5   6  10]
- [  2 107   1   4   7   5   4]
- [ 31  20 113  52  56  21  20]
- [  8   9  20 109   5   6   9]
- [  3   9   0   3  62   1   4]
- [  6   2   1   6   0  52   6]
- [ 10   3  13   9   4  24  70]]
-Node Classification on random seed  5300 -> 0.596
-Confusion Matrix:
- [[ 71   2   5  10   1   9   5]
- [  7 121   4   2   9  11   2]
- [ 26  11 129  45  37  21  48]
- [  9   3  16 111   3   5  10]
- [  2   9   4   3  61   1   1]
- [  5   3   1   6   1  41  10]
- [ 16   3   6  14   4  14  62]]
-Node Classification on random seed  5301 -> 0.638
-Confusion Matrix:
- [[ 68   7   4  18   1  10   6]
- [ 10 123   4   0   5   3   1]
- [ 24  18 160  31  19  22  34]
- [  8   2  15 101   8   7  16]
- [  1   4   4   2  63   4   4]
- [  3   1   3   4   3  49   2]
- [ 19   4   4   4  13  10  74]]
-Node Classification on random seed  5302 -> 0.563
-Confusion Matrix:
- [[ 67   1  16   6   5   6   8]
- [  7 118   4   4   9   1   6]
- [ 31  36  85  72  36  20  24]
- [ 18   6   6 118   6  11   9]
- [  0   5   4   4  56   1   2]
- [  7   1   6   0   1  43   7]
- [ 13   7  11   6   8   6  76]]
-Node Classification on random seed  5303 -> 0.657
-Confusion Matrix:
- [[ 92   3   5   9   3   3   7]
- [  7 137   7   9   3   0   0]
- [ 20  23 152  35  22  11  34]
- [ 20   3   9  95  11   6  12]
- [  2   7   0   2  68   0   1]
- [  4   4   2   2   0  41   4]
- [ 14   4   4  10   8  13  72]]
-Node Classification on random seed  5304 -> 0.607
-Confusion Matrix:
- [[ 67   1   7   4   5   3  15]
- [  2 110   8   7   8   1   5]
- [ 24  23 137  17  29  22  46]
- [ 12   2  17  92  17   6   9]
- [  3   8   6   3  65   2   0]
- [  3   7   1   1   1  48   7]
- [  6   5  23   6   7  14  88]]
-Node Classification on random seed  5305 -> 0.604
-Confusion Matrix:
- [[ 84   4   3   6   4  19   6]
- [  1 123   2   2   3  11   0]
- [ 13  31 137  17  22  38  54]
- [ 17   2  25  92  10   8  14]
- [  0   6   3   0  52   5   2]
- [  8   1   4   1   0  49   7]
- [  3   3   4  16   6  15  67]]
-Node Classification on random seed  5306 -> 0.609
-Confusion Matrix:
- [[ 62   0   9   5   9  16   6]
- [  6 120   2  10   5   0   7]
- [  6  23 163  34  30  26  35]
- [ 12   7  11 111   8   3  18]
- [  1   7   4   5  52   2   1]
- [  7   3   4   0   4  35   4]
- [  9   2   6  20   8  16  66]]
-Node Classification on random seed  5307 -> 0.629
-Confusion Matrix:
- [[ 56   4   3   6   5   7  17]
- [  6 137   8   2  11   2   3]
- [ 21  18 156  19  25  26  41]
- [  9   2   8 100   4  12  10]
- [  5   8   6   3  70   3   3]
- [  1   0   5   3   0  45   7]
- [ 17   4  12   7   3  15  65]]
-Node Classification on random seed  5308 -> 0.621
-Confusion Matrix:
- [[ 55   3   7   4  10   5  20]
- [  1 115   5   2  11   2   5]
- [ 10  16 149  22  29  19  51]
- [ 13   3  18 105  21   2  13]
- [  1   5   5   1  65   0   4]
- [  4   3   0   1   3  40   9]
- [  9   4   8   6   7  17  92]]
-Node Classification on random seed  5309 -> 0.637
-Confusion Matrix:
- [[ 81   2   1   5   2   3   4]
- [ 10 122   3   2   4   2   2]
- [ 22  22 143  36  36  19  49]
- [ 15   5  11 105  11   7   8]
- [  1   6   6   1  64   0   2]
- [  6   2   1   2   1  44   3]
- [ 17   3   5   7   4  15  78]]
-Node Classification on random seed  5310 -> 0.613
-Confusion Matrix:
- [[ 82   5   3   7   7   9   8]
- [  6 123   1   4  12   4   3]
- [ 22  25 117  32  37  24  38]
- [  7   6  12 110   2   9  13]
- [  0  10   3   2  60   0   1]
- [  7   3   1   1   0  45   5]
- [ 10   4   8  11  15  10  76]]
-Node Classification on random seed  5311 -> 0.604
-Confusion Matrix:
- [[ 70   0   6   1   7  18   1]
- [  6 129   6   0   8   3   7]
- [ 25  17 122  33  31  39  33]
- [ 12   7  18  93  13  11  13]
- [  1   2   3   5  68   3   3]
- [  6   2   4   0   1  49   2]
- [ 13   2   8   5   5  16  73]]
-Node Classification on random seed  5312 -> 0.584
-Confusion Matrix:
- [[ 85   3   3   8   4   9   5]
- [  3 111   6   2   3   2   8]
- [ 25  23 127  65  35  22  24]
- [ 18   4   8 104   2  16  13]
- [  4   5   6   1  58   1   2]
- [  8   1   0   0   1  31   7]
- [ 18   0  14   8   8  21  68]]
-Node Classification on random seed  5313 -> 0.593
-Confusion Matrix:
- [[ 63   4   1   9   2   9   8]
- [  3 126   8   5   5   3   7]
- [ 22  33 116  38  33  23  40]
- [  7   6  18 110   3   7   8]
- [  4  17   2   1  56   1   0]
- [  6   3   3   3   1  47   2]
- [  7   6   9  10   8  22  75]]
-Node Classification on random seed  5314 -> 0.614
-Confusion Matrix:
- [[ 75   1   6   0   6   6   3]
- [  2 136   3   4   2   0   9]
- [ 33  28 116  48  15  20  54]
- [ 15   6  22  85  10   9   6]
- [  1   3   2   2  64   1   3]
- [  6   0   4   3   3  65   1]
- [  8   2  13  12   4  10  73]]
-Node Classification on random seed  5315 -> 0.596
-Confusion Matrix:
- [[ 78   3   1   4   6  16   7]
- [  1 121   3   2  25   1   2]
- [ 28  19 131  25  55  27  38]
- [ 13   4  15  96   3   0  17]
- [  0   2   4   0  60   2   0]
- [ 11   0   2   3   3  50   2]
- [  6   5  21   4  12  12  60]]
-Node Classification on random seed  5316 -> 0.629
-Confusion Matrix:
- [[ 80   4   2   2   5  12   9]
- [  1 138   4   3  10   6   0]
- [ 24  15 119  32  23  29  37]
- [ 16   2  13 109   7   7  20]
- [  1   9   1   1  64   2   1]
- [  2   2   1   3   0  43   2]
- [  7   5  10   3  13  25  76]]
-Node Classification on random seed  5317 -> 0.61
-Confusion Matrix:
- [[ 58   1  10   5   6  14  13]
- [  2 136  10   3   3   2   4]
- [ 17  22 140  46  30  12  43]
- [ 10   3  22 103   4   4  13]
- [  4   7   4   3  58   1   2]
- [  7   2   4   0   0  40  14]
- [ 10   0  17   6   2   8  75]]
-Node Classification on random seed  5318 -> 0.644
-Confusion Matrix:
- [[ 65   4   2   3   1  12  13]
- [  2 126   5   4  14   4   3]
- [ 19  26 155  23  19  18  55]
- [ 10   9  11  97   3   6  15]
- [  1   6   2   0  65   1   4]
- [  4   1   0   2   0  51   6]
- [  9   2   8   4   5  20  85]]
-Node Classification on random seed  5319 -> 0.614
-Confusion Matrix:
- [[ 53   1   6   2   2  20  11]
- [  7 117  18   4  12   3   0]
- [ 19  23 143  43  32  24  41]
- [  7   2  14 116   3   5  22]
- [  1   5   5   3  55   1   1]
- [  2   2   1   1   0  52   1]
- [  4   3  16   2   3  14  78]]
-Node Classification on random seed  5320 -> 0.598
-Confusion Matrix:
- [[ 74   0   6   4   4   5  20]
- [  3 126   5   2   5   1   1]
- [ 21  22 109  45  51  12  51]
- [ 12   0  17  92  13   2  20]
- [  0   7   2   1  72   1   2]
- [ 14   0   1   0   2  43   3]
- [ 13   2   7   3   8  14  82]]
-Node Classification on random seed  5321 -> 0.599
-Confusion Matrix:
- [[ 69   4   8   9   2  19   3]
- [  4 115   6   1   9   9   1]
- [ 17  25 119  39  29  28  49]
- [ 16   1  12 104  10   2  11]
- [  1   7   1   1  63   8   1]
- [  8   0   0   2   0  41   2]
- [  7   2  13   8  13  13  88]]
-Node Classification on random seed  5322 -> 0.586
-Confusion Matrix:
- [[ 72   2   2  17   5  17   3]
- [  5 128  13   0   8   1   8]
- [ 13  23 138  37  37  14  46]
- [ 11   8  23  93   7   6   6]
- [  1   3   4   5  55   0   5]
- [  7   1   3   0   1  43   2]
- [  7   7   6  19  10  21  57]]
-Node Classification on random seed  5323 -> 0.621
-Confusion Matrix:
- [[ 66   3   6   8   4  12   6]
- [  3 126   2   2   6   1  18]
- [ 11  26 117  44  23  30  28]
- [  8   6  10 123   2   8  15]
- [  0   6   1   2  69   3   3]
- [ 11   1   2   1   2  38   7]
- [ 15   6   4   6   3  24  82]]
-Node Classification on random seed  5324 -> 0.596
-Confusion Matrix:
- [[ 69   4   4   6   2  21  11]
- [  6 117   4   8  15   4   5]
- [ 18  18 133  27  31  23  46]
- [  5   7  15 112   3   4  19]
- [  1   1   3   1  58   1   2]
- [  2   2   2   7   2  43   1]
- [ 12   4  10   9  16  22  64]]
-Node Classification on random seed  5325 -> 0.593
-Confusion Matrix:
- [[ 79   4   1   5   2  13   8]
- [  1 123  12   2   5   4   4]
- [ 10  36 137  35  39  20  48]
- [ 15   9  14  93  13   1   3]
- [  0  11   2   2  51   3   2]
- [  6   4   2   9   1  34   6]
- [  9   6  15   6   6  13  76]]
-Node Classification on random seed  5326 -> 0.644
-Confusion Matrix:
- [[ 73   1   1   6   1  13  17]
- [  2 123   1   0   7   8   4]
- [ 27  16 165  34  17  11  36]
- [ 14   0  17 108   8   5  10]
- [  1   8   5   1  55   2   2]
- [  6   1   1   2   1  53   5]
- [ 11   3  13  10   8  20  67]]
-Node Classification on random seed  5327 -> 0.653
-Confusion Matrix:
- [[ 72   3   2   3   5  10   8]
- [  5 135   2   5   9   1   4]
- [ 19  22 142  23  26  32  42]
- [ 13   1   8 119   5   9  10]
- [  2   6   2   2  58   4   2]
- [  8   1   1   0   2  45   2]
- [ 10   4   8   8   9   9  82]]
-Node Classification on random seed  5328 -> 0.632
-Confusion Matrix:
- [[ 72   0   1  11   4   4  14]
- [  4 117   6   4   5   1   5]
- [ 18  24 157  22  27  36  28]
- [ 10   6  17 105   3   7  11]
- [  0   7   4   2  57   0   5]
- [  4   2   2   3   3  44   9]
- [ 10   4  11  11  11  12  80]]
-Node Classification on random seed  5329 -> 0.609
-Confusion Matrix:
- [[ 79   3   5   3   2   9   9]
- [  3 136   4   2   6   2   3]
- [ 23  30 112  34  33  17  37]
- [ 16   8   7 100  13   8  14]
- [  0   7   5   2  64   2   4]
- [ 12   6   0   0   1  44   6]
- [ 11   3  12   6   7  16  74]]
-Node Classification on random seed  5330 -> 0.59
-Confusion Matrix:
- [[ 68   0  12   5   5   3   7]
- [ 11 118  10   0  13   0  11]
- [ 55  22 125  27  24  15  54]
- [ 15   1  15  96   4   7  15]
- [  1   2   5   0  68   2   6]
- [ 13   1   1   0   1  42   6]
- [ 22   2   7   3   3   4  73]]
-Node Classification on random seed  5331 -> 0.612
-Confusion Matrix:
- [[ 51   8   1   8   4  14   3]
- [  1 127   5   2   8   8   5]
- [ 21  20 143  42  24  38  37]
- [  4   6  12 106   6   5  17]
- [  0   7   4   4  58   1   3]
- [  5   1   3   1   0  45   8]
- [  5   5  12  14   4  12  82]]
-Node Classification on random seed  5332 -> 0.648
-Confusion Matrix:
- [[ 70  11   8   6   2  11  10]
- [  3 120   6   2   6   2   6]
- [ 21  33 177  22  14  19  36]
- [ 14   3  17 112   4   2   8]
- [  0   4   6   1  57   1   6]
- [  5   4   1   2   1  37   7]
- [ 14   3  10   7   2  12  75]]
-Node Classification on random seed  5333 -> 0.628
-Confusion Matrix:
- [[ 83   4   1   4   2   6  15]
- [ 11 123   8   1   9   8   4]
- [ 33  12 162  29  23  22  31]
- [ 15   4  13  93  10   5   9]
- [  6   3   4   1  63   2   5]
- [ 10   0   7   0   0  38   3]
- [ 17   3   8  10   4  10  66]]
-Node Classification on random seed  5334 -> 0.626
-Confusion Matrix:
- [[ 79   7   1  10   4  11   4]
- [  4 149   2   4   3   0   2]
- [ 30  38 125  31  18  21  32]
- [  9   5  13 106   9  13  10]
- [  2   8   1   0  66   2   0]
- [  3   3   0   2   3  34  15]
- [ 20   6   8   3   5  12  67]]
-Node Classification on random seed  5335 -> 0.651
-Confusion Matrix:
- [[ 62   6   0   3   2   2  26]
- [  7 120   3   8  12   0   6]
- [  9  19 151  37  34  26  39]
- [  7   4  11 125   4   4  16]
- [  1   1   1   2  60   3   2]
- [  1   1   2   0   0  42  12]
- [  6   5   1  10   4  12  91]]
-Node Classification on random seed  5336 -> 0.605
-Confusion Matrix:
- [[ 58   1   4   8   2  11   4]
- [  3 123   2   4  10   1   6]
- [ 30   6 159  18  26  37  57]
- [ 14   3  16 108   4   7  10]
- [  1   8   5   2  59   2   4]
- [  6   2   3   4   2  42   0]
- [ 26   3   5  13   8  17  56]]
-Node Classification on random seed  5337 -> 0.645
-Confusion Matrix:
- [[ 61   1   4   6   6  16   6]
- [  1 134   7   4   5   1   4]
- [ 33  18 149  40  21  16  47]
- [  5   5  23 112   2   5  20]
- [  0   4   3   1  63   0   3]
- [  4   1   1   0   1  43   5]
- [  4   3   4   7   3  15  83]]
-Node Classification on random seed  5338 -> 0.616
-Confusion Matrix:
- [[ 77   1   2   5  11  17  12]
- [  9 112  11   2  15   9   2]
- [ 24  19 156  27  26  31  27]
- [ 12   2  18  82   9  11   5]
- [  0   8   7   3  71   1   1]
- [  7   0   2   0   1  43   1]
- [ 12   2  15   2   3  12  75]]
-Node Classification on random seed  5339 -> 0.606
-Confusion Matrix:
- [[ 62   3  10   2   4  11  12]
- [  5 135   6   3   4   5   2]
- [ 21  20 140  34  29  31  46]
- [ 17   5  12  85   8   6   9]
- [  1   7   5   1  67   1   0]
- [  6   1   2   5   2  48   6]
- [ 10   5  10   5   5  17  69]]
-Node Classification on random seed  5340 -> 0.602
-Confusion Matrix:
- [[ 54   2   1   9   4  21  16]
- [  3 111  11   1   9   3   1]
- [ 24  18 151  44  22  29  33]
- [  9  11   6 114   5   6   9]
- [  0   6   5   0  57   2   4]
- [  5   2   3   3   0  48   7]
- [ 18   6  13   6   7  14  67]]
-Node Classification on random seed  5341 -> 0.596
-Confusion Matrix:
- [[ 80   1   2  10   4  13   8]
- [  0 131  10   2   6   5   7]
- [ 19  43 120  43  32  16  39]
- [ 14   4  22  87   0   1  19]
- [  0   7   3   0  62   5   2]
- [  9   2   1   2   0  44   3]
- [  4   7   9   3   5  22  72]]
-Node Classification on random seed  5342 -> 0.659
-Confusion Matrix:
- [[ 76   4   3   1   6  12   5]
- [  1 133   3   1   6   0   3]
- [ 23  37 158  25  32  28  37]
- [  3   2  14 122  10  11   8]
- [  0   5   1   0  55   0   2]
- [  3   0   1   0   2  43   5]
- [  8   3  11   3   7  15  72]]
-Node Classification on random seed  5343 -> 0.628
-Confusion Matrix:
- [[ 79   1   4   7   4   3   7]
- [  3 127  10   0   0   1   3]
- [ 22  26 144  34  26  24  45]
- [ 18   6  15  87   9   5  18]
- [  1   5   8   0  72   0   4]
- [  3   1   4   2   0  42   9]
- [ 12   2   8   6  13   3  77]]
-Node Classification on random seed  5344 -> 0.609
-Confusion Matrix:
- [[ 70   1   2   8   1   9   6]
- [  2 149   8   1   6   4   1]
- [ 33  25 101  62  27  11  32]
- [  9   4  17 103   3   2   9]
- [  0  13   3   3  61   1   5]
- [ 12   0   2   0   4  44   4]
- [ 21   3  12   7   6  12  81]]
-Node Classification on random seed  5345 -> 0.634
-Confusion Matrix:
- [[ 86   3   1   5   2   7   8]
- [  3 124   5   0   5   8   4]
- [ 21  22 159  37  15  28  45]
- [ 11   3  19  95   7   2  13]
- [  1   3   5   6  61   1   4]
- [  6   0   4   1   0  37   6]
- [ 20   3  11   3   3  15  72]]
-Node Classification on random seed  5346 -> 0.603
-Confusion Matrix:
- [[ 73   1   1   2   8  13   7]
- [  6 106  10   5  10   2   8]
- [ 34  18 119  35  26  35  27]
- [ 17   2  16 108  10   5   9]
- [  2   5   3   4  56   4   6]
- [  6   1   2   0   1  49   1]
- [ 13   5   5   3   6  23  92]]
-Node Classification on random seed  5347 -> 0.629
-Confusion Matrix:
- [[ 53   3   1   7   4  13  18]
- [  4 143   2   2   6   2   5]
- [ 29  17 158  13  31  14  30]
- [ 16   2  19  89   6  20  14]
- [  0   6   8   5  69   1   1]
- [  2   0   2   2   1  47   6]
- [  7   5  11  10   9  17  70]]
-Node Classification on random seed  5348 -> 0.582
-Confusion Matrix:
- [[ 79   1   5   7   5  11   9]
- [  3 118   7   3   9   3   3]
- [ 16  19 114  56  26  19  58]
- [ 15   2  23  79  14  10  17]
- [  3   5   3   2  59   2   5]
- [  5   0   2   0   0  47   7]
- [  8   2   9   5   5  14  86]]
-Node Classification on random seed  5349 -> 0.663
-Confusion Matrix:
- [[ 58   2   2   8  11  11  22]
- [  5 131  11   2   3   3   1]
- [ 15  20 163  23  11  12  33]
- [  7  10  25  94   3   3  15]
- [  2   7   5   1  76   0   4]
- [  3   2   1   5   0  55   8]
- [  9   0  11   4   4  13  86]]
-Node Classification on random seed  5350 -> 0.632
-Confusion Matrix:
- [[ 69   5   3   4   2  13  14]
- [  2 130   6   3   4   2   4]
- [ 20  14 147  15  30  18  50]
- [ 10   6  28  93   7   4  17]
- [  1   9   4   1  56   4   3]
- [  8   1   1   0   0  41   8]
- [ 12   3   9   2   7  14  96]]
-Node Classification on random seed  5351 -> 0.633
-Confusion Matrix:
- [[ 68   9   1   8   4  21   7]
- [  6 129   6   4   9   1   4]
- [ 26  11 155  27  38  16  35]
- [  6   3  18  98   0   9  18]
- [  1   8   3   0  70   1   1]
- [  8   2   2   1   3  41   3]
- [ 15   3   6   3   5  15  72]]
-Node Classification on random seed  5352 -> 0.622
-Confusion Matrix:
- [[ 64   4  12   1   5   9  25]
- [  2 142   6   6   3   2   3]
- [ 16  20 121  49  23  21  43]
- [ 10   2   9 118   7   3  15]
- [  1   8   6   3  52   0   1]
- [  3   1   1   1   1  38   8]
- [  9   7   7   8   6  11  87]]
-Node Classification on random seed  5353 -> 0.618
-Confusion Matrix:
- [[ 70   5   2   2   3  18   3]
- [  6 136   7   2   7   2   2]
- [ 35  28 125  35  27  19  40]
- [  7   3  18 105   8   8   8]
- [  1   2   8   2  61   0   5]
- [  7   0   1   0   0  40   6]
- [ 19   4   8   6   8  10  81]]
-Node Classification on random seed  5354 -> 0.633
-Confusion Matrix:
- [[ 76   1   3   2   7  12  12]
- [  4 130   2   3   7   2   1]
- [ 22  28 146  53  26  19  25]
- [ 10   5  10  98   0  10  13]
- [  0   6   3   1  64   0   2]
- [  5   1   5   0   0  53   4]
- [ 16   5  15   9   9   9  66]]
-Node Classification on random seed  5355 -> 0.587
-Confusion Matrix:
- [[ 70   3   6   7   4  10   6]
- [  5 144   1   3   2   2   2]
- [ 32  20  93  55  34  40  38]
- [ 16   7  10  88   5   3  16]
- [  0   4   2   0  57   2   5]
- [  5   0   2   5   0  47   6]
- [ 12   7   7   8   5  16  88]]
-Node Classification on random seed  5356 -> 0.625
-Confusion Matrix:
- [[ 58   1   0   2   1  20  15]
- [  7 119  14   1   9   2   4]
- [ 24  18 149  27  45  28  23]
- [ 18   2  13  99   3   4  10]
- [  2   6   4   0  56   2   3]
- [  3   0   1   3   2  57   7]
- [  9   1   6   3   9  23  87]]
-Node Classification on random seed  5357 -> 0.604
-Confusion Matrix:
- [[ 63   1   6   9   5  11  13]
- [  9 118   5   6   9   1   4]
- [ 27  27 123  39  15  24  52]
- [  8   3   8 130   3   5   7]
- [  3   6   4   4  54   1   6]
- [  9   6   0   2   1  44   4]
- [ 12   3  15   7   6  10  72]]
-Node Classification on random seed  5358 -> 0.613
-Confusion Matrix:
- [[ 74   4  10   3   3  17  10]
- [  7 111  10   1  14   6   7]
- [ 27  26 141  11  28  35  40]
- [ 15   3  14 110   4   8  21]
- [  4   7   7   2  56   0   1]
- [  0   1   1   1   1  41   8]
- [  3   3   4   5   4  11  80]]
-Node Classification on random seed  5359 -> 0.565
-Confusion Matrix:
- [[ 72   4   1   9   2   9  23]
- [  5 114   4   0   9   5   7]
- [ 18  13 113  42  26  33  57]
- [ 14   5  18 100   6  10   6]
- [  2   5   1   2  60   1   9]
- [  2   3   1   7   4  44   5]
- [  5   3  12   7  17  23  62]]
-Node Classification on random seed  5360 -> 0.594
-Confusion Matrix:
- [[ 51   1  10   5  12  17  21]
- [  1 121   2   5   7   2   2]
- [ 13  29 139  22  37  21  58]
- [  5   8  15  90   8   9  13]
- [  0   8   1   0  65   2   4]
- [  7   4   1   1   1  33  13]
- [  2   8  13   2   6  10  95]]
-Node Classification on random seed  5361 -> 0.624
-Confusion Matrix:
- [[ 81   7   1   2   3  14   6]
- [  2 137   5   7   7   3   4]
- [ 27  28 123  70  25  21  22]
- [ 16   2  16 105   3   2   4]
- [  0   7   3   1  62   0   4]
- [  5   2   0   0   1  47   7]
- [ 16   6   8  10   4   5  69]]
-Node Classification on random seed  5362 -> 0.618
-Confusion Matrix:
- [[ 73   0   6   9   5   4  18]
- [  5 137  10   4   3   1   8]
- [ 34  27 135  28  23  12  41]
- [ 13   3  22 101   3   2   9]
- [  6   7   4   2  60   2   5]
- [  9   1   3   3   0  39   6]
- [ 17   3   5   8   7   4  73]]
-Node Classification on random seed  5363 -> 0.594
-Confusion Matrix:
- [[ 61   2   6   2   3   8   4]
- [  5 128   3   0   6   5   3]
- [ 32  23 141  37  39  15  53]
- [ 24   7  17  99   8   2  12]
- [  2   6   4   3  63   2   1]
- [ 12   2   4   0   0  39   6]
- [ 10   7   8   7   3  13  63]]
-Node Classification on random seed  5364 -> 0.636
-Confusion Matrix:
- [[ 83   7   0   4   3  11  12]
- [  7 145   4   0   9   2   2]
- [ 24  24 144  31  20  22  42]
- [  7   4   2 110   4   2  30]
- [  0   4   8   1  53   1   3]
- [ 13   1   0   0   2  39   1]
- [ 22   7   4   1   7  16  62]]
-Node Classification on random seed  5365 -> 0.633
-Confusion Matrix:
- [[ 69   1   8   5   0   5  18]
- [  1 125   4   0   7   9   4]
- [ 23  19 145  37  20  29  41]
- [  3   1  21 110   2   7   5]
- [  1  15   4   3  56   2   2]
- [ 10   1   3   0   0  46  10]
- [ 11   3   8   7   2  15  82]]
-Node Classification on random seed  5366 -> 0.615
-Confusion Matrix:
- [[ 64   1   4   1   6  12  10]
- [  5 122   4   1  13   2   6]
- [ 21  20 159  34  34  24  25]
- [ 15   1  23 109   2   5   8]
- [  2   4   5   1  56   1   4]
- [  4   1   3   6   0  43   5]
- [ 14   3  18   9   6  22  62]]
-Node Classification on random seed  5367 -> 0.644
-Confusion Matrix:
- [[ 77   3   7   3   5   8   8]
- [  3 124   8   1   2   1   7]
- [ 24  28 156  47  22  20  24]
- [ 14   2  12  96   8   5  11]
- [  1   8   0   3  59   0   3]
- [  5   1   2   1   1  53   5]
- [ 11   2  12   9   4  15  79]]
-Node Classification on random seed  5368 -> 0.613
-Confusion Matrix:
- [[ 77   1   3   8   5   3  19]
- [  3 126   2   0  14   6   1]
- [ 28  19 133  32  42  28  31]
- [ 13   6  17 104   6   4   6]
- [  0   3   6   2  59   0   0]
- [ 10   2   9   2   0  41   7]
- [ 14   3   9  13   5   5  73]]
-Node Classification on random seed  5369 -> 0.596
-Confusion Matrix:
- [[ 62   2   9   2   5  18   5]
- [  6 123   5   1  12   2   1]
- [ 24  46 128  42  17  25  34]
- [  6   4  19 106   4   6  18]
- [  0   5   6   1  55   1   1]
- [  2   3   0   3   2  46   3]
- [ 12   5  13   8   9  17  76]]
-Node Classification on random seed  5370 -> 0.68
-Confusion Matrix:
- [[ 64   6   1   0   6   9  24]
- [  1 132   5   2  15   2   3]
- [ 10  22 175  19  22  13  36]
- [  5   2  11 114   6   7  23]
- [  1   4   3   0  54   1   3]
- [  6   3   2   2   1  49   6]
- [  6   4   7   1   8  12  92]]
-Node Classification on random seed  5371 -> 0.625
-Confusion Matrix:
- [[ 67   6   3   7   4  21   4]
- [  6 123   9   1  10   2   3]
- [ 17  25 145  34  21  24  34]
- [ 11   7  18 107   2  21   6]
- [  2   3   2   5  51   0   4]
- [  6   2   0   0   3  38   9]
- [  7   2   3  13   4  14  94]]
-Node Classification on random seed  5372 -> 0.603
-Confusion Matrix:
- [[ 64   0   1   7   6  11   1]
- [  5 139   3   7   4   4   2]
- [ 20  25 132  54  41  26  33]
- [  6   6  16 105   3   8   6]
- [  3   6   1   4  51   2   3]
- [ 10   1   0   1   1  39   9]
- [ 21   5   9   7   1  18  73]]
-Node Classification on random seed  5373 -> 0.654
-Confusion Matrix:
- [[ 65   2   3   3   3  10  13]
- [  6 111   5   0  15   4   3]
- [ 24  19 166  32  29  23  37]
- [  8   6  12 115   3   7  11]
- [  3   5   2   0  61   0   1]
- [  3   0   2   1   0  48   5]
- [  9   5   6   1   7  18  88]]
-Node Classification on random seed  5374 -> 0.604
-Confusion Matrix:
- [[ 71   3   5  13   3   8  18]
- [  0 133   3   2  24   4   2]
- [ 14  25 122  34  29  37  35]
- [  4   9  13  93   6   7   6]
- [  0   8   3   1  69   5   2]
- [  2   1   1   4   1  49   7]
- [ 10   7  11   8   9  12  67]]
-Node Classification on random seed  5375 -> 0.612
-Confusion Matrix:
- [[ 77   5   5   9   4  11  11]
- [  9 120   4   1   9   3   1]
- [ 24  21 136  37  25  22  39]
- [  4   7  11 104   5   7  23]
- [  2   3   9   2  64   0   5]
- [  8   1   1   0   0  46   6]
- [ 17   2   9   7   7  12  65]]
-Node Classification on random seed  5376 -> 0.596
-Confusion Matrix:
- [[ 63   6   3   8   6   8   6]
- [  5 117   6   6   9   8   2]
- [ 38  16 115  34  43  16  43]
- [  3   2  17 113   2   2  20]
- [  1   8   3   4  55   3   2]
- [  5   2   2   3   2  51   7]
- [  7   3   8  16   6  13  82]]
-Node Classification on random seed  5377 -> 0.623
-Confusion Matrix:
- [[ 74   7  14   3   4   3  11]
- [  7 120   7   2   4   0   5]
- [ 25  29 137  35  16  49  17]
- [  3   5  10 111   8   9  11]
- [  2  10   4   2  63   2   4]
- [  8   2   2   2   1  39   7]
- [ 15   3   5   9   3  12  79]]
-Node Classification on random seed  5378 -> 0.57
-Confusion Matrix:
- [[ 50   0  15   8   3  21   4]
- [  3 136   7   2   0   3   2]
- [ 35  31 125  70  28  17  27]
- [ 14   1  20  88   5  11  11]
- [  2  12   3   3  53   1   3]
- [  3   1   0   2   0  44   2]
- [  7   7  19   9   6  12  74]]
-Node Classification on random seed  5379 -> 0.651
-Confusion Matrix:
- [[ 74   3   3   0   2   7  21]
- [ 10 123   7   3   6   3   0]
- [ 28  33 136  29  22  23  26]
- [ 16   5  12 120   3   3  18]
- [  0   3   1   2  69   0   3]
- [  6   3   1   4   0  40   3]
- [  3   3  12   0   6  16  89]]
-Node Classification on random seed  5380 -> 0.571
-Confusion Matrix:
- [[ 51   1   3   3   4  24  15]
- [ 15 115   5   7   6   1   1]
- [ 27  27 155  36  36  22  40]
- [ 13   5  21  62  12   9   9]
- [  1   9   3   3  61   1   2]
- [  8   1   3   0   2  53   2]
- [  9   3   8   7   6  19  74]]
-Node Classification on random seed  5381 -> 0.624
-Confusion Matrix:
- [[ 61   2   7   8   3  14   5]
- [ 10 137   3   3   1   4   4]
- [ 34  17 136  31  31  31  35]
- [ 15   6  14  97   7   2  13]
- [  2   6   2   0  68   0   3]
- [ 10   4   1   1   3  39   5]
- [ 10   4   5   3   1  16  86]]
-Node Classification on random seed  5382 -> 0.57
-Confusion Matrix:
- [[ 68   4   4   7   3  11  14]
- [  2 135   7   3   5   4   8]
- [ 31  36 119  24  20  13  71]
- [ 23  13  10  95   1   4  13]
- [  2  10   3   3  53   0   3]
- [  4   1   4   1   1  30  14]
- [  8   7   9  16   4   9  70]]
-Node Classification on random seed  5383 -> 0.603
-Confusion Matrix:
- [[ 76   0   3   5   1  12   8]
- [  4 140   3   1   5   4   1]
- [ 36  15 132  48  29  27  32]
- [ 14   5  25  98   3   6   8]
- [  1   7   4   3  61   0   6]
- [  8   1   3   4   1  34   1]
- [ 10   4  13   7   3  26  62]]
-Node Classification on random seed  5384 -> 0.602
-Confusion Matrix:
- [[ 78   0  11   6   4  18   6]
- [  7 111   3   2  12   6  11]
- [ 29  23 144  30  31  19  32]
- [  8   2  22 112   5   5   9]
- [  0   3   7   4  43   1   8]
- [  7   1   1   5   1  37   5]
- [  4   3  16   6  10  15  77]]
-Node Classification on random seed  5385 -> 0.606
-Confusion Matrix:
- [[ 79   4   5   7   2  16   8]
- [  4 130   5   3   8   2   1]
- [ 25  39 128  42  21  20  34]
- [ 16   4  16 103  11   3  11]
- [  2   2   2   1  61   0   1]
- [  5   3   4   0   0  52   3]
- [ 15   4  10   7   5  23  53]]
-Node Classification on random seed  5386 -> 0.604
-Confusion Matrix:
- [[ 79   3   3   4   4   9  11]
- [ 14 127  10   1   7   2   4]
- [ 17  31 125  37  16  21  44]
- [ 13   3  12 113   3   6  16]
- [  1   6   3   1  57   2   2]
- [  4   1   5   1   2  45   3]
- [  4   0  19  21  13  17  58]]
-Node Classification on random seed  5387 -> 0.617
-Confusion Matrix:
- [[ 72   8   1   3   5  12  14]
- [  5 132   1   2   9   4   4]
- [ 20  31 139  40  10  34  30]
- [ 15   7  17  95   2   8   5]
- [  3   4   8   1  62   0   2]
- [  3   2   4   1   0  42   6]
- [ 20   5   5   5  10  17  75]]
-Node Classification on random seed  5388 -> 0.617
-Confusion Matrix:
- [[ 76   1   2   1   5  14   7]
- [  2 114   5   5   7   0   3]
- [ 37  20 156  40  25  31  16]
- [ 12   0  13 118  10   7   6]
- [  2  10   3   1  57   2   2]
- [  6   2   4   3   0  46   1]
- [ 22   4   8  10   7  27  50]]
-Node Classification on random seed  5389 -> 0.603
-Confusion Matrix:
- [[ 67   1   1   7   8   6  14]
- [  4 134   5   3   2   3   2]
- [ 23  21 126  46  22  33  36]
- [ 23   5   8  99   7  13   8]
- [  1   6   2   6  56   0   2]
- [  6   5   1   0   2  48   9]
- [ 12   3   3  15  13  10  73]]
-Node Classification on random seed  5390 -> 0.611
-Confusion Matrix:
- [[ 77   4   3   2   2  16   8]
- [  3 114   1   1  20   2   5]
- [ 21  14 109  33  54  27  38]
- [ 11   2  15 121  12   5   7]
- [  1   5   1   3  63   0   3]
- [  9   2   2   1   4  47   1]
- [ 14   2   6  13   8   8  80]]
-Node Classification on random seed  5391 -> 0.604
-Confusion Matrix:
- [[ 66   1   9   4   5   9  14]
- [ 10 125   5   3   6   2   2]
- [ 33  21 154  54  32  13  21]
- [  5   9  13  98   4  17   7]
- [  0   3   5   7  53   0   1]
- [  7   2   1   5   0  49   5]
- [ 10   2   9  26   3  11  59]]
-Node Classification on random seed  5392 -> 0.612
-Confusion Matrix:
- [[ 75   4   4   6   8   5   8]
- [  0 116   4   4  19   0   2]
- [ 10  38 139  32  25  22  50]
- [ 18   3  17 102   7   4  20]
- [  0   4   5   2  58   0   3]
- [  9   0   4   2   1  38   2]
- [ 10   5   5   5   8  13  84]]
-Node Classification on random seed  5393 -> 0.633
-Confusion Matrix:
- [[ 98   2   3   3   3  18   8]
- [ 10 111   5   8   9   0   0]
- [ 22  23 140  38  16  21  37]
- [ 10   7  13  98   5  15  14]
- [  0   5   4   2  67   4   5]
- [  7   0   0   1   0  46   4]
- [ 18   0   6   6   7   8  73]]
-Node Classification on random seed  5394 -> 0.598
-Confusion Matrix:
- [[ 69   1   1   5   8  13  10]
- [  2 145   3   4   6   0  10]
- [ 17  24 134  24  25  20  51]
- [ 17   5  23  68   7   9  22]
- [  2   3   6   0  66   1   2]
- [  1   2   1   0   1  51   7]
- [ 11   5  20   1   8  24  65]]
-Node Classification on random seed  5395 -> 0.627
-Confusion Matrix:
- [[ 66   4   2  10   4  11   9]
- [  6 116   9   1  10   4  13]
- [ 36  10 150  36  23  21  34]
- [  7   2  22 115   5   4  11]
- [  2   5   1   0  63   3   1]
- [  6   1   4   1   2  42   6]
- [ 12   3   7  11   3  11  75]]
-Node Classification on random seed  5396 -> 0.589
-Confusion Matrix:
- [[ 67   1   2  18   1   9  13]
- [  7 104   5   1  16   5   1]
- [ 26   4 119  28  32  37  53]
- [ 20   5   8 107   7  14  20]
- [  0   0   8   0  64   1   2]
- [  9   0   2   4   1  42   1]
- [ 14   1   4  15   4  12  86]]
-Node Classification on random seed  5397 -> 0.582
-Confusion Matrix:
- [[ 69   3  10   1   3   6  14]
- [  6 123  10   1   1   4   7]
- [ 28  43 119  32  15  24  44]
- [  6   6  13 114   1   6  20]
- [  2   7   6   5  55   2   2]
- [ 10   0   1   2   2  44   4]
- [  3   4  16  10  16  22  58]]
-Node Classification on random seed  5398 -> 0.599
-Confusion Matrix:
- [[ 61   8   4   6   3   7  14]
- [  8 104   2   5  14   6   3]
- [ 26  19 152  31  20  30  39]
- [ 13  13  14  87   5  12  18]
- [  1   5   2   0  63   2   4]
- [  6   2   5   0   0  50   5]
- [  8   4   4   9  10  14  82]]
-Node Classification on random seed  5399 -> 0.597
-Confusion Matrix:
- [[ 48   6   8   7   6  14  15]
- [  7 142   1   2   4   0   2]
- [ 33  18 110  46  24  29  47]
- [ 10   4  13 119   2  10   8]
- [  5  11   2   0  52   2   5]
- [  8   6   0   0   0  42   7]
- [ 12   3   3   4   7  12  84]]
-Node Classification on random seed  5400 -> 0.631
-Confusion Matrix:
- [[ 57   2   1   4   4  20  18]
- [  0 110   8   9  10   1   1]
- [ 25  20 158  30  36  21  25]
- [  4   3   7 127   4   6  15]
- [  3   6   6   3  64   0   5]
- [  3   1   0   6   3  44   5]
- [  9   2  17  11   4  11  71]]
-Node Classification on random seed  5401 -> 0.65
-Confusion Matrix:
- [[ 74   5   1   7   1  13  11]
- [  2 152   3   0   4   4   3]
- [ 28  30 140  25  19  23  38]
- [  8   3  24 109   3   6  10]
- [  0  10   3   1  52   1   2]
- [  3   3   4   1   1  48   1]
- [  7   0  14  12  10   6  75]]
-Node Classification on random seed  5402 -> 0.612
-Confusion Matrix:
- [[ 70   3  10   5   5  14   6]
- [ 13 110   4   2  11   3   4]
- [ 27   9 156  25  14  22  36]
- [ 36   4  11 111   8   2   4]
- [  0   8   3   0  52   3   4]
- [ 12   1   3   3   3  40   2]
- [ 11   3   6  22   6  20  73]]
-Node Classification on random seed  5403 -> 0.629
-Confusion Matrix:
- [[ 61   8  12  10   3   9   6]
- [  4 139   3   0   1   3   5]
- [ 25  36 162  20  20  27  27]
- [ 13   7  15  82   0  16  16]
- [  1   7   1   1  66   3   0]
- [  4   2   2   0   2  46   6]
- [ 10   7   9   4   8  18  73]]
-Node Classification on random seed  5404 -> 0.618
-Confusion Matrix:
- [[ 62   7   4   3   3  17   7]
- [  2 127   4   6   8   5   1]
- [ 17  33 150  32  23  18  38]
- [ 10  10  17  85   8   6  16]
- [  0   2   2   0  72   0   4]
- [  3   0   2   1   1  47   5]
- [ 15   7   6   3  10  26  75]]
-Node Classification on random seed  5405 -> 0.613
-Confusion Matrix:
- [[ 72   6   8  10   3   9  14]
- [  5 127  10   2   2   4   3]
- [ 15  29 151  28  22  26  35]
- [  3   8  12 106   6   3  13]
- [  1   6   5   4  51   3   3]
- [ 20   2   2   1   0  31   7]
- [  8   7   6  15   9  12  75]]
-Node Classification on random seed  5406 -> 0.633
-Confusion Matrix:
- [[ 83   6   4   3   4  15   9]
- [  7 126   3   2   8   1   7]
- [ 29  21 132  21  18  20  46]
- [  6   7  11  99  10  10   8]
- [  2   4   6   2  58   3   4]
- [  7   2   1   0   2  62   1]
- [  6   5   1  12   6  27  73]]
-Node Classification on random seed  5407 -> 0.642
-Confusion Matrix:
- [[ 60   1  15   9   0   7  11]
- [  3 137   8   4   3   7   3]
- [ 13  27 160  34  17  20  50]
- [ 12   5  15 101   5   7  19]
- [  0   5   2   3  69   0   2]
- [  5   1   0   1   2  38  12]
- [ 11   1   4   4   5   5  77]]
-Node Classification on random seed  5408 -> 0.632
-Confusion Matrix:
- [[ 72   5   2   6   4  16   2]
- [  3 130   9   2   4   2   3]
- [ 16  33 127  22  20  30  47]
- [ 16   6  13 112   3   6  17]
- [  0   6   5   1  62   1   2]
- [  5   1   0   2   1  43   3]
- [  9   6   4   6   8  21  86]]
-Node Classification on random seed  5409 -> 0.616
-Confusion Matrix:
- [[ 68   2   3  14   8  14  18]
- [ 11 113   4   6  14   1   3]
- [ 25  18 135  42  30  19  36]
- [ 17   3   2 114   3  13   8]
- [  0   5   6   0  57   0   2]
- [  4   1   1   3   0  48   5]
- [  7   2  12   4   2  16  81]]
-Node Classification on random seed  5410 -> 0.617
-Confusion Matrix:
- [[ 83   4   1   6   3  13   6]
- [  2 130   7  11   6   3   2]
- [ 33   7 136  43  25  27  41]
- [  8   4  10  95   5  11   9]
- [  1   3   8   6  48   1   0]
- [ 10   1   0   0   0  50  12]
- [ 13   2  11   5  11  12  75]]
-Node Classification on random seed  5411 -> 0.661
-Confusion Matrix:
- [[ 85   3   2   3   2  14   7]
- [  4 125   2   1   3   0   4]
- [ 11  25 145  28  34  17  46]
- [ 10   5   8 123   7   3  15]
- [  1   6   7   5  58   1   0]
- [  3   2   1   0   2  45   5]
- [ 15   6   8   2   7  14  80]]
-Node Classification on random seed  5412 -> 0.602
-Confusion Matrix:
- [[ 59   2   4  10   2   7  16]
- [  5 126   5   0   1  11   2]
- [ 17  41 125  40  22  30  42]
- [  7  11  20 105   0   8  14]
- [  0   5   6   2  61   4   2]
- [  2   1   4   0   0  35   9]
- [  8   3  10   5   8  12  91]]
-Node Classification on random seed  5413 -> 0.651
-Confusion Matrix:
- [[ 86   0   3   3   6  10   5]
- [  1 129   6   1  12   6   3]
- [ 21  16 150  27  19  32  31]
- [  8   6  16 102   7   5  23]
- [  0   1   2   2  52   2   3]
- [  6   1   0   4   0  53   5]
- [ 12   5  13   6   6  14  79]]
-Node Classification on random seed  5414 -> 0.599
-Confusion Matrix:
- [[ 75   2   2   6   4   5  17]
- [ 10 111   1   4  15   3   4]
- [ 14  22 137  48  23  24  50]
- [  9   7  20 110   3   2  10]
- [  4   6   3   4  49   1   3]
- [  9   0   3   1   2  36   5]
- [ 16   4   3  20   3   9  81]]
-Node Classification on random seed  5415 -> 0.624
-Confusion Matrix:
- [[ 72   2   6   4   4   7   8]
- [  4 147   5   1   2   1   3]
- [ 21  26 146  33  47  15  43]
- [  7   3  24  98   6   3  10]
- [  3   8   3   2  54   0   3]
- [  7   0   1   2   0  37   6]
- [ 12   3  12  11   5  13  70]]
-Node Classification on random seed  5416 -> 0.619
-Confusion Matrix:
- [[ 71   8   6   3   3  10   5]
- [ 12 118   3   1   5   5   3]
- [ 38   9 151  34  19  44  37]
- [ 13   2  18 105   3   5  11]
- [  3   4   5   1  59   2   3]
- [  6   0   0   1   0  35  12]
- [ 15   1   9   5   7  10  80]]
-Node Classification on random seed  5417 -> 0.6
-Confusion Matrix:
- [[ 66   6   3   2   7  10  14]
- [  9 113   9   4   4   8   2]
- [ 38  25 124  35  25  37  42]
- [ 14   3   6 115   4   3   7]
- [  2   2   4   1  68   2   2]
- [  8   1   0   4   1  43   1]
- [ 15   3  11   3   5  18  71]]
-Node Classification on random seed  5418 -> 0.628
-Confusion Matrix:
- [[ 82   1   8   4   4   5   2]
- [  3 127   5   0  13   0   6]
- [ 32  27 145  44  25  22  28]
- [  9   3  13 109   4   2  20]
- [  2   3   2   0  46   2   3]
- [  6   1   1   1   3  45   4]
- [ 10   5   2  12  13  22  74]]
-Node Classification on random seed  5419 -> 0.618
-Confusion Matrix:
- [[ 67   8   0   4   1  17  16]
- [  4 130   3   0   9   2  10]
- [ 18  33 152  36  13  15  36]
- [ 13   5  15 105   8   9   8]
- [  3   5  12   1  51   1   2]
- [  7   1   1   0   2  40  10]
- [ 13   7   7   7   5  15  73]]
-Node Classification on random seed  5420 -> 0.587
-Confusion Matrix:
- [[ 72   3   2   3   2  22  11]
- [  7 115   8   1  10   2   2]
- [ 19  32 119  23  28  27  60]
- [  3   1  21 101   3   8  16]
- [  3   8   4   0  65   0   6]
- [ 13   2   1   0   0  37   4]
- [ 12   2   6   9   9  20  78]]
-Node Classification on random seed  5421 -> 0.635
-Confusion Matrix:
- [[ 76   2   3   4   7   7   2]
- [  4 129  14   7   2   5   1]
- [ 15  23 124  51  21  23  46]
- [  7   3  10 129   3   3   6]
- [  1   5   3   2  61   0   4]
- [  8   0   1   1   3  32   6]
- [ 15   7   1  14   9  16  84]]
-Node Classification on random seed  5422 -> 0.626
-Confusion Matrix:
- [[ 79   5   4   2   1  15   3]
- [  6 119   5   5   9   0  11]
- [ 52  10 125  22  24  13  47]
- [  7   6   9 119   7  13  14]
- [  1   6   5   2  58   0   1]
- [  8   1   0   3   1  46   6]
- [  9   5   6   8   7  15  80]]
-Node Classification on random seed  5423 -> 0.653
-Confusion Matrix:
- [[ 68   3   4   2   6   8  16]
- [  3 125   3   6  10   2   1]
- [ 22  13 191  37  18  22  11]
- [  8   2  16 105  18   3  10]
- [  0  11   6   2  57   3   2]
- [ 13   0   2   1   2  43   2]
- [ 11   5   7   8   7  21  64]]
-Node Classification on random seed  5424 -> 0.61
-Confusion Matrix:
- [[ 65   4  11   6   3  11  11]
- [  4 132   4   0   0   0   2]
- [ 30  32 158  34  18   5  38]
- [ 15   7  13 101   2   9  18]
- [  2  10   5   2  52   0   4]
- [  9   1   2   2   2  32  18]
- [ 10   2  27   9   2   6  70]]
-Node Classification on random seed  5425 -> 0.617
-Confusion Matrix:
- [[ 57   2   6   5   6  11   8]
- [  2 141   8   0   7   4   4]
- [ 11  31 152  31  22  28  39]
- [ 17   2  11 104   9   7   5]
- [  0   8   7   0  62   4   1]
- [ 11   0   5   0   0  46   4]
- [ 10   7  14  13   4  19  55]]
-Node Classification on random seed  5426 -> 0.616
-Confusion Matrix:
- [[ 73   1   7   3  10  12   5]
- [  6 117   7   1   4   3   9]
- [ 35  17 156  23  23  22  32]
- [  4   3  17  63  16  17  24]
- [  0   9   6   3  69   0   1]
- [ 10   0   2   1   2  47   5]
- [ 22   3   6   4   3   6  91]]
-Node Classification on random seed  5427 -> 0.664
-Confusion Matrix:
- [[ 84   1   1   3   5   7   4]
- [  4 150   2   8   3   2   4]
- [ 26  33 162  31   8  16  32]
- [ 18   9  14 100   6   3   9]
- [  2   9   4   2  56   0   2]
- [  3   4   2   1   0  48   0]
- [ 20   3   5   3   2  25  64]]
-Node Classification on random seed  5428 -> 0.63
-Confusion Matrix:
- [[ 72   4   2   8   1  11  16]
- [  4 118   6   0  10   3   8]
- [ 16  10 160  36  30  30  30]
- [  6   3  13 105   5   3  18]
- [  2   4   3   0  68   0  10]
- [  9   1   1   0   0  48   6]
- [ 11   6  14   8   8  14  59]]
-Node Classification on random seed  5429 -> 0.602
-Confusion Matrix:
- [[ 83   4   2   6   2  10   5]
- [ 12 124   9   1   4   1   1]
- [ 28  28 128  35  31  19  35]
- [ 23  12  10 106   2   8   3]
- [  0   8   1   2  50   2   3]
- [ 13   1   2   1   1  36   3]
- [ 21   7  13   7   5  17  75]]
-Node Classification on random seed  5430 -> 0.595
-Confusion Matrix:
- [[ 68   3   1  13   1   6  13]
- [ 10 124   4   2   5   0   3]
- [ 32  12 136  33  30  23  52]
- [ 13   4  17  91   2  11  11]
- [  5   7   3   4  54   0   1]
- [  3   1   3   4   1  44   5]
- [ 19   4   2   6  11  25  78]]
-Node Classification on random seed  5431 -> 0.586
-Confusion Matrix:
- [[ 78   0   6   4   5   7   9]
- [ 11 122   4   4  16   4   5]
- [ 12  19 114  39  55  29  51]
- [  5   3  29  76   9   6  14]
- [  3   5   2   1  64   2   4]
- [  4   2   3   1   0  50   9]
- [  7   4   4   3   4  10  82]]
-Node Classification on random seed  5432 -> 0.633
-Confusion Matrix:
- [[ 69   0   9   5  10  10   6]
- [  4 135   4   0   5   5   5]
- [ 24  14 127  36  35  30  36]
- [ 13   3  14 117   3   3  11]
- [  5   7   1   1  66   0   3]
- [  2   0   2   0   3  39   7]
- [  7   4   7   4   3  26  80]]
-Node Classification on random seed  5433 -> 0.615
-Confusion Matrix:
- [[ 62   3   4   5   4   8  10]
- [  1 135   4   1  10   0   2]
- [ 23  20 130  34  32  29  50]
- [ 24   1   9  98   9   7  15]
- [  2   6   3   0  58   1   6]
- [  7   0   3   0   1  48   5]
- [  7   6   5   6   8  14  84]]
-Node Classification on random seed  5434 -> 0.61
-Confusion Matrix:
- [[ 66   3   5   6   6  13  18]
- [  3 121   2   2  11   5   1]
- [ 22  18 145  16  23  38  38]
- [  9   3  22 103   2   1  15]
- [  2   2   5   3  70   1   1]
- [  5   1   6   5   4  38   5]
- [ 10   5  16   3  20  14  67]]
-Node Classification on random seed  5435 -> 0.602
-Confusion Matrix:
- [[ 60   1   4   1   6  23  17]
- [  9 113   1   2  22   2   1]
- [ 23  15 144  34  36  27  42]
- [  6   2  25  85   2   5  14]
- [  3   1   1   0  77   0   3]
- [  1   1   4   3   2  52   2]
- [ 13   1   9   4  13  17  71]]
-Node Classification on random seed  5436 -> 0.645
-Confusion Matrix:
- [[ 68   6   5   6   0   9  11]
- [  4 131   5   4   9   7   2]
- [ 26  16 157  33  37  13  31]
- [ 17   1   6 110   5   9   9]
- [  3   9   2   1  48   0   1]
- [  7   1   1   2   2  41   7]
- [ 10   2  14   5   7  10  90]]
-Node Classification on random seed  5437 -> 0.636
-Confusion Matrix:
- [[ 87   1   2   3   1  15   7]
- [  8 113   9   2   7   2   0]
- [ 13  15 138  48  27  15  45]
- [  9   6  11 107   5   2  10]
- [  1   3   7   2  63   1   2]
- [  5   0   5   0   1  49   5]
- [ 15   3  13   6  13  19  79]]
-Node Classification on random seed  5438 -> 0.593
-Confusion Matrix:
- [[ 55   1   5   5   6  14   5]
- [  8 106   6   1  26   5   4]
- [ 11  17 137  48  26  25  43]
- [  7   8  22 113   8   6   7]
- [  5   4   2   1  57   1   2]
- [  5   3   5   4   0  50   5]
- [  8   1   7   7  10  23  75]]
-Node Classification on random seed  5439 -> 0.623
-Confusion Matrix:
- [[ 76   5   2   6   3  11   5]
- [  7 133  12   1   6   2   2]
- [ 28  26 125  40  21  30  29]
- [  8   5  34  95   3   8  10]
- [  1   4   5   1  73   3   3]
- [  6   0   1   2   2  47   5]
- [  9   3   9   3   4  12  74]]
-Node Classification on random seed  5440 -> 0.65
-Confusion Matrix:
- [[ 74   1   0   2   0  11  20]
- [  3 133   7   2  13   7   9]
- [ 25  13 161  22  20  18  33]
- [ 10   3  27 104   2   6  10]
- [  7   6   3   1  50   1   0]
- [  7   4   4   0   1  40  10]
- [ 10   7   2   4   9  10  88]]
-Node Classification on random seed  5441 -> 0.609
-Confusion Matrix:
- [[ 63   2   4  10  10   9   5]
- [  1 131   6   2   3   4   5]
- [ 21  23 152  38  34  25  36]
- [  7  11  17  87   4  14   7]
- [  2  11   1   0  61   1   1]
- [  4   4   1   2   1  55   4]
- [  9   5   6  13  11  17  60]]
-Node Classification on random seed  5442 -> 0.628
-Confusion Matrix:
- [[ 74   1   3   8   3   6   9]
- [  5 131   6   2   8   3   2]
- [ 33  17 164  25  27  27  33]
- [  9   3  12  99   5   9  11]
- [  0   7   8   3  48   2   3]
- [  4   1   4   3   3  58   7]
- [ 17   4   8  10   3  18  54]]
-Node Classification on random seed  5443 -> 0.617
-Confusion Matrix:
- [[ 82   0   4   4   2  20  14]
- [  4 126   3   9   5   4   4]
- [ 25  12 116  51  24  32  30]
- [  9   2  10 105   6   7  16]
- [  2   1  10   4  71   3   4]
- [  5   0   1   1   1  47   4]
- [  8   4   3  11   6  18  70]]
-Node Classification on random seed  5444 -> 0.627
-Confusion Matrix:
- [[ 72   5   5   6   1   3  24]
- [  7 119   8   5   9   0   2]
- [ 29   9 159  18  40   9  47]
- [ 14   0  19 110   6   5   5]
- [  2   7   4   2  62   0   1]
- [  4   3   6   3   0  41   6]
- [ 16   6   8  15   9   5  64]]
-Node Classification on random seed  5445 -> 0.58
-Confusion Matrix:
- [[ 79   1   1   1   3  10  10]
- [  3 127   6   6   4   5   1]
- [ 41  18 115  49  43  14  31]
- [ 26   2  15  97   3   1  22]
- [  2   9   1   3  59   0   0]
- [  9   5   3   3   0  43   2]
- [  8   5  21  10   9  14  60]]
-Node Classification on random seed  5446 -> 0.605
-Confusion Matrix:
- [[ 77   1   0  12   2  10   6]
- [  3 109   8   7  10   1   6]
- [ 14  26 164  39  34  22  34]
- [ 20   3  30  79   5  10  10]
- [  1   1   0   2  64   0   1]
- [  3   2   2   2   5  41   8]
- [ 11   2   9  16   3  14  71]]
-Node Classification on random seed  5447 -> 0.593
-Confusion Matrix:
- [[ 71   1   8   6   5  13   5]
- [  7 112  15   4   5   2   3]
- [ 22  13 125  39  52  19  47]
- [ 10   7  16  92   6   3  15]
- [  1   6   1   3  60   1   4]
- [  7   3   0   0   0  59   2]
- [ 25   6   3   8   5   9  74]]
-Node Classification on random seed  5448 -> 0.589
-Confusion Matrix:
- [[ 72   0   2   4   6   8  15]
- [  3 115   2   2   6   2   4]
- [ 27  18 125  38  47  25  48]
- [ 15   1  17  92   9   6   9]
- [  4   6   3   4  61   1   2]
- [  5   1   2   5   1  48   5]
- [ 16   6  10  13   4   9  76]]
-Node Classification on random seed  5449 -> 0.588
-Confusion Matrix:
- [[ 65   6   6  11   1   6   8]
- [  0 125  10   2   6   6   3]
- [ 21  25 108  78  46  18  22]
- [ 17   1  13 107   4   1  10]
- [  0  10   3   2  63   0   0]
- [  2   1   4   2   3  43  11]
- [ 19   4   3  11   6  10  77]]
-Node Classification on random seed  5450 -> 0.615
-Confusion Matrix:
- [[ 63   2   2   9   5  17  15]
- [  1 140   5   2   5   0  10]
- [ 21  32 148  37  18  23  39]
- [ 19   7  10  81  10  11   9]
- [  1   1   0   1  65   0   2]
- [  8   0   5   1   1  46   0]
- [  6   2   6  11   4  27  72]]
-Node Classification on random seed  5451 -> 0.596
-Confusion Matrix:
- [[ 70   2   7   4   7  10   7]
- [  2 120   6   4   9   3   4]
- [ 25  25 114  46  37  13  49]
- [ 16   4  10 108   1   4   9]
- [  0   5   5   0  60   0   7]
- [  6   1   1   2   0  41   4]
- [ 15   3  12  19   2  18  83]]
-Node Classification on random seed  5452 -> 0.616
-Confusion Matrix:
- [[ 70   5   2   5   5   6  15]
- [  6 118   6   3   9   5   8]
- [ 11  21 151  43  16  19  27]
- [  4  14  21  90   6   5  13]
- [  1   9   7   0  66   1   3]
- [  9   4   0   0   0  42  12]
- [ 26   4  20   0   9   4  79]]
-Node Classification on random seed  5453 -> 0.596
-Confusion Matrix:
- [[ 69   4   6   9   4   6   8]
- [  2 134   3   0   9   6   7]
- [ 26  25 142  38  37  29  47]
- [ 23   3  11  86  12   7   8]
- [  1   1   2   1  63   2   2]
- [  4   0   0   3   0  39   3]
- [ 13   5  16   7   3  11  63]]
-Node Classification on random seed  5454 -> 0.587
-Confusion Matrix:
- [[ 65   0   7   3   2  18  17]
- [  2 123   8   4   7   2   8]
- [ 34  32 122  43  25  26  30]
- [ 10   1  16 122   8   4  11]
- [  1   6   2   1  53   1   5]
- [ 11   1  10   0   0  34   8]
- [  5   5   5   5   7  22  68]]
-Node Classification on random seed  5455 -> 0.602
-Confusion Matrix:
- [[ 74   2   8   4   5  11  13]
- [  1 134   9   1   4   4   1]
- [ 25  34 149  44  30  17  38]
- [ 10   5   9  98   8   4  20]
- [  1   7   6   5  52   0   5]
- [ 11   0   7   1   0  30   6]
- [ 10   4  14   2   3   9  65]]
-Node Classification on random seed  5456 -> 0.607
-Confusion Matrix:
- [[ 63   4   6   3   4  17   6]
- [  3 115  10   3   4   1   2]
- [  8  24 140  48  21  35  27]
- [ 11   3  16 100   5  11  16]
- [  1  10   4   3  59   1   5]
- [  8   8   2   0   2  44   1]
- [ 10   5  17   5   2  21  86]]
-Node Classification on random seed  5457 -> 0.606
-Confusion Matrix:
- [[ 78   1   3   3   3   5   6]
- [ 12 124   2   1   7   1   7]
- [ 31  19 127  32  18  30  60]
- [ 17   0   8  91   8  18  13]
- [  0   4   8   0  63   0   7]
- [  8   0   8   2   0  43   2]
- [ 12   3   0   6   6  23  80]]
-Node Classification on random seed  5458 -> 0.621
-Confusion Matrix:
- [[ 64   4   5  11   6  16   7]
- [ 11 139   3   0   9   5   0]
- [ 21  25 158  43  28  18  29]
- [ 10   7  20  89   1   4   8]
- [  1   5   7   3  60   2   4]
- [  4   4   1   2   1  42   8]
- [  6   3   7   4   9  17  69]]
-Node Classification on random seed  5459 -> 0.623
-Confusion Matrix:
- [[ 66   0  11   6   6  21  17]
- [  1 145   3   4   2   0   5]
- [ 17  23 145  25  26  15  38]
- [ 12   5  24  99   9   2   5]
- [  0   8   3   3  57   4   8]
- [  1   3   0   5   1  46   4]
- [  9   3   9   5  15  19  65]]
-Node Classification on random seed  5460 -> 0.611
-Confusion Matrix:
- [[ 95   4   2   7   4  10   7]
- [  6 111  12   3  12   7   7]
- [ 24  22 156  23  16  39  33]
- [ 16   6  12  87   7   8   7]
- [  2  12   8   0  53   2   1]
- [  6   4   0   4   0  36   3]
- [ 18   6   6   3   9  11  73]]
-Node Classification on random seed  5461 -> 0.608
-Confusion Matrix:
- [[ 63   1   5   1   5  19  11]
- [ 10 108   8   0  11   7   0]
- [ 27   8 152  44  21  19  38]
- [ 15   1  20 105  13  16   8]
- [  0   5   7   0  49   1   0]
- [  4   1   2   0   1  53   6]
- [ 14   2  16   9   5  11  78]]
-Node Classification on random seed  5462 -> 0.615
-Confusion Matrix:
- [[ 77   6   2   2   5  10  13]
- [  2 133   5   1   4   8   1]
- [ 28  34 138  35  32  18  39]
- [ 22   1   9  82   9  12   9]
- [  0   7   5   0  63   1   1]
- [ 11   1   2   1   0  40   4]
- [ 11   3   4   4   7  16  82]]
-Node Classification on random seed  5463 -> 0.593
-Confusion Matrix:
- [[ 73   5  10   1   2  12   4]
- [  4 111  10   1   5   1   5]
- [ 15  41 111  33  17  35  43]
- [ 13   4  30 105   5   8   4]
- [  3  13   1   1  66   2   9]
- [  7   2   1   1   0  50   1]
- [ 27   2   9   4   3  13  77]]
-Node Classification on random seed  5464 -> 0.632
-Confusion Matrix:
- [[ 70   2  12   1   3  18   3]
- [  3 110   7   1  12   1   7]
- [ 34   8 150  44  21  15  42]
- [  9   1  17 108   0   4  22]
- [  3   5   1   4  64   1   1]
- [  2   0   7   5   0  50   6]
- [  4   2  11   2   7  20  80]]
-Node Classification on random seed  5465 -> 0.594
-Confusion Matrix:
- [[ 78   2   2   9   5  10   5]
- [  6 123   3   2   6   7   2]
- [ 31  13 113  45  56  22  43]
- [  8   4  13 108   6   4  19]
- [  1   6   3   1  63   2   4]
- [  5   1   2   3   0  40   6]
- [  9   1  13   7   6  13  69]]
-Node Classification on random seed  5466 -> 0.639
-Confusion Matrix:
- [[ 68   3   3   3   0  12  13]
- [ 16 129   4   6   6   1   5]
- [ 16  24 162  22  28  17  48]
- [  3   5  15  89   4   8  10]
- [  1   7   2   2  70   2   2]
- [  6   0   0   4   0  45  10]
- [ 21   3   2   9   4  14  76]]
-Node Classification on random seed  5467 -> 0.636
-Confusion Matrix:
- [[ 71   2  12   5   3  11   4]
- [  2 131   0   2   5   3   5]
- [ 21  20 158  28  28  15  42]
- [ 15   4  13 110   2   5  20]
- [  0   9   6   0  65   0   4]
- [  8   2   2   2   2  39   2]
- [  9   2  19  14   3  13  62]]
-Node Classification on random seed  5468 -> 0.608
-Confusion Matrix:
- [[ 68   5   1   2   5  20   6]
- [  8 116   4   8   8   1   5]
- [ 28  14 141  30  26  17  37]
- [ 19   2  24 108   4   3   8]
- [  5   4   4   2  57   2   2]
- [ 11   3   4   0   0  43   7]
- [ 26   2  14   8   5   8  75]]
-Node Classification on random seed  5469 -> 0.637
-Confusion Matrix:
- [[ 65   2   6   4   3  22   3]
- [  9 127   3   0   5   5   3]
- [ 30  24 152  28  26  22  25]
- [ 17   1  16 102   5   5   8]
- [  0   6   6   1  58   1   0]
- [ 11   2   0   1   0  46   5]
- [  8   7   6   9   8  20  87]]
-Node Classification on random seed  5470 -> 0.609
-Confusion Matrix:
- [[ 78   3   0   6   2  10  14]
- [  2 145   7   3   1   2   5]
- [ 30  34 112  54  18  26  33]
- [ 14   6  16  97   1   0  15]
- [  0   5   5   1  59   2   3]
- [  5   0   2   2   2  39   2]
- [ 16   3   9   7   2  23  79]]
-Node Classification on random seed  5471 -> 0.629
-Confusion Matrix:
- [[ 76   3   1   1   7  15   1]
- [  3 136   6   4   8   2   2]
- [ 18  23 125  42  19  28  57]
- [  9   2  20 117   3   8   7]
- [  2   7   1   2  65   1   1]
- [  3   1   2  12   0  38   4]
- [ 10   3   8   9   5  11  72]]
-Node Classification on random seed  5472 -> 0.626
-Confusion Matrix:
- [[ 72   3   4   0   8   4  13]
- [  5 136   5   6   5   0   4]
- [ 29  26 147  35  25  25  37]
- [ 24   7  10 103   8   2  13]
- [  0   7   5   4  57   0   3]
- [  2   0   0   4   2  40   8]
- [  8   1   9   4   8  11  71]]
-Node Classification on random seed  5473 -> 0.627
-Confusion Matrix:
- [[ 68   5   6   4   3  13   7]
- [  9 138   6   3   6   0   1]
- [ 20  22 153  35  22  13  25]
- [ 10   5  17  73  19   7  22]
- [  1   4   4   1  58   2   6]
- [  7   3   1   3   1  56   4]
- [ 11   4   5  10  11  15  81]]
-Node Classification on random seed  5474 -> 0.61
-Confusion Matrix:
- [[ 77   3   1   5   4  13  13]
- [  1 119   8   2  15   3   6]
- [ 37  22 164  27  24  21  27]
- [ 13   5  17  84  10   7  18]
- [  2   7   3   0  51   1   2]
- [  1   1   1   2   2  40   3]
- [ 18   4  17   5   3  16  75]]
-Node Classification on random seed  5475 -> 0.609
-Confusion Matrix:
- [[ 86   2   1   4   2   7  10]
- [  5 136   2   6  12   2  10]
- [ 25  26 111  39  22  24  28]
- [ 14   4  21 105   6   7  11]
- [  1   4   2   1  67   1   4]
- [ 10   1   4   3   1  31   9]
- [ 10   7  12   9   9  13  73]]
-Node Classification on random seed  5476 -> 0.612
-Confusion Matrix:
- [[ 69   1   1   5   3   7  21]
- [  7 115   5   7   6   2   9]
- [ 26  12 153  49  23  10  39]
- [ 18   3  15  96   7   3  13]
- [  2   2   4   2  58   0   3]
- [  8   3   4   3   1  45   5]
- [  5   2  16   8  15  13  76]]
-Node Classification on random seed  5477 -> 0.615
-Confusion Matrix:
- [[ 60   8   3   6   6  14   6]
- [ 16 123   6   3   7   5   1]
- [ 24  16 146  55  22  20  26]
- [ 15   5  11 105   4   6  15]
- [  2   5   2   0  52   0   0]
- [  3   1   1   2   0  45  15]
- [  5   3  12   5   7  22  84]]
-Node Classification on random seed  5478 -> 0.62
-Confusion Matrix:
- [[ 67   5  10  10   6  10   5]
- [  9 127   2   1   9   5   6]
- [ 27  26 160  25  36  13  32]
- [  6   3  15 102   9   1  14]
- [  0   3   4   2  54   2   7]
- [ 14   3   3   1   4  35   5]
- [ 17   7   2   7   8   6  75]]
-Node Classification on random seed  5479 -> 0.632
-Confusion Matrix:
- [[ 79   8   6   1   5  10   9]
- [  5 126   6   4  10   3   1]
- [ 14  35 138  34  12  24  35]
- [ 29   3  15  97   3   5   4]
- [  1   7   7   2  62   2   2]
- [  5   1   0   0   0  53   8]
- [ 17   3  17   1   7   7  77]]
-Node Classification on random seed  5480 -> 0.577
-Confusion Matrix:
- [[ 47  13   9   5   2  16   3]
- [  4 124   5   3  10   0   3]
- [ 20  20 140  34  28  23  44]
- [ 17   6  34  83   6   7  16]
- [  0   5   5   1  55   1   2]
- [ 12   4   3   2   0  42   2]
- [ 16   3  17   1   5  16  86]]
-Node Classification on random seed  5481 -> 0.632
-Confusion Matrix:
- [[ 75   3   3  15   1  10  14]
- [  6 116   2   3   5   0  15]
- [ 26  21 153  24  22  23  36]
- [  9   5  14 103   5  10  16]
- [  2   2   3   0  61   0   3]
- [  5   1   3   4   2  43   4]
- [ 16   2  13   6   5   9  81]]
-Node Classification on random seed  5482 -> 0.598
-Confusion Matrix:
- [[ 58   2   5   4   4  21  12]
- [  6 136   4   3   8   7   1]
- [ 22  10 139  41  25  29  49]
- [ 11   5  17  88   5   6  17]
- [  3   7   3   1  44   4   2]
- [  6   1   2   0   0  50   4]
- [ 14   4  11   7   7  12  83]]
-Node Classification on random seed  5483 -> 0.532
-Confusion Matrix:
- [[ 79   2  10   5   2   3   8]
- [  4 113   6   5  11   1   4]
- [ 26  36  97  50  43  27  46]
- [ 14   5  29  77  12   8  14]
- [  1   6   4   3  56   5   1]
- [  9   1   1   2   0  37   6]
- [ 16   4  10   2  15  11  73]]
-Node Classification on random seed  5484 -> 0.634
-Confusion Matrix:
- [[ 79   2   3   1   3  11  27]
- [  3 114   8   1   4   3  16]
- [ 25  15 144  36  24  20  46]
- [  8   3  16 104   2   5  13]
- [  2   6   4   0  57   0   4]
- [  4   1   1   1   0  45   8]
- [  3   8   8   3   3  15  91]]
-Node Classification on random seed  5485 -> 0.598
-Confusion Matrix:
- [[ 76   3   5   4   2  18   6]
- [ 10 106   3   1  11   1  14]
- [ 34  18 132  20  20  28  60]
- [ 15   2   8 108   6   6  21]
- [  2   4   3   0  57   1   4]
- [  2   1   3   2   0  40   3]
- [ 16   7   3  16   8  11  79]]
-Node Classification on random seed  5486 -> 0.612
-Confusion Matrix:
- [[ 78   1   1   5   4  14   7]
- [  4 129   3   5   2   4   1]
- [ 20  29 122  47  26  19  39]
- [ 15   4  15 116   8   9   9]
- [  1   4   4   0  53   5   1]
- [ 10   1   1   2   0  44   6]
- [ 11   3   9  18   6  15  70]]
-Node Classification on random seed  5487 -> 0.588
-Confusion Matrix:
- [[ 64   1   5   2   1   8  19]
- [  3 119   3   0   3   7  13]
- [ 21  20 136  54  24  26  39]
- [ 13   0  17  93   7  15   8]
- [  3   8   6   1  56   0   2]
- [  7   2   8   3   1  34   1]
- [ 16   3  10   9   8  15  86]]
-Node Classification on random seed  5488 -> 0.591
-Confusion Matrix:
- [[ 64   2   3   9   5   6   7]
- [  0 140   5   4   7   1   4]
- [ 31  32 117  46  40  27  24]
- [ 13   6  13 102  17   6   9]
- [  0   9   0   0  62   3   2]
- [  4   1   0   5   1  33  14]
- [  4   1  11  15  15   7  73]]
-Node Classification on random seed  5489 -> 0.578
-Confusion Matrix:
- [[ 68   4   2   6   3  18  12]
- [  4 118  11   0   7   6   6]
- [ 18  26 134  31  27  25  53]
- [ 15   4  18  92   7   4  23]
- [  2   6   3   0  59   0   1]
- [  8   1   3   1   1  43   5]
- [  4   5   4  18  10  20  64]]
-Node Classification on random seed  5490 -> 0.608
-Confusion Matrix:
- [[ 75   2   5   8   3   7  12]
- [  9 116   6   2   5   0   6]
- [ 22  25 112  38  25  37  37]
- [  4   6   5 109   7  10  15]
- [  0  11   4   2  55   2   0]
- [  7   1   2   4   2  44  20]
- [  2   2   8  10   8  11  97]]
-Node Classification on random seed  5491 -> 0.637
-Confusion Matrix:
- [[ 72   2   2  13   1  14   7]
- [  1 124   9   2   4   2   4]
- [ 16  13 164  37  31  24  20]
- [ 15   6  15 108   8   6  12]
- [  2  10   3   1  61   0   3]
- [  4   2   1   4   1  41   2]
- [ 10   4  18   4  10  20  67]]
-Node Classification on random seed  5492 -> 0.629
-Confusion Matrix:
- [[ 65   2   5   3   2   8  13]
- [  4 124   1   4   5   4   4]
- [ 28  17 166  38  16  29  32]
- [  5   0  12 106   8  15   8]
- [  3   4   1   4  56   4   5]
- [  8   1   0   0   2  45   9]
- [ 12   8  10   3   2  32  67]]
-Node Classification on random seed  5493 -> 0.565
-Confusion Matrix:
- [[ 83   0   7   3   0  13  10]
- [  7 140   2   4  16   3   1]
- [ 24  19 116  50  23  33  47]
- [ 15   5  27  72   6  11  12]
- [  2   6   7   1  49   0   4]
- [  9   2   1   1   1  44   1]
- [ 13  10   9   7  10  13  61]]
-Node Classification on random seed  5494 -> 0.603
-Confusion Matrix:
- [[ 84   3   0  13   6   5   7]
- [  3 124  11   0   9   2   3]
- [ 31  34 128  33  29  21  26]
- [ 17   5  12 108  15   5  18]
- [  2  13   4   0  59   0   1]
- [  7   3  10   2   0  37   0]
- [  8   4  15   7   7   6  63]]
-Node Classification on random seed  5495 -> 0.598
-Confusion Matrix:
- [[ 69   6   1   3   1  14   7]
- [  3 122   3   2   7   2   2]
- [ 29  15 138  40  36  23  34]
- [ 10  10  20 105   8   8  14]
- [  7   1   1   5  59   0   1]
- [  6   1   3   2   1  40   3]
- [ 11   8   7  10  15  22  65]]
-Node Classification on random seed  5496 -> 0.648
-Confusion Matrix:
- [[ 83   5   1   2   5   7  11]
- [  2 120   2   4   4   1   7]
- [ 36  20 136  33  23   9  33]
- [  9   7  15 109  10   3   7]
- [  0   5   7   1  65   0   4]
- [ 10   3   3   0   0  49   5]
- [ 15   1  12   9   9  12  86]]
-Node Classification on random seed  5497 -> 0.588
-Confusion Matrix:
- [[ 58   3   1   5   8   9  20]
- [  5 115  17   0   3   4   6]
- [ 33  21 143  25  50  19  32]
- [  9   6  27  87  12   6   8]
- [  0   4   0   3  56   1   3]
- [  5   2   0   4   0  52   4]
- [  7   7   6  15   6  16  77]]
-Node Classification on random seed  5498 -> 0.613
-Confusion Matrix:
- [[ 70   2   6   3   4  25   3]
- [  4 129   1   2  10   4   4]
- [ 20  38 144  27  24  21  32]
- [ 21   7  31  94   1   4   2]
- [  0   7   4   2  60   0   1]
- [ 11   1   1   1   0  47   1]
- [ 19   6   8   4   4  21  69]]
-Node Classification on random seed  5499 -> 0.614
-Confusion Matrix:
- [[ 57   6   7   8   6  10  13]
- [  2 137   3   1  13   5   4]
- [ 32  19 146  46  29  29  19]
- [  7   1  16 109   4   2  15]
- [  0   6   1   0  58   3   2]
- [  8   0   5   2   5  34   3]
- [  7   5   6  17   4  15  73]]
-Node Classification on random seed  5500 -> 0.633
-Confusion Matrix:
- [[ 86   1   2   1   1  12   3]
- [  5 126  11   2  10   5   5]
- [ 20  27 129  48  26  32  25]
- [  7   8  11 102   7   5  11]
- [  0   5   5   2  65   1   2]
- [  5   2   4   0   0  40   7]
- [ 10   1  12   7   7  12  85]]
-Node Classification on random seed  5501 -> 0.565
-Confusion Matrix:
- [[ 46   2   8   3   3  16  18]
- [  3 133  13   3   5  11   6]
- [ 18  26 145  30  31  29  43]
- [ 22   2  14  81   1   8  15]
- [  3  12   4   6  44   0   0]
- [  5   3  10   2   0  44   5]
- [ 11   3  14   4   5  18  72]]
-Node Classification on random seed  5502 -> 0.631
-Confusion Matrix:
- [[ 78   2   7  10   4  11   6]
- [  3 124   2   3   5   3   6]
- [ 21  18 144  48  32  19  29]
- [ 14   5  16 108   8   5  16]
- [  1   7   3   0  68   1   1]
- [  2   2   2   1   0  40   3]
- [  9   2   6  10   4  22  69]]
-Node Classification on random seed  5503 -> 0.594
-Confusion Matrix:
- [[ 64   0   2   1   2  20   9]
- [  4 133   7   3   6   2   3]
- [ 18  23 124  40  27  25  54]
- [  8   2  28  92   7   9  21]
- [  4   7   4   1  59   4   4]
- [  2   6   8   0   3  44   2]
- [  6   1   4   4   6  19  78]]
-Node Classification on random seed  5504 -> 0.573
-Confusion Matrix:
- [[ 61   0   5   5  12   5  17]
- [  3 123   8   2  19   5  11]
- [ 21  20 135  23  38  26  35]
- [ 12   6  30  84   1   2  16]
- [  0   9   4   4  63   0   1]
- [  3   1  11   5   1  35   4]
- [ 13   6  19   3   6  15  72]]
-Node Classification on random seed  5505 -> 0.624
-Confusion Matrix:
- [[ 87   4   1   2   6   9  14]
- [  6 136   6   0  14   3   5]
- [ 23  35 148  23  20  12  39]
- [ 21   4  21  91   4   6  11]
- [  1   5   2   3  54   1   3]
- [  4   0   2   1   0  50   3]
- [ 21   7   7   7   8  12  58]]
-Node Classification on random seed  5506 -> 0.6
-Confusion Matrix:
- [[ 69   1   5   5   3  20   7]
- [  3 120  12   3   9   5   1]
- [ 23  32 145  39  17  31  34]
- [ 12   0  15  81   6  24   7]
- [  2  11   2   1  58   1   1]
- [  5   0   2   1   0  49   3]
- [ 11   3   8  10   5  20  78]]
-Node Classification on random seed  5507 -> 0.599
-Confusion Matrix:
- [[ 64   4   9   6   1  11   6]
- [  0 124   2   3  18   3   6]
- [ 22  25 134  46  23  22  37]
- [  8   6  15 103   4   4  17]
- [  2   9   4   1  56   1   4]
- [  5   3   2   0   2  50   4]
- [ 18   5   7   4  10  22  68]]
-Node Classification on random seed  5508 -> 0.632
-Confusion Matrix:
- [[ 75   1   3   1   2  11   6]
- [  6 118   3   3  14   3   1]
- [ 26  21 138  35  25  26  47]
- [ 12   2  15 112   7   4   7]
- [  3   4   4   0  54   0   5]
- [  7   0   3   1   0  57   2]
- [ 14   5  15   7   4  13  78]]
-Node Classification on random seed  5509 -> 0.629
-Confusion Matrix:
- [[ 75   0  11   2   3  12   8]
- [  3 110   6   1  20   7   6]
- [ 25  25 154  51  17  17  32]
- [ 12   6  10 116   3   4  14]
- [  3   5   7   0  53   2   2]
- [  3   0   1   3   0  47   3]
- [ 11   3  13   3   4  13  74]]
-Node Classification on random seed  5510 -> 0.652
-Confusion Matrix:
- [[ 62   1   8   4   3  16   8]
- [  3 147   6   0   2   1   4]
- [ 29  28 141  35  27   9  42]
- [ 13   4  10 110   9   3   9]
- [  2  13   2   2  61   0   5]
- [  1   0   2   0   0  46   5]
- [  4   4   5   5   9  15  85]]
-Node Classification on random seed  5511 -> 0.631
-Confusion Matrix:
- [[ 76   4   5   4   1  12  16]
- [  7 117   5   2   7   3   3]
- [ 10  12 143  39  39  30  41]
- [  8   1  11 111   9   4   9]
- [  1   3   7   2  69   2   6]
- [ 10   3   2   0   1  47   3]
- [  8   1   8  12   7  11  68]]
-Node Classification on random seed  5512 -> 0.607
-Confusion Matrix:
- [[ 81   3   5   4   1  10  13]
- [  1 126   5   2  11   1   4]
- [ 29  19 141  30  41  19  39]
- [ 18   3  15  97   4   2  17]
- [  0   9   3   0  54   1   2]
- [  8   2   3   7   2  28   8]
- [ 23   3  10   1   6   9  80]]
-Node Classification on random seed  5513 -> 0.635
-Confusion Matrix:
- [[ 68   2   5   4   9  10  11]
- [  2 131  11   2   7   0   4]
- [ 24  22 145  64  16  15  32]
- [ 12   3  11 107   2   6   9]
- [  0  10   5   2  53   0   2]
- [  9   3   2   0   1  44   3]
- [ 10   4   8   6   6  11  87]]
-Node Classification on random seed  5514 -> 0.629
-Confusion Matrix:
- [[ 65   3   3   3   3  11  20]
- [ 11 128   5   2   2   4   9]
- [ 39  24 158  41  13  15  25]
- [ 12  11  16  85   5   5  18]
- [  2   1   3   2  73   1   2]
- [  6   0   0   0   0  43   5]
- [ 15   2   8   9   6   9  77]]
-Node Classification on random seed  5515 -> 0.616
-Confusion Matrix:
- [[ 63   0   3   4   1  18  10]
- [  3 137  12   2   6   3   4]
- [ 16  37 132  48  24  30  32]
- [  9   4   9 115   3   6  15]
- [  2   5   0   3  54   3   1]
- [  1   3   0   2   3  37  12]
- [  2   6  14   6   4  18  78]]
-Node Classification on random seed  5516 -> 0.593
-Confusion Matrix:
- [[ 74   2   4  11   2   7   6]
- [  4 138   3   3  19   5   4]
- [ 24  20 136  44  41  17  33]
- [ 15   2  15  74  10   1  18]
- [  0   8   1   1  59   0   3]
- [ 10   1   3   4   0  42   8]
- [ 28   3   2  12   8   5  70]]
-Node Classification on random seed  5517 -> 0.625
-Confusion Matrix:
- [[ 68   0   5   3   2  10  13]
- [  2 117   5   6   6  12   5]
- [ 13  24 154  42  19  19  45]
- [  2   3  22  94  16   4  21]
- [  1  13   3   0  51   4   3]
- [  4   4   0   2   0  50   4]
- [  5   0   4   5   9  15  91]]
-Node Classification on random seed  5518 -> 0.616
-Confusion Matrix:
- [[ 72   1   7   8   4   2  12]
- [  4 141   3   0   8   3   0]
- [ 33  24 124  27  36  17  44]
- [  6   3  13 103   1  11  12]
- [  4   8   2   1  63   1   1]
- [ 18   1   2   2   0  41   4]
- [ 24   2   9   5   8  13  72]]
-Node Classification on random seed  5519 -> 0.611
-Confusion Matrix:
- [[ 57   4   8   3   5  20   9]
- [  6 130   5   0   7   1   3]
- [ 24  16 148  15  28  32  51]
- [  7   1  25  92   8   8  15]
- [  4   8   4   1  57   2   5]
- [  6   0   1   2   0  49   5]
- [ 17   2   8   4   4  15  78]]
-Node Classification on random seed  5520 -> 0.581
-Confusion Matrix:
- [[ 75   2   7   3   6  11  13]
- [  9 113   6   1   5  13   1]
- [ 31  24 129  23  26  28  40]
- [ 16  15  19  83   5   8  11]
- [  0   1  10   1  62   1   0]
- [  6   2   2   0   2  39  12]
- [ 18   6   9   2  12  12  80]]
-Node Classification on random seed  5521 -> 0.596
-Confusion Matrix:
- [[ 65   2   8   6   1  10  12]
- [  6 138   3   1   2   2   1]
- [ 19  31 116  38  25  20  50]
- [ 17   4  19  98  10   7  12]
- [  2   7   6   3  58   3   0]
- [  6   2   3   2   1  43   7]
- [ 13   5  11   1  12  14  78]]
-Node Classification on random seed  5522 -> 0.549
-Confusion Matrix:
- [[ 69   5   2   9   5   5  12]
- [  9 116  12   0   7   6   6]
- [ 21  22 113  41  48  20  64]
- [ 13   8  20  95  14   2   9]
- [  0   4  10   0  54   2   2]
- [  6   0   4   3   1  30   4]
- [ 12   4   9   7  14   9  72]]
-Node Classification on random seed  5523 -> 0.607
-Confusion Matrix:
- [[ 65   1   1   3   1  13  12]
- [  6 111   9   0  13   4   8]
- [ 32  28 136  30  27  21  39]
- [  9   7   7 107  15   4  15]
- [  1   7   4   2  53   1   3]
- [  1   2   3   2   1  54  12]
- [  7   3   8   8   6  17  81]]
-Node Classification on random seed  5524 -> 0.628
-Confusion Matrix:
- [[ 62   0   6   7   3  13   5]
- [  5 132   6   0  14   3   1]
- [ 20  33 142  48  17  16  35]
- [  4   8  14 118   1   6  11]
- [  3   6   5   4  68   0   3]
- [  1   2   5   1   1  41   1]
- [  6   4   4  17   9  24  65]]
-Node Classification on random seed  5525 -> 0.605
-Confusion Matrix:
- [[ 55   4   6   8   5   8   5]
- [  6 134   7   2   3   8   2]
- [ 37  23 130  29  26  24  48]
- [ 15   4  15  95  10   5  12]
- [  2   1   0   2  67   1   4]
- [  3   2   1   4   0  37   6]
- [ 16   5  14   7   3  12  87]]
-Node Classification on random seed  5526 -> 0.593
-Confusion Matrix:
- [[ 66   1  10   1   5  11  11]
- [  9 126   1   5  12   3   9]
- [ 24  25 118  44  27  11  48]
- [ 16   2  12  99   7   8  19]
- [  1   5   2   3  69   1   2]
- [  8   1   4   2   1  36   4]
- [ 11   8   5  10   7  11  79]]
-Node Classification on random seed  5527 -> 0.622
-Confusion Matrix:
- [[ 75   5   2   6   3  10   6]
- [  2 113  15   1  11   5   4]
- [ 24  33 149  27  21  24  47]
- [  9   6   9 103   6   7  13]
- [  4   3  10   2  56   0   1]
- [  3   1   2   0   1  47   4]
- [  5   5  12  10   8  11  79]]
-Node Classification on random seed  5528 -> 0.651
-Confusion Matrix:
- [[ 78   3   6   7   3  10   6]
- [  3 143   4   7   1   5   4]
- [ 24  14 138  41  20  18  34]
- [  6   4  18 101  10   7   9]
- [  1  10   4   2  57   4   6]
- [  5   0   4   0   2  45   5]
- [ 11   3  10   4   3  11  89]]
-Node Classification on random seed  5529 -> 0.625
-Confusion Matrix:
- [[ 76   8  21   2   2   8   9]
- [ 10 129   4   3   2   0   3]
- [ 23  23 140  22  25  16  42]
- [ 14   4  21  85   2   3   9]
- [  2   7   3   5  64   1   2]
- [  6   1   4   1   0  46   5]
- [ 17   4  16   4  11  10  85]]
-Node Classification on random seed  5530 -> 0.628
-Confusion Matrix:
- [[ 76   1   0   6   2  14  18]
- [  1 136   6   4   3   6   2]
- [ 26  13 147  40  28  21  24]
- [ 17   3  15 100   8   4  15]
- [  3   7   8   1  40   0   1]
- [  7   1   1   0   1  46   4]
- [ 11   3  15   5  11  16  83]]
-Node Classification on random seed  5531 -> 0.635
-Confusion Matrix:
- [[ 66   5   2   8   0  12   7]
- [  7 112   9   0   5   2   9]
- [ 30  16 131  30  37  20  50]
- [  6   3  10 120   1   2  19]
- [  4   5   4   1  69   0   0]
- [ 18   0   2   0   1  37   6]
- [ 11   1   6   8   3   5 100]]
-Node Classification on random seed  5532 -> 0.638
-Confusion Matrix:
- [[ 75   3   3   4   6   9  13]
- [  6 137   5   3   3   0   0]
- [ 28  21 152  35  19  18  47]
- [ 17   2  14  96  11   6   9]
- [  2   0   4   1  66   1   1]
- [ 12   0   2   1   3  40   2]
- [ 14   4   5  13   5  10  72]]
-Node Classification on random seed  5533 -> 0.651
-Confusion Matrix:
- [[ 77   0   1   9   5   4   7]
- [  3 144   4   0   5   3   2]
- [ 25  24 178  23  20  10  39]
- [ 19   1  20  86   8   4  20]
- [  1   8   3   0  59   2   1]
- [  7   1   0   1   3  42  13]
- [ 10   7   7  12   8   9  65]]
-Node Classification on random seed  5534 -> 0.599
-Confusion Matrix:
- [[ 74   1   4   8   5   3  11]
- [  6 136   8   1  11   1   2]
- [ 29  15 121  52  37  17  42]
- [ 17   2   7 100   7   4   7]
- [  2   5   3   0  74   1   1]
- [  7   1   5   5   2  40   1]
- [ 16   5  17   8  10  15  54]]
-Node Classification on random seed  5535 -> 0.607
-Confusion Matrix:
- [[ 62   2   1  23   4   9   4]
- [  6 124   5   4  10   4   3]
- [ 21  30 155  56  13  22  27]
- [ 11   5  20  92   6   6  11]
- [  1   6   5   0  65   0   2]
- [ 11   0   0   5   0  29   9]
- [ 18   6   5   6  10   6  80]]
-Node Classification on random seed  5536 -> 0.605
-Confusion Matrix:
- [[ 63   9   8   5   4  19  10]
- [  2 114   8   2  15   9   4]
- [ 32  20 139  36  27  38  29]
- [  7   4  12  90   7   4   8]
- [  3   1   4   0  60   0   3]
- [  7   0   0   6   1  42   5]
- [  9   6   3   6   7  15  97]]
-Node Classification on random seed  5537 -> 0.617
-Confusion Matrix:
- [[ 75   0   2   8   7   8  13]
- [  2 122   2  12   8   0   4]
- [ 28  24 147  38  41  15  43]
- [ 11   0  12  95   7   6  14]
- [  1   4   2   0  54   0   5]
- [  6   4   3   1   3  47   5]
- [  4   3   7  14   7   9  77]]
-Node Classification on random seed  5538 -> 0.605
-Confusion Matrix:
- [[ 49   4   6   6   6  20  12]
- [  3 126   9   2   7   0   9]
- [ 21  15 144  47  24  19  31]
- [ 13   3  13  96   9   7  21]
- [  0   7   5   3  62   2   2]
- [  3   0   5   5   1  46   7]
- [ 14   1  15   2   8   8  82]]
-Node Classification on random seed  5539 -> 0.575
-Confusion Matrix:
- [[ 71   2   4  16   2   6   4]
- [  4 137   3   3   0   1   4]
- [ 24  27 106  47  49  15  31]
- [ 11   5   3  95  13   4  29]
- [  3   7   6   2  60   0   6]
- [  2   1   4   6   1  47   5]
- [  2   3  12  27  19  12  59]]
-Node Classification on random seed  5540 -> 0.632
-Confusion Matrix:
- [[ 52   9   4   6   6  29   9]
- [  2 133   2   1   5   4   0]
- [ 20  26 159  28  34  21  31]
- [  6   2  14  98   5   6   7]
- [  0  10   1   0  78   1   4]
- [  3   1   4   1   2  29  10]
- [  9   6   8  10   6  15  83]]
-Node Classification on random seed  5541 -> 0.603
-Confusion Matrix:
- [[ 74   2   3   7   8   6   2]
- [  4 117   4   3   5   4   5]
- [ 13  14 118  29  56  29  62]
- [  7   4  17  99   8   5   6]
- [  1  12   3   0  74   0   0]
- [  9   1   3   3   1  49   3]
- [ 11   4   6   8  14  15  72]]
-Node Classification on random seed  5542 -> 0.6
-Confusion Matrix:
- [[ 81   3  14   4   3   3   5]
- [  5 124   9   5  12   0   3]
- [ 21  26 111  47  24  26  54]
- [  8   6  13 109   2   3  10]
- [  3   7   3   3  66   2   3]
- [  3   3   5   3   0  42   8]
- [ 10   4  19   6   3   9  67]]
-Node Classification on random seed  5543 -> 0.636
-Confusion Matrix:
- [[ 71   5   4   8   2   7  10]
- [  5 137   3   2   4   1   7]
- [ 20  23 125  26  29  12  59]
- [  7   4  13 106  12   4  19]
- [  3   8   2   1  59   0   4]
- [  2   2   2   2   3  51   5]
- [ 13   6   8   7   4   6  87]]
-Node Classification on random seed  5544 -> 0.636
-Confusion Matrix:
- [[ 75   2   0   3   4  11  10]
- [  4 135   2   0   9   4   2]
- [ 15  25 147  42  22  30  40]
- [ 12   3  13 110   4   4  16]
- [  1   3   2   1  59   0   8]
- [ 10   2   0   1   2  44   5]
- [ 18   2   6   9   3  14  66]]
-Node Classification on random seed  5545 -> 0.619
-Confusion Matrix:
- [[ 79   4   1   0   5   8   5]
- [  3 139   6   2   8   2   2]
- [ 27  14 133  35  29  27  38]
- [ 19   5  10  96   5  18  11]
- [  4   9   1   0  50   1   3]
- [  4   0   1   0   0  50   9]
- [ 14   4  12  12   5  18  72]]
-Node Classification on random seed  5546 -> 0.594
-Confusion Matrix:
- [[ 55   2   4   2  10  11  11]
- [  0 131  14   6   6   7   1]
- [ 23  27 121  31  43  25  42]
- [ 22   1  15 108   6   5  16]
- [  0   2   7   4  61   2   3]
- [  6   2   2   1   1  43   5]
- [ 14   1   6   6   2  12  75]]
-Node Classification on random seed  5547 -> 0.627
-Confusion Matrix:
- [[ 82   2   5   5   3  16  10]
- [ 12 101   8   6  11   0   5]
- [ 25  22 148  46  15  24  30]
- [ 14   4   6 123   3   3  16]
- [  2   9   1   2  63   1   1]
- [  7   3   1   1   3  36  10]
- [ 14   2   3   7   4  11  74]]
-Node Classification on random seed  5548 -> 0.597
-Confusion Matrix:
- [[ 71   6   4   4   6  13   8]
- [  2 117   8   6   7   3   3]
- [ 25  14 125  29  44  22  48]
- [ 24   3  16 100  13   9   8]
- [  2   8   0   2  60   1   3]
- [  5   0   0   2   0  50   2]
- [ 14   1   5   9  11  13  74]]
-Node Classification on random seed  5549 -> 0.657
-Confusion Matrix:
- [[ 59   2   2   5   7  11  16]
- [  2 144   4   4   7   3   4]
- [ 16  13 150  35  25  18  50]
- [ 15   4  18 104   2   2   7]
- [  0   6   5   0  64   1   3]
- [ 10   2   1   2   0  50   2]
- [ 10   3   2   2   2  20  86]]
-Node Classification on random seed  5550 -> 0.59
-Confusion Matrix:
- [[ 68   2  13   6   3   6   6]
- [  6 116   8   0   8   2   9]
- [ 25   7 150  23  26  36  39]
- [  9   6   9  97   4   9  21]
- [  1   6   9   2  58   1   3]
- [  3   4   6   6   0  50   5]
- [ 11   5  14   9  21  21  51]]
-Node Classification on random seed  5551 -> 0.572
-Confusion Matrix:
- [[ 50   4   9   4   3  10  13]
- [  2 131   3   2   6   3   3]
- [ 39  24 117  37  35  16  55]
- [ 13   7  23 106   6   6   8]
- [  1   6   4   3  51   0   7]
- [  6   1   1   2   2  41   6]
- [ 14   3  13  12   4  12  76]]
-Node Classification on random seed  5552 -> 0.596
-Confusion Matrix:
- [[ 89   6   6   4   6   9   8]
- [  9 100  12   2   3   4   6]
- [ 30  21 125  39  39  19  29]
- [ 19   4  18  84  14   5   7]
- [  2   2   5   1  67   0   1]
- [  4   1   3   2   1  57   4]
- [ 16   3  18   2   6  14  74]]
-Node Classification on random seed  5553 -> 0.596
-Confusion Matrix:
- [[ 77   3   4   2   3  13  16]
- [  4 132   3   6   5   1   4]
- [ 25  39 112  48  18  23  40]
- [  7   2  19  99   2   6  24]
- [  1   6   2   3  61   3   7]
- [  6   2   2   1   3  36   4]
- [  7   9  11   4   7   9  79]]
-Node Classification on random seed  5554 -> 0.632
-Confusion Matrix:
- [[ 77   1   2   5   1   7  16]
- [  9 141   5   7   5   0   2]
- [ 17  16 142  34  25  20  36]
- [ 14   4  23 109   3   3  13]
- [  2   8   3   6  65   2   2]
- [  6   0   3   2   1  33   3]
- [ 15   4   8  11   1  23  65]]
-Node Classification on random seed  5555 -> 0.638
-Confusion Matrix:
- [[ 77   2   3   1   2  20   6]
- [  2 131   3   3   4   5   2]
- [ 18  15 149  33  14  26  44]
- [ 22   2  18  93   3   4  20]
- [  2   5   5   2  70   0   6]
- [  2   1   6   0   3  51   1]
- [  9   6   4  10   4  24  67]]
-Node Classification on random seed  5556 -> 0.585
-Confusion Matrix:
- [[ 56   4  12   4   9  15  11]
- [  4 119   5   3   5   1   3]
- [ 26  19 154  39  25  21  37]
- [  9   5  31  79  12   7  13]
- [  2   5   4   1  61   4   3]
- [  8   3   2   2   4  48   4]
- [ 19   1  12   6   7   8  68]]
-Node Classification on random seed  5557 -> 0.64
-Confusion Matrix:
- [[ 64   3   4   1   6  17   5]
- [  3 117  12   4  11   2   0]
- [ 19  15 169  34  25  18  44]
- [  7   0  12  94  11   5  15]
- [  1   3   3   1  75   1   6]
- [  5   1   6   3   2  48   5]
- [ 10   1  12   9   6  12  73]]
-Node Classification on random seed  5558 -> 0.586
-Confusion Matrix:
- [[ 55   1   5   7   5  17  10]
- [  5 124  11   1  15   4   3]
- [ 29  12 102  42  43  31  55]
- [  1   2  22 100   2   9   6]
- [  1   8   1   3  65   2   1]
- [  7   1   1   0   2  47   8]
- [  5   3   2   8   6  17  93]]
-Node Classification on random seed  5559 -> 0.58
-Confusion Matrix:
- [[ 67   1  12   8   1  14   2]
- [  1 133   6  11  10   0   4]
- [ 10  40 113  48  17  22  62]
- [ 11   2  11  97   4   4  16]
- [  1   6   4   3  55   1   8]
- [  4   2   5   2   1  46   4]
- [ 11   8   6  11   6  20  69]]
-Node Classification on random seed  5560 -> 0.598
-Confusion Matrix:
- [[ 58   6   1  10   6  14   8]
- [  4 126   7   7   2   1   4]
- [ 17  23 148  34  27  33  38]
- [  7   6  14 104   8   4   9]
- [  0  10   7   5  61   2   3]
- [ 10   3   0   5   1  45   3]
- [  4   9   3  16   5  26  56]]
-Node Classification on random seed  5561 -> 0.613
-Confusion Matrix:
- [[ 72   0   7   5  11  20   4]
- [  0 133   6   7   3   0   1]
- [ 17  25 119  53  38  11  46]
- [ 17   3  14 114   7   1   7]
- [  1   3   2   3  59   0   3]
- [  3   2   8   1   5  38   3]
- [  6   1  10  10   6  17  78]]
-Node Classification on random seed  5562 -> 0.615
-Confusion Matrix:
- [[ 65   3   4   3   1  16   5]
- [ 14 129   7   0   6   2   4]
- [ 19  23 137  21  45  17  41]
- [ 13  10  17 102   6   6   9]
- [  3  10   1   1  65   3   6]
- [  5   2   1   4   1  41   7]
- [ 21   3   3   8   5   9  76]]
-Node Classification on random seed  5563 -> 0.636
-Confusion Matrix:
- [[ 63   3   1   5   3   8  11]
- [ 11 130   2   6   7   2   4]
- [ 18  31 128  32  19  22  52]
- [ 18   1  11 112   1   3  10]
- [  0   7   3   0  65   1   2]
- [  7   1   2   4   1  49   7]
- [ 11   4   4  12   8   9  89]]
-Node Classification on random seed  5564 -> 0.615
-Confusion Matrix:
- [[ 62   3   6  14   4  12   9]
- [  2 129   7   6   5   8   7]
- [ 28  22 150  23  45  17  40]
- [  4   0  23 103   7   6   8]
- [  1   3   2   1  62   0   1]
- [  8   0   4   2   3  48   5]
- [  5   2  12   4   7  19  61]]
-Node Classification on random seed  5565 -> 0.647
-Confusion Matrix:
- [[ 60   2   3  11   4  16   5]
- [  9 127   5   3  12   1   2]
- [ 18  24 159  45  20  15  37]
- [  3   4  19 107  11   0   7]
- [  3   9   3   1  77   0   1]
- [  2   0   5   6   1  44   3]
- [  6  10   5   7   4  11  73]]
-Node Classification on random seed  5566 -> 0.583
-Confusion Matrix:
- [[ 64   4   1   3   8  22  10]
- [ 12 109   7   2   7   4   5]
- [ 24  32 139  29  15  15  35]
- [ 14   4  18  89   9   8  30]
- [  3   5   4   2  55   3   0]
- [  8   6   3   1   1  50   6]
- [ 18   7   7   0   8  17  77]]
-Node Classification on random seed  5567 -> 0.606
-Confusion Matrix:
- [[ 75   2   2   7   6  10   6]
- [  3 115  10   2  10   5   2]
- [ 20  28 156  32  40  18  32]
- [  7   3  24  92  10   8  14]
- [  1   8   2   2  51   1   5]
- [  0   2   1   1   3  42  10]
- [  8   5   6   8  16  14  75]]
-Node Classification on random seed  5568 -> 0.581
-Confusion Matrix:
- [[ 59  11   3   4   3  13   4]
- [  4 130   8   0   8   4   1]
- [ 19  26 105  52  43  21  33]
- [  7   8  21 111   9  12   9]
- [  3   4   4   4  59   0   3]
- [  5   3   1   1   0  51   2]
- [ 12   4  15   8   6  21  66]]
-Node Classification on random seed  5569 -> 0.595
-Confusion Matrix:
- [[ 76   1   4  10   7   9   7]
- [  6 128  10   5   4   3   2]
- [ 28  21 136  32  15  23  49]
- [ 17   6  15  92   3   6  20]
- [  2   7   5   0  49   0   2]
- [  2   1   4   5   0  51   6]
- [ 11   3  17  15   5  17  63]]
-Node Classification on random seed  5570 -> 0.609
-Confusion Matrix:
- [[ 51   4   3   3  13  19   4]
- [  2 107   5   4   7   7   0]
- [ 14  21 143  39  31  34  45]
- [  5   1  18 119   2  12   6]
- [  0   8   3   3  56   1   4]
- [  4   2   1   2   0  59   2]
- [ 16   2   4  12   9  19  74]]
-Node Classification on random seed  5571 -> 0.617
-Confusion Matrix:
- [[ 80   2   3   4   4  11   9]
- [  5 135   8   1   4   5   4]
- [ 26  15 128  39  23  30  47]
- [ 15   4  13  97   5   6   9]
- [  0   2   3   4  59   0   4]
- [  7   2   2   1   1  50   3]
- [ 13   4  12   8   8  17  68]]
-Node Classification on random seed  5572 -> 0.638
-Confusion Matrix:
- [[ 66   1   1   4   2  16  13]
- [  9 147   5   4   2   3   7]
- [ 12  22 150  31  24  19  41]
- [ 11   3  29  89   4   8   5]
- [  1  11   1   2  66   1   5]
- [  7   0   5   5   0  41   6]
- [ 10   1   6   5   5  15  79]]
-Node Classification on random seed  5573 -> 0.624
-Confusion Matrix:
- [[ 82   4   1   0   3  13   5]
- [  2 137   3   1  11   7   5]
- [ 29  23 131  29  43  26  38]
- [ 11   5   9  98  15   8  16]
- [  0   4   3   1  63   0   2]
- [  5   0   1   2   1  38   3]
- [  6   6   5   4   5  21  75]]
-Node Classification on random seed  5574 -> 0.622
-Confusion Matrix:
- [[ 77   1   5   2   2  10  14]
- [  5 131   1   5   9   2   1]
- [ 13  18 147  36  33  24  41]
- [ 15   2  17  97  13   5  18]
- [  1   8   3   1  58   1   1]
- [  7   1   1   3   5  39   1]
- [ 12   2  12   5   7  15  73]]
-Node Classification on random seed  5575 -> 0.629
-Confusion Matrix:
- [[ 72   0  10   7   3  12   0]
- [  1 123  10   3   5  12   3]
- [ 20  21 149  18  41  13  41]
- [ 16   7  23  99   5  11   4]
- [  1   5   4   1  60   0   4]
- [  5   2   5   1   0  44   2]
- [ 12   7  10   2   7  17  82]]
-Node Classification on random seed  5576 -> 0.606
-Confusion Matrix:
- [[ 66   2   4   4   1  10  21]
- [  4 122   8   9   8   0   4]
- [ 18  12 152  26  16  27  53]
- [  7   4  18 109   4  12  12]
- [  2   2   6   7  49   0   3]
- [  6   0   9   2   0  44   4]
- [ 11   4  12   5   2  35  64]]
-Node Classification on random seed  5577 -> 0.617
-Confusion Matrix:
- [[ 68   3   2   6   5  15   8]
- [  9 128  18   2   6   3   0]
- [ 24  13 148  29  26  27  44]
- [ 12   1  16 103   5   5   4]
- [  2   9   8   3  53   1   1]
- [  8   1   4   1   0  34   9]
- [ 25   1  10   3   9   5  83]]
-Node Classification on random seed  5578 -> 0.578
-Confusion Matrix:
- [[ 47   5   2   3   7  11  15]
- [  9 131   8   0  11   2   4]
- [ 30  29 114  47  26  31  34]
- [ 15   7  20  88  11   3  16]
- [  0   1   6   0  54   0   3]
- [  7   0   0   2   1  52   9]
- [ 13   2  14   4   7   7  92]]
-Node Classification on random seed  5579 -> 0.653
-Confusion Matrix:
- [[ 63   6   1   2   6   3  15]
- [  0 146   6   1  13   2   2]
- [ 10  18 142  33  27  27  33]
- [  8   2  13 106   1   7  11]
- [  3   7   3   1  73   3   3]
- [  9   1   2   3   0  34  17]
- [ 13   7  12   2   8   6  89]]
-Node Classification on random seed  5580 -> 0.585
-Confusion Matrix:
- [[ 58   2   0   2   1  27   6]
- [  2 124   6   5   3   5   2]
- [ 26  24 128  30  24  57  45]
- [  4   3  16  99   2  12  16]
- [  2   5   4   6  65   1   6]
- [  6   0   0   0   0  41  14]
- [  5   3  19   7   4  13  70]]
-Node Classification on random seed  5581 -> 0.614
-Confusion Matrix:
- [[ 56   0   0   8   0  22  10]
- [  3 124   7   4   9   0   9]
- [ 27  17 138  48  14  23  40]
- [  9   2  17  99   5   7  14]
- [  0   7   2   2  71   1   2]
- [  4   2   0   0   2  43  11]
- [ 13   8  12   4   5  16  83]]
-Node Classification on random seed  5582 -> 0.602
-Confusion Matrix:
- [[ 76   1   2   8   3  22  10]
- [  1 128   5   2  11   1   1]
- [ 26  26 131  41  27  30  29]
- [ 16   3   9  92  13  11  12]
- [  1   8   2   2  67   1   0]
- [  4   0   4   3   1  43  13]
- [ 11   1  11  11   8   7  65]]
-Node Classification on random seed  5583 -> 0.637
-Confusion Matrix:
- [[ 71   3   4   1   4  18  10]
- [  8 121   7   2   4   4   4]
- [ 11  25 152  27  26  32  42]
- [  9   3   9 122   4   6  12]
- [  1   7   2   3  62   0   6]
- [  9   2   0   0   3  33   7]
- [ 11   2   3  10   8  14  76]]
-Node Classification on random seed  5584 -> 0.655
-Confusion Matrix:
- [[ 69   1   4   4   2  22  11]
- [  1 136   0   3   2   2   6]
- [ 25  14 154  41  22  27  38]
- [ 17   1   9 100   7   9   9]
- [  0   5   3   0  71   1   3]
- [  4   1   0   4   1  43   2]
- [ 10   3   4   3   2  22  82]]
-Node Classification on random seed  5585 -> 0.627
-Confusion Matrix:
- [[ 71  10   2  10   3  11   9]
- [  4 122   4   2   1   5   4]
- [ 28  27 172  31  19  25  33]
- [ 13   7  13 109   4   4  10]
- [  7   6   2   0  44   0   2]
- [  7   1   2   4   2  39   5]
- [  8   6   8   3   6  25  70]]
-Node Classification on random seed  5586 -> 0.583
-Confusion Matrix:
- [[ 68   5   8   6   0  12  10]
- [  4 124   6   6   5   3   5]
- [ 23  18 141  42  17  29  45]
- [  7   6  27  93   8   2  18]
- [  3   5   6   3  50   0   0]
- [  4   3   7   2   1  34   6]
- [  9   3  16  10   4  23  73]]
-Node Classification on random seed  5587 -> 0.627
-Confusion Matrix:
- [[ 80   5   3   7   0  10   8]
- [  3 130  11   7   4   3   7]
- [ 22  23 151  26  23  10  49]
- [  9   9  16  85   5   4  13]
- [  0   3   5   0  65   0   3]
- [  2   0   8   3   2  43   6]
- [ 19   2  11   7   7  18  73]]
-Node Classification on random seed  5588 -> 0.657
-Confusion Matrix:
- [[ 71   3   4   3   3  10  18]
- [  2 120   1   0   3   6   6]
- [ 28  23 174  25  16  20  20]
- [ 11  13  15 115   5   9   9]
- [  2   7   5   2  58   1   3]
- [  8   3   3   1   0  39   6]
- [ 15   5  11   4   2  12  80]]
-Node Classification on random seed  5589 -> 0.596
-Confusion Matrix:
- [[ 73   2   2  10   2  12   6]
- [  4 125  11   1   2   0   5]
- [ 39  17 133  48  33  18  44]
- [ 15   3  10  96  15  11  12]
- [  2  10   1   2  54   3   0]
- [ 10   2   2   4   0  42   6]
- [  5   5   3  12   7   8  73]]
-Node Classification on random seed  5590 -> 0.643
-Confusion Matrix:
- [[ 66   3   5   6   5   9   9]
- [  3 119  16   0  13   2   7]
- [ 19  11 168  29  16  33  25]
- [ 14   3  16 109   7  10  10]
- [  0   5   7   1  57   0   3]
- [  3   1   1   3   0  55   3]
- [ 10   2   6  12   5  24  69]]
-Node Classification on random seed  5591 -> 0.622
-Confusion Matrix:
- [[ 70   3   3   2   3   8  11]
- [  2 130   5   2  18   1   6]
- [ 41  17 138  26  31  23  30]
- [ 13  11   4 105   6   8   4]
- [  5   2   1   0  68   2   4]
- [  8   6   1   0   2  37  11]
- [  8   1   7  15  10  17  74]]
-Node Classification on random seed  5592 -> 0.641
-Confusion Matrix:
- [[ 81   2   6   2   4   6   5]
- [  3 126   9   0  10   0   4]
- [ 25  14 146  50  32  20  20]
- [ 10   2  13 118   7   7  12]
- [  1   5   1   1  65   1   1]
- [  3   0   5   3   0  41   4]
- [ 19   2  17   7   8  18  64]]
-Node Classification on random seed  5593 -> 0.637
-Confusion Matrix:
- [[ 68   3   3   3   2   7   9]
- [  2 132  12   2   4   3   2]
- [ 25  20 150  27  21  38  40]
- [ 14   4  10 111   4   4  17]
- [  0   5   8   1  52   1   8]
- [ 14   3   1   0   1  41   4]
- [  3   3   8   2   7  18  83]]
-Node Classification on random seed  5594 -> 0.632
-Confusion Matrix:
- [[ 66   4   7   4   3  13   6]
- [  3 113   6   7  13   2   2]
- [ 18  19 158  32  38  33  38]
- [  8   0  15 108   4   6  10]
- [  0   6   2   5  63   2   2]
- [  6   1   1   3   0  45   5]
- [ 13   3   3   2   7  16  79]]
-Node Classification on random seed  5595 -> 0.576
-Confusion Matrix:
- [[ 71   1   8   2   7  11  12]
- [  3 110   1   5  17   1   3]
- [ 16  26 116  45  47  17  59]
- [  9   2  21  75   9  10  11]
- [  1   3   5   0  74   2   1]
- [  2   0   3   0   2  48  13]
- [  3   1   8   7  20  10  82]]
-Node Classification on random seed  5596 -> 0.627
-Confusion Matrix:
- [[ 71   1   3   5   4   9  21]
- [  5 142   3   0  13   1   6]
- [ 25  28 134  27  19  27  44]
- [  3   6  10 118   3   8  14]
- [  2   5   4   4  51   1   4]
- [  0   3   0   0   0  44  14]
- [ 10   0   9   3  13  16  67]]
-Node Classification on random seed  5597 -> 0.621
-Confusion Matrix:
- [[ 83   1   0   4   6   7   3]
- [  1 132   1   3   5   3   6]
- [ 21  45 118  30  22  11  62]
- [ 12  12  16  85  17   1  17]
- [  2   7   2   4  62   0   1]
- [  7   0   3   3   2  43   5]
- [  9   4  11   3   3   7  98]]
-Node Classification on random seed  5598 -> 0.659
-Confusion Matrix:
- [[ 61   4   5   7   3   8  20]
- [  0 124   9   1   3   1   1]
- [ 13  16 177  19  31  17  46]
- [  9   6  13 104   8   7  20]
- [  1   5   3   3  67   1   2]
- [  2   0   2   1   1  54   5]
- [  6   3  13   4   8  14  72]]
-Node Classification on random seed  5599 -> 0.571
-Confusion Matrix:
- [[ 71   2  13   4  10   5   7]
- [  2 108   3   2   9   9   4]
- [ 30  32 150  34  27  18  42]
- [ 22   7  15  88   9   5  20]
- [  2   7   1   1  45   1   1]
- [  9   2   5   6   2  40   6]
- [ 11   2  19   5  10   8  69]]
-Node Classification on random seed  5600 -> 0.602
-Confusion Matrix:
- [[ 77   5   5   3   0   4   6]
- [  7 127  13   0   7   3   2]
- [ 44  35 131  22  25  28  38]
- [ 11   7  21 112   1   4   8]
- [  0   9   5   1  62   2   4]
- [ 10   2   3   1   0  33   5]
- [ 12   3   6   3  16  17  60]]
-Node Classification on random seed  5601 -> 0.63
-Confusion Matrix:
- [[ 71   3   2   3   4   5  11]
- [  2 123  10   3  12   6   7]
- [ 22  21 160  27  19  13  45]
- [ 16   4  11 104   5   4  13]
- [  0   5   7   1  49   0   6]
- [ 11   0   2   5   1  46   4]
- [ 17   7  13  11   2  10  77]]
-Node Classification on random seed  5602 -> 0.623
-Confusion Matrix:
- [[ 78   7   2   7   2  17   1]
- [  6 102  17   0   1   4   7]
- [ 46  30 155  17  26  16  15]
- [  9   1  28 111   8   8  17]
- [  2   2   7   3  63   0   2]
- [  4   0   0   2   1  48   3]
- [  9   4  17   4   7  18  66]]
-Node Classification on random seed  5603 -> 0.631
-Confusion Matrix:
- [[ 62   5   0   3   7  20   3]
- [  2 130   7   2   2   2   0]
- [ 22  28 142  45  20  19  31]
- [  7   3  11 116   7  10   8]
- [  3   9   0   2  68   0   1]
- [  6   3   1   4   1  44   6]
- [  9   9   6  13   6  26  69]]
-Node Classification on random seed  5604 -> 0.63
-Confusion Matrix:
- [[ 61   6   7   8   3   5  10]
- [  4 120   2   3   8   1   4]
- [ 27  21 170  29  35  16  31]
- [ 16   5  13 113   4   6   7]
- [  2   6   3   0  59   0   1]
- [  9   0   5   4   2  43   2]
- [ 17   2  13   6  10  17  64]]
-Node Classification on random seed  5605 -> 0.577
-Confusion Matrix:
- [[ 76   5   0   6   6  14   7]
- [  6 132   2   5   3   0   9]
- [ 18  31 138  38  28  19  41]
- [ 16   2  42  62   4  14  22]
- [  1   4   2   0  52   4   4]
- [  3   3   1   3   2  42   6]
- [ 18   6   8   3   5  12  75]]
-Node Classification on random seed  5606 -> 0.599
-Confusion Matrix:
- [[ 65   2   3   4   5  17  13]
- [  1 130   4   6  11   2   5]
- [ 34  16 123  37  33  16  30]
- [ 13   3  27  96   8   7  12]
- [  3   6   3   1  63   0   2]
- [  7   2   1   1   2  34   7]
- [  5   6  12   9  10  15  88]]
-Node Classification on random seed  5607 -> 0.627
-Confusion Matrix:
- [[ 75   1   0   9   1  15   9]
- [  5 138   0  10  11   2   5]
- [  8  19 140  39  44  23  34]
- [ 10   3  17  98   5   3  11]
- [  2   7   3   6  52   4   5]
- [  1   1   1   3   1  51  10]
- [  4   4   5   7   7  18  73]]
-Node Classification on random seed  5608 -> 0.622
-Confusion Matrix:
- [[ 85   1   2   4   1  12   5]
- [  5 133   3   4   4   2   5]
- [ 34  11 154  38  14  19  34]
- [ 17   5   9 102   5   4  21]
- [  1   3   5   2  58   2   3]
- [  8   2   1   2   1  39  11]
- [ 21   4  14   6  16  17  51]]
-Node Classification on random seed  5609 -> 0.613
-Confusion Matrix:
- [[ 72   2   3  11   4   7   7]
- [  9 131   6   1   9   4   4]
- [ 19  21 162  31  25  27  32]
- [ 16   2  18  96   4   6  14]
- [  1   6   2   0  56   3   2]
- [  8   0   4   1   1  44   1]
- [ 16   0   6  23  10  21  52]]
-Node Classification on random seed  5610 -> 0.606
-Confusion Matrix:
- [[ 55   3  11   6   9  20   7]
- [  5 134   6   1   4   3   1]
- [ 22  24 158  40  21  21  41]
- [ 14   1  19  82  11  10  10]
- [  0   4   4   1  59   2   2]
- [  1   2   3   0   0  48   9]
- [ 15   1  11   7   8  14  70]]
-Node Classification on random seed  5611 -> 0.643
-Confusion Matrix:
- [[ 69   3   5   3   9  11  13]
- [  2 125   6   3   9   6   4]
- [ 37  12 168  30  24  21  32]
- [ 10   5  17 103   4   4   4]
- [  0   8   6   3  66   0   0]
- [  5   2   4   3   3  46   4]
- [  6   4  17   8   4   6  66]]
-Node Classification on random seed  5612 -> 0.611
-Confusion Matrix:
- [[ 61   4   4   6   9  14  11]
- [  2 124   4   3  14   0   8]
- [ 38  17 139  29  48  14  30]
- [ 14   3  14  98   1   4  16]
- [  1   3   1   2  60   2   2]
- [  3   4   1   1   0  51   7]
- [  6   5   8  10  15  11  78]]
-Node Classification on random seed  5613 -> 0.617
-Confusion Matrix:
- [[ 81   1   1   5   4   8   5]
- [  7 119  13  11   3   4   3]
- [ 25  26 128  47  32  14  24]
- [  6   4  12 112   9  16  14]
- [  1   5   1   4  57   2   4]
- [  2   0   5   5   1  46   5]
- [ 20   4   6  10   4  10  74]]
-Node Classification on random seed  5614 -> 0.641
-Confusion Matrix:
- [[ 64   3   1   6   0  13  18]
- [  6 146   4   0  19   4   6]
- [ 26  18 140  20  22  27  37]
- [ 13   5  11 111   1   8   7]
- [  0   8   4   0  59   0   2]
- [  3   0   0   1   0  50   5]
- [  7   5  13   7   7  22  71]]
-Node Classification on random seed  5615 -> 0.624
-Confusion Matrix:
- [[ 64   1   2   2   3  11  16]
- [  6 138   7   7   6   5   7]
- [ 21  14 140  53  19  23  34]
- [ 14   3  11 118   8   4   7]
- [  1   6   5   0  49   2   1]
- [  8   0   2   4   2  43   8]
- [ 17   4   7   6   8  11  72]]
-Node Classification on random seed  5616 -> 0.59
-Confusion Matrix:
- [[ 79   9   4   7   4   9   9]
- [  6 102  17   2  21   2   4]
- [ 26  17 151  31  34  17  48]
- [  9   9  15  99   4   8  13]
- [  4   5   6   2  60   0   2]
- [  6   0   4   1   0  28   3]
- [ 21   4   7   7   6   7  71]]
-Node Classification on random seed  5617 -> 0.618
-Confusion Matrix:
- [[ 71   0   2   5   3  14  18]
- [  8 110   1   7   5   1   1]
- [ 24  17 131  48  30  26  19]
- [ 11   4  11 134   1   3   4]
- [  2   8   2   3  62   4   2]
- [  3   0   4   5   0  42  12]
- [ 19   3   4  17   5  26  68]]
-Node Classification on random seed  5618 -> 0.572
-Confusion Matrix:
- [[ 79   1   3  10   4   5  10]
- [  8 106  13   3  20   2   5]
- [ 27   9 130  47  22  12  51]
- [ 28   4  21  77   3  12  17]
- [  2   4   1   2  61   0   1]
- [  5   2   2   4   2  33  14]
- [ 22   2  10   5   5   8  86]]
-Node Classification on random seed  5619 -> 0.571
-Confusion Matrix:
- [[ 75   2   0   5   5  12  11]
- [ 13 118   6   3   7   7   6]
- [ 29  41 103  22  32  36  26]
- [ 20   2  21  75  15   8  15]
- [  4   8   1   3  63   0   2]
- [  2   2   1   6   1  46   9]
- [ 11   4  11   6   5   9  91]]
-Node Classification on random seed  5620 -> 0.61
-Confusion Matrix:
- [[ 79   3   1   7   3   5   7]
- [  3 131   1   1   6   2   9]
- [ 21  19 110  49  36  27  48]
- [  9   3  27  89   4  10  10]
- [  2   7   6   0  67   2   3]
- [  2   1   0   1   1  55   3]
- [  8   4   4   2  10  23  79]]
-Node Classification on random seed  5621 -> 0.628
-Confusion Matrix:
- [[ 79   4   5   5   3  11   8]
- [  5 116   4   2   8   6   4]
- [ 35  13 129  31  27  29  42]
- [ 14   2  16 115   3   5  14]
- [  0   2   7   3  62   1   3]
- [  4   0   3   1   0  55   3]
- [ 12   2  11   7   4  13  72]]
-Node Classification on random seed  5622 -> 0.596
-Confusion Matrix:
- [[ 80   4   1   6   2  10   7]
- [  5 124   4   5   4   5   8]
- [ 23  42 115  49  27  17  48]
- [  7   1  12 114  10   6   6]
- [  3   5   5   0  56   0   7]
- [  4   3   8   2   0  42   4]
- [ 11   5   8   6   4  20  65]]
-Node Classification on random seed  5623 -> 0.651
-Confusion Matrix:
- [[ 60   3   2   8   6   9  12]
- [  5 136   3   3   9   2   7]
- [ 24  17 154  26  20  21  43]
- [ 11   2  10 124   6   2  13]
- [  1   5   3   3  64   0   2]
- [  7   3   3   5   2  35   1]
- [  9   3   7   4  12  15  78]]
-Node Classification on random seed  5624 -> 0.63
-Confusion Matrix:
- [[ 72   3   3   9   5   7   8]
- [  4 126   2   2   2   9  11]
- [ 29  27 157  24  22  16  33]
- [  6   6  19 109   2  10  10]
- [  2   4   4   0  64   1   3]
- [ 12   0   3   3   0  41   2]
- [ 14   5  10   9   9  20  61]]
-Node Classification on random seed  5625 -> 0.609
-Confusion Matrix:
- [[ 69   5   8   6   4  12   8]
- [  3 122   8   0   4   1   9]
- [ 28  27 142  34  24  23  24]
- [ 12   6  15 101  20   6  16]
- [  2   8   5   1  63   0   1]
- [  1   1   3   1   1  43   7]
- [ 12  12  13   3   5  12  69]]
-Node Classification on random seed  5626 -> 0.633
-Confusion Matrix:
- [[ 64   3  11   5   3  25   8]
- [  4 119   8   1   3   1   5]
- [ 14  20 155  22  16  35  28]
- [  6   8  16 103   3   9  25]
- [  2   5   8   5  55   1   4]
- [  5   1   8   0   0  50   6]
- [ 14   2  12   2   4   9  87]]
-Node Classification on random seed  5627 -> 0.576
-Confusion Matrix:
- [[ 63   1   2   8   2  20  10]
- [  6 118   5   2  14   0   4]
- [ 22  47 125  22  28  25  45]
- [ 11   6  27 108   3   4  16]
- [  5  11   2   1  56   0   3]
- [  7   1   1   7   2  40   3]
- [ 13   6   4   8   8  12  66]]
-Node Classification on random seed  5628 -> 0.615
-Confusion Matrix:
- [[ 65   1   4   8   2   7  15]
- [  5 128   8   2   7   4   3]
- [ 31  30 146  42  25  15  41]
- [ 12   4  19 110   7   3   8]
- [  3   9   1   2  53   1   2]
- [  5   2   5   1   1  45   6]
- [ 14   4   8   8   3   7  68]]
-Node Classification on random seed  5629 -> 0.641
-Confusion Matrix:
- [[ 58   0   5   2   2   5  20]
- [  7 127   5   4   2   3   4]
- [ 17  38 143  30  36  16  33]
- [ 16   3  14 120  15   5  11]
- [  2   8   3   2  56   0   1]
- [  1   1   4   0   0  41   7]
- [  7   2  11   6   4   7  96]]
-Node Classification on random seed  5630 -> 0.589
-Confusion Matrix:
- [[ 70   1   7   6   1   7   6]
- [  4 133  14   1   6   2   5]
- [ 29  30 131  43  16  18  58]
- [ 18   4  25  80   5   7  14]
- [  4   4   5   1  57   3   1]
- [  8   1   3   0   0  51   7]
- [ 12   3   4   4   4  20  67]]
-Node Classification on random seed  5631 -> 0.63
-Confusion Matrix:
- [[ 72   1   1   5   2  12  10]
- [  6 137   4   1   6   5   4]
- [ 27  13 141  33  32  16  37]
- [  4   3  20 107   6   2  12]
- [  2   6   2   4  60   0   7]
- [  7   1   4   3   2  43   8]
- [ 14   2   7   9  18  12  70]]
-Node Classification on random seed  5632 -> 0.599
-Confusion Matrix:
- [[ 70   4   7   3  10  15   9]
- [ 13 127   9   4   6   2   5]
- [ 37  22 122  49  14  22  38]
- [ 10   2  13  92   7   7   9]
- [  0   9   0   3  63   3   1]
- [  4   9   0   1   0  49   5]
- [  8   5  12   8   6  10  76]]
-Node Classification on random seed  5633 -> 0.617
-Confusion Matrix:
- [[ 92   3   2   5   2  11   6]
- [  8 126   7   6   3   0   1]
- [ 27  16 122  34  35  18  44]
- [ 11   9  12 107  17   5   9]
- [  0   7   5   1  57   1   3]
- [  2   1   2   4   0  49   7]
- [  9   4   5   8  12  21  64]]
-Node Classification on random seed  5634 -> 0.614
-Confusion Matrix:
- [[ 74   2   4   2   1  11  13]
- [  5 132   8   5   4   1   2]
- [ 23  28 135  43  17  20  45]
- [ 12   6  13  95   4   2  16]
- [  2  15  10   4  59   1   1]
- [  3   0   1   4   3  44   7]
- [  6   6   5   9   3  19  75]]
-Node Classification on random seed  5635 -> 0.622
-Confusion Matrix:
- [[ 43   7   3   6   5  25  19]
- [  8 132   8   3   4   0   4]
- [ 16  11 151  23  52  11  46]
- [  9   3  11 105   4  10  10]
- [  0   7   8   5  63   0   1]
- [  3   1   3   0   1  47   5]
- [  6   1  10   7   6  16  81]]
-Node Classification on random seed  5636 -> 0.619
-Confusion Matrix:
- [[ 73   3   5   5   3  14  11]
- [  4 115   9   3   9   2   1]
- [ 21  23 145  45  28  29  25]
- [ 18   6   7 112   6   9  11]
- [  1   6   3   0  62   1   2]
- [  3   0   2   1   0  49   6]
- [ 13   4   9   4   8  21  63]]
-Node Classification on random seed  5637 -> 0.634
-Confusion Matrix:
- [[ 64   3   4   4   6  18  13]
- [  3 129   3   1   7   4   5]
- [ 14  13 152  43  31  24  32]
- [ 13   6  13  90   5   9  16]
- [  1   3   6   0  69   3   2]
- [  3   0   2   1   1  51   9]
- [  7   2   8   8   6  14  79]]
-Node Classification on random seed  5638 -> 0.648
-Confusion Matrix:
- [[ 66   2   2   0   2  10  18]
- [  1 155   7   3   5   3   4]
- [ 18  21 153  18  24  31  27]
- [ 21   0  17 108   6   9  10]
- [  1   2   3   0  57   1   3]
- [  4   4   5   1   1  52   6]
- [ 13   6  10   9   4  20  57]]
-Node Classification on random seed  5639 -> 0.65
-Confusion Matrix:
- [[ 72   2   2   8   0   9  13]
- [  6 141   9   0   7   1   3]
- [ 27  21 143  20  36  21  40]
- [ 10   3  17 107   6   5  10]
- [  1   4   5   2  57   1   3]
- [  3   0   2   2   1  42   6]
- [ 11   1  12   6   9   5  88]]
-Node Classification on random seed  5640 -> 0.588
-Confusion Matrix:
- [[ 81   2   9   3   2  10  10]
- [  2 123   8   3  10   2   2]
- [ 20  25 115  46  32  22  40]
- [ 11   1  16 100   6   7  14]
- [  2   9   3   0  57   1   4]
- [  7   1   4   5   2  37   5]
- [ 13   1  19   7   6  20  75]]
-Node Classification on random seed  5641 -> 0.65
-Confusion Matrix:
- [[ 80   2   7   3   0   7  16]
- [  3 114  10   6   3   3   6]
- [ 23  12 149  39  30   7  53]
- [ 10   2  12 102   8   3  22]
- [  0   6   6   0  70   1   0]
- [  3   0   1   2   0  42   7]
- [  5   2   5   8   9   8  93]]
-Node Classification on random seed  5642 -> 0.592
-Confusion Matrix:
- [[ 71   1   5   9   6   7  11]
- [  3 119  17   0   2   1   7]
- [ 25  21 125  36  27  29  38]
- [ 25   6   4 100   3  13  13]
- [  2   4   6   2  59   2   1]
- [  6   0   0   1   3  44   7]
- [ 14   2   4  21  14  10  74]]
-Node Classification on random seed  5643 -> 0.589
-Confusion Matrix:
- [[ 59   4   6  16   5  10  12]
- [  5 127   4   4   6   1   2]
- [ 24  29 128  62  18  30  28]
- [ 12   5  25  84   1   8  13]
- [  1   9   2   0  65   1   2]
- [  0   0   2   1   0  47   8]
- [  9   5  20   6   4  11  79]]
-Node Classification on random seed  5644 -> 0.63
-Confusion Matrix:
- [[ 78   2   1  12   4   7   2]
- [  5 123   4   0   1   1   6]
- [ 36  19 154  32  30  13  46]
- [ 12   2   8  96   3  10  16]
- [  2   7   6   2  56   2   3]
- [  6   5   2   0   0  53   4]
- [ 15   5  11  11   4  13  70]]
-Node Classification on random seed  5645 -> 0.625
-Confusion Matrix:
- [[ 79   3   2   8   4  13   7]
- [  6 124   5   4   4   1   2]
- [ 22  22 167  20  21  32  42]
- [  9   7  18  94   6   6  16]
- [  2   4   6   1  47   0   4]
- [ 14   1   3   0   5  29   9]
- [ 11   2   7   0   3  23  85]]
-Node Classification on random seed  5646 -> 0.617
-Confusion Matrix:
- [[ 75   2   8   4   3  12   9]
- [  5 116   6   0   6   2   8]
- [ 24  20 127  47  23  21  31]
- [  8   4  10 107   5  10  11]
- [  0   4   6   0  65   6   3]
- [  6   0   3   2   0  49   7]
- [ 11   7   9  10  10  20  78]]
-Node Classification on random seed  5647 -> 0.596
-Confusion Matrix:
- [[ 85   2   2   6   0  10  10]
- [ 10 121   9   9   4   3   5]
- [ 22  21 146  35  33  16  41]
- [ 21   4  23  94   3   6   3]
- [  4   3   2   3  65   1   3]
- [  7   1   2   5   0  33   8]
- [ 10   4  19  15   4  15  52]]
-Node Classification on random seed  5648 -> 0.656
-Confusion Matrix:
- [[ 56   2   4   4   9  14  20]
- [  6 124   5   0  10   2   6]
- [ 30  19 171  25  21  14  30]
- [  7   4  14 119   2   4  11]
- [  1   3   3   0  71   1   7]
- [ 10   1   3   1   0  44   4]
- [  2   2  15   5   3  20  71]]
-Node Classification on random seed  5649 -> 0.62
-Confusion Matrix:
- [[ 75   4   4   7   2   5   8]
- [  4 114   7   3   7   2  10]
- [ 21  28 146  20  40   8  62]
- [ 14   6  13 111   4   6  11]
- [  1   1   2   2  62   0   3]
- [  7   0   1   1   3  41   9]
- [ 13   7   4  12   7  11  71]]
-Node Classification on random seed  5650 -> 0.61
-Confusion Matrix:
- [[ 66   2   1  11   6  15   4]
- [ 11 127   5   1   2   0   2]
- [ 11  17 153  35  32  20  36]
- [ 12   5  14 104   2  12  12]
- [  4   6   1   3  56   4   2]
- [  6   2   2   0   4  49   4]
- [ 18   5  18   9  18  16  55]]
-Node Classification on random seed  5651 -> 0.631
-Confusion Matrix:
- [[ 68   3   7   3   3  11   6]
- [  7 141   7   4   5   3   1]
- [ 17  24 141  32  41  35  24]
- [ 21   3  11  93   5   9   4]
- [  2   8   3   1  55   2   2]
- [  9   1   0   2   0  49   5]
- [  8   6   7   5   3  19  84]]
-Node Classification on random seed  5652 -> 0.573
-Confusion Matrix:
- [[ 70   4   8   2   4  22   6]
- [  2 109   5   3  20   5   1]
- [ 34  21 137  28  25  14  54]
- [ 13   7   6  90   4  13  24]
- [  4   2   6   5  63   0   5]
- [  4   0   9   3   1  38  12]
- [ 11   2  14   4  13   7  66]]
-Node Classification on random seed  5653 -> 0.614
-Confusion Matrix:
- [[ 80   3   7   2   5   2  20]
- [  4 147   5   4   9   4   1]
- [ 20  34 118  26  53  15  30]
- [  9   7  23  73   7   5  12]
- [  0   7   1   1  62   1   2]
- [  4   0   3   2   4  38   4]
- [  7   6   9  10  14   4  96]]
-Node Classification on random seed  5654 -> 0.667
-Confusion Matrix:
- [[ 79   2   3   7   3   5   8]
- [  3 126   8   2   4   4   6]
- [ 11  27 174  43  33  19  19]
- [  8   3  13 111   0   6  11]
- [  3   3   4   0  56   2   2]
- [  5   2   0   6   2  35   8]
- [ 17   1   5   6  12   7  86]]
-Node Classification on random seed  5655 -> 0.619
-Confusion Matrix:
- [[ 66   4   3   6  11  12  11]
- [  3 124   4   6   5   5   0]
- [ 22  34 152  25  29  20  30]
- [ 22   4  11  96   1   4  17]
- [  3   6   2   4  60   0   1]
- [ 13   1   0   0   0  45   5]
- [ 17   3  11   7   4  15  76]]
-Node Classification on random seed  5656 -> 0.624
-Confusion Matrix:
- [[ 61   2   1   2   5   6  29]
- [  4 136   4   2   6   1   4]
- [ 31  10 157  32  16  31  41]
- [ 12  11   8 107   5   8  14]
- [  2   5   6   1  51   0   1]
- [  9   0   2   0   2  40   9]
- [ 13   2  22   4   3  10  72]]
-Node Classification on random seed  5657 -> 0.608
-Confusion Matrix:
- [[ 66   6   6   8   5   6   3]
- [  1 121   3   1  20   0   3]
- [ 23  19 129  25  31  20  59]
- [ 11   8  23  95  12   1  19]
- [  1   3   3   2  60   1   3]
- [  7   1   1   2   0  39   7]
- [ 14   6   9   7   7   5  98]]
-Node Classification on random seed  5658 -> 0.601
-Confusion Matrix:
- [[ 82   2   0   7   3   6  18]
- [  5 126  19   3  12   0   2]
- [ 15  24 129  44  19  25  41]
- [ 14   3  10  90  12   4  18]
- [  3   5   6   0  60   0   1]
- [ 10   2   0   3   1  39   4]
- [ 19   5  16   2   9   7  75]]
-Node Classification on random seed  5659 -> 0.58
-Confusion Matrix:
- [[ 71   4   4   9   6  12   7]
- [  6 133   2   2   2   0   1]
- [ 28  40 101  64  23  19  39]
- [ 10   6  16 102  11  10  20]
- [  1  10   2   2  56   1   5]
- [  6   1   3   0   2  42   4]
- [ 15   5   5   6   4   7  75]]
-Node Classification on random seed  5660 -> 0.606
-Confusion Matrix:
- [[ 64   3   4   8   2  15  18]
- [ 10 117   6   2   9   3   5]
- [ 17  20 128  31  42  17  31]
- [  6   5  16 116   7   6  12]
- [  0   4   3   2  64   3   2]
- [  7   3   1   1   0  43   5]
- [  4   1  15  14   6  28  74]]
-Node Classification on random seed  5661 -> 0.606
-Confusion Matrix:
- [[ 70   2  11   4   6   7   3]
- [  6 126   1   2  14   6   0]
- [ 28  30 127  58  14  18  37]
- [  5   9   6 116  12   8   7]
- [  0   7   6   2  53   1   2]
- [  5   2   4   2   0  51   3]
- [ 23   6   7   9  11  10  63]]
-Node Classification on random seed  5662 -> 0.616
-Confusion Matrix:
- [[ 82   3   4   7   4  12   9]
- [  3 104   6   4  27   3   6]
- [ 21  11 142  55  30  25  28]
- [ 18   2  10 102   4   4  17]
- [  3   1   1   0  71   1   2]
- [  6   0   0   3   1  42   4]
- [ 10   1  11  11   5  11  73]]
-Node Classification on random seed  5663 -> 0.582
-Confusion Matrix:
- [[ 75   2   4   7   3  14   6]
- [  1 134  13   4   7   4   6]
- [ 50  33 108  30  32  25  31]
- [ 15   5  10  91   7   5  15]
- [  3   2   9   0  52   0   4]
- [ 11   1   1   0   1  40  11]
- [ 22   4   7   1   5   7  82]]
-Node Classification on random seed  5664 -> 0.577
-Confusion Matrix:
- [[ 61   3   6  12  11  14   4]
- [  8 111   7   8   9   2   5]
- [ 30  17 155  29  15  42  29]
- [ 12   2  19  94   9  21   1]
- [  0   6   8   3  57   1   2]
- [  7   3   2   2   3  46   4]
- [ 12   5   4  15   8  23  53]]
-Node Classification on random seed  5665 -> 0.623
-Confusion Matrix:
- [[ 79   5   5   3   4  12  15]
- [  2 124   6   3   7  12   6]
- [ 24  27 126  36  24  34  18]
- [ 13   3  14 124   3   2   9]
- [  0   6   3   5  58   1   2]
- [  6   0   4   2   0  38   6]
- [ 14   0   8   8   3  22  74]]
-Node Classification on random seed  5666 -> 0.627
-Confusion Matrix:
- [[ 72   3   1   1   7  16   5]
- [  6 123   5   2  13   4   8]
- [ 31  23 156  34  30   9  34]
- [  7   4   9 110   4  11  12]
- [  2   6   5   2  59   0   1]
- [  3   0   4   7   1  47   5]
- [ 14   6  15   2  14   7  60]]
-Node Classification on random seed  5667 -> 0.629
-Confusion Matrix:
- [[ 78   5   5   4   2   7  13]
- [  3 130   6   3   5   1   3]
- [ 26  28 132  31  23  20  62]
- [  9   5  12 111   6   7  10]
- [  0  11   4   1  54   1   2]
- [  4   3   0   5   0  49   4]
- [  4   7   6   6   8   9  75]]
-Node Classification on random seed  5668 -> 0.575
-Confusion Matrix:
- [[ 72   1  10   9   2  17   7]
- [  2 117   2   6  11   6   5]
- [ 29  23 119  32  33  32  32]
- [ 10   6  20 105  14   7  16]
- [  0   5   6   1  53   0   1]
- [  7   0   5   7   1  45   2]
- [  8   4   7  12   7  20  64]]
-Node Classification on random seed  5669 -> 0.604
-Confusion Matrix:
- [[ 72   0   7   3   7  15   8]
- [  2 135   3  10   5   0   3]
- [ 18  21 139  46  27  14  37]
- [ 11   6  13 101   3   2  20]
- [  1   7   7   6  53   2   4]
- [  3   4   1   6   0  44   9]
- [  7   6  11  20   5  16  60]]
-Node Classification on random seed  5670 -> 0.59
-Confusion Matrix:
- [[ 79   2  20   4   6  11   3]
- [  2 126  10   3  16   0   6]
- [ 46  13 115  43  31  14  35]
- [ 10   4  15 111   5   6  12]
- [  0   4   7   1  56   1   2]
- [  5   2   1   2   6  40   4]
- [ 17   1  13   5   9  13  63]]
-Node Classification on random seed  5671 -> 0.636
-Confusion Matrix:
- [[ 74   2   9   5   4   7   6]
- [  1 126   7   6   8   3   2]
- [ 14  21 157  31  18  19  42]
- [ 14   0  19 102   7  11  12]
- [  0   7   2   2  62   4   3]
- [  4   5   1   4   3  43   1]
- [ 15   3  16   5   5  16  72]]
-Node Classification on random seed  5672 -> 0.595
-Confusion Matrix:
- [[ 70   3   1   7   4  14  19]
- [  6 125   4   2   7   2   3]
- [ 27  14 135  37  23  29  53]
- [  9   7  15  88   4   9  18]
- [  3   4   5   0  61   1   1]
- [  3   1   1   1   0  45   9]
- [ 12   6  10   2  10  19  71]]
-Node Classification on random seed  5673 -> 0.633
-Confusion Matrix:
- [[ 74   2   9   2   6   8   6]
- [  1 127   6   3   2   5   2]
- [ 33  12 155  33  17  18  36]
- [ 16   6  14 100   2   9  10]
- [  1   8   7   1  56   2   3]
- [  4   1   4   5   1  43  10]
- [ 13   1  13  15   8  12  78]]
-Node Classification on random seed  5674 -> 0.6
-Confusion Matrix:
- [[ 70   9   5   8   7   2  14]
- [  4 119  17   1   2   5   0]
- [ 15  35 156  40  26  27  30]
- [ 12   4  14  99   8   4   6]
- [  1   4   8   1  56   1   0]
- [ 16   3   4   2   0  29   4]
- [ 12   5  12   9   5  18  71]]
-Node Classification on random seed  5675 -> 0.614
-Confusion Matrix:
- [[ 54   5  12   9   5   9   9]
- [  5 124   9   0  10   2   4]
- [ 14  15 153  36  24  24  55]
- [ 11   4  17  95   3   5  15]
- [  0  10   6   0  58   1   5]
- [  1   1   3   3   1  44   6]
- [ 13   3  10   0  11  10  86]]
-Node Classification on random seed  5676 -> 0.63
-Confusion Matrix:
- [[ 72   4   1   8  11   7  19]
- [  2 127  11   3   5   8   0]
- [ 14  24 150  17  34  15  48]
- [ 14   3  16  98  10   3  11]
- [  1  12   9   0  51   0   3]
- [  6   0   1   3   0  45   9]
- [ 17   4   1   4   8   4  87]]
-Node Classification on random seed  5677 -> 0.646
-Confusion Matrix:
- [[ 79   6   4   8   5   5   5]
- [  2 128   4   1   8   6   6]
- [ 21  24 165  25  38  19  29]
- [ 11   4  15  91   5   8  14]
- [  0  11   4   2  54   1   2]
- [ 10   3   3   0   1  54   1]
- [ 10   3  10   1   3  16  75]]
-Node Classification on random seed  5678 -> 0.61
-Confusion Matrix:
- [[ 58   0   8   5   2  17  13]
- [  6 126   1   5   7   5   1]
- [ 13  18 146  44  50  12  24]
- [  4   7  17 108   3  18  15]
- [  3   5   1   2  70   1   1]
- [  4   1   2   1   2  39   9]
- [  6   4  23   3   9  18  63]]
-Node Classification on random seed  5679 -> 0.615
-Confusion Matrix:
- [[ 69   2   2   3   6  10  10]
- [  3 131   2   2   7   0   1]
- [ 26  21 133  28  38  15  50]
- [ 29   3  26  82   7   7   6]
- [  1   6   4   1  60   1   4]
- [  4   0   0   0   0  50  14]
- [  8   1   3   9  10  15  90]]
-Node Classification on random seed  5680 -> 0.613
-Confusion Matrix:
- [[ 81   3   5   4   3   9  13]
- [  4 143   5   0   3   2   5]
- [ 30  23 117  38  31  16  46]
- [  6   4  18  99   5  11   8]
- [  2   5   3   2  60   2   3]
- [  1   0   0   7   0  43   9]
- [ 16  12   8   5   2  18  70]]
-Node Classification on random seed  5681 -> 0.612
-Confusion Matrix:
- [[ 73   0   1   8   8  13  10]
- [  6 131   7   1   4   5   9]
- [ 31  17 114  28  27  32  46]
- [ 17   3   7 109   5   4   9]
- [  1   5   0   1  59   3   7]
- [  4   2   0   7   0  48   8]
- [ 12   4   5  12   4  15  78]]
-Node Classification on random seed  5682 -> 0.622
-Confusion Matrix:
- [[ 63   8   3  11   2   9  10]
- [  3 117  13   1  10   2   2]
- [  8  19 148  33  30  23  42]
- [  2   4  19  97  10   5  21]
- [  2   8   1   5  64   0   1]
- [  3   6   1   3   0  56   6]
- [  5  10   6   9  11  11  77]]
-Node Classification on random seed  5683 -> 0.561
-Confusion Matrix:
- [[ 71   0   9   8   2   7   5]
- [  4 117  10   1  11  10   2]
- [ 30  35 115  38  30  22  44]
- [ 11   1  17  87  14   4  18]
- [  2  11   2   3  62   0   3]
- [  9   3   2   4   2  40   3]
- [  6   3  11  14  12  16  69]]
-Node Classification on random seed  5684 -> 0.643
-Confusion Matrix:
- [[ 58   2   5   5   2   9  24]
- [  7 139   0   3   6   4   3]
- [ 19  18 147  33  25  22  41]
- [  4   7  16 109  15   4   7]
- [  0   1   2   7  62   1   0]
- [  4   3   0   4   0  43   7]
- [  7   1   6  12   7  14  85]]
-Node Classification on random seed  5685 -> 0.64
-Confusion Matrix:
- [[ 53   1   6  12   1   3  17]
- [  4 120  12   1   8   2   1]
- [ 16  19 163  37  29  14  39]
- [ 17   2  11 114  10   3   9]
- [  1   8   2   0  61   2   2]
- [  6   2   1   2   0  42   3]
- [ 15   6   8  14   3  11  87]]
-Node Classification on random seed  5686 -> 0.608
-Confusion Matrix:
- [[ 83   8   3   2   2   8   8]
- [  3 107  15   2   9   2   5]
- [ 29   7 131  43  26  21  53]
- [ 26   4   6 101   7   9  10]
- [  3   4   5   2  69   1   1]
- [  8   5   3   1   0  31   7]
- [ 16   4  10   5   6   3  86]]
-Node Classification on random seed  5687 -> 0.595
-Confusion Matrix:
- [[ 74   4   6   3   3  11   5]
- [ 15 121  12   1   9   3   8]
- [ 32  27 122  37  47  19  34]
- [  9   4  21  92   6   4   5]
- [  0   2   3   2  58   0   3]
- [  6   2  10   5   0  41   3]
- [  7   1  10   7   6  13  87]]
-Node Classification on random seed  5688 -> 0.639
-Confusion Matrix:
- [[ 77   2   3   8   3  10   8]
- [  7 129   8   2  19   9   0]
- [ 27  21 158  30  22  20  29]
- [ 12   3  17 103   5   2   8]
- [  3   5   6   2  56   0   1]
- [  4   4   0   2   1  40   3]
- [  7   6   8   8  10  16  76]]
-Node Classification on random seed  5689 -> 0.617
-Confusion Matrix:
- [[ 82   2   8   7   5   5   1]
- [  6 115   2   6  17   4   5]
- [ 31  21 144  34  24  19  45]
- [ 15   2  10  95  12   4   8]
- [  1   4   1   2  74   0   2]
- [  6   0   5   3   0  43   3]
- [ 21   4   8  13   6  11  64]]
-Node Classification on random seed  5690 -> 0.632
-Confusion Matrix:
- [[ 89   4   5   2   2   9   7]
- [  3 127   3   2   1   5   6]
- [ 18  25 139  36  15  36  41]
- [ 17   7  11 105   3   4  15]
- [  2  11   5   6  43   2   5]
- [  8   4   1   3   0  50   3]
- [ 12   1   4   9   3  12  79]]
-Node Classification on random seed  5691 -> 0.608
-Confusion Matrix:
- [[ 74   1   4   3   2  10  14]
- [  7 137   4   1  11   6   6]
- [ 17  30 121  41  24  22  34]
- [ 10   1  10  93   5   6  41]
- [  1   7   3   0  54   2   4]
- [  4   0   1   2   1  49   8]
- [  9   1  14   4   7  14  80]]
-Node Classification on random seed  5692 -> 0.633
-Confusion Matrix:
- [[ 80   1   1   4   8   7   8]
- [  5 124   4   7  14   0   8]
- [ 35  21 147  30  27  17  31]
- [  9   2  20  96   7   1  15]
- [  1   5   2   0  69   1   2]
- [  5   2   1   2   5  39   5]
- [ 22   2   7   3  14   6  78]]
-Node Classification on random seed  5693 -> 0.61
-Confusion Matrix:
- [[ 75   4   3   2   5  20   1]
- [  4 136   5   1   4   2   3]
- [ 21  40 149  62  20  17  31]
- [ 14   6  13  93   5   5   8]
- [  2  11   3   1  39   0   2]
- [  9   1   1   0   0  43   6]
- [ 19   6   7   5  10  11  75]]
-Node Classification on random seed  5694 -> 0.604
-Confusion Matrix:
- [[ 73   2   2   4   1  18   7]
- [  8 129   3   1  10   0   4]
- [ 23  21 142  44  42   9  42]
- [ 30   1  27  71   7   5  10]
- [  0   7   3   2  62   2   2]
- [  6   0   1   3   0  46   9]
- [  6   2  16   6   7   3  81]]
-Node Classification on random seed  5695 -> 0.657
-Confusion Matrix:
- [[ 81   5   5   3   2   5   5]
- [  0 137   2   2  17   3   2]
- [ 27  25 161  31  22  11  21]
- [ 12   2  19 102   4   3  15]
- [  4   4   7   4  56   0   5]
- [  6   1   1   1   1  43  13]
- [ 13   2  12   7   3  16  77]]
-Node Classification on random seed  5696 -> 0.589
-Confusion Matrix:
- [[ 65   8  10   5   4  11   8]
- [  6 123   8   2   2   3   2]
- [ 14  48 129  37  40  16  32]
- [ 18  10  21 106   5   1  20]
- [  0   6   6   1  57   0   0]
- [  5   3   1   0   3  36   4]
- [  7   7  12   7   6  12  73]]
-Node Classification on random seed  5697 -> 0.651
-Confusion Matrix:
- [[ 76   2   5   4   8   3  15]
- [  7 122  11   2   6   1   3]
- [ 34  17 168  25  33  11  36]
- [ 11   5  17 107   5   1  10]
- [  2   6   4   0  58   0   2]
- [  5   0   5   5   2  42   7]
- [  8   5  11   9   2   4  78]]
-Node Classification on random seed  5698 -> 0.612
-Confusion Matrix:
- [[ 84   4   0   0   1  14  13]
- [  7 131   3   3   5   2   4]
- [ 14  25 126  43  50  11  40]
- [ 18   6  16 103   3   4  17]
- [  1  14   2   1  59   3   5]
- [  2   0   1   2   3  37   5]
- [ 14   3   3   5   9  12  72]]
-Node Classification on random seed  5699 -> 0.594
-Confusion Matrix:
- [[ 66   1   0   7  10  10   9]
- [  0 127   4   9  15   2   5]
- [ 21  27 134  20  25  39  45]
- [ 25   3  13 101   8  10   8]
- [  0   5   5   2  57   0   7]
- [  5   2   1   4   0  33   5]
- [  5   5   6  21   9   8  76]]
-Node Classification on random seed  5700 -> 0.656
-Confusion Matrix:
- [[ 82   3   8   4   5  12   8]
- [  6 141   4   0   6   0   3]
- [ 23  24 145  33  21  36  29]
- [ 11   7  13 114   3   4   9]
- [  1   6   5   1  60   1   1]
- [  3   3   1   1   1  46   0]
- [  9   2   9   4   7  17  68]]
-Node Classification on random seed  5701 -> 0.652
-Confusion Matrix:
- [[ 65   2   1   5   5   6  19]
- [  6 118   2   1  11   1   7]
- [ 25  11 178  29  17  16  34]
- [ 11   5  13  83   2  11  27]
- [  1   5   2   5  62   1   3]
- [  7   0   2   0   0  51   6]
- [ 17   2  11   6   6   7  95]]
-Node Classification on random seed  5702 -> 0.606
-Confusion Matrix:
- [[ 60   1   0   5   8  16  13]
- [  4 132   3   3   9   1   4]
- [ 48  25 122  25  38  16  39]
- [  7   2  11 102   5   3  15]
- [  4   4   4   1  66   2   0]
- [  1   4   2   1   2  52   2]
- [ 10   1   6   6  26  17  72]]
-Node Classification on random seed  5703 -> 0.587
-Confusion Matrix:
- [[ 64   5   1   4   1  11  18]
- [  9 112   4   0  19   5   1]
- [ 15  27 134  28  16  15  63]
- [ 12   5  17  91   6   7  15]
- [  0   5   8   2  62   4   1]
- [  6   0   2   2   0  49  11]
- [ 19   1   7   9   7  25  75]]
-Node Classification on random seed  5704 -> 0.61
-Confusion Matrix:
- [[ 64   6  11   9   2   3   9]
- [  1 127   4   2  14  10   2]
- [ 21   8 131  26  32  33  48]
- [ 12   5  14 107   3  11  12]
- [  3   7   7   0  52   2   2]
- [  8   4   4   2   1  44   6]
- [  3   2  18   7   2  14  85]]
-Node Classification on random seed  5705 -> 0.582
-Confusion Matrix:
- [[ 61   6   7   4   2  17  15]
- [  4 119   9   1   5   0   2]
- [ 18  15 115  56  31  26  49]
- [ 15   2  10  97   2   4  28]
- [  0   7   5   0  65   2   3]
- [  7   0   2   0   0  51   2]
- [  8   6  11   9   8  20  74]]
-Node Classification on random seed  5706 -> 0.62
-Confusion Matrix:
- [[ 81   1   1   8   4   5   6]
- [  7 121   1   3  10   3   2]
- [ 26  31 110  34  35  22  32]
- [  7   1  13 121   5   5  11]
- [  3   4   4   3  56   1   2]
- [ 10   1   4   4   0  47   5]
- [ 27   2  10  10   9   8  84]]
-Node Classification on random seed  5707 -> 0.62
-Confusion Matrix:
- [[ 68   1   5   4   6  12   4]
- [ 11 120   4   2   4   2   7]
- [ 26  24 147  32  26  27  27]
- [ 22   3  20 101   6   8   6]
- [  2   8   4   6  58   0   3]
- [  5   1   1   2   6  45   3]
- [  7   3   6   9   2  23  81]]
-Node Classification on random seed  5708 -> 0.628
-Confusion Matrix:
- [[ 77   2   6   3   4  10  15]
- [  5 119   4   3  10   4   7]
- [ 11  31 170  33  18  17  33]
- [ 12   3  23  85   4   8  11]
- [  3   3   3   2  62   6   4]
- [  4   0   5   0   0  42  14]
- [  5   3  13   5  17   8  73]]
-Node Classification on random seed  5709 -> 0.624
-Confusion Matrix:
- [[ 72   7   0   8   1   4  15]
- [  7 126   5   4   5   1   1]
- [ 25  32 144  36  28  19  40]
- [  9   1  12 112   2   6  14]
- [  2   4   2   8  64   0   4]
- [  8   1   2   2   0  43   4]
- [ 11   3  15  16   6   6  63]]
-Node Classification on random seed  5710 -> 0.605
-Confusion Matrix:
- [[ 61   2   5   5   3  16  14]
- [  4 124   3   2  11   4   3]
- [  8  25 137  37  47  17  52]
- [  5   6  20 106   3   8  13]
- [  1   8   1   4  58   1   2]
- [  2   2   2   3   1  46   1]
- [  4   5   4  12   6  23  73]]
-Node Classification on random seed  5711 -> 0.581
-Confusion Matrix:
- [[ 56   3  14   3   4   7  21]
- [  4 127  15   2   2   1   2]
- [ 28  14 117  51  29  25  28]
- [ 12   5  16  91   7   5  13]
- [  2   9   4   2  69   1   8]
- [  6   3   4   2   0  46  11]
- [ 12   6  14   0   5  19  75]]
-Node Classification on random seed  5712 -> 0.624
-Confusion Matrix:
- [[ 76   7  12   3   4   7   3]
- [  3 129   4   0   5   2   3]
- [ 37  27 133  34  20  24  35]
- [  7   0  11 111   7   8   7]
- [  2  13   2   0  66   5   2]
- [  8   2   2   1   2  44   7]
- [ 16   2   4  19   9  10  65]]
-Node Classification on random seed  5713 -> 0.614
-Confusion Matrix:
- [[ 68   5   6  10   4  19   6]
- [  6 125  11   0   3   9   5]
- [ 24  24 144  27  10  26  41]
- [ 15   6  16  96   3  11   7]
- [  1   6   8   2  53   2   1]
- [  6   3   0   2   3  44   8]
- [  6   7   9   1   4  23  84]]
-Node Classification on random seed  5714 -> 0.621
-Confusion Matrix:
- [[ 69   3   3   3   5   6  22]
- [ 12 118  11   4   4   8   0]
- [ 25   8 168  32  12  33  35]
- [  6   2  22 103   4   6  16]
- [  0  12   4   2  49   4   3]
- [  7   4   1   0   0  35   5]
- [ 13   8   9   5   4  16  79]]
-Node Classification on random seed  5715 -> 0.633
-Confusion Matrix:
- [[ 73   3  10   2   2  19   3]
- [  8 127   0   2  16   9   2]
- [ 33  16 138  51  16  22  24]
- [  9   3  10 116   5   7   9]
- [  1   7   2   1  59   3   6]
- [  8   1   2   1   1  43   5]
- [  8   2   8   9   4  17  77]]
-Node Classification on random seed  5716 -> 0.612
-Confusion Matrix:
- [[ 78   2   4   3   6   8  22]
- [  8 125   8   3   9   1   3]
- [ 24  13 126  31  39  20  30]
- [  7   4  29  89   5   5  12]
- [  1   4   2   1  71   2   3]
- [  9   2   1   1   1  43   9]
- [ 10   6   8   9   7  16  80]]
-Node Classification on random seed  5717 -> 0.618
-Confusion Matrix:
- [[ 68   2   3   4   5  14  16]
- [  8 127   2   4   9   3   5]
- [ 24  17 135  41  14  23  53]
- [ 10   2   7  96   9   7  19]
- [  2   4   4   0  64   1   1]
- [  9   0   3   2   0  49   5]
- [ 17   0  13   0   3  17  79]]
-Node Classification on random seed  5718 -> 0.641
-Confusion Matrix:
- [[ 69   6   3   0   1   2  12]
- [  2 151   5   7   2   2   2]
- [ 18  22 143  30  27  28  41]
- [  9   4  14  99   8   5  17]
- [  1   8   7   2  67   2   1]
- [  3   3   2   4   0  32  11]
- [ 10   4   4   4   5  21  80]]
-Node Classification on random seed  5719 -> 0.585
-Confusion Matrix:
- [[ 74   5   2   5   1   7   2]
- [  3 117   5   1  11   2   3]
- [ 46  20 114  64  29  19  29]
- [ 14   4  21 106   7   3  10]
- [  3   4   7   9  54   1   2]
- [  9   3   0   0   0  44   6]
- [ 20   3  13   8   5   9  76]]
-Node Classification on random seed  5720 -> 0.628
-Confusion Matrix:
- [[ 57   4   9   2   5  12  11]
- [  5 132   6   3   7   3   6]
- [ 12  20 138  36  27  22  53]
- [ 16   2  11 120   6   2  11]
- [  0  10   4   0  52   1   2]
- [  6   0   1   0   2  50   3]
- [ 11   4   9  12   7   9  79]]
-Node Classification on random seed  5721 -> 0.624
-Confusion Matrix:
- [[ 62   5   4   1   3  13  18]
- [  2 128   5   0   7   2   4]
- [ 20  17 156  34  22  23  50]
- [ 17   1  10 106   2   3  20]
- [  0   8   4   2  59   1   3]
- [  0   0   3   2   2  39  15]
- [  7   2   9   9  15  11  74]]
-Node Classification on random seed  5722 -> 0.595
-Confusion Matrix:
- [[ 55   6   2  16   2  15  14]
- [  7 120   3   2  11   3   5]
- [ 31  38 138  16  39  27  23]
- [ 15   4  10  83   6  12   8]
- [  1   7   5   3  63   0   5]
- [  6   1   0   0   2  54   2]
- [  4   5   8  10   7  24  82]]
-Node Classification on random seed  5723 -> 0.593
-Confusion Matrix:
- [[ 66   3   9   4   4   5  11]
- [  3 112   7   3  16   4   9]
- [ 35  24 120  47  21  47  25]
- [  3   1  12 115   8   5  12]
- [  0   1   3   3  66   3   3]
- [  6   0   1   1   2  28  14]
- [  6   1  13   9   7  16  86]]
-Node Classification on random seed  5724 -> 0.612
-Confusion Matrix:
- [[ 71   4   8   3   0  12   2]
- [  5 132   9   3  11   3   4]
- [ 33  24 139  25  39  24  35]
- [ 11   1  15 110   4   6   8]
- [  8   8   1   1  54   0   4]
- [  9   0   2   1   1  37   3]
- [  6   7   4  11   7  26  69]]
-Node Classification on random seed  5725 -> 0.614
-Confusion Matrix:
- [[ 70   5   5   4  12   6   5]
- [  8 132   3   0   4   4   3]
- [ 27  18 143  29  41  18  54]
- [ 12   5  10 106   5   4   6]
- [  0   7   5   1  48   2   2]
- [  4   2   4   3   2  46   7]
- [ 18   4  11   9   4  13  69]]
-Node Classification on random seed  5726 -> 0.614
-Confusion Matrix:
- [[ 51   3  10   4  11  11  15]
- [  5 134   9   1   8   4   2]
- [ 28  36 138  33  22  14  21]
- [ 18   5  14  90   5   5  11]
- [  1   6   3   3  70   0   2]
- [  7   0   4   1   1  53   2]
- [ 14   4  14  13   5  11  78]]
-Node Classification on random seed  5727 -> 0.626
-Confusion Matrix:
- [[ 82   3   2   8   3  11   3]
- [  4 119   4   4   8   1   6]
- [ 24  12 142  35  35  19  62]
- [  9   1  15  98   8  12   8]
- [  3   3   3   0  69   1   2]
- [  6   3   5   2   2  41   2]
- [ 10   2  10   8   4  11  75]]
-Node Classification on random seed  5728 -> 0.589
-Confusion Matrix:
- [[ 75   3   6   6   5   2  16]
- [  6 134   4   2   5   5   3]
- [ 39  32 113  33  26  21  45]
- [  5   2  16 103   8   0  20]
- [  2   5   3   0  51   0   3]
- [  4   2   6   5   1  39  12]
- [  8   7  16   2   5  20  74]]
-Node Classification on random seed  5729 -> 0.575
-Confusion Matrix:
- [[ 62   3  11   6  11  18   2]
- [  3 135   7   1   3   2   6]
- [ 27  27 129  22  25  26  52]
- [  9   4  16  99  10  12   8]
- [  0   9   4   4  55   5   4]
- [  1   0   9   0   2  46   2]
- [ 11   3  20  10   6  24  49]]
-Node Classification on random seed  5730 -> 0.61
-Confusion Matrix:
- [[ 66   3  12   9   5   4  16]
- [ 12 120   4   2   9   3   6]
- [ 27  25 147  50  21  20  40]
- [ 14   3   7 102   1  12  15]
- [  0   6   2   4  55   1   3]
- [  3   1   2   4   1  44   4]
- [  4   2  11   8   1  13  76]]
-Node Classification on random seed  5731 -> 0.598
-Confusion Matrix:
- [[ 62   4   4  11   2   5  18]
- [  6 130   6   4   7   4   6]
- [ 19  15 134  34  24  18  51]
- [ 14   4  15  90   9   3  21]
- [  3   4   8   6  64   0   4]
- [  6   0   0   0   2  40   7]
- [ 17   2  14   4  13   8  78]]
-Node Classification on random seed  5732 -> 0.621
-Confusion Matrix:
- [[ 78   0   3   7   2  28   6]
- [  2 122   5   1  10   4   5]
- [ 28  15 131  34  20  15  54]
- [ 10   6  13 108   3   7  11]
- [  3   9   6   1  61   2   2]
- [  3   2   3   2   0  50   4]
- [ 14   3   9   5   8  14  71]]
-Node Classification on random seed  5733 -> 0.619
-Confusion Matrix:
- [[ 70   2   4  11   4   5  11]
- [  6 127  11   3  11   2   2]
- [ 31  10 155  32  23  18  43]
- [ 10   1  11 107   7   9  15]
- [  0   4   4   1  59   2   7]
- [  5   2   1   4   0  38   5]
- [ 20   4  13   9   7  11  63]]
-Node Classification on random seed  5734 -> 0.61
-Confusion Matrix:
- [[ 72   1   5   3   3  14  18]
- [  3 125   6   5   4   5   1]
- [ 15  20 142  34  18  37  43]
- [  9  10   7  90  11   9  23]
- [  1  11   4   0  59   2   2]
- [  9   1   1   5   2  42   4]
- [  6   4   4   5   6  19  80]]
-Node Classification on random seed  5735 -> 0.65
-Confusion Matrix:
- [[ 68   7   6   7   6  11  12]
- [  9 134   9   0   1   0   2]
- [ 18  35 157  23  24  15  32]
- [  5   9  11 117   1   8   7]
- [  2   9   6   1  48   0   2]
- [  3   1   4   0   0  53   5]
- [ 14   6   1  15   8  15  73]]
-Node Classification on random seed  5736 -> 0.603
-Confusion Matrix:
- [[ 87   2   4   3   6  11   2]
- [  9 110   2   3   9   2   7]
- [ 21  21 103  36  51  18  57]
- [ 12   5  14 100   7   8   6]
- [  1   7   0   4  71   0   3]
- [  8   1   2   0   0  49   7]
- [ 11   2   9   7   6  13  83]]
-Node Classification on random seed  5737 -> 0.579
-Confusion Matrix:
- [[ 80   3   4   4   3  16   1]
- [  4 120   4   2  10   5   1]
- [ 34  25 116  29  41  24  53]
- [ 11   8  19  82  10   4  12]
- [  1   9   2   0  53   0   2]
- [  6   0   1   1   0  46   3]
- [  9   6   8  18   9  19  82]]
-Node Classification on random seed  5738 -> 0.601
-Confusion Matrix:
- [[ 86   6   4   3   5  17   9]
- [ 11 118  10   3   3   6   2]
- [ 28  22 144  59  16  26  23]
- [ 24   4   8 106   2   2   9]
- [  1   5   5   2  64   1   3]
- [ 10   0   4   2   1  28   4]
- [ 17   8   7  12   3  12  55]]
-Node Classification on random seed  5739 -> 0.631
-Confusion Matrix:
- [[ 73   1   2  12   1   7   5]
- [  5 135  10   7   5   1   1]
- [ 25  26 160  22  41  28  26]
- [  5   4  21 105   7   5   6]
- [  4  10   2   0  55   1   1]
- [  6   2   4   2   1  40   1]
- [ 19   5  11   7   4  16  63]]
-Node Classification on random seed  5740 -> 0.626
-Confusion Matrix:
- [[ 67   2   5   8   4   6  15]
- [  6 146   9   0   5   2   0]
- [ 26  28 145  41  24  23  21]
- [ 10   3  26  98   3   4   6]
- [  2   2   7   3  57   0   2]
- [  6   2   4   1   1  33   8]
- [  9   2  14  12   8  14  80]]
-Node Classification on random seed  5741 -> 0.593
-Confusion Matrix:
- [[ 68   2   4   2   1  12   7]
- [ 11 116   4   4   3   3   6]
- [ 26  22 143  35  48  20  35]
- [  6   1  27  81  11   1  21]
- [  1  12   2   2  47   4   4]
- [  6   0   0   4   1  47   7]
- [ 14   3  11   7   4  13  91]]
-Node Classification on random seed  5742 -> 0.611
-Confusion Matrix:
- [[ 66   2   8   8   6   2   1]
- [  1 121   5   8   7   1   3]
- [ 18  36 137  45  41  15  33]
- [  8   5  17 112   7   3  12]
- [  0   9   2   2  63   1   8]
- [  8   4   2   0   0  47   4]
- [ 11   2  14  10   4  16  65]]
-Node Classification on random seed  5743 -> 0.644
-Confusion Matrix:
- [[ 64   6   4   2   4  17   8]
- [  7 133   1   6  11   0   4]
- [ 11  35 154  22  36  19  34]
- [ 16   4  17 101   4   4  11]
- [  2   2   1   2  58   0   5]
- [  0   1   1   1   2  56   6]
- [  9   1  10   7   5  18  78]]
-Node Classification on random seed  5744 -> 0.669
-Confusion Matrix:
- [[ 71   1   5   2   1   8   9]
- [  2 135   3   2   6   1   3]
- [ 12  21 167  49  21  17  38]
- [ 10   3  10 111   6   5   9]
- [  2   9   4   3  52   2   4]
- [ 16   1   0   0   1  43   7]
- [  7   5   3   5   6  12  90]]
-Node Classification on random seed  5745 -> 0.643
-Confusion Matrix:
- [[ 68   0   1   4   5  11  18]
- [  3 123   3   4  14   2   4]
- [ 18  17 157  34  25  19  48]
- [ 13   4   9 103   4   6  19]
- [  0   3   3   1  49   2   3]
- [  1   0   0   2   3  55   5]
- [  6   7  10   4   7  15  88]]
-Node Classification on random seed  5746 -> 0.644
-Confusion Matrix:
- [[ 78   2   1   7   1  17   9]
- [  1 126  15   7   5   1   1]
- [ 27  26 160  28  14  27  33]
- [ 12   4  14 105   7   3  10]
- [  0   8   5   1  51   2   0]
- [  5   2   2   4   2  52   2]
- [  9   6   3   7   8  18  72]]
-Node Classification on random seed  5747 -> 0.628
-Confusion Matrix:
- [[ 71   2   2   3   3   8  12]
- [  5 133   9   3   2   7   4]
- [ 15  24 126  31  38  17  44]
- [  7   6  12 110  14   2  10]
- [  3   4   3   2  57   0   3]
- [  7   2   0   4   0  44   9]
- [ 11   3  10   7  10  14  87]]
-Node Classification on random seed  5748 -> 0.616
-Confusion Matrix:
- [[ 68   1   2   3   3  13   3]
- [  4 116   6   2   3   1   9]
- [ 20  17 138  55  20  29  43]
- [  7   6  11 108   4  14  14]
- [  1  10   5   1  62   1   5]
- [  1   1   1   0   1  58  10]
- [ 15   1   6   8   7  20  66]]
-Node Classification on random seed  5749 -> 0.605
-Confusion Matrix:
- [[ 76   1   2   2   4   8   5]
- [  1 113   2   5  18   6   2]
- [ 27  18 140  41  34  23  52]
- [ 12   5   4  92  14   8  14]
- [  1   5   2   1  65   0   2]
- [  9   1   0   0   1  41   5]
- [ 13   4   5  10  10  18  78]]
-Node Classification on random seed  5750 -> 0.594
-Confusion Matrix:
- [[ 65   1   6  13   8  12   6]
- [  1 104  10   5   8   8   8]
- [ 18  11 158  39  33  30  43]
- [ 16   2  26  81   3   8   5]
- [  3   4   5   0  64   1   1]
- [  3   1   2   1   2  58   6]
- [ 10   1  17  11   8  10  64]]
-Node Classification on random seed  5751 -> 0.627
-Confusion Matrix:
- [[ 72   5   1   7   5   2  20]
- [  4 100  18   3  22   0   3]
- [ 23  12 150  30  31  36  30]
- [  5   4  11 110   3   7   9]
- [  4   5   2   1  59   2   2]
- [  5   3   0   3   1  47   9]
- [ 12   3   4   3   8  15  89]]
-Node Classification on random seed  5752 -> 0.617
-Confusion Matrix:
- [[ 72   2   6   7   1  12   8]
- [  6 135   1   0  14   2   6]
- [ 40  20 126  26  24  21  55]
- [ 10   6  10 103  12   6  10]
- [  1   5   2   0  61   3   5]
- [  8   1   3   3   0  43   4]
- [ 12   1   3  14   2  11  77]]
-Node Classification on random seed  5753 -> 0.653
-Confusion Matrix:
- [[ 81   3   4   1   5  17   4]
- [  7 129   6   0   2   5   4]
- [ 17  35 136  34  12  18  53]
- [ 11   6  21 119   2   2  11]
- [  0   3   4   2  60   1   5]
- [  3   0   1   1   3  53   7]
- [  3   2   5   5   5  17  75]]
-Node Classification on random seed  5754 -> 0.627
-Confusion Matrix:
- [[ 61   4   3   9   3   7  21]
- [  3 135   5   3   6   0   1]
- [ 16  16 141  46  19  25  42]
- [ 11   3  16  92   4   9  18]
- [  1   6   8   0  68   2   5]
- [  3   2   4   2   0  47   8]
- [  8   5   7   8   7   7  83]]
-Node Classification on random seed  5755 -> 0.623
-Confusion Matrix:
- [[ 85   1   8   1   4  10   6]
- [  1 125   8   3  10   1   9]
- [ 23  15 114  37  12  22  50]
- [ 19   4  12 123   6  13   1]
- [  0   8   3   3  58   2   1]
- [  5   0   4   2   0  51   2]
- [ 27   5  12   8   5  14  67]]
-Node Classification on random seed  5756 -> 0.634
-Confusion Matrix:
- [[ 74   0   1   2   1  22  12]
- [ 14 111  10   2   7   4   2]
- [ 19  16 159  34  27  19  40]
- [  7   1  17 107   4  10   9]
- [  1   3   5   2  59   0   8]
- [  4   0   2   2   1  49   0]
- [  7   2  10   6   4  29  75]]
-Node Classification on random seed  5757 -> 0.57
-Confusion Matrix:
- [[ 72   2   5  12   1  14  16]
- [  2 126   6   1   9   1   6]
- [ 20  11 108  72  37  16  42]
- [ 12   3  19 104  11   2  16]
- [  0  10   7   4  51   2   6]
- [  0   1   2   6   1  46   4]
- [  8   2  11   8   8  14  63]]
-Node Classification on random seed  5758 -> 0.641
-Confusion Matrix:
- [[ 60   3   7   9   3   9  10]
- [  1 125   9   2   8   0   8]
- [ 16  27 151  38  32  18  42]
- [  9   7  12 119   9   7   6]
- [  0   6   3   1  61   0   2]
- [  5   2   2   1   1  42   3]
- [  7   1  11   4   8  10  83]]
-Node Classification on random seed  5759 -> 0.663
-Confusion Matrix:
- [[ 72   5   2   2   1  17   7]
- [  7 124   5   3   5   1   4]
- [ 17  14 186  39  20  19  24]
- [  6   5  26 103   9  12   6]
- [  0   7   4   3  53   0   2]
- [  4   1   3   0   1  48   4]
- [  7   3   6   6  10  20  77]]
-Node Classification on random seed  5760 -> 0.631
-Confusion Matrix:
- [[ 69   1   9   7   2   4  18]
- [  8 132   3   6  11   2   2]
- [ 12  39 135  39  22  24  24]
- [ 10   5   8 112   9   4  13]
- [  3  10   3   3  63   1   2]
- [ 10   1   2   0   1  48   2]
- [ 13   1  11   9   9   6  72]]
-Node Classification on random seed  5761 -> 0.631
-Confusion Matrix:
- [[ 81   2   7   5   3   4   6]
- [ 10 132   7   5  10   3   2]
- [ 17  17 143  40  29  13  35]
- [ 24   1  12  88   9   8  12]
- [  4   4   4   4  58   1   2]
- [ 10   1   2   1   0  51   3]
- [ 16   2   4   9   9  12  78]]
-Node Classification on random seed  5762 -> 0.633
-Confusion Matrix:
- [[ 77   1   3   3  14   8   6]
- [  2 131   5   2  14   1   3]
- [ 32  15 147  52  35   6  32]
- [ 12   8   9  91  10   5  18]
- [  0   1   1   0  59   0   4]
- [  6   0   1   2   3  41   5]
- [ 17   2  10   2   4  13  87]]
-Node Classification on random seed  5763 -> 0.608
-Confusion Matrix:
- [[ 82   3   3   1   4   9   7]
- [  3 119   8   8   1   0  11]
- [ 36  26 127  36  12  44  36]
- [  7   2  12 103   6   6  11]
- [  3   8   3   1  61   3   4]
- [  4   2   0   2   2  34  10]
- [ 15   5   6   8   2  22  82]]
-Node Classification on random seed  5764 -> 0.621
-Confusion Matrix:
- [[ 59   3   3   3   4  12  23]
- [  3 133   7   1   6   1   0]
- [ 17  17 136  35  30  32  36]
- [ 16   1  21 114   3   3   7]
- [  0   2   4   3  59   0   4]
- [ 10   2   5   0   1  36   7]
- [  7   8  11   8   7  16  84]]
-Node Classification on random seed  5765 -> 0.636
-Confusion Matrix:
- [[ 75   1   7   5   7   9   3]
- [  3 122  10   5   8   2   9]
- [ 27  17 148  43  17  21  24]
- [ 14   3  22 101   3   4  11]
- [  0   5   6   3  60   1   2]
- [  9   2   0   2   1  54   3]
- [  8   5  11  13   5  13  76]]
-Node Classification on random seed  5766 -> 0.616
-Confusion Matrix:
- [[ 69   4  12   2   1  13   8]
- [  2 117   2  17  14   3   3]
- [ 27   7 168  33  18  32  39]
- [ 16   0  16  95   3   8   9]
- [  7   6   6   0  66   0   1]
- [  2   2   2   1   2  38   1]
- [ 14   7   6   8   7  23  63]]
-Node Classification on random seed  5767 -> 0.625
-Confusion Matrix:
- [[ 80   1   7   3   4  17  12]
- [  7 138   5   0   2   4   1]
- [ 30  46 128  28  29  19  34]
- [ 17   5   4 106   6   3  18]
- [  1   4   3   2  62   0   0]
- [  6   0   0   0   2  37   1]
- [ 10   5   7  11   5  16  74]]
-Node Classification on random seed  5768 -> 0.623
-Confusion Matrix:
- [[ 56  10   6   7   2   8  15]
- [  4 142   3   0   8   2  10]
- [ 25  21 129  36  26  32  26]
- [  2   2   7 105   7  11  16]
- [  4  10   2   0  66   1   2]
- [  5   2   2   1   0  43   6]
- [ 10   4   8  11   7  16  82]]
-Node Classification on random seed  5769 -> 0.632
-Confusion Matrix:
- [[ 73   3   5   4   5  15   7]
- [  0 124   6   3   6   1   8]
- [ 21  41 142  37  15  15  34]
- [ 11   9  15 130   3   4  15]
- [  0  12   4   5  46   1   2]
- [  3   0   0   3   0  40   7]
- [  6   4   6   9   5  18  77]]
-Node Classification on random seed  5770 -> 0.656
-Confusion Matrix:
- [[ 75   2   2   3   6   9   2]
- [  3 125   6   4  16   2   4]
- [ 13  18 140  33  28  31  37]
- [ 10   1  17 126   4   4   6]
- [  0   4   4   1  66   2   0]
- [  3   3   2   0   2  52   5]
- [ 11   1   0  15   6  24  72]]
-Node Classification on random seed  5771 -> 0.615
-Confusion Matrix:
- [[ 74   3   3   3   0  15   7]
- [  9 136   9   6   8   1   3]
- [ 31  22 123  39  23  16  36]
- [ 13   4  12 115   4   8   7]
- [  3   8   6   1  56   4   3]
- [  7   1   8   0   8  41   4]
- [ 12   5   9   9   4  11  70]]
-Node Classification on random seed  5772 -> 0.646
-Confusion Matrix:
- [[ 85   0   2   5   5   7   3]
- [  5 120   7   2   5   7   3]
- [ 21  17 156  40  19  13  45]
- [ 16   6  10 101  13   7   9]
- [  0   3   2   2  64   1   3]
- [  8   2   2   3   1  45   6]
- [ 13   3  16  10   2  10  75]]
-Node Classification on random seed  5773 -> 0.663
-Confusion Matrix:
- [[ 94   1   1   4   3   5  16]
- [  3 136   6   4   3   4   6]
- [ 20  16 155  30  28   9  52]
- [  4   3  13 105   4   6  14]
- [  2   7   4   2  63   1   5]
- [  3   2   0   3   3  41   9]
- [ 15   0   3   9   4  10  69]]
-Node Classification on random seed  5774 -> 0.594
-Confusion Matrix:
- [[ 66   2   5   6   4   8   8]
- [  9 122   8   8   3   1   3]
- [ 26  27 140  23  26  31  37]
- [ 16   1  23  94   9  13   9]
- [  2   5   4   7  54   3   0]
- [ 15   0   3   1   0  34   6]
- [ 18   2   9  11   3  11  84]]
-Node Classification on random seed  5775 -> 0.618
-Confusion Matrix:
- [[ 63   5  10   3   4  12   9]
- [  7 123  12   3   9   1   6]
- [ 21  10 146  36  29  29  33]
- [  7   3  18 106   2  12  15]
- [  1   4   4   4  54   3   0]
- [  7   3   2   0   1  47   6]
- [ 21   1   3   6   7  13  79]]
-Node Classification on random seed  5776 -> 0.642
-Confusion Matrix:
- [[ 65   1   3   2   3   6  19]
- [  7 135   7   0   2   2   9]
- [ 28  16 174  34  25  16  25]
- [  6   4  22  93   7   6  14]
- [  3  11  10   0  47   0   4]
- [  2   0   4   0   0  47   5]
- [ 15   6  11   4   5  14  81]]
-Node Classification on random seed  5777 -> 0.623
-Confusion Matrix:
- [[ 60   2   1   4   8  18  15]
- [ 15 117   9   1  14   4   7]
- [  9   5 158  33  36  19  40]
- [ 11   7  13 103   2   7  14]
- [  1   8   2   1  67   0   3]
- [  2   1   3   0   2  41   7]
- [ 14   4   5   8   4  18  77]]
-Node Classification on random seed  5778 -> 0.599
-Confusion Matrix:
- [[ 63   5   8  10   4  10   5]
- [  4 122   7   8  16   7   1]
- [ 30  22 134  31  18  38  31]
- [ 14   6   7 106   5   8  20]
- [  0   6   4   0  50   0   2]
- [  5   0   4   3   4  40   2]
- [  8   7   7   9   3  22  84]]
-Node Classification on random seed  5779 -> 0.568
-Confusion Matrix:
- [[ 51   2   4   8   4  16  10]
- [  4 123   3   1   6   3   2]
- [ 21  29 129  46  18  37  48]
- [ 33  11   9  94   2  14   4]
- [  1   8   2   1  59   0   2]
- [ 10   1   3   1   3  42   6]
- [ 11   6   7  17   5  13  70]]
-Node Classification on random seed  5780 -> 0.648
-Confusion Matrix:
- [[ 69   0   7   5   3  21   8]
- [  2 114   4   6   1   1   7]
- [ 21  29 145  40  14  19  36]
- [ 14   1  10 126   3   2  13]
- [  0  11   4   1  59   1   2]
- [  5   1   1   3   0  54   5]
- [  8   4   8   9   1  21  81]]
-Node Classification on random seed  5781 -> 0.604
-Confusion Matrix:
- [[ 59   4   3   3   3   6  12]
- [ 10 137   4   0   3   1   4]
- [ 23  29 141  45  29  22  41]
- [ 13   1  27  81   7  10   7]
- [  4   6   5   1  58   1   4]
- [  5   2   3   0   3  47   3]
- [ 13   4   9   6   7  13  81]]
-Node Classification on random seed  5782 -> 0.614
-Confusion Matrix:
- [[ 71   0   8   3   1  19   5]
- [  8 124   7   2   6   0   0]
- [ 15  15 151  38  42  22  33]
- [ 10   2  29  84   6  17  14]
- [  1   6  14   3  57   0   0]
- [  3   1   4   1   1  51   3]
- [  8   2   7   5   5  20  76]]
-Node Classification on random seed  5783 -> 0.586
-Confusion Matrix:
- [[ 58   2  10   5   4  15  23]
- [  1 132   9   5  10   3   3]
- [ 14   8 145  41  37  21  32]
- [ 11   5  21  86   6  15  19]
- [  0   3   8   4  58   0   4]
- [  0   3   2   8   1  49   6]
- [  6   6   3   7  22  11  58]]
-Node Classification on random seed  5784 -> 0.587
-Confusion Matrix:
- [[ 70   3   8   3   3  10  14]
- [  3 119   3   3   3   3   5]
- [ 30  32 127  38  30  27  49]
- [  5   6  19  85   6   6  23]
- [  4   1   4   1  64   1   3]
- [  4   1   2   4   1  42   7]
- [  5   4  18   2   6  13  80]]
-Node Classification on random seed  5785 -> 0.588
-Confusion Matrix:
- [[ 74   6  11   4   8  16   2]
- [  7 119   4   2  12   6   4]
- [ 24  15 119  42  34  42  38]
- [ 14   4  20  92   4   2   6]
- [  0   6   5   3  63   0   4]
- [  2   3   0   1   1  48   3]
- [ 15   6  11   5  11   9  73]]
-Node Classification on random seed  5786 -> 0.658
-Confusion Matrix:
- [[ 84   1   3   8   3  10   5]
- [  6 130   5   1  10   3   9]
- [ 17  17 154  33  37  13  37]
- [  9   4  13 112   5  12  12]
- [  0   3   5   0  61   0   0]
- [  6   0   2   2   0  49   2]
- [ 12   2   8   8   2  17  68]]
-Node Classification on random seed  5787 -> 0.611
-Confusion Matrix:
- [[ 75   1   4  12   3  10   8]
- [  4 126   8   2  16   1   5]
- [ 25  19 124  37  39  16  48]
- [  9   4  18  96   7   5  10]
- [  1   1   7   1  59   4   7]
- [  2   1   1   1   0  45   5]
- [  8   4   7  11   7  10  86]]
-Node Classification on random seed  5788 -> 0.584
-Confusion Matrix:
- [[ 67   0   7   3   2   8  22]
- [  2 128   2   4   9   2  13]
- [ 19  25 135  43  24  23  48]
- [ 15   1  29  83   5   8  11]
- [  0   4   1   0  64   0   3]
- [  3   1   5   2   1  40   8]
- [ 11   5  10  11  16  10  67]]
-Node Classification on random seed  5789 -> 0.642
-Confusion Matrix:
- [[ 64   3  10   5   0  11  13]
- [  4 148   8   2   6   0   3]
- [ 26  20 151  47  20  10  35]
- [  6   3  14 122   2   0  15]
- [  3   7   4   1  50   1   2]
- [  7   3   3   1   1  36  10]
- [ 14   6  11   4   5  12  71]]
-Node Classification on random seed  5790 -> 0.643
-Confusion Matrix:
- [[ 75   4   3   7   2  11   6]
- [ 14 117   3   3  10   3   0]
- [ 34  14 167  23  18  24  44]
- [  9   3  16 103   6   6  13]
- [  1  10   6   0  58   0   3]
- [  7   1   1   0   0  48   6]
- [ 10   4   8   3   9  12  75]]
-Node Classification on random seed  5791 -> 0.614
-Confusion Matrix:
- [[ 73   3   0   5   5   3  24]
- [  3 132   4   4   4   3   4]
- [ 27  22 125  45  16  24  44]
- [ 20   1   5  98   4   4  13]
- [  2   7   5   0  70   0   3]
- [  9   2   6   4   3  39   7]
- [ 10   7  13   9   4   8  77]]
-Node Classification on random seed  5792 -> 0.644
-Confusion Matrix:
- [[ 77   1   1   4   3  16  10]
- [  7 135   3   0   6   4   6]
- [ 18  24 157  18  27  33  28]
- [ 12   6  12  89  11  13  12]
- [  0   6   2   3  57   1   3]
- [  8   1   1   0   1  52   4]
- [ 13   3   6   2   7  20  77]]
-Node Classification on random seed  5793 -> 0.63
-Confusion Matrix:
- [[ 79   4   3   6   9   3   3]
- [  6 116   5   6   5   1   5]
- [ 42  20 142  29  27   8  40]
- [ 18   2  11 106   9   2   9]
- [  0   8   2   0  59   2   4]
- [ 11   2   2   1   2  45   4]
- [ 28   5   4   8   4  10  83]]
-Node Classification on random seed  5794 -> 0.578
-Confusion Matrix:
- [[ 53   4   9   6   5   8   9]
- [  1 129   6   3  13   3   0]
- [ 24  23 121  40  23  35  41]
- [ 17   7  32  79   7   2  13]
- [  2   8   1   5  74   0   6]
- [  9   4   1   1   1  38   3]
- [  6   2  10  10   3  19  84]]
-Node Classification on random seed  5795 -> 0.638
-Confusion Matrix:
- [[ 75   3   3  11   2  13   5]
- [  2 112   3   4  14   2   9]
- [ 32  10 179  23  23  25  29]
- [ 14   4  13  91   8   7   7]
- [  1   3   5   5  65   2   7]
- [  7   0   0   4   0  51   1]
- [ 15   5   5  15   5  16  65]]
-Node Classification on random seed  5796 -> 0.571
-Confusion Matrix:
- [[ 61   5   9  13   3  12   7]
- [  8 130   9   2   3   0   2]
- [ 17  29 141  53  37  30  18]
- [ 19   6  18  80   6   8  14]
- [  3   5   4   2  61   0   5]
- [  3   2   1   0   1  47   3]
- [  9   5   4   8  24  22  51]]
-Node Classification on random seed  5797 -> 0.605
-Confusion Matrix:
- [[ 75   2   1  10   2  13  19]
- [  2 131   9   1   4   3   9]
- [ 32  17 141  55  13  16  41]
- [ 10   4  13  92   3   6  14]
- [  2   7  10   2  52   1   3]
- [  4   3   3   3   0  42   6]
- [ 15   1   9   7   3  17  72]]
-Node Classification on random seed  5798 -> 0.643
-Confusion Matrix:
- [[ 65   3   1   4   4   8  15]
- [  5 125   6   6  14   2   5]
- [ 18  26 178  26  24   8  34]
- [ 10   5  16 105  12   3   5]
- [  4   6   1   2  58   0   1]
- [  5   1   3   6   1  41  13]
- [ 12   7   6  12   7  10  71]]
-Node Classification on random seed  5799 -> 0.631
-Confusion Matrix:
- [[ 69   2   8   3   1  12  12]
- [  4 125   8   1   6   1   6]
- [ 26  13 160  29  27  32  27]
- [  5   9  23 104   0  10   5]
- [  4   3   8   5  57   1   4]
- [  4   3   5   3   1  39   5]
- [ 15   6  16   6   6   4  77]]
-Node Classification on random seed  5800 -> 0.619
-Confusion Matrix:
- [[ 54   8   9   2   5  19   4]
- [  4 132   7   1   0   2  12]
- [ 19  19 136  38  31  22  44]
- [  7   4  11 108   5   6  12]
- [  0   8   4   2  60   0   6]
- [  5   3   6   0   3  43   5]
- [  9   4   9   2   4  20  86]]
-Node Classification on random seed  5801 -> 0.626
-Confusion Matrix:
- [[ 75   6  10   7   1  10   3]
- [  3 128   4   0  13   4   5]
- [ 21  24 152  20  16  20  45]
- [ 19  10  16 100   1   1  23]
- [  2   5   4   0  62   0   4]
- [  4   2   3   1   1  39   6]
- [  6   4   6  17   7  20  70]]
-Node Classification on random seed  5802 -> 0.643
-Confusion Matrix:
- [[ 75   2  14   4   3   6   7]
- [  5 121   5   0   3   0   9]
- [ 28  25 152  49  19  14  21]
- [ 11  13  20 104   4   3  16]
- [  0   6   3   2  60   2   1]
- [  5   3   4   1   0  45   3]
- [ 10   3  13   7   4   9  86]]
-Node Classification on random seed  5803 -> 0.609
-Confusion Matrix:
- [[ 56   4   6   3   1  17  14]
- [  4 138   5   5   6   2   5]
- [ 19  23 153  32  23  29  45]
- [ 11   3  15  97   2   4  18]
- [  2   9   9   1  41   0   3]
- [  4   1   4   0   1  51   8]
- [  5   4   9   7   9  19  73]]
-Node Classification on random seed  5804 -> 0.647
-Confusion Matrix:
- [[ 74   3   8   3   2   7   9]
- [  3 125   1   1   4   4   8]
- [ 29  30 149  31  25  10  38]
- [  8   2  16  89   3  10  19]
- [  0   7   1   3  65   0   2]
- [ 10   0   3   1   3  45  13]
- [  3   3  13   3   8   6 100]]
-Node Classification on random seed  5805 -> 0.618
-Confusion Matrix:
- [[ 71   4   5  12   5   8   2]
- [  6 123   5   3  10   5   1]
- [ 22  18 142  45  30  29  31]
- [ 15   2  19 102   6   6   9]
- [  2   3   3   1  62   1   3]
- [  1   1   3   3   2  40   0]
- [ 11   6   4  14   9  17  78]]
-Node Classification on random seed  5806 -> 0.648
-Confusion Matrix:
- [[ 79   1   5   2   3  27   1]
- [  4 142   5   1   3   3   0]
- [ 23  33 150  36  11  22  27]
- [  8   6  25  91   4   5  12]
- [  2   7   3   0  64   2   0]
- [  6   3   2   0   2  57   1]
- [ 16   5   6   3   8  19  65]]
-Node Classification on random seed  5807 -> 0.603
-Confusion Matrix:
- [[ 56   6   2   1   2   8  10]
- [  4 116   4   3  12   1   5]
- [ 32  26 169  36  35  16  38]
- [ 10   3  21  79  18   5   7]
- [  0   8   2   2  68   0   1]
- [  4   1   4   2   1  45   7]
- [ 12   3  14   6   8  17  70]]
-Node Classification on random seed  5808 -> 0.634
-Confusion Matrix:
- [[ 65   0   3  11   7  13   8]
- [  9 126   9   3  11   2   1]
- [ 22  26 132  37  26  13  38]
- [  7   1  12 123   6   6  12]
- [  1   3   1   7  68   0   3]
- [  8   0   0   4   1  50   3]
- [ 10   2   1  14   5  20  70]]
-Node Classification on random seed  5809 -> 0.623
-Confusion Matrix:
- [[ 61   1   9  16   6  15   5]
- [  6 119   4   3   2   2   4]
- [ 28  14 176  29  18  16  33]
- [ 16   4  18  93   6  10  11]
- [  0   3   4   1  58   2   2]
- [  4   2   6   0   1  48   5]
- [ 21   1  29   4   3  13  68]]
-Node Classification on random seed  5810 -> 0.621
-Confusion Matrix:
- [[ 81   1   4   9   5   6   9]
- [  6 125   5   0   4   0   5]
- [ 19  12 131  51  43  22  33]
- [  5   4  10 124  10   2  20]
- [  2   4   4   0  58   2   2]
- [  8   0   4   1   0  43   3]
- [ 22   7  10   7   4  14  59]]
-Node Classification on random seed  5811 -> 0.637
-Confusion Matrix:
- [[ 59   2   5   8   3  14  10]
- [  6 138   5   2   3   0  12]
- [ 25   9 142  21  40  30  35]
- [  9   1  11 111   6   9   7]
- [  1   6   4   2  58   0   4]
- [  2   1   0   2   0  56   7]
- [ 14   2   5  13  12  15  73]]
-Node Classification on random seed  5812 -> 0.553
-Confusion Matrix:
- [[ 52  11   4   4   2  15  15]
- [  6 129   6   5   2   5   3]
- [ 28  33 111  30  43  23  38]
- [ 10   4  30  82  13   7  17]
- [  2   7   2   2  54   1   3]
- [  3   2   4   1   2  52   8]
- [  9   3  10   3  19  12  73]]
-Node Classification on random seed  5813 -> 0.623
-Confusion Matrix:
- [[ 87   1   1   5   7   9   5]
- [  4 120   7   1   9   2   6]
- [ 35  24 105  37  53  22  30]
- [ 14   5   6 110   9   3  17]
- [  2   1   0   0  57   1   1]
- [  7   0   2   0   1  47   3]
- [  9   2  10   3  10  13  97]]
-Node Classification on random seed  5814 -> 0.568
-Confusion Matrix:
- [[ 70   1   5   9   3  16  11]
- [  4 128   2   6  10   1   4]
- [ 42  31 106  48  34  22  32]
- [  9   2  19 107  11   4   8]
- [  0  12   2   1  59   2   3]
- [  2   0   0   4   0  45   6]
- [  6   2   7  21   8  22  53]]
-Node Classification on random seed  5815 -> 0.618
-Confusion Matrix:
- [[ 76   2   5   4   4  11   6]
- [  3 137   6   1   8   3   4]
- [ 20  14 134  37  25  19  46]
- [ 17   0   9  95  13   6  16]
- [  3   7   6   0  55   3   7]
- [  7   0   1   0   1  33  11]
- [ 13   4  10  10   9  11  88]]
-Node Classification on random seed  5816 -> 0.624
-Confusion Matrix:
- [[ 67   3   4   4   1  10  14]
- [  3 122   4   2   9   2   6]
- [ 20  10 159  26  26  18  62]
- [  6   5  16 105   5   5  15]
- [  4   5   5   9  58   1   0]
- [ 14   2   1   2   0  46   7]
- [ 16   3   7   3   8  13  67]]
-Node Classification on random seed  5817 -> 0.602
-Confusion Matrix:
- [[ 68   2   1   8   4  13  20]
- [  6 113   8   2  16   5   1]
- [ 23  24 126  42  22  26  35]
- [  8   6  17  95   2   5  14]
- [  2   3   3   5  67   0   1]
- [  6   4   0   2   0  59   5]
- [  6   1   6  13   4  27  74]]
-Node Classification on random seed  5818 -> 0.647
-Confusion Matrix:
- [[ 70   3   0   4   5  20  14]
- [  5 133   1   3   4   0   0]
- [ 14  22 170  27  32  10  39]
- [ 16   1  18  97   8   8  15]
- [  4   8   5   1  50   0   4]
- [  4   3   2   0   4  40   5]
- [  7   2  11   5   6  13  87]]
-Node Classification on random seed  5819 -> 0.62
-Confusion Matrix:
- [[ 79   5   5   6   4  10   2]
- [  5 122  16   2  10   1   8]
- [ 27  12 161  34  19  17  36]
- [ 15   1  15  99   7   7   7]
- [  0   3   2   0  58   4  10]
- [  7   2   3   4   3  40   7]
- [ 10   1  22   5   6  20  61]]
-Node Classification on random seed  5820 -> 0.588
-Confusion Matrix:
- [[ 59   1   3   3   9  23   9]
- [  1 130   3   2   8   6   5]
- [ 16  21 148  32  42  30  33]
- [ 17   6  20  84   9   9  11]
- [  1   5   3   2  63   1   3]
- [  4   2   2   7   1  40   7]
- [  7   1  15   1  12  19  64]]
-Node Classification on random seed  5821 -> 0.598
-Confusion Matrix:
- [[ 75   6   6   3   4  22   8]
- [  4 139   4   3   7   3   1]
- [ 33  23 112  51  26  24  34]
- [ 18   0  11 108   6   5  10]
- [  1   8   3   4  61   0   2]
- [  7   2   5   3   5  28   6]
- [  6   4   4   7   5  18  75]]
-Node Classification on random seed  5822 -> 0.636
-Confusion Matrix:
- [[ 82   1   1   3   4   9   7]
- [  4 116   6   1  13   2   5]
- [ 24  24 154  40  24  28  35]
- [  2   5  12 103   9   7  20]
- [  4   1   4   0  56   3   2]
- [  1   1   1   6   0  37  12]
- [ 10   4   8   4   5  12  88]]
-Node Classification on random seed  5823 -> 0.613
-Confusion Matrix:
- [[ 78   6   2   6   6   8  12]
- [  7 115   5   2  16   0   4]
- [ 27  13 130  35  32  17  59]
- [ 18   3  15 106   8   2  14]
- [  2   2   3   2  66   0   1]
- [  5   0   0   3   1  46   4]
- [ 11   4   7   8   9   8  72]]
-Node Classification on random seed  5824 -> 0.637
-Confusion Matrix:
- [[ 73   2   2   8   0   5  17]
- [  7 133   6   4   7   1   1]
- [ 27  10 141  34  18  17  34]
- [ 13   1  20 112   6   5  11]
- [  7   9   5   2  57   0   2]
- [  4   2   5   4   2  43   4]
- [ 11   5   7  11   6  21  78]]
-Node Classification on random seed  5825 -> 0.595
-Confusion Matrix:
- [[ 75   5   0   3  10   3  10]
- [  4 111  11   3   8   7   1]
- [ 32  22 156  27  21  19  35]
- [ 17  10  17 102   8   6  16]
- [  2  10   2   1  67   2   2]
- [ 14   5   3   1   0  24   9]
- [ 18   7   7   4  12  11  60]]
-Node Classification on random seed  5826 -> 0.602
-Confusion Matrix:
- [[ 68   3   6   8   9   9   2]
- [  5 120   7   4   7   3   9]
- [ 26  15 144  46  25  22  29]
- [ 12   5  10  90  11   1  14]
- [  0  13   3   1  63   1   4]
- [ 10   2   4   2   0  49   1]
- [ 11   4  17  12   8  17  68]]
-Node Classification on random seed  5827 -> 0.596
-Confusion Matrix:
- [[ 68   6   2   4   5   5   9]
- [  4 144  12   0   6   2   3]
- [ 36  24 129  46  27  18  44]
- [  9   2   8 105   1   7  14]
- [  1   9   5   2  51   3   2]
- [  5   0   7   1   2  43   9]
- [ 13   3   8  10   6  24  56]]
-Node Classification on random seed  5828 -> 0.606
-Confusion Matrix:
- [[ 71   2   7   4   3   7   4]
- [ 12 144   3   4   8   2   4]
- [ 32  23 120  47  30  17  46]
- [ 12   1  15  97   4  13  16]
- [  3   5   2   5  51   1   3]
- [  5   0   5   5   2  39   3]
- [ 12   3   7   3   2  12  84]]
-Node Classification on random seed  5829 -> 0.595
-Confusion Matrix:
- [[ 70   1  12   0   3   9   7]
- [  3 122  19   2   4   5   3]
- [ 31  18 127  47  22  31  39]
- [ 13   3  13 110   3   5   8]
- [  3   6   3   1  52   2   2]
- [  7   0   0   3   2  40   7]
- [ 12   4   9  13   9  21  74]]
-Node Classification on random seed  5830 -> 0.621
-Confusion Matrix:
- [[ 68   3  10   1   5  15  14]
- [  5 128  12   4   2   4   5]
- [ 25  20 140  21  31  25  42]
- [ 16   4  10 112   5   4  13]
- [  1   8   3   2  58   0   2]
- [  9   1   3   3   1  33   2]
- [ 13   3   4   3  11  14  82]]
-Node Classification on random seed  5831 -> 0.614
-Confusion Matrix:
- [[ 63   4  11   9   0  11   7]
- [ 10 124   3   1  10   4   2]
- [ 18  25 129  25  30  27  53]
- [  5   4   9 124   3   8  17]
- [  1   8   3   1  61   2   4]
- [  2   2   2   1   2  47  10]
- [ 13   4  13   6   6  10  66]]
-Node Classification on random seed  5832 -> 0.613
-Confusion Matrix:
- [[ 85   2   2   6   0  13   8]
- [  3 122   2   3  12   6   4]
- [ 25  18 133  43  25  26  43]
- [  5   0  18  92   3  16  19]
- [  2   4   4   9  61   0   1]
- [  4   2   1   1   7  41   4]
- [  9   4   5  11   5  12  79]]
-Node Classification on random seed  5833 -> 0.651
-Confusion Matrix:
- [[ 75   0   2   6   4   6  11]
- [  6 133   9   0  15   0   5]
- [ 34  11 171  14  23  19  48]
- [ 12   6  11  96   4   8   7]
- [  3   5   7   1  43   0   2]
- [ 10   1   3   1   0  51   3]
- [ 16   3   8   9   5  11  82]]
-Node Classification on random seed  5834 -> 0.617
-Confusion Matrix:
- [[ 70   4   4   5   7   7  10]
- [  3 146   2   4  15   3   8]
- [ 24  16 135  26  31  19  51]
- [  8   7  11  94  17   5   8]
- [  1   7   2   4  52   0   1]
- [  8   1   1   2   0  43   7]
- [ 17   2   6   6   3  20  77]]
-Node Classification on random seed  5835 -> 0.646
-Confusion Matrix:
- [[ 74   3  10   5   6   5  10]
- [  6 137   2   2   4   5   0]
- [ 24  29 164  29  26  13  25]
- [ 10   5  17 114   5   3   6]
- [  3   9   5   1  62   0   3]
- [ 11   3   2   0   4  34   6]
- [ 10   3  18  13   6   7  61]]
-Node Classification on random seed  5836 -> 0.601
-Confusion Matrix:
- [[ 75   2   6   6  10   8   4]
- [  8 137   4   3   8   2   9]
- [ 20  32 129  32  26  22  41]
- [  7   2   9  95   2  12  21]
- [  0  16   3   1  52   0   5]
- [  9   0   7   1   0  44   5]
- [  8   3   5  11   9  20  69]]
-Node Classification on random seed  5837 -> 0.618
-Confusion Matrix:
- [[ 55   4   3  21   2   8   7]
- [  4 125  10   3   8   1   2]
- [ 32  19 141  28  26  17  38]
- [ 11   4  17 130   5   5  10]
- [  0   5   4   1  55   0   6]
- [  6   0   5   2   5  46   3]
- [ 12   0   8  19   2  19  66]]
-Node Classification on random seed  5838 -> 0.632
-Confusion Matrix:
- [[ 78   5   5   3   4   5  10]
- [  3 138   1   1   9   1   7]
- [ 38  16 126  43  23  16  48]
- [  6   5  13 105   6   3  16]
- [  2   6   1   2  59   0   2]
- [  1   1   2   1   0  44   9]
- [ 11   5  13   9   7   9  82]]
-Node Classification on random seed  5839 -> 0.634
-Confusion Matrix:
- [[ 85   6   3   4   3  11   7]
- [  5 125   5   4  10   1   4]
- [ 17  30 166  17  27  15  51]
- [  8   7  15  82   6   4  25]
- [  0   7   6   2  48   2   1]
- [  0   1   3   0   0  45   5]
- [ 14   5  10   2  11  12  83]]
-Node Classification on random seed  5840 -> 0.609
-Confusion Matrix:
- [[ 71   3   4   4   6  11   5]
- [  9 137  10   3   0   1   4]
- [ 24  18 137  59  18  15  37]
- [ 20   3  22  82   4   7  13]
- [  2   3  11   1  54   2   2]
- [  5   1   2   0   0  50   6]
- [ 22   0  10   2   7  15  78]]
-Node Classification on random seed  5841 -> 0.631
-Confusion Matrix:
- [[ 70   2   2   5   8  11  12]
- [  3 131   4   2   7   5  12]
- [ 27  12 151  25  41  15  43]
- [ 13   1  18  96   2   7   7]
- [  0   7   3   0  64   2   1]
- [  4   0   1   4   2  41   5]
- [ 12   4   7  13  10  10  78]]
-Node Classification on random seed  5842 -> 0.608
-Confusion Matrix:
- [[ 91   4   6   6   2  18   1]
- [ 10 130   5   5   4   5   8]
- [ 25  23 127  33  14  28  34]
- [ 13   5  18  99  12   5  13]
- [  1   4   3   3  57   1   6]
- [  5   1   5   2   2  36   8]
- [ 10   3  15   6   2  18  68]]
-Node Classification on random seed  5843 -> 0.621
-Confusion Matrix:
- [[ 85   0   6   0   2  10  10]
- [  4 125   9   5  10   1   1]
- [ 18  25 129  37  33  38  28]
- [ 21   4  10 112  10   2   5]
- [  1   3   3   0  67   2   3]
- [  4   3   5   3   3  42   3]
- [  9   2  10   2   6  28  61]]
-Node Classification on random seed  5844 -> 0.593
-Confusion Matrix:
- [[ 66   1   6   6   0  18   2]
- [  8 112   9   4   7   2   4]
- [ 19  20 113  64  47  22  28]
- [  9   5  14 118   3   6  10]
- [  4   4   9   3  66   0   2]
- [  8   2   1   3   1  44   4]
- [  9   1  14   9   5  14  74]]
-Node Classification on random seed  5845 -> 0.639
-Confusion Matrix:
- [[ 85   3   1   0   3  15  11]
- [  4 127   3   3   2   1   3]
- [ 25  30 136  51  15  22  41]
- [  3   3  12 113   6  12  10]
- [  1   6   3   2  61   0   4]
- [  5   2   1   3   0  41   7]
- [ 16   5   7   4   8   8  76]]
-Node Classification on random seed  5846 -> 0.614
-Confusion Matrix:
- [[ 75   2  11   2   3  17   3]
- [  5 122   8   0   6   1   4]
- [ 26  19 126  38  27  25  24]
- [ 11   8  15 123   6   6  19]
- [  3   6   4   2  53   1   4]
- [  3   0   5   3   1  46   2]
- [ 13   2  17   9   5  20  69]]
-Node Classification on random seed  5847 -> 0.63
-Confusion Matrix:
- [[ 64   5   3   1   2  16  13]
- [  3 139   4   2   3   7   5]
- [ 26  14 154  32  26  26  44]
- [ 15   8  12  77   3   8  15]
- [  0   5   4   2  72   1   1]
- [  8   1   1   5   0  41   5]
- [  7   7   6   6   3  15  83]]
-Node Classification on random seed  5848 -> 0.629
-Confusion Matrix:
- [[ 83   2   4  11   4   6   5]
- [  4 122  11   2  17   3   4]
- [ 24  16 152  30  26  20  42]
- [ 12   2  11  97   3  12   8]
- [  1   2   6   3  53   1   0]
- [  8   1   6   5   6  63   2]
- [  7   3  11   5   7  18  59]]
-Node Classification on random seed  5849 -> 0.618
-Confusion Matrix:
- [[ 72   1   2   2   2  19   9]
- [  6 119  17   1   3   0   0]
- [ 21  29 149  41  14  28  52]
- [ 10   4   6 110   3   5  13]
- [  1  11   4   3  47   1   3]
- [  7   6   7   0   0  43   2]
- [  3   4   2  10   5  25  78]]
-Node Classification on random seed  5850 -> 0.613
-Confusion Matrix:
- [[ 68   2   5   1   8  13   4]
- [  5 134   4   5  16   0   4]
- [ 28  32 134  43  14  21  29]
- [ 13   7  18  95   4   6  17]
- [  0   6   5   5  67   1   1]
- [  8   2   0   2   0  38   5]
- [ 10   2  15   6   3  17  77]]
-Node Classification on random seed  5851 -> 0.626
-Confusion Matrix:
- [[ 90   1   2   5   4  16   3]
- [  4 130   5   7   8   0   3]
- [ 34  18 131  42  34  15  29]
- [  9   2  15 110   3   8  13]
- [  1   7   7   1  63   0   4]
- [  8   2   3   0   0  46   3]
- [ 11   1   9   8  10  19  56]]
-Node Classification on random seed  5852 -> 0.625
-Confusion Matrix:
- [[ 70   3  10   4   2   8   6]
- [  9 125   5   7   5   3   9]
- [ 38  17 154  33  12  11  52]
- [ 15   0  14 101   3   4  23]
- [  3   7   3   1  49   2   4]
- [  6   1   1   0   1  41   8]
- [ 19   4   4   9   1   8  85]]
-Node Classification on random seed  5853 -> 0.61
-Confusion Matrix:
- [[ 77   4   2   6   2   8   9]
- [  3 140   2   3   1   3   4]
- [ 25  33 119  62  13  16  38]
- [ 17   3   5 106   5   1  22]
- [  2  18   5   1  56   2   2]
- [  9   4   4   6   0  30   3]
- [ 13   3  12   8   3   8  82]]
-Node Classification on random seed  5854 -> 0.585
-Confusion Matrix:
- [[ 79   3   3   5   2  12  16]
- [  3 116   7  10   2   2   4]
- [ 30  27 128  43  21  30  33]
- [ 15   4  11 107   2   6  17]
- [  3  15   4   0  51   1   2]
- [  3   0   1   2   1  36   7]
- [ 14   2   9   5  16  22  68]]
-Node Classification on random seed  5855 -> 0.638
-Confusion Matrix:
- [[ 75   2   2   6   7   9   3]
- [  6 113  20   0   3   3   1]
- [ 33  12 182  20  16  23  28]
- [ 12   0  28 107   9   9   9]
- [  2   6   5   3  55   3   3]
- [ 10   1   1   1   1  46   9]
- [ 12   3  15   5   6  15  60]]
-Node Classification on random seed  5856 -> 0.639
-Confusion Matrix:
- [[ 78   7   9   3   8  11   9]
- [  4 127   6   3  10   0   8]
- [ 28  25 154  14  23  24  29]
- [ 10   4  14  99   4  11  10]
- [  3   5   1   3  57   0   3]
- [  2   1   4   2   2  43   7]
- [ 10   6   5   9   8  16  81]]
-Node Classification on random seed  5857 -> 0.582
-Confusion Matrix:
- [[ 63   4   1   7   2  11  19]
- [  5 136   4   6   2   3   8]
- [ 51  21 109  26  47  20  37]
- [ 17   1  14  99   3   5   7]
- [  1   7   3   3  63   1   4]
- [  6   1   4   2   0  37   5]
- [ 10   0  15  13   7  15  75]]
-Node Classification on random seed  5858 -> 0.647
-Confusion Matrix:
- [[ 63   3   2   8   5  18   7]
- [ 11 131   2   3   8   1   3]
- [ 14  18 159  38  19  20  46]
- [ 13   6  13 113   6   7   2]
- [  0  10   2   0  49   1   6]
- [  8   1   0   1   0  38   3]
- [ 13   4   2  13   3  13  94]]
-Node Classification on random seed  5859 -> 0.601
-Confusion Matrix:
- [[ 63   4   5  11   1   6   7]
- [  4 144   1   7   5   4   8]
- [ 34  23 128  31  19  15  58]
- [ 10   4  19  99  13   6  10]
- [  3   4   2   4  60   1   3]
- [ 10   1   5   1   2  38   4]
- [  8   3  10   9   9  15  69]]
-Node Classification on random seed  5860 -> 0.627
-Confusion Matrix:
- [[ 76   6   3   1   5   7  14]
- [  6 138  10   0  11   1   1]
- [ 30  29 151  24  25  22  29]
- [ 12   2  22  82  13  12   8]
- [  1   9   4   0  57   0   1]
- [  3   0   2   0   0  57   6]
- [ 15   3  13   6   8   9  66]]
-Node Classification on random seed  5861 -> 0.606
-Confusion Matrix:
- [[ 58   9   1   8   5  14  13]
- [  8 125   9   4   7   6   1]
- [ 24  20 140  31  41  16  42]
- [  4   2  12 101   1   2  18]
- [  1   5   3   4  63   0   5]
- [  9   3   3   0   1  50   4]
- [  5   7  10  17   6  13  69]]
-Node Classification on random seed  5862 -> 0.561
-Confusion Matrix:
- [[ 55   1   1   5   8   5  13]
- [ 10 122   7   0   6   0   7]
- [ 35  38 108  16  24  11  63]
- [ 19   4  14 103   5   7  18]
- [  1   6   5   1  59   2   5]
- [ 16   3   4   3   1  41   4]
- [ 36   3   3  15   4  10  73]]
-Node Classification on random seed  5863 -> 0.622
-Confusion Matrix:
- [[ 72   4  16   6   3   4  12]
- [  6 142   8   2   5   0   4]
- [ 19  28 109  25  53  24  32]
- [ 10   2  13 123   7   5  16]
- [  1   6   7   0  59   0   0]
- [  9   0   0   3   2  34   2]
- [ 15   4   8   4  10   3  83]]
-Node Classification on random seed  5864 -> 0.616
-Confusion Matrix:
- [[ 69   2   9   6   4   3   6]
- [  4 127  11   0   7   0   7]
- [ 29  25 143  38  25  20  38]
- [  7   2  13  98   4   3  13]
- [  3   6   5   1  51   0   4]
- [  9   1   6   3   1  50   7]
- [ 12   1  10  15   3  21  78]]
-Node Classification on random seed  5865 -> 0.586
-Confusion Matrix:
- [[ 68   3   6   9   0  14   7]
- [  9 109   6   3   5   9   6]
- [ 24  21 126  26  42  38  27]
- [  3   7  16 104   9   9  13]
- [  3   5   1   0  58   1   5]
- [  8   1   1   3   2  51   4]
- [ 23   1   6  14   7  17  70]]
-Node Classification on random seed  5866 -> 0.581
-Confusion Matrix:
- [[ 64   6   4   3   9   4  17]
- [  6 115   0   2  22   3   7]
- [ 18  29 130  58  27  16  49]
- [  7   2  12 101  10   8  23]
- [  3   1   4   1  66   0   3]
- [ 10   1   1   0   1  35  11]
- [ 16   4   2   6   5   8  70]]
-Node Classification on random seed  5867 -> 0.599
-Confusion Matrix:
- [[ 77   1   1   1   7   7  19]
- [  7 108   6   2   4   1   6]
- [ 37  18 146  37  31  10  35]
- [ 21   3  23  72  15   4  21]
- [  1   7   1   1  65   2   7]
- [ 11   1   1   0   1  47   3]
- [ 14   3   7   6   8  10  84]]
-Node Classification on random seed  5868 -> 0.605
-Confusion Matrix:
- [[ 72   4   5   6   3   6   8]
- [  8 121   7   1   9   6   4]
- [ 16  16 154  45  25  19  45]
- [  9   6  20 100   4   1  12]
- [  2  11   7   3  60   0   2]
- [ 13   0   3   2   0  38   1]
- [  9   0  13  19  19   6  60]]
-Node Classification on random seed  5869 -> 0.641
-Confusion Matrix:
- [[ 62   4   6   3   4  10   6]
- [  6 142   6   2   2   2   2]
- [ 32  21 131  41  23  20  39]
- [ 13   2  10 113   1  11  14]
- [  2  10   6   0  66   0   2]
- [  4   3   0   2   0  53   8]
- [ 13   2   5   6   9   7  74]]
-Node Classification on random seed  5870 -> 0.641
-Confusion Matrix:
- [[ 69   2   5   4   2  11   6]
- [ 10 121   9   3   6   1   2]
- [ 21  18 146  39  28  34  27]
- [ 12   2  14 113   8   3   4]
- [  1   5   4   0  51   6   3]
- [  6   1   6   5   2  46   3]
- [  7   2   7   9   3  18  95]]
-Node Classification on random seed  5871 -> 0.592
-Confusion Matrix:
- [[ 76   1   3   6   1   9  13]
- [  6 110  10   3   9   5   2]
- [ 22  28 114  38  36  27  43]
- [ 10   5  33 109   2   7  11]
- [  3   6   1   0  58   3   2]
- [  6   1   1   2   3  39  10]
- [ 16   2   8   5   4   5  86]]
-Node Classification on random seed  5872 -> 0.667
-Confusion Matrix:
- [[ 75   3   2   5   2  13   8]
- [  3 143   2   6   8   1   9]
- [ 23  15 138  23  27  19  51]
- [  8   4   7 113   3   8  12]
- [  0   2   1   1  68   2   2]
- [  5   0   1   1   0  47   7]
- [ 12   3  11   6   8   9  83]]
-Node Classification on random seed  5873 -> 0.624
-Confusion Matrix:
- [[ 60   8   8   1   5   5  11]
- [ 11 138   3   0   1   3   2]
- [ 35  17 156  40  31  22  28]
- [ 13   2  12 102   0   5  20]
- [  5   6   4   0  58   5   3]
- [  7   1   2   1   2  41   4]
- [ 16   3  14   3   7  10  69]]
-Node Classification on random seed  5874 -> 0.555
-Confusion Matrix:
- [[ 69   2  10   4   9   8   6]
- [  3 124   5   0   5   3   4]
- [ 29  27 103  62  34  25  45]
- [ 15   4   8 102  17  11   9]
- [  2  12   1   2  59   0   2]
- [  6   0   3   5   1  41   2]
- [ 12   8  10   5  11  18  57]]
-Node Classification on random seed  5875 -> 0.587
-Confusion Matrix:
- [[ 61   6   3   3   2  12   5]
- [  2 125   8   7   2   0   7]
- [ 41  19 144  31  30  27  34]
- [ 16   3  22  85   9  19   6]
- [  1   5   4   4  57   3   2]
- [  4   2   0   1   2  47   8]
- [ 21   4  13   7   9   9  68]]
-Node Classification on random seed  5876 -> 0.607
-Confusion Matrix:
- [[ 66   3   3   3   6   9  11]
- [  4 128   3   1  11   7   7]
- [ 32  18 133  48  16  27  34]
- [ 10   8  16 101   3   6  10]
- [  1   5   5   2  57   0   0]
- [  7   0   3   1   0  43   2]
- [ 15   7   4  16   6  23  79]]
-Node Classification on random seed  5877 -> 0.597
-Confusion Matrix:
- [[ 62   5   6   5   3  10  10]
- [  2 130   4   2  14   3   9]
- [ 17  17 131  60  15  30  48]
- [ 11   1  20 103   4   3  14]
- [  2   3   2   5  53   1   3]
- [  8   2   6   0   2  50   4]
- [ 13   3  15   6   5  10  68]]
-Node Classification on random seed  5878 -> 0.614
-Confusion Matrix:
- [[ 64   3   2   2   1  20  12]
- [  1 138   7   4   4   5   4]
- [ 10  16 117  61  21  17  47]
- [ 21   5  10  86   5   7  19]
- [  4   7   3   1  61   1   3]
- [  1   1   1   3   1  54   4]
- [  5   6   9  13   7  12  94]]
-Node Classification on random seed  5879 -> 0.609
-Confusion Matrix:
- [[ 76   2   1   5   3  11   8]
- [  1 118  13   5   2   0   4]
- [ 32  28 116  18  40  17  49]
- [ 14   5  13 103   7   7  14]
- [  0   8   2   0  64   2   8]
- [  3   2   0   0   2  44   6]
- [ 12   2  11   5   6  23  88]]
-Node Classification on random seed  5880 -> 0.591
-Confusion Matrix:
- [[ 67   2   8   4   6  15  11]
- [  4 109  12   6  12   5   0]
- [ 20  28 135  40  20  30  30]
- [ 18   3  15  96   2  10   8]
- [  2  11   3   5  72   0   1]
- [  5   0   0   1   1  42  10]
- [  9   5   4  13  15  15  70]]
-Node Classification on random seed  5881 -> 0.652
-Confusion Matrix:
- [[ 82   2   1   5   8   7   7]
- [  5 124   5   2   4   1   9]
- [ 28  14 152  27  21  17  54]
- [ 14   3  11 110   2   5  12]
- [  1   4   4   0  65   0   3]
- [ 12   3   1   0   2  50   5]
- [ 28   1   8   2   2   8  69]]
-Node Classification on random seed  5882 -> 0.603
-Confusion Matrix:
- [[ 65   1   1   2   2  10  12]
- [  7 112  11   9   6   8   7]
- [ 34  16 139  40  18  18  44]
- [ 14   3  16 100   7   6  22]
- [  1   3   4   0  53   1   4]
- [  6   1   3   1   0  45   4]
- [ 18   4  14   3   5  11  89]]
-Node Classification on random seed  5883 -> 0.618
-Confusion Matrix:
- [[ 61   3   3   4   8  16   6]
- [  5 127   7   7   3   3   1]
- [ 36  18 146  39  16  23  38]
- [ 14   3   9 110   3   3  18]
- [  2   9   6   5  57   2   2]
- [  9   2   1   6   1  43   5]
- [  9   1   7   9   5  15  74]]
-Node Classification on random seed  5884 -> 0.597
-Confusion Matrix:
- [[ 60   4  12   2   4  12  20]
- [  2 112   0   4   6   0   4]
- [ 27  29 131  37  16   9  58]
- [  8   2  18 116   1   5  14]
- [  2  14   5   2  48   2   5]
- [  4   2   5   3   0  43  10]
- [ 15   9  10   5   4  12  87]]
-Node Classification on random seed  5885 -> 0.626
-Confusion Matrix:
- [[ 80   0   8   4   6  13   2]
- [  4 135   9   3   8   3   5]
- [ 25  20 134  39  27  20  36]
- [ 18   4  17  80   4   4  12]
- [  0  13   5   3  68   1   0]
- [  9   3   1   1   2  51   3]
- [  8   3  11   3   7  10  78]]
-Node Classification on random seed  5886 -> 0.609
-Confusion Matrix:
- [[ 75   4   6  11   2   3   5]
- [  5 127   2   2   3   6  15]
- [ 20  21 147  45  24  25  16]
- [  4   2  20  79   9  30  20]
- [  0   4   1   0  75   1   1]
- [  6   4   6   0   0  33   3]
- [ 13   4  18  14   6  10  73]]
-Node Classification on random seed  5887 -> 0.598
-Confusion Matrix:
- [[ 89   6   2   2   5   7   6]
- [  4 131   7   3  12   1   2]
- [ 35  16 107  40  43  16  51]
- [  8   1   8  98  10   4  17]
- [  0   1   0   1  58   0   6]
- [  4   0   1   6   2  53   3]
- [ 17   3  19   8  10  15  62]]
-Node Classification on random seed  5888 -> 0.628
-Confusion Matrix:
- [[ 60   2   3  14   3   9  12]
- [  1 135   4   3   6   1   7]
- [ 24  19 148  27  30  23  40]
- [  6   3  14 117   6   4   8]
- [  0   6   3   0  64   1   5]
- [  9   0   1  11   0  42   6]
- [  6   2  16  15  11  11  62]]
-Node Classification on random seed  5889 -> 0.595
-Confusion Matrix:
- [[ 73   2   9   3   5  10  14]
- [  7 134   8   6   8   4   6]
- [ 27  40 117  24  22  22  49]
- [  6   5  18 101   4  12   9]
- [  0   9   4   0  50   1   2]
- [  2   0   1   1   1  39   9]
- [  7   3  17  14   5   9  81]]
-Node Classification on random seed  5890 -> 0.612
-Confusion Matrix:
- [[ 74   2  12   7   2   4  11]
- [  6 116  11   5   6   3   4]
- [ 13  21 151  48  18  16  44]
- [  5   3  32  86   5  12  25]
- [  1   6   4   0  54   2   0]
- [  3   0   7   1   0  43   8]
- [  4   2   9   8   4  14  88]]
-Node Classification on random seed  5891 -> 0.619
-Confusion Matrix:
- [[ 79   9   2   3   3   7  16]
- [  1 140   1   2   4   4   5]
- [ 21  24 122  45  25  20  41]
- [ 11   6  14  89  11   7  10]
- [  0  12   1   2  59   0   6]
- [  4   1   1   1   1  53  11]
- [ 13   6   8  11   3   8  77]]
-Node Classification on random seed  5892 -> 0.598
-Confusion Matrix:
- [[ 72   7   8   4   6   6  10]
- [  0 118   4   1  15   3   3]
- [ 25  20 119  33  43  22  46]
- [  9   8  23 110   3   1  17]
- [  0   7   3   0  65   1   0]
- [  2   3   2   4   0  45   3]
- [  4   6  10   8  14  18  69]]
-Node Classification on random seed  5893 -> 0.626
-Confusion Matrix:
- [[ 68   5   4   4   2  12  19]
- [  4 126   8   6   7   0   1]
- [ 14  23 147  47  25  22  41]
- [  7   1  16 105   6   2  10]
- [  2   5   9   2  69   0   2]
- [  4   1   3   1   5  39   5]
- [  3   6  11   5   8  16  72]]
-Node Classification on random seed  5894 -> 0.617
-Confusion Matrix:
- [[ 81   3   8   4   3  12   2]
- [ 11 122   8   4  10   5   2]
- [ 21  26 148  32  14  21  54]
- [  5   2  16  96   5   4  16]
- [  2   6   8   4  61   0   3]
- [  0   5   1   3   3  40   4]
- [ 12   1   6   6  18  13  69]]
-Node Classification on random seed  5895 -> 0.617
-Confusion Matrix:
- [[ 55  12  10   4   3  14   7]
- [  4 132   4   3   6   1   8]
- [ 22  26 146  24  20  27  39]
- [ 14   8  18 123   3   4   8]
- [  1   7   1   3  61   3   5]
- [  5   2   3   0   2  37   7]
- [ 22   4   8   5   5  11  63]]
-Node Classification on random seed  5896 -> 0.634
-Confusion Matrix:
- [[ 61   6   7   9   1   3   7]
- [  4 139   2   3   8   2   3]
- [ 25  21 154  11  29  22  47]
- [ 14   3  22  82   7   8  16]
- [  1   8   5   1  71   0   3]
- [  4   1   3   4   3  52   1]
- [  7   3   8  10   8  16  75]]
-Node Classification on random seed  5897 -> 0.621
-Confusion Matrix:
- [[ 75   3   1  10   3   5  12]
- [  9 126   9   3   6   4   3]
- [ 20  27 157  24  23   6  50]
- [ 16   6  18  92   5   7  17]
- [  1   8   3   1  59   1   7]
- [  7   2   1   0   3  37   6]
- [ 14   4   9   2   5  18  75]]
-Node Classification on random seed  5898 -> 0.612
-Confusion Matrix:
- [[ 77   2   2   3   2   3  12]
- [  9 105   8   3  14   4  14]
- [ 27  29 133  23  37  21  39]
- [ 12   4  10 103  12   5  10]
- [  4   5   0   1  70   2   1]
- [  6   3   2   4   0  34   8]
- [ 11   3  14   4   5  10  90]]
-Node Classification on random seed  5899 -> 0.632
-Confusion Matrix:
- [[ 85   2   3   6   5  12   1]
- [ 10 122   3   1   7   5   2]
- [ 33  11 149  22  29  16  51]
- [ 11   7  20 115   2   3   6]
- [  4   7   6   0  54   1   2]
- [  8   2   2   3   0  38   4]
- [ 22   2   6   8  10  13  69]]
-Node Classification on random seed  5900 -> 0.603
-Confusion Matrix:
- [[ 69   0   7   6   4   7   9]
- [  1 131  11   5   3   4   5]
- [ 24  29 133  36  20  24  46]
- [ 11   4  10 104   3   5  18]
- [  1   6   3   3  61   0   0]
- [  2   1   0   6   3  38   5]
- [ 10   6  11   6  11  31  67]]
-Node Classification on random seed  5901 -> 0.591
-Confusion Matrix:
- [[ 80   2   1  11   4   5  15]
- [  4 113   5   4  17   0   4]
- [ 34  13 124  42  39  23  49]
- [ 22   1  14  97   7   5  10]
- [  1   1   5   2  56   3   4]
- [  2   2   0   1   1  36  10]
- [  5   4   7  10   8  12  85]]
-Node Classification on random seed  5902 -> 0.598
-Confusion Matrix:
- [[ 58   3  15   6   3  11  12]
- [  5 123   7   5  16   5   7]
- [ 21  14 127  33  26  18  60]
- [  4   0  31 103   2   8  10]
- [  3   5   4   1  62   0   4]
- [  4   2   5   3   1  47   3]
- [  4   4   8   4  10  15  78]]
-Node Classification on random seed  5903 -> 0.629
-Confusion Matrix:
- [[ 65   4   5   4   2   5  20]
- [  3 128   1   8   6   1  11]
- [ 27  26 142  48  16  16  41]
- [ 15   2  12  86   1   8  22]
- [  1   6   0   4  63   2   2]
- [  2   4   1   1   0  53   4]
- [  4   5  11   4  10   6  92]]
-Node Classification on random seed  5904 -> 0.631
-Confusion Matrix:
- [[ 98   1   3   3   4   6   3]
- [  7 113   4   3  11   9   3]
- [ 23  28 149  29  25  17  39]
- [ 10   7  11 106   5  11  15]
- [  3   6   5   3  51   0   3]
- [  9   0   2   0   2  40   8]
- [ 20   4   6   8   3  10  74]]
-Node Classification on random seed  5905 -> 0.602
-Confusion Matrix:
- [[ 47   3  13   2   6  26   6]
- [  6 131   8   2   6   2   1]
- [ 26  19 149  40  27  34  33]
- [ 11   1  19  91   5   8  12]
- [  1   7   1   3  56   3   2]
- [  4   3   1   2   0  52   3]
- [ 12   2  11   3   8  16  76]]
-Node Classification on random seed  5906 -> 0.611
-Confusion Matrix:
- [[ 73   2   2   5   1  13  21]
- [  5 125   4   0  14   7   1]
- [ 34  37 137  17  24  24  30]
- [ 12   4  11  87   4  10  32]
- [  1   2   5   1  67   3   3]
- [  3   1   0   5   0  43   4]
- [  9   6   4   1  12  15  79]]
-Node Classification on random seed  5907 -> 0.581
-Confusion Matrix:
- [[ 59   9   8   7   1   4  21]
- [  9 112   8   1  11   0   4]
- [ 18  22 144  29  51  25  33]
- [ 10   5  20  96   3   5   7]
- [  0   4   7   2  65   0   3]
- [  8   3   4   0   1  35   7]
- [ 12   5  18   4  19  11  70]]
-Node Classification on random seed  5908 -> 0.638
-Confusion Matrix:
- [[ 72   5   6   5   5   5  10]
- [  2 119   5   7  15   8   2]
- [ 18  12 162  29  21  28  43]
- [ 23   3   7 104   9   2  12]
- [  1   4   3   1  55   1   4]
- [  4   3   1   0   0  45  11]
- [  9   2  11   2   6  17  81]]
-Node Classification on random seed  5909 -> 0.622
-Confusion Matrix:
- [[ 61   2   3   5   7   9  11]
- [  4 114   3   2   8   4  10]
- [ 30  16 132  24  33  27  44]
- [ 12   5   7 112   7   4  15]
- [  2   3   2   2  70   2   3]
- [ 10   0   3   0   1  48   3]
- [ 17   1   7   2  13  15  85]]
-Node Classification on random seed  5910 -> 0.641
-Confusion Matrix:
- [[ 76   2  12   0   1   8  11]
- [  9 117  10   1   7   2   5]
- [ 26  26 158  17  34  17  35]
- [ 11   8  18  95   2   6  12]
- [  2  11   5   2  62   0   0]
- [  2   1   1   3   0  47   6]
- [  9   3   7   1   4  22  86]]
-Node Classification on random seed  5911 -> 0.629
-Confusion Matrix:
- [[ 65   4   2   7   1  16  19]
- [  8 124   5   1   3   2   2]
- [ 17  23 135  43  16  33  38]
- [ 15   0   7 103   9   9  12]
- [  1   7   4   0  65   1   1]
- [  6   0   0   0   1  56   6]
- [  5   9   5  13   3  17  81]]
-Node Classification on random seed  5912 -> 0.63
-Confusion Matrix:
- [[ 52   1   1   7   8   6  15]
- [  5 129  12   0  15   2   0]
- [ 18  12 161  43  26  19  41]
- [  8   3  32  87  10   3   5]
- [  1   2   4   4  63   1   3]
- [  4   0   2   4   1  53   4]
- [ 15   2   5   6   8  12  85]]
-Node Classification on random seed  5913 -> 0.626
-Confusion Matrix:
- [[ 72   2   2   2   3   8   5]
- [  2 137   6   3   5   1   4]
- [ 21  37 123  40  35  31  34]
- [  9   3  13 110   3  11  13]
- [  2   7   5   1  63   0   2]
- [  8   1   0   1   0  50   5]
- [  7   3  12   6   8  13  71]]
-Node Classification on random seed  5914 -> 0.553
-Confusion Matrix:
- [[ 58   8   4   5   9  13  13]
- [  6 131   4   2  10   8   3]
- [ 42  14 129  48  27  23  34]
- [ 13   3  21  89   5  14  11]
- [  1   6   6   0  46   1   7]
- [  6   0   1   4   1  41   1]
- [ 26   5   2   6  11  23  59]]
-Node Classification on random seed  5915 -> 0.597
-Confusion Matrix:
- [[ 81   1   2   6   3   6   8]
- [  4 124   3   3  11   6   4]
- [ 13  22 145  46  45  21  38]
- [  8   1  16  95   8   5  26]
- [  4   7   4   1  54   0   2]
- [  6   1   1   1   2  35   8]
- [ 15   4   2   6  22  11  63]]
-Node Classification on random seed  5916 -> 0.634
-Confusion Matrix:
- [[ 71   3   7   2   6  14  13]
- [  5 118   1   2   5   4   3]
- [ 39  32 152  30  17  12  40]
- [ 16   8   9 124   4   9   6]
- [  0   6   6   0  61   2   1]
- [  5   0   3   0   1  38   8]
- [  9   1   7  12   4  14  70]]
-Node Classification on random seed  5917 -> 0.615
-Confusion Matrix:
- [[ 61   0   2   4   6   9   7]
- [  4 128   8   5   7   2   2]
- [ 15  16 149  46  34  44  20]
- [ 10   3  24 107   4   6  20]
- [  0  10   3   0  53   1   3]
- [  7   2   0   1   0  51   1]
- [ 12   7  11   7   7  15  66]]
-Node Classification on random seed  5918 -> 0.627
-Confusion Matrix:
- [[ 77   1   3   4   3  12   4]
- [  2 132   2   4   3   4   3]
- [ 18  20 111  51  24  21  58]
- [ 17   2  19 114   0   7   9]
- [  2   7   9   1  51   4   1]
- [  2   1   0   0   0  54   7]
- [  9   3   6   5   6  19  88]]
-Node Classification on random seed  5919 -> 0.606
-Confusion Matrix:
- [[ 74   0   2   5   4  16   3]
- [  5 125   5   1   7   6   9]
- [ 22  28 116  44  24  30  35]
- [ 12   1  12  99   2   3  19]
- [  0   6   1   3  63   0   2]
- [  6   3   2   3   0  51   4]
- [ 15  13  10   8   8  15  78]]
-Node Classification on random seed  5920 -> 0.674
-Confusion Matrix:
- [[ 66   3   9  10   3   9   9]
- [  2 132   4   1  11   2   2]
- [ 19  19 175  14  30  21  36]
- [  3   1  18 103   4   8   5]
- [  3   4  11   0  60   0   1]
- [  8   3   2   1   0  48   5]
- [  9   6  11   6   8   5  90]]
-Node Classification on random seed  5921 -> 0.629
-Confusion Matrix:
- [[ 80   2   2   8   6   8  10]
- [  5 138   5   3   3   0   8]
- [ 23  27 149  29  18  17  42]
- [ 15   7  18  98   1   6   9]
- [  0   9   3   0  49   0   5]
- [ 12   3   2   4   0  37   2]
- [  6   3   6  14   8  22  78]]
-Node Classification on random seed  5922 -> 0.61
-Confusion Matrix:
- [[ 73   3   0  10   3  16  10]
- [  3 127   7   1   9   6   1]
- [ 22  18 153  40  30  21  38]
- [ 12  10  12  85  12   5  10]
- [  0   4   4   0  63   5   1]
- [  1   4   3   2   0  40   4]
- [  4   3   9  22  15  10  69]]
-Node Classification on random seed  5923 -> 0.574
-Confusion Matrix:
- [[ 64   2   8  11   3  15   7]
- [  0 121   3  11   8   6   4]
- [ 22  26 108  40  43  29  46]
- [  2   3  19 116  11   5  11]
- [  1   2   5   4  52   3   2]
- [  8   2   2   1   1  39   4]
- [  5   1  17  12   5  16  74]]
-Node Classification on random seed  5924 -> 0.635
-Confusion Matrix:
- [[ 91   1   1   4   0   5  11]
- [  0 119   4   6   7   0   5]
- [ 33  27 141  42  11  22  24]
- [ 17   5   7 121   4   4  13]
- [  3  11   3   2  61   5   1]
- [  4   3   1   6   2  33   6]
- [ 25   4   6   4   9  17  69]]
-Node Classification on random seed  5925 -> 0.592
-Confusion Matrix:
- [[ 82   3  11   4   3   9  13]
- [  4 113  16   8  10   2   3]
- [ 21  30 118  28  32  25  42]
- [  5   2  22  85  16   5  15]
- [  2   2   6   0  70   5   3]
- [  1   2   3   6   1  49   8]
- [  9   2   9   2   7  11  75]]
-Node Classification on random seed  5926 -> 0.639
-Confusion Matrix:
- [[ 73   3   4   1   2  20   8]
- [  8 126   1   9  12   5   1]
- [ 15  19 138  45  25  25  46]
- [  7   5   7 112   7   6  11]
- [  1   3   2   0  66   0   3]
- [  6   0   3   1   0  49   4]
- [  6   2  13   8   6  11  75]]
-Node Classification on random seed  5927 -> 0.63
-Confusion Matrix:
- [[ 63   3   1   4   5  14   6]
- [  3 128   3   3   9   7   5]
- [ 34  17 153  30  24  17  34]
- [ 11   2  18  94   0   5  21]
- [  1   7   1   4  53   1   7]
- [  3   1   2   0   2  63   8]
- [ 11   2   5   7  21  11  76]]
-Node Classification on random seed  5928 -> 0.616
-Confusion Matrix:
- [[ 69   0   6   3   4  13   8]
- [  7 135   5   2   9   3   3]
- [ 33  22 125  37  49  25  27]
- [ 15   2  10 106   9   4   8]
- [  2   9   3   1  60   0   0]
- [  3   0   3   2   4  48   2]
- [ 16   1   4   8   9  13  73]]
-Node Classification on random seed  5929 -> 0.583
-Confusion Matrix:
- [[ 52   1  11   6   1  15  18]
- [  3 133   9   5  10   6   1]
- [ 17  28 146  19  29  29  47]
- [ 10   9  17 101   7  11  13]
- [  2   3   4   3  55   1   5]
- [  6   2   3   1   1  44   4]
- [ 17   4   8   2  10  19  52]]
-Node Classification on random seed  5930 -> 0.654
-Confusion Matrix:
- [[ 66   1   7   2   3  18  12]
- [  5 119   7   3   9   5   1]
- [ 14  16 172  23  37  22  32]
- [ 13   0  14 112   5   6  11]
- [  1   2   7   0  66   3   2]
- [  8   1   2   4   0  44   3]
- [  3   7   7   4   7  19  75]]
-Node Classification on random seed  5931 -> 0.612
-Confusion Matrix:
- [[ 57   3   8   2   3  13  15]
- [  8 138   5   2   6   2   4]
- [ 19  24 140  19  29  32  50]
- [  8   3  25  86   0   7  26]
- [  0   3   2   2  70   1   2]
- [  3   2   1   2   0  46   8]
- [ 10   7  10   6   1  15  75]]
-Node Classification on random seed  5932 -> 0.615
-Confusion Matrix:
- [[ 59   4   6   9   6   7  13]
- [  9 128  17   3   4   2   3]
- [ 26  10 156  31  24  23  44]
- [ 20   3  12  93   6   8  10]
- [  1   7   3   1  62   0   1]
- [  3   2   2   7   2  40   4]
- [ 17   6   9   6   2  12  77]]
-Node Classification on random seed  5933 -> 0.593
-Confusion Matrix:
- [[ 56   3   8   2   3  19  17]
- [  1 127   5   4  12   4   7]
- [ 20  17 139  53  20  16  38]
- [ 14   2  21  95   3   6  18]
- [  4   6   7   4  58   0   3]
- [  1   1   0   2   0  49   4]
- [  8   3  11   8   5  27  69]]
-Node Classification on random seed  5934 -> 0.585
-Confusion Matrix:
- [[ 81   2   5   6   5   8  12]
- [  9 113   8   0   7   6   2]
- [ 24  26 110  27  46  35  55]
- [ 11   2  14  87   6   6  22]
- [  2  10   2   0  57   2   0]
- [  7   0   5   1   0  50   4]
- [ 12   3   9   2   4   8  87]]
-Node Classification on random seed  5935 -> 0.616
-Confusion Matrix:
- [[ 71   6   3   6   2  12   4]
- [  1 128   3   1  13   3   6]
- [ 37  15 129  33  38  20  50]
- [  2  11  10 108   5   5  11]
- [  2   4   4   3  65   0   6]
- [  9   4   1   1   3  38   9]
- [  6   2   9   9   6   9  77]]
-Node Classification on random seed  5936 -> 0.604
-Confusion Matrix:
- [[ 58   5   6   7   4  11  16]
- [  3 124   5   0  15   5   1]
- [ 24  40 120  38  27  18  40]
- [ 11   1  20 111   2   6  16]
- [  3   6   4   6  64   3   3]
- [  3   1   3   0   1  47   3]
- [  9   1  11   6   2  10  80]]
-Node Classification on random seed  5937 -> 0.614
-Confusion Matrix:
- [[ 63   5   8   7   1  13   7]
- [  3 118   2   9   6   2   5]
- [ 24  23 137  44  36  20  33]
- [  4   3  14 103   7   6   7]
- [  2   3   1   5  57   3   1]
- [  7   0   6   4   2  47   7]
- [ 11   4   6   7  15  13  89]]
-Node Classification on random seed  5938 -> 0.63
-Confusion Matrix:
- [[ 74   0   4   2   6  14  13]
- [  5 129   5   2   9   0   1]
- [ 19  19 127  36  41  21  46]
- [ 10   3  11 110   3   4  13]
- [  0   6   3   0  65   1   1]
- [  7   3   3   4   0  53   3]
- [  9   4  10   6   7  16  72]]
-Node Classification on random seed  5939 -> 0.592
-Confusion Matrix:
- [[ 70   2  11   4   6  13  11]
- [  9 119   5   1  18   2   6]
- [ 22  24 118  19  41  26  38]
- [  7   1  23  90  16   5  10]
- [  2   5   4   4  59   0   6]
- [  7   2   0   2   0  50   8]
- [  7   5   4   6  17   9  86]]
-Node Classification on random seed  5940 -> 0.643
-Confusion Matrix:
- [[ 70   2  10   2   1   8   8]
- [  3 142   6   3   3   3   4]
- [ 23  26 169  20  17  27  33]
- [ 11   8  15  97  11   7  15]
- [  1   8   4   0  50   1   2]
- [ 10   1   4   2   2  35   3]
- [  3   5  13   3   5  24  80]]
-Node Classification on random seed  5941 -> 0.596
-Confusion Matrix:
- [[ 69   1   1   8   3   2  10]
- [  8 124   5   6   5   2   2]
- [ 35  19 137  50  17  35  39]
- [ 14   8  14  68   3  13  32]
- [  3   6   5   1  56   1   1]
- [  7   2   1   1   1  50   3]
- [  7   1   5   8   7  12  92]]
-Node Classification on random seed  5942 -> 0.622
-Confusion Matrix:
- [[ 76   1   2   3   2  15  12]
- [  3 124   6   4   5   1   8]
- [ 22  11 143  49  39  22  41]
- [ 11   6  15 112   7   1   8]
- [  3   6   3   2  59   0   2]
- [  3   2   4   0   0  40   5]
- [  9   6   7  14   3  15  68]]
-Node Classification on random seed  5943 -> 0.622
-Confusion Matrix:
- [[ 83   2   9   5   7   9   6]
- [  2 131   2   0  10   3   4]
- [ 22  24 137  39  24  24  35]
- [ 22   2  14 103   5   3  15]
- [  0   5   6   1  53   2   1]
- [  6   1   2   1   2  46   1]
- [ 15   3  14   3   7  20  69]]
-Node Classification on random seed  5944 -> 0.552
-Confusion Matrix:
- [[ 69   2   3   7   1  12  19]
- [  3 130   3   4   6   2   2]
- [ 31  24  97  78  19  34  45]
- [ 26   1   7 109   6   5   3]
- [  3   4   4   5  57   0   5]
- [  4   4   6   3   0  36   3]
- [ 14   5   8   4   6  27  54]]
-Node Classification on random seed  5945 -> 0.631
-Confusion Matrix:
- [[ 77   6   4   1   2   4   1]
- [  4 130   5   3   7   4   4]
- [ 26  18 161  45  27  21  32]
- [ 12   2  15 107   4   9  15]
- [  0  13   6   7  57   2   1]
- [  4   1   5   1   0  42   1]
- [ 17   5  12   8   6   9  57]]
-Node Classification on random seed  5946 -> 0.653
-Confusion Matrix:
- [[ 61   4  14   3   5   4  11]
- [  0 123   1   6   9   2   5]
- [ 22  20 162  30  38  18  36]
- [  9   7   5 126   7   3  15]
- [  1   9   2   0  64   0   0]
- [  6   1   2   1   1  48   2]
- [ 10   3  12   7   7   9  69]]
-Node Classification on random seed  5947 -> 0.622
-Confusion Matrix:
- [[ 74   1   2   3   3   8   4]
- [  2 152   3   2   0   4   0]
- [ 36  34  96  44  20  25  50]
- [ 19   1   4 114   4   3  12]
- [  0   6   4   0  66   2   1]
- [  6   2   0   3   0  57   3]
- [ 24   8   6  12   4  13  63]]
-Node Classification on random seed  5948 -> 0.613
-Confusion Matrix:
- [[ 62   6   6   5   3   8  15]
- [  1 118  11   1   8   0   5]
- [ 26  27 141  30  47  23  27]
- [  9   3  14 108   8   9  14]
- [  2   4   2   2  61   1   1]
- [  1   2   2   1   0  44   7]
- [ 10   2  14   4   6  20  79]]
-Node Classification on random seed  5949 -> 0.609
-Confusion Matrix:
- [[ 76   0   4   3   4   8   7]
- [  1 133   7   5   6   4   7]
- [ 30  30 134  23  35  25  46]
- [ 11   2  26  93   3   7   4]
- [  4   3   3   0  56   0   1]
- [  2   1   8   2   0  36  17]
- [ 14   4  12   4   9   9  81]]
-Node Classification on random seed  5950 -> 0.589
-Confusion Matrix:
- [[ 78   1   0   3   4  17   2]
- [  4 127   2   0  11   7   1]
- [ 34  23 128  31  31  30  33]
- [ 12   3  22 104  14   8   6]
- [  1   6   3   0  61   4   4]
- [ 13   3   1   2   1  34   7]
- [ 25   2   1   9   4  26  57]]
-Node Classification on random seed  5951 -> 0.633
-Confusion Matrix:
- [[ 82   3   3   2   3  13   7]
- [  4 150   3   4   1   2   4]
- [ 29  22 134  37  17  25  32]
- [ 16   8  21  81   4   6  21]
- [  1   6   7   1  57   0   0]
- [  3   0   0   4   2  37  13]
- [  6   3   9   7   5  13  92]]
-Node Classification on random seed  5952 -> 0.597
-Confusion Matrix:
- [[ 76   2   2   5   3  10  11]
- [  5 122   7   2   6   2   6]
- [ 37  21 156  59  20  14  27]
- [  8   6  19  86   4   3  14]
- [  1   6   2   2  69   1   2]
- [  6   0   6   5   1  31   7]
- [  8   2  17   2  14  28  57]]
-Node Classification on random seed  5953 -> 0.61
-Confusion Matrix:
- [[ 78   2   4   5   5  11  13]
- [  3 124   8   2   6   2   3]
- [ 36  26 141  26  18  12  53]
- [ 16   4  19  83  11   8   5]
- [  0   5   5   1  54   2   3]
- [  0   0   3   1   2  44   9]
- [  8   6  12   7   9  19  86]]
-Node Classification on random seed  5954 -> 0.621
-Confusion Matrix:
- [[ 65   1   3  11   5  15   8]
- [  3 124   6   2  11   1   3]
- [ 21  24 154  46  10  19  36]
- [ 10   1  12 115   1  10   8]
- [  0   4   3   4  62   2   1]
- [  9   3  10   1   2  41   6]
- [  3   3  10  15   3  33  60]]
-Node Classification on random seed  5955 -> 0.656
-Confusion Matrix:
- [[ 75   0   7   1   1   9   3]
- [  4 140   7   6   6   3   1]
- [ 17  27 142  37  21  21  41]
- [ 10   3   9 115   4   9  17]
- [  0   8   8   0  54   0   4]
- [  6   0   1   1   1  56   3]
- [  4   5  13   3   6  17  74]]
-Node Classification on random seed  5956 -> 0.639
-Confusion Matrix:
- [[ 75   4   8   4   2  15   5]
- [  9 131   8   4   1   5   3]
- [ 12  31 161  30  19  14  39]
- [ 10   5  16  95   8   5  14]
- [  1   8   3   0  51   1   4]
- [  8   1   2   7   0  49   4]
- [  9   4  10   2  14  12  77]]
-Node Classification on random seed  5957 -> 0.636
-Confusion Matrix:
- [[ 79   3   6   2   5   7  12]
- [  2 125   7   0  11   4   8]
- [ 22  17 139  17  37  41  29]
- [ 11   4  17 103   2   6  14]
- [  1   2   2   3  56   1   4]
- [  2   3   1   3   3  55   4]
- [ 14   5   2   3   8  19  79]]
-Node Classification on random seed  5958 -> 0.582
-Confusion Matrix:
- [[ 76   3   6   2   9   6  17]
- [  3 124   4   0   5   4  10]
- [ 24  30 121  35  55  13  45]
- [  6  12  27  85   9   8   4]
- [  0  11   2   1  64   0   1]
- [  7   3   5   2   2  38   3]
- [  7   0   7  11   8  11  74]]
-Node Classification on random seed  5959 -> 0.623
-Confusion Matrix:
- [[ 77   4   6   1   3  11  11]
- [  7 125   6   0  17   2   6]
- [ 25  15 144  29  34  21  31]
- [ 12   2  23 107   4   6  11]
- [  0   4   2   3  71   0   1]
- [  3   0   2   0   3  46   6]
- [ 18   0  12   6  18  12  53]]
-Node Classification on random seed  5960 -> 0.626
-Confusion Matrix:
- [[ 84   2   3   4   5   8   9]
- [  6 123   5   3   3   1   0]
- [ 32  22 111  66  26  26  28]
- [ 15   5   6 105   3   3   7]
- [  0   6   4   2  61   1   3]
- [  7   0   2   2   0  56   1]
- [  9   7  17   7   7  11  86]]
-Node Classification on random seed  5961 -> 0.616
-Confusion Matrix:
- [[ 62   5   6   2   1  17  14]
- [  5 133   3   3   8   5   3]
- [ 13  31 136  36  36  16  38]
- [  5   3  22 105   8  13   9]
- [  0   4   1   3  55   1   1]
- [  4   1   6   1   2  47   1]
- [ 11   5  13   6   8  14  78]]
-Node Classification on random seed  5962 -> 0.593
-Confusion Matrix:
- [[ 67   2   4   4   6  14  14]
- [  8 111   6   6   8   4  13]
- [ 22  32 112  48  35  26  28]
- [  9   2  20 107   3   6  13]
- [  0   3   2   2  74   5   0]
- [  7   0   1   1   0  49   6]
- [  5   6   5   4   9  18  73]]
-Node Classification on random seed  5963 -> 0.612
-Confusion Matrix:
- [[ 77   2   3   2   2  14  19]
- [  5 125   3   4   4   4  10]
- [ 18  26 134  46  31  21  29]
- [ 26   6  17  85   1   6  16]
- [  2   5   8   1  56   2   1]
- [  6   3   7   1   0  46   4]
- [  5   5   7   2   6   8  89]]
-Node Classification on random seed  5964 -> 0.57
-Confusion Matrix:
- [[ 54   3   5  14   5   8  17]
- [  8 135   8   3   7   5   1]
- [ 22  24 126  48  19  51  36]
- [ 16   3   9 102  10   5  13]
- [  0   7   5   1  65   0   0]
- [  4   1   3   4   0  37   5]
- [ 11  10   9  12   6  12  51]]
-Node Classification on random seed  5965 -> 0.609
-Confusion Matrix:
- [[ 76   4   3   2   4  14  13]
- [ 11 117   3   3   7   1   3]
- [ 12  15 140  31  56  29  50]
- [ 13   6   9  90   3   5  15]
- [  1   8   2   1  57   0   3]
- [  6   2   0   2   1  48   2]
- [  2   3   9   7  13  17  81]]
-Node Classification on random seed  5966 -> 0.613
-Confusion Matrix:
- [[ 62   3   1  10   4  17   6]
- [  5 114  10   0  14   8   3]
- [ 33  27 129  42  17  22  28]
- [  8   4  14 128   2   9  15]
- [  2   5   8   1  63   2   2]
- [  3   4   3   0   0  37   4]
- [ 11   3   7   3   8  19  80]]
-Node Classification on random seed  5967 -> 0.62
-Confusion Matrix:
- [[ 64   3   2   7   4  10  11]
- [  3 125   2   5   2   4   4]
- [ 23  31 132  36  24  21  31]
- [ 17  13  12 111   5   4  16]
- [  1   6   5   0  58   2   1]
- [  6   1   1   3   3  48   7]
- [ 13  11   7   2  12   9  82]]
-Node Classification on random seed  5968 -> 0.658
-Confusion Matrix:
- [[ 81   0   1   4   5  10   8]
- [  1 127   5   4   4   0   7]
- [ 24  22 174  16  22  17  38]
- [  6   7  32  92   4   4  17]
- [  0   8   1   1  60   2   1]
- [  4   1   3   0   0  50   6]
- [  7   6  12  14   3  15  74]]
-Node Classification on random seed  5969 -> 0.643
-Confusion Matrix:
- [[ 76   1   1   5   2  11   5]
- [  3 119   4   2   9   2   3]
- [ 35  27 144  38  32  16  25]
- [  8   4  11 100   3   3  17]
- [  0   4   1   4  76   0   4]
- [  3   2   3   1   1  46   7]
- [ 12   3  13   8  17   7  82]]
-Node Classification on random seed  5970 -> 0.602
-Confusion Matrix:
- [[ 63   2   4   5   1  14  10]
- [  5 105  12   0  12   5   6]
- [ 13  15 148  43  48  20  36]
- [  9   4  22  84  10  10  22]
- [  0   2   4   0  67   1   1]
- [  5   2   1   1   2  47   4]
- [  6   2   4  10   7  18  88]]
-Node Classification on random seed  5971 -> 0.597
-Confusion Matrix:
- [[ 71   0   4   6   2   6   8]
- [  2 126   5   3   8   4   7]
- [ 39  29 127  21  35  33  43]
- [ 16   2  11  99  10  10  19]
- [  2   4   2   1  62   0   1]
- [  1   0   5   0   0  37   9]
- [  3   4  29   3   8   8  75]]
-Node Classification on random seed  5972 -> 0.645
-Confusion Matrix:
- [[ 60   0   4   8   5  16   6]
- [  7 130   4   3   9   4   2]
- [ 15  16 158  37  32  18  42]
- [  5   9  11 122   3   5  12]
- [  2   3   5   3  54   5   0]
- [  3   2   2   1   1  41   6]
- [  7   3  14   6   9  10  80]]
-Node Classification on random seed  5973 -> 0.604
-Confusion Matrix:
- [[ 71   7   8   2   0   8   7]
- [  4 128   7   3   7   1   2]
- [ 18  26 147  54  37  23  31]
- [ 12   5  14 108   7   6  10]
- [  1   8   3   4  54   0   2]
- [  3   4   0   2   3  41   4]
- [ 12   6   6  20   5  14  55]]
-Node Classification on random seed  5974 -> 0.592
-Confusion Matrix:
- [[ 63   2   4  10   4  17   6]
- [  3 106   1   2  12   3   7]
- [ 28  27 129  31  16  18  62]
- [ 16   5  20 105   4   1   5]
- [  1   6   3   6  70   0   4]
- [  6   2   3   0   0  38   4]
- [  4   7  15  20   3  20  81]]
-Node Classification on random seed  5975 -> 0.614
-Confusion Matrix:
- [[ 75   1   9   3   1   9   8]
- [  6 111   9   1   3   3  10]
- [ 14  15 148  28  60  12  40]
- [ 12  11  16 111   6   8  10]
- [  6   4   4   3  65   1   1]
- [  3   4   3   0   1  44   3]
- [  8   1  22   7   8  12  60]]
-Node Classification on random seed  5976 -> 0.614
-Confusion Matrix:
- [[ 73   3   4   5   3  18   7]
- [  1 118   5   2   6   1   2]
- [ 27  16 149  29  33  33  37]
- [  4   8  22  98  10   4  16]
- [  1   5   3   1  61   1   1]
- [  4   1   2   5   1  37   9]
- [ 14   4  11  13   2  12  78]]
-Node Classification on random seed  5977 -> 0.643
-Confusion Matrix:
- [[ 78   1   2   4   1  22   9]
- [  2 132   5   1   6   1   1]
- [  9  36 144  32  20  25  36]
- [ 15   7  14 103   9   4  13]
- [  2   4   1   0  60   3   2]
- [  7   1   7   0   0  43   5]
- [  8   6  12   1   6  17  83]]
-Node Classification on random seed  5978 -> 0.592
-Confusion Matrix:
- [[ 48   1   8   5   6  21   9]
- [  3 127   1   3  15   2   3]
- [ 17  19 126  37  52  16  40]
- [  8   1  11 122   6   6   5]
- [  0  11   1   0  63   0   3]
- [  5   2   4   3   0  45   7]
- [ 12   3   6  13  14  29  61]]
-Node Classification on random seed  5979 -> 0.596
-Confusion Matrix:
- [[ 66   2   2   6   3  19  12]
- [  6 137   5   1   5   2   9]
- [ 30  20 124  41  32  20  26]
- [ 22   4  10  96   8   4   9]
- [  2   9   3   3  54   1   7]
- [ 10   2   3   3   1  37   4]
- [  9   2   2  12   8  25  82]]
-Node Classification on random seed  5980 -> 0.618
-Confusion Matrix:
- [[ 77   3   7   3   3   3  15]
- [  8 130   2   0   8   7   2]
- [ 32  27 139  25  19  24  27]
- [ 27   6  10  94   4   3  20]
- [  0   9   3   0  67   0   2]
- [  6   2   5   0   2  36  11]
- [ 27   4   8   6   8   4  75]]
-Node Classification on random seed  5981 -> 0.641
-Confusion Matrix:
- [[ 62   6   7   5   3   7  17]
- [  4 137   5   3  10   3   3]
- [ 25  30 151  27  17  14  38]
- [ 14   2  14 111   5   2  16]
- [  1   3   3   2  67   0   1]
- [  7   2   1   2   0  36   6]
- [ 15   1   9  13   2  14  77]]
-Node Classification on random seed  5982 -> 0.645
-Confusion Matrix:
- [[ 77   0   2   5   2  11  13]
- [  3 125   3   1   8   0   0]
- [ 22  19 151  32  15  15  57]
- [ 15   4  13 114   2   6  15]
- [  0   9   3   1  57   0   1]
- [  6   1   2   2   0  44   7]
- [ 11   6  10  18   7   8  77]]
-Node Classification on random seed  5983 -> 0.63
-Confusion Matrix:
- [[ 68   2   8   6   4   5   5]
- [  4 120   4   8   3   0   8]
- [ 27  22 146  43  30  22  31]
- [ 11   3  16 131   0   2  12]
- [  0   5   6   3  51   0   1]
- [ 12   0   2   3   1  38   3]
- [ 14   2   6  22   4  10  76]]
-Node Classification on random seed  5984 -> 0.617
-Confusion Matrix:
- [[ 78   0   6   6   3   7   4]
- [  7 128   8   1   6   0   8]
- [ 15  29 149  55  29  12  36]
- [  7   5  11 104  13   5  13]
- [  4   6  11   0  56   1   1]
- [  2   0   2   1   3  36   5]
- [ 10   6  11   7  12  15  66]]
-Node Classification on random seed  5985 -> 0.608
-Confusion Matrix:
- [[ 85   1   2   4   2  16   5]
- [  1 121  13   2  12   6   2]
- [ 32  15 143  26  15  29  47]
- [  7   6  15 104   4   5  14]
- [  0   8   9   1  48   2   1]
- [  2   2   3   4   1  48   0]
- [ 14   7   6  12  18  21  59]]
-Node Classification on random seed  5986 -> 0.633
-Confusion Matrix:
- [[ 73   3   2   9   2  11   8]
- [  2 139   4   6   7   2   2]
- [ 22  25 137  23  44  13  41]
- [ 15   8  16  94   5   9   9]
- [  1   2   5   2  64   3   2]
- [  1   1   4   5   0  48   4]
- [  3   2   9   3  12  20  78]]
-Node Classification on random seed  5987 -> 0.63
-Confusion Matrix:
- [[ 82   2   4   1   3   9  16]
- [  5 128   7   1   4   0   3]
- [ 22  16 139  41  24  19  45]
- [ 10   4  27 105   2   6  18]
- [  1   8   4   1  54   2   1]
- [  7   1   0   0   0  50   4]
- [ 11   4   7   7   6  17  72]]
-Node Classification on random seed  5988 -> 0.623
-Confusion Matrix:
- [[ 60   3   2   2   6  18  10]
- [ 14 138   5   1   6   0   5]
- [ 36  18 137  19  24  22  51]
- [ 20   4  14  92   2   5   5]
- [  2   8   3   0  66   3   2]
- [ 10   0   0   1   0  46   7]
- [ 11   3   7   4   6  18  84]]
-Node Classification on random seed  5989 -> 0.624
-Confusion Matrix:
- [[ 74   3   3   5   8  26   6]
- [  1 117   8   1   5   3   3]
- [ 17  18 144  22  45  23  43]
- [ 15   2  13  95  14   5  11]
- [  3  12   4   1  67   0   0]
- [  4   2   2   5   2  42   2]
- [  6   4   1   6   7  15  85]]
-Node Classification on random seed  5990 -> 0.634
-Confusion Matrix:
- [[ 60   0   8   9   4  14   5]
- [  7 138   9   0  12   2   0]
- [ 29  23 156  24  39  18  18]
- [ 16   5  12  92   4   5  13]
- [  1   9   7   0  55   2   4]
- [  5   0   0   3   2  47   1]
- [ 11   3   8   9   6  19  86]]
-Node Classification on random seed  5991 -> 0.591
-Confusion Matrix:
- [[ 73   4  11   2   5   9   5]
- [ 11 121   6   2   7   4   9]
- [ 25  18 124  39  30  32  36]
- [ 10   2  21  93   3  10  12]
- [  1   8   5   2  60   2   1]
- [  8   4   3   0   2  45   7]
- [  9   4   7  13   6  14  75]]
-Node Classification on random seed  5992 -> 0.619
-Confusion Matrix:
- [[ 70   1   3   5   7   6  10]
- [  2 130   7   1  13   2   3]
- [ 24  21 170  15  33  15  37]
- [ 21   2  21  79   3  15  14]
- [  1   4   8   2  67   0   0]
- [  6   1   9   0   2  41   2]
- [ 21   5   6  10   7  16  62]]
-Node Classification on random seed  5993 -> 0.597
-Confusion Matrix:
- [[ 68   4   9   6   5   8   5]
- [  1 124   6   0  13   1   7]
- [ 24  37 130  47  27  24  30]
- [ 14   3  19 105   5  11   6]
- [  2   6   2   1  61   0   2]
- [  5   0   1   0   0  48   8]
- [ 13   3   1  12  10  25  61]]
-Node Classification on random seed  5994 -> 0.606
-Confusion Matrix:
- [[ 51   5  27   5   6  13   4]
- [  6 136   2   3   4   8   8]
- [ 19  16 129  37  18  26  53]
- [  7   6  12 110   2   6  16]
- [  2   7   2   2  64   1   5]
- [  4   0   2   4   1  39   6]
- [ 14   2   7   1  12  13  77]]
-Node Classification on random seed  5995 -> 0.61
-Confusion Matrix:
- [[ 64   0   9   8   1   8  12]
- [ 10 135   3   1   9   3   6]
- [ 14  16 127  38  40  20  49]
- [ 15   1   4 100  12   5   8]
- [  1   4   7   3  60   3   1]
- [  5   0   3   2   4  48   7]
- [ 17   3   7  11   8  12  76]]
-Node Classification on random seed  5996 -> 0.647
-Confusion Matrix:
- [[ 62   9   5   6   6   4   9]
- [  4 114   3   3   7   3   6]
- [ 16  26 162  30  22  11  46]
- [ 13   3  17 114   5   6   9]
- [  3   4   5   0  63   1   3]
- [  9   0   3   1   1  50   4]
- [ 12   1  15   7   6   9  82]]
-Node Classification on random seed  5997 -> 0.608
-Confusion Matrix:
- [[ 73   6   0   6   2   6  17]
- [  6 146   3   7   2   1   4]
- [ 14  18 130  24  17  36  61]
- [  6   7  21 106   7   5   9]
- [  1  13   7   1  46   2   3]
- [  6   3   0   3   1  44   6]
- [ 22   6   6   7   9  11  63]]
-Node Classification on random seed  5998 -> 0.617
-Confusion Matrix:
- [[ 59   5   8   5   2  10  27]
- [  4 140   9   0   1   2   4]
- [ 28  16 155  27  28  16  33]
- [ 13   8  14 102   2   6  13]
- [  1   8   5   3  49   0   5]
- [  6   0   9   4   1  39   9]
- [  9   3   9   9   6  15  73]]
-Node Classification on random seed  5999 -> 0.642
-Confusion Matrix:
- [[ 72   2   6   3   0   5   9]
- [  2 118   9   1   5   7   1]
- [ 28  15 179  40  17  19  37]
- [  8   3  23 113   3   4  13]
- [  3   9   2   3  55   0   1]
- [ 12   2   2   2   0  43   1]
- [ 19   1  11   5   5  20  62]]
-Node Classification on random seed  6000 -> 0.621
-Confusion Matrix:
- [[ 72   4   2   3   4   8  14]
- [  1 129   4   1   4   4   4]
- [ 31  19 124  49  16  23  58]
- [  7   7  17 105   5   9   7]
- [  4   9   2   0  59   1   3]
- [  9   2   2   1   0  46   3]
- [  9   5   4   4   9  11  86]]
-Node Classification on random seed  6001 -> 0.635
-Confusion Matrix:
- [[ 71   3   3  12  11  13   3]
- [  6 127   8   1   4   7   3]
- [ 22  11 146  23  17  20  38]
- [ 16   6  19 118  18   6  10]
- [  1   7   5   2  57   1   1]
- [  2   2   1   3   1  50   5]
- [ 14   8   7   7   4  14  66]]
-Node Classification on random seed  6002 -> 0.582
-Confusion Matrix:
- [[ 83   1   1   6   5   7  11]
- [  7 120  11   1   6   3   9]
- [ 27  39 102  42  29  19  45]
- [ 15   5  12  92   9   6  11]
- [  2  11   1   0  68   1   1]
- [  9   3   0   0   4  45   2]
- [ 19   4   7   6   8  13  72]]
-Node Classification on random seed  6003 -> 0.627
-Confusion Matrix:
- [[ 51   4   5  14   4  14  10]
- [  3 124   7   1  14   7   6]
- [ 14  22 160  27  30  27  20]
- [  3   5  20 106  10   5   6]
- [  1   7   5   1  71   0   1]
- [  6   1   3   4   1  48   4]
- [  8  10   9   7   9  18  67]]
-Node Classification on random seed  6004 -> 0.569
-Confusion Matrix:
- [[ 61   4   9   7   5  11   6]
- [  8 136   4   2   4   0   2]
- [ 35  30 122  49  31  17  51]
- [ 23   7  11  94   8   1   8]
- [  2  16   1   0  43   1   3]
- [  5   3  14   1   0  38   4]
- [ 21   1  11   6   1   8  75]]
-Node Classification on random seed  6005 -> 0.601
-Confusion Matrix:
- [[ 64   3   7   2   3  17  10]
- [  9 127   8   5   8   1   1]
- [ 44  17 121  23  35  15  59]
- [ 13   3   7 107   4   5  19]
- [  2   4   2   2  62   0   6]
- [  5   6   2   0   0  47   4]
- [ 12   2  11   3   7  13  73]]
-Node Classification on random seed  6006 -> 0.646
-Confusion Matrix:
- [[ 73   1   8   9   3  13   4]
- [  4 122   5   0   7   0   4]
- [ 16  21 150  19  30  26  45]
- [  9   1  15 117  11  10  11]
- [  2   6   4   1  58   0   0]
- [  2   3   2   4   0  49   2]
- [ 11   3  11   7   8  16  77]]
-Node Classification on random seed  6007 -> 0.629
-Confusion Matrix:
- [[ 69   2   6   4   3  17   4]
- [  1 135   3   0   9   5   2]
- [ 16  25 142  28  34  24  37]
- [ 14   3  14 101   9   5   8]
- [  0   9   2   3  63   3   1]
- [ 10   5   0   2   0  50   5]
- [ 13   6   6  13  10  10  69]]
-Node Classification on random seed  6008 -> 0.607
-Confusion Matrix:
- [[ 69   2   2   4   5  12  17]
- [  3 137   2   2   6   0   5]
- [ 13  31 121  53  23  17  66]
- [ 12   4   6 107   8   7   6]
- [  2   5   5   5  51   0   6]
- [  5   2   2   4   4  34   6]
- [  5   3   8   1  12  12  88]]
-Node Classification on random seed  6009 -> 0.604
-Confusion Matrix:
- [[ 69   4   4  10   3   7   9]
- [  4 132  12   0   7   6   0]
- [ 15  21 126  21  56  14  73]
- [  9  11  18  94   5   5   7]
- [  0   4   7   0  66   1   2]
- [  9   2   1   1   0  35   2]
- [ 11   4   3   4   9  15  82]]
-Node Classification on random seed  6010 -> 0.61
-Confusion Matrix:
- [[ 74   5   2   7   7  16   5]
- [  3 131   3   2   4   2   7]
- [ 20  12 131  16  49  21  48]
- [ 13  11  20  95  10   4  16]
- [  1   5   6   1  66   0   4]
- [  4   1   4   4   0  47   1]
- [ 13   3   6  17   5  12  66]]
-Node Classification on random seed  6011 -> 0.606
-Confusion Matrix:
- [[ 53   3  17   7   1  10  10]
- [  0 119  16   2  16   0   3]
- [ 16  19 142  37  14  20  65]
- [  9   1  21 101   7   9  12]
- [  1   5   3   4  66   0   6]
- [  2   1   9   1   0  48   2]
- [  9   2  15   8   2   9  77]]
-Node Classification on random seed  6012 -> 0.63
-Confusion Matrix:
- [[ 76   0   4   3   5   7  14]
- [  7 126   4   9   6   1   8]
- [ 36  18 149  36  15  11  34]
- [  8   3  10  97  13   9  17]
- [  2   5   2   0  59   0   4]
- [ 12   2   3   1   0  43   9]
- [ 14   9  17   3   5   4  80]]
-Node Classification on random seed  6013 -> 0.583
-Confusion Matrix:
- [[ 74   2   4   9   3  25  14]
- [  4 137  11   2   4   3   4]
- [ 12  28 107  56  35  19  35]
- [ 22   3  16  92   9   4  10]
- [  1   7   5   1  55   3   4]
- [  6   1   7   1   1  43   6]
- [  8   2   6   4   5  15  75]]
-Node Classification on random seed  6014 -> 0.581
-Confusion Matrix:
- [[ 55   7   4   5   8  16   9]
- [  3 127   7   1   1   3   5]
- [ 29  28 122  29  27  20  37]
- [ 14   3  24  95   4   3  27]
- [  2  13   5   0  55   4   2]
- [ 10   4   1   2   1  41   6]
- [  7   7  11   5  13  12  86]]
-Node Classification on random seed  6015 -> 0.602
-Confusion Matrix:
- [[ 73   0   4   3   3   8  11]
- [  6 142   1   3   7   3   7]
- [ 25  24 106  57  18  12  63]
- [ 12   0  18 102   2   5  20]
- [  2  10   2   3  64   0   2]
- [  2   1   5   0   0  47   5]
- [ 17   3   7  13   5   9  68]]
-Node Classification on random seed  6016 -> 0.662
-Confusion Matrix:
- [[ 73   0   0   1   4  20   7]
- [  4 124   5   1  10   1   1]
- [ 24  33 136  23  25  13  50]
- [  7   5  15 121   6   5   5]
- [  0   3   5   2  63   0   2]
- [  5   0   1   3   2  62   3]
- [  4   4  10  11   5  13  83]]
-Node Classification on random seed  6017 -> 0.629
-Confusion Matrix:
- [[ 66   2   4   3   5   7  10]
- [  5 126  10   1   4   1   5]
- [ 25  30 161  21  27  24  40]
- [ 10  10  13  95   5  17  17]
- [  1   5   4   2  70   0   2]
- [  5   2   4   0   0  38   5]
- [ 11   5   4   3   2  20  73]]
-Node Classification on random seed  6018 -> 0.557
-Confusion Matrix:
- [[ 69   1   8   4   1   6   8]
- [  5 114   6   1   6   4   2]
- [ 17  31 116  42  25  43  58]
- [ 16   4  15 103  12   3  14]
- [  1   5   7   2  64   1   1]
- [  4   3   3   6   3  42   4]
- [ 15   2  15  15   7  17  49]]
-Node Classification on random seed  6019 -> 0.632
-Confusion Matrix:
- [[ 68   2   6   9   7   8   5]
- [  4 118   9   0  23   0   3]
- [ 16  17 163  25  45  20  39]
- [  7   7  11 111   1   4  12]
- [  1   2   2   4  69   0   1]
- [  4   2   4   3   4  29   6]
- [ 15   3  12  11  12   2  74]]
-Node Classification on random seed  6020 -> 0.635
-Confusion Matrix:
- [[ 68   3   2   4   1  11   9]
- [  2 144   5   2   2   4   3]
- [ 18  28 136  22  38  18  27]
- [ 15  10  18 108   1   5  10]
- [  2  12   4   0  58   1   3]
- [  8   3   3   2   1  49   5]
- [ 21   3   7   9  11  12  72]]
-Node Classification on random seed  6021 -> 0.648
-Confusion Matrix:
- [[ 61   2   7   4   1   8   6]
- [  9 113   9   0   9   5   3]
- [ 24  25 186  21  27  25  20]
- [  8   2  13 127   6   4  20]
- [  5   1   5   2  65   3   1]
- [  6   1   6   5   0  42   4]
- [  9   4   6   3   8  25  54]]
-Node Classification on random seed  6022 -> 0.601
-Confusion Matrix:
- [[ 71   0   3   3   3   6   8]
- [  4 118   4   1  20   3   5]
- [ 17  19 117  48  36  33  51]
- [ 12   2   7 109   7   8  16]
- [  2   2   5   1  66   2   2]
- [  8   0   3   3   0  42   3]
- [ 14   1  10   2  11  14  78]]
-Node Classification on random seed  6023 -> 0.641
-Confusion Matrix:
- [[ 63   3   7   9   2   9  11]
- [  4 129   8   3   0   3   5]
- [ 28  15 164  34  13  19  51]
- [  6   0  14 104  14   5  11]
- [  3   5   6   2  60   1   5]
- [  5   1   2   2   1  44   4]
- [ 11   6  11   6   4  10  77]]
-Node Classification on random seed  6024 -> 0.605
-Confusion Matrix:
- [[ 52   1   4   4   5  11  11]
- [  7 121   8   3  10   2   4]
- [ 25  33 157  16  39  18  23]
- [  8   5  19  87   7  16  14]
- [  2   7   4   2  60   1   1]
- [  9   3   1   2   1  47  10]
- [ 10   5   9   8  12  15  81]]
-Node Classification on random seed  6025 -> 0.631
-Confusion Matrix:
- [[ 66   1  13   9   1  12   6]
- [  7 140   1   1   2   0   3]
- [ 17  19 160  33  15  26  49]
- [  9   5  21  85   3   1  12]
- [  2   6   4   0  71   1   3]
- [  0   6   3   3   9  39   9]
- [ 19   2   8   5   5  18  70]]
-Node Classification on random seed  6026 -> 0.575
-Confusion Matrix:
- [[ 65   4  10   4   3  16   2]
- [  7 127   8   5   6   2   5]
- [ 19  13 108  57  49  25  39]
- [  7   2  17 109   3  11   8]
- [  3   5   0   5  59   0   5]
- [  3   2   3   0   2  43   9]
- [  8   2  21  11   7  17  64]]
-Node Classification on random seed  6027 -> 0.602
-Confusion Matrix:
- [[ 66   2   3   2   5  12  16]
- [ 15 139   9   2   4   6   2]
- [ 28  24 153  30  22  24  38]
- [ 28   5  17  69   2   5  16]
- [  1   5   6   1  61   0   1]
- [  7   0   0   4   2  35   8]
- [ 13   7   7   1   5  13  79]]
-Node Classification on random seed  6028 -> 0.639
-Confusion Matrix:
- [[ 68   2   3   1   2  23  14]
- [  2 144   2   2   3   3   3]
- [ 23  30 127  33  25  22  42]
- [ 12   6   5 109   6   7  12]
- [  1   8   5   1  63   0   0]
- [  6   0   4   0   3  46   5]
- [  6   2  10   3   3  21  82]]
-Node Classification on random seed  6029 -> 0.56
-Confusion Matrix:
- [[ 56   9   2   3   5  17   5]
- [  6 130   4   2  13   1   5]
- [ 30  33 118  49  43  21  34]
- [ 12   4  20  89  11   4  10]
- [  2   9   2   3  58   4   3]
- [  5   1   5   4   1  39   6]
- [ 15   2  16   5   4  10  70]]
-Node Classification on random seed  6030 -> 0.575
-Confusion Matrix:
- [[ 64   6   6  12   3  17  17]
- [ 12 133   7   1   2   4   2]
- [ 28  38 119  33  20  41  27]
- [ 10   5  20  84   2   6  10]
- [  1   4   4   2  64   2   1]
- [ 13   2   3   2   0  40   3]
- [ 18   6   9   5   5  16  71]]
-Node Classification on random seed  6031 -> 0.576
-Confusion Matrix:
- [[ 61  14   4   5   6  14  17]
- [  3 121   5   1  14   0   6]
- [ 17  15 133  28  46  20  43]
- [  8   3  22  94   7  10  17]
- [  2  10   2   2  53   0   1]
- [  5   1   1   1   1  41  12]
- [ 14   4  13   8   8  14  73]]
-Node Classification on random seed  6032 -> 0.605
-Confusion Matrix:
- [[ 59   4   3   8   5  12   5]
- [  5 134   5   6   5   3   7]
- [ 39  19 149  21  19  19  52]
- [ 25   2  24  86   4   3  11]
- [  3   6   2   0  65   0   2]
- [  9   1   2   1   3  51   4]
- [ 17   1   9   7   5  17  61]]
-Node Classification on random seed  6033 -> 0.637
-Confusion Matrix:
- [[ 81   0   6   1   1  10  13]
- [  1 104   6   2  11   2   2]
- [ 22  15 165  37  15  25  37]
- [  8   2  14 102   4   7  19]
- [  1  11   6   0  62   2   1]
- [  5   3   6   4   0  44  11]
- [ 14   3   6   1   8  21  79]]
-Node Classification on random seed  6034 -> 0.627
-Confusion Matrix:
- [[ 79   3   5   6   5   8   6]
- [  4 119   0   4  11   2   2]
- [ 28  21 139  34  34  37  28]
- [ 10   8  14 107   8  11  11]
- [  1   4   1   1  63   0   3]
- [  4   1   1   5   1  42   7]
- [ 10   2  12   3   8   9  78]]
-Node Classification on random seed  6035 -> 0.599
-Confusion Matrix:
- [[ 65   8   3   8   8  18   4]
- [  1 132   4   5   8   3   3]
- [ 22  24 112  28  28  34  42]
- [ 11   3  11 120  13   5   7]
- [  1   6   2   4  57   0   1]
- [  0   2   3   4   0  46   6]
- [  8   6  11   8  15  23  67]]
-Node Classification on random seed  6036 -> 0.628
-Confusion Matrix:
- [[ 66   3   4  10   1  19  12]
- [  6 145   7   1   3   2   8]
- [ 20  20 142  33  27  11  40]
- [  4   6   9 121   4   7  13]
- [  2   7   3   1  56   1   3]
- [  7   0   6   7   0  37   5]
- [  3   5   7   7  19  19  61]]
-Node Classification on random seed  6037 -> 0.619
-Confusion Matrix:
- [[ 61   1   3   5  10  10   8]
- [  1 137   5   3   7   5   4]
- [ 19  30 142  23  24  27  37]
- [  7   6  23 112   8   2  11]
- [  1   8   5   0  57   2   3]
- [  3   0   0   6   1  42   4]
- [  9   1  11  16   9  23  68]]
-Node Classification on random seed  6038 -> 0.589
-Confusion Matrix:
- [[ 51   3  14   7   9   8  10]
- [  2 132   9   0   9   1   5]
- [ 29  27 130  38  33  34  36]
- [ 14  12  10  87   6   9  18]
- [  0   5   1   2  63   1   2]
- [  9   0   0   1   1  52   3]
- [  4   6  11   0   3  19  74]]
-Node Classification on random seed  6039 -> 0.619
-Confusion Matrix:
- [[ 81   3   6   4   4  15   8]
- [  3 125   6   1   6   4   2]
- [ 37  25 141  25  31  26  26]
- [  6   8  17 114  11   6   6]
- [  5   5   5   0  60   2   3]
- [  5   2  13   2   0  32   4]
- [  8   6   3  12  11   9  66]]
-Node Classification on random seed  6040 -> 0.638
-Confusion Matrix:
- [[ 91   3   2   9   6   6   3]
- [  4 112   9   1   8   1   8]
- [ 18  17 142  25  31  19  43]
- [ 18   8  13 104   3   4  14]
- [  1   7   2   0  62   1   4]
- [  8   2   3   1   0  49   6]
- [  9   1   9  18  10   7  78]]
-Node Classification on random seed  6041 -> 0.62
-Confusion Matrix:
- [[ 75   3   0   6   1   9   8]
- [  3 124   6   2   8   5   5]
- [ 25  14 149  41  29  18  49]
- [  7   8  23 107   2   3  15]
- [  1   8   7   0  53   1   5]
- [  6   3   2   6   0  38   5]
- [ 13   6   3  13   5   6  74]]
-Node Classification on random seed  6042 -> 0.604
-Confusion Matrix:
- [[ 72   1   7   6   3  10  11]
- [  3 115   5   1   1  10  11]
- [ 28  19 143  31  23  45  16]
- [  4   2  31  91  11  11  16]
- [  0   5   4   2  67   3   0]
- [  6   1   3   2   2  50   5]
- [ 10   2   5   1   8  31  66]]
-Node Classification on random seed  6043 -> 0.619
-Confusion Matrix:
- [[ 75   9   3   4   2  19   3]
- [  3 124   6   4   2   6   4]
- [ 15  23 155  34  15  30  42]
- [ 17   2  24  97   4   3   5]
- [  1  14   2   1  57   1   4]
- [  8   4   1   4   0  48  11]
- [  8   8  13   5   6  11  63]]
-Node Classification on random seed  6044 -> 0.626
-Confusion Matrix:
- [[ 67   0   7   8   6  10   4]
- [  5 139   3   1   6   3   1]
- [ 20  13 146  28  38  24  36]
- [ 17   4  11  89  17   6  14]
- [  0  10   4   1  61   4   2]
- [  5   2   3   1   0  50   7]
- [  6   1   3   4  12  27  74]]
-Node Classification on random seed  6045 -> 0.643
-Confusion Matrix:
- [[ 61   0   6  11   2   7  12]
- [  8 131   8   2   7   3   2]
- [ 28  16 157  43   9  18  39]
- [ 10   2  19 104   4   7   5]
- [  2   4   2   5  61   1   6]
- [  5   0   4   4   1  50   4]
- [ 11   2   9  14   3  12  79]]
-Node Classification on random seed  6046 -> 0.621
-Confusion Matrix:
- [[ 61   8   6   4   0  11   5]
- [  8 132   4   4   6   2   4]
- [ 23  20 139  29  40  25  30]
- [ 15   4   5 100   4   5  18]
- [  0   8   3   1  59   1   2]
- [  7   3   2   2   0  57   1]
- [ 10   8  12   9   7  23  73]]
-Node Classification on random seed  6047 -> 0.617
-Confusion Matrix:
- [[ 64   3   4   6   3  11  13]
- [  3 127   1   0   1   1   4]
- [ 35  41 151  35  21  13  36]
- [  8   5  24 101   3   1  13]
- [  1  11   5   1  59   0   6]
- [  5   4   2   0   0  48   3]
- [ 11   7  27   2   3  10  67]]
-Node Classification on random seed  6048 -> 0.638
-Confusion Matrix:
- [[ 84   2   4  16   3  12   8]
- [  6 114   4   3   7   0   3]
- [ 21  30 151  45  16  10  39]
- [  9   1  18 100   4   7   3]
- [  3   8   4   1  62   0   2]
- [  7   0   3   2   2  49   2]
- [ 14   4   4   8   6  21  78]]
-Node Classification on random seed  6049 -> 0.623
-Confusion Matrix:
- [[ 58   3   3   8   4   8  27]
- [  3 120   4   4   6   2   5]
- [ 25  19 136  24  20  30  57]
- [  3   7   9 108   2   7  15]
- [  1   8   4   1  59   3   1]
- [ 10   1   3   1   0  44   6]
- [ 14   1  13   3   8   4  98]]
-Node Classification on random seed  6050 -> 0.668
-Confusion Matrix:
- [[ 76   3   3   3   1   9  10]
- [  2 139   3   7   5   2  10]
- [ 27  17 184  23  14  11  36]
- [ 11   0  16  83   0   3  28]
- [  0   6   2   3  56   0   3]
- [  2   1   3   3   1  43  10]
- [ 13   6   5   5  12  13  87]]
-Node Classification on random seed  6051 -> 0.641
-Confusion Matrix:
- [[ 79   1   6   4   2   4   4]
- [  2 136   5   0   3   0   4]
- [ 27  29 159  28  21  29  37]
- [  7   4  22  89   0  19  30]
- [  1   8   0   4  47   2   2]
- [  3   0   3   1   1  45   7]
- [ 14   2   3   7   3  10  86]]
-Node Classification on random seed  6052 -> 0.632
-Confusion Matrix:
- [[ 71   2   6   6   4  19   4]
- [  9 121   7   0   5   0   7]
- [ 14  30 137  22  23  25  52]
- [  8   6  13 114   7   3  14]
- [  2   1   6   2  59   0   5]
- [  6   4   1   1   2  42   4]
- [  3   4  10   6   7  18  88]]
-Node Classification on random seed  6053 -> 0.575
-Confusion Matrix:
- [[ 55   2   4   5   0  15   8]
- [ 14 111  11   3   2   4   4]
- [ 18  17 123  47  24  34  54]
- [ 10   5  14 106   8   8  11]
- [  5   8   9   1  48   1   3]
- [  3   2   3   4   0  49   7]
- [  9   0  13  14   6  15  83]]
-Node Classification on random seed  6054 -> 0.643
-Confusion Matrix:
- [[ 71   4   2   1   3   8   7]
- [  4 128   5   1   8   1   2]
- [ 16  15 157  40  20  39  30]
- [ 11   0  15 108   4  10  18]
- [  2   6   4   1  65   0   1]
- [  1   0   0   5   0  38  12]
- [ 22   2  13   2   3  19  76]]
-Node Classification on random seed  6055 -> 0.628
-Confusion Matrix:
- [[ 71   1   2   3   3  14   5]
- [  1 134   3   1   9   8   7]
- [ 26  26 157  42  16  20  27]
- [ 10   3  25  86   8   8  14]
- [  3   3   3   1  65   2   1]
- [ 17   1   7   4   0  40   1]
- [ 15   1   6  11   5   9  75]]
-Node Classification on random seed  6056 -> 0.62
-Confusion Matrix:
- [[ 65   1  13   2   2  18   6]
- [  2 124   5   0   5   2   5]
- [ 18  33 134  33  32  33  21]
- [  8   6   6 110   5  11   8]
- [  0  10   7   1  67   0   4]
- [  2   2   2   1   0  53   5]
- [ 11   4   8   7  14  27  67]]
-Node Classification on random seed  6057 -> 0.6
-Confusion Matrix:
- [[ 67   2   6   4   1  15   7]
- [  4 135   2   5  17   5   2]
- [ 25  25 135  37  20  29  43]
- [  9   1  17  94   3   7  10]
- [  0   2   5   5  55   1   3]
- [ 12   0   8   1   1  47   0]
- [  8   1  18  15   7  17  67]]
-Node Classification on random seed  6058 -> 0.635
-Confusion Matrix:
- [[ 59   2   9   5   3   7   8]
- [ 11 119   6   3   8   0   2]
- [ 29  24 156  28  21  15  28]
- [  6   8  12 133   2   7  10]
- [  5  12   6   1  58   0   4]
- [  5   3   3   3   2  36   9]
- [ 12   4   5   7  10  20  74]]
-Node Classification on random seed  6059 -> 0.586
-Confusion Matrix:
- [[ 60   1   6   3   3  12  23]
- [  7 127   2   1  19  12   4]
- [ 32  15 132  24  43  28  44]
- [  8   4  13  84   6   7  26]
- [  0  10   3   2  48   1   2]
- [  5   2   1   0   0  44   6]
- [ 10   5   8   1   6   9  91]]
-Node Classification on random seed  6060 -> 0.624
-Confusion Matrix:
- [[ 73   1   0   2   6   8  16]
- [  3 120  13   0   8  12   2]
- [ 26  22 157  35  39  17  36]
- [  8   0  22 112   2   2  12]
- [  1   3   1   2  50   2   2]
- [  6   4   3   1   0  40  11]
- [ 16   1   8   7   5  11  72]]
-Node Classification on random seed  6061 -> 0.571
-Confusion Matrix:
- [[ 59   3  32   5   2   8  11]
- [  7 127   9   1   4   3   4]
- [ 13  15 120  48  31  32  61]
- [  5   0  21 110   5   4   8]
- [  0   5   3   5  68   3   0]
- [  1   1   4   5   0  31  10]
- [ 13   4   5  14   5  19  56]]
-Node Classification on random seed  6062 -> 0.618
-Confusion Matrix:
- [[ 73   4   4   2   3  12   5]
- [  3 137   6   4   1   2   2]
- [ 36  24 159  29  24  26  29]
- [ 11   3  25 104  13   3   8]
- [  3  11   2   3  48   1   4]
- [  5   1   1   2   0  41   5]
- [ 17   7  12  11   2  16  56]]
-Node Classification on random seed  6063 -> 0.626
-Confusion Matrix:
- [[ 70   3  11   5   2  14  15]
- [  4 117   6   3   7   4   6]
- [ 18  19 135  20  23  26  55]
- [  7   1  15 106   6   5  13]
- [  2   6   2   0  65   1   1]
- [  7   2   3   6   2  45  10]
- [  4   7  11   6   3  13  88]]
-Node Classification on random seed  6064 -> 0.594
-Confusion Matrix:
- [[ 77   7   3   2   1   5  19]
- [  3 120  11   5   1   1   4]
- [ 21  27 151  18  24  23  59]
- [ 20   5  16  87  10   7  26]
- [  3  11   7   1  50   0   3]
- [  5   4   2   2   0  39   6]
- [ 10   5  10   5   4  10  70]]
-Node Classification on random seed  6065 -> 0.624
-Confusion Matrix:
- [[ 80   2   7   6   4  10  15]
- [  1 131   5   4   8   4   1]
- [ 26  25 143  45  12  12  43]
- [  7   2  15 112   5   6  14]
- [  1   5   5   4  64   0   5]
- [  5   4   2   0   5  26   6]
- [  9   4  13   8   7  14  68]]
-Node Classification on random seed  6066 -> 0.632
-Confusion Matrix:
- [[ 90   8   2   6   8  11   9]
- [  6 130   5   1   6   2   6]
- [ 28  18 126  41  13  24  36]
- [  5   3  10 104   7   5  20]
- [  2   3   5   7  53   0   5]
- [  5   2   0   0   0  49   6]
- [ 17   6  10   4   5  11  80]]
-Node Classification on random seed  6067 -> 0.646
-Confusion Matrix:
- [[ 68   5   2   5   2  10   8]
- [ 13 122   4   1  10   4   1]
- [ 22  26 138  26  31  25  30]
- [  7   6  13 121   5   3   5]
- [  1   8   4   1  65   0   1]
- [  8   1   0   3   0  46   0]
- [ 17  11   8   4   8  15  86]]
-Node Classification on random seed  6068 -> 0.599
-Confusion Matrix:
- [[ 61   6   3   2   7  12  12]
- [  3 119  10   1  14   3   5]
- [ 23  30 139  62  16  29  16]
- [  8   1  16  91   5  13  16]
- [  0  11   4   1  58   2   1]
- [  7   1   2   1   1  64   5]
- [ 13   4  12   7   3  13  67]]
-Node Classification on random seed  6069 -> 0.601
-Confusion Matrix:
- [[ 72   2   2   3   1  10  11]
- [  3 119   9  14   3   2   2]
- [ 26  22 126  23  49  16  35]
- [ 14   6  16  92  14   5   8]
- [  0   6   5   5  68   0   1]
- [  8   2   3   0   1  53   2]
- [ 21   1  13   8   6  21  71]]
-Node Classification on random seed  6070 -> 0.629
-Confusion Matrix:
- [[ 71   3   0   6   4  15  16]
- [  2 128   0   3   5   4   3]
- [ 24  29 127  38  29  24  32]
- [  9   1  11 116   2   6  26]
- [  1   5   3   0  59   1   3]
- [  4   1   3   4   0  50   2]
- [ 11   7  11   7  10   6  78]]
-Node Classification on random seed  6071 -> 0.617
-Confusion Matrix:
- [[ 65   2   2   3   4  13   9]
- [  0 116   5   4   7   3   3]
- [ 21  17 155  31  19  24  54]
- [ 25   7  13  82   9   6  13]
- [  1   6   7   1  69   1   1]
- [  7   2   3   3   2  52   6]
- [ 11   4   5   6   3  20  78]]
-Node Classification on random seed  6072 -> 0.58
-Confusion Matrix:
- [[ 67   5   2   9   5   8  10]
- [  6 129   8   1  15   2   3]
- [ 32  21 126  25  42   7  56]
- [ 21   4  15  80   9   7  23]
- [  5   8   2   0  66   0   1]
- [  6   1   3   0   0  43  11]
- [ 11   1   7   3  11  14  69]]
-Node Classification on random seed  6073 -> 0.599
-Confusion Matrix:
- [[ 64   3   3   4   2  15  18]
- [  9 128   8   2   3   5   6]
- [ 31  18 134  45  20  22  34]
- [  8   8  11 102   4   4  18]
- [  2   6   6   4  59   1   3]
- [  3   1   2   2   0  44   4]
- [ 15   5  20  11   4  11  68]]
-Node Classification on random seed  6074 -> 0.638
-Confusion Matrix:
- [[ 69   5   1   7   4  16   8]
- [  6 131   7   3   3   6   4]
- [ 23  22 163  41  26  17  26]
- [  7   1  21  80  11  13  10]
- [  1   7   3   2  65   1   0]
- [  3   0   3   1   2  56   7]
- [  5   3   8   8   7  13  74]]
-Node Classification on random seed  6075 -> 0.556
-Confusion Matrix:
- [[ 61   6   4   2  12   7  13]
- [  6 105   7   1  11   4   5]
- [ 23  41 120  42  38  21  47]
- [ 15   5  14  88  14  14   8]
- [  1   5   1   3  58   0   6]
- [  6   2   1   1   1  43   8]
- [ 17   1   5  10   8   8  81]]
-Node Classification on random seed  6076 -> 0.635
-Confusion Matrix:
- [[ 86   4   6   3   5  10   8]
- [  4 124   3   0  16   5   6]
- [ 29  21 139  19  32  20  25]
- [  9   2  11  94  11   8  17]
- [  0   7   4   2  62   2   0]
- [ 13   1   0   0   2  43   3]
- [  8   6  13  14   5  11  87]]
-Node Classification on random seed  6077 -> 0.577
-Confusion Matrix:
- [[ 64   1   6   4   8   6   8]
- [  2 118   4   6  13   3   8]
- [ 21  15 129  38  43  21  41]
- [  8   9  27  84  12   5  12]
- [  3   6   8   1  53   3   7]
- [  5   2   3   5   0  42   5]
- [ 15   3  10  13   7   6  87]]
-Node Classification on random seed  6078 -> 0.569
-Confusion Matrix:
- [[ 64   5   5  15   0  11  14]
- [  7 126   6   2  10   5   4]
- [ 16  21 117  44  34  22  32]
- [ 10   5  21  87   3   6  28]
- [  1   3   2   2  64   0   1]
- [  5   2   4   0   1  45   9]
- [ 13   4   6   9  29  14  66]]
-Node Classification on random seed  6079 -> 0.586
-Confusion Matrix:
- [[ 55   3  21   4   8  13   6]
- [  1 108   6   2  22   5   7]
- [ 21  13 122  45  26  22  48]
- [ 12   2  25 106   8   4   9]
- [  0   4   3   1  64   3   4]
- [  2   0   2   0   0  48   7]
- [  2   1  21   3  11  17  83]]
-Node Classification on random seed  6080 -> 0.604
-Confusion Matrix:
- [[ 61   4   8  11   4   7  17]
- [  4 149   9   1   4   0   3]
- [ 34   7 139  41  31  25  37]
- [ 18   6  22  85   4   2  15]
- [  0   9   7   0  57   0   0]
- [  2   1   9   0   0  47   4]
- [ 11   2  10  10  11   6  66]]
-Node Classification on random seed  6081 -> 0.596
-Confusion Matrix:
- [[ 67   4   7   3   1  15   5]
- [  3 123   2   5  15   2   2]
- [ 29  20 120  38  34  27  31]
- [  7   5  16  97   6  11  20]
- [  4  11   2   1  69   0   6]
- [  2   3   0   5   2  54   2]
- [ 15   4   5   3  11  20  66]]
-Node Classification on random seed  6082 -> 0.659
-Confusion Matrix:
- [[ 68   2   2   5   5   8   8]
- [  1 135   7   3   5   3   0]
- [ 31  20 167  25  20  31  31]
- [  8   6  15  98   2   9  13]
- [  0   6   4   1  61   0   3]
- [  9   0   3   4   0  48   6]
- [ 14   2   8   1   9  11  82]]
-Node Classification on random seed  6083 -> 0.623
-Confusion Matrix:
- [[ 66   1   2   3   4  16   8]
- [  9 126   8   3   2   4   5]
- [ 17  25 136  34  25  27  37]
- [  4   6  20 109   6   5  12]
- [  3   4   2   0  61   0   3]
- [ 12   0   2   4   2  48   4]
- [ 19   2   6   7   5  19  77]]
-Node Classification on random seed  6084 -> 0.619
-Confusion Matrix:
- [[ 58   3   8   6   4   5  10]
- [  7 113   6   1   5   2  10]
- [ 30  27 157  22  41  25  36]
- [ 12   1  11 105  12   8  10]
- [  0   2   4   2  62   1   3]
- [  3   1   4   1   0  36   7]
- [ 11   4   8  13   1  14  88]]
-Node Classification on random seed  6085 -> 0.575
-Confusion Matrix:
- [[ 76   6   1   1  10   7  15]
- [ 13 114   4   2  22   0   6]
- [ 27  39 126  26  32  18  40]
- [ 30  10  11  87   3   2  15]
- [  1   2   7   3  60   0   4]
- [  9   2   3   0   0  44   2]
- [ 18   6   6   2  13   7  68]]
-Node Classification on random seed  6086 -> 0.625
-Confusion Matrix:
- [[ 54   1  11   6   5  11  12]
- [  5 133   3   3  23   0   4]
- [  8  24 157  33  21  15  35]
- [  6   8  28  81  10   8  22]
- [  1   4   4   4  72   1   7]
- [  1   0   5   2   1  48   7]
- [  8   3  13   2   4   6  80]]
-Node Classification on random seed  6087 -> 0.608
-Confusion Matrix:
- [[ 80   2   5   4   4   9   5]
- [  4 124   2   6  12   0   5]
- [ 31  22 126  56  29  23  31]
- [ 17   1  19 110   4   5   5]
- [  2   8   4   4  63   0   0]
- [  6   0   4   1   0  37   3]
- [ 16   2  20  12   3   6  68]]
-Node Classification on random seed  6088 -> 0.638
-Confusion Matrix:
- [[ 71   3   9   1   1  14  11]
- [  3 136   3   2   2   0   8]
- [ 18  41 134  53  14   8  34]
- [  3   6  19 111   2   6  11]
- [  2   7   3   1  42   3   7]
- [  3   2   4   0   1  60   4]
- [ 20   6   4   8   3  12  84]]
-Node Classification on random seed  6089 -> 0.653
-Confusion Matrix:
- [[ 74   2   6   3   2  14   9]
- [  5 124   5   3   6   3   4]
- [ 13  21 154  27  18  29  45]
- [  2   2  18  92   5   6  18]
- [  1  12   4   0  68   1   2]
- [  9   0   1   2   0  51   1]
- [ 13   0   8  10   5  12  90]]
-Node Classification on random seed  6090 -> 0.609
-Confusion Matrix:
- [[ 57   2  16   4   3  13  12]
- [  4 129   5   3   8   7   4]
- [ 31  15 155  41  38   5  46]
- [  5   0  19 110   3   7  12]
- [  6   5   0   3  49   1   1]
- [  6   0   3   2   0  55   3]
- [ 13   3  14   5   9  14  54]]
-Node Classification on random seed  6091 -> 0.61
-Confusion Matrix:
- [[ 62   5  13   2   2  12   9]
- [  4 115  10   7   7   1   2]
- [ 28  26 144  36  39  14  34]
- [ 12   8  17 105   5   5   5]
- [  3   5   1   1  56   1   5]
- [ 10   2   2   2   2  42   7]
- [  8   7  11   4   4  12  86]]
-Node Classification on random seed  6092 -> 0.637
-Confusion Matrix:
- [[ 71   5   0   9   5   7  13]
- [  1 132   3   1  12   2   8]
- [ 18  11 134  43  28  18  48]
- [ 16   1  13 103   4   3  13]
- [  0   8   2   4  70   1   1]
- [  4   3   1   2   3  45   8]
- [  5   5   5   8   7  14  82]]
-Node Classification on random seed  6093 -> 0.583
-Confusion Matrix:
- [[ 53   0   4   2   3  24   6]
- [  3 116   5   7  13   5   6]
- [ 14  13 130  55  33  24  36]
- [ 11   2  16 103   9  15  16]
- [  0   4   3   2  65   1   1]
- [  3   2   6   3   2  48   5]
- [  3   3  10  13  12  22  68]]
-Node Classification on random seed  6094 -> 0.626
-Confusion Matrix:
- [[ 79   6   1   8   4  11  11]
- [  4 119   9   2   2   1   2]
- [ 37  17 151  38  21  15  31]
- [  6   5  13 105   5   7  15]
- [  4  10   7   0  59   2   1]
- [  6   1   6   0   0  41   5]
- [ 16   6  10   6   7  16  72]]
-Node Classification on random seed  6095 -> 0.614
-Confusion Matrix:
- [[ 66   2   1   3   4  19  14]
- [  6 127   2   3  10   3   5]
- [ 21  11 150  28  31  38  35]
- [  4   2  11 104   6   7  17]
- [  1   5   6   3  62   0   0]
- [  8   1   2   0   3  40   6]
- [ 10   5   7   6  17  23  65]]
-Node Classification on random seed  6096 -> 0.618
-Confusion Matrix:
- [[ 63   1   4   7  10   8  20]
- [  6 123   7   0   8   5   2]
- [ 26  29 154  35  30  13  29]
- [  6   5  24  97   6   4  18]
- [  0   7   6   1  59   0   1]
- [  5   2   3   3   0  38   7]
- [  3   5  16   2  10   8  84]]
-Node Classification on random seed  6097 -> 0.614
-Confusion Matrix:
- [[ 78   6   1   6   2  12  14]
- [  3 122   5   3   4   3   6]
- [ 17  22 146  60  15  35  30]
- [ 15   9  11 113   2   0  18]
- [  1   3   6   1  46   0   4]
- [  5   1   0   4   2  42   9]
- [  7   6   9  11   5  13  67]]
-Node Classification on random seed  6098 -> 0.586
-Confusion Matrix:
- [[ 72   2  11   5   4   9   8]
- [  5 129   7   4   7   1   8]
- [ 29  10 115  61  25  22  35]
- [  9   5  20  80  15  10  22]
- [  1   7   2   1  61   1   6]
- [  2   1   1   2   1  50  11]
- [  4   5  13   6   6  10  79]]
-Node Classification on random seed  6099 -> 0.613
-Confusion Matrix:
- [[ 64   4   2   6   2  10  15]
- [  6 133   4   6   4   3   6]
- [ 20  27 160  39  13  24  32]
- [ 17   4  17  96  11   8  12]
- [  3   3   9   0  57   2   8]
- [ 10   2   2   2   1  35   9]
- [ 16   0   5  13   5   5  68]]
-Node Classification on random seed  6100 -> 0.67
-Confusion Matrix:
- [[ 84   1   2   4   2   4   8]
- [  5 115   4   3   5   0   6]
- [ 12  18 179  30  45   9  24]
- [ 21   4   8  97   4   6  21]
- [  2   8   1   3  66   2   2]
- [  5   2   2   3   0  51   6]
- [ 12   5   8   5   6  12  78]]
-Node Classification on random seed  6101 -> 0.641
-Confusion Matrix:
- [[ 83   1   5   4   2  17  10]
- [  4 120   6   1  16   2   6]
- [ 16  32 128  42  25  20  28]
- [ 16   6  10  94   5   9   8]
- [  1   1   2   0  65   2   3]
- [  3   0   4   0   2  55   8]
- [  4   4  15   5   4  10  96]]
-Node Classification on random seed  6102 -> 0.646
-Confusion Matrix:
- [[ 66   2   7   3   5   7  14]
- [  4 110   4   3   3   6   5]
- [ 14  23 173  35  23  18  34]
- [  7   6  14 120   5   4  15]
- [  1  11   5   3  64   1   3]
- [  3   0   1   1   2  32   3]
- [ 14   3   3   3  14  22  81]]
-Node Classification on random seed  6103 -> 0.625
-Confusion Matrix:
- [[ 71   0   6   6   4  17  17]
- [  6 114   5   3   6   4   8]
- [ 25   9 154  35  23  26  41]
- [ 24   2  10  98   3   3  10]
- [  1   5   4   1  61   0   7]
- [  8   1   4   1   2  50   3]
- [ 11   3   6   2   2  21  77]]
-Node Classification on random seed  6104 -> 0.61
-Confusion Matrix:
- [[ 68   2   3   5   1  17   5]
- [  3 140   9   2   5   2   2]
- [ 22  32 119  31  39  20  28]
- [  9  10  15 118   3   7   5]
- [  2   7   5   0  60   0   6]
- [  5   0   4   0   1  45   4]
- [ 22   6   5  14   8  24  60]]
-Node Classification on random seed  6105 -> 0.651
-Confusion Matrix:
- [[ 78   1   3   4   3  20   9]
- [  4 132   3   2   5   0   9]
- [ 11  21 162  31  29  28  20]
- [ 23   0  17 108   4   7  13]
- [  1   7   2   6  57   0   0]
- [  5   1   4   1   1  42   5]
- [  9   3  13   6   5  13  72]]
-Node Classification on random seed  6106 -> 0.586
-Confusion Matrix:
- [[ 57   3   7   5   1  14   7]
- [  3 114  21   2  11   2   7]
- [ 23  21 145  22  43  29  40]
- [  9   3  19 101   3   4   9]
- [  1   2   8   0  61   0   1]
- [  5   1   1   3   1  45  11]
- [  8   3  17   8  13  23  63]]
-Node Classification on random seed  6107 -> 0.65
-Confusion Matrix:
- [[ 76   0   3   0   2   8  11]
- [  8 118   3   5   8   4   3]
- [ 31  16 156  49  32  15  32]
- [  8   7   7 114   2   6  11]
- [  0   9   4   5  58   3   0]
- [  3   0   4   2   0  46   4]
- [  9   2   5   8   4  17  82]]
-Node Classification on random seed  6108 -> 0.64
-Confusion Matrix:
- [[ 74   1   4   4   5   8  15]
- [  7 135   1   1   3   1   7]
- [ 27  31 164  27  23   8  34]
- [  9   5  16  99   6   1  24]
- [  1   7   5   1  54   0   4]
- [  4   1   2   2   0  35  12]
- [ 14   3  15   6   7   8  79]]
-Node Classification on random seed  6109 -> 0.645
-Confusion Matrix:
- [[ 68   2   5   4   5  12  11]
- [  4 135   4   1   6   2   2]
- [ 34  22 174  29  24  15  39]
- [  9   6  15  99   1   3  17]
- [  3   6   2   3  57   1   3]
- [  0   2   5   2   1  50   5]
- [ 15   2  14   6   2  11  62]]
-Node Classification on random seed  6110 -> 0.598
-Confusion Matrix:
- [[ 54   2  11   5   6   5  14]
- [  3 139   5   4   6   2   5]
- [ 24  22 115  34  35  25  48]
- [  9   3  16 112   6   6  17]
- [  0   6   4   3  58   1   2]
- [  3   3   2   1   4  41   6]
- [ 15   2   9   3  12  13  79]]
-Node Classification on random seed  6111 -> 0.58
-Confusion Matrix:
- [[ 80   9   6   2   5   8   7]
- [  3 126   8   0  11   1  10]
- [ 28  28 119  31  37  33  42]
- [ 10   4  18  88   7   5  23]
- [  3   4   3   3  51   1   3]
- [  3   2   1   2   0  48   6]
- [ 12   2   7   7  10  15  68]]
-Node Classification on random seed  6112 -> 0.609
-Confusion Matrix:
- [[ 54   1  19   4   2  14   8]
- [  1 126   2   0   7   3   6]
- [ 21  26 128  40  27  21  44]
- [ 16   8   4 109   9   7  12]
- [  3   6   5   1  67   2   5]
- [  2   1   6   1   6  40   7]
- [  6   4  14   6   5   9  85]]
-Node Classification on random seed  6113 -> 0.619
-Confusion Matrix:
- [[ 77   0   1   1   1  17   8]
- [  1 118   9   5   0   6   2]
- [ 18  40 133  44  22  24  27]
- [ 13   1  15 101   8   9  11]
- [  0   8   1   6  56   1   4]
- [  2   1   2   3   0  52   7]
- [  6   4   9  10  13  21  82]]
-Node Classification on random seed  6114 -> 0.627
-Confusion Matrix:
- [[ 57   2   3   5   4  15  26]
- [  0 128   4   0   5   8  10]
- [ 26  19 175  27  21  27  18]
- [ 12   3  21  92   5   0  12]
- [  1   5   4   1  55   2   2]
- [  8   1   2   4   2  43   7]
- [ 11   5   7   7   6  25  77]]
-Node Classification on random seed  6115 -> 0.597
-Confusion Matrix:
- [[ 67   3   5   6   4  19  15]
- [  4 120   8   3  20   2   1]
- [ 23  13 127  43  46  18  39]
- [  4   5  20  95  11   4   8]
- [  0   6   6   3  50   1   2]
- [  7   1   7   3   0  40   2]
- [  9   2   8   6   3  13  98]]
-Node Classification on random seed  6116 -> 0.637
-Confusion Matrix:
- [[ 62   2   4   9   0   3  24]
- [  4 135   3   5   7   1   1]
- [ 19  13 158  37  37  23  29]
- [  9   5  20  85   3  10  18]
- [  2   2   7   0  66   1   2]
- [  6   3   1   2   0  51   9]
- [  5   2   8   9   5  13  80]]
-Node Classification on random seed  6117 -> 0.607
-Confusion Matrix:
- [[ 61   2   1   7   1  10  11]
- [ 10 129   2   7   9   0   3]
- [ 28  22 120  47  16  30  42]
- [ 11   3  21 107   3   8  10]
- [  0   3   1   1  71   0   1]
- [  8   0   3   1   1  52   2]
- [ 15   2   3  15  16  17  67]]
-Node Classification on random seed  6118 -> 0.679
-Confusion Matrix:
- [[ 68   1   2   3   3  14  15]
- [  4 132   4   2   3   2   5]
- [ 20  16 185  21  16  21  39]
- [  8   0  17  98   1  10  14]
- [  1   8   4   0  64   2   3]
- [  3   1   3   5   5  51   4]
- [  8   3   4   4   7  15  81]]
-Node Classification on random seed  6119 -> 0.635
-Confusion Matrix:
- [[ 86   2   6   2   3  17   8]
- [  1 118   5   3  14   3   1]
- [ 31   9 156  24  24  19  52]
- [ 15   4  13  98   3   9  16]
- [  2   0   1   1  64   0   4]
- [  5   3   5   1   1  43   1]
- [  8   6   9   7   7  20  70]]
-Node Classification on random seed  6120 -> 0.622
-Confusion Matrix:
- [[ 66   0   5   7   3  11   9]
- [  9 135   9   5   4   0   1]
- [ 18  28 150  32  20  31  35]
- [  5   0  27 103  10   8   6]
- [  1   4   5   2  59   1   3]
- [  7   1   2   0   1  50   5]
- [  9   4   9  12   8  21  59]]
-Node Classification on random seed  6121 -> 0.609
-Confusion Matrix:
- [[ 68   5   0   6   5  15  10]
- [  2 141   2   6  12   4   4]
- [  8  39 124  48  25  28  27]
- [ 10   5  23  99   4  10  11]
- [  0   9   7   0  58   0   4]
- [  1   2   2   0   0  55   3]
- [  4   4   9  14   4  19  64]]
-Node Classification on random seed  6122 -> 0.625
-Confusion Matrix:
- [[ 67   8   3   9   3  16   8]
- [  6 135   3   2   4   3   3]
- [ 28  29 134  32  28   8  38]
- [  9   9  20 117   4   6   9]
- [  1   7   8   5  55   1   0]
- [  8   0   1   1   1  44   4]
- [ 11   1   7   5  12  14  73]]
-Node Classification on random seed  6123 -> 0.595
-Confusion Matrix:
- [[ 67   4   4   4   9   8   9]
- [  2 121   7   5   4   0   6]
- [ 23  16 134  32  30  23  68]
- [  5   3  12 111   3   5  17]
- [  0   7   2   1  53   0  10]
- [  5   1   5   5   2  46  10]
- [ 10   5   5  25   6   7  63]]
-Node Classification on random seed  6124 -> 0.582
-Confusion Matrix:
- [[ 62   9   8   5   3  14  10]
- [  0 119   3   4   8   2   9]
- [  9  26 136  32  15  24  66]
- [ 16   8  24  84   4  11  22]
- [  1   5   4   1  58   3   3]
- [  7   2   4   1   2  37   4]
- [  6   2   8   5   5  23  86]]
-Node Classification on random seed  6125 -> 0.614
-Confusion Matrix:
- [[ 72   0   6   9   3   3   6]
- [ 15 129   1   2   2   2   3]
- [ 24  35 136  34  23  23  37]
- [ 10   8  26 106   2  10  13]
- [  4   2   5   1  56   0   3]
- [  5   1   3   2   0  45   4]
- [  9   2  20  13   4  11  70]]
-Node Classification on random seed  6126 -> 0.595
-Confusion Matrix:
- [[ 74   4   3   6   7  11   4]
- [  8 101   9   3  12   2   2]
- [ 23   8 141  39  47  24  41]
- [ 16   5  16 102   7   3  10]
- [  1   6   4   3  58   2   3]
- [  7   0   2   2   0  41   6]
- [ 16   6   6   5   7  19  78]]
-Node Classification on random seed  6127 -> 0.618
-Confusion Matrix:
- [[ 77   1   3  14   7   4  12]
- [  1 120   4   3   5   0   4]
- [ 20   9 136  41  36  23  54]
- [  9   3   8 101  10   5  18]
- [  0   7   3   1  58   2   3]
- [  3   2   4   2   0  43  15]
- [  6   2  11   9   6  12  83]]
-Node Classification on random seed  6128 -> 0.617
-Confusion Matrix:
- [[ 69   3   5   5   6  12  13]
- [  4 130   7   7  18   2   0]
- [ 28  16 150  24  22  28  41]
- [ 22   1   3 103  10   3  10]
- [  4   3   9   1  64   2   0]
- [ 11   0   5   0   1  27  12]
- [ 11   3   8   1   3  19  74]]
-Node Classification on random seed  6129 -> 0.598
-Confusion Matrix:
- [[ 58   1   0  14   5  10  11]
- [  8 124   5   6   7   2   1]
- [ 18  24 130  41  28  32  44]
- [ 19   7  12 108   3   7   6]
- [  1   5   1   3  62   1   0]
- [  6   2   2   8   1  50   2]
- [ 10   1   8  18   5  17  66]]
-Node Classification on random seed  6130 -> 0.613
-Confusion Matrix:
- [[ 78   1   2  14   4  13   9]
- [  5 116   7   3   2   2   4]
- [ 32  37 127  35  21  36  22]
- [  7   6  15 107   4  12  17]
- [  1   5   3   2  55   2   1]
- [  6   3   0   1   0  57   4]
- [ 10   5   8   6   3  17  73]]
-Node Classification on random seed  6131 -> 0.631
-Confusion Matrix:
- [[ 81   1   8   5   4   9   6]
- [  3 133   7   7   4   5   8]
- [ 34  15 135  45  22  20  28]
- [ 19   5  14  99   5   3  12]
- [  3   5   2   1  60   1   3]
- [  3   3   0   0   1  43   2]
- [ 13   2  11  12   5  13  80]]
-Node Classification on random seed  6132 -> 0.651
-Confusion Matrix:
- [[ 91   1   3   1   3   8  11]
- [  3 143   5   2  13   2   8]
- [ 23  26 141  25  30  25  32]
- [  8   5   8 110   6   6   4]
- [  3   4   1   0  74   0   2]
- [  7   1   0   1   0  44   1]
- [ 15   7   7  11  18  13  48]]
-Node Classification on random seed  6133 -> 0.634
-Confusion Matrix:
- [[ 87   2   2   7   2   4   7]
- [  6 143   3   2   9   1   4]
- [ 35  21 158  44  31  12  29]
- [ 11   5   6 103   6   3  13]
- [  3  10   2   1  58   1   6]
- [  5   0   6   0   0  36   5]
- [ 23   4  12  14   1   8  49]]
-Node Classification on random seed  6134 -> 0.633
-Confusion Matrix:
- [[ 78   0   2   3   5   9   8]
- [  3 133   6   6   6   3   7]
- [ 26  18 145  38  24  19  42]
- [ 17   4  16  88   2   8  13]
- [  2   4   3   6  64   1   5]
- [ 10   1   0   0   1  38   4]
- [ 19   0   6   8   5   7  87]]
-Node Classification on random seed  6135 -> 0.601
-Confusion Matrix:
- [[ 76   2   7   4   8  11   6]
- [  3 124   1   8   7   1   2]
- [ 29  19 137  43  32  20  27]
- [ 25   7  12  96   8  11   8]
- [  0   9   3   2  68   0   1]
- [  7   6   0   0   2  47   2]
- [ 13   9   7   9  13  15  53]]
-Node Classification on random seed  6136 -> 0.594
-Confusion Matrix:
- [[ 51   5  11   0   8  20   9]
- [  5 126   7   0   4   3   7]
- [ 32  30 136  36  23  17  47]
- [ 20   0   8 109   8   3   7]
- [  1   5   1   6  55   1   1]
- [  5   2  11   2   0  44   1]
- [ 13   4   9   5   4  25  73]]
-Node Classification on random seed  6137 -> 0.627
-Confusion Matrix:
- [[ 71   2   3   5   5  11   6]
- [  2 128   2   2  10   1  10]
- [ 26  23 125  51  24  28  30]
- [ 10   1   7 113   4   6  15]
- [  2   4   6   2  66   0   3]
- [  6   1   2   1   1  42   2]
- [ 16   1   8   5  12  17  82]]
-Node Classification on random seed  6138 -> 0.637
-Confusion Matrix:
- [[ 77   4   1   3   4  14   9]
- [  1 125  10   1   6   2   3]
- [ 21  20 133  16  22  33  50]
- [ 11   5  12 112   6   5   7]
- [  1   9   5   3  67   0   1]
- [  8   4   1   0   1  51   2]
- [ 14   5   6   7   4  26  72]]
-Node Classification on random seed  6139 -> 0.629
-Confusion Matrix:
- [[ 78   2   1   7   3  16   1]
- [  4 146   4   3   3   2   0]
- [ 19  17 148  33  26  27  35]
- [ 23   2  11  90  13   6  15]
- [  0  12   4   0  58   0   4]
- [  5   4   4   1   2  41   7]
- [ 17   4   6   5   3  20  68]]
-Node Classification on random seed  6140 -> 0.567
-Confusion Matrix:
- [[ 82   4   5   2   4   8   7]
- [  4 131   0   1  12   1   9]
- [ 38  27  93  33  40  26  47]
- [ 22   9   9  88   5  10  14]
- [  1  13   5   2  59   0   1]
- [  4   2   2   2   1  43   4]
- [ 21   2   4   9   4  19  71]]
-Node Classification on random seed  6141 -> 0.613
-Confusion Matrix:
- [[ 66   4   2   6   6  19  24]
- [  3 116   6   5  15   3  10]
- [ 13  16 153  21  45  22  44]
- [ 13   2  17  98   6   2  11]
- [  2   4   2   0  60   2   0]
- [  6   2   2   1   1  45   8]
- [  8   4   3   5   8  14  75]]
-Node Classification on random seed  6142 -> 0.622
-Confusion Matrix:
- [[ 70   1   6   2   4   7  11]
- [  7 137   3   0   8   5   8]
- [ 17  22 156  23  19  34  41]
- [ 21   5  13  89  13   6  10]
- [  1   7   9   1  54   0   2]
- [  7   5   0   0   3  33   4]
- [ 15   0  12   9   3  14  83]]
-Node Classification on random seed  6143 -> 0.638
-Confusion Matrix:
- [[ 83   6   3   6   3   9   9]
- [  3 125   6   2   9   1   5]
- [ 13  21 163  15  15  29  29]
- [ 12   3  15  95   6  17  21]
- [  1   7   7   0  53   5   3]
- [  5   1   2   3   1  44   5]
- [  7   5  16   6   5  25  75]]
-Node Classification on random seed  6144 -> 0.641
-Confusion Matrix:
- [[ 76   8   3   1   3   9   8]
- [  1 122   8   6   9   1   6]
- [ 15  18 173  23  28  12  44]
- [ 17   0  14 110   4  11   7]
- [  1   7   6   2  55   5   1]
- [  4   1   6   0   1  49  10]
- [  9   7  14   6   8  15  56]]
-Node Classification on random seed  6145 -> 0.615
-Confusion Matrix:
- [[ 82   4   5   0   2   3  14]
- [  6 117   6   2  18   0   8]
- [ 21   8 131  31  45  15  42]
- [ 22   2  20  95   7   3   6]
- [  2   6   3   1  71   1   3]
- [ 12   2   4   4   1  44   4]
- [ 14   3  18   1   6  10  75]]
-Node Classification on random seed  6146 -> 0.639
-Confusion Matrix:
- [[ 93   4   2   3   3  16   8]
- [ 10 129   4   1   7   5   4]
- [ 22  15 158  38  13  15  33]
- [  3   5  10  95   6  17  12]
- [  0   6   2   2  61   1   3]
- [ 10   1   3   2   2  33   6]
- [ 15   3   6  11  11  21  70]]
-Node Classification on random seed  6147 -> 0.615
-Confusion Matrix:
- [[ 70   1   3  11   3   9  10]
- [  8 135   4   3   2   6   2]
- [ 39  21 134  46  13  14  38]
- [ 30   4   7  85   3   3  12]
- [  0  10   4   3  60   1   2]
- [  9   3   0   0   0  50   6]
- [ 19   2  16   8   4   6  81]]
-Node Classification on random seed  6148 -> 0.635
-Confusion Matrix:
- [[ 80   9   2   4   4   7   5]
- [  5 136   3   1  10   2   3]
- [ 24  16 140  19  34  30  38]
- [ 12   8   7  90  20   4  13]
- [  1   5   5   1  70   1   5]
- [ 10   0   0   1   3  49   1]
- [ 10   3   3   6  15  15  70]]
-Node Classification on random seed  6149 -> 0.622
-Confusion Matrix:
- [[ 80   3   2   4   3   7  12]
- [  6 112   4   6   4   3   2]
- [ 27  12 152  44  34  18  36]
- [ 20  10  13  99   5  12  12]
- [  4   6   5   1  55   0   0]
- [  7   2   2   0   2  51   2]
- [ 10   2   2  13   6  15  73]]
-Node Classification on random seed  6150 -> 0.616
-Confusion Matrix:
- [[ 54   2   4   8   9  32   6]
- [  4 119   9   5  11   3   7]
- [ 12  13 170  27  31  32  26]
- [ 25   2  16  96   3   2   9]
- [  1   5   0   1  54   2   2]
- [  8   1   1   2   2  48   4]
- [ 13   3   3   6   7  25  75]]
-Node Classification on random seed  6151 -> 0.597
-Confusion Matrix:
- [[ 77   0   1   1   4   2  16]
- [  3 128   6   3   5   6   5]
- [ 29  36 116  36  30  20  47]
- [ 32   8  13  99   2   7  10]
- [  1   6   5   3  61   0   1]
- [  6   0   3   0   0  40   4]
- [ 14   5  12   7   2  12  76]]
-Node Classification on random seed  6152 -> 0.615
-Confusion Matrix:
- [[ 79   2   4   1   8   4  14]
- [  4 127   8   0   6   3   2]
- [ 25  20 123  55  21  37  33]
- [ 13   1  14 112   4   4  14]
- [  2   9   7   4  64   2   1]
- [  2   2   1   2   0  41  10]
- [ 14   0   6   9   5  12  69]]
-Node Classification on random seed  6153 -> 0.627
-Confusion Matrix:
- [[ 79   4   8   1   6   9   4]
- [  6 131   2   4   9   2   4]
- [ 22  13 144  34  32  30  46]
- [ 10   8  20  97   4   4   4]
- [  2   5   3   1  59   1   5]
- [  7   0   0   2   0  47   7]
- [ 10   3   8  12  11  10  70]]
-Node Classification on random seed  6154 -> 0.598
-Confusion Matrix:
- [[ 66   4   7   5   5  13   6]
- [  4 144   8   4   5   4   3]
- [ 35  15 133  65  20  23  20]
- [ 27   6  15  89   8   4  12]
- [  1   5   6   5  56   0   2]
- [  5   1   3   1   1  39   9]
- [  5   1  17   6   3  13  71]]
-Node Classification on random seed  6155 -> 0.65
-Confusion Matrix:
- [[ 88   2   3   3   6   9   6]
- [  2 129   4   1   9   1   5]
- [ 28  18 136  29  14  17  53]
- [ 13   3  12 119   5   1   8]
- [  1   6   5   3  62   1   4]
- [ 12   3   2   0   1  37   7]
- [ 16   3   9   5   3  17  79]]
-Node Classification on random seed  6156 -> 0.572
-Confusion Matrix:
- [[ 68   2   2   2   6  11  15]
- [  3 127   1   7   4   3   2]
- [ 17  18 128  75  24  20  23]
- [ 14   7  18  88  10   2  26]
- [  4  11   2   6  51   3   1]
- [ 10   0   2   2   0  41   4]
- [ 15   3  10  14   3  26  69]]
-Node Classification on random seed  6157 -> 0.602
-Confusion Matrix:
- [[ 76   4   7  13   3   0   5]
- [  3 125   4   2   8   4   7]
- [ 36  23 127  32  33  24  31]
- [ 25   4  11  98   4   4   9]
- [  0   6   0   1  66   1   4]
- [ 10   3   2   4   1  39   5]
- [ 16  14  10   9   4  12  71]]
-Node Classification on random seed  6158 -> 0.61
-Confusion Matrix:
- [[ 66   1   4   4   2  18   9]
- [  7 114   6   5   5   6   3]
- [ 26  26 139  48  13  35  22]
- [  6  10   9 105   9   3  13]
- [  2   9   3   1  61   1   1]
- [  6   1   6   0   2  48   5]
- [ 11   5  13   2  11  21  77]]
-Node Classification on random seed  6159 -> 0.627
-Confusion Matrix:
- [[ 56   4   5   6   1  18  16]
- [  2 109   5   2  18   2   4]
- [ 14  13 149  24  33  30  26]
- [ 10   5  18 104   4  15  11]
- [  5   1   4   1  70   1   3]
- [ 11   2   1   2   0  51   5]
- [ 10   3  11   8   8  11  88]]
-Node Classification on random seed  6160 -> 0.604
-Confusion Matrix:
- [[ 74   2   1   4   2  17  11]
- [  7 122   6   1   3   4   2]
- [ 25  17 131  28  40  23  55]
- [ 17   3  16  88   5  11  16]
- [  0   6   5   0  70   0   3]
- [  1   5   3   0   2  45   8]
- [  7   5  10   6   8  11  74]]
-Node Classification on random seed  6161 -> 0.629
-Confusion Matrix:
- [[ 56   2   6  10   4  12  13]
- [  1 117   7   3  12   4  12]
- [ 33  17 145  50  19  19  31]
- [  6   4   9 111   5   3   9]
- [  1   6   7   0  71   0   9]
- [  8   0   2   3   0  51   1]
- [  6   3   5   6   7  16  78]]
-Node Classification on random seed  6162 -> 0.627
-Confusion Matrix:
- [[ 63   4   2   8   2  15  10]
- [  4 128   1   2  14   4   3]
- [ 24  44 134  26  26  14  40]
- [  9   8  14 113   9   4  14]
- [  1  12   2   1  71   0   1]
- [  1   4   1   1   1  41   7]
- [  5   3   4   5   9  14  77]]
-Node Classification on random seed  6163 -> 0.595
-Confusion Matrix:
- [[ 73   8   5   1   3  10  17]
- [  3 125   4   6  12   1   3]
- [ 36  25 138  64  17  29  19]
- [  7   4  12 101   5   5  15]
- [  1   1  11   6  58   0   5]
- [  4   0   0   2   1  36   9]
- [  8   3  16   9   6  12  64]]
-Node Classification on random seed  6164 -> 0.606
-Confusion Matrix:
- [[ 67   2   1   2   5  16   6]
- [ 12 122   4   3   7   4   4]
- [ 33   8 144  53  20  27  38]
- [ 12   7   9 108   5   8  15]
- [  2   8   4   0  55   5   2]
- [  3   0   1   0   2  37   4]
- [ 10   6   5  11  12  18  73]]
-Node Classification on random seed  6165 -> 0.593
-Confusion Matrix:
- [[ 73   9   2  10   2   7  14]
- [  4 114  14   6  14   6   1]
- [ 34  17 136  15  21  22  57]
- [  8   2  21  95   7   7  10]
- [  3   5   5   1  49   1   9]
- [  4   2   0   7   0  44  11]
- [ 10   2   8  10   6  13  82]]
-Node Classification on random seed  6166 -> 0.609
-Confusion Matrix:
- [[ 51   0   6   8   7   8  13]
- [  9 125   5   4   7   2   8]
- [ 25  25 141  33  28  22  33]
- [ 18   8  16 102   2   9   7]
- [  2   7   5   2  69   1   2]
- [  5   2   2   1   0  52   3]
- [  8   4  15   7   8  14  69]]
-Node Classification on random seed  6167 -> 0.606
-Confusion Matrix:
- [[ 75   4   7   9   8  11   5]
- [  8 129   7   2  13   3   8]
- [ 25  27 145  26  25  33  28]
- [ 13   3  15  85  13   4   9]
- [  0   3   3   1  44   0   5]
- [ 10   1   1   2   0  45   3]
- [ 11   7   5  11  10  15  83]]
-Node Classification on random seed  6168 -> 0.594
-Confusion Matrix:
- [[ 66   2   9   9   3  14  11]
- [  8  94   7   2  13   2   5]
- [ 25  12 150  39  23  34  35]
- [  4   5  16 112   5  17  10]
- [  1   3   5   3  58   2   5]
- [  7   1   3   0   1  35  11]
- [ 20   2   6   5  12   9  79]]
-Node Classification on random seed  6169 -> 0.63
-Confusion Matrix:
- [[ 65   1   1   4   2  16  16]
- [  5 136   1   2   9   2   3]
- [ 28  17 156  32  16  14  39]
- [ 15   2  14 118  11   8   7]
- [  0   8   7   2  60   1   2]
- [  7   5   1   0   1  26   7]
- [ 19   3   8   3   8  23  69]]
-Node Classification on random seed  6170 -> 0.635
-Confusion Matrix:
- [[ 75   2   3   9   1   6   5]
- [  2 118  11   3   5   2   2]
- [ 38  21 145  42  29  21  30]
- [ 20   9   7 110   0   2   7]
- [  2   9   2   1  63   1   4]
- [  2   2   2   0   1  49   3]
- [  9   5   8  21   8   8  75]]
-Node Classification on random seed  6171 -> 0.567
-Confusion Matrix:
- [[ 67   1  14   6   7  14   8]
- [  4 119  10   2   9   0   5]
- [ 26  31 111  42  42  22  42]
- [  7   2  15 102   8   6  20]
- [  2   7   3   1  61   1   6]
- [  3   1   3   0   0  49   5]
- [ 10   3  10   6   6  23  58]]
-Node Classification on random seed  6172 -> 0.651
-Confusion Matrix:
- [[ 68   2   2   3   4  17   2]
- [  3 129   2   2  11   4   1]
- [ 14  27 147  40  25  10  51]
- [  9   2  15 114   2   2  11]
- [  0   5   2   4  66   0   2]
- [  3   2   0   1   3  38   8]
- [  5   2   9   3  18  21  89]]
-Node Classification on random seed  6173 -> 0.605
-Confusion Matrix:
- [[ 76   8   4   2   4  11   8]
- [ 16 117   5   2   8   5   2]
- [ 23  24 136  30  34  27  32]
- [ 11   1  12  92   7  10   8]
- [  3   6   5   3  66   1   1]
- [  8   2   1   2   0  46   5]
- [ 14   6  14   9   6  15  72]]
-Node Classification on random seed  6174 -> 0.625
-Confusion Matrix:
- [[ 79   4   6  11   1   9   8]
- [  6 128   1   7   2   8   3]
- [ 24   8 142  44  23  29  43]
- [ 11   2  17  85   5  13   6]
- [  2   6   4   7  67   0   2]
- [  3   2   2   3   0  42   4]
- [ 13   1   9   4   6  16  82]]
-Node Classification on random seed  6175 -> 0.625
-Confusion Matrix:
- [[ 72   7   1   9   3   6  12]
- [  3 124   5   9   8   4   2]
- [ 22  28 127  28  38  22  38]
- [  8   3  12 117  12   1  11]
- [  0   2   6   1  62   1   1]
- [ 11   1   1   3   1  38   8]
- [ 18   6   2   6  10   5  85]]
-Node Classification on random seed  6176 -> 0.625
-Confusion Matrix:
- [[ 86   2   9   1   4   6   5]
- [  1 116   7   3  12   2   2]
- [ 27  31 169  12  35  21  32]
- [  8   6  16  96   0   8  17]
- [  1   6   4   2  59   2   2]
- [ 11   1   7   1   1  31   6]
- [ 12   2  20   3  11  16  68]]
-Node Classification on random seed  6177 -> 0.611
-Confusion Matrix:
- [[ 65   3   6   6   3   6  12]
- [  7 117   9   0  14   5   2]
- [ 49  21 154  16  15  18  46]
- [ 14   5   8 109   3   5  22]
- [  4   8   5   0  52   0   1]
- [ 12   0   4   1   0  44   1]
- [ 29   1   9   2   6  11  70]]
-Node Classification on random seed  6178 -> 0.612
-Confusion Matrix:
- [[ 61   4   4   4   1  20  11]
- [  0 146   7   8   5   0   2]
- [ 27  17 157  34  18  20  58]
- [  9   1  18  86   9   3  13]
- [  1   5   2   2  50   3   7]
- [  1   4   3   2   0  41   7]
- [ 16   3   5   7   5  22  71]]
-Node Classification on random seed  6179 -> 0.626
-Confusion Matrix:
- [[ 73   3   5   2   9  11  14]
- [  4 123   7  10   4   2   1]
- [ 16  18 160  25  23  27  49]
- [ 13   1  11  87   9   5  25]
- [  0   5   4   0  56   2   2]
- [  5   1   2   4   3  45   6]
- [ 12   4  10   3   7  10  82]]
-Node Classification on random seed  6180 -> 0.613
-Confusion Matrix:
- [[ 69   4   2   9   9  11  16]
- [  5 110   8   7   8   4   3]
- [ 33  20 155  25  20  24  40]
- [ 13   3  20 110   2   5   7]
- [  2   3   6   3  58   1   2]
- [  7   1   1   3   0  35  11]
- [ 12   4   8   3  10  12  76]]
-Node Classification on random seed  6181 -> 0.593
-Confusion Matrix:
- [[ 70   2   2  12   4  11   5]
- [  5 132   3   1   5   3   2]
- [ 30  29  98  61  35  20  24]
- [ 11   5  14 107   9   2   9]
- [  2   9   4   1  66   1   1]
- [  9   1   4   1   3  47   3]
- [ 18   3  10  14   5  14  73]]
-Node Classification on random seed  6182 -> 0.58
-Confusion Matrix:
- [[ 79   1   6   5   5   6   9]
- [  2 122  13   2   8   1   4]
- [ 31  24 124  40  21  32  42]
- [ 26   4  16  84   4   8  14]
- [  2   9   4   1  68   2   6]
- [  4   1   3   3   1  32   8]
- [ 19   4  11   4   6   8  71]]
-Node Classification on random seed  6183 -> 0.652
-Confusion Matrix:
- [[ 76   2   0   3  12   8  11]
- [  7 139   2   3   5   2   3]
- [ 14  12 173  28  33  12  47]
- [ 14   4   9 107   5   6  19]
- [  1   9   5   1  57   2   3]
- [  0   2   3   0   1  43   2]
- [ 17   8   8   6   8  11  57]]
-Node Classification on random seed  6184 -> 0.634
-Confusion Matrix:
- [[ 74   2   6   9   9   7  11]
- [  3 119  10   4  12   2   0]
- [ 21  16 153  38  28  25  42]
- [ 14   8   8 110   3   1  15]
- [  0   4   2   1  60   1   1]
- [  2   1   3   2   3  39   6]
- [ 11   3   4   7   9  12  79]]
-Node Classification on random seed  6185 -> 0.597
-Confusion Matrix:
- [[ 60   2   6   3   5  16   9]
- [  5 118   5   3  13   5   3]
- [ 23  13 142  33  35  30  29]
- [ 25   2  11  92  12   8   8]
- [  0   4   3   0  63   2   7]
- [  7   2   6   3   0  52   5]
- [  7   1  12  18   4  18  70]]
-Node Classification on random seed  6186 -> 0.632
-Confusion Matrix:
- [[ 82   3   2   8   2   9   5]
- [  2 127   6   1  16   1   1]
- [ 26  28 140  41  26  23  29]
- [ 15   4  14 104   9   9  12]
- [  1   5   3   1  48   0   2]
- [  2   1   1   1   5  43   2]
- [ 15   4   8   4   6  15  88]]
-Node Classification on random seed  6187 -> 0.592
-Confusion Matrix:
- [[ 63   5   4   7   7   9  11]
- [ 13 121   4   2  10   4   2]
- [ 22  17 127  59  36  24  33]
- [ 11   6   9 108   5   6  10]
- [  2   6   1   2  59   0   1]
- [  8   0   4   2   1  43   3]
- [  9   3   9  14   7  20  71]]
-Node Classification on random seed  6188 -> 0.605
-Confusion Matrix:
- [[ 79   1   4  10   8   8   3]
- [  5 123   7   4   7   4   3]
- [ 18  42 147  50  18  10  44]
- [ 15   3  15  97   4   6   3]
- [  0   8   2   2  61   1   2]
- [ 11   4   2   3   1  36   2]
- [ 23   8   6   5   6  17  62]]
-Node Classification on random seed  6189 -> 0.66
-Confusion Matrix:
- [[ 65   3   9   4   2  16   2]
- [  2 149   3   1   4   8   5]
- [ 22  21 140  19  36  20  42]
- [  5   4   9 107   7  12   8]
- [  1   6   2   1  66   1   4]
- [  6   2   0   1   3  50   7]
- [  8   2   6   6   5  15  83]]
-Node Classification on random seed  6190 -> 0.622
-Confusion Matrix:
- [[ 79   3   3   4   2   9   8]
- [  4 130   5   1   4   1   9]
- [ 31  24 134  27  27  22  51]
- [ 10   1  22 108   5   5   9]
- [  1   7   2   1  60   0   3]
- [ 12   1   0   1   1  43   6]
- [ 14   3   5   7   9  18  68]]
-Node Classification on random seed  6191 -> 0.616
-Confusion Matrix:
- [[ 54   1  11   7   0  11  20]
- [  0 126   4   6   5   1   7]
- [ 13  13 148  42  38  16  49]
- [  5   8   7 112   3   7  17]
- [  1   4   2   5  62   0   5]
- [  2   0   0   1   0  49  13]
- [  4   2   5  17  18  14  65]]
-Node Classification on random seed  6192 -> 0.648
-Confusion Matrix:
- [[ 66   1   6   3   4  16   7]
- [  1 136   5   7   9   1   7]
- [ 16  17 157  27  20  12  56]
- [ 14   2   9 109   3   2  14]
- [  0  12   4   4  58   1   4]
- [  3   4   3   0   1  45   9]
- [  2   2   8   6   7  23  77]]
-Node Classification on random seed  6193 -> 0.59
-Confusion Matrix:
- [[ 71   4  12   4   3  15  21]
- [  5 138   5   1   2   4   3]
- [ 10  20 109  60  38  16  38]
- [  9   2  18  83   9   7  22]
- [  0  12   2   0  74   1   2]
- [  2   1   9   1   3  41   7]
- [  5   7  10   1   4  15  74]]
-Node Classification on random seed  6194 -> 0.634
-Confusion Matrix:
- [[ 90   4   6  10   2   7  14]
- [  3 112  10   2   7   0   2]
- [ 19  22 167  15  27  24  31]
- [ 14  13  18  85   7   5  13]
- [  2   7   5   0  55   2   2]
- [  6   3   1   4   2  48   4]
- [ 15   5   7   3   7  16  77]]
-Node Classification on random seed  6195 -> 0.59
-Confusion Matrix:
- [[ 68   5   5  12   4   5  13]
- [  3 127   5   2   4   1   3]
- [ 19  31 128  42  43  17  39]
- [ 10   7  16  98   4   8  16]
- [  2   7   2   2  63   2   2]
- [  6   2   4   3   0  40   3]
- [  9   8   5   5  18  16  66]]
-Node Classification on random seed  6196 -> 0.605
-Confusion Matrix:
- [[ 76   2   3   1   2  14  17]
- [  3 117   8   2   7   2   7]
- [ 19  22 147  26  33  19  40]
- [ 14  11  13  85   7  10  27]
- [  3  10   2   1  59   0   2]
- [  5   0   1   2   3  44   5]
- [  6   2   3   7   9  25  77]]
-Node Classification on random seed  6197 -> 0.598
-Confusion Matrix:
- [[ 70   2   8   4   6  16  10]
- [  3 133   2   7   4   6  10]
- [ 16  33 118  36  33  26  50]
- [ 11   3   7  97   5   2  12]
- [  0   5   3   2  62   5   5]
- [  4   7   3   1   0  47   4]
- [  1   3   8  10   9  20  71]]
-Node Classification on random seed  6198 -> 0.584
-Confusion Matrix:
- [[ 62   4   8   5   4   9  20]
- [  9 117  10   0   4   8   6]
- [ 26  17 134  30  35  28  34]
- [ 14   7  11  74  17   7  13]
- [  1   4   0   1  68   1   2]
- [  3   4   5   2   0  44   9]
- [ 12   3  10   7   6  20  85]]
-Node Classification on random seed  6199 -> 0.635
-Confusion Matrix:
- [[ 56   4   8   4   7  11   4]
- [  6 126   2   7   4   5   2]
- [ 31  22 157  33  28  22  24]
- [ 11   2  19 113  12   3  10]
- [  0   9   2   1  59   2   1]
- [  8   0   3   1   2  51   0]
- [ 15   5   7   8   3  17  73]]
-Node Classification on random seed  6200 -> 0.59
-Confusion Matrix:
- [[ 52   4  11   7   7   6  30]
- [  4 123   2   3   6   2   2]
- [ 20  37 124  49  27  21  35]
- [  8   8   7 109  13   3  10]
- [  0   9   1   1  61   1   4]
- [  3   1   5   3   0  46   6]
- [ 12   2  18   7   7   8  75]]
-Node Classification on random seed  6201 -> 0.641
-Confusion Matrix:
- [[ 83   1   0   5   4  10  10]
- [  4 132   3   1   8   2   1]
- [ 19  27 153  24  16  37  44]
- [ 10   5  18  89   6   3  13]
- [  3   8   7   2  64   0   5]
- [  3   2   2   4   1  45   3]
- [  4   4  11   0  11  18  75]]
-Node Classification on random seed  6202 -> 0.602
-Confusion Matrix:
- [[ 69   4   3   5   6  17  13]
- [  5 119   6   2  17   1   4]
- [ 28  22 133  29  37  16  52]
- [  3  12   7  94   3   5  19]
- [  0   7   4   0  66   1   1]
- [  1   5   4   0   0  46   9]
- [  5   2  13   9   9  12  75]]
-Node Classification on random seed  6203 -> 0.605
-Confusion Matrix:
- [[ 74   2  11   6   1  11  10]
- [  5 116   3   4   7   1   6]
- [ 18  27 140  38  34  16  41]
- [ 10   5  30  78   5  13  21]
- [  1   9   3   1  66   3   3]
- [  6   3   2   0   0  43  11]
- [  6   2   2   3   8   7  88]]
-Node Classification on random seed  6204 -> 0.629
-Confusion Matrix:
- [[ 74   3   9   4   5  12   5]
- [  7 122   6   4   4   1   6]
- [ 14  32 147  27  15  22  58]
- [  7   3  12  87   6   9  22]
- [  1   9   0   0  65   0   1]
- [  4   0   7   0   0  46   7]
- [ 10   5  11   4   8  11  88]]
-Node Classification on random seed  6205 -> 0.65
-Confusion Matrix:
- [[ 79   3   7   2   4  11   7]
- [  6 130   2   1   7   7   5]
- [ 19  12 166  29  23  20  39]
- [ 20   5  22  88   4   8  14]
- [  1   5   1   2  65   0   2]
- [  4   0   0   0   0  44  10]
- [ 16   3   5   7   4  13  78]]
-Node Classification on random seed  6206 -> 0.616
-Confusion Matrix:
- [[ 67   3   0   3   0  24   8]
- [  8 141   5   3   9   2   2]
- [ 35  16 151  26  20  26  39]
- [ 12   5  22  88   9  13  16]
- [  3   3   2   1  50   0   8]
- [  4   1   1   0   0  42   2]
- [ 15   4  13   6   5  10  77]]
-Node Classification on random seed  6207 -> 0.57
-Confusion Matrix:
- [[ 65   5  12  19   6   9   6]
- [  6 116   4   4   8   4   7]
- [ 15  10 104  59  52  16  40]
- [ 14   0   8 103   2   2  25]
- [  1   4   3   0  70   1   6]
- [ 10   2   2  10   0  44   4]
- [ 22   1   5  13   6   7  68]]
-Node Classification on random seed  6208 -> 0.615
-Confusion Matrix:
- [[ 46   4   3   7   4   7  24]
- [  4 116  14   0   5   7   3]
- [ 27  17 153  51  27  15  41]
- [ 11   0  12 122   6   6   2]
- [  1   5   4   0  59   0   3]
- [  6   1   2   3   0  40   4]
- [  9   3   9   9  13  16  79]]
-Node Classification on random seed  6209 -> 0.611
-Confusion Matrix:
- [[ 66   3   3   2   1  14  19]
- [  0 108   5   5  15   4  10]
- [ 18   9 155  49  31  36  30]
- [  4   1  11 106   2   6  25]
- [  4   2   4   1  60   0   6]
- [  4   0   1   1   0  55  10]
- [  6   2   7   4  13  21  61]]
-Node Classification on random seed  6210 -> 0.619
-Confusion Matrix:
- [[ 63   5   7   2   1  20  10]
- [  1 130   6   1   7   0   6]
- [ 13  27 121  26  30  23  50]
- [  9  11  14 104   8   7  12]
- [  1   7   2   3  76   1   2]
- [  4   3   4   6   0  42   5]
- [  6   6   6   9   3  17  83]]
-Node Classification on random seed  6211 -> 0.606
-Confusion Matrix:
- [[ 73   3   1   3   5  10  21]
- [  4 111   7   2  22   0   4]
- [ 11  26 142  39  30  17  38]
- [ 14   3  12 101  11  11  10]
- [  2   2   6   1  68   0   0]
- [ 10   1   0   1   8  38   4]
- [ 12   4   9  11   5  14  73]]
-Node Classification on random seed  6212 -> 0.593
-Confusion Matrix:
- [[ 41   2  15  16   1  18   6]
- [  2 121   6   2   9   1   3]
- [ 15  27 125  39  18  23  54]
- [  9   3  19 110   0   3  12]
- [  1   5   4   5  57   3   2]
- [  5   2   2   3   0  42   9]
- [ 19   8   5   6   9  16  97]]
-Node Classification on random seed  6213 -> 0.612
-Confusion Matrix:
- [[ 61   3   5   2   1  17  17]
- [  6 135   7   1   2   4   2]
- [ 19  28 141  60  19  18  39]
- [ 11   6  10 101   9   6  11]
- [  0  13   5   3  55   0   4]
- [  2   2   1   4   0  49   3]
- [ 10   5   6   5   5  17  70]]
-Node Classification on random seed  6214 -> 0.615
-Confusion Matrix:
- [[ 64   2   9   8   2  11  15]
- [  9 133   6   1  11   1   3]
- [ 16  15 135  38  40  27  30]
- [ 15   5  16  97   4   4   9]
- [  1   6   4   2  63   1   1]
- [  6   2   0   4   0  43   5]
- [ 12   4   9   6  13  12  80]]
-Node Classification on random seed  6215 -> 0.614
-Confusion Matrix:
- [[ 71   4   6   6   2   5  10]
- [  8 136   4   0   2   1   3]
- [ 44  22 139  34  18  14  59]
- [ 20   5  17  91   5   1  10]
- [  2  13   1   0  55   1   1]
- [  3   4   3   2   1  41   8]
- [ 12   3   5  10   7  10  81]]
-Node Classification on random seed  6216 -> 0.629
-Confusion Matrix:
- [[ 61   1   5   4   2  26   7]
- [  8 110  14   2  12   1   3]
- [ 21  18 166  25  23  23  29]
- [ 25   2  17  97  12   8   7]
- [  0   1   2   0  55   2   3]
- [  4   0   3   6   1  55   2]
- [ 12   4   9   2  11  14  85]]
-Node Classification on random seed  6217 -> 0.612
-Confusion Matrix:
- [[ 63   1   2   1   7  15   3]
- [  5 119   7   1  23   3   8]
- [ 20  17 161  16  54  30  25]
- [ 21   2  21  88   4  10   8]
- [  3   1   3   1  55   3   4]
- [  6   5   0   0   0  50   3]
- [ 17   4   6  11   3  14  76]]
-Node Classification on random seed  6218 -> 0.604
-Confusion Matrix:
- [[ 68   0   8   3   1  13  14]
- [  6 116   6   1   5   0   3]
- [ 24  22 125  42  43  32  35]
- [  4   3  17 113   2   5  13]
- [  2   9   5   4  62   0   5]
- [  6   1   3   4   0  40   7]
- [ 12   1   7   9   6  13  80]]
-Node Classification on random seed  6219 -> 0.592
-Confusion Matrix:
- [[ 66   2   3   3   3  17   8]
- [  8 123   5   5   9   1   1]
- [ 21  20 129  47  24  28  49]
- [ 25   3  10  90   3  12  13]
- [  3   4   6   2  58   0   3]
- [  3   1   6   0   1  48   6]
- [ 24   4   6  11   5   3  78]]
-Node Classification on random seed  6220 -> 0.573
-Confusion Matrix:
- [[ 75   3  10  13   0  15   3]
- [  6 112   6   1   5   7   3]
- [ 30  25 102  32  32  27  60]
- [  8   5  15  95   3   5  18]
- [  0   7   4   0  74   1   2]
- [  9   1   5   3   2  49   0]
- [  5  10  16  11   4  15  66]]
-Node Classification on random seed  6221 -> 0.607
-Confusion Matrix:
- [[ 87   1   1   7   3  22   9]
- [  2 134   2   0  13   3   5]
- [ 28  23 120  32  19  38  44]
- [ 16   4  23  91  10   8  11]
- [  0   2   3   2  55   1   2]
- [  3   0   1   0   1  52   4]
- [  8   5   3   9  11  14  68]]
-Node Classification on random seed  6222 -> 0.605
-Confusion Matrix:
- [[ 54   8   3   2   2  17  14]
- [  6 126   4   0   8   4   4]
- [ 22  31 134  48  21  19  41]
- [ 17   4  15 105   8   4   3]
- [  4   4   6   0  60   1   5]
- [  6   1   0   0   0  47   9]
- [ 14   4   5   6   7  18  79]]
-Node Classification on random seed  6223 -> 0.657
-Confusion Matrix:
- [[ 76   1   8   3   3  12   7]
- [  8 109  14   2   4   4   2]
- [ 20  13 187  26  24  19  42]
- [ 12   0   9 107   2   8  12]
- [  5   5   3   3  66   0   2]
- [  5   1   2   1   2  50   7]
- [  8   0  12   7   9  16  62]]
-Node Classification on random seed  6224 -> 0.591
-Confusion Matrix:
- [[ 85   5   1   3   2   9   9]
- [  4 120   2   0   9   0   2]
- [ 28  22 106  25  56  21  48]
- [ 26   6  12  97  10   6   9]
- [  2   4   2   0  65   4   3]
- [  7   3   2   5   1  37   2]
- [ 16   8   7  12   6  10  81]]
-Node Classification on random seed  6225 -> 0.638
-Confusion Matrix:
- [[ 75   3   3   5   1  13   7]
- [  5 132   8   4   4   0   4]
- [ 17  24 162  21  26  25  48]
- [ 15   2  20  92   6   7  13]
- [  0   7   6   2  63   1   3]
- [  2   1   5   0   1  45   7]
- [  7   6  11   5   9   8  69]]
-Node Classification on random seed  6226 -> 0.642
-Confusion Matrix:
- [[ 57   1   0   7   3  13  11]
- [  4 132   5   6   7   1   2]
- [ 22  27 147  32  22  22  46]
- [ 16   4  10 103   4   5  12]
- [  1   6   6   3  72   1   1]
- [  2   0   4   0   1  45   7]
- [  3   1  10   5  10  15  86]]
-Node Classification on random seed  6227 -> 0.587
-Confusion Matrix:
- [[ 75   1  11   6   3   5   9]
- [ 11 111   8   2   1   2  12]
- [ 21  27 118  52  40  36  23]
- [  6   5  14 104   5   4  17]
- [  3   8   2   2  61   0   4]
- [  4   3   1   3   1  42   5]
- [ 11   2   8  11   6  18  76]]
-Node Classification on random seed  6228 -> 0.61
-Confusion Matrix:
- [[ 68   4   6   2   3  16  10]
- [  0 142   5   0  15   1   5]
- [ 12  24 136  29  10  29  64]
- [ 10   8  27  95   3   7  12]
- [  3   2   3   3  66   1   2]
- [  6   2   7   1   0  43   6]
- [ 12   5   7   4  10  14  60]]
-Node Classification on random seed  6229 -> 0.611
-Confusion Matrix:
- [[ 73   1   1   3   5  21  10]
- [  3 128   8   4   2   0   1]
- [ 20  27 139  53  31  18  43]
- [  9   6  10  97   5   5  13]
- [  1   6   6   0  58   0   1]
- [  4   0   1   1   0  44  19]
- [ 11   2   8  10  11   9  72]]
-Node Classification on random seed  6230 -> 0.636
-Confusion Matrix:
- [[ 54   0   3   3   3  22  13]
- [  6 122   4   3  14   2   2]
- [ 28  24 170  19  15  27  43]
- [  6   4  10 108   5   2  18]
- [  1   2   8   0  64   4   2]
- [  4   0   0   2   2  39   9]
- [ 11   2  11   5   9  16  79]]
-Node Classification on random seed  6231 -> 0.602
-Confusion Matrix:
- [[ 80   3   3   8   1  10  10]
- [  5 130   4   0   3   1  10]
- [ 15  30 140  47  30  25  39]
- [ 19   6  11  86   7  11   7]
- [  3   6   3   7  62   2   2]
- [  4   2   1   0   2  39   3]
- [ 17   5  11   5   7  13  65]]
-Node Classification on random seed  6232 -> 0.646
-Confusion Matrix:
- [[ 69   5   3   7   4  15  11]
- [  3 135   7   2   0   3   3]
- [ 16  18 169  51  15  22  24]
- [ 11   1  17  99  13   3  13]
- [  1   9   3   2  64   1   5]
- [  1   2   3   2   0  45   3]
- [ 15   2   9   7   7  15  65]]
-Node Classification on random seed  6233 -> 0.606
-Confusion Matrix:
- [[ 67   2   1   7   8  11   8]
- [  8 119  10   1   5   3   2]
- [ 23  16 129  45  25  33  42]
- [ 22   1   8  98   8   3  14]
- [  2   1   2   3  64   3   2]
- [  3   0   2   0   1  46   9]
- [ 20   3   5   1  12  19  83]]
-Node Classification on random seed  6234 -> 0.656
-Confusion Matrix:
- [[ 74   2   6   8   3   8   9]
- [  2 128   4   8   0   1   2]
- [ 17  35 143  49  10  20  28]
- [ 14   5  11 114   1   7  13]
- [  0   7   5   1  56   1   2]
- [  3   1   5   4   0  48   3]
- [ 18   4   3   7   5  12  93]]
-Node Classification on random seed  6235 -> 0.631
-Confusion Matrix:
- [[ 62   0   3   3  12   5  18]
- [  6 131   6   7   8   3   2]
- [ 31  23 147  40  13  15  38]
- [  8   1  12 119   2   4   9]
- [  2   7   2   4  67   1   2]
- [  3   1   2   2   1  43   9]
- [ 10   3  14   7   6  24  62]]
-Node Classification on random seed  6236 -> 0.594
-Confusion Matrix:
- [[ 75   1   6   6   6   6   6]
- [  2 139   4   1   6   2   5]
- [ 32  25 112  80  10  27  39]
- [ 11   3  13 108   1   6  18]
- [  0   5   5   2  58   0   2]
- [  9   1   2   3   1  44   2]
- [ 14   5   8  10   2  19  58]]
-Node Classification on random seed  6237 -> 0.616
-Confusion Matrix:
- [[ 78   2   5   9   4  14   6]
- [  2 113   5   4  15   5   4]
- [ 18  18 135  35  46  14  50]
- [  5   6   7 104   9  13  19]
- [  0   7   4   0  63   1   7]
- [  6   0   3   1   0  45   1]
- [  9   2   0  12   4  12  78]]
-Node Classification on random seed  6238 -> 0.568
-Confusion Matrix:
- [[ 58   1   4   7   6  14  19]
- [  5 148   0   1   5   2   2]
- [ 24  21 134  35  24  16  53]
- [ 27   4  19  60  10   9  24]
- [  1  16   3   0  57   1   4]
- [ 16   0   1   1   0  39   7]
- [ 14   5   4   5   4  18  72]]
-Node Classification on random seed  6239 -> 0.605
-Confusion Matrix:
- [[ 79   4   1   5   3   3  14]
- [  3 114   6   1   4  10   0]
- [ 29  26 138  47  25  20  45]
- [ 25   8   6  97   5   2   9]
- [  1   7   3   2  54   2   1]
- [ 10   1   2   2   1  43   3]
- [ 21   4   4  10   6  14  80]]
-Node Classification on random seed  6240 -> 0.592
-Confusion Matrix:
- [[ 79   2   1   3   4   6   7]
- [  8 140   7   4   5   2   6]
- [ 19  29 128  38  47  19  27]
- [ 34   7  31  78   4   2   9]
- [  1   4   2   4  68   1   3]
- [  6   2   1   1   0  35   3]
- [  9   8  11   6   7  18  64]]
-Node Classification on random seed  6241 -> 0.593
-Confusion Matrix:
- [[ 72   3   7   5   3   6  15]
- [  1 117  13   1   7   2  18]
- [ 24  22 126  47  41  15  27]
- [ 17   7  10 109   4   4  12]
- [  2   6   2   0  70   0   2]
- [  8   1   3   2   0  38   5]
- [ 13   5   6  15   9  17  61]]
-Node Classification on random seed  6242 -> 0.655
-Confusion Matrix:
- [[ 82   2   1   4   3   3  15]
- [  2 118   6   2   6   3   7]
- [ 22  12 166  42  18  14  38]
- [  9   5  12 102  20   3  11]
- [  0  10   3   0  64   0   2]
- [  3   2   4   2   5  32   7]
- [ 11   2   8   7   6  13  91]]
-Node Classification on random seed  6243 -> 0.6
-Confusion Matrix:
- [[ 67   1  10   5   3  12   6]
- [  3 123   4   8   5   6   6]
- [ 25  19 131  41  38  17  44]
- [ 13   5  14 110   2   1  14]
- [  1   7   1   7  59   1   2]
- [  9   2   2   4   0  34   2]
- [  5   3  14  17  10  11  76]]
-Node Classification on random seed  6244 -> 0.595
-Confusion Matrix:
- [[ 69   3  15   4   4   8  19]
- [ 14 125   5   0   5   2   4]
- [ 18  17 150  37  25  40  39]
- [  9   7  11  88  12   4  16]
- [  2   4   3   2  59   1   2]
- [  3   2   3   3   0  32  10]
- [  8   2  14   5   7  16  72]]
-Node Classification on random seed  6245 -> 0.625
-Confusion Matrix:
- [[ 65   5   2   5   6  18   5]
- [  1 122  16   1  15   6   4]
- [ 24  16 153  26  16  27  33]
- [ 14   5  11 101  10   6  20]
- [  1   8   4   1  55   2   3]
- [  3   1   1   1   0  48   4]
- [ 14   3   4   7  15  11  81]]
-Node Classification on random seed  6246 -> 0.636
-Confusion Matrix:
- [[ 62   7   4   9   4   2  18]
- [  2 128   3   7  16   3   3]
- [ 23  18 150  39  16  26  26]
- [ 12   1  17 105   4   6  13]
- [  1   2   4   4  79   0   2]
- [  1   3   3   1   0  44   8]
- [  8   8  20   6   2  12  68]]
-Node Classification on random seed  6247 -> 0.648
-Confusion Matrix:
- [[ 74   1   5   5   2  14   6]
- [  7 129   7   2  10   3   1]
- [ 30  25 168  36  15  19  28]
- [ 26   4  11 108  10   5   5]
- [  2   4   6   1  58   2   1]
- [  9   1   0   0   3  41   4]
- [ 17   1   3   9   3   9  70]]
-Node Classification on random seed  6248 -> 0.613
-Confusion Matrix:
- [[ 59   5   4   9   6  18   8]
- [  2 128   9   2   7   4   2]
- [ 28  27 138  26  17  10  42]
- [ 10   2  14 111  10   5  16]
- [  3   8   4   0  65   0   4]
- [  6   2   4   2   2  40   5]
- [ 12   2   8  12  14  16  72]]
-Node Classification on random seed  6249 -> 0.616
-Confusion Matrix:
- [[ 66   2   2   7   2  24  13]
- [  7 117   9   0  10   0   0]
- [ 16  31 147  42  24  25  32]
- [ 14   0  12 104   9   7  24]
- [  0   5   4   6  62   0   2]
- [  1   2   2   1   2  42   5]
- [  7   3   9   4   6  13  78]]
-Node Classification on random seed  6250 -> 0.599
-Confusion Matrix:
- [[ 58   4   4   9   6  13  11]
- [  3 125   3   1  16   3   2]
- [ 41  24 142  38  13  14  42]
- [ 19   5  16  85   3  10  17]
- [  2   4   4   0  62   0   2]
- [  7   1   3   5   4  52   5]
- [ 11   4  10   7   5  10  75]]
-Node Classification on random seed  6251 -> 0.602
-Confusion Matrix:
- [[ 71   2   8   4   4  16  18]
- [  9 112  17   5   7   3   2]
- [ 21  15 130  36  22  27  45]
- [  8   2  10  95   5   5  16]
- [  3   7   3   2  68   0   0]
- [  6   0   1   1   2  50   6]
- [  8   4  11   9  11  17  76]]
-Node Classification on random seed  6252 -> 0.611
-Confusion Matrix:
- [[ 75   1   9   1   6  13  15]
- [  7 100   6   2  15   7   2]
- [ 21  24 155  42  33  14  41]
- [ 17   8  10 113   6   4  11]
- [  0   5   5   0  63   2   2]
- [  7   1   0   1   1  33   4]
- [ 15   2   7   2  10  10  72]]
-Node Classification on random seed  6253 -> 0.656
-Confusion Matrix:
- [[ 82   2   4   4   2  10   5]
- [  3 145   4   2   2   0   5]
- [ 23  20 159  29  29  16  33]
- [ 16   2  13  97   4   4  15]
- [  1  10   2   0  61   1   4]
- [  5   1   3   0   0  41   6]
- [ 14   6   9   5   5  25  71]]
-Node Classification on random seed  6254 -> 0.625
-Confusion Matrix:
- [[ 73   2   0   5   3  19  11]
- [  9 128   2   0  11   2   8]
- [ 28  23 144  29  18  26  40]
- [ 12   2  17  97   1   4  18]
- [  3   5   0   0  57   3   4]
- [  6   0   3   1   1  50   2]
- [ 14   2   7   5   8  21  76]]
-Node Classification on random seed  6255 -> 0.618
-Confusion Matrix:
- [[ 49   2   6   7   4  20  16]
- [  6 126   8   3  10   7   3]
- [ 28  18 133  33  12  26  44]
- [  6   2  17 115   0  13  10]
- [  1   7   7   0  64   2   3]
- [  1   2   3   0   1  51   7]
- [ 14   7   6   5   1  14  80]]
-Node Classification on random seed  6256 -> 0.594
-Confusion Matrix:
- [[ 58   8   6   4   4  14  17]
- [  7 111   5   1  10   3   7]
- [ 24  22 136  19  30  23  59]
- [ 13   5  18  97   5   4  19]
- [  1   8   1   0  59   0   3]
- [  3   3   4   3   1  47   1]
- [  8   3   6  12   6  16  86]]
-Node Classification on random seed  6257 -> 0.611
-Confusion Matrix:
- [[ 71   5   4   1   4  18   6]
- [  3 143   5   6   4   3   2]
- [ 29  35 135  35  25  17  21]
- [ 31   5  12  89   7   5   6]
- [  0   5   2   3  59   1   6]
- [  2   5   6   2   2  46   2]
- [ 16   8  10   7  10  13  68]]
-Node Classification on random seed  6258 -> 0.61
-Confusion Matrix:
- [[ 68   2   6   8   0   8   8]
- [  4 143   2   7   3   2   8]
- [ 22  24 125  42  33  33  32]
- [  6   9  10  88  13   8  14]
- [  0   9   3   0  71   0   2]
- [  8   0   7   1   0  34   6]
- [  9   4   9   8  12   8  81]]
-Node Classification on random seed  6259 -> 0.669
-Confusion Matrix:
- [[ 66   7   5   6   1  13   6]
- [  1 128   9   2   9   3   3]
- [ 27  22 161  22  20  16  38]
- [  6   9  18 105   3   2   7]
- [  3   7   3   4  70   0   1]
- [  4   2   2   3   0  44   3]
- [ 10   4   5   5   6  14  95]]
-Node Classification on random seed  6260 -> 0.634
-Confusion Matrix:
- [[ 81   1   0   5   6  16   2]
- [  5 119   5   4   5   1   6]
- [ 30  22 145  45  25  19  32]
- [  3   1   7 106   3   8  24]
- [  3   3   4   4  64   0   4]
- [  5   0   1   7   0  35   6]
- [ 18   1   8   5   7  15  84]]
-Node Classification on random seed  6261 -> 0.608
-Confusion Matrix:
- [[ 67   5   4   6   7  13  14]
- [  1 136   4   1   4   7   5]
- [ 35  14 113  27  27  29  48]
- [ 10   1  26 108   9   8  11]
- [  2   6   2   0  50   4   2]
- [  9   0   2   0   0  44   7]
- [ 18   4   9   0   6   5  90]]
-Node Classification on random seed  6262 -> 0.634
-Confusion Matrix:
- [[ 69   5   4   4   1  14  11]
- [  5 137   7   0   6   2   5]
- [ 27  22 154  15  24  29  32]
- [  5   5  28  95   9   8  16]
- [  1  11   4   0  69   0   1]
- [  1   4   3   1   0  42   6]
- [  9   4  10   5   7  15  68]]
-Node Classification on random seed  6263 -> 0.626
-Confusion Matrix:
- [[ 61   2   3   4   5  19  10]
- [  9 116   5   1  13   1   0]
- [ 13  19 174  28  32  15  37]
- [ 20   3  26  99   2   7   6]
- [  0   8   5   5  57   0   3]
- [  5   3   2   2   4  42   1]
- [  6   2  14   4  14  16  77]]
-Node Classification on random seed  6264 -> 0.603
-Confusion Matrix:
- [[ 56   2   6   2   5  10  17]
- [  1 117   6   5  11   1   3]
- [ 21  21 143  22  36  32  39]
- [  9   1  21  91  14   5  22]
- [  1   8   8   0  59   0   1]
- [  7   0   4   3   2  44   9]
- [ 10   1   6   4  11  10  93]]
-Node Classification on random seed  6265 -> 0.594
-Confusion Matrix:
- [[ 60   5  13   2   4  15  10]
- [  7 125  10   2   2   1   4]
- [ 23  25 115  31  31  33  59]
- [ 15   2  16 112   7   5   8]
- [  1   3   4   3  63   2   1]
- [  3   3   2   0   0  46   4]
- [ 12   4   8   2   4  20  73]]
-Node Classification on random seed  6266 -> 0.583
-Confusion Matrix:
- [[ 75   0   5   4   1   8  14]
- [  5 128   5   6   7   4   5]
- [ 34  10 119  44  48  23  39]
- [ 19   4   9 112  14   4  12]
- [  1   6   5   2  54   1   4]
- [  2   0   1   1   0  31  15]
- [ 13   2  16  10   6   8  64]]
-Node Classification on random seed  6267 -> 0.642
-Confusion Matrix:
- [[ 69   9   4   4   3   8  12]
- [  4 135   7   5   8   2   1]
- [ 18  20 150  58  18  11  36]
- [ 13   4  15 118   3   4   3]
- [  1   8   3   3  58   0   2]
- [  5   5   1   1   1  45   5]
- [ 15   2  11   9   2  14  67]]
-Node Classification on random seed  6268 -> 0.606
-Confusion Matrix:
- [[ 70   1   8   2  12   6   5]
- [  0 130   1   3  12   2   1]
- [ 18  28 131  46  26  24  41]
- [ 23   7  24  84   6   9  10]
- [  0   4   6   0  56   1   0]
- [  7   1   6   4   0  41   7]
- [  8   2   8   6   7  12  94]]
-Node Classification on random seed  6269 -> 0.599
-Confusion Matrix:
- [[ 71   3  16   4   2  15   4]
- [ 12 133   3   1   7   6   0]
- [ 13  21 135  45  32  11  46]
- [ 18   1  16  89  15   4  10]
- [  5   7   4   1  55   3   0]
- [  6   1   3   3   0  45   6]
- [ 13   3  10   8   5  18  71]]
-Node Classification on random seed  6270 -> 0.626
-Confusion Matrix:
- [[ 67   3   5   7   4  15  11]
- [  6 113  12   3  13   2   2]
- [ 26  16 150  26  36  21  31]
- [  9   2  15 119   0   4  16]
- [  6   3   3   3  62   0   1]
- [  9   1   2   1   2  38   8]
- [ 26   2   6   6   6   4  77]]
-Node Classification on random seed  6271 -> 0.642
-Confusion Matrix:
- [[ 74   5   8   9   4  10   5]
- [  4 136   9   6   5   2   3]
- [ 26  24 137  26  31  19  33]
- [  6   8  17 110   3   5   6]
- [  0   5   5   2  54   0   2]
- [  2   3   2   3   2  49   4]
- [  9   4   7  15   8  11  82]]
-Node Classification on random seed  6272 -> 0.616
-Confusion Matrix:
- [[ 80   2   3   5   4  11   9]
- [  5 107  10   2  15   4   3]
- [ 28  23 156  36  19  24  31]
- [ 18   7   7 123   2   4   7]
- [  3   8   5   2  55   0   0]
- [  2   1   5   2   0  45   4]
- [ 19   2  13  13  11  15  50]]
-Node Classification on random seed  6273 -> 0.6
-Confusion Matrix:
- [[ 72   3   8   8   2  11   7]
- [  4 130   4   2   3   6   6]
- [ 38  22 136  24  26  21  36]
- [ 21   4  21  78   5   8  19]
- [  3   7   2   1  65   0   2]
- [  6   3   2   0   1  50   4]
- [ 20   8  12   1  10   9  69]]
-Node Classification on random seed  6274 -> 0.587
-Confusion Matrix:
- [[ 74   5   5   6   2  10  15]
- [  1 125  13   7   3   2  10]
- [ 21  43 127  43  16  36  18]
- [ 15   4  17 103   8   6  22]
- [  0   4   7   2  51   1   0]
- [  9   2   0   2   1  40  14]
- [  9   3  12   2  10   7  67]]
-Node Classification on random seed  6275 -> 0.596
-Confusion Matrix:
- [[ 57   3   5  15   3   2  10]
- [  3 138   4   2   3   1   8]
- [ 29  12 117  35  37  25  59]
- [ 11   3  18 108  10   2  12]
- [  0  11   5   1  57   0   4]
- [  8   1   2   1   0  38   6]
- [  6   4  11   7   9  16  81]]
-Node Classification on random seed  6276 -> 0.653
-Confusion Matrix:
- [[ 85   1   2   5   5   9  18]
- [  3 128   9   8   8   2   1]
- [ 22  29 145  34  16  22  26]
- [ 11   4  10 119   3   4   8]
- [  2   6   6   3  57   0   1]
- [  0   0   4   4   1  45   8]
- [  8   8  10   4  11  11  74]]
-Node Classification on random seed  6277 -> 0.584
-Confusion Matrix:
- [[ 76   3   6  10   8   8   5]
- [  5 121   9   4   5   2   3]
- [ 24  29 127  44  25  19  33]
- [ 25   7  23  73  20   0  10]
- [  2   9   1   3  56   0   2]
- [  6   0   2   2   0  48  14]
- [  3   3  18  14   4   6  83]]
-Node Classification on random seed  6278 -> 0.65
-Confusion Matrix:
- [[ 80   2   2   5   5  17   4]
- [  1 146   2   4   3   2   7]
- [ 20  17 155  25  35   8  53]
- [ 12   4   9  79  16   4   5]
- [  0   6   3   3  65   0   5]
- [ 10   1   1   2   3  45   6]
- [  7   3   6   8   8  16  80]]
-Node Classification on random seed  6279 -> 0.624
-Confusion Matrix:
- [[ 50   3  12  13   1  10  13]
- [  4 132   6   1   4   3   7]
- [ 26  31 159  26  31  11  35]
- [  8   6  25 118   4   3   7]
- [  0  13   2   1  47   1   2]
- [  1   2   6   0   3  40   6]
- [  9   7  12   6   2  13  78]]
-Node Classification on random seed  6280 -> 0.604
-Confusion Matrix:
- [[ 65   0  12   4   7  14   9]
- [  8 143   2   5  10   1  10]
- [ 24  15 128  22  27  29  64]
- [  7   3  23 103   6  10   7]
- [  2   3   1   1  53   3   2]
- [  8   2   2   0   0  39   4]
- [  9   4   6   9   7  14  73]]
-Node Classification on random seed  6281 -> 0.6
-Confusion Matrix:
- [[ 65   6   3   4   2  14   3]
- [  1 126   6   5   6   1   5]
- [ 19  19 147  27  22  14  53]
- [ 13   2  10  88   4   5  30]
- [  1   9   5   2  64   1   1]
- [  5   2   7   2  10  34   5]
- [ 13   5  13  14  11  20  76]]
-Node Classification on random seed  6282 -> 0.621
-Confusion Matrix:
- [[ 62   5   4  12   3   6   6]
- [  3 137   7   3  14   1   3]
- [ 41  25 149  42  21   9  24]
- [ 10   3  27 104   8   1  10]
- [  2   7   2   2  57   0   1]
- [ 17   2   2   0   1  32   7]
- [ 21   5   9   3   3   7  80]]
-Node Classification on random seed  6283 -> 0.587
-Confusion Matrix:
- [[ 74   5   9   4   5  13   5]
- [  6 132  10   0   2   6   8]
- [ 39  15 118  30  24  19  56]
- [ 19   3  19  87   8   5  12]
- [  1   8   8   0  60   0   3]
- [  7   5   1   1   2  42   4]
- [ 15   3   3   2   7  21  74]]
-Node Classification on random seed  6284 -> 0.583
-Confusion Matrix:
- [[ 68   4   5   9   6   8  11]
- [  3 119   9   4   8   2   7]
- [ 35  18 135  34  27  21  37]
- [  9   3  14 112   5   8   7]
- [  1   7   5   6  66   3   1]
- [ 12   2   2   1   7  30   4]
- [ 14   5  12  13   4  24  53]]
-Node Classification on random seed  6285 -> 0.629
-Confusion Matrix:
- [[ 64   2   2   9   7  10  10]
- [  4 126   7   4   7   0   7]
- [ 23  42 144  31  22  10  43]
- [ 14   9  11 116   3   1   8]
- [  3   4   6   1  59   0   2]
- [ 16   0   4   1   1  37   2]
- [ 10   3   4  11   5  12  83]]
-Node Classification on random seed  6286 -> 0.635
-Confusion Matrix:
- [[ 71   4   5   4   3  12   2]
- [  6 122   3   0   8   5   5]
- [ 22  16 147  31  37  12  47]
- [  9   1  17 108   7   8  23]
- [  1   3   2   0  63   7   3]
- [  5   1   2   0   0  43   6]
- [ 16   5   6   5   7   9  81]]
-Node Classification on random seed  6287 -> 0.629
-Confusion Matrix:
- [[ 92   3   2   7   3   8   7]
- [  6 129   6   7   4   4   7]
- [ 18  31 117  41  19  23  44]
- [  5   4  20 118   4   2   5]
- [  0   8   5   1  62   1   3]
- [  7   2   0   3   0  42   5]
- [ 16   5   5   3   9  18  69]]
-Node Classification on random seed  6288 -> 0.604
-Confusion Matrix:
- [[ 75   0   7   3   3  11   3]
- [  7 121   4   3  10   2   8]
- [ 22  19 113  35  37  29  40]
- [ 12   3   4 127  10   5   5]
- [  0   8   3   4  64   1   2]
- [  9   3   2   3   1  48   3]
- [ 17   8  10  13   4  23  56]]
-Node Classification on random seed  6289 -> 0.609
-Confusion Matrix:
- [[ 67   0   2   9   8  22   3]
- [  0 130   3   2  14  10   4]
- [ 32  21 155  34  16  21  42]
- [ 14   0  28  88   2   4  11]
- [  1  11   6   2  62   1   1]
- [  9   0   0   0   2  39   4]
- [  5   3   9   8   8  19  68]]
-Node Classification on random seed  6290 -> 0.661
-Confusion Matrix:
- [[ 99   3   3   8   1   6   5]
- [ 10 136   9   3   6   1   1]
- [ 28  29 151  31  15  18  25]
- [ 15  11   6 113   3   7   7]
- [  4   1   9   5  51   1   1]
- [ 12   1   2   0   5  33   3]
- [ 17   3   8   5   6   5  78]]
-Node Classification on random seed  6291 -> 0.647
-Confusion Matrix:
- [[ 74   2   7   3   3  19   2]
- [  9 140   9   1   4   4   6]
- [ 14  26 153  25  20  22  31]
- [  5   2  13 116   5   8  12]
- [  2   4   4   0  64   3   1]
- [  3   0   6   1   1  47   4]
- [ 15   4  13   4  11  25  53]]
-Node Classification on random seed  6292 -> 0.624
-Confusion Matrix:
- [[ 66   9   5   4   6  12  15]
- [  0 114   3   1  18   0   4]
- [ 10  16 176  20  32  26  34]
- [ 11   6  19  78   7  13  16]
- [  0   4   3   3  57   4   3]
- [  5   2   1   1   1  53   5]
- [ 16   4  11   7   5  14  80]]
-Node Classification on random seed  6293 -> 0.615
-Confusion Matrix:
- [[ 59   2  11   6   5  16   2]
- [  4 131   2   1   2   2   5]
- [ 13  25 166  42  19  20  47]
- [ 14   9   7  86   5   9  10]
- [  0   8   2   0  53   2   4]
- [  4   1   3   8   0  52   7]
- [ 13  11   8  17   3  16  68]]
-Node Classification on random seed  6294 -> 0.597
-Confusion Matrix:
- [[ 66   2   2   5   1  14  14]
- [  6 109  20   3   8   1   3]
- [ 42  18 144  43  26  19  26]
- [ 11   7  22  99   7   8   8]
- [  0   9   3   1  63   0   4]
- [  7   0   1   5   1  41   4]
- [ 13   3  10   7   7  12  75]]
-Node Classification on random seed  6295 -> 0.598
-Confusion Matrix:
- [[ 76   0   3   4   4   6  15]
- [  4 125   5   2   5   3   0]
- [ 21  37 121  48  56  20  22]
- [ 10   5  14 114   6   5  10]
- [  3   3   4   1  58   0   9]
- [  7   0   7   0   1  39   9]
- [ 16   4   8   8   6  11  65]]
-Node Classification on random seed  6296 -> 0.612
-Confusion Matrix:
- [[ 71   7   2   6   7   6   7]
- [  2 133   6   0   1   5   5]
- [ 24  31 161  23  30  17  35]
- [ 14   9  18  82   4  18  12]
- [  2   9   5   0  56   2   3]
- [ 12   0   1   0   0  43   9]
- [ 13   3  10   7   8  15  66]]
-Node Classification on random seed  6297 -> 0.632
-Confusion Matrix:
- [[ 73   1   4  10   4   5   6]
- [  4 133   4   5   6   5   2]
- [ 22  34 137  27  32  18  38]
- [ 14   5  17 116   5   7   5]
- [  1   8   0   0  62   1   4]
- [  1   1   0   1   0  37   9]
- [ 13   3   3  16  13  14  74]]
-Node Classification on random seed  6298 -> 0.613
-Confusion Matrix:
- [[ 80   1   0   4   3   9   7]
- [  5 101  20   1   9   1   5]
- [ 15  18 139  35  33  27  51]
- [  6   1  23  99   4   7  24]
- [  1   2   3   0  65   1   2]
- [  4   0   6   0   1  37   3]
- [ 14   1  10   5   5  20  92]]
-Node Classification on random seed  6299 -> 0.614
-Confusion Matrix:
- [[ 70   0   9   4   6  18   3]
- [  1 142   7   0   6   1   0]
- [ 18  30 123  42  48  16  42]
- [ 12   6  15  94   8   3  13]
- [  0   8   1   0  73   1   1]
- [  7   4   2   2   0  46   2]
- [ 13   0   3   6   5  23  66]]
-Node Classification on random seed  6300 -> 0.585
-Confusion Matrix:
- [[ 65   1   3   4   2  17   7]
- [  5 104   8   0  13   2   6]
- [ 31  15 125  56  35  13  42]
- [ 25   3  12  82   4   4  15]
- [  3   5   0   2  73   2   4]
- [  5   1   2   0   0  50  10]
- [ 20   2   7   4  11  14  86]]
-Node Classification on random seed  6301 -> 0.561
-Confusion Matrix:
- [[ 60   1   7   4   2  10  14]
- [  4 131   4   5   7   5   3]
- [ 30  22  98  71  22  24  51]
- [ 14  16  20  93   4   7   7]
- [  1   7   1   3  64   0   3]
- [  0   3   2   0   2  47   6]
- [  9   7   3  17   4  17  68]]
-Node Classification on random seed  6302 -> 0.616
-Confusion Matrix:
- [[ 66   1   4   4  11   7  14]
- [  6 135   7   2  11   2   2]
- [ 17  27 161  34  15  24  33]
- [ 16   4  20 107   2   5   5]
- [  0   9  11   3  45   0   2]
- [  7   2   4   3   0  40   9]
- [  9   1  19  13   8  11  62]]
-Node Classification on random seed  6303 -> 0.62
-Confusion Matrix:
- [[ 71   1   9   1   4  10   5]
- [  4 118   9   3   3   4   3]
- [ 26  22 140  47  16  23  46]
- [  8   1  14 118   2   8  10]
- [  2  11   3   3  54   2   3]
- [  1   2   1   0   0  58   5]
- [ 17   3   8  15   9  16  61]]
-Node Classification on random seed  6304 -> 0.56
-Confusion Matrix:
- [[ 59   2   7   5   2   9  21]
- [  1 116  17   1   4   3  17]
- [ 16  17 113  42  44  27  44]
- [  8   2  17 104   6   3  22]
- [  2   9   9   0  54   2   2]
- [  9   0   4   2   1  41   4]
- [  6   0  13   8   9  23  73]]
-Node Classification on random seed  6305 -> 0.607
-Confusion Matrix:
- [[ 71   2  10   8   3  12   5]
- [  3 123   6   2   7   0   3]
- [ 18  25 145  41  18  26  28]
- [ 27   2  18  92   7   2  10]
- [  0   6   7   2  64   3   4]
- [  6   1   5   1   2  36  11]
- [ 10   3  21   4   3  21  76]]
-Node Classification on random seed  6306 -> 0.627
-Confusion Matrix:
- [[ 69   1   3   8   2   9  11]
- [  5 118   1   7   6   4   8]
- [ 31  10 132  51  25  20  31]
- [ 16   1  12 111  10   7  11]
- [  3   5   8   1  63   4   1]
- [  1   2   1   2   0  53   5]
- [ 14   1   3   7   8  17  81]]
-Node Classification on random seed  6307 -> 0.618
-Confusion Matrix:
- [[ 82   2   2   2   8  19   4]
- [  6 114   6   6   8   0   2]
- [ 30  17 136  45  12  26  35]
- [  9   6  26  94   3   5   9]
- [  2   5   6   2  64   2   4]
- [  3   2   2   0   1  56   1]
- [ 18   5   4  11   2  24  72]]
-Node Classification on random seed  6308 -> 0.614
-Confusion Matrix:
- [[ 72   1   1   6   3  15  24]
- [ 12 107   5   1  13   1   5]
- [ 15  20 137  45  27  17  45]
- [  6   1  12  97   7   7  18]
- [  1   5   5   2  62   1   5]
- [  5   1   2   1   0  60   5]
- [  6   4   7   6   8  15  79]]
-Node Classification on random seed  6309 -> 0.583
-Confusion Matrix:
- [[ 57   6   4   8   9  16   4]
- [  7 123   6   4   7   3   8]
- [ 34  22 139  32  24  27  38]
- [  9   7  15  93   7   8  14]
- [  2   4   4   1  54   0   7]
- [  9   1   4   2   3  38   6]
- [  9   2  12   5  10  17  79]]
-Node Classification on random seed  6310 -> 0.591
-Confusion Matrix:
- [[ 69   9  10   8   5  13   2]
- [  2 111  18   5   8   1   5]
- [ 25  17 135  55  24  24  36]
- [ 13   6  11  87  10   7  13]
- [  1   3   7   2  56   1   2]
- [  3   1   3   1   0  48   6]
- [  8   3  17   6   4  14  85]]
-Node Classification on random seed  6311 -> 0.633
-Confusion Matrix:
- [[ 69   4   4   6   9  16   9]
- [  3 133   7   0   7   2   1]
- [ 32  21 153  33  18  17  29]
- [ 24   2   5  91   1  10  16]
- [  3   7   2   2  73   3   1]
- [  1   2   4   0   1  49   4]
- [ 15   6  12   3   5  20  65]]
-Node Classification on random seed  6312 -> 0.638
-Confusion Matrix:
- [[ 82   5   2   7   3  16   1]
- [  2 120   5   5   9   0   2]
- [ 22   7 142  48  38  25  27]
- [ 23   2   8 103   7   9   9]
- [  2   6   5   1  59   0   2]
- [  0   6   4   0   2  50   8]
- [  5   4   3  12   4  16  82]]
-Node Classification on random seed  6313 -> 0.601
-Confusion Matrix:
- [[ 65   6  10   5   2   9  18]
- [  3 140   6   3   8   0   3]
- [ 15  19 135  31  31  21  49]
- [ 19   5   9  98  12   5  11]
- [  4   4   8   0  57   1   3]
- [  3   5   4   1   0  36   7]
- [  8   8  10  13   8  12  70]]
-Node Classification on random seed  6314 -> 0.584
-Confusion Matrix:
- [[ 63   0   6   9   1  11   9]
- [  5 118   5  15   8   5   5]
- [ 42  13 139  41  22  27  45]
- [ 11   2  18  94   4   5  17]
- [  2   7   5   1  62   1   0]
- [  8   2   3   1   1  39   7]
- [ 14   3  11   5   8  11  69]]
-Node Classification on random seed  6315 -> 0.564
-Confusion Matrix:
- [[ 66   0   7  10   5  11  15]
- [  7 125   2   1   5   5   2]
- [ 40  21 104  41  35  36  50]
- [ 21   0  16  80   6   8  13]
- [  0   5   3   0  65   1   2]
- [  6   2   3   3   1  44   2]
- [  6   6  15   2   4  18  80]]
-Node Classification on random seed  6316 -> 0.633
-Confusion Matrix:
- [[ 90   2   4   1   2   9   6]
- [  2 109   9   5   4   1   0]
- [ 29  20 153  27  26  17  41]
- [ 16   9   9 110   4   6  15]
- [  1   4  10   1  59   2   2]
- [ 10   1   4   1   0  41   4]
- [ 18   5  14   3   6  17  71]]
-Node Classification on random seed  6317 -> 0.649
-Confusion Matrix:
- [[ 66   4   3   4   4   7  14]
- [  4 137   4   4   9   1   4]
- [ 24  18 159  30  14  18  41]
- [  6   3  25 103   1   7  17]
- [  5  10   1   1  59   0   1]
- [  2   0   3   3   1  50   6]
- [  7   1  13   9   6  16  75]]
-Node Classification on random seed  6318 -> 0.646
-Confusion Matrix:
- [[ 70   0   3   4   8  22   8]
- [  1 111  14   2   9   2   6]
- [ 15  26 152  40  17  13  43]
- [ 15   4  10 114   6  10   7]
- [  2   7   7   0  62   2   2]
- [  4   1   3   1   2  44   6]
- [  8   4   2   5   2  11  93]]
-Node Classification on random seed  6319 -> 0.622
-Confusion Matrix:
- [[ 65   2   4  10   5   6  14]
- [  6 135   4   2   9   6   5]
- [ 19  29 149  27  29  24  35]
- [ 17   7   6  94  12   4  12]
- [  1   6   3   3  57   0   6]
- [  5   0   1   2   1  48   8]
- [ 10   1   6   9  11  11  74]]
-Node Classification on random seed  6320 -> 0.651
-Confusion Matrix:
- [[ 69   1   3  10   1  14   7]
- [  2 142   2   4   5   4   5]
- [ 20  27 146  41  19  22  44]
- [  7   5   7 115   3   7  10]
- [  0   6   3   4  50   0   4]
- [  8   2   2   4   0  50   2]
- [  0   4   7   6   4  23  79]]
-Node Classification on random seed  6321 -> 0.631
-Confusion Matrix:
- [[ 85   0   5   2   0   7  12]
- [  8 127   2   2  17   3   7]
- [ 34  24 128  25  35  28  36]
- [ 17   4  24  98   5   2  11]
- [  1   0   1   1  72   0   0]
- [  3   1   1   7   1  40   6]
- [ 16   4   7   2   4   4  81]]
-Node Classification on random seed  6322 -> 0.589
-Confusion Matrix:
- [[ 65   6   3  13   6  17  17]
- [  6 111  10   1   9   4   4]
- [ 35  13 122  53  23  20  39]
- [ 10   2  15 108   4   6  13]
- [  0   4   6   2  66   0   4]
- [  5   0   1   4   0  56   9]
- [  7   2   3   6   9  20  61]]
-Node Classification on random seed  6323 -> 0.617
-Confusion Matrix:
- [[ 59   5  12   1   3  15  12]
- [  6 122   3   5  17   3   5]
- [ 18  14 140  47  14  20  44]
- [  9   7  18  99   7   4  11]
- [  2   4   6   0  65   0   4]
- [  5   1   3   1   0  53   8]
- [ 21   2   8   3   4  11  79]]
-Node Classification on random seed  6324 -> 0.649
-Confusion Matrix:
- [[ 67   4   6   8   2   7   3]
- [  0 139   8   1   5   5   5]
- [ 22  19 165  40  27   8  28]
- [ 12   4  23 103   3   7  11]
- [  1  10   6   1  57   1   2]
- [  7   2   2   0   1  45  10]
- [ 15   2  10   8   9   6  73]]
-Node Classification on random seed  6325 -> 0.612
-Confusion Matrix:
- [[ 73   1   7   3   4  14   1]
- [  1 121   8   1   9   3   4]
- [ 33   9 131  45  23  30  41]
- [  8   1  17 115   2   8   4]
- [  5   4   7   0  67   0   2]
- [  5   1   5   2   4  49   5]
- [ 11   4  11  11  12  22  56]]
-Node Classification on random seed  6326 -> 0.612
-Confusion Matrix:
- [[ 72   3   9   2   2   5   9]
- [  1 115  13   2  12   2   3]
- [ 16  23 139  44  32  16  36]
- [  6   6  16 121   3  13   5]
- [  1   5   0   2  59   2   1]
- [  6   2   5   1   1  54   7]
- [ 17   3  14  19   5  18  52]]
-Node Classification on random seed  6327 -> 0.621
-Confusion Matrix:
- [[ 73   2   5   7   4   9  17]
- [  5 139   6   3   4   3   3]
- [ 35  21 117  38  30  32  31]
- [  7   6   9 108   2   6  14]
- [  1   8   1   4  67   0   2]
- [  7   1   3   1   0  45   6]
- [  4   2   6   9   3  22  72]]
-Node Classification on random seed  6328 -> 0.574
-Confusion Matrix:
- [[ 85   5   4   3   2  12   8]
- [  7 136   2   6   8   7   3]
- [ 35  19 111  52  28  35  35]
- [ 19   5   4  75  12  15  15]
- [  0   8   0   2  54   1   7]
- [  6   3   2   0   0  44   9]
- [ 12   4   5   9   5  12  69]]
-Node Classification on random seed  6329 -> 0.588
-Confusion Matrix:
- [[ 72   3   9   6   7   9  14]
- [  3 121   4   2   1   3   3]
- [ 16  19 126  53  30  24  43]
- [  8   5  34  84   3   7  14]
- [  1   3   7   2  58   1   0]
- [  6   4   0   2   1  45  14]
- [  9   4  15   6   7  10  82]]
-Node Classification on random seed  6330 -> 0.562
-Confusion Matrix:
- [[ 52   7   1   8   6  18  16]
- [  1 129   5   4   3   7   7]
- [ 32  16 100  50  21  44  55]
- [ 21   1   5 105   5   9  14]
- [  2   3   3   1  48   4   2]
- [  2   0   0   2   0  44   6]
- [ 13   4   6   6   5  23  84]]
-Node Classification on random seed  6331 -> 0.66
-Confusion Matrix:
- [[ 78   3   1   7   2  15  12]
- [  2 124   5   3   8   1   1]
- [ 12  17 195  38  14  17  41]
- [ 10   5  14 105   4   1  17]
- [  0   5   4   0  65   0   7]
- [  2   3   0   1   6  37   6]
- [ 11   2   7  12   8  16  56]]
-Node Classification on random seed  6332 -> 0.606
-Confusion Matrix:
- [[ 50   2   2   7   1  10  13]
- [  2 124   6   2  14   3   9]
- [ 37  25 141  21  20  33  44]
- [ 14   2  20 103   3   4  15]
- [  2   7   1   1  54   1   5]
- [  8   0   2   0   0  45   6]
- [ 10   4  13   4   3  18  89]]
-Node Classification on random seed  6333 -> 0.625
-Confusion Matrix:
- [[ 71   7   7   8   2   7  15]
- [  7 121   8   4  12   1   3]
- [ 20  21 169  22  24  16  39]
- [  9   6  14  92   5   7  19]
- [  2   7   4   1  67   0   2]
- [  6   4   4   6   0  29   1]
- [ 12   4  15   2   9  13  76]]
-Node Classification on random seed  6334 -> 0.622
-Confusion Matrix:
- [[ 77   6   8   2   3   9   4]
- [  3 116  10   1  25   3   2]
- [ 33  12 149  37  18  17  34]
- [ 10   4  22  98   7   8  11]
- [  3   3   5   4  60   2   2]
- [ 10   1   0   1   0  44   4]
- [ 14   8   6   8   7  11  78]]
-Node Classification on random seed  6335 -> 0.607
-Confusion Matrix:
- [[ 70   2   5   3   4   6  14]
- [  4 140   9   4   5   0   4]
- [ 33  30 128  26  33  23  36]
- [  7   4  18 113   4   7  10]
- [  1   7   2   4  62   1   5]
- [  9   0   7   2   0  33   9]
- [ 15   4   7   7   5  17  61]]
-Node Classification on random seed  6336 -> 0.648
-Confusion Matrix:
- [[ 74   3   4   5   2  12   9]
- [ 17 130   7   0   4   0   8]
- [ 17  22 148  33  23   7  60]
- [ 10   4  11 109   2   5  15]
- [  2   5   2   1  49   1   0]
- [  6   3   1   0   1  31   8]
- [ 12   1   1  12   6  10 107]]
-Node Classification on random seed  6337 -> 0.538
-Confusion Matrix:
- [[ 73   1   2   2   5   7  12]
- [ 10 121   5   3   3   2   2]
- [ 25  26  93  57  47  26  50]
- [ 20   3  25  87   4   9  16]
- [  3   7   1   1  60   3   6]
- [  8   2   2   1   0  44   3]
- [ 16   4  10  14   4  15  60]]
-Node Classification on random seed  6338 -> 0.591
-Confusion Matrix:
- [[ 85   0   2   4   1  12   8]
- [  3 129   4   3  13   2   3]
- [ 25  45 108  49  10  30  45]
- [ 12   6  20  82   8   5  14]
- [  2   5   3   0  60   0   0]
- [  6   4   1   3   0  44   4]
- [ 18   1  11   7   5  15  83]]
-Node Classification on random seed  6339 -> 0.589
-Confusion Matrix:
- [[ 82  13   5   3   1  10   7]
- [  7 114  14  11   3   0   4]
- [ 33  20 139  41  14  19  47]
- [ 18   3  17  88   1   9  15]
- [  6   6  12   0  47   0   3]
- [  9   4   2   2   0  41   6]
- [ 11   2  12   7   8   6  78]]
-Node Classification on random seed  6340 -> 0.582
-Confusion Matrix:
- [[ 71   1   7  10   5  10   3]
- [  3 133   5   4   3   7   3]
- [ 29  29 123  28  56  29  21]
- [ 12   8  27  82   5   6  10]
- [  1   4   1   1  63   1   3]
- [  7   2   0   2   1  34  16]
- [ 10   5  12   9   8  14  76]]
-Node Classification on random seed  6341 -> 0.604
-Confusion Matrix:
- [[ 67   4   8   0   4  24   7]
- [  5 127  11   1   8   0   3]
- [ 23  16 117  42  41  19  45]
- [  5   4  15  95   4   4  11]
- [  0   9   6   2  66   3   4]
- [  7   1   0   2   2  51   3]
- [ 17   4   3   7   6  16  81]]
-Node Classification on random seed  6342 -> 0.623
-Confusion Matrix:
- [[ 63   2   2   7   4  10  16]
- [  2 129   9   3   3   4   9]
- [ 18  23 139  33  20  22  50]
- [ 14   1  15 102   8   4  10]
- [  1   7   8   0  61   0   5]
- [  2   1   1   1   1  59   2]
- [ 10   2  17   5   3  22  70]]
-Node Classification on random seed  6343 -> 0.584
-Confusion Matrix:
- [[ 73   1   5   6   7   9   9]
- [  1 139  11   5   8   2   4]
- [ 38  17  90  49  27  30  26]
- [ 22   3  16  97   3  10  13]
- [  0   8   4   7  54   0   8]
- [  5   1   4   3   0  40   7]
- [  7   3  11  13   4   9  91]]
-Node Classification on random seed  6344 -> 0.615
-Confusion Matrix:
- [[ 70   2   2   3   6  16  13]
- [  6 122   6   7   5   2   9]
- [ 22  22 130  49  26  23  46]
- [ 10   3  11 107   8   5   8]
- [  1  10   0   6  63   1   4]
- [  4   2   2   3   1  49   5]
- [  6   6   4   2   2  16  74]]
-Node Classification on random seed  6345 -> 0.589
-Confusion Matrix:
- [[ 63   7   7   6   3  13   8]
- [  8 105   2   2  19   7   3]
- [ 24  19 128  49  31  22  38]
- [ 10   4   9 108  15   2  18]
- [  1   5   1   2  58   0   3]
- [ 12   1   2   1   0  44   2]
- [ 15   5   4   7  10  14  83]]
-Node Classification on random seed  6346 -> 0.637
-Confusion Matrix:
- [[ 75   2   4   5   4   6  16]
- [  4 121   5   3   6   2  10]
- [ 21   9 174  34  26  20  38]
- [  8   3  18 111   7   2  16]
- [  1   3   3   6  51   1   2]
- [  3   3   4   1   2  34   5]
- [ 11   6  11  12   2  18  71]]
-Node Classification on random seed  6347 -> 0.627
-Confusion Matrix:
- [[ 60   0   8   3   3  14   3]
- [  4 134   7   2  16   1   5]
- [ 24  18 161  33  20  27  39]
- [ 13   8   8  90   2  19  12]
- [  1   2   4   3  70   0   3]
- [  3   2   4   0   2  48   2]
- [ 10   4   7   3   7  27  64]]
-Node Classification on random seed  6348 -> 0.606
-Confusion Matrix:
- [[ 78   3   3  10   5  20   7]
- [  3 116   4   3  14   1   8]
- [ 28  12 145  34  23  28  22]
- [ 14   2  13  90  10  14   8]
- [  8   5   8   0  55   0   5]
- [  5   2   0   0   0  46   7]
- [ 22   3   6  11   8  15  76]]
-Node Classification on random seed  6349 -> 0.589
-Confusion Matrix:
- [[ 60   2   3   2   2  11  17]
- [  6 122   7   4   5   1   3]
- [ 18  27 145  25  24  19  53]
- [ 12   1  18  97   6   4  21]
- [  1  11   1   3  70   0   1]
- [  2   3   4   3   2  41  10]
- [ 15   5  11   6  22  20  54]]
-Node Classification on random seed  6350 -> 0.647
-Confusion Matrix:
- [[ 74   0   2   1   5   7   9]
- [  2 111   6   3  17   3   3]
- [ 20  23 152  33  24  32  39]
- [ 16   3  12 121   1   3  10]
- [  2   5   3   2  64   2   1]
- [  2   1   3   0   0  48   8]
- [  4   8   8   8   9  13  77]]
-Node Classification on random seed  6351 -> 0.62
-Confusion Matrix:
- [[ 56   1   2  13   6   6  16]
- [  9 125   6   4  21   9   1]
- [ 31  11 156  27  29  24  38]
- [ 10   2  14  92   7  14   6]
- [  1   4   2   3  65   4   1]
- [  2   1   2   1   0  49   4]
- [  9   2   5   1  10  21  77]]
-Node Classification on random seed  6352 -> 0.6
-Confusion Matrix:
- [[ 63   8   7   6   6   8  10]
- [  8 109   7   2  12   2   2]
- [ 26  26 130  30  55  15  28]
- [ 15   3   9 117  12   4  13]
- [  1   6   1   1  62   0   1]
- [  2   0  10   1   7  26   6]
- [  3   3  10   8  10  16  93]]
-Node Classification on random seed  6353 -> 0.646
-Confusion Matrix:
- [[ 82   6   4   2   1   4  11]
- [  1 122   3   1  14   1   6]
- [ 20  15 184  42  24  12  35]
- [  9   6  12  94  12   3  20]
- [  1   6   5   0  51   0   1]
- [  8   1   3   3   1  49   3]
- [ 12   4  12  10   6  14  64]]
-Node Classification on random seed  6354 -> 0.605
-Confusion Matrix:
- [[ 76   7   5   3   4  13   8]
- [  4 130   8   7   8   0   1]
- [ 26  46 119  29  19  22  37]
- [  9   0  12 116   5   0  18]
- [  0   8   5   5  62   0   1]
- [  4   2   2   5   0  40   4]
- [  4   3  11  10  26  14  62]]
-Node Classification on random seed  6355 -> 0.659
-Confusion Matrix:
- [[ 61   1   2   2   2   9  16]
- [  6 135   2   5   5   0   3]
- [ 20  22 174  29  18  26  36]
- [ 10   5  25  99   2   7  16]
- [  5   5   2   3  62   1   3]
- [  1   3   3   0   0  45   8]
- [  9   2  11   2   3  11  83]]
-Node Classification on random seed  6356 -> 0.599
-Confusion Matrix:
- [[ 64   4  10  10   1   1  12]
- [  6 139   5   6   3   0   4]
- [ 37  17 128  55  16  30  29]
- [ 12   4  20  84   3  20   9]
- [  6   4   4   5  71   1   0]
- [  7   1   2   1   0  42   3]
- [ 13   3  15   5   5  12  71]]
-Node Classification on random seed  6357 -> 0.586
-Confusion Matrix:
- [[ 69   1   6   2   5   8   8]
- [  3 133  15   5   1   1   9]
- [ 13  28 121  36  20  29  49]
- [ 15   5  12 101  11  10  12]
- [  2   2   3   2  59   2   5]
- [  4   0   1   1   2  41  11]
- [  9   9   6   8  12  31  62]]
-Node Classification on random seed  6358 -> 0.601
-Confusion Matrix:
- [[ 74   2   2  11   4   6   6]
- [  3 120   5   3   4   8   4]
- [ 35  39 118  49  18  23  38]
- [  8   2   9 108   2   4  17]
- [  0   7   5   2  56   3   0]
- [  9   1   2   3   1  51   6]
- [ 10   7   9   7   5  20  74]]
-Node Classification on random seed  6359 -> 0.608
-Confusion Matrix:
- [[ 82   2   8   2   2   7   5]
- [  1 112   5   1   5   4   9]
- [ 25  14 121  51  50  18  33]
- [  6   1  18 107  14   7  12]
- [  3   6   2   5  65   0   5]
- [  5   2   2   2   0  50  10]
- [ 10   3  15   3   6  13  71]]
-Node Classification on random seed  6360 -> 0.627
-Confusion Matrix:
- [[ 83   1   6   5   1  12   0]
- [  9 124   5   1   7   2   3]
- [ 23  21 134  63  24  21  26]
- [ 24   3   5 121   4   5   4]
- [  3   7   0   0  62   0   4]
- [  3   6   2   1   2  39   0]
- [ 14   6  12   6   9  23  64]]
-Node Classification on random seed  6361 -> 0.598
-Confusion Matrix:
- [[ 66   6   2   6   8  13  16]
- [  2 128   2   5   6   4   0]
- [ 23  15 141  32  32  15  46]
- [ 14   4   8 101   2  11  22]
- [  0   8   7   0  61   1   2]
- [  2   2   4   3   0  40  12]
- [ 13   5  13  11  12  13  61]]
-Node Classification on random seed  6362 -> 0.632
-Confusion Matrix:
- [[ 76   2   7   7   4   5  11]
- [  8 130   5   3   5   0   6]
- [ 19  21 129  42  27  27  39]
- [  8   2  17 100   5   7  14]
- [  1   8   3   1  67   1   2]
- [  4   0   0   4   0  50  10]
- [  6   6   4   4   7  16  80]]
-Node Classification on random seed  6363 -> 0.547
-Confusion Matrix:
- [[ 63   2   2  15   4  15   8]
- [  4 125   4   2   3   1   5]
- [ 47  22  92  49  65  28  36]
- [  8   4   9  94  13   8  14]
- [  1  10   4   0  58   3   3]
- [  7   1   2   1   1  49   5]
- [  8   2  12   7   7  11  66]]
-Node Classification on random seed  6364 -> 0.631
-Confusion Matrix:
- [[ 52   2   7   5   4   6  20]
- [  0 141  13   4   8   5   6]
- [ 10  14 145  31  30  12  51]
- [  3   4  16 107  13   5  25]
- [  1   6   2   4  58   4   1]
- [  5   1   1   1   0  48   5]
- [  7   5  10   6   4  12  80]]
-Node Classification on random seed  6365 -> 0.627
-Confusion Matrix:
- [[ 68   4   5   3   3  14   5]
- [  2 118   7   5  12   4   0]
- [ 18   7 153  34  16  25  51]
- [  9   5  17 106   6   5  18]
- [  1  10   7   3  56   2   2]
- [  6   4   2   2   0  47   3]
- [  8   3  15   1  17  12  79]]
-Node Classification on random seed  6366 -> 0.617
-Confusion Matrix:
- [[ 56   1   1   2   2  20   7]
- [  6 126   5   2  11   2   6]
- [ 24  14 150  23  28  35  38]
- [ 14   1  16 109   4  12  13]
- [  2   6   2   2  56   2   4]
- [  3   1   2   1   0  51   1]
- [  4   1  16   8  10  31  69]]
-Node Classification on random seed  6367 -> 0.619
-Confusion Matrix:
- [[ 72   2   3   1   1  10  12]
- [ 12 134   5   2   7   2  10]
- [ 15  33 139  30  19  34  36]
- [ 11   8  21  93   2   5  12]
- [  8   5   4   0  54   0   0]
- [  6   1   2   1   1  40   9]
- [ 20   5   8   3   5  10  87]]
-Node Classification on random seed  6368 -> 0.625
-Confusion Matrix:
- [[ 70   2   3   4   0  12  21]
- [  3 122   3   3  10   0  14]
- [ 17  32 135  29  22  17  43]
- [ 11   1   8 118   3   5  13]
- [  2   7   4   4  59   0   3]
- [ 11   0   0   3   1  45   9]
- [ 16   7  10   4   7  11  76]]
-Node Classification on random seed  6369 -> 0.604
-Confusion Matrix:
- [[ 70   2   5   1   6   2  22]
- [  6 140   8   1   3   1   9]
- [ 26  14 133  33  24  18  59]
- [ 18   1  12  92   4   9   9]
- [  1   9   4   1  55   0   9]
- [  6   6   2   0   1  36   6]
- [ 14   0  13   8   6  17  78]]
-Node Classification on random seed  6370 -> 0.64
-Confusion Matrix:
- [[ 60   3  13   3   6   8   7]
- [  3 134   4   3   5   6   1]
- [ 21  21 157  34  42  20  26]
- [ 11   4  18 110   2   9   8]
- [  3   4   3   3  60   3   3]
- [  2   0   5   3   2  46   4]
- [  9   1  19   2   3  13  73]]
-Node Classification on random seed  6371 -> 0.619
-Confusion Matrix:
- [[ 72   1  13   6   4  12   3]
- [  2 133   4   2   5   1   0]
- [ 12  43 142  37  17  29  29]
- [ 12   3  22 111   2   3   4]
- [  1   8   5   4  57   0   0]
- [  3   1   9   4   3  41   6]
- [  9   6  20   6   5  25  63]]
-Node Classification on random seed  6372 -> 0.586
-Confusion Matrix:
- [[ 60   3   4   7   6  16   4]
- [  8 122   5   3   7   4   4]
- [ 48  20 148  14  23  27  38]
- [  5   5  24  92  15   9   7]
- [  1   9   1   0  57   3   4]
- [ 10   0   2   1   1  48   3]
- [ 16   2  11   8  12  24  59]]
-Node Classification on random seed  6373 -> 0.615
-Confusion Matrix:
- [[ 73   6   2   4   2   7   4]
- [  4 122   6   2   3   0   2]
- [ 21  33 149  34  21  34  22]
- [ 25   5  16 101   5  15   5]
- [  1   6   6   2  58   1   3]
- [  8   2   2   1   0  51   2]
- [ 22   3  15  11   3  19  61]]
-Node Classification on random seed  6374 -> 0.614
-Confusion Matrix:
- [[ 75   2   4   3   4   6  17]
- [ 13 121   7   4   7   3   5]
- [ 24  20 139  27  21  20  41]
- [ 19  11  14  88  13  16  12]
- [  1   4   4   2  65   1   3]
- [  2   4   0   0   1  43   6]
- [  3   5  12   8   3  14  83]]
-Node Classification on random seed  6375 -> 0.624
-Confusion Matrix:
- [[ 75   2   5   5   5  12   6]
- [  1 126   6   5  19   6   1]
- [ 29   8 140  43  21  30  30]
- [  6   3  12 106   5  10  15]
- [  2  10   4   2  53   1   2]
- [  4   1   2   0   0  45   3]
- [ 12   6   6  11   8  17  79]]
-Node Classification on random seed  6376 -> 0.64
-Confusion Matrix:
- [[ 70   5   9   4   1   5  13]
- [  5 117   5   2  13   0   5]
- [ 24  12 153  32  33   4  38]
- [  9   1  17 107  10  10  16]
- [  2   5   5   0  74   1   3]
- [  4   1   6   5   0  45   3]
- [ 12   0  10  15   6   9  74]]
-Node Classification on random seed  6377 -> 0.664
-Confusion Matrix:
- [[ 60   3  11   4   0  11  14]
- [  4 114   3   3  16   3   3]
- [ 17  17 164  23  37  17  31]
- [  7   5  16 115   3   7   7]
- [  2   2   3   1  63   0   2]
- [  3   0   0   1   2  53   6]
- [  8   2   9  16   5  12  95]]
-Node Classification on random seed  6378 -> 0.624
-Confusion Matrix:
- [[ 73   0   6   1   2  12   9]
- [  5 112   3   6  14   4   2]
- [ 25   8 136  22  49  22  59]
- [  6   1  12 121   4   3  12]
- [  0   2   3   4  70   2   3]
- [  7   2   1   0   2  42   8]
- [  9   6  12   8   7  13  70]]
-Node Classification on random seed  6379 -> 0.629
-Confusion Matrix:
- [[ 57   1  15   7   3  11  13]
- [ 22 120   5   1   7   3   6]
- [ 33   9 151  31  25  20  37]
- [  6   4   6 105  11   3  13]
- [  1   6   5   1  63   0   2]
- [  6   1   3   2   2  43   4]
- [ 12   1  13   3   1  16  90]]
-Node Classification on random seed  6380 -> 0.621
-Confusion Matrix:
- [[ 74   4   4   3   6   8  12]
- [  7 132   6   1  11   1   8]
- [ 17  31 140  46  17  18  31]
- [ 23   8  10  96   4  10  14]
- [  0   3   4   2  57   1   1]
- [ 10   1   1   6   0  36  13]
- [  9   1   7   8   4   8  86]]
-Node Classification on random seed  6381 -> 0.598
-Confusion Matrix:
- [[ 54   3  10   6   3  16   7]
- [  0 102   8   7  11   4  15]
- [ 30  16 170  49  30  20  19]
- [ 11   3  25  80   9   5  13]
- [  1   4   4   0  64   2   1]
- [  3   3   4   0   0  43   8]
- [  9   2  16   7   7  11  85]]
-Node Classification on random seed  6382 -> 0.631
-Confusion Matrix:
- [[ 69   2   6   4   6   8  14]
- [  0 149   3   1   4   2   0]
- [ 26  27 139  40  23  18  40]
- [  9   7  17 101   5   7   9]
- [  0   7   4   2  57   2   3]
- [  5   3   2   2   3  37   2]
- [  6   7   9   3  19  12  79]]
-Node Classification on random seed  6383 -> 0.651
-Confusion Matrix:
- [[ 69   3   2   2   8   4  16]
- [  4 112  12   4  13   3   1]
- [ 15  26 168  26  23  17  37]
- [  3   1  16 114  11   6  13]
- [  1  11   6   0  55   2   1]
- [  5   2   3   0   3  51   1]
- [ 11   8   2   6  10  11  82]]
-Node Classification on random seed  6384 -> 0.589
-Confusion Matrix:
- [[ 63   5   5   4   9   5  16]
- [  5 126   6   7   4   0   7]
- [ 20  21 123  41  33  12  62]
- [ 22   7  13 100   7   1  10]
- [  3   7   7   0  64   0   2]
- [ 12   2   2   4   0  34   4]
- [ 11   6   8   6   5  10  79]]
-Node Classification on random seed  6385 -> 0.661
-Confusion Matrix:
- [[ 74   1   3   1   4  12  15]
- [  9 137   2   4   8   5   8]
- [ 25  27 172  10  14  20  25]
- [  8   4  16 101   3   4  15]
- [  6   6   4   2  61   3   1]
- [ 10   7   6   0   0  36   1]
- [ 13   5   3   6   6  17  80]]
-Node Classification on random seed  6386 -> 0.664
-Confusion Matrix:
- [[ 69   6  11   2   1  12  10]
- [ 10 122   2   4   9   1   1]
- [ 25  12 169  36  22  13  40]
- [  6   1   9 123   6   2  20]
- [  3   9   4   2  51   0   2]
- [ 14   2   3   0   2  43   1]
- [  5   4   6  11   4   3  87]]
-Node Classification on random seed  6387 -> 0.616
-Confusion Matrix:
- [[ 57   5  11  14   1  12   7]
- [  4 130  11   4   7   0   1]
- [ 17  23 146  34  29  36  23]
- [  9   5  13 108   3   7   5]
- [  3   8   5   3  59   0   1]
- [  6   3   3   4   1  41   5]
- [  5   3  15  12   5  21  75]]
-Node Classification on random seed  6388 -> 0.618
-Confusion Matrix:
- [[ 78   4  10   2   1  13  10]
- [  7 131   2   4   7   1   0]
- [ 16  21 137  48  31  10  42]
- [ 18   6  22  96   6   4  13]
- [  2   9   6   1  54   0   5]
- [  4   1   5   0   0  46   2]
- [ 10   2   2   4  14  17  76]]
-Node Classification on random seed  6389 -> 0.629
-Confusion Matrix:
- [[ 68   3   3   4   4   8  15]
- [  3 123   3   6  21   2   3]
- [ 16  22 140  29  34  25  40]
- [ 11   8   6 104   0   6  17]
- [  1   6   5   3  64   0   2]
- [  2   3   2   0   4  51   6]
- [  7   4  14   6   7  10  79]]
-Node Classification on random seed  6390 -> 0.583
-Confusion Matrix:
- [[ 67   3   3   2   3  12   7]
- [  4 110   8   4  23   3   2]
- [ 24  29 134  42  29  15  42]
- [ 21   4  17 100   5   3  11]
- [  1   6   4   2  49   1   3]
- [  6   1   4   2   0  53   6]
- [  8   4  20   5   7  21  70]]
-Node Classification on random seed  6391 -> 0.621
-Confusion Matrix:
- [[ 70   6   4   8   4  12  12]
- [  3 135   8  13   6   0   3]
- [ 27  12 171  44  15  17  27]
- [ 10   5   6  92  21   4  18]
- [  1   7   7   2  45   0   1]
- [ 11   0   1   1   0  37   5]
- [ 25   3   9   3   5  13  71]]
-Node Classification on random seed  6392 -> 0.632
-Confusion Matrix:
- [[ 72   1   8   5   4  11   6]
- [  7 144   2   1   7   6   8]
- [ 27  49 131  27  26  26  46]
- [ 10   5  13 105   7   3   6]
- [  2   9   2   0  59   1   1]
- [  2   0   0   3   1  46   1]
- [  0   4   4   4   5  18  75]]
-Node Classification on random seed  6393 -> 0.638
-Confusion Matrix:
- [[ 75   0   1   1   5  11  13]
- [  5 118   6   1   6   5   3]
- [  8  24 159  23  27  35  36]
- [ 15   4  19 103   2   6  18]
- [  1   6   5   0  50   2   1]
- [  3   1   4   1   1  53   4]
- [  4   3   9   4   9  30  80]]
-Node Classification on random seed  6394 -> 0.606
-Confusion Matrix:
- [[ 60   8   3   5   9  13  12]
- [  8 126   3   3  14   1   3]
- [ 19  11 137  38  34  18  39]
- [ 11   4  18  99  10   7  10]
- [  1   2   5   2  56   2   6]
- [  9   1   0   2   0  38   9]
- [ 11   3   9  14   9   8  90]]
-Node Classification on random seed  6395 -> 0.616
-Confusion Matrix:
- [[ 74   5   4   3   3   5  10]
- [  3 135   4   7   2   3   5]
- [ 20  31 115  47  18  18  54]
- [ 12   2   9  98   1   3  13]
- [  2   8   1   6  63   4   1]
- [  3   3   2   4   4  40   9]
- [ 10   9   5   8   7  16  91]]
-Node Classification on random seed  6396 -> 0.627
-Confusion Matrix:
- [[ 72   1   3  10   1  13   7]
- [  6 137   9   2   4   1   2]
- [ 39  14 140  21  36  15  42]
- [ 12   1  14  98   7  11   6]
- [  0   7   6   1  54   1   2]
- [  5   0   8   2   1  45   2]
- [ 17   1  11   1   6  25  81]]
-Node Classification on random seed  6397 -> 0.646
-Confusion Matrix:
- [[ 69   6   1   6   2  23   7]
- [  0 123   8   1   3   7   2]
- [ 17  17 154  37  20  30  39]
- [ 22   3   7 102   4   8  10]
- [  2   4   3   4  55   2   0]
- [  7   3   3   0   0  61   2]
- [  5   6   7   4   3  19  82]]
-Node Classification on random seed  6398 -> 0.579
-Confusion Matrix:
- [[ 69   1   5   8   5  12   9]
- [  3 115   4   0  23   8   4]
- [ 16  16 109  24  76  22  32]
- [ 11   4  22  88   5   5  13]
- [  2   6   1   1  66   2   1]
- [ 10   0   4   3   3  45   3]
- [  6   6   9   5   9  22  87]]
-Node Classification on random seed  6399 -> 0.574
-Confusion Matrix:
- [[ 79   4   7   9   1  11   4]
- [  4 109   2   6   7   2  10]
- [ 26  25 101  46  38  44  27]
- [ 13   2  20 109   7   8  14]
- [  1   5   7   1  50   1   1]
- [ 10   0   4   4   0  51   3]
- [ 14   5  10   2   4  17  75]]
-Node Classification on random seed  6400 -> 0.63
-Confusion Matrix:
- [[ 61   3   1   5   6  17  10]
- [  3 129   3   1   5   2   4]
- [ 27  21 165  28  27  24  21]
- [ 15   0  16 104  15   2  14]
- [  2  10   2   0  49   0   5]
- [ 13   3   4   2   1  36   3]
- [  8   1  11   8   9  18  86]]
-Node Classification on random seed  6401 -> 0.589
-Confusion Matrix:
- [[ 67   2   7   1   1  23  12]
- [  3 128   7   1   1   2   5]
- [ 22  33 114  40  27  23  44]
- [ 12   6  25  97  15  10   8]
- [  0   7   7   2  62   2   1]
- [  5   0   2   2   0  42   7]
- [  3  11  10   1   4  17  79]]
-Node Classification on random seed  6402 -> 0.659
-Confusion Matrix:
- [[ 71   3   2   8   5   9   9]
- [  4 130   4   3  13   0   4]
- [ 24   9 166  31  23  35  40]
- [ 15   0   9 120   4   4   4]
- [  5   6   5   1  51   2   3]
- [  5   1   1   4   0  42   3]
- [ 11   2   5  10   3  12  79]]
-Node Classification on random seed  6403 -> 0.61
-Confusion Matrix:
- [[ 72   2   2   2   2  16  16]
- [  5 125   3   4  13   3   2]
- [ 22  16 122  37  24  32  52]
- [ 18   6  20  99   6   4   8]
- [  3   6   1   3  50   0   3]
- [  5   1   2   0   0  57   7]
- [  5   4   7   6  10  12  85]]
-Node Classification on random seed  6404 -> 0.605
-Confusion Matrix:
- [[ 80   0   1   6   3  10   6]
- [  0 136  12   1   2   5   2]
- [ 16  29 118  42  35  13  39]
- [ 20   6   8  93   7  12  20]
- [  3  11   0   2  61   3   1]
- [  9   3   2   4   1  46   3]
- [ 14   5   6  15   7  11  71]]
-Node Classification on random seed  6405 -> 0.613
-Confusion Matrix:
- [[ 63   5   3   5   2  12  17]
- [ 11 127  11   1   7   1   2]
- [ 18  29 151  33  23  25  32]
- [ 13   4  17  93   4   8  13]
- [  3   6   8   0  60   2   1]
- [  3   0   1   2   0  48   8]
- [ 12   6  15   2   9  13  71]]
-Node Classification on random seed  6406 -> 0.615
-Confusion Matrix:
- [[ 75   3   7   5   3   5  11]
- [  2 113   6   5  18   1   7]
- [ 16  17 147  39  33  30  28]
- [ 11   6  22 110   5   5  12]
- [  1   3   6   1  59   0   7]
- [  4   0   3   3   0  47   4]
- [  8   1  16  16   7   8  64]]
-Node Classification on random seed  6407 -> 0.623
-Confusion Matrix:
- [[ 80   2   3   5   3  13   4]
- [  5 137   4   0  14   2   1]
- [ 21  12 160  25  28  35  35]
- [ 11   4  24  92   7   5  11]
- [  2   8   6   2  48   1   3]
- [ 11   1   0   2   1  46   2]
- [ 17   3  10  11   6  17  60]]
-Node Classification on random seed  6408 -> 0.621
-Confusion Matrix:
- [[ 59   3   6   4   3  14  19]
- [  7 126   5   0  13   1   8]
- [ 24  13 146  37  29  21  42]
- [  7   3  17 100   2   5  16]
- [  3   7   3   7  58   1   2]
- [  2   0   3   2   1  57   6]
- [  9   3   5   8   4  14  75]]
-Node Classification on random seed  6409 -> 0.613
-Confusion Matrix:
- [[ 75   3  15   4  10   4   3]
- [  1 141  10   2  11   1   3]
- [ 22  38 122  42  25  13  36]
- [  4   7  13 112   5   8   6]
- [  0  11   3   2  55   0   3]
- [  5   4   7   2   0  43   5]
- [ 19   1  14   8   7  10  65]]
-Node Classification on random seed  6410 -> 0.557
-Confusion Matrix:
- [[ 58   5   2   3   5  18  10]
- [  5 114   7   1   7   6  11]
- [ 24  22 128  36  22  41  39]
- [ 11   5  38  83  10   8  11]
- [  2   7   5   3  62   2   5]
- [  6   1   4   3   0  46   3]
- [ 14   2   2   8  11  18  66]]
-Node Classification on random seed  6411 -> 0.559
-Confusion Matrix:
- [[ 59   4   1  11   8  10  18]
- [  0 117   8   3   8   5   9]
- [ 36  21 148  32  30  19  35]
- [ 30   1   8  83   6  12  10]
- [  0   7   3   0  52   0   5]
- [  4   2   1   1   0  39   9]
- [ 26   5   6  23  11  13  61]]
-Node Classification on random seed  6412 -> 0.63
-Confusion Matrix:
- [[ 66   2   3   6   5  11   8]
- [  4 137   1   5   2   2   2]
- [ 11  16 149  49  13  17  49]
- [  9   6   9 110   7  12   9]
- [  2   3   7   4  66   0   2]
- [  5   0   8   5   0  40   3]
- [ 19   4  12  12   4  22  62]]
-Node Classification on random seed  6413 -> 0.618
-Confusion Matrix:
- [[ 63   3   6   4   3  16  11]
- [  1 117   7   2   9   4  11]
- [ 19  23 157  22  27  32  40]
- [ 13   1  10  93   1   4  17]
- [  2   8   2   0  55   1   3]
- [  6   3   2   4   0  53   5]
- [  6   3  10   5  15  21  80]]
-Node Classification on random seed  6414 -> 0.621
-Confusion Matrix:
- [[ 70   3   0   3   0  14  16]
- [  2 121   4   3  10   3   5]
- [ 20  28 154  39  30  30  23]
- [ 10   8  18 100   1   7  12]
- [  2   1   3   2  68   0   4]
- [  8   0   4   1   0  49   1]
- [ 11   3   4   4  19  23  59]]
-Node Classification on random seed  6415 -> 0.609
-Confusion Matrix:
- [[ 70   6   2   1   0  11  19]
- [  2 114   6   3   6   1  15]
- [ 33  27 152  28  26  13  33]
- [  9  12  20  96   6   1  16]
- [  2   5   1   1  55   0   4]
- [ 12   2   2   0   2  37  12]
- [  9   4  12   8   8  11  85]]
-Node Classification on random seed  6416 -> 0.596
-Confusion Matrix:
- [[ 74   5   3   6   1  14  11]
- [  2 121  10   4   8   6   5]
- [ 22  27 107  47  25  22  48]
- [  4   6  20  99   7   5   7]
- [  0  14   2   0  62   0   4]
- [  2   4   3   2   2  54   5]
- [  8   6   8   9   4  16  79]]
-Node Classification on random seed  6417 -> 0.61
-Confusion Matrix:
- [[ 63   5   5   7   3  18  15]
- [  2 117   5   1   3   2   3]
- [ 21  28 147  43  21  19  36]
- [  7   2  25 103   1   4  19]
- [  1  16   2   2  53   0   4]
- [  3   1   8   3   1  44  13]
- [  9   4   8   4   6  10  83]]
-Node Classification on random seed  6418 -> 0.606
-Confusion Matrix:
- [[ 72   5   3   2   4   7  19]
- [  1 116  12   0  10   7   3]
- [ 28  11 129  54  29  15  31]
- [ 10   5  11 101   4  10  27]
- [  0   4   4   1  52   1   3]
- [  5   5   2   4   1  38   8]
- [ 14   1   4   9   4  16  98]]
-Node Classification on random seed  6419 -> 0.611
-Confusion Matrix:
- [[ 66   7   3   2   3   6  19]
- [  4 145   4   3   3   3   3]
- [ 22  26 122  30  41  18  56]
- [ 10   4  19  87   2   6  12]
- [  1   4   2   1  68   0  10]
- [  5   0   2   0   2  42   8]
- [ 12   3   6   7   7  13  81]]
-Node Classification on random seed  6420 -> 0.573
-Confusion Matrix:
- [[ 72   3   8   7   3  12   6]
- [  5 119   5   1   8   7   4]
- [ 16  33 116  45  41  20  41]
- [ 19   5  10 106   2   5  12]
- [  5   8   2   0  46   0   2]
- [  3   0   4   2   2  51   7]
- [ 12   8  13  25   6  10  63]]
-Node Classification on random seed  6421 -> 0.618
-Confusion Matrix:
- [[ 61   2   3  10   1  16  10]
- [  5 139   3   4   3   3   3]
- [ 32  26 135  58  15  20  34]
- [  7   4   9 119   3   4  10]
- [  2  12   7   0  49   1   6]
- [  2   2   4   3   0  44   4]
- [ 10   4   9   5   5  21  71]]
-Node Classification on random seed  6422 -> 0.63
-Confusion Matrix:
- [[ 87   1   3   5   6   4   8]
- [  2 115   3   3   8   1   4]
- [ 22  26 137  37  35  14  42]
- [  6   8   8 117   5   3  22]
- [  3   8   3   0  60   0   1]
- [  6   3   3   1   1  41   6]
- [ 11   8  15   7   6  12  73]]
-Node Classification on random seed  6423 -> 0.599
-Confusion Matrix:
- [[ 84   4   5   3   3   6  10]
- [  6 128   9   0   5   2  16]
- [ 28  24 110  20  62  20  39]
- [  5   8   8 113   7   7   8]
- [  4   4   4   2  66   0   1]
- [ 10   1   3   4   0  44   3]
- [  9   3   1  10  19  18  54]]
-Node Classification on random seed  6424 -> 0.61
-Confusion Matrix:
- [[ 57   2  11   9  11  11   8]
- [  4 129   9   3  12   0   8]
- [ 24  19 148  36  24  31  33]
- [ 14   0  11 102   7   9  17]
- [  1   4   3   1  67   4   2]
- [  2   1   4   0   1  38   6]
- [  8   1  12   6   5  16  69]]
-Node Classification on random seed  6425 -> 0.61
-Confusion Matrix:
- [[ 83   3   0   3   6  11   2]
- [ 12 133   4   1   5   2   3]
- [ 28  14 129  28  36  25  51]
- [ 15   4  13 101   3  17   9]
- [  1  11   5   4  55   1   3]
- [ 10   1   0   1   1  40   1]
- [ 16   4   7   7   7  15  69]]
-Node Classification on random seed  6426 -> 0.569
-Confusion Matrix:
- [[ 72   1   8   3   8  17   7]
- [  4 125  13   0  14   1  11]
- [ 17  22 121  51  47  16  24]
- [ 11   4  19  84  22   7   8]
- [  1   1   1   2  58   6   4]
- [  5   3   1   2   1  49   6]
- [ 10   2  13  11  10  17  60]]
-Node Classification on random seed  6427 -> 0.611
-Confusion Matrix:
- [[ 79   2   8  10   1  20   3]
- [  2 136   2   3   5   5   6]
- [ 38  26 111  47  13  40  21]
- [  7   7  10 113   2   5  11]
- [  0  10   5   1  57   1   3]
- [  2   0   0   0   0  51   1]
- [ 16   4  11   8   6  27  64]]
-Node Classification on random seed  6428 -> 0.603
-Confusion Matrix:
- [[ 63   4   2   3   3   8  26]
- [ 12 135   6   1  11   2   8]
- [ 22  13 121  33  49  12  58]
- [  7   5   5 110   6  13   5]
- [  1   6   1   1  55   0   3]
- [ 11   2   0   1   0  42   3]
- [  5   3   8  23   6   9  77]]
-Node Classification on random seed  6429 -> 0.62
-Confusion Matrix:
- [[ 65   3   4   6   3  24  11]
- [  2 118   6   2   8   0   3]
- [ 20  29 160  24  15  31  33]
- [  7   3  21 113   1   8  12]
- [  0   9   6   4  49   1   3]
- [  4   4  17   0   1  44   2]
- [ 10   3   3   8  16  13  71]]
-Node Classification on random seed  6430 -> 0.594
-Confusion Matrix:
- [[ 54   1   1   9   7  24  17]
- [  1 131   0   3   6   3   5]
- [ 43  29 127  27  30  22  28]
- [ 10   6  16  90  15   7  13]
- [  2   6   0   0  61   0   3]
- [  1   2   6   1   1  51   6]
- [  7   3   3  16   4  22  80]]
-Node Classification on random seed  6431 -> 0.644
-Confusion Matrix:
- [[ 79   4   8   3   2  17   9]
- [  6 111  10   4   9   3   2]
- [ 26  12 152  39  27  16  23]
- [ 17   2  14 118   8   7  12]
- [  2   2   6   1  56   0   0]
- [  6   2   1   1   0  55   3]
- [  7   3  21   3   6  12  73]]
-Node Classification on random seed  6432 -> 0.596
-Confusion Matrix:
- [[ 81   7   6   6   0  14  17]
- [  1 109   4   1  18   4   5]
- [ 31  18 133  28  43  35  26]
- [  5   0   9 110   6   8   5]
- [  2   4   2   3  62   0   1]
- [  4   0   8   3   1  30  11]
- [  7   2  16  18  10  15  71]]
-Node Classification on random seed  6433 -> 0.604
-Confusion Matrix:
- [[ 72   2   3   4   2   7  12]
- [  5 112   8   4  17   0   8]
- [ 11  27 128  38  27  29  52]
- [  8   3  17 120   2   5   5]
- [  2   2   5   4  57   2   2]
- [  2   0   5   6   3  39  11]
- [ 10   2  25   5   5   9  76]]
-Node Classification on random seed  6434 -> 0.6
-Confusion Matrix:
- [[ 43   2   2   3   7  21  23]
- [  6 128  11   6   4   0   4]
- [ 12  23 143  32  33  34  32]
- [  6   4  13 107   3   7  19]
- [  1   6   3   2  60   1   3]
- [  7   1   4   1   3  44   4]
- [  5   7   2   6  12  25  75]]
-Node Classification on random seed  6435 -> 0.643
-Confusion Matrix:
- [[ 62   5   5   6   2   8  17]
- [  1 137   4   3   3   0   5]
- [ 10  30 151  32  22  14  51]
- [  6   8  13 108   5   7  13]
- [  0   8   6   2  51   1   3]
- [  8   3   0   4   0  45   9]
- [ 12   6   7   7   3   8  89]]
-Node Classification on random seed  6436 -> 0.587
-Confusion Matrix:
- [[ 54   5   6  10   6  15  13]
- [  5 118   5   2  15   2   4]
- [ 55  27 155  18  21  19  35]
- [ 16   4  16  99   6   5  17]
- [  3   2   6   0  62   0   2]
- [ 12   2   1   2   0  34   5]
- [ 20   5  12   6   3   5  65]]
-Node Classification on random seed  6437 -> 0.594
-Confusion Matrix:
- [[ 57   3  12  12   7  12   7]
- [  2 126   5   5   3   5   4]
- [ 19  19 116  61  18  28  51]
- [  9   2  13 119   4   6  11]
- [  1  10   3   1  60   1   1]
- [  5   2   1   3   3  48   2]
- [  5   2  11   9   3  25  68]]
-Node Classification on random seed  6438 -> 0.596
-Confusion Matrix:
- [[ 71   1   5   9   5  12  10]
- [  5 109   4   2  14   4   2]
- [ 25  22 137  47  33  22  50]
- [ 13   9  11  98   8   3   8]
- [  1   8   2   0  72   0   2]
- [  4   2   2   7   0  36   6]
- [  8   4   4  11   9  10  73]]
-Node Classification on random seed  6439 -> 0.588
-Confusion Matrix:
- [[ 79   1   1   3   6  19  13]
- [  3 116   8   2  12   5   5]
- [ 31   8 149  25  18  23  59]
- [  5   2  19  97   8   9  13]
- [  4   6   4   4  52   2   0]
- [  7   0   3   4   3  33   8]
- [  8   0   5  13  19  24  62]]
-Node Classification on random seed  6440 -> 0.604
-Confusion Matrix:
- [[ 48   5   4   6   4   9  21]
- [  6 106   5   1  17   1   3]
- [ 23  15 158  44  14  31  45]
- [ 15   2  16 107   3   8  17]
- [  1   2   7   0  59   0   5]
- [  4   2   2   1   2  44   9]
- [  9   3  14   5   5  10  82]]
-Node Classification on random seed  6441 -> 0.617
-Confusion Matrix:
- [[ 77   6   7   0   3  10   2]
- [  5 130   6   6   8   0   5]
- [ 21  19 148  43  23  39  31]
- [ 12   2  21  88   6   5  10]
- [  3   4  14   4  56   0   3]
- [  6   2   3   0   0  45   3]
- [ 16   9   2   7   6  11  73]]
-Node Classification on random seed  6442 -> 0.615
-Confusion Matrix:
- [[ 57   3   3   4   6  16   8]
- [  0 122   9   2   9   3   8]
- [ 18  16 135  55  23  27  27]
- [  9   3  24 124   2   4  10]
- [  0   7   6   2  51   0   4]
- [  2   1   2   2   1  47   4]
- [  4   5  14  14  14  14  79]]
-Node Classification on random seed  6443 -> 0.579
-Confusion Matrix:
- [[ 51   4   6  16   5   1  21]
- [  3 120   8   3  14   4   5]
- [ 33  11 143  39  28  15  44]
- [ 18   5  23  83   6  14  12]
- [  1   7   2   2  61   0   1]
- [  7   0   3   5   2  46   6]
- [  4   3  13  10   5  12  75]]
-Node Classification on random seed  6444 -> 0.583
-Confusion Matrix:
- [[ 72   1  10  13   2  18   4]
- [  4 117   8   7   8   5   3]
- [ 11  29 125  66  19  28  27]
- [  6   2  17 100   7   5  19]
- [  0  10   9   2  55   1   2]
- [  2   0   5   1   0  42   1]
- [  9   3   8   8   6  31  72]]
-Node Classification on random seed  6445 -> 0.613
-Confusion Matrix:
- [[ 69   3   3  12   8  14   5]
- [  4 126   8   2   5   2   8]
- [ 24  28 137  31  23  13  37]
- [ 17   6  14 110   5  10   8]
- [  1   9   5   1  49   0   2]
- [ 10   4   2   3   0  41   3]
- [ 24   2  11   3   7  10  81]]
-Node Classification on random seed  6446 -> 0.57
-Confusion Matrix:
- [[ 58   0  10   9   4  19  14]
- [  6 107  12   4  16   6   3]
- [ 19  16 154  39  17  27  51]
- [ 21   3  11  87   1   9  14]
- [  1   5   5   0  63   2   2]
- [  3   0   4   0   1  49   7]
- [  8   2   4  20  11  24  52]]
-Node Classification on random seed  6447 -> 0.61
-Confusion Matrix:
- [[ 78   1   0   3   0  10  20]
- [  8 140   8   0   9   2   7]
- [ 23  17 142  28  16  31  57]
- [ 17   7  11  89   2  10  15]
- [  1   6   3   2  49   0   1]
- [  7   3   2   0   4  34  13]
- [  9   5   8  11   9   4  78]]
-Node Classification on random seed  6448 -> 0.626
-Confusion Matrix:
- [[ 69   1   5   4   6  12  11]
- [  5 109   7   1  17   2   6]
- [ 16  14 157  19  33  18  43]
- [ 10   5  16 116  10   2  14]
- [  1   6   1   3  51   2   2]
- [ 18   6   4   0   3  34   3]
- [ 12   4   6   6  10  10  90]]
-Node Classification on random seed  6449 -> 0.577
-Confusion Matrix:
- [[ 66   2   6   7   4   4  23]
- [  4 140   2   0   6  10   3]
- [ 31  30 112  68  20   8  30]
- [ 21   6  19  93   2   1  15]
- [  0   8   6   0  58   0   1]
- [  9   1   7   1   4  33   6]
- [  5   1  16  13   5  18  75]]
-Node Classification on random seed  6450 -> 0.643
-Confusion Matrix:
- [[ 80   2   0   4   1   4  11]
- [  4 146   4   1   5   0   5]
- [ 31  17 148  30  31  14  33]
- [ 17   1  19  99  10   5  22]
- [  1   8   3   1  63   0   1]
- [  3   2   1   2   0  46   8]
- [  8   3  12  11   6  16  61]]
-Node Classification on random seed  6451 -> 0.603
-Confusion Matrix:
- [[ 57   6  13   7   3   7   8]
- [  6 127   6   1   8   5   5]
- [ 17  22 130  26  28  23  58]
- [  9  10  22 100   9   2  17]
- [  3   5   4   1  59   0   3]
- [  4   0   7   0   1  43   6]
- [  6   5  10   1   8  15  87]]
-Node Classification on random seed  6452 -> 0.592
-Confusion Matrix:
- [[ 67   2   7   8   5  10  10]
- [  6 109   3   3   7   2   9]
- [ 10  25 135  39  43  22  51]
- [  9   5  10  90  13   8   9]
- [  2   4   8   1  63   0   1]
- [  7   1   2   5   1  42   6]
- [  9   4   5  14  10  12  86]]
-Node Classification on random seed  6453 -> 0.614
-Confusion Matrix:
- [[ 77   2   2   3   5   8  17]
- [  3 125   2   3  14   4   0]
- [ 35  19 135  18  38  14  50]
- [  8   0   7 107   3   7  18]
- [  2   2   5   4  66   1   0]
- [  2   4   2   1   2  44   9]
- [  6   1  13   5  41   6  60]]
-Node Classification on random seed  6454 -> 0.595
-Confusion Matrix:
- [[ 62   2   6   8   2  14  23]
- [  5 131   0   4   5   1   6]
- [ 18  21 123  47  22  42  29]
- [ 10   4  17  90   2   6  23]
- [  4   7   5   0  52   4   4]
- [  4   4   1   4   1  58   3]
- [ 14   3   6   2   4  18  79]]
-Node Classification on random seed  6455 -> 0.622
-Confusion Matrix:
- [[ 72   7   3   2   2   7   4]
- [  5 122   5   2  13   3   2]
- [ 21  24 146  28  35  37  24]
- [  8   0  19 106   3   7  14]
- [  1  10   5   0  60   1   3]
- [  9   2   5   2   0  46   4]
- [ 14   3   4  13  12  15  70]]
-Node Classification on random seed  6456 -> 0.614
-Confusion Matrix:
- [[ 78   3   1   3   5  11  13]
- [  5 119   1   1  11   0  14]
- [ 26  19 142  44  26  26  31]
- [ 14   0   9 110   4   5  12]
- [  2   9   2   1  51   0   6]
- [  9   2   3   1   0  43   3]
- [ 11   4  15   8   6  20  71]]
-Node Classification on random seed  6457 -> 0.629
-Confusion Matrix:
- [[ 71   3   5   5   5   5  10]
- [  1 137   9   5   7   2   3]
- [ 27  27 135  60  11  14  22]
- [  6   1   7  96   1   2  28]
- [  1  11   2   0  71   2   5]
- [  7   3   0   2   3  41   5]
- [ 17   2  19   9   8   9  78]]
-Node Classification on random seed  6458 -> 0.611
-Confusion Matrix:
- [[ 63   4   3  11   3  15   8]
- [  0 130   5   2   3   1   7]
- [ 27  15 144  44  20  27  45]
- [  3   3  13  93   4  15  19]
- [  1   8   3   1  62   5   2]
- [  4   2   2   1   1  36  11]
- [ 10   6   8   4   8  15  83]]
-Node Classification on random seed  6459 -> 0.615
-Confusion Matrix:
- [[ 77   4   0   4   4   5  12]
- [  7 133  14   2   6   0   6]
- [ 26  30 130  36  37  25  28]
- [ 13   2  12 106   7   3   8]
- [  5   9   7   2  61   0   6]
- [  4   1   0   1   4  51   4]
- [  6   3   6  10   7  19  57]]
-Node Classification on random seed  6460 -> 0.619
-Confusion Matrix:
- [[ 70   1   4  19   1   7   6]
- [  5 117   7   7   6   1   1]
- [ 40  24 144  32  20  37  19]
- [ 11   7  15 118   0   5  15]
- [  4   5   3   2  49   2   3]
- [  7   0   1   2   3  39   4]
- [ 13   3   9   5   9  16  82]]
-Node Classification on random seed  6461 -> 0.574
-Confusion Matrix:
- [[ 58   2   3   2   8  20  13]
- [ 12 114   3   6   9   8   5]
- [ 32  20  89  32  45  22  44]
- [ 13   4  15 112   2   3  16]
- [  4   5   0   5  63   1   2]
- [  9   2   0   1   2  50   4]
- [  6   2   6   5  14  19  88]]
-Node Classification on random seed  6462 -> 0.648
-Confusion Matrix:
- [[ 69   2   3   2   2  18   7]
- [  6 106   7   3  17   4   3]
- [ 24  17 136  26  24  39  34]
- [ 14   2  14 138   1   6   7]
- [  1   6   5   1  64   1   1]
- [  3   0   0   0   1  52   5]
- [  6   4   9   1   3  23  83]]
-Node Classification on random seed  6463 -> 0.635
-Confusion Matrix:
- [[ 86   2   3   4   3   9  10]
- [  5 123   9   5   5   6   1]
- [ 23  13 148  23  30  26  36]
- [ 30   1  12 101  10   6  13]
- [  1   4   6   0  58   1   2]
- [  4   0   2   0   0  39   2]
- [ 18   1  12   5   3  19  80]]
-Node Classification on random seed  6464 -> 0.569
-Confusion Matrix:
- [[ 60   5   9   8   3  15   7]
- [ 12 135   2   7   7   5   2]
- [ 21  40 115  60  24  25  30]
- [  8   4  19  86   3  12  21]
- [  1   3   3   0  62   6   4]
- [  7   2   0   2   0  44   3]
- [ 12   5   4   8   7  15  67]]
-Node Classification on random seed  6465 -> 0.64
-Confusion Matrix:
- [[ 66   2   5   4   5  14   3]
- [  2 147   3   1   6   6   4]
- [ 17  32 146  38  24  14  39]
- [  5   1   7  97   9   4  17]
- [  3   4   5   2  70   1   0]
- [  5   1   1   2   2  33  22]
- [ 11   4   9   5   9  12  81]]
-Node Classification on random seed  6466 -> 0.612
-Confusion Matrix:
- [[ 89   2   1   1   6   8   7]
- [  5 115  14   3   2   3   3]
- [ 26  28 144  33  28  22  32]
- [ 21   2  14  88   2   5  12]
- [  2  11   1   0  66   1   5]
- [  8   2   1   0   2  45   5]
- [ 15   4  18  12   4  17  65]]
-Node Classification on random seed  6467 -> 0.618
-Confusion Matrix:
- [[ 66   3   2   4  10  16   8]
- [  3 147   4   4   8   0   6]
- [ 24  17 142  37  22  27  36]
- [  7   5  18  94  11   2  13]
- [  1   4   3   3  67   0   1]
- [  4   0   3   1   0  39   4]
- [ 16   5  10  12   6  22  63]]
-Node Classification on random seed  6468 -> 0.643
-Confusion Matrix:
- [[ 77   2   5   6   1   5   6]
- [  4 135   4   6  15   1   8]
- [ 20  15 163  37  31  22  24]
- [ 16   4  16  91   3   4  10]
- [  0   6   3   0  59   0   3]
- [  9   1   1   0   1  41  12]
- [ 16   2  17   4   8   9  77]]
-Node Classification on random seed  6469 -> 0.596
-Confusion Matrix:
- [[ 76   1   4   4   3  17   8]
- [  6 114   9   4  10   4   1]
- [ 35  25 115  37  33  30  32]
- [ 10   4   8 112   5   7   9]
- [  1   4   0   2  68   1   2]
- [ 10   1   3   1   5  46   2]
- [ 17   2  11  12   6  18  65]]
-Node Classification on random seed  6470 -> 0.63
-Confusion Matrix:
- [[ 91   5   6   4   2  11   3]
- [  3 126   1   4   5   3   5]
- [ 30  26 117  28  32  33  30]
- [  8   2  25 111   5   7   9]
- [  3   5   3   0  47   1   3]
- [  4   2   3   0   0  47   9]
- [ 10   4  11   3   5  17  91]]
-Node Classification on random seed  6471 -> 0.671
-Confusion Matrix:
- [[ 64   3   0   3   1  11  25]
- [  5 118   6   8   1   9   2]
- [ 15  17 169  35  20  18  33]
- [ 13   6  16  97   3   3   8]
- [  1   5   0   1  57   3   2]
- [  3   2   0   0   0  62  13]
- [  3   4  14   3   3  11 104]]
-Node Classification on random seed  6472 -> 0.592
-Confusion Matrix:
- [[ 85   8   3   0   4  19   9]
- [  5 108   8   4  10   3   2]
- [ 28  13 129  28  29  32  36]
- [ 29   4   8  88  12   6   7]
- [  0  10  10   5  58   2   1]
- [  4   0   3   0   2  49   2]
- [ 15   7   7   9   5  19  75]]
-Node Classification on random seed  6473 -> 0.612
-Confusion Matrix:
- [[ 67   8   3   7   3   6  10]
- [  6 128   4   0   7   3   9]
- [ 23  19 123  55  23  32  45]
- [  2   6  12 112   3   8  11]
- [  1   6   1   1  53   2   5]
- [  4   3   1   7   2  44   3]
- [ 17   3   1   5   7  14  85]]
-Node Classification on random seed  6474 -> 0.576
-Confusion Matrix:
- [[ 60   1   2   6   7  14  10]
- [  2 112   7   1  30   4   3]
- [ 36  13 149   7  29  46  43]
- [  8   1  10  80   7   8  21]
- [  0   3   3   0  69   4   1]
- [ 11   2   3   2   4  40   1]
- [ 18   4   9  12  15  16  66]]
-Node Classification on random seed  6475 -> 0.585
-Confusion Matrix:
- [[ 62   2  14   5   3  23   2]
- [  8 127   3   3  10   4   3]
- [ 27  36 126  38  35  16  30]
- [  9   8  18  96   8   4  13]
- [  0   4   1   4  69   0   5]
- [  9   5   6   1   3  36   3]
- [ 15   4   9   5   7  12  69]]
-Node Classification on random seed  6476 -> 0.588
-Confusion Matrix:
- [[ 70   5   5   4   3  13   3]
- [ 18 108   3   3   9   6   3]
- [ 24   9 124  56  31  36  29]
- [ 15   7   3  98  18   7  12]
- [  1   2   4   0  64   1   1]
- [ 12   1   3   2   1  55   1]
- [ 20   2   5   7  13  14  69]]
-Node Classification on random seed  6477 -> 0.636
-Confusion Matrix:
- [[ 63   4   2   2   2  10   7]
- [  6 143   7   1   5   2   0]
- [ 33  28 154  29  15  24  29]
- [ 12   6  22 105   3   6  14]
- [  2  11   8   3  52   1   1]
- [  7   5   6   5   1  33   3]
- [ 14   1   5   5   5  12  86]]
-Node Classification on random seed  6478 -> 0.629
-Confusion Matrix:
- [[ 58  10   5   4   2  15  21]
- [  4 127   1   3   4   0  12]
- [ 11  17 152  46  20  21  36]
- [  6   7  15 106   6   5  22]
- [  2   7   3   1  61   0   1]
- [  1   2   2   0   0  43  15]
- [  9   3  13   4   5  10  82]]
-Node Classification on random seed  6479 -> 0.609
-Confusion Matrix:
- [[ 70   4   2   5   8  14   3]
- [  8 126   9   6   5   5   5]
- [ 29  19 111  27  28  32  50]
- [ 10   4  11 112  12   9   9]
- [  1   7   3   3  58   0   1]
- [  5   0   6   1   0  43   8]
- [ 12   2   3   6   3  16  89]]
-Node Classification on random seed  6480 -> 0.6
-Confusion Matrix:
- [[ 74   8   7   3   5  16   8]
- [  5 125   8   1  12   2   0]
- [ 23  19 121  26  34  33  48]
- [ 17   5   9  97   7   3  17]
- [  1   8   2   2  69   1   3]
- [  5   0   0   1   0  42   4]
- [ 11   1  11   3  13  18  72]]
-Node Classification on random seed  6481 -> 0.601
-Confusion Matrix:
- [[ 77   4   2   6   6  10  12]
- [  9 102  10   1  14   4   5]
- [ 22  30 125  48  40  24  16]
- [ 10   2   9 123   8   4  13]
- [  2  10   4   0  61   0   1]
- [  4   1   0   2   2  37   9]
- [ 17   6   7   4   5  16  76]]
-Node Classification on random seed  6482 -> 0.635
-Confusion Matrix:
- [[ 70   2   0   5   3  16  12]
- [  1 141   2   2   3   2   5]
- [ 16  18 147  35  14  20  59]
- [  2   8  10 120   5   8  16]
- [  0   8   6   2  60   1   1]
- [  4   0   1   5   0  38   2]
- [ 14   2  12  15  11  17  59]]
-Node Classification on random seed  6483 -> 0.583
-Confusion Matrix:
- [[ 67   4   6   5   3   9  10]
- [  1 121   5   1  22   7   2]
- [ 34  28 111  32  37  26  51]
- [ 10   1   7  99   6   5  18]
- [  3   2   4   0  68   0   2]
- [  6   1   4   2   0  40   7]
- [  7   5  13   4  11  16  77]]
-Node Classification on random seed  6484 -> 0.622
-Confusion Matrix:
- [[ 76   2   2   4   3  15   8]
- [ 10  95   7   8  15   0   4]
- [ 13  36 144  29  34  21  44]
- [  6   4  16 112   6  11  10]
- [  4   3   1   2  60   0   6]
- [  1   4   1   1   3  47   3]
- [  9   3  10   6   3  10  88]]
-Node Classification on random seed  6485 -> 0.588
-Confusion Matrix:
- [[ 69   1   2   6   7   9  10]
- [  4 122   7   3  17   4   2]
- [ 25  30 133  39  29  23  33]
- [ 20   8  18  92  14   8  14]
- [  1   5   3   1  45   6   2]
- [  4   3   1   4   0  47   6]
- [  8   3   6   9   6  11  80]]
-Node Classification on random seed  6486 -> 0.612
-Confusion Matrix:
- [[ 57   3  11   3   1  17  10]
- [  2 122   8   3   8   2   2]
- [ 41  20 150  38  24  17  36]
- [  9   5  15 104  10   1  16]
- [  1   6   4   4  51   1   2]
- [  5   1   2   0   1  50   9]
- [ 12   4  10   2  10  12  78]]
-Node Classification on random seed  6487 -> 0.594
-Confusion Matrix:
- [[ 62   3  10   6   6  18   5]
- [ 10 143   5   2   5   1   1]
- [ 29  25 120  46  30  14  30]
- [ 16   1  20  99   5  12  11]
- [  0   8   3   4  55   1   0]
- [ 10   0   5   0   1  32   5]
- [ 18   4  10   9   2  15  83]]
-Node Classification on random seed  6488 -> 0.607
-Confusion Matrix:
- [[ 58   1  11   7   6  19   7]
- [  5 130   6   1   2   0   4]
- [ 19  21 116  40  24  18  57]
- [ 10   7   9 118   2   7  19]
- [  6   6   4   0  64   0   1]
- [  7   3   4   2   0  41   6]
- [  7  10  11   6   6  12  80]]
-Node Classification on random seed  6489 -> 0.597
-Confusion Matrix:
- [[ 73   1   0   6   4  13   6]
- [  3 115   3   3  10   0   4]
- [ 32  16 137  27  41  28  48]
- [  7   1  18 111   3   5  19]
- [  0   6   4   1  66   3   1]
- [  4   1   1   3   3  36   6]
- [ 11   3  12   9  11  26  59]]
-Node Classification on random seed  6490 -> 0.603
-Confusion Matrix:
- [[ 76   1  10   3   5  10   9]
- [  4 121   1  12   3   0   7]
- [ 21  23 150  42  15  24  31]
- [ 11   0  14  82  15  11  25]
- [  3   5   2   5  61   1   1]
- [  6   1   1   0   2  37   9]
- [ 12   6  13  10   9  14  76]]
-Node Classification on random seed  6491 -> 0.604
-Confusion Matrix:
- [[ 71   5   0   7   4  14  14]
- [  6 123   4   7   7   4   1]
- [ 14  22 137  29  35  34  47]
- [ 13   1  15 100   6   8  11]
- [  2   6   1   1  56   3   0]
- [  8   2   1   2   2  43   2]
- [  8  10   4  11   9  16  74]]
-Node Classification on random seed  6492 -> 0.598
-Confusion Matrix:
- [[ 54   3  12   7   5   9  10]
- [ 11 112   4   1   4   9   3]
- [ 28  23 137  31  34  25  37]
- [ 14   7  12 101   9   3  15]
- [  0   5   4   0  65   3   1]
- [  5   1   1   2   1  39   5]
- [ 10   2  11   6  11  18  90]]
-Node Classification on random seed  6493 -> 0.625
-Confusion Matrix:
- [[ 74   4  13   4   3  13   9]
- [  5 119  11   1  11   6   4]
- [ 26  17 137  36  25  19  31]
- [  5   3  25 104   7   6  11]
- [  3   3   2   0  58   3   4]
- [  1   1   5   0   1  59   5]
- [  5   4  15   7   4  17  74]]
-Node Classification on random seed  6494 -> 0.586
-Confusion Matrix:
- [[ 63   6   5   1   1  23   7]
- [  3 119   9   2   6   5   7]
- [ 21  16 136  45  25  26  43]
- [ 14   6  24 105  11   2  18]
- [  2  14   3   3  54   3   2]
- [  1   0   6   1   0  48   6]
- [  8   2   7   9   6  15  61]]
-Node Classification on random seed  6495 -> 0.628
-Confusion Matrix:
- [[ 62   6   4   1   8  20   2]
- [  1 124   9   2   3   4   6]
- [ 26  33 151  39  23  19  25]
- [  9   3  18 116   6   2  13]
- [  1   7   7   1  60   0   4]
- [  7   2   1   1   0  37   6]
- [ 12   2   5  12   7  15  78]]
-Node Classification on random seed  6496 -> 0.642
-Confusion Matrix:
- [[ 69   2   5   9   2  12   1]
- [  2 140   5   5   4   1   0]
- [ 28  23 149  54  16  21  18]
- [ 11   8  11 115   4   0  12]
- [  2   5   8  10  48   0   2]
- [  5   1   1   5   2  48   0]
- [ 11   1  11   8  13  19  73]]
-Node Classification on random seed  6497 -> 0.624
-Confusion Matrix:
- [[ 73   7   3   4   2  11  17]
- [  2 127   7   9   8   2   3]
- [ 18  13 138  30  22  45  44]
- [  7   4  13 106   5   9  14]
- [  2   4   4   4  46   0   4]
- [  3   1   1   0   3  42   2]
- [  7   3   8   5   1  25  92]]
-Node Classification on random seed  6498 -> 0.632
-Confusion Matrix:
- [[ 72   1   6   4   1  14   4]
- [  4 114   8   1  12   4   4]
- [ 15  20 160  30  38  15  49]
- [ 24   2   9  91   6  13   9]
- [  1   2   1   1  73   0   6]
- [ 10   0   2   1   1  44   6]
- [ 10   3  11   6   5   9  78]]
-Node Classification on random seed  6499 -> 0.574
-Confusion Matrix:
- [[ 62   7   5   1   5  14  12]
- [  4 128   5   2   1   2   9]
- [ 22  27 146  31  31  20  40]
- [  9  14  18 103  10   8  13]
- [  1   8   3   3  48   1   5]
- [  8   3   3   0   1  33   6]
- [ 34   2   3   6   9  20  54]]
-Node Classification on random seed  6500 -> 0.639
-Confusion Matrix:
- [[ 78   4   2  10   3   1  14]
- [  3 105   9   2  12   3   3]
- [ 26  14 149  31  17  16  63]
- [ 12   3   1 129   5   3  18]
- [  1   6   3   0  58   2   3]
- [  6   3   1   3   3  43   8]
- [ 19   5   5   4   3  11  77]]
-Node Classification on random seed  6501 -> 0.634
-Confusion Matrix:
- [[ 81   0   3   4   2   4   2]
- [  3 120   1   0   9  11   9]
- [ 17  13 151  41  21  22  50]
- [  6   3  17 100   9   0  18]
- [  1  10   3   0  61   1   2]
- [  2   3   3  11   3  49   7]
- [  6   2   9  10  15  13  72]]
-Node Classification on random seed  6502 -> 0.563
-Confusion Matrix:
- [[ 44   5   9   3   7  15  16]
- [  9 123  11   3   8   2   8]
- [ 34  44 133  31  17  29  44]
- [ 11   4  20  95   7   2  11]
- [  1   6   9   4  56   2   0]
- [  3   1   2  12   0  41   9]
- [  6   3   6   6  10   7  71]]
-Node Classification on random seed  6503 -> 0.579
-Confusion Matrix:
- [[ 64   2  10   6   4  11   3]
- [  1 114   4   5   6   3   5]
- [ 27  27 108  49  30  30  36]
- [ 15   2  13 117   3   8  13]
- [  2   3   1   2  67   1   8]
- [ 11   0   3   3   1  39   1]
- [ 18   6   1  20   6  21  70]]
-Node Classification on random seed  6504 -> 0.588
-Confusion Matrix:
- [[ 67   4  11   4   0  15   5]
- [  1 117   8   2   9   2   0]
- [ 33  22 140  28  39  17  26]
- [ 20   8  16  84   8  11  13]
- [  3   8   5   0  55   0   0]
- [  2   0   5   2   0  53   6]
- [ 22   4  12  13   6  22  72]]
-Node Classification on random seed  6505 -> 0.601
-Confusion Matrix:
- [[ 75   3   4   3   4  13   8]
- [  2 114   5   4  16   5   3]
- [ 23  17 155  32  22  24  44]
- [ 18   1  14  89  11   6  11]
- [  3   3   5   4  61   1   2]
- [  8   4   5   2   2  38   2]
- [  8   1  15   7  17  17  69]]
-Node Classification on random seed  6506 -> 0.604
-Confusion Matrix:
- [[ 64   5   5   6   5  13  18]
- [  2 126   4   1   7   2   4]
- [ 20  27 127  48  16  33  40]
- [ 10   3  14 115   3   9  11]
- [  3   3   0   3  51   2   9]
- [  5   0   3   2   1  38   5]
- [ 20   4   7   5   7  11  83]]
-Node Classification on random seed  6507 -> 0.629
-Confusion Matrix:
- [[ 76   3  13   4   7   7  11]
- [  6 116   4   2   9   0   8]
- [ 25  24 143  26  16  21  39]
- [ 13  13  13 107   3   7  16]
- [  2   3   2   1  56   0   2]
- [  7   0  10   2   1  51   4]
- [  7   2   7   0   7  24  80]]
-Node Classification on random seed  6508 -> 0.635
-Confusion Matrix:
- [[ 73   2   5   8   2  11   4]
- [  1 140   4   2   3   3   2]
- [ 30  12 142  44  28  32  39]
- [ 13   9  12 115   5   4  15]
- [  2   8   3   3  53   0   5]
- [  3   1   0   3   0  42   4]
- [ 10   3   8   3   5  14  70]]
-Node Classification on random seed  6509 -> 0.617
-Confusion Matrix:
- [[ 62   2   5   2   8   9  13]
- [  2 131   7   4   4   1   0]
- [ 21  18 130  51  26  22  37]
- [ 12   2  23 107  12   4  13]
- [  2  12   8   0  55   1   1]
- [  5   5   0   0   0  49   6]
- [ 10   1  12   2   6  14  83]]
-Node Classification on random seed  6510 -> 0.607
-Confusion Matrix:
- [[ 68   3   4   6   4  11   3]
- [  5 137   3   7   9   4   5]
- [ 19  11 137  51  29  25  39]
- [ 17   3  24  76   4   5  11]
- [  1   1   0   3  63   2   3]
- [  7   0   2   0   1  46  12]
- [  9   2  20   8   6  14  80]]
-Node Classification on random seed  6511 -> 0.607
-Confusion Matrix:
- [[ 60   0   7   8   2  15   9]
- [  3 135   6   4   3   5   2]
- [ 28   8 129  36  38  24  42]
- [ 17   1   9 114   3   6   9]
- [  6   6   2   3  52   1   2]
- [  7   5   1   1   2  42   3]
- [  7   2  10  15  11  24  75]]
-Node Classification on random seed  6512 -> 0.65
-Confusion Matrix:
- [[ 75   3   1   5   2  14  11]
- [  7 137   4   3   2   2   4]
- [ 28  14 168  35  21  12  41]
- [ 19   2  15  89   3   1  23]
- [  3   7   6   2  52   1   3]
- [  3   2   0   4   2  45   6]
- [  8   5   2   7   5  12  84]]
-Node Classification on random seed  6513 -> 0.599
-Confusion Matrix:
- [[ 59   1  10   6   6  15  10]
- [  8 124   3   5   7   2   8]
- [ 20  18 158  50  30  18  35]
- [ 17   1  19  90   6   1  13]
- [  2   2   4   3  67   1   4]
- [ 11   3   4   0   0  40   2]
- [  9   2  14   9   5  17  61]]
-Node Classification on random seed  6514 -> 0.634
-Confusion Matrix:
- [[ 78   5   2   0   4  11   6]
- [  4 125   4   4   4   3   2]
- [ 13  19 146  48  44  15  42]
- [ 11   4  23  97   3   5  11]
- [  3   5   4   4  71   0   1]
- [  3   2   1   6   2  46   2]
- [ 16   6   3   4   4  13  71]]
-Node Classification on random seed  6515 -> 0.591
-Confusion Matrix:
- [[ 81   1   4   4   1  11   1]
- [  9 124   3   4   6   3   9]
- [ 32  14 133  44  20  40  38]
- [  9   5  22  96   1   9  18]
- [  1   7   3   4  51   2   7]
- [  7   1   0   0   1  48   3]
- [ 19   5   9   3   6  23  58]]
-Node Classification on random seed  6516 -> 0.591
-Confusion Matrix:
- [[ 77   1   7   6   3  16  11]
- [  4 128   5   0   6   1   6]
- [ 16  18 119  29  47  29  65]
- [ 14   3  11  88  12   1  19]
- [  0   5   4   3  67   0   3]
- [  5   3   1   2   6  38   6]
- [ 12   0   9   4   6  10  74]]
-Node Classification on random seed  6517 -> 0.6
-Confusion Matrix:
- [[ 69   2   3   4   6  22   3]
- [  1 142   2   4  13   2   4]
- [ 19  28 129  31  27  32  40]
- [ 14  10  13 101   2   7  14]
- [  0   7   3   2  51   2   4]
- [  6   2   0   7   5  30  12]
- [  4   5  10   5   6  17  78]]
-Node Classification on random seed  6518 -> 0.605
-Confusion Matrix:
- [[ 73   3   2   9   8   8   7]
- [  3 119   4   0   5   7   4]
- [ 34  12 121  47  31  32  37]
- [ 18   4   8 119   3   6  14]
- [  1   5   0   2  60   3   4]
- [  3   3   0   0   0  49   7]
- [ 16   7   7   6   4  21  64]]
-Node Classification on random seed  6519 -> 0.619
-Confusion Matrix:
- [[ 60   0   4  13   4  15   4]
- [  4 139   4   3   5   4   4]
- [ 17  17 135  45  30  22  41]
- [ 11   6  20 115  10   4   6]
- [  1  10   3   2  52   0   3]
- [  2   0   2   2   1  52   2]
- [  9   6   8  18   1  18  66]]
-Node Classification on random seed  6520 -> 0.658
-Confusion Matrix:
- [[ 85   2   4   2   1  13  12]
- [  4 125   4   3   5   1   3]
- [ 24  29 135  32  21  26  27]
- [ 18   2  14 116   4   2  13]
- [  2   6   4   1  52   5   3]
- [  3   2   2   0   0  59   2]
- [ 10   8  11   5   0  12  86]]
-Node Classification on random seed  6521 -> 0.606
-Confusion Matrix:
- [[ 51   2   5   8   4  15  20]
- [  7 140   3   1   7   3   3]
- [ 19  16 138  32  22  25  54]
- [ 10   6  20 104   4   5  12]
- [  1   9   7   2  62   4   0]
- [  3   0   0   5   1  44  10]
- [  7   3   8   4   5  22  67]]
-Node Classification on random seed  6522 -> 0.582
-Confusion Matrix:
- [[ 64   1   5   1   5  12  18]
- [  9 124   4   3   9   2   6]
- [ 23  30 110  37  38  23  45]
- [  7   6  11 107   5   2  14]
- [  1   3   6   1  59   1   2]
- [  7   1   2   3   1  51   4]
- [ 15   4  17  12   6  16  67]]
-Node Classification on random seed  6523 -> 0.606
-Confusion Matrix:
- [[ 79   3   1   3   3  18   7]
- [  6 131   4   1   6   5   4]
- [ 17  16 142  21  17  23  69]
- [ 14   1  27  90  10   3  18]
- [  3   7   2   1  55   1   0]
- [  4   1   3   2   0  45   5]
- [  6   3  12  14  12  21  64]]
-Node Classification on random seed  6524 -> 0.624
-Confusion Matrix:
- [[ 70   3   2   4   2   6  19]
- [  5 125   4   3  10   0   4]
- [ 18  25 138  31  26  13  59]
- [  6   1  21 111   4   3  13]
- [  1  10   3   2  64   3   2]
- [  6   2   2   0   0  38  16]
- [  3   5  10  10   8  11  78]]
-Node Classification on random seed  6525 -> 0.621
-Confusion Matrix:
- [[ 72   1   2   4   0  20   4]
- [  0 135   5   4   9   2   6]
- [ 34  19 134  44  20  33  32]
- [ 14   3   7  91   4  11  11]
- [  1   3   4   4  71   0   1]
- [  5   1   4   2   1  40   4]
- [ 10   5  22   3   3  17  78]]
-Node Classification on random seed  6526 -> 0.64
-Confusion Matrix:
- [[ 59   6   3   2   4  12   6]
- [  3 137   5   6   7   0   0]
- [ 10  25 167  54  29   9  28]
- [ 16   2   5 111   6  10  11]
- [  0  10   0   3  57   2   2]
- [  4   3   4   0   1  47   5]
- [  9   5   9  14  16  14  62]]
-Node Classification on random seed  6527 -> 0.617
-Confusion Matrix:
- [[ 77   3   1   2   2   5  17]
- [  3 117  11   2  11   2   3]
- [ 21  15 134  44  26  31  32]
- [ 13   4  13 103   7   9  11]
- [  1   4   4   2  64   3   1]
- [  9   0   2   1   2  37   5]
- [ 21   5  10   6   9  10  85]]
-Node Classification on random seed  6528 -> 0.631
-Confusion Matrix:
- [[ 77   3   6   3   3  19  11]
- [  8 131   5   4   8   8   4]
- [ 29  22 145  35  17  10  42]
- [ 15   1  12  85  13   5  14]
- [  2   5   3   2  58   1   2]
- [  0   0   0   2   3  44   7]
- [  5   3  13   7   1  16  91]]
-Node Classification on random seed  6529 -> 0.658
-Confusion Matrix:
- [[ 82   1   2   3   2   9  22]
- [  5 127   5   4   5   3  11]
- [ 25  19 146  14  44  20  34]
- [  6   0   6 103   9   6  16]
- [  0  12   1   2  65   0   3]
- [  4   2   2   1   2  48   4]
- [  9   6   6   1   6  10  87]]
-Node Classification on random seed  6530 -> 0.574
-Confusion Matrix:
- [[ 70   3   2   5   2  18  10]
- [  9 113   7   2   9   0   5]
- [ 26  17 100  27  53  18  59]
- [ 13   6  20  99   4  13   9]
- [  1   6   3   2  75   0   2]
- [  0   1   5   0   3  41   8]
- [  8   2  13  10  15  10  76]]
-Node Classification on random seed  6531 -> 0.617
-Confusion Matrix:
- [[ 71   2   4   2   4  14  21]
- [  3 134   3   3  14   2   0]
- [ 12  22 135  39  19  19  55]
- [  9   1  20 102   8   3  13]
- [  1   6   0   5  61   1   3]
- [  2   2   2   6   1  43   4]
- [  4   4  14   2  18  16  71]]
-Node Classification on random seed  6532 -> 0.626
-Confusion Matrix:
- [[ 74   6  10   3   3  18   2]
- [  1 135   9   1   5   2   4]
- [ 36  21 140  33  21  28  34]
- [  9   6  14 113   3   7  11]
- [  4   7   1   0  52   0   2]
- [  3   1   7   1   3  42   1]
- [  9   2  14   9   0  23  70]]
-Node Classification on random seed  6533 -> 0.608
-Confusion Matrix:
- [[ 83   2   6   8   2  11   2]
- [  3 119   5   0   6   5   8]
- [ 20  21 137  26  41  12  62]
- [ 15   3  12  88  24   7  10]
- [  1   2   2   0  54   5   3]
- [  4   1   4   2   0  43   5]
- [  9   0   7  15   6  15  84]]
-Node Classification on random seed  6534 -> 0.591
-Confusion Matrix:
- [[ 84   4   4   2   5  10   6]
- [  1 125   3   3  12  11   5]
- [ 24  33 121  27  34  29  40]
- [ 13   4  15  80   3   5  23]
- [  3   5   5   0  55   1   2]
- [  8   2   2   2   0  48   6]
- [  8   7   9   6  12  15  78]]
-Node Classification on random seed  6535 -> 0.605
-Confusion Matrix:
- [[ 71   4   8   4   3  11  11]
- [  1 122   2   6  10   1  12]
- [ 16  12 129  60  28  18  38]
- [ 13   2  24 111   3   4  11]
- [  1   9   2   3  59   0   7]
- [  7   1   5   4   2  46   8]
- [  3   5   9   9   8  10  67]]
-Node Classification on random seed  6536 -> 0.593
-Confusion Matrix:
- [[ 71   2   9   4   0   9   4]
- [  4 126   5   1   3   5   3]
- [ 21  19 134  53  45  17  38]
- [ 14  10  12  93   6  11  10]
- [  3   9   0   1  67   1   2]
- [  3   1   2   4   0  48   5]
- [ 20  10   9   5   6  21  54]]
-Node Classification on random seed  6537 -> 0.624
-Confusion Matrix:
- [[ 73   8   5  11   6   7   7]
- [  4 140   3   2  11   4   5]
- [ 29  16 160  28  14  25  37]
- [  5   2  20  85  11   5  12]
- [  0   6   0   6  54   0   4]
- [  6   1   0   2   3  40   1]
- [ 20   5  10   2  11  22  72]]
-Node Classification on random seed  6538 -> 0.637
-Confusion Matrix:
- [[ 68   3   8   2   4  16   4]
- [  7 136   4   1   6   2   5]
- [ 24  16 145  31  24  27  29]
- [  9   1  12 105  12   9   9]
- [  1   1   5   1  63   0   5]
- [  9   2   4   2   0  43   5]
- [ 15   2  11  10   8  17  77]]
-Node Classification on random seed  6539 -> 0.622
-Confusion Matrix:
- [[ 58   3   7   9   3   6  14]
- [ 11 116   7   3   9   6   2]
- [ 16   3 148  30  34  37  41]
- [  6   8  17 112  10   3  13]
- [  3   8   0   3  67   2   1]
- [  9   0   0   7   1  34   2]
- [  9   1   6   3   5  20  87]]
-Node Classification on random seed  6540 -> 0.655
-Confusion Matrix:
- [[ 93   5   3   6   3   7   1]
- [  7 131   2   1   7   2   7]
- [ 41  24 139  28  29  11  35]
- [  8   5   7 106   2   6  16]
- [  1   6   1   4  65   1   1]
- [  5   3   3   2   0  46   4]
- [ 13   4  11   5   6  12  75]]
-Node Classification on random seed  6541 -> 0.591
-Confusion Matrix:
- [[ 83   2   2   5   5  16   6]
- [  3 130   6   7   5   5   2]
- [ 25  33 116  43  27  20  39]
- [ 10   5  21 106   7   3  11]
- [  1  12   7   3  55   0   0]
- [  4   0   3   2   2  47   5]
- [ 17   5  14   4   9  13  54]]
-Node Classification on random seed  6542 -> 0.611
-Confusion Matrix:
- [[ 68   4   7   5   5  10   6]
- [  6 115   5   6   7   3   5]
- [ 26  17 123  49  29  15  55]
- [ 18   6  10 108   4   5  19]
- [  2   4   3   0  67   0   1]
- [  3   1   1   2   0  44   5]
- [ 10   3  10   5   4  13  86]]
-Node Classification on random seed  6543 -> 0.611
-Confusion Matrix:
- [[ 60   0  15   2   9   7   6]
- [  4 123   4   6   3   1   5]
- [ 24  32 141  25  21  23  30]
- [ 15   6  19 105   6   7  15]
- [  0  10   3   2  50   0   2]
- [ 13   0   4   2   0  49   2]
- [ 20   3  18   8   7  10  83]]
-Node Classification on random seed  6544 -> 0.616
-Confusion Matrix:
- [[ 61   4   3   4   5  21  17]
- [  2 140   8   0  10   3   1]
- [ 18  21 142  43  30  22  20]
- [  9  11  26  87   4   9  12]
- [  1   2   6   1  58   4   0]
- [  9   1   2   0   0  55   4]
- [ 11   4   9   3   5  19  73]]
-Node Classification on random seed  6545 -> 0.606
-Confusion Matrix:
- [[ 68   7   0   5  11   8  11]
- [  6 119   1   2   6   6   5]
- [ 24  31 129  52  21  33  26]
- [ 12   3  12 109   9   4   6]
- [  1  11   6   1  68   2   1]
- [  3   0   2   5   1  41   5]
- [ 12   3  15   7   2  16  72]]
-Node Classification on random seed  6546 -> 0.619
-Confusion Matrix:
- [[ 78   3   2   5   3  11   4]
- [  7 127   2   1   4   2   6]
- [ 15  25 120  48  42  26  29]
- [ 15   5  11 115   4   5  22]
- [  0   9   2   2  62   1   2]
- [  7   0   3   3   0  46   7]
- [  7   3  13   3   2  20  71]]
-Node Classification on random seed  6547 -> 0.631
-Confusion Matrix:
- [[ 73   0   6   9   3  21   2]
- [  9 114  14   0   6   1   2]
- [ 30  14 150  33  15  28  35]
- [ 14   1  14 101   4   5   9]
- [  2   4   2   0  56  10   3]
- [  3   5   4   2   5  52   0]
- [ 15   2  14   5   6  12  85]]
-Node Classification on random seed  6548 -> 0.614
-Confusion Matrix:
- [[ 68   5   1  10   2  15   6]
- [  5 141   4   5  11   0   8]
- [ 28  17 145  38  40  22  29]
- [ 20   8   8  92   5  10   5]
- [  0   6   0   3  63   1   5]
- [  7   0   0   1   0  45   2]
- [  9   1  12  18   8  11  60]]
-Node Classification on random seed  6549 -> 0.588
-Confusion Matrix:
- [[ 85   1   1   2   3  14  12]
- [  3 122  16   0   8   6   2]
- [ 31  30 109  33  34  21  46]
- [  8   7  23 102   5   9  11]
- [  1  13   7   2  57   3   0]
- [  5   0   1   1   0  43   3]
- [ 10   4  13   7   2  14  70]]
-Node Classification on random seed  6550 -> 0.612
-Confusion Matrix:
- [[ 70   4   5   6   2   8  12]
- [  4 132   4   0   5   4   7]
- [ 47  20 133  26  21  14  45]
- [  3   7  17 104   5   5  21]
- [  0   7   4   3  61   4   7]
- [  2   0   5   3   1  44   6]
- [ 13   3   9   8  10  11  68]]
-Node Classification on random seed  6551 -> 0.624
-Confusion Matrix:
- [[ 59   1   5   3   5  14  13]
- [  8 127   4   2   4   2   4]
- [ 19  17 152  39  17  21  46]
- [ 13   4  18 112   5   6  15]
- [  0  13   3   2  50   4   1]
- [  6   4   2   1   1  47   6]
- [ 16   1   9   6   7   9  77]]
-Node Classification on random seed  6552 -> 0.604
-Confusion Matrix:
- [[ 64   1   1   3   8  13  16]
- [  6 114   1   4  12   1   1]
- [ 25  35 137  36  30  21  46]
- [  6   4  14  99   8   9  13]
- [  1   7   4   0  64   1   1]
- [  7   0   1   0   0  52   4]
- [ 16   6   6   2  14  12  74]]
-Node Classification on random seed  6553 -> 0.636
-Confusion Matrix:
- [[ 73   7   3   1   6  13   7]
- [  6 121   3   3  12   3   0]
- [ 31  12 152  25  16  18  49]
- [ 18   2  14 112   4   4  20]
- [  1   7   6   1  50   2   1]
- [ 10   1   1   2   0  42   1]
- [ 16   2   2   5   7  22  86]]
-Node Classification on random seed  6554 -> 0.607
-Confusion Matrix:
- [[ 68   1   7   3   4  15   4]
- [  8 124   5   5   5   3  11]
- [ 27  24 129  46  23  30  33]
- [  7   4  15 124   9   7  11]
- [  1   4   2   2  54   1   3]
- [  8   3   0   0   0  44   4]
- [ 18   0   8   8  10  14  64]]
-Node Classification on random seed  6555 -> 0.624
-Confusion Matrix:
- [[ 77   6   3   7   3   7  18]
- [ 10 128   6   2   8   2   0]
- [ 22  15 148  48  23  23  19]
- [  8   3  10 121   6  10  13]
- [  1  11   2   4  54   1   1]
- [  6   1   4   0   0  38   4]
- [ 22   8   8  11   9  11  58]]
-Node Classification on random seed  6556 -> 0.619
-Confusion Matrix:
- [[ 69   2   2  15   3   6  11]
- [  3 121   3   4  12   5  17]
- [ 14  30 141  22  21  35  34]
- [ 15   1  18 108   1   7   9]
- [  6   5   3   0  56   7   4]
- [  1   0   3   4   0  41   7]
- [  9   3   9  10   3  17  83]]
-Node Classification on random seed  6557 -> 0.549
-Confusion Matrix:
- [[ 85   2   2   6   2   8  10]
- [ 10 102  11   3   2   7   4]
- [ 36  29 105  58  30  21  35]
- [ 15   4  23  72  10  15  17]
- [  3   4   1   5  64   0   2]
- [  4   3   0   1   1  46   3]
- [ 16   1  15   6   7  19  75]]
-Node Classification on random seed  6558 -> 0.599
-Confusion Matrix:
- [[ 91   2   2   8   3  17   3]
- [  6 124   6   2   7   2   3]
- [ 17  19 123  51  43  20  36]
- [ 13   7  12 111   3   4  11]
- [  4  11   4   2  52   0   2]
- [  5   1   5   0   1  48   4]
- [  8   3   6  14   8  26  50]]
-Node Classification on random seed  6559 -> 0.583
-Confusion Matrix:
- [[ 63   3   2   7   6  23   8]
- [  5 120   6   3   4   3   7]
- [ 29  28 137  43  20  39  21]
- [  9   6  19  74  13   7  19]
- [  1   4   3   0  63   2   2]
- [  9   2   2   2   0  48   7]
- [ 14   4   8   8   7  12  78]]
-Node Classification on random seed  6560 -> 0.627
-Confusion Matrix:
- [[ 76   1   3   6   7  10  11]
- [  6 126   6   2   8   0   3]
- [ 26  31 131  30  25  25  36]
- [  4   9  17 111   4   8   4]
- [  2   6   3   1  63   1   3]
- [  6   0   4   1   2  49   1]
- [ 16   3  12   8  13   9  71]]
-Node Classification on random seed  6561 -> 0.626
-Confusion Matrix:
- [[ 80   3   6   5   7   9   3]
- [  0 136   9   5   4   1   2]
- [ 29  19 130  52  30  16  35]
- [  6   1   6 101   1   4  26]
- [  1   8   7   6  60   1   0]
- [  3   1   1   4   1  45   7]
- [ 11   7   1  11  11  14  74]]
-Node Classification on random seed  6562 -> 0.609
-Confusion Matrix:
- [[ 50   2   0   4   3  24  14]
- [  7 129   5   4  11   1   3]
- [ 21  28 153  25  34  32  23]
- [ 13   2  12 100  11   5  21]
- [  1   6   1   0  69   3   0]
- [ 13   0   0   0   7  42   6]
- [ 14   7   3   4   7  14  66]]
-Node Classification on random seed  6563 -> 0.603
-Confusion Matrix:
- [[ 63   3   2   8   1   8  13]
- [  6 122  10   2  13   2   9]
- [ 27  23 148  32  26  33  29]
- [  5   3  17  95   4  13  19]
- [  1   6   5   1  61   0   4]
- [  3   0   2   3   1  41   6]
- [  5   3  11   6   7  25  73]]
-Node Classification on random seed  6564 -> 0.63
-Confusion Matrix:
- [[ 75   7   4   2   1   7   4]
- [  2 134   3   1   3   0   3]
- [ 28  23 149  32  23  27  36]
- [  7   6  22  93   8   6  11]
- [  1   8   7   1  53   1   5]
- [  3   2   3   1   1  57   2]
- [ 10   2  11  10  18  18  69]]
-Node Classification on random seed  6565 -> 0.609
-Confusion Matrix:
- [[ 77   6   4   6   2  15   4]
- [  6 125   8   0   8  10   3]
- [ 28  18 143  23  38  24  50]
- [  8   7  13 102   5  13  12]
- [  3   5   6   2  56   0   3]
- [  4   0   3   1   0  47   1]
- [ 13   1  16   4   6  12  59]]
-Node Classification on random seed  6566 -> 0.628
-Confusion Matrix:
- [[ 73   3   0   8   3  10  15]
- [  5 127   6   1   5   2   2]
- [ 14  25 134  57  34  15  42]
- [ 10  11  11  96   6  11   4]
- [  1   7   2   3  58   0   0]
- [  7   2   2   3   1  51   6]
- [ 14   1   3   7   4   9  89]]
-Node Classification on random seed  6567 -> 0.606
-Confusion Matrix:
- [[ 78   6   0   4   5   6  17]
- [ 10 120  19   6   3   2   4]
- [ 22  26 124  44  29  24  33]
- [  8   6   8 117   6   5   7]
- [  3   3   2   4  56   1   2]
- [  5   4   3   3   0  44  11]
- [ 13   5  12   8   7   8  67]]
-Node Classification on random seed  6568 -> 0.622
-Confusion Matrix:
- [[ 65   1   2  12   8  13   8]
- [  6 109   9   2   9   5   5]
- [ 37  10 151  28  25  15  48]
- [ 25   4   9 113   4   2   5]
- [  0   4   2   0  55   0   2]
- [  5   0   7   1   1  52   4]
- [ 11   4  14   3  12  16  77]]
-Node Classification on random seed  6569 -> 0.581
-Confusion Matrix:
- [[ 76   4   6  14   2   7  17]
- [  3 131   6   5   1   0   2]
- [ 20  27 105  41  30  28  64]
- [  9   8  11 103  11   2  19]
- [  1   9   3   1  62   2   1]
- [  7   0   2   1   0  33   6]
- [ 12   3  14  11   3   6  71]]
-Node Classification on random seed  6570 -> 0.572
-Confusion Matrix:
- [[ 58   2  12   2   4  18  24]
- [  7 109  13   3   2   7   7]
- [ 33  39 142  26  14  46  24]
- [  7   4  23  85   6  10  18]
- [  3  11   3   1  61   0   4]
- [  3   1   1   1   0  43   7]
- [  9   3   6   3   6  15  74]]
-Node Classification on random seed  6571 -> 0.637
-Confusion Matrix:
- [[ 73   1   3   5   6   6  10]
- [  9 130   6   2   6   3   3]
- [ 23  21 138  28  36  15  54]
- [  9   2   9 110   3   4  19]
- [  1   3   1   4  55   0   2]
- [  4   1   2   3   1  52   4]
- [ 16   5   4   6   8  15  79]]
-Node Classification on random seed  6572 -> 0.615
-Confusion Matrix:
- [[ 56   1   7   2   3  18   9]
- [  3 141   1   6   5   5   5]
- [ 18  29 128  31  19  37  38]
- [  4   5  12 109   4  12  22]
- [  1   9   1   2  57   0   4]
- [  8   3   4   2   0  46   3]
- [  8   4   8   6   3  23  78]]
-Node Classification on random seed  6573 -> 0.649
-Confusion Matrix:
- [[ 62   2   6   8   1   7  12]
- [  1 147   8   2  11   2   4]
- [ 21  16 150  47  13  21  28]
- [ 19   4  16 107   1   4  19]
- [  1   6   5   2  60   0   5]
- [  7   1   6   0   1  37   6]
- [ 10   3   7   7   3   8  86]]
-Node Classification on random seed  6574 -> 0.655
-Confusion Matrix:
- [[ 73   0   3   3   3  11  16]
- [  3 117   3   1  10   1   4]
- [ 26  24 157  40  27  25  30]
- [  6   1  14 118   5   3  10]
- [  2   4   4   0  56   1   4]
- [  5   0   2   0   0  45   7]
- [ 12   0  11   5   4  15  89]]
-Node Classification on random seed  6575 -> 0.625
-Confusion Matrix:
- [[ 67   1   2   7   7  16   9]
- [  1 127   2   1  12   3   3]
- [ 27  23 149  23  12  32  45]
- [ 10   5  17  86   7  15  12]
- [  1   8   4   1  58   3   4]
- [ 12   2   1   0   0  48   5]
- [  7   3   4   4   7  17  90]]
-Node Classification on random seed  6576 -> 0.607
-Confusion Matrix:
- [[ 72   2  15   3   5  15   6]
- [  1 138   6   5   4   3   3]
- [ 30  27 115  43  26  26  30]
- [ 14   2   7 117  10   3  11]
- [  2   6   7   2  61   0   0]
- [  5   1   2   3   1  34   6]
- [  9   2  21   8   9  12  70]]
-Node Classification on random seed  6577 -> 0.626
-Confusion Matrix:
- [[ 75   1   2   0   2  21   7]
- [  2 129   1   1  13   2   2]
- [ 12  21 143  27  28  28  44]
- [ 15   4  20  97   6   5  14]
- [  0   3   5   1  72   0   3]
- [ 15   2   1   0   1  37   2]
- [ 12   6   4  13   7  21  73]]
-Node Classification on random seed  6578 -> 0.601
-Confusion Matrix:
- [[ 81   2   4   8   5   9  11]
- [  0 120  19   5   7   6   3]
- [ 20  11 142  54  24  27  24]
- [ 14   2  22  98   1  18   5]
- [  0   9   4   2  45   3   1]
- [  7   0   5   1   1  50   6]
- [ 15   5  15   8   9   7  65]]
-Node Classification on random seed  6579 -> 0.627
-Confusion Matrix:
- [[ 82   0   3   4   2  11   6]
- [  4 134   7   1  11   4   1]
- [ 31  15 117  35  49  15  47]
- [  8   2   9 115   6  10   8]
- [  4   7   4   0  60   1   4]
- [  9   0   0   0   0  45   4]
- [  8   4   7   3  10  19  74]]
-Node Classification on random seed  6580 -> 0.632
-Confusion Matrix:
- [[ 86   7   4   3   2   9   6]
- [  3 116  11   0   5   3   2]
- [ 21  22 152  27  34  25  34]
- [ 17   3  21  98   4   5  10]
- [  2   7   4   1  56   2   0]
- [  8   1   0   1   0  45   8]
- [ 14   3  10   5  13  11  79]]
-Node Classification on random seed  6581 -> 0.618
-Confusion Matrix:
- [[ 71   4   7   9   2   9   2]
- [  4 124   7   8  13   2   5]
- [ 30  18 147  31  33  17  40]
- [ 10   1  16  99   6   8  17]
- [  1   6   2   3  61   4   3]
- [  3   1   3   1   0  46   5]
- [ 16   2  10  12   4   7  70]]
-Node Classification on random seed  6582 -> 0.62
-Confusion Matrix:
- [[ 66   1   4   5   5   4  12]
- [  5 120   7   4   7   0   4]
- [ 34  12 164  42  23  14  40]
- [ 25   0   9 103   2   1  25]
- [  0   6   7   0  65   1   3]
- [ 12   1   0   1   0  38   2]
- [ 27   3   5  14   3  10  64]]
-Node Classification on random seed  6583 -> 0.607
-Confusion Matrix:
- [[ 65   5   7   7   3  12  13]
- [  3 147   8   1  10   2   3]
- [ 36  36 136  23  17  14  47]
- [ 10   7  24  88   5   1  16]
- [  2   6   8   5  57   0   0]
- [  9   2   1   0   0  34   4]
- [ 15   3   7   2   9  10  80]]
-Node Classification on random seed  6584 -> 0.628
-Confusion Matrix:
- [[ 71   0   3   8   3   7   8]
- [  4 102  15   5  12   1  13]
- [ 22  19 173   7  26  27  35]
- [  7   4  14  96   3  10  22]
- [  1   6  13   0  53   0   2]
- [  6   0   2   0   0  46   8]
- [ 16   4  12   2   7  18  87]]
-Node Classification on random seed  6585 -> 0.529
-Confusion Matrix:
- [[ 69   4   2   5   4  13  19]
- [  5 125   4   6  13   1   2]
- [ 24  27  96  58  18  11  66]
- [ 10  10  20  93  10   4  19]
- [  2   7   4   4  51   0   3]
- [  3   1   8   1   2  39   5]
- [ 18   5  12   9  10  22  56]]
-Node Classification on random seed  6586 -> 0.61
-Confusion Matrix:
- [[ 69   7   3   2   5  13  17]
- [  4 108  10   5   5   0   6]
- [ 16  19 143  18  34  29  52]
- [  9   5  11 107   2  10  26]
- [  2   6   7   1  56   0   3]
- [  4   2   1   2   0  52   4]
- [  7   6   1   4   8  24  75]]
-Node Classification on random seed  6587 -> 0.551
-Confusion Matrix:
- [[ 54   2   5  15   4   3  22]
- [  3 141   4   4   9   7   5]
- [ 25  26  97  22  42  23  50]
- [ 22   2   9 110   7  11  11]
- [  1   4   3   2  50   1   2]
- [ 11   2   0   3   2  28  14]
- [ 12   5  11   9  17  17  71]]
-Node Classification on random seed  6588 -> 0.603
-Confusion Matrix:
- [[ 67   1   2   3   6  17   7]
- [ 10 117   6   1   8   3   5]
- [ 24  13 131  33  31  21  53]
- [ 15   2  25  99   4   4  17]
- [  0   9   3   1  69   0   4]
- [  7   0   2   1   0  44   2]
- [ 20   6   3   1   4  23  76]]
-Node Classification on random seed  6589 -> 0.603
-Confusion Matrix:
- [[ 79   2   5  13   2   9   7]
- [  2 126   3   2  10   3   4]
- [ 25  16 114  48  38  25  43]
- [ 12   4  20 101   9   3  12]
- [  1   2   1   5  62   0   1]
- [  5   2   1   7   0  51   3]
- [ 18   4   6   6   6  12  70]]
-Node Classification on random seed  6590 -> 0.613
-Confusion Matrix:
- [[ 60   2   8  13   2  16   9]
- [  4 151   1   6   5   5   2]
- [ 26  16 142  27  46  31  20]
- [  4   4  17  92  17   3  18]
- [  6   4   5   2  58   0   0]
- [  5   0   2   1   0  40   4]
- [ 14   1  12   3   8  18  70]]
-Node Classification on random seed  6591 -> 0.64
-Confusion Matrix:
- [[ 76   5   2   6   2   6   7]
- [  1 132   6   3   6   1   6]
- [ 27  19 155  28  25  26  39]
- [ 11   2  13 106   1  12  15]
- [  1   3   4   3  59   2   2]
- [  4   0   1   4   1  47   6]
- [  9   4   3  10  15  19  65]]
-Node Classification on random seed  6592 -> 0.634
-Confusion Matrix:
- [[ 67   7   3   1   4  10  16]
- [  2 132   9   0   5   3   2]
- [ 31  22 135  22  38  26  27]
- [ 17   8  15 106   0   1  13]
- [  1   1   1   3  70   0   4]
- [  5   1   5   2   1  38  11]
- [ 10   3   9   5   8  14  86]]
-Node Classification on random seed  6593 -> 0.635
-Confusion Matrix:
- [[ 60   4   2  12  11   4  15]
- [  5 141   2   1   3   2   3]
- [ 23  16 149  45  19  12  42]
- [  9   4  20 105   3   7  10]
- [  2   5   4   2  54   1   2]
- [  2   1   2   2   0  49  10]
- [  6   3  15   6   6  22  77]]
-Node Classification on random seed  6594 -> 0.644
-Confusion Matrix:
- [[ 65   4   4   9   6  17   9]
- [  2 119   5   6  12   1   7]
- [ 19  17 148  40  25  16  40]
- [  2   3  17 113   5   4  16]
- [  1   5   0   3  65   1   2]
- [  3   0   1   1   0  49   7]
- [  6   4   7   4   7  18  85]]
-Node Classification on random seed  6595 -> 0.653
-Confusion Matrix:
- [[ 73   2   1  11   2   8  16]
- [  4 131  12   4   4   2   1]
- [ 12  14 169  37  16   8  41]
- [ 21   4  15  93   9   4  13]
- [  2   8   4   3  68   2   3]
- [  7   2   1   3   0  37   3]
- [  8   3  10  18   3   6  82]]
-Node Classification on random seed  6596 -> 0.578
-Confusion Matrix:
- [[ 50   0  11  10   4   5  11]
- [  3 126   5   1  13   0   4]
- [ 16  22 121  38  29  42  47]
- [ 15   8  15  83   6  20  16]
- [  1   3   3   0  73   1   3]
- [  3   2   1   3   2  53   9]
- [ 14   2   9  10   5  10  72]]
-Node Classification on random seed  6597 -> 0.651
-Confusion Matrix:
- [[ 86   2   0   9   3   4   5]
- [  3 131   4   1   5   3   5]
- [ 19  25 169  29  32  14  19]
- [  9   6  29 106   8   2   9]
- [  2   3   5   2  68   1   2]
- [ 11   0   3   3   0  29   9]
- [ 12   4  11  13   6  17  62]]
-Node Classification on random seed  6598 -> 0.658
-Confusion Matrix:
- [[ 68   4   4   2   1   7  13]
- [  4 150   3   3   8   5   0]
- [ 16  23 160  21  37  21  28]
- [  6   1  13 104   9   2  13]
- [  1   7   2   2  65   0   0]
- [ 10   2   3   3   3  35   6]
- [ 14   1  13   6  14  11  76]]
-Node Classification on random seed  6599 -> 0.616
-Confusion Matrix:
- [[ 73   1   4   2   8   4  11]
- [  3 122   5   6   8   2   1]
- [ 26  15 156  37  29  25  32]
- [ 13   2  19  97  15   3  14]
- [  3   7   8   3  58   0   0]
- [  7   4   6   4   2  41   7]
- [ 16   4   7  11   5   5  69]]
-Node Classification on random seed  6600 -> 0.605
-Confusion Matrix:
- [[ 71   0   3   6   6  12   9]
- [  6 125   9   2   1   0   4]
- [ 37  23 145  15  16  17  62]
- [ 17  12  18  89   2   4  24]
- [  0   6   1   0  64   2   2]
- [ 11   3   1   4   4  40   2]
- [ 22   4   6   3  12   7  71]]
-Node Classification on random seed  6601 -> 0.632
-Confusion Matrix:
- [[ 68   2   3  11   0  10   4]
- [  2 144   3   0   3   0   4]
- [ 14  29 136  27  46  28  32]
- [  7   5  14  95   7  17   9]
- [  1  11   5   2  54   1   3]
- [  9   1   2   1   0  43   6]
- [ 10   5   5  10   9  10  92]]
-Node Classification on random seed  6602 -> 0.615
-Confusion Matrix:
- [[ 55   2   0   6  10  21  14]
- [  5 122   9   0  12   3   4]
- [ 33  31 141  25  21  29  41]
- [ 12   2  13 100   1   5  11]
- [  2   4   4   0  66   0   2]
- [ 12   2   0   2   2  47   3]
- [ 10   4   7   5   5  11  84]]
-Node Classification on random seed  6603 -> 0.648
-Confusion Matrix:
- [[ 73   1   2   5   2  15  12]
- [  6 120   4   2   5   1   6]
- [ 25  22 152  23  19  28  38]
- [ 15   7  13 104   5   5  11]
- [  1   2   3   1  73   2   0]
- [ 13   2   0   2   3  44   2]
- [ 14   3   7   5   4  16  82]]
-Node Classification on random seed  6604 -> 0.612
-Confusion Matrix:
- [[ 79   5   2   4   1   6  12]
- [  9 120   6   2   7   2  15]
- [ 43  35 123  27  30  26  21]
- [ 14   3  17 110   1   6   8]
- [  0  15   5   0  58   0   1]
- [ 10   2   2   2   3  38   4]
- [  5   1  10   5   3  18  84]]
-Node Classification on random seed  6605 -> 0.634
-Confusion Matrix:
- [[ 63   2   6   4   2  11  10]
- [  5 141   3   2  11   3   4]
- [ 15  13 164  26  16  25  64]
- [  8   7   9  93   6   5  16]
- [  0  11   7   0  67   0   3]
- [  3   2   2   2   1  40   4]
- [  4   8   5   8   9  24  66]]
-Node Classification on random seed  6606 -> 0.618
-Confusion Matrix:
- [[ 67   2   1   2   5  19  15]
- [  2 129   1   1   6   3   9]
- [ 20  19 153  28  22  36  39]
- [ 10   2   8 114   3   1  18]
- [  3   7   4   3  50   1   1]
- [  4   2   4   4   0  41   8]
- [  5   8  12   8  23  13  64]]
-Node Classification on random seed  6607 -> 0.643
-Confusion Matrix:
- [[ 64   2   2   5   5  15  11]
- [  6 126   4   2   5   4   3]
- [ 31  26 159  28  20  25  34]
- [  7   3  17 120   5   3   4]
- [  0   9   8   2  63   1   2]
- [  7   1   2   4   0  39   4]
- [  5   4   7   4  13  17  72]]
-Node Classification on random seed  6608 -> 0.609
-Confusion Matrix:
- [[ 85   4   3   3   6  11   8]
- [  4 120   6   0  17   5   3]
- [ 27  11 134  38  32  20  44]
- [ 10   2  13  94   4   5  16]
- [  2   3   4   4  67   2   2]
- [  4   0   2   2   1  43   4]
- [ 14   1  18   5  13  18  66]]
-Node Classification on random seed  6609 -> 0.607
-Confusion Matrix:
- [[ 67   5   4   2   1  15  14]
- [  2 125   3   4   9   3   5]
- [ 27  15 141  30  42  24  36]
- [ 17   6  17 102   2   1  21]
- [  1   5   1   3  56   1   2]
- [  9   2   0   2   3  43   3]
- [ 10   9   8   4  10  15  73]]
-Node Classification on random seed  6610 -> 0.615
-Confusion Matrix:
- [[ 59   3   7   8   1  14  16]
- [ 11 115   5   6  13   4   2]
- [ 12  22 157  31  26  33  19]
- [ 20   2  15  95   5   7   7]
- [  1   3   2   3  70   0   0]
- [ 11   1   8   2   2  38   3]
- [  9   3  14   8   8  18  81]]
-Node Classification on random seed  6611 -> 0.618
-Confusion Matrix:
- [[ 88   2   3   4   3   7   2]
- [  3 131   2   3   7   0   8]
- [ 27  32 112  25  40  15  37]
- [ 16   0  24 104   3   2  21]
- [  1   8   5   2  59   0   0]
- [  8   0   2   1   0  48   5]
- [ 26   5   7   6  10  10  76]]
-Node Classification on random seed  6612 -> 0.575
-Confusion Matrix:
- [[ 61   2   1  16   4  17   4]
- [  8 116   6   5   8   6   5]
- [ 33  16 134  47  26  25  44]
- [ 15   1  11  86   6  16  15]
- [  4   5   1   0  71   0   3]
- [  5   3   8   2   0  41   0]
- [  8   3   1  13  12  20  66]]
-Node Classification on random seed  6613 -> 0.613
-Confusion Matrix:
- [[ 77   4   4   1   5   8   8]
- [  4 126   7   1   4   0   4]
- [ 29  25 137  30  28  27  31]
- [ 12   1  15  72   5  23  17]
- [  1   5   4   6  66   0   4]
- [  6   3   4   0   1  45   6]
- [ 19   3   4   6   8  14  90]]
-Node Classification on random seed  6614 -> 0.633
-Confusion Matrix:
- [[ 75   5   3   4   5  15  13]
- [  7 128   8   0   4   3   1]
- [ 31  33 139  27  19  31  26]
- [  4   6  10 104   6   8  14]
- [  2   6   6   5  54   1   1]
- [  5   1   0   0   1  45   8]
- [  9   4  11   6   5  13  88]]
-Node Classification on random seed  6615 -> 0.61
-Confusion Matrix:
- [[ 68   1   3   1   3  26   5]
- [  1 119   4   3   8   3   4]
- [ 27  15 150  39  24  22  23]
- [ 20   1   9  95  22   6   9]
- [  1   5   5   0  60   3   3]
- [  4   1   3   3   4  58   3]
- [ 21   3   9  11  10  22  60]]
-Node Classification on random seed  6616 -> 0.621
-Confusion Matrix:
- [[ 68   1   4   2   2  18  11]
- [  3 132   3   1  19   4   3]
- [ 25  27 149  35  28  22  20]
- [  7   0  13 104   2  10  16]
- [  0   4   3   1  56   4   2]
- [  5   2   1   0   3  57   9]
- [ 12   0  10   3   8  36  55]]
-Node Classification on random seed  6617 -> 0.607
-Confusion Matrix:
- [[ 75   4   2   2   6  11   5]
- [  7 115   8   2   9   4   4]
- [ 14  26 129  38  28  34  46]
- [ 14  11  11 103   3   7  12]
- [  2   2   1   0  58   2   2]
- [  5   2   5   3   1  48   1]
- [  4   2   8  11   7  27  79]]
-Node Classification on random seed  6618 -> 0.603
-Confusion Matrix:
- [[ 81   1   0   8   2   8  14]
- [  4 135   8   4   1   5   3]
- [ 19  29 134  25  33  26  34]
- [ 18   2  32  84   1   5  11]
- [  1   9   8   5  60   1   3]
- [ 17   0   2   0   3  40   5]
- [  7   2   7   7  12  15  69]]
-Node Classification on random seed  6619 -> 0.62
-Confusion Matrix:
- [[ 79   3   2   7   4  17   1]
- [  6 114   2   0  25   1   5]
- [ 19  15 143  10  39  19  44]
- [ 13   6  22 112   8   5  18]
- [  0   4   6   0  69   1   6]
- [  1   2   1   4   2  44   3]
- [ 14   7  10   9   6  13  59]]
-Node Classification on random seed  6620 -> 0.621
-Confusion Matrix:
- [[ 74   2  14   8   6  13   2]
- [ 10 124   1   0  14   4   3]
- [ 25  18 144  35  29  23  30]
- [  7   2  28  92   4   5  16]
- [  0   6   4   0  54   1   3]
- [  5   1   1   3   3  61   3]
- [  8   5   5  14   5  13  72]]
-Node Classification on random seed  6621 -> 0.591
-Confusion Matrix:
- [[ 63   0   8   3   4  14  10]
- [  5 121   4   4  19   1   2]
- [ 26  28 107  39  58  16  40]
- [ 16   4  14 107   9   7   8]
- [  0   5   3   3  62   0   2]
- [  0   1   1   2   1  49   6]
- [  7   4  11   6   6  12  82]]
-Node Classification on random seed  6622 -> 0.622
-Confusion Matrix:
- [[ 70   2  13   2   4  12   6]
- [  6 103   8   2  16   5   8]
- [ 31  15 149  27  19  27  26]
- [ 24   2  21  96   3  11  12]
- [  0   9   7   0  66   2   3]
- [  6   0   2   3   0  47   5]
- [ 14   4   7   4   3   7  91]]
-Node Classification on random seed  6623 -> 0.61
-Confusion Matrix:
- [[ 69   4   0   1   3  13  19]
- [  2 136   7   0   9   3   1]
- [ 25  22 135  31  20  54  25]
- [ 10   5   9  86   8  13  18]
- [  2   8   7   1  63   1   1]
- [  5   1   1   4   0  43   6]
- [  7   2  11   6   6  19  78]]
-Node Classification on random seed  6624 -> 0.624
-Confusion Matrix:
- [[ 76   1   7   1   2  12  17]
- [  2 125   4   1   1   4   5]
- [ 19  21 150  34  18  36  37]
- [ 13   7  18 101   8   2   8]
- [  0  12   4   1  46   4   3]
- [  8   1   7   0   2  49   6]
- [ 11   6  10   2  12   9  77]]
-Node Classification on random seed  6625 -> 0.653
-Confusion Matrix:
- [[ 66   3   9   5   7  19   3]
- [  2 134   3   5   4   1   6]
- [ 24  24 142  28  24  15  47]
- [ 14   4  10 119   7   5   7]
- [  1   6   4   3  66   1   4]
- [  1   0   3   1   0  41   5]
- [ 12   3   5   2   4  16  85]]
-Node Classification on random seed  6626 -> 0.599
-Confusion Matrix:
- [[ 80   4   2   5   1   8  16]
- [  6 135   5   3   4   2   5]
- [ 27  32 118  55  13  11  50]
- [ 13   7  13  92   6   6  14]
- [  6   9   6   3  57   0   3]
- [  4   1   1   2   0  45   8]
- [  3   2   9  15   7  14  72]]
-Node Classification on random seed  6627 -> 0.616
-Confusion Matrix:
- [[ 57   0   0   3   2  27  11]
- [ 11 124   9   5   9   2   3]
- [ 29  26 163  36  15  13  50]
- [  5   0  23 111   6   5  17]
- [  1   5   4   2  59   1   5]
- [  3   1   6   1   0  29   2]
- [ 12   3  15   1   4  11  73]]
-Node Classification on random seed  6628 -> 0.68
-Confusion Matrix:
- [[ 69   1   6   6   1   6  11]
- [  2 145   6   0   6   1   6]
- [ 34  26 163  23  20  12  31]
- [ 12   3  15 108   1   1  13]
- [  2   6   7   1  59   1   3]
- [  2   0   3   4   1  42   7]
- [ 11   3   9   3   7   7  94]]
-Node Classification on random seed  6629 -> 0.601
-Confusion Matrix:
- [[ 57   7  15  13  12  12   8]
- [  2 110   4   7  10   5   6]
- [ 12  18 138  38  18  21  41]
- [ 18   1   7 109  24   3   6]
- [  1   6   3   7  64   1   2]
- [  4   3   3   5   1  40   1]
- [ 16   4  12   5   7  10  83]]
-Node Classification on random seed  6630 -> 0.629
-Confusion Matrix:
- [[ 71   1   0   1   7  10  16]
- [  3 137   5   0  16   2   0]
- [ 20  14 153  30  29  16  53]
- [ 23   7   9  78   9   6  18]
- [  2   4   8   1  61   0   0]
- [  2   4   1   1   0  43   7]
- [ 10   1   3   6  12  14  86]]
-Node Classification on random seed  6631 -> 0.609
-Confusion Matrix:
- [[ 61   4   0   9   3  18   4]
- [  5 134   4   3   2   2   2]
- [ 28  21 136  25  14  31  57]
- [ 11   5  15 101   2  16  15]
- [  2   8   7   1  53   4   1]
- [  4   2   4   0   1  50   7]
- [ 14   5  16   2   6  11  74]]
-Node Classification on random seed  6632 -> 0.595
-Confusion Matrix:
- [[ 72   1   4   4   3   6  16]
- [  6 115   6   4  12   4   6]
- [ 23  14 130  41  26   7  69]
- [ 12   2  16  92   6   7  21]
- [  0   5   4   2  51   3   7]
- [  7   1   0   1   3  60   6]
- [  5   1   4  17   8  15  75]]
-Node Classification on random seed  6633 -> 0.593
-Confusion Matrix:
- [[ 65   3  10   4  12   9  13]
- [  6 109  12   2   7   4   5]
- [ 29  23 139  48  24  18  33]
- [ 19   1  20 104   2   4   9]
- [  0   7   5   2  54   0   6]
- [  3   1   2   3   1  54   5]
- [  8   3  14   6   8  16  68]]
-Node Classification on random seed  6634 -> 0.579
-Confusion Matrix:
- [[ 68   5   3   5   7   8   8]
- [  4 122   9   3   3   6   2]
- [ 13  33 130  36  47  27  39]
- [ 15   2  20 107   3   4   2]
- [  0  13   1   5  53   2   3]
- [ 11   4   2   6   1  42   2]
- [  6  11  15  10   8  17  57]]
-Node Classification on random seed  6635 -> 0.574
-Confusion Matrix:
- [[ 59   2   6   2   5  11  18]
- [  3 138   3   3   9   7   2]
- [ 21  34 117  45  32  20  45]
- [ 16   7  26  99   5   5  13]
- [  1   9   2   1  61   0   4]
- [ 13   2   3   0   1  30   4]
- [ 14   3   4   6   4  15  70]]
-Node Classification on random seed  6636 -> 0.623
-Confusion Matrix:
- [[ 62   3   7   0   2   7  13]
- [ 11 115  16   5   4   1   5]
- [ 21  31 149  26  28  22  32]
- [  9   2  20 109   6   4  19]
- [  1  10   3   4  62   2   2]
- [  3   0   1   1   0  52   5]
- [ 24   2   5   3   4  13  74]]
-Node Classification on random seed  6637 -> 0.616
-Confusion Matrix:
- [[ 64   4   4  12   5   7   5]
- [  1 126   7   6   9   0   2]
- [ 15  34 154  16  18  25  46]
- [ 21   3  11  92   7   7  14]
- [  0   9   4   2  68   1   1]
- [ 13   1   5   2   0  39   4]
- [ 19   2  15   8   5  14  73]]
-Node Classification on random seed  6638 -> 0.565
-Confusion Matrix:
- [[ 58   1   3   3   3  11  27]
- [  7 131   8   0   4   1   4]
- [ 18  41 126  36  21  43  45]
- [ 14   5  12  75   3  12  18]
- [  1   9   5   1  64   0   4]
- [  4   4   1   2   0  47   4]
- [  4   5  14  14   9  14  64]]
-Node Classification on random seed  6639 -> 0.617
-Confusion Matrix:
- [[ 65  13   4   8   1  13   4]
- [  3 132   0   4   8   7   5]
- [ 33  25 145  29  24  19  35]
- [ 11   9  16 108   2   5   5]
- [  3   4   6   2  55   1   2]
- [  9   3   4   3   0  38   3]
- [ 14   8  10   9   3  16  74]]
-Node Classification on random seed  6640 -> 0.635
-Confusion Matrix:
- [[ 69   1   5   4   3  13  11]
- [  2 121   2   3   8   5   3]
- [ 20  25 144  31  35  16  25]
- [  3   2  22 108   5   7  11]
- [  2   3   3   5  71   1   5]
- [  5   1   4   1   1  39   9]
- [ 13   3  10   4  10  23  83]]
-Node Classification on random seed  6641 -> 0.57
-Confusion Matrix:
- [[ 59   2  15   6   3  20  10]
- [  4 141   5   7   2   5   3]
- [ 28  36 106  52  26  22  37]
- [ 14   1  16 107   5  11   5]
- [  1  16   3   0  40   4   9]
- [  2   2   0   3   0  49   3]
- [ 11   7   7   8   5  14  68]]
-Node Classification on random seed  6642 -> 0.645
-Confusion Matrix:
- [[ 72   2   5   1   9  16   6]
- [  2 135   2   0   2   0   3]
- [ 28  26 144  25  21  17  42]
- [  9   8  16 115   2   4  24]
- [  1   8   1   2  64   0   3]
- [  4   5   0   3   1  41   4]
- [  7   1  10   2  22  11  74]]
-Node Classification on random seed  6643 -> 0.618
-Confusion Matrix:
- [[ 72   1   1   7   3  15   4]
- [  6 120  11   0  12   2   5]
- [ 23  15 148  23  23  31  38]
- [ 14   3  26  92   2   6  14]
- [  0   4   5   0  63   0   4]
- [ 10   1   4   0   0  43  11]
- [ 25   2   5   7   3  16  80]]
-Node Classification on random seed  6644 -> 0.593
-Confusion Matrix:
- [[ 72   4   0   4   1   3  20]
- [  7 116  13   4  16   2   2]
- [ 24  19 134  58  23  24  29]
- [ 18   3  19 106   2   3  10]
- [  0  11   2   2  60   1   0]
- [  6   4   2   3   2  45   7]
- [  8   1   9  16   5  20  60]]
-Node Classification on random seed  6645 -> 0.618
-Confusion Matrix:
- [[ 58   1   3   7   5  19   8]
- [  8 118   5   2  10   5   9]
- [ 16  15 137  37  45  16  40]
- [ 15   3  20 114   6   4   9]
- [  1   3   3   2  70   1   2]
- [  2   3   2   5   2  39   8]
- [  5   5   8   2   7  13  82]]
-Node Classification on random seed  6646 -> 0.591
-Confusion Matrix:
- [[ 82   2   5   6   4  12   8]
- [  5 128   6   1   6   0   9]
- [ 12  51 105  36  41  14  37]
- [ 15  10  13 104   3   8  14]
- [  3   6   4   1  60   0   2]
- [  4   2   4   0   0  43   4]
- [ 15   9   0   6   8  23  69]]
-Node Classification on random seed  6647 -> 0.618
-Confusion Matrix:
- [[ 71   5   6  17   1   8   3]
- [  1 120  12   5   7  11   3]
- [ 48  20 146  29  16  26  24]
- [  8   3  16 109   3   9   9]
- [  1  13   4   2  54   3   3]
- [  8   0   3   0   1  41   5]
- [  8   2  10  12   3  14  77]]
-Node Classification on random seed  6648 -> 0.61
-Confusion Matrix:
- [[ 82   2   7  11   4   6  10]
- [  3 110   5   2  12   3   1]
- [ 26  20 148  63  24  23  31]
- [  7   3  12 107   1   4  14]
- [  1   5   1   4  60   0   1]
- [  4   0   3   6   0  43   1]
- [ 21   6  14  13   6  10  60]]
-Node Classification on random seed  6649 -> 0.615
-Confusion Matrix:
- [[ 67   4   8   1   4  15  12]
- [  3 115   7   6   8   3   3]
- [ 15  15 136  43  18  42  39]
- [ 11   3  11 110   4  10   8]
- [  1   3   8   0  64   4   2]
- [ 13   0   3   1   0  38   4]
- [ 12   5   4   9   3  20  85]]
-Node Classification on random seed  6650 -> 0.638
-Confusion Matrix:
- [[ 79   2   1   3   5  15  13]
- [ 10 134   7   0   5   2   8]
- [ 24  14 160  29  19  17  38]
- [ 12   7  11  99   5  13  13]
- [  0   5   6   1  45   0   2]
- [  3   2   5   4   2  43   4]
- [ 15   3  17   4   7   9  78]]
-Node Classification on random seed  6651 -> 0.595
-Confusion Matrix:
- [[ 89   4   0   6   3  10   9]
- [  2 120   6   1  20   5   2]
- [ 22  22 115  50  54  20  25]
- [  8   7  21 111   3   4   7]
- [  0   5   0   3  57   0   1]
- [  6   1   1   1   1  54   3]
- [  8   4   6  22   7  25  49]]
-Node Classification on random seed  6652 -> 0.613
-Confusion Matrix:
- [[ 79   2   0   9   6   9  16]
- [  3 117   3   2   4   1   9]
- [ 14  33 148  32  20  28  38]
- [ 12   7  28  89   1   8   8]
- [  2   8   7   0  62   1   1]
- [  2   0   3   1   0  44  11]
- [ 14   5   6  11   8  14  74]]
-Node Classification on random seed  6653 -> 0.649
-Confusion Matrix:
- [[ 79   8   6   6   1   9   6]
- [  4 140   9   3  10   1   1]
- [  9  16 147  41  30  28  48]
- [  8   5   7 106  10   4  13]
- [  1   7   1   3  59   1   5]
- [  5   2   0   0   2  44   2]
- [  9   2   1   7   3  17  74]]
-Node Classification on random seed  6654 -> 0.597
-Confusion Matrix:
- [[ 51   3   3   5   7  22   2]
- [  3 134   5   4   5   5   7]
- [ 33  11 113  44  45  24  39]
- [ 14   5   9 112   4   5   9]
- [  1   4   3   0  66   3   4]
- [  4   2   1   2   2  42   2]
- [ 16   1   7   9   9  20  79]]
-Node Classification on random seed  6655 -> 0.608
-Confusion Matrix:
- [[ 88   1   0   5   5  12   5]
- [  4 130   6   4   4   3  10]
- [ 35  29 148  35  18  26  28]
- [ 16   6  15  85   3   8  13]
- [  0  10   8   1  61   3   1]
- [  3   4   3   1   1  41   3]
- [ 17   4  13   1   4  24  55]]
-Node Classification on random seed  6656 -> 0.638
-Confusion Matrix:
- [[ 64   4   9   2  11  11   3]
- [  9 135   4   2   2   2   5]
- [ 21   9 147  23  41  13  48]
- [ 16   2  19  96   3   3  16]
- [  4   8   4   0  59   0   2]
- [  4   4   4   3   1  48   3]
- [  9   3   8   7  13   7  89]]
-Node Classification on random seed  6657 -> 0.599
-Confusion Matrix:
- [[ 83   3   2   8   2  14  12]
- [  4 107  10   7   3   2   7]
- [ 21  14 142  40  43  29  34]
- [ 14   2  15  93   8   9  17]
- [  1   9   2   0  65   0   1]
- [  5   1   2   3   0  31   8]
- [  2   4   3  11  16  13  78]]
-Node Classification on random seed  6658 -> 0.58
-Confusion Matrix:
- [[ 64   4   7  14   8  13   3]
- [  6 125   6   6  12   0   6]
- [ 25  14 132  46  21  18  45]
- [ 16   4  27 101   6   6   8]
- [  2   4   3   5  61   0   3]
- [  8   2   9   2   1  32   2]
- [  7   0   6  19  11  15  65]]
-Node Classification on random seed  6659 -> 0.6
-Confusion Matrix:
- [[ 78   7   5   3   4  11   7]
- [  0 109   2   5  13   3   3]
- [ 27  19 146  26  51  35  32]
- [ 16   4  13  87   6   7   7]
- [  0   6   3   3  64   0   1]
- [  8   1   3   1   0  42  12]
- [ 11  10   6   7   9  13  74]]
-Node Classification on random seed  6660 -> 0.619
-Confusion Matrix:
- [[ 55   2   6   6   9  11   8]
- [  4 141   3   5   8   2   3]
- [ 23  15 123  50  44  15  32]
- [  5   3  10 111  14   6  10]
- [  1   6   4   1  65   1   5]
- [  9   0   4   0   1  47  11]
- [ 10   6   6   8   7   7  77]]
-Node Classification on random seed  6661 -> 0.591
-Confusion Matrix:
- [[ 63   4   7   3   4  20   4]
- [  1 123   8   4   5   6   1]
- [ 27  22 107  37  42  24  47]
- [ 12   6   7 100   6   8  12]
- [  1   6   2   1  59   1   2]
- [  8   1   3   1   0  41   8]
- [  6   2   4  12   5  29  98]]
-Node Classification on random seed  6662 -> 0.62
-Confusion Matrix:
- [[ 72   5   4   3   4   9   8]
- [  8 128   5   6   8   5   4]
- [ 23  28 150  35  25  28  31]
- [ 11   2   7  93  19   7   5]
- [  0   6   4   1  57   5   3]
- [  2   1   5   4   1  52   2]
- [ 14   4   7  10   4  17  68]]
-Node Classification on random seed  6663 -> 0.613
-Confusion Matrix:
- [[ 69   5   3   8   5   9  11]
- [  7 129   5   0  13   0  11]
- [ 22  26 132  22  26  18  33]
- [ 13   3  13 112  11  10  16]
- [  1   6   5   1  60   1   2]
- [  8   1   0   1   2  47   4]
- [ 10   5  10   9  12  19  64]]
-Node Classification on random seed  6664 -> 0.612
-Confusion Matrix:
- [[ 71   3   2   5   6  14   8]
- [  2 128   4   0  16   2   1]
- [ 30  27 128  34  37  22  36]
- [ 13   5  19 103   7   5   5]
- [  0   6   4   1  69   0   1]
- [  5   4   0   0   1  40   7]
- [ 11  10   7   6   9  13  73]]
-Node Classification on random seed  6665 -> 0.627
-Confusion Matrix:
- [[ 65   8   5   7   6   8  17]
- [  7 119   5   1  10   6   1]
- [ 33   9 151  21  21  18  31]
- [  9   3  30 110   8   1   8]
- [  0   7   5   2  61   1   0]
- [  4   3   2   6   2  39   6]
- [ 12   3  10  20  11   6  82]]
-Node Classification on random seed  6666 -> 0.631
-Confusion Matrix:
- [[ 57   3  13   5   2   7  16]
- [  6 127   4   3   2   3   2]
- [ 22  24 144  35  21  23  29]
- [  6   9  21 113   3   5  23]
- [  7   5   4   3  52   0   2]
- [  2   3   4   0   3  50   4]
- [  9   5  13   3   2  13  88]]
-Node Classification on random seed  6667 -> 0.6
-Confusion Matrix:
- [[ 62   2   7   9   4  13  14]
- [  2 123  11   1  13   2   1]
- [ 22  26 138  36  16  36  38]
- [  5   2  20 103  10   3  10]
- [  1   2   6   0  66   1   2]
- [  6   4   0   5   0  44   6]
- [  4   5   6   6   7  36  64]]
-Node Classification on random seed  6668 -> 0.654
-Confusion Matrix:
- [[ 82   4   3   2   4   7   5]
- [  2 111   9   1   9   4   2]
- [ 20  19 170  30  22  18  38]
- [ 10   1  16 116   3   5  16]
- [  0   6   1   2  54   3   7]
- [  5   2   3   3   3  46   4]
- [ 14   4   7  12   9  11  75]]
-Node Classification on random seed  6669 -> 0.609
-Confusion Matrix:
- [[ 65   2   4   2   7  14   7]
- [  4 122   8   6   7   4   5]
- [ 21  21 138  31  30  26  44]
- [ 21   6  16  86   4   5  20]
- [  0   2   2   0  64   2   5]
- [  3   1   3   0   0  53   5]
- [  8   2   9   6  14  14  81]]
-Node Classification on random seed  6670 -> 0.659
-Confusion Matrix:
- [[ 71   2   7   4   7  14   1]
- [  6 119   4   0   7   5   5]
- [ 19  18 165  39  19  20  29]
- [ 16   5  14 124   4   5   6]
- [  0   9   3   1  62   2   2]
- [  2   4   2   1   1  55   2]
- [  8   4   4  11   9  20  63]]
-Node Classification on random seed  6671 -> 0.6
-Confusion Matrix:
- [[ 70   1   6   8   7   9   4]
- [  7 115  12   6  11   1   1]
- [ 33  33 138  41  11  30  38]
- [ 21   3   4  96   2   7  19]
- [  0   1   6   1  52   0   3]
- [  6   3   1   5   0  43   6]
- [  8   3   7  10   6  19  86]]
-Node Classification on random seed  6672 -> 0.575
-Confusion Matrix:
- [[ 76   3   9  10   2   2   7]
- [ 18 122   7   2  10   1   1]
- [ 40  27 115  23  51   9  44]
- [ 11   2  14 101   2   8   6]
- [  0   6   1   3  51   2   2]
- [ 14   2   9   3   7  41   4]
- [ 16   4   9   5  10  19  69]]
-Node Classification on random seed  6673 -> 0.607
-Confusion Matrix:
- [[ 62   0   4   2   3  16  15]
- [  8 132   6   3   6   3   2]
- [ 34  12 148  36  16  23  39]
- [ 13   4  15  94   5   4  18]
- [  2  11   4   4  56   2   3]
- [  9   1   1   3   3  50   5]
- [ 17   4   6   5  10  16  65]]
-Node Classification on random seed  6674 -> 0.607
-Confusion Matrix:
- [[ 78   1   4   5   2  12  11]
- [  7 121  13   6   4   2   2]
- [ 37  19 153  29  19  30  19]
- [ 21   7  16  91   1   7  17]
- [  2  10   4   2  44   0   2]
- [ 14   1   2   2   0  46   1]
- [ 17   3  10   3   5  24  74]]
-Node Classification on random seed  6675 -> 0.626
-Confusion Matrix:
- [[ 69   2  14   5   2   5   4]
- [  2 127  11   3  11   0   8]
- [ 16  20 152  38  33  13  42]
- [  4   5  22 107   5   5   6]
- [  2   6   6   3  56   1   3]
- [  2   2   3   1   1  44   7]
- [ 13   2  12  11   6  17  71]]
-Node Classification on random seed  6676 -> 0.607
-Confusion Matrix:
- [[ 77   3   0   4   3   6  12]
- [  9 112   4   1  11   4   5]
- [ 11  21 168  40  29  13  42]
- [ 19   0  16  94   6   5  14]
- [  1   8   3   2  52   1   3]
- [ 10   0   5   2   0  39   8]
- [ 24   2  11   9   6  20  65]]
-Node Classification on random seed  6677 -> 0.628
-Confusion Matrix:
- [[ 82   3   0   8   1   6   8]
- [  4 122   4   8   5   2   7]
- [ 21  17 140  54  26  22  33]
- [ 11   1  18 108   8  12   8]
- [  1   2   4   3  61   0   3]
- [ 13   2   1   1   2  39   1]
- [ 13   2   9  12   2  14  76]]
-Node Classification on random seed  6678 -> 0.57
-Confusion Matrix:
- [[ 62   9   5   4   2  17  10]
- [  2 108  11   1  16   3   8]
- [ 40  18 115  28  42  29  31]
- [ 16   3  13 101   8   9  10]
- [  0   4   5   1  59   0   3]
- [  4   3   2   1   1  52   3]
- [ 11   4   9  11  12  21  73]]
-Node Classification on random seed  6679 -> 0.624
-Confusion Matrix:
- [[ 70   5   2   1   3  16   0]
- [  6 126   5   1   7   4   6]
- [ 15  28 145  17  44  31  34]
- [  7   1  13  96  12   5  26]
- [  0   6   2   0  58   3   4]
- [  0   4   2   0   2  53   5]
- [ 12   4   5   2  16  20  76]]
-Node Classification on random seed  6680 -> 0.639
-Confusion Matrix:
- [[ 64   3   2   4   3   8  16]
- [  6 131   4   2   2   2   7]
- [ 27  24 156  40  24  16  34]
- [  8   4  24 104   4   4   8]
- [  1   3   5   3  69   1   1]
- [  7   0   1   0   0  39   6]
- [ 14   3  12   3   8  17  76]]
-Node Classification on random seed  6681 -> 0.574
-Confusion Matrix:
- [[ 74   1   6   3   1   8  11]
- [  4 122  11   6  13   6   4]
- [ 27  14 114  31  26  42  56]
- [  7   4  30  85   3   7  25]
- [  0   8   2   1  58   1   2]
- [  1   0   3   0   2  46   6]
- [  7   5  11   3   6  22  75]]
-Node Classification on random seed  6682 -> 0.655
-Confusion Matrix:
- [[ 76   3   6   3   4  13   5]
- [  4 136   6   3   7   2   5]
- [ 27  15 151  27  17  15  50]
- [  9   5  16 112   5   8   8]
- [  3   8   0   2  60   0   3]
- [  4   3   2   5   3  35   8]
- [  6   1   8   2   7  17  85]]
-Node Classification on random seed  6683 -> 0.631
-Confusion Matrix:
- [[ 80   3   3   2   3   9  11]
- [  6 136   8   6   6   4   1]
- [ 27  27 136  25  14  25  53]
- [ 10   2   4 119   6  11  10]
- [  0  11   5   2  63   1   1]
- [  8   1   2   0   1  46   5]
- [ 10   4   8  11  11  12  51]]
-Node Classification on random seed  6684 -> 0.596
-Confusion Matrix:
- [[ 82   2   3   2   1  13  11]
- [  0 122  10   1   7   3   3]
- [ 26  34 128  39  25  22  51]
- [  9   2  19  91   5   4  10]
- [  3   7   5   2  60   0   0]
- [  7   0   0   4   0  37   5]
- [  8   8   9   8   9  27  76]]
-Node Classification on random seed  6685 -> 0.634
-Confusion Matrix:
- [[ 67   3   5   5   5   7  13]
- [  8 134   0   4  12   2   2]
- [ 12  11 150  32  33  38  34]
- [ 15   4  19 116   3  12   8]
- [  5   3   5   0  59   0   0]
- [  5   0   7   1   1  34  10]
- [  5   0  13   7  11   6  74]]
-Node Classification on random seed  6686 -> 0.582
-Confusion Matrix:
- [[ 62   2   5   9   3   5  15]
- [  4 122   5   2  10   4  11]
- [ 22  21 119  20  42  18  73]
- [ 16   6   7 101   6  11  20]
- [  0   5   5   1  56   0   4]
- [  1   1   8   2   1  42   9]
- [  7   6  14   2   2  13  80]]
-Node Classification on random seed  6687 -> 0.583
-Confusion Matrix:
- [[ 73   1   8   9   3   9  13]
- [  1 120   9   4  19   5   3]
- [ 18  23 123  30   7  32  60]
- [ 26   6  20  94   2  10  13]
- [  2   4   3   4  72   0   1]
- [  7   0   1   6   1  41   4]
- [ 11   1   5  13  10  13  60]]
-Node Classification on random seed  6688 -> 0.626
-Confusion Matrix:
- [[ 69   2   1   7   5  20   8]
- [  6 117   4   0   8   9   5]
- [ 39  29 147  44  20  16  23]
- [  9   2   8 106   4   4  21]
- [  1   6   5   0  62   0   2]
- [  6   0   2   1   1  48   4]
- [  8   4   8   7  10  15  77]]
-Node Classification on random seed  6689 -> 0.627
-Confusion Matrix:
- [[ 78   0   3   7   8  12   7]
- [  7 111   8   5   3   4   4]
- [ 27  18 143  30  50  23  37]
- [  7   6  16 108   2   6   5]
- [  1   5   3   5  60   0   0]
- [  1   1   3   1   0  53   7]
- [ 16   0   7   5   9  14  74]]
-Node Classification on random seed  6690 -> 0.647
-Confusion Matrix:
- [[ 57   1   1   4   2  12  19]
- [ 10 135   8   3   8   0   5]
- [ 20  34 172  21  25  15  35]
- [ 10   0   6  88   9   9  19]
- [  5   4   1   1  67   2   0]
- [  4   0   3   2   0  47   9]
- [ 15   3   7   6   7   8  81]]
-Node Classification on random seed  6691 -> 0.627
-Confusion Matrix:
- [[ 58   3   3  11   3  14  16]
- [  3 142   3   4   7   5   3]
- [ 18  17 140  21  20  23  47]
- [ 18   6  21 110   5   4   9]
- [  0   4   2   0  54   1   5]
- [  4   0   2   2   2  43   2]
- [ 16   8   6   6  13  16  80]]
-Node Classification on random seed  6692 -> 0.607
-Confusion Matrix:
- [[ 75   4   6   4   4  17  13]
- [  1 113   5   2   3   5   7]
- [ 26  14 153  45  34  17  41]
- [  6   4  23  76   6   4  30]
- [  0   4   1   0  66   1   1]
- [  4   1   2   2   0  39   5]
- [ 10   6   7  10   5  13  85]]
-Node Classification on random seed  6693 -> 0.618
-Confusion Matrix:
- [[ 82   1   4   3   3  11   5]
- [  8 127   3   0  10   1   5]
- [ 25  19 141  41  45  29  26]
- [  9   5   7 106   5  11  27]
- [  3   5   3   0  59   0   2]
- [  4   3   2   2   1  41   0]
- [ 18   1   6   7   6  16  62]]
-Node Classification on random seed  6694 -> 0.581
-Confusion Matrix:
- [[ 65   5   4  16   7   8   9]
- [  8 117   2   0   4   0   8]
- [ 36  21 139  35  31  29  32]
- [ 18   9  16  96  11   6  13]
- [  3   5   3   0  59   4   0]
- [ 10   0   7   0   2  37   3]
- [  8   5  17   6   5  13  68]]
-Node Classification on random seed  6695 -> 0.605
-Confusion Matrix:
- [[ 70   3   4   4   3  12  16]
- [  3 111  11   0   2   4   3]
- [ 29  23 123  34  29  28  50]
- [ 24   6  10 106   3   8  13]
- [  1   4   7   1  69   0   2]
- [  5   2   1   1   3  43   4]
- [  9   3  11   5   7   7  83]]
-Node Classification on random seed  6696 -> 0.646
-Confusion Matrix:
- [[ 80   8   2   5   6   2   8]
- [  2 140   6   1  11   0   3]
- [ 17  12 152  29  31  18  38]
- [  4   7  23 109   2   8  14]
- [  1   1   4   1  63   2   3]
- [ 14   0   3   1   1  33   7]
- [ 14   3   9   8  14  11  69]]
-Node Classification on random seed  6697 -> 0.673
-Confusion Matrix:
- [[ 73   5   3   6   7  15   8]
- [  2 147   4   2   3   3   3]
- [ 21  20 177  23  20   9  35]
- [  4   6  17 112   1  13  12]
- [  0   6   4   0  64   0   3]
- [  2   0   3   2   1  38   7]
- [ 16   4  15   1   7  14  62]]
-Node Classification on random seed  6698 -> 0.659
-Confusion Matrix:
- [[ 81   4   3   4   6  12   3]
- [  5 119   2   0   9   4   9]
- [ 14  31 168  26  20  17  36]
- [  4  10  16 109   6   5   9]
- [  0   5   5   0  57   0   6]
- [  1   3   2   4   1  52   0]
- [  6   5  13  14   5  16  73]]
-Node Classification on random seed  6699 -> 0.611
-Confusion Matrix:
- [[ 57   2  12   2   4  16  13]
- [  6 117   2   2  10   2   5]
- [ 13  32 163  25  26  19  52]
- [ 12   5  25  91   8   3  14]
- [  1   7   7   3  54   0   2]
- [  5   0   5   0   0  46   1]
- [ 12   2   5   8   7  14  83]]
-Node Classification on random seed  6700 -> 0.636
-Confusion Matrix:
- [[ 80   5   3   3   3  22   4]
- [  0 151   4   4   4   4   1]
- [ 29  27 131  24  23  22  36]
- [ 15   1  19  92  21   8  20]
- [  1   3   1   3  64   1   3]
- [  0   2   1   2   2  42   6]
- [  9   6   4   2   5  11  76]]
-Node Classification on random seed  6701 -> 0.62
-Confusion Matrix:
- [[ 53   3   1   5   1  14  20]
- [  0 129  11   1   4   4   6]
- [ 21  11 156  32  15  36  46]
- [ 10   5  15 120   3   3  13]
- [  1   3   7   6  45   0   3]
- [  3   3   5   1   0  45   1]
- [ 13  16   9   5   7  17  72]]
-Node Classification on random seed  6702 -> 0.58
-Confusion Matrix:
- [[ 74   4   7   1   3  12   5]
- [  4 120  15   1   7   7   3]
- [ 11  31 106  24  33  35  65]
- [  5   3  17 115   1   7  19]
- [  3   8   7   2  60   0   2]
- [  4   1   1   4   0  48   4]
- [ 16   5  10   3   8  22  57]]
-Node Classification on random seed  6703 -> 0.654
-Confusion Matrix:
- [[ 69   1   1   1   1   5   7]
- [  6 109   8   0   2   6   6]
- [ 31  10 155  30  17  21  46]
- [ 12   2  10 120   4   9  22]
- [  2   5   6   5  61   1   2]
- [  5   0   5   1   2  42   5]
- [  9   4  10  10   6  10  98]]
-Node Classification on random seed  6704 -> 0.598
-Confusion Matrix:
- [[ 64   2   1   3   2   7  14]
- [  5 131  10  11  12   0   2]
- [ 15  26 111  30  36  17  67]
- [ 11   2   6 113   7   5  17]
- [  1   7   3   3  58   3   2]
- [ 10   0   4   4   1  39   7]
- [ 13   4   5  12   9   6  82]]
-Node Classification on random seed  6705 -> 0.599
-Confusion Matrix:
- [[ 70   2   6   4   3  10  17]
- [  6 114   8   2   6   2   0]
- [ 24  35 135  35  43  30  30]
- [ 10   8  12 104   9   3  10]
- [  2   3   5   3  52   1   1]
- [  8   1   2   5   1  43   2]
- [ 11   6   6   6  12  11  81]]
-Node Classification on random seed  6706 -> 0.595
-Confusion Matrix:
- [[ 53   3   2   7   4  11  23]
- [  7 149   9   6   4   1   2]
- [ 32  21 113  34  31  16  50]
- [  5  10  12 115   3  10  13]
- [  3   4   2   1  47   0   2]
- [  5   4   0   5   2  45   4]
- [ 18   7   5   7   8  12  73]]
-Node Classification on random seed  6707 -> 0.621
-Confusion Matrix:
- [[ 66   0   3   7   8  14   3]
- [  0 140   4   1   7   7   4]
- [ 13  24 139  46  17  33  40]
- [ 15   7  19 105   2   6  10]
- [  1   8   1   1  55   2   0]
- [  4   1   1   2   4  44   2]
- [ 10   4  10  14   3  21  72]]
-Node Classification on random seed  6708 -> 0.602
-Confusion Matrix:
- [[ 60   5   4  13   2   9   9]
- [  3 131   2   0   1   3   6]
- [ 24  28 132  29  17  45  35]
- [  8   5  35 105   4   3  10]
- [  2  11   3   2  58   4   2]
- [  5   7   6   0   0  39   6]
- [ 10   3   7   8   6  16  77]]
-Node Classification on random seed  6709 -> 0.606
-Confusion Matrix:
- [[ 72   3   6   1   9   4   9]
- [ 11 117   5   4   9   5   1]
- [ 22  20 131  52  26  12  52]
- [ 15   3  24  98   6  12   3]
- [  2  10   2   0  57   0   3]
- [  0   0   3   1   1  51   4]
- [ 15   2  11   8   9   9  80]]
-Node Classification on random seed  6710 -> 0.589
-Confusion Matrix:
- [[ 69   1   2   5   5  23  19]
- [  4 128   8   4  10   1   5]
- [ 18  28 133  25  32  20  48]
- [ 14   2  26  76   7   7  19]
- [  2   3   4   2  64   1   1]
- [  2   2   3   5   0  41   5]
- [  4   3   9   8   7  17  78]]
-Node Classification on random seed  6711 -> 0.601
-Confusion Matrix:
- [[ 62   1   9  10   4   7  14]
- [ 15 102   9   4   6   7   2]
- [ 39  18 145  21  36  18  43]
- [ 13   2  11 114   7   3  16]
- [  2   1   8   1  68   1   1]
- [  6   1   0   4   0  36  15]
- [ 16   6   6   4   6   6  74]]
-Node Classification on random seed  6712 -> 0.614
-Confusion Matrix:
- [[ 82   2   1   8   4  10  12]
- [  9 120   2   5   7   8   3]
- [ 16  31 144  64  19  10  38]
- [ 17   4  15  98   5   3   7]
- [  4   4   6   3  43   1   2]
- [  3   0   1   3   0  46   7]
- [ 14   3   6  12   6  11  81]]
-Node Classification on random seed  6713 -> 0.64
-Confusion Matrix:
- [[ 81   2   2   3   6   8   5]
- [  4 130   5   5   9   1   4]
- [ 28   8 135  28  33  30  32]
- [  7   3  18 113   5   4  15]
- [  3   5   6   0  66   3   3]
- [  5   3   1   2   3  39   8]
- [ 12   2  11   3   7  18  76]]
-Node Classification on random seed  6714 -> 0.594
-Confusion Matrix:
- [[ 61   4   2  10   7  14  10]
- [  9 132   6   7   8   1   4]
- [ 27  30 141  31  19  22  40]
- [ 29   4  21  87   4   6   5]
- [  0   4   3   3  64   0   0]
- [  7   1   8   0   1  42   4]
- [ 19   2   7   7   9  11  67]]
-Node Classification on random seed  6715 -> 0.629
-Confusion Matrix:
- [[ 73   4   1   9   7   9  10]
- [  1 137   5   6   6   0   6]
- [ 31  23 138  42  20  21  31]
- [ 20   3  11 113   9   5   6]
- [  2   6   3   4  59   1   8]
- [  3   0   1   2   0  42   4]
- [ 12   0  10  12   6  11  67]]
-Node Classification on random seed  6716 -> 0.58
-Confusion Matrix:
- [[ 42   5  13   7   5  11  12]
- [  3 130   9   8  10   3   6]
- [ 23  10 142  35  51  13  27]
- [ 11  10  14  95  15  15   7]
- [  0   6   7   0  59   0   3]
- [ 11   2   1   0   3  39   4]
- [ 10   4   7   6   8  25  73]]
-Node Classification on random seed  6717 -> 0.659
-Confusion Matrix:
- [[ 68   3   3   7   5   8  15]
- [  4 141   5   4  10   0   1]
- [ 24  26 148  32  23  20  15]
- [  6   6  13 109   4   9  10]
- [  2   4   6   2  64   0   2]
- [  3   3   4   8   0  43   6]
- [ 12   3  10   8   3  12  86]]
-Node Classification on random seed  6718 -> 0.578
-Confusion Matrix:
- [[ 57   1   0   5   2  23  12]
- [  5 135   3   3   6   1   6]
- [ 27  37 126  49  16  21  36]
- [ 15   8  20  93   7  12  19]
- [  3   8   3   1  57   2   2]
- [  2   2   2   0   1  32  13]
- [  3   2  15   5   4  20  78]]
-Node Classification on random seed  6719 -> 0.597
-Confusion Matrix:
- [[ 62   3   3   9   4   8   9]
- [  6 132   5   1   7   0   6]
- [ 25  23 132  36  35  26  39]
- [  8   7  23 104   9   8  11]
- [  0   6   4   2  57   2   1]
- [  9   2   3   6   1  40   6]
- [  6   1   7  10   9  17  70]]
-Node Classification on random seed  6720 -> 0.6
-Confusion Matrix:
- [[ 72   1   1   4   2   7   8]
- [ 10 129   8   0   1   4   6]
- [ 25  12 117  78  36  18  20]
- [ 11   7  33  92   1  10  14]
- [  2   4   6   3  61   3   2]
- [  9   2   0   1   0  53   0]
- [ 12   4   5  10   8  12  76]]
-Node Classification on random seed  6721 -> 0.6
-Confusion Matrix:
- [[ 55   3  12   7   0  14   6]
- [  4 134   2   1  18   6   1]
- [ 23  26 140  24  16  31  49]
- [ 10   3  11  98  10   7  24]
- [  0   4   5   1  55   2   3]
- [  2   0   0   4   6  39   5]
- [ 10   4  14   7   9  16  79]]
-Node Classification on random seed  6722 -> 0.574
-Confusion Matrix:
- [[ 77   1  14   6   4   9   6]
- [  7 116   6   4   5   4   3]
- [ 19  17  88  66  36  31  43]
- [ 12   6  17 104   2  12   7]
- [  3   6   0   3  60   1   4]
- [  5   0   0   0   1  51   7]
- [ 13   5   6  12   5  18  78]]
-Node Classification on random seed  6723 -> 0.612
-Confusion Matrix:
- [[ 68   1   4  13   1  10  10]
- [  5 142   5   2   7   5   3]
- [ 28  22 134  40  24  20  46]
- [ 16   6  10  94   7   9  14]
- [  3   7   3   2  58   0   2]
- [  6   1   4   3   0  38   5]
- [ 13   7   3   7   5   9  78]]
-Node Classification on random seed  6724 -> 0.637
-Confusion Matrix:
- [[ 94   2   2   3   6   7   8]
- [  2 129   8   2   8   1   1]
- [ 16  23 152  42  23  16  57]
- [  9   8  15 105   1   2   9]
- [  0   6   4   0  62   4   1]
- [  8   0   1   0   2  34   6]
- [ 13   3  14   6  11  13  61]]
-Node Classification on random seed  6725 -> 0.625
-Confusion Matrix:
- [[ 64   3   5  11  10   6  17]
- [  3 117   6   3  17   2   7]
- [ 18  25 145  26  23  16  39]
- [  9   6  13 101   6   6  12]
- [  0   3   2   2  66   0   3]
- [  8   1   6   0   2  43   6]
- [ 12   1  16   1   7  16  89]]
-Node Classification on random seed  6726 -> 0.635
-Confusion Matrix:
- [[ 60   2  10   5   2  10   6]
- [  2 134   6   4   4   1   2]
- [ 15  25 131  30  22  30  43]
- [  7   4  11 119   5   8  17]
- [  1  13   2   2  67   2   2]
- [  5   3   0   1   2  46   3]
- [  7   5   4  12   7  23  78]]
-Node Classification on random seed  6727 -> 0.626
-Confusion Matrix:
- [[ 77   7   5   2   4   7  14]
- [  0 134   1   1  10   5   3]
- [ 23  21 137  21  48   6  36]
- [ 24   6  19 101   4   6  13]
- [  1   3   1   0  63   0   4]
- [  7   1   1   1   2  43  12]
- [ 17   4   5  12  12   5  71]]
-Node Classification on random seed  6728 -> 0.608
-Confusion Matrix:
- [[ 70   4   5   4   5  13  13]
- [  0 124   2   5   9   3   3]
- [ 20  26 124  52  34  32  32]
- [ 10   2   8 108   6   5  17]
- [  0   8   5   1  56   0   1]
- [  7   2   0   2   3  51   5]
- [ 11   2   9   8   9   9  75]]
-Node Classification on random seed  6729 -> 0.591
-Confusion Matrix:
- [[ 73   0   1   8   6  10  17]
- [  4 118  10   5   2   4   6]
- [ 23  17 144  33   7  29  54]
- [  6   1  12  97   7   8  33]
- [  3   6  12   1  48   2   5]
- [ 14   3   1   0   1  33  11]
- [ 17   2   7   5   9   7  78]]
-Node Classification on random seed  6730 -> 0.621
-Confusion Matrix:
- [[ 73   3   8   6  10   8   4]
- [  4 139   2   2   4   3   7]
- [ 38  34 119  22  23  20  31]
- [  9   4  18 113   4   5   7]
- [  2  11   2   1  68   0   3]
- [  6   4   2   4   1  47   5]
- [ 10   6   9   0  12  25  62]]
-Node Classification on random seed  6731 -> 0.63
-Confusion Matrix:
- [[ 56   5   3   9   3  14  13]
- [  2 140   5   1   9   4   5]
- [ 25  20 147  44   5  30  32]
- [  9   5  10 115   1   5   7]
- [  1   6   8   4  55   3   2]
- [  5   1   1   5   0  46   5]
- [ 16   3  18   6   7  13  71]]
-Node Classification on random seed  6732 -> 0.656
-Confusion Matrix:
- [[ 77   4   3   5   5  10   1]
- [  4 134   5   2  10   1   4]
- [ 26  15 153  22  35  15  50]
- [  9   1  11 108  15   4   8]
- [  2   3   6   0  64   0   4]
- [  9   1   2   0   1  49   2]
- [ 16   2   6  12   9   4  71]]
-Node Classification on random seed  6733 -> 0.616
-Confusion Matrix:
- [[ 76   4   5   3   0  11   9]
- [  6 128   1   4   2   2  10]
- [ 12  33 145  23  40  29  30]
- [ 10   7  22  97  13   5  12]
- [  3   8   0   3  64   2   4]
- [  3   1   4   4   3  44   3]
- [  7   2   9  12  10  13  62]]
-Node Classification on random seed  6734 -> 0.617
-Confusion Matrix:
- [[ 74   6   6   4   6  10  10]
- [  1 133   6   1   7   4   2]
- [ 21  20 138  26  34  27  41]
- [ 10   3  12 109   6   7  21]
- [  1   6   7   2  53   3   0]
- [  9   2   2   2   1  35   3]
- [ 13   2  13   1  14  11  75]]
-Node Classification on random seed  6735 -> 0.623
-Confusion Matrix:
- [[ 58   6   3   7   4  13   6]
- [  5 135   3   0   7   1   5]
- [ 30  22 126  50  16  28  33]
- [ 10   4  16 120   5   5  10]
- [  0   5   4   2  52   4   5]
- [ 11   0   2   3   0  45   6]
- [ 12   3   5   5   9  12  87]]
-Node Classification on random seed  6736 -> 0.554
-Confusion Matrix:
- [[ 52   4   2   3   2  24  12]
- [  9 133  11   0   8   3   1]
- [ 20  34 123  22  19  51  38]
- [ 11   3  27  84   4   8  24]
- [  2   2   8   4  59   2   3]
- [  2   0   1   0   1  27  24]
- [ 18   5  11   2   5  16  76]]
-Node Classification on random seed  6737 -> 0.625
-Confusion Matrix:
- [[ 62   6   2   4   3  18  22]
- [  2 138   4   2  10   6   0]
- [ 17  12 136  25  32  32  25]
- [ 17   3  10 102   9   8  13]
- [  0  11   5   1  63   0   3]
- [  6   2   1   0   1  44  10]
- [ 14   3  10   3  10  13  80]]
-Node Classification on random seed  6738 -> 0.627
-Confusion Matrix:
- [[ 81   5   0   8   2  13   5]
- [  7 128   3   2   7   2   2]
- [ 28  18 139  62  22   7  28]
- [  9   5  20  88  14   7  10]
- [  3   8   5   0  63   3   4]
- [  2   1   2   0   0  47   8]
- [ 12   4  11   6   6  12  81]]
-Node Classification on random seed  6739 -> 0.617
-Confusion Matrix:
- [[ 65   1  13   5   3   6   4]
- [  5 126  10   4   2   4   2]
- [ 23  30 135  27  43  18  33]
- [ 16   2  12 106  10  14   6]
- [  0   3   4   3  68   2   2]
- [  3   2   5   1   0  49   8]
- [ 15   1  11   9   8  13  68]]
-Node Classification on random seed  6740 -> 0.669
-Confusion Matrix:
- [[ 78   3   0   4   8   6   9]
- [  5 148   2   1   9   1   3]
- [ 40  19 170  11  15  11  38]
- [ 20   6  12  89   5   7   7]
- [  1   8   4   3  63   1   1]
- [  4   1   5   4   0  44   3]
- [ 12   5   9   8   2  18  77]]
-Node Classification on random seed  6741 -> 0.592
-Confusion Matrix:
- [[ 70   3   3   2   5  14   7]
- [  2 131   9   1  11   0   2]
- [ 31  17 134  54  26  32  24]
- [ 11   2  20 117  11   4   5]
- [  1   2   6   2  56   0   5]
- [  5   2   3   0   0  32   1]
- [  5   5  18  16   5  36  52]]
-Node Classification on random seed  6742 -> 0.641
-Confusion Matrix:
- [[ 74   4   2   5   3  15   5]
- [  3 112  10   3  20   0   2]
- [ 26  15 161  29  19  20  44]
- [ 13   1  20 111   5   7   6]
- [  1   4   5   0  55   0   3]
- [  5   5   5   3   1  44   6]
- [ 10   8   3   4   5  14  84]]
-Node Classification on random seed  6743 -> 0.622
-Confusion Matrix:
- [[ 81   1  10   9   2  12  10]
- [  5 123   6   2   2   4   3]
- [ 22  25 131  48  20  24  43]
- [ 10   1  13 112   0   3  17]
- [  3   7   4   0  51   0   3]
- [  2   0   2   1   3  45   9]
- [ 11   3  13   6   7  12  79]]
-Node Classification on random seed  6744 -> 0.62
-Confusion Matrix:
- [[ 62   9  12   4   3  18   6]
- [  2 117   4   1  10   2   1]
- [ 26  29 141  28  25  18  38]
- [ 20   2  19 102   1   6  11]
- [  3   5   4   6  77   0   2]
- [  4   2   5   0   0  43   3]
- [  8   3  15   7   2  16  78]]
-Node Classification on random seed  6745 -> 0.619
-Confusion Matrix:
- [[ 78   3   4   2   4   7   7]
- [  3 110   7   5  17   3   6]
- [ 32  19 142  30  30  32  19]
- [ 14   6  13 119   5   3   6]
- [  1   8   3   1  55   2   6]
- [  7   1   3   0   1  45   4]
- [ 11   3   9  20   4  20  70]]
-Node Classification on random seed  6746 -> 0.596
-Confusion Matrix:
- [[ 69   2   3  11   0  10  11]
- [  4 125   4   0   6   0   4]
- [ 29  27 137  31  29  15  44]
- [ 21   5  13  93   1  12  14]
- [  0   4   7   6  58   0   3]
- [ 12   1   2   0   3  45   4]
- [ 15   2   7  28   1  13  69]]
-Node Classification on random seed  6747 -> 0.658
-Confusion Matrix:
- [[ 65   5   2   3   4   9  15]
- [  6 144  12   0   2   2   4]
- [ 16  25 183  24  22  15  38]
- [ 12   9  22  87   4   5  13]
- [  2   6   8   0  58   0   4]
- [  5   0   1   1   0  36   9]
- [ 11   1   4   6   7   8  85]]
-Node Classification on random seed  6748 -> 0.617
-Confusion Matrix:
- [[ 71   2   3   5   4  22  13]
- [  1 123  12   5  13   2   4]
- [ 13  33 131  53  20  25  36]
- [  4   2  16 136   1   6  11]
- [  3   3   3   0  46   0   4]
- [  4   2   1   0   1  43  11]
- [  8   7  12   1   5  12  67]]
-Node Classification on random seed  6749 -> 0.595
-Confusion Matrix:
- [[ 52   0   5   6   3  16   5]
- [  8 122   8   3   4   2   9]
- [ 26  18 134  37  27  40  36]
- [  9   2  11 118   2  10  13]
- [  2   8   3   1  49   2   2]
- [  3   5   6   3   0  34   8]
- [ 10   3   3  10   9  27  86]]
-Node Classification on random seed  6750 -> 0.65
-Confusion Matrix:
- [[ 65   0   1   1   3  13  11]
- [  3 129   6   2  11   2   2]
- [ 24  18 138  38  33  16  38]
- [  8   6   7 122   3   5  10]
- [  3   7   2   2  58   1   1]
- [  4   2   1   1   1  58   6]
- [  9   6   4   9  11  19  80]]
-Node Classification on random seed  6751 -> 0.557
-Confusion Matrix:
- [[ 64   2   9   9   6  10  21]
- [  4 123   9   2   4   0   6]
- [ 39  16 102  61  30  17  51]
- [ 16   3  21 103   6   4  14]
- [  0   9   2   1  61   0   1]
- [  4   0   4   4   0  36   3]
- [ 10   8   9   9  13   6  68]]
-Node Classification on random seed  6752 -> 0.603
-Confusion Matrix:
- [[ 76   9   3   6   7   6  11]
- [  0 122   8   1  19   2  10]
- [ 25  26 163  28  28  18  21]
- [ 10   7  23  85   9   9  17]
- [  1   6   6   3  53   0   2]
- [  3   1   3   4   5  33   4]
- [ 16   5  17   3  10   5  71]]
-Node Classification on random seed  6753 -> 0.655
-Confusion Matrix:
- [[ 76   0   1  14   5   7   3]
- [  4 129   3   6   4   3   0]
- [ 19  27 138  18  35  17  42]
- [  8   2  10 141   3   4  12]
- [  0   5   4   0  65   4   2]
- [ 14   2   0   6   0  37   3]
- [  9   3   3  21   6  16  69]]
-Node Classification on random seed  6754 -> 0.649
-Confusion Matrix:
- [[ 93   8   2   8   4   6   6]
- [  4 123   3   0   9   1   8]
- [ 31  21 138  27  22  12  45]
- [ 13  10  20 116   2   4   4]
- [  0   9   4   0  58   1   3]
- [  5   0   1   2   2  44   9]
- [ 10   3   7  12   7   6  77]]
-Node Classification on random seed  6755 -> 0.634
-Confusion Matrix:
- [[ 64   6   6   7   5   9  10]
- [  5 129   5   0   5   3   3]
- [ 30  23 154  19  26  29  32]
- [  5   5  20  98   7   7  11]
- [  0   8   3   5  56   0   2]
- [  3   2   3   6   3  44   4]
- [ 14   5   7   1  11  11  89]]
-Node Classification on random seed  6756 -> 0.631
-Confusion Matrix:
- [[ 70   4   1   5   3  18  17]
- [  2 136   2   3   8   2   1]
- [ 17  18 159  29  22  29  46]
- [ 12   0  19  95   5  10  24]
- [  0   4   5   2  59   0   2]
- [  4   1   0   0   1  34   9]
- [ 15   5   3   6   2  13  78]]
-Node Classification on random seed  6757 -> 0.606
-Confusion Matrix:
- [[ 71   0   9   5   4   7   8]
- [  2 124  10   7   9   4   5]
- [ 46  29 132  24  23  30  37]
- [  6   2  12  89   5   5  17]
- [  3   3   5   1  74   2   1]
- [  4   1   1   1   2  50   6]
- [ 14   1  10   8  10  15  66]]
-Node Classification on random seed  6758 -> 0.629
-Confusion Matrix:
- [[ 74   9   3   3   3   6   8]
- [  2 127   5   2  11   0   5]
- [ 22  12 136  52  40  22  28]
- [ 11   0  18 114   5   4   6]
- [  5   5   4   1  64   0   5]
- [ 13   2   3   4   0  42   0]
- [ 21   2   5   6   3  15  72]]
-Node Classification on random seed  6759 -> 0.635
-Confusion Matrix:
- [[ 73   4   3   0   6  12   2]
- [  2 115   5   2  19   3   7]
- [ 24  40 133  23  36  21  25]
- [ 11   7  15 119   5   2   6]
- [  1   7   2   1  71   0   1]
- [  4   1   3   2   0  49   2]
- [ 10   2  21   9   6  13  75]]
-Node Classification on random seed  6760 -> 0.632
-Confusion Matrix:
- [[ 80   1   6   1   3  13   4]
- [  4 134   6   7   4   2   8]
- [ 19  26 128  35  17  19  26]
- [ 19   1  21 100   4   2  19]
- [  6  12   2   4  54   0   3]
- [  3   3   1   0   1  55   5]
- [ 11   6  14   6  10  14  81]]
-Node Classification on random seed  6761 -> 0.593
-Confusion Matrix:
- [[ 71   2   7   5  11  13   8]
- [  7 131   1  12   7   4   5]
- [ 32  18 121  19  28  36  42]
- [ 19   0  17  94  14   3  19]
- [  0   3   6   1  56   1   4]
- [  5   1   2   2   2  47   1]
- [ 10   1   5   7   8  19  73]]
-Node Classification on random seed  6762 -> 0.609
-Confusion Matrix:
- [[ 72   2   3   5   6  13  19]
- [  4 118   9   3  15   2   5]
- [ 26  16 152  24  18  22  44]
- [  4   5  30  82   5   8   9]
- [  3   8   1   1  50   0   4]
- [  6   3   0   1   0  52   7]
- [ 12   5  10   9  12  12  83]]
-Node Classification on random seed  6763 -> 0.605
-Confusion Matrix:
- [[ 72   7  11   3   5   7   7]
- [  5 128   5   3   6   1   1]
- [ 36  18 163  24  22  30  34]
- [ 29   5  15  78   7   7  16]
- [  0   5   8   1  54   3   1]
- [ 10   0   3   2   0  30   5]
- [ 16   3  14   4   4  12  80]]
-Node Classification on random seed  6764 -> 0.589
-Confusion Matrix:
- [[ 66   9   5  15   4  11  13]
- [  1 110   2   5  13   4   6]
- [ 32  30 151  23  23  23  39]
- [  9   4  28  78   9   5  14]
- [  1   2   3   0  69   0   1]
- [  2   0   3   0   0  50  14]
- [  9   4  10   4  16  15  65]]
-Node Classification on random seed  6765 -> 0.658
-Confusion Matrix:
- [[ 76   0   1   2   3  15   7]
- [  6 144   1   1   7   1   2]
- [ 37  12 151  43  29  18  27]
- [ 13   1  18 106   6   2  14]
- [  3   4   4   3  67   4   2]
- [  3   1   1   0   0  51   3]
- [  9   1   7   8   9  14  63]]
-Node Classification on random seed  6766 -> 0.625
-Confusion Matrix:
- [[ 70   3   0   3   4  15  11]
- [  0 126   9   3   4   2   5]
- [ 18  29 158  25  22  22  45]
- [ 21   4  20  97   4   3  13]
- [  0  11   4   1  65   0   5]
- [  5   4   0   0   5  38   4]
- [  4   5  18   4   6  14  71]]
-Node Classification on random seed  6767 -> 0.643
-Confusion Matrix:
- [[ 80   3  10   6   2  20  12]
- [  5 117   3   2   7   2   0]
- [ 20  29 160  25  20  26  35]
- [  9   5  13 111   2  10   9]
- [  1   6   3   1  66   1   6]
- [  3   2   4   0   0  40   4]
- [ 12   6   5   3   4  21  69]]
-Node Classification on random seed  6768 -> 0.632
-Confusion Matrix:
- [[ 63   0   6   5   2   6  15]
- [  6 126   8   1   7   3   5]
- [ 33  13 159  30  30  23  46]
- [ 12   3   8  89  10   7  17]
- [  0   3   2   2  64   1   1]
- [  3   0   7   2   0  47  10]
- [  9   3   4   3   8  14  84]]
-Node Classification on random seed  6769 -> 0.591
-Confusion Matrix:
- [[ 58   1   9  12   2  14  12]
- [  1 125  14   6   7   3   2]
- [ 21  33 163  35  21  29  29]
- [ 17   4  19  93   8   8  14]
- [  2   5   5   3  48   2   1]
- [  4   0   5   1   1  46   3]
- [  3   2   9  12   5  25  58]]
-Node Classification on random seed  6770 -> 0.619
-Confusion Matrix:
- [[ 72   2   1  10   9  11   3]
- [  1 117  11   5   4   7   7]
- [ 27  21 151  38  23  25  31]
- [  6   5  18 109  13   2  11]
- [  1   9   4   2  62   1   3]
- [  6   1   1   2   3  42   3]
- [ 13   5   7   3   6  20  66]]
-Node Classification on random seed  6771 -> 0.619
-Confusion Matrix:
- [[ 81   3   2   2   2   7  16]
- [  2 117   4   4  17   1   2]
- [ 32  23 136  35  21  28  35]
- [ 14   3  11 104   3   5  15]
- [  0   7   4   0  60   1   1]
- [  8   0   2   2   0  45   9]
- [ 12   1  26   6   7   8  76]]
-Node Classification on random seed  6772 -> 0.623
-Confusion Matrix:
- [[ 90   3   2   2   4   8   9]
- [  0 120   6   5   7   1   6]
- [ 37  10 146  39  34  11  26]
- [  9   6  22  93   6   5  16]
- [  2  10   8   3  55   2   1]
- [  4   3   0   1   5  51   4]
- [  9   6   9  12   5  19  68]]
-Node Classification on random seed  6773 -> 0.611
-Confusion Matrix:
- [[ 81   2   7   4   3  11   5]
- [  3 124   2   8   6   1   4]
- [ 17  18 143  43  42  22  39]
- [ 12   0   8  94  12  10  11]
- [  0   8   1   0  60   1   1]
- [  4   1   4   8   4  42   2]
- [ 15   5  13   5   7  20  67]]
-Node Classification on random seed  6774 -> 0.612
-Confusion Matrix:
- [[ 76   9   5   4   1   5  11]
- [ 13 109   7   0  11   1   6]
- [ 15  29 131  39  41  23  36]
- [  8   3  12  98   7   7  17]
- [  1   3   6   0  68   0   1]
- [  2   4   2   1   0  46   7]
- [  8   6  13   7   2  15  84]]
-Node Classification on random seed  6775 -> 0.618
-Confusion Matrix:
- [[ 77   4   0   4   4  13   7]
- [  5 112  17   5  11   0   3]
- [ 30  17 138  20  43  23  31]
- [ 14   3   9  90   5   9  26]
- [  1   6   6   2  70   0   2]
- [  9   1   1   0   1  48   6]
- [  9   1   9  10   4  11  83]]
-Node Classification on random seed  6776 -> 0.638
-Confusion Matrix:
- [[ 64   2   5   4   6   4  14]
- [  0 130   6   2   8   2  10]
- [ 25  13 144  22  36  25  35]
- [ 10   5  23 114  10   4   9]
- [  4   3   3   0  72   0   2]
- [  0   0   7   2   1  49   5]
- [  4   2  21  12   5  11  65]]
-Node Classification on random seed  6777 -> 0.613
-Confusion Matrix:
- [[ 58   6   6   2   4   8  11]
- [  2 121   4   6  11   1   2]
- [ 38  22 134  38  31  17  37]
- [  5   2  17  99   5   3  21]
- [  3   4   5   2  73   0   4]
- [  3   1   2   5   1  43   6]
- [ 16   4   8   4  11   9  85]]
-Node Classification on random seed  6778 -> 0.598
-Confusion Matrix:
- [[ 57   3  12   8   7  18  15]
- [  5 128  11   1   2   3   2]
- [ 19  43 116  28  22  20  55]
- [ 10   2  18  94  11   5  12]
- [  2   4   4   2  52   1   3]
- [  0   2   1   0   0  63   1]
- [  4  11   9   3   5  18  88]]
-Node Classification on random seed  6779 -> 0.64
-Confusion Matrix:
- [[ 77   6   7  10   3  17   6]
- [  8 124   5   1   7   5   3]
- [ 29  20 135  25  32  26  24]
- [  9   8  11 123   8   8   7]
- [  0   3   6   1  57   1   1]
- [  5   0  13   0   0  48   1]
- [  7   5   5   4   6  17  76]]
-Node Classification on random seed  6780 -> 0.634
-Confusion Matrix:
- [[ 77   1   2   7   6  11  10]
- [  0 130   6   2  10   4   4]
- [ 25  21 162  25  32  12  44]
- [ 29   2  13  93   8   5   9]
- [  0   5   2   3  67   1   3]
- [  7   2   0   4   2  37   7]
- [  9   1   7   7   7  11  68]]
-Node Classification on random seed  6781 -> 0.618
-Confusion Matrix:
- [[ 70   1   4   8   4  14   8]
- [ 10 125   8   1  11   2   5]
- [ 24  18 145  50  18  20  35]
- [  7   0  10  95   2  15  16]
- [  2   8  10   0  56   0   4]
- [  1   1   2   2   0  56   3]
- [  8   2   7   8  14  19  71]]
-Node Classification on random seed  6782 -> 0.605
-Confusion Matrix:
- [[ 69   3   8   4   2  15  17]
- [  8 135   2   4   1   5   4]
- [ 30  26 138  43  20  18  47]
- [ 11   3   8  94  10   4  13]
- [  2  10   3   0  54   0   3]
- [  3   0   1   4   2  38   8]
- [ 12   1  16  13   4   7  77]]
-Node Classification on random seed  6783 -> 0.63
-Confusion Matrix:
- [[ 79   2   5   3   5   6  14]
- [  7 131  10   0   5   4   8]
- [ 24  18 148  30  23  21  20]
- [ 13   5  17 102   3   6  13]
- [  2   4   7   2  51   0   7]
- [  7   0   2   2   6  46   8]
- [  9   4   7  10  11  20  73]]
-Node Classification on random seed  6784 -> 0.567
-Confusion Matrix:
- [[ 61   2   6   4   8  21  12]
- [  2 133   1   3   4   5   3]
- [ 28  37 112  52  13  18  49]
- [ 14   8   8  92   1   7  16]
- [  1  13   2   0  55   0   0]
- [  7   1   2   5   0  40  14]
- [ 18   5  13   6  12  12  74]]
-Node Classification on random seed  6785 -> 0.649
-Confusion Matrix:
- [[ 76   8   4   4   2   5   6]
- [  3 130   4   2   4   1   8]
- [ 30  17 147  46  27  11  40]
- [  6   2  13 117   3   7   9]
- [  4   7   3   5  64   1   4]
- [  7   2   3   1   1  38   1]
- [ 17   1   3  10   5  14  77]]
-Node Classification on random seed  6786 -> 0.631
-Confusion Matrix:
- [[ 74   2   7   2   7  20   6]
- [  3 132   5   0   7   6   0]
- [ 27  24 164  37  10  29  29]
- [  9   5   5 100   9   8  12]
- [  2   4   8   1  56   2   4]
- [ 11   2   3   2   1  38  10]
- [ 12   6   4   6   4  18  67]]
-Node Classification on random seed  6787 -> 0.596
-Confusion Matrix:
- [[ 73   3   4   8   5   5  13]
- [  6 110  23   1  12   2   2]
- [ 39  12 118  34  33  24  33]
- [  9   3  11 117   9  10  17]
- [  1   5   2   3  62   0   1]
- [  3   0   6   3   0  38   5]
- [ 12   2   1  12  13  17  78]]
-Node Classification on random seed  6788 -> 0.626
-Confusion Matrix:
- [[ 69   2   3   5   3   7  14]
- [  9 137   0   2   5   3   3]
- [ 28  14 124  35  58  19  42]
- [  7   2   5 111   6  17  13]
- [  0  10   1   0  58   0   3]
- [  7   1   0   0   1  43   7]
- [ 11   3   4   4   7  13  84]]
-Node Classification on random seed  6789 -> 0.606
-Confusion Matrix:
- [[ 65   7   4   9   5  16   8]
- [  2 128  11   3  12   1   6]
- [ 37  31 118  34  19  29  35]
- [  4   3  16 117   2   9   7]
- [  1   6   4   0  66   2   1]
- [  6   3   3   1   1  47   1]
- [ 17   1  11   9   5  12  65]]
-Node Classification on random seed  6790 -> 0.58
-Confusion Matrix:
- [[ 67   2   6   1   0  13  13]
- [  5  99   6   4   9   1  13]
- [ 23  17 134  51  26  20  39]
- [ 16   4  17  95   8   8  13]
- [  1   7   4   1  55   0   4]
- [  8   4   4   1   5  48   3]
- [ 16   4   8   3   5  27  82]]
-Node Classification on random seed  6791 -> 0.62
-Confusion Matrix:
- [[ 60   2   4   4   3   7  12]
- [  9 126   8   1   6   0   1]
- [ 19  22 153  36  22  34  33]
- [  8   8  22  93   3  18  11]
- [  3   6   5   3  66   0   1]
- [  5   6   3   1   0  47   7]
- [ 11   0  10   2   7  17  75]]
-Node Classification on random seed  6792 -> 0.629
-Confusion Matrix:
- [[ 66   3   8   4   4  11   9]
- [  2 117   8   8  18   1   1]
- [ 20  17 163  25  16  25  33]
- [ 12   1  19 103   2  14  10]
- [  2   4   7   2  67   2   2]
- [  9   2   3   2   0  40   8]
- [ 16   4   7   6   9  15  73]]
-Node Classification on random seed  6793 -> 0.62
-Confusion Matrix:
- [[ 65   2   8   7   3  11   5]
- [  1 134   2   3  11   3   4]
- [ 37  26 132  28  31  26  38]
- [  5   5   8 108   9   4  11]
- [  4   7   4   0  67   0   4]
- [  8   0   6   3   1  42   9]
- [ 10   4  10   4   2  16  72]]
-Node Classification on random seed  6794 -> 0.576
-Confusion Matrix:
- [[ 48   2   5   8   5   8  22]
- [  5 128  10   9  11   3   3]
- [ 21  16 111  71  20  18  28]
- [ 17   3  13 119  10   4   8]
- [  2   5   7   3  57   0   3]
- [  3   1   2   9   1  48   3]
- [  5   2   6   8  15  29  65]]
-Node Classification on random seed  6795 -> 0.591
-Confusion Matrix:
- [[ 74   2   4   4   5  17   7]
- [  3 132   5   7   4   3   1]
- [ 18  25 117  64  22  28  44]
- [ 19   5  15  94   4   6  10]
- [  2  10   5   1  52   1   0]
- [  6   1   5   4   0  48   2]
- [  5   3  11   5   6  20  74]]
-Node Classification on random seed  6796 -> 0.668
-Confusion Matrix:
- [[ 79   1   1  12   3   8   7]
- [  3 128   0   1  12   5   6]
- [ 22  25 158  33  14  18  39]
- [  9   1   7 115  10   5  16]
- [  2  10   2   3  58   0   4]
- [  4   1   3   1   2  50   3]
- [  7   4   8   1   3  16  80]]
-Node Classification on random seed  6797 -> 0.576
-Confusion Matrix:
- [[ 68   2   5   4   2  15   4]
- [  2 131   3   5  13   2   8]
- [ 32  19 113  54  33  31  27]
- [ 20   2  19  77   8   6  16]
- [  2   4   4   2  66   1   4]
- [  8   1   1   1   0  43  15]
- [ 19   3   2   7   5  13  78]]
-Node Classification on random seed  6798 -> 0.626
-Confusion Matrix:
- [[ 68   2   2   4   5  10  15]
- [  3 123   4   4   6   2   2]
- [ 31  18 137  34  24  34  28]
- [  9   4  19 118   7   7  13]
- [  3   9   2   0  52   6   0]
- [  3   2   0   3   0  43  13]
- [  6   2   9   7   6  16  85]]
-Node Classification on random seed  6799 -> 0.618
-Confusion Matrix:
- [[ 82   1   1   5   5   3   9]
- [  2 118   7   6   9   1   2]
- [ 38  23 141  44  29  26  29]
- [ 12   4  12 105   3   4  13]
- [  1   6   5   1  50   0   2]
- [  6   1   4   1   1  45   8]
- [ 16   3  12   2  15  10  77]]
-Node Classification on random seed  6800 -> 0.647
-Confusion Matrix:
- [[ 84   2   3   1   3  15   6]
- [  5 128   3   0  11   3   1]
- [ 13  11 142  32   8  29  61]
- [  9   4   9 113   1   6  18]
- [  3   3   5   1  52   0   1]
- [ 12   0   2   1   0  50   7]
- [ 18   2   8   4   9  23  78]]
-Node Classification on random seed  6801 -> 0.619
-Confusion Matrix:
- [[ 80   0   2   3   2  16  13]
- [  5 121   8   5  18   3   4]
- [ 38   8 134  36  22  18  34]
- [ 14   2  26  94   2   7  15]
- [  3   1   2   2  64   2   1]
- [  4   0   3   1   3  50   9]
- [ 14   4   7   3   5  16  76]]
-Node Classification on random seed  6802 -> 0.611
-Confusion Matrix:
- [[ 59   1   6   8   6  14   5]
- [  3 122   8   1   8   5   2]
- [ 34   7 161  43  18  26  36]
- [ 14   3   9  92   6  12  19]
- [  0   3   5   2  57   3   1]
- [ 15   0   3   1   0  47   2]
- [ 19   0   6  17   5  13  73]]
-Node Classification on random seed  6803 -> 0.608
-Confusion Matrix:
- [[ 72   2   0   9   3   8  13]
- [  9 122  11  10  10   3   1]
- [ 18  10 147  36  26  14  50]
- [ 10   9  25  91   3   8  14]
- [  0   3   2   1  72   0   3]
- [ 10   0   3   3   2  36   5]
- [ 14   3   8  13   5  15  68]]
-Node Classification on random seed  6804 -> 0.629
-Confusion Matrix:
- [[ 78   5   9   1   4   8   8]
- [  7 114  13   1   3   1   7]
- [ 34  16 157  49  27  23  24]
- [  8   3  12 110   5   3  15]
- [  0   6   4   3  60   0   2]
- [  8   0   1   0   1  40   5]
- [ 15   1  13   4  10  12  70]]
-Node Classification on random seed  6805 -> 0.626
-Confusion Matrix:
- [[ 69   2   7   4   2  12  15]
- [  2 122   6   5  17   1   3]
- [  5  27 147  47  31  21  26]
- [  6   8  12 102   7  11  19]
- [  1   4   1   2  56   1   4]
- [  5   2   2   0   0  55   3]
- [  6   7  11   7   6  16  75]]
-Node Classification on random seed  6806 -> 0.609
-Confusion Matrix:
- [[ 54   5   6   3   6  10  10]
- [  4 114   3  13   4   4   2]
- [  9  29 176  50  28  28  30]
- [ 15   1  12  98   1   4  15]
- [  0   8  10   4  62   2   0]
- [  6   0   3   4   2  47   4]
- [ 13   6  22   2   4   9  58]]
-Node Classification on random seed  6807 -> 0.634
-Confusion Matrix:
- [[ 74   3   4  10   3  12  15]
- [  3 134   5   2   1   2   2]
- [ 25  25 123  31  22  19  44]
- [  8   8  19 114   3   2   8]
- [  3   7   1   3  68   0   3]
- [  2   2   2   1   1  40  13]
- [ 11   3  10   7   6  15  81]]
-Node Classification on random seed  6808 -> 0.609
-Confusion Matrix:
- [[ 79   0   2   5   6  14  10]
- [ 11 129   7   1   4   0   5]
- [ 27  39 128  28  20  24  33]
- [ 15   2  18  99  10   5  14]
- [  4  12   1   0  58   0   1]
- [ 10   0   2   1   1  40   1]
- [ 18   1   9   5   6  19  76]]
-Node Classification on random seed  6809 -> 0.576
-Confusion Matrix:
- [[ 60   4  10  12   3   7  12]
- [  2 124   6   0   2   6   5]
- [ 18  17 134  21  24  32  52]
- [ 11   1  26 111   4  14   5]
- [  1   9   7   2  57   0   2]
- [  3   0   5  13   2  38   3]
- [  6   4  13  23   6  31  52]]
-Node Classification on random seed  6810 -> 0.63
-Confusion Matrix:
- [[ 88   0   4   5   3  14   7]
- [  2 129   0   5   4   4   6]
- [ 24  29 140  19  30  15  35]
- [ 17   9  13 103   5  11   6]
- [  1   5   6   1  54   4   0]
- [ 11   1   1   3   0  45   3]
- [ 23   4   9  18   5   8  71]]
-Node Classification on random seed  6811 -> 0.592
-Confusion Matrix:
- [[ 72   3   3   4  10  20   2]
- [  3 117   1   4  10   6   7]
- [ 29   6 139  55  36  30  37]
- [ 22   2  26  74   3   1  11]
- [  2   5   2   0  68   3   4]
- [  2   1   5   0   0  49   2]
- [ 15   4   3   2  10  17  73]]
-Node Classification on random seed  6812 -> 0.61
-Confusion Matrix:
- [[ 70   2   8   3   4  10   9]
- [  6 130   5   6   5   1   5]
- [ 38  32 128  42  22  13  33]
- [ 10   3  20  97   6   4  18]
- [  2   8   2   1  57   0   4]
- [  4   0   2   3   3  40   6]
- [ 15   2   7   7   7  12  88]]
-Node Classification on random seed  6813 -> 0.63
-Confusion Matrix:
- [[ 77   3   8   7   1  16   3]
- [  5 133   6   2   5   1   0]
- [ 26  25 144  21  44  28  27]
- [  9   3  14 107   5   9  11]
- [  1  11   3   2  54   3   2]
- [  4   1   2   5   1  47   1]
- [ 10   2   9  10   7  17  68]]
-Node Classification on random seed  6814 -> 0.601
-Confusion Matrix:
- [[ 62   0   2   3   2  10  21]
- [  5 116   9   9   2   5   2]
- [ 14  13 130  34  49  21  50]
- [ 13   3  20 105   6   9  19]
- [  2   7   6   3  62   1   3]
- [  6   0   2   1   0  52   4]
- [  9   3   4   6   7  14  74]]
-Node Classification on random seed  6815 -> 0.589
-Confusion Matrix:
- [[ 69   1   2   4   4  18   6]
- [  7 119  12   4   1   0   6]
- [ 21  23 128  48  49  18  31]
- [  8   4  16  98   8   4  20]
- [  2   2   2   0  68   1   9]
- [  9   1   3   2   0  41   5]
- [ 16   2   5   4   6  27  66]]
-Node Classification on random seed  6816 -> 0.585
-Confusion Matrix:
- [[ 65   2   2   2   2   6   7]
- [ 13 124   3   4  12   4   3]
- [ 28  25  96  28  61  33  44]
- [ 11   0   8 108   9  10  10]
- [  3   8   6   1  57   2   6]
- [  6   1   0   1   4  50   4]
- [  7   7   4   5   6  17  85]]
-Node Classification on random seed  6817 -> 0.59
-Confusion Matrix:
- [[ 63   2   3  10   9  23   9]
- [  1 137   7   3   6   5   2]
- [ 23  23 131  54  18  21  48]
- [ 10   0  10  98   8  19  14]
- [  4   3   4   0  51   2   7]
- [  1   1   3   1   1  41   5]
- [  6   3  11   6   6  18  69]]
-Node Classification on random seed  6818 -> 0.621
-Confusion Matrix:
- [[ 68   1   7   7   4   8  13]
- [  7 126   2   1   9   2   2]
- [ 16  24 146  24  22  28  51]
- [ 11   3  17  83  18   4  10]
- [  4   8   4   1  62   2   0]
- [  1   2   0   0   3  52  11]
- [ 11   1   9   4   9  18  84]]
-Node Classification on random seed  6819 -> 0.62
-Confusion Matrix:
- [[ 70   3   3  13   3  12   7]
- [ 10 120   9   4   9   5   2]
- [ 33  13 156  22  29  27  42]
- [ 11   3   4 100   6   7   5]
- [  0   5   7   5  57   1   2]
- [  8   2   2   0   2  50   5]
- [ 18   1   3  13  13  11  67]]
-Node Classification on random seed  6820 -> 0.565
-Confusion Matrix:
- [[ 69   5   0   6   5   5  10]
- [  3 114  10   4  20   1   5]
- [ 34  28  87  35  27  16  75]
- [  8   7   6  99   9   4  19]
- [  2   5   3   1  62   0   5]
- [  3   5   3   1   7  42   7]
- [  9   2  13   6   6  15  92]]
-Node Classification on random seed  6821 -> 0.585
-Confusion Matrix:
- [[ 67   1   0   6   0   8   7]
- [  9 109  16   3  12   3   3]
- [ 33  17 128  22  27  38  40]
- [ 12   0  23  92   4   6  19]
- [  4   9   4   2  48   6   4]
- [ 10   0   1   3   0  51   8]
- [ 14   6  12   4   4  15  90]]
-Node Classification on random seed  6822 -> 0.629
-Confusion Matrix:
- [[ 55   2   0  11   3  10  20]
- [  3 144   4   4   1   4   7]
- [ 31  21 139  29  35  46  28]
- [  6   4  15 115   4   2   9]
- [  2   9   3   1  55   1   1]
- [  4   1   0   2   0  45   7]
- [  7   2   6   5   6  15  76]]
-Node Classification on random seed  6823 -> 0.629
-Confusion Matrix:
- [[ 79   2   5   7   3  11   8]
- [  6 129   6   7   7   1   1]
- [ 13  27 141  45  15  35  25]
- [ 13   7  24  98   5   4   6]
- [  2   6   3   3  62   0   2]
- [  8   1   1   3   1  46   3]
- [  8   3   6  14   5  19  74]]
-Node Classification on random seed  6824 -> 0.586
-Confusion Matrix:
- [[ 73   2   6   5   7  12   7]
- [  7 150   4   0   5   2   0]
- [ 27  24  98  54  57  21  39]
- [ 12   5   9 101   7   7  12]
- [  2   1   3   1  67   0   6]
- [  6   0   3   2   3  43   1]
- [ 15   2  10   3  14  11  54]]
-Node Classification on random seed  6825 -> 0.647
-Confusion Matrix:
- [[ 74   2   3   4   3  25   5]
- [  4 118   6   3   6   3   5]
- [ 18  15 180  31  23  25  35]
- [ 19   1  14  87  11   3  15]
- [  0   5   3   3  60   1   1]
- [  3   0   1   4   2  47   2]
- [ 12   3  10   5   1  18  81]]
-Node Classification on random seed  6826 -> 0.612
-Confusion Matrix:
- [[ 83   1   1   3   5  10   1]
- [  5 123   7   2  11   0   6]
- [ 34  36 125  45  32  12  38]
- [ 16  10   7 103   6   5  12]
- [  1   8   1   3  56   2   1]
- [  6   2   2   2   0  47   6]
- [ 15   0  11   7   4  12  75]]
-Node Classification on random seed  6827 -> 0.61
-Confusion Matrix:
- [[ 88   2   3   2   1  11   9]
- [  4 104   4   6  14   7  12]
- [ 23   9 125  43  37  27  44]
- [  6   1  18 106   2  15  12]
- [  4   4   3   2  56   3   3]
- [  1   0   3   0   2  41  11]
- [  7   5   9   4   7  10  90]]
-Node Classification on random seed  6828 -> 0.619
-Confusion Matrix:
- [[ 65   2   7  16   2   7  17]
- [  7 141   4   2   5   0  10]
- [ 27  26 165  36  15  19  33]
- [  6   7  14  93   3   4  13]
- [  3  16   1   2  50   1   3]
- [ 11   1   1   2   0  36   5]
- [  7   6  13   4   6  17  69]]
-Node Classification on random seed  6829 -> 0.606
-Confusion Matrix:
- [[ 62   0   2  15   6  10  15]
- [  1 121   2   5   4   5   8]
- [ 13  41 129  51  14  37  35]
- [  7   3   9 116   5   2  23]
- [  0   7   5   4  62   2   3]
- [  5   3   1   0   5  47   4]
- [  6   5   2  10   5  14  69]]
-Node Classification on random seed  6830 -> 0.581
-Confusion Matrix:
- [[ 59   6   6   4   5  12   9]
- [  5 121   5   2   7   7   6]
- [ 38  39 114  37  21  49  34]
- [ 11  10  11 101   6   6  12]
- [  0   3   1   3  65   1   3]
- [  4   2   2   5   0  44   3]
- [ 10   5   6  11   4   8  77]]
-Node Classification on random seed  6831 -> 0.627
-Confusion Matrix:
- [[ 68   1  12   5  10   3   7]
- [  4 134   2   3  10   2   2]
- [ 46  22 152  23  13   8  44]
- [ 14   4  13 107   6   4  14]
- [  1   4   7   3  60   0   5]
- [  1   3   2   5   0  37   5]
- [ 10   4  20   6  17   8  69]]
-Node Classification on random seed  6832 -> 0.606
-Confusion Matrix:
- [[ 78   2   2  11   3   5  11]
- [ 13 123  16   0  12   1   5]
- [ 19  24 129  38  27   7  43]
- [  4   8  22 111   5   5  14]
- [  3   4   4   0  53   0   1]
- [ 10   3   2   0   1  46   6]
- [ 13   7  18   3   7  15  66]]
-Node Classification on random seed  6833 -> 0.634
-Confusion Matrix:
- [[ 77   3   2   5   5  23   7]
- [  6 120   2   2  12   2   6]
- [ 14  22 150  32  17  35  30]
- [  8   8   7 105   5   7  14]
- [  0  12   8   0  59   1   2]
- [  4   2   3   3   3  50   8]
- [ 10   1   8   4   8  15  73]]
-Node Classification on random seed  6834 -> 0.613
-Confusion Matrix:
- [[ 94   1   2   2   2  10  12]
- [  5 125   5   2   4   5   2]
- [ 24  29 130  35  19  30  41]
- [ 18   1  18  93   7   6  10]
- [  1   7   7   0  64   0   8]
- [  8   3   7   2   0  39   2]
- [ 12   5   2   3   5  25  68]]
-Node Classification on random seed  6835 -> 0.595
-Confusion Matrix:
- [[ 80   1  10   3   7  10   7]
- [  7 132   7   2  12   2   7]
- [ 34  20 128  28  31  32  31]
- [ 11   1  18  99   6   8   9]
- [  2   8   5   4  50   2   1]
- [  9   0   5   4   1  41   3]
- [ 11   4   8  15   5  14  65]]
-Node Classification on random seed  6836 -> 0.619
-Confusion Matrix:
- [[ 80   4   5   2   3  13  12]
- [  1 109   8   6   2   0  14]
- [ 30  28 139  40  15  18  34]
- [  9   6  11 111   8   6   8]
- [  3   8   4   0  69   1   4]
- [ 13   0   3   0   1  36   2]
- [ 18   3  15   8   5  10  75]]
-Node Classification on random seed  6837 -> 0.624
-Confusion Matrix:
- [[ 66   1   6   4   5  16  10]
- [  6 123   7   2   9  11   5]
- [ 24  26 153  22  23  34  30]
- [ 14   4  10  98   7   9  12]
- [  2   5   3   1  61   1   5]
- [  6   0   1   1   2  44   3]
- [  8   2  21   3   3  12  79]]
-Node Classification on random seed  6838 -> 0.612
-Confusion Matrix:
- [[ 61   2  11   4   3  14   9]
- [  6 120   4   6  11   3   2]
- [ 32  10 157  35  40  16  38]
- [  6   1  15  95  13  15  14]
- [  2   6   2   1  61   1   1]
- [  4   0   1   1   1  47   9]
- [  5   3   5  11  13  12  71]]
-Node Classification on random seed  6839 -> 0.628
-Confusion Matrix:
- [[ 84   1   1   2   4   9  19]
- [  0 113   5   3  20   4   3]
- [ 14  27 131  20  39  30  37]
- [ 10   4  15 118   6   4  12]
- [  2   5   1   1  60   1   5]
- [  3   3   4   1   3  39  12]
- [  7   6   7   6   6  10  83]]
-Node Classification on random seed  6840 -> 0.582
-Confusion Matrix:
- [[ 86   1   2   6   5  14   1]
- [  4 137   3   3  12   3   3]
- [ 11  32 128  39  36  22  35]
- [ 19   3  21  80  18  11  19]
- [  2   3   1   0  55   2   1]
- [  9   1   3   2   0  38   4]
- [ 14   7   8   7  11  20  58]]
-Node Classification on random seed  6841 -> 0.618
-Confusion Matrix:
- [[ 63   5   6   3   1   9  14]
- [  4 142   6   2  10   3   1]
- [ 29  27 115  25  27  24  37]
- [ 15   4  13 102   7   4  16]
- [  2   2   5   3  65   4   1]
- [  6   1   4   1   0  52   6]
- [ 10   3  16   5   6  15  79]]
-Node Classification on random seed  6842 -> 0.63
-Confusion Matrix:
- [[ 78   2   5   3   6   8   8]
- [  3 125   9   2  13   1   4]
- [ 38  23 141  38  20  24  27]
- [  9   5  12  93   9   5  14]
- [  1   4   3   1  74   0   2]
- [  6   0   1   1   1  40   4]
- [  9   1   9   7   8  24  79]]
-Node Classification on random seed  6843 -> 0.65
-Confusion Matrix:
- [[ 74   5  12   4   1   4   7]
- [ 13 129   0   1   2   1   5]
- [ 26  17 158  25  35  29  22]
- [  7   5  16 102   4   3  15]
- [  1   8   0   0  63   1   3]
- [  7   1   4   2   1  42   4]
- [ 13   4  14  13   7   8  82]]
-Node Classification on random seed  6844 -> 0.601
-Confusion Matrix:
- [[ 71   6   8   7   3   5   9]
- [  4 126   6   4   3   3   3]
- [ 31  30 135  29  30  21  27]
- [ 11   6  29  95   4   5  17]
- [  0   7   8   5  52   2   2]
- [  2   1   2   1   0  49   7]
- [ 13   6   5   8   7  22  73]]
-Node Classification on random seed  6845 -> 0.63
-Confusion Matrix:
- [[ 67   3   1   4   1  10  18]
- [  1 148   6   1   6   5   5]
- [ 22  26 126  24  37  32  44]
- [  6   4  20  99   0   4   9]
- [  1   6   5   2  59   0   1]
- [ 12   2   2   0   0  54   3]
- [  9   8   6   3   5  16  77]]
-Node Classification on random seed  6846 -> 0.597
-Confusion Matrix:
- [[ 75   9   6   5   2  12   6]
- [ 15 136   5   1  11   1   4]
- [ 31  47 124  23  26  17  36]
- [ 16   4  16  96   1   5  13]
- [  1   5   3   0  58   1   7]
- [ 14   2   9   0   1  33   3]
- [  9   3  13   4   5  11  75]]
-Node Classification on random seed  6847 -> 0.604
-Confusion Matrix:
- [[ 74   1   5   4   3  12   7]
- [  0 105   8   1  12   5  12]
- [ 17  31 150  35  27  23  27]
- [ 17   3  17  98  10  10  10]
- [  2   3   1   2  65   3   7]
- [  1   0   4   3   0  44  11]
- [ 12   2  10   7   6  25  68]]
-Node Classification on random seed  6848 -> 0.602
-Confusion Matrix:
- [[ 66   2   2  12   2   9  12]
- [  6 122   6   5   3   5   2]
- [ 33  18 130  39  53  22  24]
- [  6   7  10 103   8   2  14]
- [  1   9   2   0  61   2   1]
- [  3   3   3   3   0  49   3]
- [ 16   7   4  13   8  18  71]]
-Node Classification on random seed  6849 -> 0.586
-Confusion Matrix:
- [[ 70   2   0   7   3  15  14]
- [ 16 109   6   1  14   1  15]
- [ 19  29 132  23  32  24  40]
- [ 13   2  19  99   3   6  18]
- [  2   0   3   2  65   0   2]
- [  4   1   2   0   1  49   4]
- [ 14   7   6   6  29   9  62]]
-Node Classification on random seed  6850 -> 0.657
-Confusion Matrix:
- [[ 69   2   4   9   4   7   6]
- [  6 123   1   4   4   2   0]
- [ 15  17 168  33  31  18  29]
- [  3   4  22 109   6   3  17]
- [  0   8   2   0  76   2   3]
- [  7   1   2   2   2  48  10]
- [ 13   4  11   8   6  15  64]]
-Node Classification on random seed  6851 -> 0.657
-Confusion Matrix:
- [[ 76   3  11   4   0   7   8]
- [  8 145   7   2   1   2   2]
- [ 26  11 139  29  46  14  21]
- [ 13   5   9 105  17   3  14]
- [  5   5   2   1  53   0   3]
- [  2   4   2   1   1  40   2]
- [  6   2  15  14   5  10  99]]
-Node Classification on random seed  6852 -> 0.632
-Confusion Matrix:
- [[ 82   1   2   4   3  13   4]
- [  5 148   4   2   9   4   9]
- [ 19  15 146  34  23  15  39]
- [  8   1  25  91   6  13   5]
- [  0   6   5   1  66   1   3]
- [ 14   1   3   0   0  48   3]
- [ 15   1   4  16  10  22  51]]
-Node Classification on random seed  6853 -> 0.597
-Confusion Matrix:
- [[ 65   1   9   3   6  20  13]
- [  7 107   9   4  10   0   3]
- [ 20  25 140  52  25  28  34]
- [  5   2  16 107   0   7  14]
- [  2   0   8   3  53   2   5]
- [  5   1   2   4   1  41   8]
- [  5   3  17   7   4  13  84]]
-Node Classification on random seed  6854 -> 0.578
-Confusion Matrix:
- [[ 62   0   7   5   6  18  15]
- [  8 120   5  11   2   2   0]
- [ 25  22 138  36  24  29  35]
- [ 17   4  22  84  15   5   9]
- [  1   8   2   4  53   3   1]
- [  8   0   2   3   1  42   7]
- [  7   8  13  12   7  13  79]]
-Node Classification on random seed  6855 -> 0.615
-Confusion Matrix:
- [[ 71   2   3   5   7   2  18]
- [  1 111   5   1  16   0   3]
- [ 26  36 140  34  16  13  37]
- [ 16   9  19 100   2   5   7]
- [  2   5   3   0  74   1   2]
- [ 11   4   3   6   0  44   5]
- [ 14   1  19  11  10   5  75]]
-Node Classification on random seed  6856 -> 0.634
-Confusion Matrix:
- [[ 64   4   6   5   1  10  14]
- [  3 139   5   3   1   0   1]
- [ 23  23 130  30  35  12  43]
- [ 17   5  10  95   6   7  17]
- [  3   2   3   1  61   2   3]
- [  7   1   3   1   0  52   8]
- [ 10   6   9   4   8  14  93]]
-Node Classification on random seed  6857 -> 0.581
-Confusion Matrix:
- [[ 68   4  10   5   5  10   9]
- [  5 122   9   3   9   0   4]
- [ 36  31 126  47  24  19  29]
- [ 13   5   8  89   8  10   7]
- [  3   6   5   1  57   2   0]
- [  8   2   1   3   2  46   7]
- [ 14  11   8   7  21   8  73]]
-Node Classification on random seed  6858 -> 0.627
-Confusion Matrix:
- [[ 77   2   4   3   6  13  10]
- [  7 133   2   1   6   6   2]
- [ 38  31 128  36  18  20  40]
- [  8   3  18 104   8   4   5]
- [  1   9   0   2  69   1   1]
- [  7   3   2   1   1  45   6]
- [ 13   2   9   7   1  16  71]]
-Node Classification on random seed  6859 -> 0.66
-Confusion Matrix:
- [[ 83   4   2   2   2   8   8]
- [  7 130   8   0  14   3   1]
- [ 23  15 178  35  19  17  23]
- [  4   7  15  96  11   8  11]
- [  1   8   6   0  57   0   3]
- [ 11   3   1   1   0  41   4]
- [ 20   6   6   7   6  10  75]]
-Node Classification on random seed  6860 -> 0.639
-Confusion Matrix:
- [[ 92   5   6   3   0  12   7]
- [  5 143   4   1   3   2   4]
- [ 25  23 138  37  33  20  25]
- [ 13   4  13  92   7   3  14]
- [  3  10   2   7  58   1   4]
- [  4   1   2   2   0  49   5]
- [ 11   4   9   5   3  19  67]]
-Node Classification on random seed  6861 -> 0.584
-Confusion Matrix:
- [[ 69   4   5   6   4  11  18]
- [  3 129   4   0   3   2   4]
- [ 37  22 113  52  29  20  36]
- [ 14   3  16  96   7   2  16]
- [  1   6   6   0  51   1   3]
- [ 10   2   3   0   0  51   1]
- [ 14   5   8  14   8  16  75]]
-Node Classification on random seed  6862 -> 0.616
-Confusion Matrix:
- [[ 66  10  12   2   3  13   4]
- [  5 123   8   1   4   5   7]
- [ 27  21 151  35  16  26  35]
- [ 14   3  18  86  10   7  13]
- [  0   3   4   1  66   0   3]
- [  4   4   1   6   1  47   3]
- [ 10   1   6  12   4  22  77]]
-Node Classification on random seed  6863 -> 0.643
-Confusion Matrix:
- [[ 80   1   2   2   7  13   4]
- [  5 125   3   4   6   1   2]
- [ 37  19 137  42  24  20  30]
- [ 10   3  17 118   6   3  17]
- [  1   4   3   0  59   1   1]
- [  5   3   4   5   1  39   6]
- [ 11   5   5   6   4  14  85]]
-Node Classification on random seed  6864 -> 0.623
-Confusion Matrix:
- [[ 80   8   2   6   4   6  10]
- [  3 134   3   0  11   1   3]
- [ 24  21 128  33  45   6  33]
- [  9   3  16 113   5   2  10]
- [  1   7   2   4  59   2   4]
- [  5   0   3   2   0  54   8]
- [ 13   5  13  17  17  10  55]]
-Node Classification on random seed  6865 -> 0.623
-Confusion Matrix:
- [[ 51   1  10   6   4  21  11]
- [  4 135   1   0   4   3   9]
- [ 29  22 155  15  25  14  49]
- [  8   4  10 121  10  10  12]
- [  1   8   3   3  48   4   3]
- [ 13   1   2   0   1  48   0]
- [ 16   3   5   9   4  19  65]]
-Node Classification on random seed  6866 -> 0.584
-Confusion Matrix:
- [[ 71   1   1  12   5  11  10]
- [  2 129   1   3   3  11   4]
- [ 34  17  97  58  31  28  53]
- [ 12   5  13 111   1   5  13]
- [  3   4   1   7  59   1   2]
- [  4   0   1   6   0  48   7]
- [  9   2   9   3  12  11  69]]
-Node Classification on random seed  6867 -> 0.645
-Confusion Matrix:
- [[ 71   3   3   4   5   9   1]
- [  0 149  10   2   6   3   0]
- [ 27  28 156  11  20  40  30]
- [  7   2  22  92   2   7  22]
- [  2  20   4   0  62   2   1]
- [  2   3   3   0   0  46   1]
- [ 13   0   6   8   6  20  69]]
-Node Classification on random seed  6868 -> 0.615
-Confusion Matrix:
- [[ 60   4   3  10   4  14  12]
- [  4 112   3   5  13   3   8]
- [ 22  12 151  33  25  42  36]
- [ 11   6  18  99   4   7  10]
- [  1   4   4   2  60   2   7]
- [  1   2   4   0   0  46   3]
- [ 13   1   7   3  12  10  87]]
-Node Classification on random seed  6869 -> 0.585
-Confusion Matrix:
- [[ 63   0   2   2   7  10   6]
- [ 15 106   8   1   6   4   4]
- [ 46  18 146  53  21  27  26]
- [ 12   4  16  87  11   6  16]
- [  1   4   4   2  64   5   0]
- [  7   4   3   1   1  36   8]
- [ 21   0   7   6   7  13  83]]
-Node Classification on random seed  6870 -> 0.601
-Confusion Matrix:
- [[ 79   2  15   3   4   5   9]
- [  7 123   3   3   5   2  10]
- [ 21  27 125  32  37  41  30]
- [ 12   7   9 105   9   2   8]
- [  0   4   0   2  67   0   3]
- [ 16   3   1   0   1  34   6]
- [ 17   3   9  13   4  14  68]]
-Node Classification on random seed  6871 -> 0.577
-Confusion Matrix:
- [[ 68   7   4   3   5  12  10]
- [ 13 124   3   0  11   6   1]
- [ 24  21 131  36  37  23  48]
- [ 10   6  18  94  12   7  16]
- [  0   2   2   0  64   0   1]
- [ 15   2   0   3   0  34   5]
- [ 21   1   6   9   9  14  62]]
-Node Classification on random seed  6872 -> 0.663
-Confusion Matrix:
- [[ 68   3   5   2   2   6  20]
- [  0 123   2   8   7   1   7]
- [ 16  11 185  31  25  25  37]
- [  6   3  26  93   2   1  14]
- [  0  11   1   2  58   0   4]
- [  5   2   0   4   1  55   1]
- [ 11   2  10   2  10  11  81]]
-Node Classification on random seed  6873 -> 0.627
-Confusion Matrix:
- [[ 71  10   2   5   2  15   8]
- [  7 127   8   5   6   4   1]
- [ 30  25 138  38  18  23  34]
- [ 14   2  18 108   9   4   7]
- [  2   9   6   2  53   1   0]
- [  4   0   3   1   0  48   5]
- [ 13   1  11  14   3   3  82]]
-Node Classification on random seed  6874 -> 0.628
-Confusion Matrix:
- [[ 75   2   9   3   1  17   4]
- [  6 128   6   2  12   2   2]
- [ 17  24 145  37  31  15  37]
- [ 16   1  24  89   6   3  10]
- [  2   1   4   4  59   1   1]
- [  6   2   1   2   2  58   3]
- [  7   3   5  11   8  22  74]]
-Node Classification on random seed  6875 -> 0.624
-Confusion Matrix:
- [[ 75   4   4   6   3  11  15]
- [  5 143   5   1   3   4   4]
- [ 12  32 123  52  15  25  34]
- [  9   7  20  99   1   6  14]
- [  2  10   3   2  61   1   4]
- [  3   1   2   3   0  50   6]
- [ 14   5  10   3   4  11  73]]
-Node Classification on random seed  6876 -> 0.618
-Confusion Matrix:
- [[ 69   0   6   5   3  22   8]
- [  5 134   6   5   7   3   3]
- [ 37  19 147  28  33  20  34]
- [ 18   6  10  93  13   4  10]
- [  2   6   0   0  52   0   1]
- [  3   1  13   4   0  32   2]
- [  6   6   8   4   6  15  91]]
-Node Classification on random seed  6877 -> 0.645
-Confusion Matrix:
- [[ 71   2   7   6   1   6  14]
- [  6 132   2   5   4   0   6]
- [ 19  28 158  41  18  23  27]
- [ 23   4  19  85   5   5   7]
- [  0   6   1   1  65   1   5]
- [  4   2   1   3   0  54   2]
- [  9   5  11   8   9   9  80]]
-Node Classification on random seed  6878 -> 0.579
-Confusion Matrix:
- [[ 61   5   3   9   4   6   6]
- [  7 121  10   4  11   1   1]
- [ 26  14 126  51  52  33  28]
- [ 13   4  12 103   1   5  20]
- [  2   1   0   2  58   1   0]
- [  3   3   1   3   0  45   5]
- [  8   4   7  19  19  17  65]]
-Node Classification on random seed  6879 -> 0.63
-Confusion Matrix:
- [[ 70   2   1   3   3  14  11]
- [  3 127   3   4  13   2   1]
- [ 38  24 151  38  17  26  33]
- [ 11   3   6 104  13   6  10]
- [  3   4   4   1  60   1   2]
- [  3   0   4   2   1  43  12]
- [ 14   3   7   4   4  16  75]]
-Node Classification on random seed  6880 -> 0.609
-Confusion Matrix:
- [[ 72   2   2   8   3   7  16]
- [  1 132   2   1   9   1   2]
- [ 45  36 118  39  17  31  24]
- [ 15   4  17 106   7   4   9]
- [  1  12   1   1  59   2   1]
- [  7   1   4   4   2  40   7]
- [  9   5  10   6   5  11  82]]
-Node Classification on random seed  6881 -> 0.6
-Confusion Matrix:
- [[ 75   6   4   6   8   6   6]
- [  2 142   5   1   3   7  11]
- [ 23  38 111  32  26  16  37]
- [ 20  11   8  94   6   5  13]
- [  1   8   7   2  64   1   1]
- [  7   3   2   3   0  44   7]
- [ 13   8  10  11   5  11  70]]
-Node Classification on random seed  6882 -> 0.597
-Confusion Matrix:
- [[ 44   2   0  15   4  20  11]
- [  2 132   3   4   8   2   7]
- [ 17  13 153  43  25  21  41]
- [ 15   8  19 101   9   0   8]
- [  2   3   9   0  60   1   1]
- [  8   3   1   5   2  46   4]
- [ 14   9  11  15   4  14  61]]
-Node Classification on random seed  6883 -> 0.584
-Confusion Matrix:
- [[ 49   8   2  10   5  15  22]
- [  6 120   6   1   4   1   1]
- [ 28  22 115  61  39  13  32]
- [  9  11  20 109   3   2  16]
- [  2   6   5   1  73   0   1]
- [  7   1   2   0   1  36   9]
- [  9   2   6   9   7  11  82]]
-Node Classification on random seed  6884 -> 0.601
-Confusion Matrix:
- [[ 64   3  12   8   3  18   4]
- [  4 129   6   1   6   3   4]
- [ 19  19 135  58  33  27  29]
- [ 14   1   9  96   6   4  14]
- [  5   4   7   2  56   0   2]
- [  2   0   3   1   0  50  10]
- [ 13   0   9  16   4  16  71]]
-Node Classification on random seed  6885 -> 0.604
-Confusion Matrix:
- [[ 68   2   2   6   1   6  27]
- [  7 117   2   0  12   3   5]
- [ 53   7 129  27  16  46  31]
- [  9   5  10  96   2  14  22]
- [  2   5   5   0  57   2   1]
- [  1   0   2   1   2  54   6]
- [ 10   4  18   3   7  12  83]]
-Node Classification on random seed  6886 -> 0.61
-Confusion Matrix:
- [[ 61   2   9   9   2   8  10]
- [  1 130   3   4   9   7   5]
- [ 17  22 153  31  25  29  32]
- [ 14   5  13  92  12   5  18]
- [  0   6   4   1  53   4   2]
- [  5   1   4   3   2  39   6]
- [ 11   4  13   7   5  20  82]]
-Node Classification on random seed  6887 -> 0.592
-Confusion Matrix:
- [[ 62   3   9  10   6  16   8]
- [  4 130  12   4   5   5   1]
- [ 21  20 143  43  23  20  43]
- [ 22   2  13  95   6  15   5]
- [  2   8   6   1  54   1   2]
- [  2   2   4   5   5  41   3]
- [  5   4  10   4   9  19  67]]
-Node Classification on random seed  6888 -> 0.64
-Confusion Matrix:
- [[ 78   3   4   4   3  10  12]
- [  6 116   9  11   4   2   3]
- [ 26  24 152  34  31   5  42]
- [  2   3  22 115   8   1   9]
- [  1   5   7   1  60   1   4]
- [  3   2   3   0   1  43   4]
- [ 11   3  13   9   6   8  76]]
-Node Classification on random seed  6889 -> 0.634
-Confusion Matrix:
- [[ 81   3   1   0   2   7  16]
- [  3 109   5   4   2   0  13]
- [ 19  30 140  24  26  19  43]
- [ 16   7  10 112   2   7  16]
- [  2  10   7   2  58   3   5]
- [  1   1   3   1   0  35  16]
- [ 14   6   6   6   4   4  99]]
-Node Classification on random seed  6890 -> 0.595
-Confusion Matrix:
- [[ 77   2   5   6   2   9  16]
- [ 10 126  12   2  12   2   2]
- [ 34  19 154  22  37  14  37]
- [ 25   6  11  79   5  11  13]
- [  2   6   1   0  62   0   7]
- [ 10   1   3   1   4  27   6]
- [ 19   5   6   5   5  10  70]]
-Node Classification on random seed  6891 -> 0.612
-Confusion Matrix:
- [[ 70   6   7   3   4   5  15]
- [  8 135   1   5   1   0  12]
- [ 20  27 139  60  19  10  41]
- [ 13   5  21 104   5   6   9]
- [  1   6   8   0  46   0   3]
- [  5   2   1   4   0  40   8]
- [ 12   6   7   1   5  16  78]]
-Node Classification on random seed  6892 -> 0.631
-Confusion Matrix:
- [[ 88   3   2   8   3   3  13]
- [  4 133  13   2   6   0   6]
- [ 31  33 112  30  42  19  22]
- [ 16   8   8 116   2   5  14]
- [  0   5   3   3  51   0   0]
- [  8   0   3   0   0  42   9]
- [ 10   2  12   7   5   9  89]]
-Node Classification on random seed  6893 -> 0.628
-Confusion Matrix:
- [[ 67  12   8   8   1  11   4]
- [ 10 128   4   1  10   2   1]
- [ 29  20 165  26  15  16  45]
- [ 17   4  12  95   7   7  16]
- [  3   2   5   1  67   2   3]
- [  5   2   1   3   3  47   7]
- [ 19   2   9   9   2   8  59]]
-Node Classification on random seed  6894 -> 0.592
-Confusion Matrix:
- [[ 69   4   5   9   3   9  17]
- [  7 115   7   4   7   1   5]
- [ 22  19 152  40  23  15  46]
- [ 12   4  30  86  13   7   7]
- [  0  12   3   0  67   0   6]
- [  7   0   7   0   0  39   4]
- [ 16   3  11  13   2   8  64]]
-Node Classification on random seed  6895 -> 0.641
-Confusion Matrix:
- [[ 76   3   2   2   2   8  10]
- [  4 115   2   5   5   0   7]
- [ 15  40 157  38  28  11  43]
- [  7   6  12 101   7   1  20]
- [  3   6   4   3  68   0   2]
- [  7   0   3   1   0  48   6]
- [  9   2   6   5   7  17  76]]
-Node Classification on random seed  6896 -> 0.633
-Confusion Matrix:
- [[ 80   1   4   4   1   6   3]
- [  2 141   6   4   4   2   5]
- [ 37  12 155  28  25  18  47]
- [ 12   2  28  84   5   6  22]
- [  2   8   6   6  52   2   3]
- [  7   4   2   1   0  44   4]
- [ 16   5   7   2   1   7  77]]
-Node Classification on random seed  6897 -> 0.624
-Confusion Matrix:
- [[ 59   7   2   1   3  13  20]
- [  5 122   9   4  17   4   3]
- [ 20  13 148  26  24  34  35]
- [ 15   3  14 101   1   9  11]
- [  2   6   3   4  56   2   2]
- [  3   0   2   2   0  58   4]
- [  2   3   9   7   2  30  80]]
-Node Classification on random seed  6898 -> 0.632
-Confusion Matrix:
- [[ 67   2   6   3   1   8  12]
- [  4 120  13   2   9   3   6]
- [ 21   7 129  38  30  29  44]
- [  8   1  17 118   7   3   8]
- [  2   2   7   1  69   0   6]
- [  5   2   1   0   1  53   1]
- [ 17   3   8   8   5  17  76]]
-Node Classification on random seed  6899 -> 0.597
-Confusion Matrix:
- [[ 64   2   4   5   1  20  10]
- [ 11 141   3   1   7   3   3]
- [ 30  28 125  25  37  28  25]
- [ 11   5  20 102   8  10   7]
- [  3   9   3   2  66   1   1]
- [  8   1   3   6   2  35   2]
- [ 13   6   8   4   6  21  64]]
-Node Classification on random seed  6900 -> 0.608
-Confusion Matrix:
- [[ 63   1   9   6   8  11   9]
- [  3 125  10   3  27   1   2]
- [ 27  23 121  19  38  24  38]
- [ 16   0  12 118   3   5  15]
- [  2   6   1   4  49   3   6]
- [  4   1   2   2   0  36   5]
- [  9   2   8  11   8   8  96]]
-Node Classification on random seed  6901 -> 0.632
-Confusion Matrix:
- [[ 88   3   3   5   3   8  10]
- [ 10 122   5   5   7   6   3]
- [ 13  27 144  31  27  36  38]
- [ 10   4  19  90   2   6  10]
- [  1   2   4   2  62   1   2]
- [  4   1   0   3   0  44   6]
- [ 10   5  15   6   7   8  82]]
-Node Classification on random seed  6902 -> 0.618
-Confusion Matrix:
- [[ 82   1   6  10   2  16   3]
- [  2 135   3   9   7   1   7]
- [ 20  16 122  38  18  34  49]
- [ 10   2  13  99   5   5  15]
- [  1   5   3   2  62   1   3]
- [  3   1   3   0   1  45   8]
- [  5   3  11  11   7  22  73]]
-Node Classification on random seed  6903 -> 0.621
-Confusion Matrix:
- [[ 82   1   3   7   5  13   6]
- [  8 129   4   1   3   5   6]
- [ 24  12 148  44  25  18  22]
- [  6   9  26 102  17   7  11]
- [  3   7   7   1  50   3   3]
- [  4   4   1   0   0  42   6]
- [  9   3  13   6  10  16  68]]
-Node Classification on random seed  6904 -> 0.578
-Confusion Matrix:
- [[ 56   1   7  10   4  11   4]
- [  7 121   3   0  19   5  10]
- [ 36  21 123  43  23  29  39]
- [ 21   1  11  97   2   7  16]
- [  1   7   2   2  65   0   2]
- [  3   3   4   1   3  45   1]
- [ 14   3  10   6   3  27  71]]
-Node Classification on random seed  6905 -> 0.574
-Confusion Matrix:
- [[ 61   2  13   7   6  11  17]
- [  7 122   3   5   8   3  10]
- [ 31  20 130  35  15  36  48]
- [  9   3  14  99   1   4  27]
- [  0   6   4   4  55   0   0]
- [  7   1   1   3   0  31   5]
- [ 14   4   6   7  10  19  76]]
-Node Classification on random seed  6906 -> 0.594
-Confusion Matrix:
- [[ 68   1   2   7   6  10  12]
- [ 17 123   4   3   1   8   6]
- [ 24  22 149  49  23  27  22]
- [  8   0  15  97   3  15  22]
- [  0   2   4   0  50   3   3]
- [  5   2   0   3   1  46   2]
- [  8   4  15  12  10  25  61]]
-Node Classification on random seed  6907 -> 0.632
-Confusion Matrix:
- [[ 69   0   2   2   3  13   9]
- [  6 122   4   5   3   4   1]
- [ 25  29 139  34  26  20  45]
- [ 12   7  13 110   9   6  12]
- [  1   8   1   1  66   1   3]
- [  1   2   5   0   2  52   4]
- [ 12   3   8   5   7  14  74]]
-Node Classification on random seed  6908 -> 0.596
-Confusion Matrix:
- [[ 84   2   0   2   2  16   3]
- [  4 125   2   1   1   9   2]
- [ 53  17 108  34  24  30  46]
- [ 14   7   8 111   7  14   5]
- [  0  10   5   4  56   1   2]
- [  5   0   1   1   1  41   7]
- [  3   7  12   9   7  26  71]]
-Node Classification on random seed  6909 -> 0.643
-Confusion Matrix:
- [[ 75   3   3   4   3   9   9]
- [ 10 123   6   3  11   3   3]
- [ 26  25 163  19  15  40  34]
- [  7   5  13  93   2  17   6]
- [  1   6   6   1  60   1   1]
- [  3   0   2   1   0  61   6]
- [ 12   5   9   5   8  14  68]]
-Node Classification on random seed  6910 -> 0.592
-Confusion Matrix:
- [[ 75   5   7   2   3   6   8]
- [  6 123   4   3   9   1   6]
- [ 20  21 147  46  16  25  53]
- [ 31   4  18  72  11   8  18]
- [  0   6   3   0  57   0   3]
- [  3   0   4   1   1  49   4]
- [ 13   3  16   8   2  10  69]]
-Node Classification on random seed  6911 -> 0.585
-Confusion Matrix:
- [[ 59   0   6   7   4  16  11]
- [  2 122   4   4  11   6   5]
- [ 32  13 132  27  26  24  44]
- [ 16   2  12 103   6   6  18]
- [  2   6   7   1  49   4  10]
- [  3   0   1   1   0  54   6]
- [ 18   4  10   6  16  18  66]]
-Node Classification on random seed  6912 -> 0.631
-Confusion Matrix:
- [[ 65   0   3   5   2  10  14]
- [  6 123  17   1   9   1   2]
- [ 20  18 128  67  45  21  28]
- [  4   2   9 118   6  10  16]
- [  1   5   0   2  70   2   3]
- [  4   0   1   1   0  46   5]
- [  4   0   4   8   4   9  81]]
-Node Classification on random seed  6913 -> 0.612
-Confusion Matrix:
- [[ 80   3   2   6   2  18   1]
- [  1 107   5   3  20   3   2]
- [ 23  19 155  43  31  13  29]
- [ 12   3  11  96  12  12   8]
- [  3   5   8   2  61   1   1]
- [  7   1   3   5   0  49   8]
- [ 22   7  13   6   8   6  64]]
-Node Classification on random seed  6914 -> 0.634
-Confusion Matrix:
- [[ 92   1   4   2   7   5   4]
- [  6 123   8   1   6   1   7]
- [ 27  24 155  29  23  14  38]
- [ 12   3  11 114   2   3  21]
- [  2   7   7   1  58   0   1]
- [  7   2   1   4   1  43   4]
- [ 21   4  14   2  12  17  49]]
-Node Classification on random seed  6915 -> 0.625
-Confusion Matrix:
- [[ 60   4   6   5   7  18  12]
- [  2 140   5   6   5   5   0]
- [ 23  29 130  34  19  17  23]
- [ 14   9   8 101   3   6  31]
- [  4   7   2   3  67   2   5]
- [  2   0   2   2   2  47   3]
- [  6   8   7   2  12  15  80]]
-Node Classification on random seed  6916 -> 0.615
-Confusion Matrix:
- [[ 62   4   6   9   0   6  13]
- [  4 130   6   2  12   4   5]
- [ 26  25 129  38  27  29  44]
- [  9   7  10 101   8   2  16]
- [  1   2   5   1  59   3   1]
- [  2   0   3   3   1  56   5]
- [  3   6   8   7   9  13  78]]
-Node Classification on random seed  6917 -> 0.622
-Confusion Matrix:
- [[ 63   7   4  16   2   2  11]
- [  1 131   6   7   8   3   0]
- [ 21  42 135  26  28  20  37]
- [ 11   8  18  95   5   7   8]
- [  1   5   6   1  67   1   1]
- [  1   2   1   4   1  45   5]
- [ 18   8   6  10   4   5  86]]
-Node Classification on random seed  6918 -> 0.654
-Confusion Matrix:
- [[ 64   2  11   4   4   4  15]
- [  3 128   2   1   8   0   7]
- [ 10  34 147  39  35  21  28]
- [  2   5  21 114   3   4  11]
- [  1   4   3   0  62   1   0]
- [  7   0   2   3   3  42   6]
- [ 15   4  11   0   7   5  97]]
-Node Classification on random seed  6919 -> 0.623
-Confusion Matrix:
- [[ 73   4   5   8   1   7  11]
- [ 11 120   5   1  16   3   2]
- [ 25  34 134  36  19  25  27]
- [  7   4  13  98   4   4   9]
- [  2   7   9   1  56   0   3]
- [ 13   3   5   4   0  52   2]
- [  9   7   4   6   8  13  90]]
-Node Classification on random seed  6920 -> 0.61
-Confusion Matrix:
- [[ 58   2  10   7   3   8   6]
- [  7 120   4   2   5   4   2]
- [ 24  32 141  49  28  22  38]
- [ 12   4  18 103   5   3  14]
- [  1   7   3   0  63   4   2]
- [  2   2   0   2   0  35  12]
- [ 13   1   9   5   8  10  90]]
-Node Classification on random seed  6921 -> 0.573
-Confusion Matrix:
- [[ 56   2   0  13   7  15   9]
- [  8 118   1   3   8   6   2]
- [ 25  32  97  50  29  34  37]
- [ 22   7  11 107   2  14   7]
- [  2   4   2   4  69   2   2]
- [  7   0   3   4   0  46   3]
- [ 15   2   3  12   4  14  80]]
-Node Classification on random seed  6922 -> 0.596
-Confusion Matrix:
- [[ 71   5   3   5   5  14   8]
- [  6 131   4   3   2   1   4]
- [ 31  20 126  43  30  14  46]
- [ 33   6  15  84   3   6  15]
- [  0   7   4   1  53   2   2]
- [  0   1   3   1   2  46   3]
- [ 13   5   9  10   4  15  85]]
-Node Classification on random seed  6923 -> 0.579
-Confusion Matrix:
- [[ 66   0   7   6   2  15   8]
- [  5 129   8   3  11   5   5]
- [ 23  30 122  35  34  11  51]
- [  4   4  23  98   4   4  13]
- [  2   1   4   1  65   2   1]
- [  3   1   6   5   2  41   9]
- [ 11   4  12  11  10  25  58]]
-Node Classification on random seed  6924 -> 0.614
-Confusion Matrix:
- [[ 90   1   1   4   4   6  19]
- [  8 132   4   1   5   5   1]
- [ 22  17 110  31  53  27  36]
- [ 21   0  21  88   8   1  10]
- [  2   5   3   3  73   1   1]
- [  7   1   1   1   0  45   3]
- [ 12  10   7   7   7   9  76]]
-Node Classification on random seed  6925 -> 0.624
-Confusion Matrix:
- [[ 74   8   5   3   1  10   6]
- [  9 112   3   3   8   3   1]
- [ 29  25 123  28  34  29  42]
- [  9   3  12 119   5   4   7]
- [  2  15   1   1  56   2   1]
- [  8   3   3   2   0  47   6]
- [  8   6   5   5   7  14  93]]
-Node Classification on random seed  6926 -> 0.579
-Confusion Matrix:
- [[ 66   4   2   1   1  16  18]
- [  2 122  14   3   6   4   4]
- [ 20  25 139  43  27  13  55]
- [  9   5  13  97  14   1  10]
- [  1   9   2   3  44   1   9]
- [ 13   2   4   3   1  39   7]
- [ 11   4  11   9   9  12  72]]
-Node Classification on random seed  6927 -> 0.595
-Confusion Matrix:
- [[ 92   3   4   3   2  12   4]
- [  9 115  17   0   6   4   5]
- [ 20  39 126  37  34  20  41]
- [  9  10   9  92   5  11  12]
- [  0   5   7   3  55   0   6]
- [  3   0   3   0   1  55   5]
- [ 16   2  10   6   8  14  60]]
-Node Classification on random seed  6928 -> 0.563
-Confusion Matrix:
- [[ 60   2   2   2   4   5  22]
- [ 15 100  16   4   5   2   7]
- [ 23  29 115  60  21  20  68]
- [  5   5  13 111   6   5  20]
- [  6   3   5   0  55   2   1]
- [  5   0   2   0   0  49   7]
- [ 15   3   8   4   6   9  73]]
-Node Classification on random seed  6929 -> 0.642
-Confusion Matrix:
- [[ 78   2   3   5   6   9   6]
- [  0 126   9   8  11   0   9]
- [ 29  18 145  26  14  34  23]
- [ 21   3  15  98   5   5   8]
- [  1   4   5   0  69   2   3]
- [  6   0   2   1   0  50   9]
- [ 16   3  10  12   2  13  76]]
-Node Classification on random seed  6930 -> 0.618
-Confusion Matrix:
- [[ 75   1   2   3   2  17   6]
- [ 10 124   7   5  10   0   0]
- [ 36  10 149  34  24  23  38]
- [ 18   3  12  98  11   3  18]
- [  2   4   8   1  54   1   0]
- [  7   0   2   1   0  47   3]
- [ 19   2  12   5  12  10  71]]
-Node Classification on random seed  6931 -> 0.626
-Confusion Matrix:
- [[ 76   0   2   4   5  10   9]
- [  3 111   5  11   3   3   2]
- [ 31  21 125  39  21  11  55]
- [ 13   4  10 120   5   6   8]
- [  5   2   7   0  67   2   2]
- [  9   1   5   6   0  34   3]
- [ 13   3  10   5   5  15  93]]
-Node Classification on random seed  6932 -> 0.615
-Confusion Matrix:
- [[ 80   3   3  10   1   6   3]
- [  8 134   4   4  11   3   1]
- [ 37  26 148  31  31  13  34]
- [ 24   4  16  90   3   2   9]
- [  4   2   3   5  52   1   3]
- [  8   2   4   2   1  43   3]
- [ 21   1   8   7   9  14  68]]
-Node Classification on random seed  6933 -> 0.632
-Confusion Matrix:
- [[ 76   3   4  10   4   9   7]
- [  5 129   7   7   3   4   8]
- [ 14  24 159  36  13  23  27]
- [ 14   7  16  95   7  11   8]
- [  3  15   3   0  53   2   2]
- [  7   1   1   2   1  38   2]
- [ 16   5  14   5   6  12  82]]
-Node Classification on random seed  6934 -> 0.605
-Confusion Matrix:
- [[ 68   2   2  11   6   7  17]
- [  4 117   5   3  15   2   1]
- [ 22  19 149  51  34  19  41]
- [ 11   1  20  98   8  10   7]
- [  0   2   2   0  65   0   2]
- [ 10   1   2   1   2  44   1]
- [ 16   5   8   8   9   8  64]]
-Node Classification on random seed  6935 -> 0.591
-Confusion Matrix:
- [[ 78   1   2   5   2   8  11]
- [  8 120   4   3   8   2   6]
- [ 18  31 104  48  45  23  44]
- [  8   1  18 116   3   5  20]
- [  4   6   2   0  52   0   2]
- [ 10   1   0   1   3  40   4]
- [ 10   3   6   6   6  21  81]]
-Node Classification on random seed  6936 -> 0.605
-Confusion Matrix:
- [[ 80   5   6   3   4   8   8]
- [  2 141   3   4   3   1   8]
- [ 27  24 124  23  23  32  52]
- [ 13   1  12  92   3   7  18]
- [  1  15   3   2  54   0   5]
- [  8   2   2   0   0  43   6]
- [ 16   4   7   2  16  16  71]]
-Node Classification on random seed  6937 -> 0.606
-Confusion Matrix:
- [[ 69   5   1   9   4  12   5]
- [  4 134   5   6  11   2   5]
- [ 28  28 146  41  31  16  36]
- [ 21   3  10 101   3   3  10]
- [  0   7   3   2  57   0   4]
- [  9   1   3   4   3  46   5]
- [  5   3   8  13  12  13  53]]
-Node Classification on random seed  6938 -> 0.631
-Confusion Matrix:
- [[ 63   8   7   7   2   7   7]
- [  2 130   5   1   5   3   1]
- [ 25  16 176  16  25  36  28]
- [ 10   9  16  90   3   2  23]
- [  0  14   3   1  51   4   1]
- [  8   2   0   5   0  42   2]
- [ 16   5  15   8   4  17  79]]
-Node Classification on random seed  6939 -> 0.585
-Confusion Matrix:
- [[ 56   3   1   1   2  23  15]
- [  3 118   3   5  11   4   5]
- [ 21  30 131  49  37  33  28]
- [  9   4  13  86   4  11  20]
- [  1  11   1   1  66   0   2]
- [  0   2   3   4   1  50   1]
- [ 13   4  10   4   0  22  78]]
-Node Classification on random seed  6940 -> 0.626
-Confusion Matrix:
- [[ 83   4   5   0   5  17   4]
- [  7 120   7   4   6   9   3]
- [ 23  25 143  29  24  29  40]
- [  9   6  10 115   1   6   8]
- [  0   6   4   1  55   2   3]
- [  9   0   4   5   0  39   4]
- [  9   5  10   5   5  21  71]]
-Node Classification on random seed  6941 -> 0.586
-Confusion Matrix:
- [[ 84   4   4   9   4   6   6]
- [ 13 125   4   3   9   4   3]
- [ 25  17 110  62  50  15  27]
- [ 15   4  10 102   8  10   9]
- [  0   5   2   2  52   1   2]
- [  9   0   8   0   1  36   6]
- [ 10   3   6  16   8  14  77]]
-Node Classification on random seed  6942 -> 0.662
-Confusion Matrix:
- [[ 74   0   2  12   3   3  10]
- [  2 113   5   4  12   4   6]
- [ 14  21 161  27  22  17  44]
- [ 12   2  10 120   7   4  11]
- [  2   3   2   1  73   0   2]
- [  5   3   3   0   1  40  13]
- [  5   5   8   5   9  17  81]]
-Node Classification on random seed  6943 -> 0.624
-Confusion Matrix:
- [[ 67   1   5  10   3  14   5]
- [  2 134   2   7   2   9   1]
- [ 18  18 137  27  21  22  51]
- [ 14   2  13 100  10   7  13]
- [  1   8   7   3  58   5   3]
- [  7   1   3   3   4  49   3]
- [  8   5  10   8   2  18  79]]
-Node Classification on random seed  6944 -> 0.62
-Confusion Matrix:
- [[ 83   1   5   3   2   7   7]
- [  6 139   7   3   2   4   3]
- [ 29  12 121  34  39  26  30]
- [ 10   2  29 100   1   5  14]
- [  6   2   3   3  59   0   3]
- [  5   3   3   2   0  51   3]
- [ 20   2  22   7   4  11  67]]
-Node Classification on random seed  6945 -> 0.589
-Confusion Matrix:
- [[ 71   2   4   5   5   6   9]
- [  4 113   8   2  14   1   4]
- [ 34  27 124  42  40  14  45]
- [  4   3  22 101   7   8  17]
- [  1   3   2   2  58   4   2]
- [  0   1   3   0   1  42   7]
- [  8   5  20   5   5  15  80]]
-Node Classification on random seed  6946 -> 0.583
-Confusion Matrix:
- [[ 72   5   5   6   5  15   8]
- [  3 123   3   4  11   3   3]
- [ 14  31 106  40  43  36  37]
- [  8  12   8  97   7  12   7]
- [  2   3   4   0  68   0   4]
- [  5   2   3   1   2  41   1]
- [ 14   4   8   8   6  24  76]]
-Node Classification on random seed  6947 -> 0.599
-Confusion Matrix:
- [[ 78   2   9   7   2   6  11]
- [  7 131   6   2   9   2   5]
- [ 28  33 120  27  31  36  41]
- [  7   1  28  97   1   7  13]
- [  3   4   2   0  59   0   1]
- [  6   1   0   0   1  49   6]
- [ 20   5  10   4   4  13  65]]
-Node Classification on random seed  6948 -> 0.586
-Confusion Matrix:
- [[ 64   8   3   8   1  12   7]
- [ 13 102   5  10   6   2   2]
- [ 24  29 144  47  29  26  32]
- [ 10   6  16 107   4   7  12]
- [  3   7   5   1  61   3   5]
- [  7   4   5   2   1  34   7]
- [ 10   1   8   7   5  14  74]]
-Node Classification on random seed  6949 -> 0.586
-Confusion Matrix:
- [[ 66   3  13   7   6  10   1]
- [  4 140   5   1   4   1   3]
- [ 41  21 124  35  32  16  34]
- [ 11   4  17  87  17   1  20]
- [  8   9   1   0  50   2   5]
- [  1   0   5   3   4  47   2]
- [ 15   4  15  14   4  15  72]]
-Node Classification on random seed  6950 -> 0.638
-Confusion Matrix:
- [[ 70   4   4  14   2  16  15]
- [  8 111   7   0   1   1   3]
- [ 17  18 170  33  48   9  35]
- [  4   6  22 103   0   7  15]
- [  1   5   6   3  61   2   0]
- [  7   1   4   1   0  46   3]
- [ 10   1   4   6   7  12  77]]
-Node Classification on random seed  6951 -> 0.607
-Confusion Matrix:
- [[ 83   3   2   3   4  16   5]
- [  4 112   5   4   8   8   7]
- [ 39  26 148  24  22  24  25]
- [ 27   0  25  83   2   3   9]
- [  3   3   6   4  65   1   7]
- [  8   1   4   4   0  40   2]
- [ 11   0  10   9   5  20  76]]
-Node Classification on random seed  6952 -> 0.613
-Confusion Matrix:
- [[ 75   4   0   5   6   5   5]
- [  5 111   1   2  13   5   6]
- [ 30  27 139  18  39  21  55]
- [  8   8  13 110   5   5  16]
- [  1   6   3   1  71   0   6]
- [  4   1   1   3   1  45   6]
- [ 11   2   4  16   7  12  62]]
-Node Classification on random seed  6953 -> 0.606
-Confusion Matrix:
- [[ 68   6   4   6   4  16   6]
- [  5 116   5  15   3   2   8]
- [ 25  21 144  40  29  17  41]
- [ 17   2   6 111   2   2  10]
- [  1  11   2   5  55   1   2]
- [  6   0   7   0   0  50   8]
- [ 21   4   7   6  12   9  62]]
-Node Classification on random seed  6954 -> 0.628
-Confusion Matrix:
- [[ 68   1  10   4   2  12  13]
- [  3 142   4   5   8   6   3]
- [ 19  10 144  33  25  22  44]
- [ 14   4  12 106   2   8   5]
- [  0  11   1   4  54   1   0]
- [  6   0   3   3   1  40  10]
- [ 14   5  13  11   4  16  74]]
-Node Classification on random seed  6955 -> 0.611
-Confusion Matrix:
- [[ 73  13   7   5   3   3   7]
- [  6 140   5   0   6   2   8]
- [ 14  31 125  44  32  22  40]
- [  9   4  24  97   6   4  13]
- [  3   9   3   0  53   0   4]
- [  2   2   4   0   2  35   6]
- [ 13   4  12   1   9   7  88]]
-Node Classification on random seed  6956 -> 0.572
-Confusion Matrix:
- [[ 58   4   8   1   5  10  11]
- [  4 123  13   0   8   3   4]
- [ 62  18 125  26  43  25  37]
- [ 14  11   6 105   4   4  15]
- [  2   6   1   1  56   0   5]
- [  2   0   3   4   2  36  15]
- [  9   7  11   4   8  12  69]]
-Node Classification on random seed  6957 -> 0.611
-Confusion Matrix:
- [[ 62   2  15   3   3   8  16]
- [  1 130   6   1   2   3   8]
- [ 26  28 144  42  19  16  42]
- [ 17   3  16  94  13   5   6]
- [  0   6   5   1  44   1   6]
- [  3   0   2   2   1  54   5]
- [ 21   5   6   9   3  12  83]]
-Node Classification on random seed  6958 -> 0.646
-Confusion Matrix:
- [[ 86   4   3   2   4   8  13]
- [  7 132   4   1   4   7   1]
- [ 20  19 142  19  37  34  28]
- [  9   5  12  95   4   8  15]
- [  1  10   6   5  62   0   2]
- [ 12   3   2   2   2  41   7]
- [  4   4   9   5   3   9  88]]
-Node Classification on random seed  6959 -> 0.626
-Confusion Matrix:
- [[ 66   1   4  16   5   4   4]
- [  1 140   3   4  11   3   1]
- [ 26  16 145  32  44  14  42]
- [  5   4  23 101   8   8  14]
- [  3   6   5   2  71   0   2]
- [  3   1   0   5   0  37   8]
- [  9   4   4  14   2  13  66]]
-Node Classification on random seed  6960 -> 0.662
-Confusion Matrix:
- [[ 77   7   8   3   3  10   7]
- [  3 132   5   2   6   3   3]
- [ 28  12 155  34  30  20  33]
- [  6   4   7 111   5   7   9]
- [  1   3   5   0  60   0   0]
- [  7   1   3   1   9  49   3]
- [ 17   3   9   7   4  10  78]]
-Node Classification on random seed  6961 -> 0.642
-Confusion Matrix:
- [[ 78   9   1   1   3  15   4]
- [  6 123   5   3  11   0   5]
- [ 33  17 154  28  13  35  35]
- [  7   5   6 111   4   8  23]
- [  1   4   2   2  52   0   1]
- [  8   1   1   0   0  48   2]
- [ 19   3   3   6   7  21  76]]
-Node Classification on random seed  6962 -> 0.584
-Confusion Matrix:
- [[ 91   3   2   2   2   5   5]
- [  6 126  10   1   6   1   5]
- [ 27  33 106  21  45  23  61]
- [ 13   8  15  81   7   4  21]
- [  2   3   2   4  56   0   4]
- [  6   3   2   3   0  46   5]
- [ 16   4  11   1   4  20  78]]
-Node Classification on random seed  6963 -> 0.545
-Confusion Matrix:
- [[ 70   2  13   1   5  11   6]
- [  1 124   9   1   4   6   0]
- [ 29  33 121  41  29  34  32]
- [ 20   8  29  82   2   6   7]
- [  2  11   4   1  50   3   2]
- [  4   3  10   0   1  41   9]
- [ 10   2  20   7   8  29  57]]
-Node Classification on random seed  6964 -> 0.611
-Confusion Matrix:
- [[ 79   4   4   4   7   5   9]
- [  4 127   9   2   3   1   7]
- [ 21  34 129  29  55  12  43]
- [ 10   8  19 106   3   2   5]
- [  0   7   2   1  59   0   2]
- [  4   2   4   6   4  43   3]
- [  5  10   7  14   3  15  68]]
-Node Classification on random seed  6965 -> 0.624
-Confusion Matrix:
- [[ 77   7   2   1   0  13   5]
- [  1 139   6   0  14   5   3]
- [ 30  28 135  16  20  18  53]
- [  9   4  18  93   5   6  23]
- [  0  10   2   3  56   1   4]
- [  3   1   6   4   3  41   4]
- [ 11   4   5  11   6  11  83]]
-Node Classification on random seed  6966 -> 0.636
-Confusion Matrix:
- [[ 77   2   4  12   1  14   4]
- [  6 143   1   2   2   2   7]
- [ 14  15 144  30  42  16  45]
- [ 10   2  13 100   7   9  15]
- [  2   9   4   1  49   1   4]
- [  9   4   1   2   0  44   3]
- [ 15   4  12   1   2  15  79]]
-Node Classification on random seed  6967 -> 0.601
-Confusion Matrix:
- [[ 71   2   4   4   4  20  13]
- [  1 129  13   4  12   2   7]
- [ 32  18 129  22  27  28  44]
- [ 13   4  16  90   0  14  13]
- [  1   1   7   1  61   1   4]
- [  4   2   0   1   1  49   5]
- [  8   3   7   6   5  25  72]]
-Node Classification on random seed  6968 -> 0.626
-Confusion Matrix:
- [[ 77   4   0   5   8  14  11]
- [  3 121   3   2  16   2   4]
- [ 21  16 149  35  26  21  38]
- [  9   4  18 108   5  10  10]
- [  1   8   3   2  50   3   5]
- [  1   3   2   3   0  43   6]
- [  8   4  11  14   8   7  78]]
-Node Classification on random seed  6969 -> 0.572
-Confusion Matrix:
- [[ 72   1   6   4   4   3  11]
- [  3 134  17   0   5   4   1]
- [ 33  17  92  32  42  50  48]
- [  9   2  17 107  16   3  12]
- [  0   0   6   1  60   2   1]
- [  6   1   4   4   0  40   9]
- [  8   2  10  15  12   7  67]]
-Node Classification on random seed  6970 -> 0.65
-Confusion Matrix:
- [[ 76   2   6  12   1   9  13]
- [  5 122  10   4   6   3   1]
- [ 18  26 164  22  25   7  40]
- [ 12   2  11 117  10   1  14]
- [  2   5   3   1  53   2   1]
- [  3   1   8   3   1  46   2]
- [ 12   6   8   9  10  13  72]]
-Node Classification on random seed  6971 -> 0.622
-Confusion Matrix:
- [[ 61   2   3   3   8  12  18]
- [  6 120   3   2  11   1  10]
- [ 14  20 152  38  39  22  31]
- [ 11   5  11 102   6   1  16]
- [  2   3   2   3  62   1   5]
- [  3   5   6   5   0  37  11]
- [  6   1   5  10   6  11  88]]
-Node Classification on random seed  6972 -> 0.633
-Confusion Matrix:
- [[ 68   2   5   7   4  10  11]
- [  7 131   7   1   5   4   7]
- [ 12  23 150  28  23  20  43]
- [  7   7  21  89   2   7  16]
- [  4   8   5   2  62   1   2]
- [  6   1   1   0   0  51   6]
- [  8   3  11   3   6  21  82]]
-Node Classification on random seed  6973 -> 0.668
-Confusion Matrix:
- [[ 72   3   5  10   1   7   8]
- [  0 135   7   3   8   0   4]
- [ 18  21 173  17  22  19  32]
- [  6   7  22 106   6   3  15]
- [  1   8   5   3  58   0   5]
- [  2   0   2   3   2  56   3]
- [  9   1  13  14   8   9  68]]
-Node Classification on random seed  6974 -> 0.63
-Confusion Matrix:
- [[ 81   3   0   1   9  11  10]
- [  5 137   6   4   7   1   3]
- [ 21  27 152  31  19   8  52]
- [ 14   7  14  86   7   1   8]
- [  0   3   5   0  57   1   6]
- [ 12   7  11   1   1  30   4]
- [ 11   3  15   7   3  11  87]]
-Node Classification on random seed  6975 -> 0.63
-Confusion Matrix:
- [[ 74   3   4   3   4   5   4]
- [  7 117   5   0  11   1   6]
- [ 15   9 138  43  25  21  41]
- [  8   3  16 119   4   3  11]
- [  1   6   5   6  64   0   5]
- [ 11   0   7   2   1  42   5]
- [ 13   3  10  17  10  16  76]]
-Node Classification on random seed  6976 -> 0.566
-Confusion Matrix:
- [[ 66   2   9   2   3   8   9]
- [  4 132   9   1   1   2   4]
- [ 23  27 101  36  60  24  47]
- [ 17   3   9  89  18   8  14]
- [  1   7   0   0  64   2   5]
- [  5   2   4   0   2  46   6]
- [ 16   3   9   4   9  19  68]]
-Node Classification on random seed  6977 -> 0.62
-Confusion Matrix:
- [[ 78   2   5   4   5  11   9]
- [  9 140   0   3   9   2   5]
- [ 28  30 126  26  38  24  42]
- [ 17   2   8 102   8   5   9]
- [  1   3   2   0  62   0   3]
- [  4   0   4   0   3  53   6]
- [ 15   3   4   6   6  19  59]]
-Node Classification on random seed  6978 -> 0.568
-Confusion Matrix:
- [[ 61  11   7  13   4  13  11]
- [  4 107   2   2  22   5   5]
- [ 24  21 144  38  16  32  44]
- [  6   7  24  98   2   9  11]
- [  0   5   5   1  56   2   1]
- [ 10   0   2   4   3  44   4]
- [  4   3  13   9   9  24  58]]
-Node Classification on random seed  6979 -> 0.586
-Confusion Matrix:
- [[ 85   0   1   6   7  15   4]
- [  7 134  12   6   9   2   3]
- [ 21  19 136  39  27  31  35]
- [ 28   4  14  75   8   9  11]
- [  3   5   4   4  53   1   3]
- [  7   0   2   3   3  44   3]
- [  6   8   4   8   7  25  59]]
-Node Classification on random seed  6980 -> 0.612
-Confusion Matrix:
- [[ 62  10   3   4   2   5  21]
- [  7 113  16   0   7   6   2]
- [  9  23 173  22  24  27  23]
- [ 18   9  16  87   7   7  15]
- [  3   7   5   3  62   0   1]
- [  7   5   5   4   3  41   4]
- [  2   7  12   8   3  26  74]]
-Node Classification on random seed  6981 -> 0.613
-Confusion Matrix:
- [[ 93   2   1   2   7  10   7]
- [  3 120   3   2  10   2   4]
- [ 21  15 128  38  29  31  39]
- [ 19   7  16 113  10   6   8]
- [  0   5   7   0  52   4   2]
- [ 11   1   0   2   0  35   3]
- [ 10   3  15   6   7  19  72]]
-Node Classification on random seed  6982 -> 0.621
-Confusion Matrix:
- [[ 85   1   8   1   8  10   9]
- [  4 125  11   2   8   2   2]
- [ 20  19 146  32  33  35  22]
- [ 17   8  15  90   6  11   7]
- [  0   3   6   1  55   0   2]
- [  8   0   2   4   2  45   3]
- [ 16   1   7   2   8  23  75]]
-Node Classification on random seed  6983 -> 0.59
-Confusion Matrix:
- [[ 70   0   7   3   3  14   4]
- [  3 133   9   5   7   3   3]
- [ 21  27  86  61  33  34  30]
- [  7   2  24 107   6   7  15]
- [  1   5   0   1  69   0   2]
- [ 13   0   5   0   1  47   1]
- [ 23   1   4   6  10   9  78]]
-Node Classification on random seed  6984 -> 0.645
-Confusion Matrix:
- [[ 69   2   3   6   3  11   8]
- [  3 139   3   3   5   3   1]
- [ 14  27 145  46  13  22  52]
- [  6   3  15 116   4   6  18]
- [  1   8   3   2  58   2   0]
- [  4   1   4   1   0  44   7]
- [  4   3   9   7   8  14  74]]
-Node Classification on random seed  6985 -> 0.662
-Confusion Matrix:
- [[ 69   6   4   7   3   9  12]
- [  4 122   9   4   7   2   1]
- [ 14   5 164  44  31  20  27]
- [  4   4  12 122   6   6  22]
- [  1   5   6   2  66   1   0]
- [  3   1   4   1   0  56   5]
- [  8   3  14   3   6  12  63]]
-Node Classification on random seed  6986 -> 0.649
-Confusion Matrix:
- [[ 67   2   7   4   2  10   8]
- [  2 138   7   2   4   4   2]
- [ 32  29 149  19  37  20  26]
- [ 10   6  15 105   8   7  12]
- [  0  10   6   3  52   0   2]
- [  7   2   1   0   1  50   4]
- [  6   8   6   3   6  11  88]]
-Node Classification on random seed  6987 -> 0.593
-Confusion Matrix:
- [[ 62   1   4   7   4  11  25]
- [  3 127   4   4   5   1   7]
- [ 33  17 150  30  15  28  38]
- [  6   5  29  88  15   7   8]
- [  1   4   2   4  65   2   5]
- [ 11   3   2   2   0  39   4]
- [  9   5   7  20   6  13  62]]
-Node Classification on random seed  6988 -> 0.633
-Confusion Matrix:
- [[ 82   3   6   2   3   8   9]
- [  5 135   3   3   2   0   8]
- [ 24  22 142  30  28  22  48]
- [ 12   7  12  98   5   8   8]
- [  1   6   3   2  56   0   2]
- [ 12   2   2   0   2  34  13]
- [ 13   2   4  10   7   8  86]]
-Node Classification on random seed  6989 -> 0.587
-Confusion Matrix:
- [[ 62   2   2  24   3  12  11]
- [  2 127   2   1  10   9   6]
- [ 36  12 137  27  25  29  44]
- [ 16   7  11 104   3   7  18]
- [  0   4   3   0  52   2   4]
- [  1   2   4   6   0  27  16]
- [  6   4   6   8   8  20  78]]
-Node Classification on random seed  6990 -> 0.61
-Confusion Matrix:
- [[ 70   2   8   7   5   4  10]
- [  1 130   1   4  12   4   5]
- [ 22  33 132  25  25  25  24]
- [ 11   4  30  97   6   1   9]
- [  1   6   5   4  65   0   5]
- [  2   2   0  13   1  38  11]
- [  5   4   9  19   9  16  78]]
-Node Classification on random seed  6991 -> 0.572
-Confusion Matrix:
- [[ 77   0   5   6   6  18   2]
- [  1 121  16   3   3   3   5]
- [ 28  33 100  77  24  18  25]
- [  9   1  16 101   5  12   6]
- [  3   3   8   1  53   3   3]
- [  7   0   4   1   0  54   4]
- [ 13   1   9  23   4  19  66]]
-Node Classification on random seed  6992 -> 0.616
-Confusion Matrix:
- [[ 56   3   0   4   3   8  21]
- [ 14 119   7   6   2   3   5]
- [ 26  19 157  35  27  37  41]
- [ 10   4  11 106   6   5  16]
- [  1   3   1   4  68   1   2]
- [  5   0   1   0   2  34  14]
- [  9   4   6   6   4   8  76]]
-Node Classification on random seed  6993 -> 0.605
-Confusion Matrix:
- [[ 58   4  10   0   6  15   8]
- [  2 130   6   5   5   2   4]
- [ 24  15 134  51  24  23  40]
- [  6   1   9  98   7  11  10]
- [  2   6   4   6  60   3   4]
- [  6   1   4   0   1  43   6]
- [  9   4  12  15   4  20  82]]
-Node Classification on random seed  6994 -> 0.607
-Confusion Matrix:
- [[ 63   2   9   5   6  12  12]
- [  7 128   4   2   6   4   3]
- [ 19  20 139  43  29  27  27]
- [ 18   2  22  78   6   8  18]
- [  1  10   0   2  65   2   0]
- [  1   1   1   1   2  48   1]
- [  8   2  17   6   6  21  86]]
-Node Classification on random seed  6995 -> 0.625
-Confusion Matrix:
- [[ 92   2   0   4   2   9   4]
- [  5 123   5   3  12   1   3]
- [ 19  21 143  37  29  16  43]
- [ 14   4  19  90  10   5  19]
- [  1   2   6   0  60   0   3]
- [  8   1   3   3   2  47   5]
- [ 14   2   9  11   8  11  70]]
-Node Classification on random seed  6996 -> 0.612
-Confusion Matrix:
- [[ 59   6   8   1   5   3   9]
- [  5 136   3   1  12   2   1]
- [ 17  27 144  38  28  23  41]
- [ 14   1  19  93   5   8  13]
- [  4   5   5   1  68   1   2]
- [  3   0   3   0   4  38  15]
- [ 12   7  11   5  12   8  74]]
-Node Classification on random seed  6997 -> 0.633
-Confusion Matrix:
- [[ 81   2   0   4   1   9   7]
- [  5 122   4   3   7   0   7]
- [ 22  22 168  49  18  16  26]
- [ 18   1  22 100   3   7   7]
- [  0   7   5   0  66   3   3]
- [  1   6   5   0   1  39   9]
- [ 19   2  13  11   4  18  57]]
-Node Classification on random seed  6998 -> 0.598
-Confusion Matrix:
- [[ 65   3  11   6   4  14   4]
- [  6 118   1  11   7   2   5]
- [ 24  29 153  24  21  29  37]
- [ 11   3  19  84  16   3   7]
- [  0   5   1   0  60   5   5]
- [ 11   1   3   0   1  44   8]
- [ 16   3  15   7   7  17  74]]
-Node Classification on random seed  6999 -> 0.596
-Confusion Matrix:
- [[ 75   3   5   4   4  15  13]
- [  5 113   3   2   4   9   5]
- [ 15  30 141  21  26  30  48]
- [ 22   3  15  92   6  10  10]
- [  0   6   5   4  51   1   1]
- [  3   8   1   0   4  38   8]
- [  8   4  14   2   9  18  86]]
-Node Classification on random seed  7000 -> 0.587
-Confusion Matrix:
- [[ 72   0   4   4   7   9   4]
- [ 14 122   9   1   2   4   3]
- [ 31  24 118  32  29  43  34]
- [  8   4  24 105   5   1  11]
- [  1  12   3   1  58   1   2]
- [ 15   3   0   2   1  48   1]
- [ 16   4   7  12   2  23  64]]
-Node Classification on random seed  7001 -> 0.596
-Confusion Matrix:
- [[ 62   1   5   6   6  14   7]
- [  3 121   6   0   8   5   3]
- [ 12  32 147  39  17  26  43]
- [ 13   4  21  97   9   9  16]
- [  0   8   0   1  60   4   4]
- [  7   2   2   3   1  52   4]
- [ 17   2  11  19   6   8  57]]
-Node Classification on random seed  7002 -> 0.597
-Confusion Matrix:
- [[ 86   3   1   4   0   8  12]
- [  4 131   5   4   9   3   2]
- [ 28  22 142  54  24  17  30]
- [ 23   4   8  91  10   3  19]
- [  3   5   5   2  52   2   2]
- [ 11   0   2   5   1  33   3]
- [ 15   5  16  11   5  13  62]]
-Node Classification on random seed  7003 -> 0.591
-Confusion Matrix:
- [[ 68   2   5   6  10   9  12]
- [  3 133   5   3   7   2   5]
- [ 27  17 146  25  27  21  36]
- [ 30   0  20  78   9   8   5]
- [  0   8   8   2  61   3   2]
- [  4   1   3   4   1  42   5]
- [ 24   4   8  19   2  17  63]]
-Node Classification on random seed  7004 -> 0.633
-Confusion Matrix:
- [[ 64  15   0   1   4  11   5]
- [  1 135   4   4   4   1   4]
- [ 29  24 161  25  21  22  43]
- [  8   5   9 109   5  10  12]
- [  2   9   4   0  47   0   1]
- [  4   2   7   0   0  39   8]
- [ 17   0   9   7  11  19  78]]
-Node Classification on random seed  7005 -> 0.646
-Confusion Matrix:
- [[ 66   3   3   1   1  19   4]
- [  3 129   5   3   5   3   3]
- [ 14  24 154  53  22  22  40]
- [  4   4   5 118   4  11   8]
- [  2   7   3   2  60   1   2]
- [  1   0   1   0   0  55   2]
- [  8   2  11  17   7  24  64]]
-Node Classification on random seed  7006 -> 0.618
-Confusion Matrix:
- [[ 83   4   0   5   3  16   9]
- [  3 117   5   2   5   1   4]
- [ 19  33 143  35  15  29  49]
- [ 14   7   9 105   6   8  10]
- [  2   4   6   3  53   1   1]
- [  5   4   0   1   0  46  10]
- [  6   6   7   1   8  26  71]]
-Node Classification on random seed  7007 -> 0.635
-Confusion Matrix:
- [[ 74   3   6   8   4   5  17]
- [  2 114   6   4   9   5   5]
- [ 29  23 160  26  14   4  49]
- [  6   8  17 107   4   5  13]
- [  3   7   4   1  55   0   9]
- [  7   0   2   1   0  41   6]
- [  9   6  10   7   6  15  84]]
-Node Classification on random seed  7008 -> 0.629
-Confusion Matrix:
- [[ 68   5  10   4   8  11  10]
- [ 10 125   4   0   7   2   6]
- [ 27  12 141  41  17  13  40]
- [  7   4  18 116   2   2  14]
- [  2   8   2   3  57   0   1]
- [  7   0   2   1   1  42   2]
- [ 20   4  14  11   5  14  80]]
-Node Classification on random seed  7009 -> 0.608
-Confusion Matrix:
- [[ 65   1   6   5   3  14   3]
- [  5 114   5   4   6   4   9]
- [ 22  25 148  46  19  32  39]
- [ 13   3  15 106   6   6  10]
- [  1   6   5   5  55   3   0]
- [  8   1   3   0   0  58   2]
- [  5   3  16   5   4  24  62]]
-Node Classification on random seed  7010 -> 0.631
-Confusion Matrix:
- [[ 73   2   3   7   4  15   9]
- [ 12 145   0   0   8   0   3]
- [ 25  11 158  31  15  11  58]
- [ 11   5  14  90   4   7  18]
- [  0  10   3   4  60   1   3]
- [  8   2   3   0   0  37   9]
- [ 13  10   6   8   9   7  68]]
-Node Classification on random seed  7011 -> 0.607
-Confusion Matrix:
- [[ 56   2   6   9   7  15  11]
- [  7 138   3   6   8   2   2]
- [ 26  15 129  37  16  19  46]
- [ 21   5  19  86   2   3  12]
- [  3  10   4   0  62   0   2]
- [  4   1   1   4   2  44   6]
- [ 15   5   2   8   6  21  92]]
-Node Classification on random seed  7012 -> 0.609
-Confusion Matrix:
- [[ 70   0   1   8   1  12   9]
- [  5 119   3   5   8   0   3]
- [ 22  11 133  42  40  25  42]
- [  6   4  14 109   5   6  13]
- [  1   6   3   4  61   0   5]
- [  6   1   3   4   1  45   6]
- [ 13   3   2  11   8  29  72]]
-Node Classification on random seed  7013 -> 0.569
-Confusion Matrix:
- [[ 66   3  10  18   2   6   2]
- [  2 121   5   4  13   2   2]
- [ 23  11 126  47  75  19  27]
- [  9   1  15 109   1  10  13]
- [  1   3   4   4  43   1   8]
- [  3   3   5   6   3  35   2]
- [  9   5  16  17  10  11  69]]
-Node Classification on random seed  7014 -> 0.633
-Confusion Matrix:
- [[ 68   2   5  12   5  15  11]
- [  3 142   6   0  10   2   3]
- [ 28  31 134  39  10  16  45]
- [ 12   3  16 109   6   1   8]
- [  1   8   5   0  60   2   3]
- [ 11   0   2   1   1  40   2]
- [  7   5   7   8   6   9  80]]
-Node Classification on random seed  7015 -> 0.638
-Confusion Matrix:
- [[ 63   2   1   8   6  12  12]
- [  8 131  13   4  10   2   3]
- [ 26  29 146  26  28  25  31]
- [  3   1   6 120   5   5   8]
- [  3   6   2   3  50   0   7]
- [  4   1   1   0   1  53   7]
- [ 14   5  11   7   6  10  75]]
-Node Classification on random seed  7016 -> 0.591
-Confusion Matrix:
- [[ 67   2   6   6   7  13   8]
- [  3 121   9   3  17   2   7]
- [ 22  21 151  18  28  19  41]
- [ 13   1  12  90   5  16  21]
- [  1   8   5   1  49   2   5]
- [  5   1   3   2   4  43   3]
- [ 11   2   8  12  18  18  70]]
-Node Classification on random seed  7017 -> 0.594
-Confusion Matrix:
- [[ 60   2   3   7   4  15  10]
- [ 12 116   7   2   7   1   5]
- [ 16  32 145  32  31  25  48]
- [  9   5  14  86  12  12  12]
- [  1   2   6   0  64   0   3]
- [  6   1   0   2   4  39   6]
- [ 16   7   6   3   7  13  84]]
-Node Classification on random seed  7018 -> 0.641
-Confusion Matrix:
- [[ 80   3   3   5   5  12   5]
- [  2 136   7   1   2   2   2]
- [ 39  31 151  48   7  18  22]
- [ 12   9  17  98   4   5   9]
- [  1   6   8   2  49   2   4]
- [  5   3   2   0   1  44   7]
- [  8   7   9   2   5  17  83]]
-Node Classification on random seed  7019 -> 0.569
-Confusion Matrix:
- [[ 61   2   5   7   4  15   6]
- [  3 117   3   1  10   5   3]
- [ 22  36 107  56  45  22  37]
- [  3   5  11 107   8   9   7]
- [  2   8   1   4  64   5   3]
- [  1   0   1   2   3  48   8]
- [ 12   4  12   8  13  19  65]]
-Node Classification on random seed  7020 -> 0.633
-Confusion Matrix:
- [[ 72   4   0   6   6  14   8]
- [  6 127   9   1  11   2   7]
- [ 28  20 155  30  21  21  33]
- [  9   3  11  87  22   8  16]
- [  3   2   2   1  62   3   3]
- [  1   0   2   2   1  50   5]
- [ 10   4   6   5   5  16  80]]
-Node Classification on random seed  7021 -> 0.635
-Confusion Matrix:
- [[ 73   2   3   3  10   9   6]
- [  0 126   7   3  10   2   0]
- [ 14  27 147  31  35  17  33]
- [ 21   3  17  97   5   3  16]
- [  0   9   5   1  65   2   2]
- [  8   2   0   2   1  40   1]
- [ 10   7   8   7   4  19  87]]
-Node Classification on random seed  7022 -> 0.58
-Confusion Matrix:
- [[ 64   7  14   6   3   8   9]
- [  7 108   3   3  11   5   5]
- [ 27  19 167  23  21  28  44]
- [  9   5  29 105   2   8  15]
- [  4   5   5   2  47   1   6]
- [  6   1   3   2   0  28   9]
- [ 14   6  25   2   9   9  61]]
-Node Classification on random seed  7023 -> 0.629
-Confusion Matrix:
- [[ 69   3   2   8   2  13   7]
- [  2 118  13   0   8   3   5]
- [ 26  19 173  40  13  32  25]
- [  8   6  16  99   5  11  13]
- [  4   4   5   0  54   0   2]
- [  7   0   0   0   2  46   9]
- [ 16   5  10   6   7  14  70]]
-Node Classification on random seed  7024 -> 0.588
-Confusion Matrix:
- [[ 55   5   1   4   3  20  16]
- [  2 123   3   4  11   9   4]
- [ 31  22 132  35  25  31  36]
- [  9   1   6  97  11  14  18]
- [  3   2   4   5  54   7   4]
- [  3   0   2   1   2  45   7]
- [ 14   2  12   8   3  12  82]]
-Node Classification on random seed  7025 -> 0.652
-Confusion Matrix:
- [[ 73   6   3   5   6   8   6]
- [  3 148   7   3   1   1   6]
- [ 18  20 165  53  23  10  24]
- [  7   2  20  99   4   4   9]
- [  0   4   5   4  51   3   5]
- [  3   0   0   1   0  48   4]
- [  8   3  20  19   2  18  68]]
-Node Classification on random seed  7026 -> 0.618
-Confusion Matrix:
- [[ 83   1   0   6   2  10   3]
- [  3 120  16   5   2  10   2]
- [ 23  23 132  36  38  20  26]
- [  8   9   7  97  10   9  13]
- [  0   8   5   1  54   1   2]
- [ 10   3   1   1   0  53   8]
- [  8   4  13  11   3  21  79]]
-Node Classification on random seed  7027 -> 0.557
-Confusion Matrix:
- [[ 64   3   9  14   5   9  16]
- [  3 124   2   4   9   4   5]
- [ 38  32 113  28  22  23  63]
- [ 24   1  14 100   6   5   1]
- [  1   6   1   3  60   0   1]
- [  5   1   2   7   0  46   7]
- [ 22   4  10   9   2  22  50]]
-Node Classification on random seed  7028 -> 0.614
-Confusion Matrix:
- [[ 60   1   0   9   3  12  13]
- [  5 114   6   2  15   5  13]
- [ 28  12 146  35  28  24  37]
- [  8   9   8  97   9  13  13]
- [  2   5   1   1  71   2   0]
- [  5   2   1   1   1  50   6]
- [ 17   1  11   8   4  10  76]]
-Node Classification on random seed  7029 -> 0.591
-Confusion Matrix:
- [[ 60   1   9   5   3  14  17]
- [  7 129   3   6   5   4   3]
- [ 21  28 135  44  30  24  30]
- [ 13   9  10  97   4   7   8]
- [  2   6   2   2  66   0   3]
- [  8   0   5   1   2  40   4]
- [  7   1  24   8   6  23  64]]
-Node Classification on random seed  7030 -> 0.611
-Confusion Matrix:
- [[ 69   6   8   9   1  17   6]
- [  5 114   6   5  14   2   6]
- [ 21  16 163  32  27  27  35]
- [  9   2  15  91   5  12  19]
- [  2   2   5   1  57   0   5]
- [  2   0   2   5   0  38   1]
- [ 20   6   3   9   3  18  79]]
-Node Classification on random seed  7031 -> 0.637
-Confusion Matrix:
- [[ 71   1   5   1   5   8  19]
- [  3 121   2   4  14   2   1]
- [ 31  15 171  42  24  14  27]
- [ 17   4  11 102  11   2  17]
- [  3   4   2   0  59   1   3]
- [  6   1   1   1   1  39   8]
- [ 21   5  12   1   5   8  74]]
-Node Classification on random seed  7032 -> 0.612
-Confusion Matrix:
- [[ 86   4   0   3   6   9   7]
- [  6 113   5  12  16   3   6]
- [ 25  29 145  33  14  11  50]
- [ 26   6  12  83  14   5  10]
- [  1   4   3   0  61   1   1]
- [  5   0   1   3   0  48   3]
- [ 13   4   5   6   5  21  76]]
-Node Classification on random seed  7033 -> 0.65
-Confusion Matrix:
- [[ 54   1   7  11   3  12   3]
- [  6 147   1   3   5   3   3]
- [ 10  11 174  29  41  26  28]
- [ 22   4  14 106   3   6  11]
- [  3   4   6   1  71   0   1]
- [  1   0   4   6   2  30   6]
- [  7   1  16  13   3  13  68]]
-Node Classification on random seed  7034 -> 0.613
-Confusion Matrix:
- [[ 64   3   7   3   2  25  11]
- [  5 138  10   0   2   4   2]
- [ 20  32 127  36  31  31  29]
- [  8   5  13 111   5   5  15]
- [  0   7   2   5  54   1   1]
- [  2   2   1   6   1  39   7]
- [  9   4  11   4   3  17  80]]
-Node Classification on random seed  7035 -> 0.626
-Confusion Matrix:
- [[ 75   0  13   9   5   8   2]
- [  3 119   5   5   9   2   6]
- [ 23  31 146  34  23  18  32]
- [ 18   2  11 100  13   9   8]
- [  2  13   4   1  75   0   0]
- [  6   1   0   8   0  44   4]
- [ 10   3   4   8   7  14  67]]
-Node Classification on random seed  7036 -> 0.614
-Confusion Matrix:
- [[ 59   3  10   8   5  10  20]
- [ 12 114  10   9   7   8   3]
- [ 22  16 137  30  22  25  36]
- [  7   6  15 106   5   5  10]
- [  2   2   9   2  64   2   3]
- [ 11   0   4   3   1  37   4]
- [  3   4   8   3   6  15  97]]
-Node Classification on random seed  7037 -> 0.607
-Confusion Matrix:
- [[ 69   1  12   2   7  10   5]
- [  4 134   5   4   7   1  10]
- [ 14  22 145  39  24  17  49]
- [ 14   4  20  88  12   4  23]
- [  3   5   4   3  62   0   2]
- [  8   1   0   2   0  32  12]
- [  6   3  12  11   6   5  77]]
-Node Classification on random seed  7038 -> 0.611
-Confusion Matrix:
- [[ 78   0  11   5   1   8   6]
- [  4 121   9   3  14   5   5]
- [ 18  25 128  39  34  25  41]
- [  4   3  18  99   8  10  11]
- [  2   5   4   2  53   3   1]
- [  9   1   2   0   0  44   2]
- [ 10   2   9  10   6  14  88]]
-Node Classification on random seed  7039 -> 0.597
-Confusion Matrix:
- [[ 61   2   8   1   8   7  12]
- [  5 123   2   6  16   5   1]
- [ 27  35 146  38  27  24  26]
- [ 10   2  25  89  14   5   8]
- [  2   5   6   1  61   0   6]
- [  8   0   1   2   1  39   5]
- [  9   3  10  12   6  12  78]]
-Node Classification on random seed  7040 -> 0.641
-Confusion Matrix:
- [[ 76   3   3   1   3   7  23]
- [  6 135   3   1   7   4   4]
- [ 21  27 149  30  29  33  21]
- [ 15   7  14 110   1   5   7]
- [  1   9   4   0  65   1   0]
- [  4   0   3   1   0  39   7]
- [  7   1  14   7   8  17  67]]
-Node Classification on random seed  7041 -> 0.629
-Confusion Matrix:
- [[ 89   1   3   1   5  10  11]
- [  1 126  13   2   3   2   5]
- [ 23  22 134  35  25  39  35]
- [  5   2  27  84   8   4  10]
- [  0   5   4   6  60   1   1]
- [  3   3   0   1   1  48   3]
- [  6   7   6   7   8  17  88]]
-Node Classification on random seed  7042 -> 0.637
-Confusion Matrix:
- [[ 74   1   8   6   4   7   5]
- [  9 114   2   5  12   2   5]
- [ 36  24 173  20  19  17  38]
- [  9   6  20  98   4   6  12]
- [  2   3   2   4  54   0   3]
- [  8   2   2   0   2  60   2]
- [ 15   5   4   5   9  18  64]]
-Node Classification on random seed  7043 -> 0.649
-Confusion Matrix:
- [[ 61   2   2   6   8  10  13]
- [  3 135   3   5   4   2   1]
- [ 16  21 166  29  29  20  39]
- [ 13   6  13 112   2   9  16]
- [  0   7   9   1  50   2   1]
- [  5   2   0   1   1  42   6]
- [  5   7   7   6   5  14  83]]
-Node Classification on random seed  7044 -> 0.646
-Confusion Matrix:
- [[ 71   6   3  10   4  10   2]
- [  3 125   3   2  10   1   5]
- [ 22  17 158  31  24  22  39]
- [ 12   3   6 101   9   4   7]
- [  1  10   6   2  61   0   3]
- [  7   1   6   2   0  42   5]
- [ 14   1   6   6  11  18  88]]
-Node Classification on random seed  7045 -> 0.65
-Confusion Matrix:
- [[ 54   5   2   0   4  19  10]
- [  2 139   4   4   4   2   2]
- [ 19  22 162  42  14  15  53]
- [ 12   5  18 114   2   3   6]
- [  2   5   4   2  50   1   6]
- [  5   3   7   1   1  48   4]
- [ 11   2   5   0   6  16  83]]
-Node Classification on random seed  7046 -> 0.624
-Confusion Matrix:
- [[ 70   4   2   3   2   9   6]
- [  3 123   9   1   4   4   4]
- [ 22  27 133  43  24  15  37]
- [ 16   7  12 107   6   2  18]
- [  0   6   8   1  56   4   1]
- [ 17   2   3   0   1  44   3]
- [ 13   8   3   7   6  13  91]]
-Node Classification on random seed  7047 -> 0.63
-Confusion Matrix:
- [[ 76   0   6   7   3  12   6]
- [ 12 122   5   4   6   0   1]
- [ 16  28 136  35  22  22  37]
- [  6   4  15  99   4   7  21]
- [  2   7   0   3  64   0   2]
- [  3   3   2   4   6  45   6]
- [ 11   7   5   4   1  25  88]]
-Node Classification on random seed  7048 -> 0.625
-Confusion Matrix:
- [[ 69   2   7   6   6  19   9]
- [  3 132   3   3  10   0   5]
- [ 24  30 139  27  23  19  46]
- [  9   6  14  95   6  10   7]
- [  0   3   1   1  65   0   2]
- [  4   3   1   1   1  48   2]
- [ 14   4   9  12   7  16  77]]
-Node Classification on random seed  7049 -> 0.663
-Confusion Matrix:
- [[ 62  10   8   8   1  13  11]
- [  8 140   1   1   4   1   1]
- [ 22  27 190  33  14  16  22]
- [  5   2  24 100   5   6   4]
- [  0  12   2   3  55   2   1]
- [  5   0   0   0   2  49   3]
- [  8  11  11  10   8  12  67]]
-Node Classification on random seed  7050 -> 0.632
-Confusion Matrix:
- [[ 72   4   6   8   3   9   8]
- [  7 117  14   2   6   0   2]
- [ 14  15 163  39  45  10  41]
- [  6   6  16 104   3   9   7]
- [  3   6   5   6  54   0   2]
- [  6   2   3   1   2  45   5]
- [  7   6   6  14   5   9  77]]
-Node Classification on random seed  7051 -> 0.644
-Confusion Matrix:
- [[ 76   3   6   9   4   9   6]
- [  3 144   6   1   8   1   1]
- [ 22  20 136  50  35  18  31]
- [  7   5   9 119  10   3  13]
- [  0   5   1   0  58   0   2]
- [  5   1   0   5   4  40   4]
- [  4   2  16  15   4   8  71]]
-Node Classification on random seed  7052 -> 0.629
-Confusion Matrix:
- [[ 77   3   4   7   6  12   4]
- [  3 125  11   1   9   4   2]
- [ 34  28 134  34  30  20  29]
- [  9   4  10 102   6   7   7]
- [  3   5   2   2  60   1   1]
- [  7   0   3   1   0  45   8]
- [ 13   2   6   5  11  17  86]]
-Node Classification on random seed  7053 -> 0.642
-Confusion Matrix:
- [[ 78   2   2   5   7   9   4]
- [  2 145   6   0   4   1   3]
- [ 29  21 151  29  19  17  31]
- [ 25   4  13 102  13   5   9]
- [  2   9   5   1  54   0   2]
- [  6   1   3   1   0  35   9]
- [ 18   2  12   7   8  12  77]]
-Node Classification on random seed  7054 -> 0.643
-Confusion Matrix:
- [[ 86   1   1   4   1   7  10]
- [  5 120   3   2  17   2   6]
- [ 21  23 157  25  26  18  40]
- [ 15   7  17 108   2   7   9]
- [  3   6   4   4  56   2   4]
- [  4   0   1   1   0  43   5]
- [ 13   6  11   1  10  13  73]]
-Node Classification on random seed  7055 -> 0.618
-Confusion Matrix:
- [[ 67   7   8   9   4  14   3]
- [  3 133   5   3   5   6   3]
- [ 14  17 125  34  43  16  44]
- [  8   9  13 115   9   4   5]
- [  1   2   3   2  61   1   5]
- [  4   3   2   3   0  43   7]
- [ 10   4   6  24   6  13  74]]
-Node Classification on random seed  7056 -> 0.633
-Confusion Matrix:
- [[ 80   2   3   2   9   4  12]
- [  6 122   3   2   5   2   3]
- [ 20  21 136  54  38  19  36]
- [ 13   8  12  91  10   5   9]
- [  0   6   0   1  74   1   1]
- [  7   0   3   1   3  40   7]
- [  8   4   8   9   4   6  90]]
-Node Classification on random seed  7057 -> 0.595
-Confusion Matrix:
- [[ 63   3   3  10   8  15   4]
- [  1 135   3   0   5   4   5]
- [ 18  14 132  51  24  22  42]
- [  5   2  13  92  12   9  20]
- [  3  13   1   1  52   0   0]
- [  7   0   4   3   2  43   8]
- [ 14   9   4   8  18  17  78]]
-Node Classification on random seed  7058 -> 0.636
-Confusion Matrix:
- [[ 65   7   9   2   2  19   8]
- [  1 126   5   1   6   2   8]
- [ 14  24 152  46  18  19  28]
- [ 17   2  12 110   2  12   6]
- [  3  11   2   3  56   0   5]
- [  3   3   3   1   0  54   4]
- [  7   5  16   6   8  14  73]]
-Node Classification on random seed  7059 -> 0.63
-Confusion Matrix:
- [[ 67   5   2   3   3  16   4]
- [  4 139   8   0   9   4   0]
- [ 25  29 150  18  19  21  43]
- [  7  10  23  95   8  10   7]
- [  2   6   4   0  63   1   3]
- [  2   1   0   0   0  47   9]
- [ 14   5  10  16   8  11  69]]
-Node Classification on random seed  7060 -> 0.646
-Confusion Matrix:
- [[ 82   2   0   1   2   5   9]
- [  8 126   6   3  10   1   7]
- [ 24  22 170  21  24  17  29]
- [ 12   3  14 104   7   8  13]
- [  1   6   6   1  55   2   1]
- [  2   3   3   2   2  44   4]
- [ 17   6  11   5  12  22  65]]
-Node Classification on random seed  7061 -> 0.633
-Confusion Matrix:
- [[ 67   4   0   2   4   6   7]
- [  2 133  18   8   7   3   5]
- [ 11  20 156  34  30  22  34]
- [ 12   0  17 112   4   3  15]
- [  3   4   3   3  63   3   1]
- [  6   5   3   2   1  45   6]
- [ 12   3  12   8   7  17  57]]
-Node Classification on random seed  7062 -> 0.651
-Confusion Matrix:
- [[ 72   0   2   5   5   9  15]
- [  2 133   2   5  14   0   4]
- [ 15  27 156  42  14  23  24]
- [ 10   9  21  90   7   3  18]
- [  2   5   2   3  67   0   2]
- [  4   0   3   4   1  48   3]
- [  7   7  12   3   7   8  85]]
-Node Classification on random seed  7063 -> 0.597
-Confusion Matrix:
- [[ 78   2   7   5   9   7   2]
- [  4 123  14   1  15   9   5]
- [ 32  14 127  28  42  11  38]
- [ 12   1  17 114   0   4  22]
- [  1   6   3   2  56   0   2]
- [  4   1   4   2   2  43   1]
- [ 26   6  10   3  14  15  56]]
-Node Classification on random seed  7064 -> 0.608
-Confusion Matrix:
- [[ 72   3  10   2   0  11  12]
- [  2 133   1   1  10   4   6]
- [ 24  18 125  35  25  35  33]
- [ 17   5  10  91   5   5  18]
- [  4   6   1   2  61   3   2]
- [  6   0  11   0   0  41  13]
- [  6   5  15   3   9  14  85]]
-Node Classification on random seed  7065 -> 0.577
-Confusion Matrix:
- [[ 64   1   6   8   5  19   9]
- [  4 120   2   2   6   2   6]
- [ 36  21 128  47  37  22  37]
- [ 21   5  11  92  12   5  10]
- [  3   4   3   0  64   1   5]
- [  7   1   2   5   1  39   6]
- [ 13   4  16   6   4   8  70]]
-Node Classification on random seed  7066 -> 0.617
-Confusion Matrix:
- [[ 74   8   2   3   2  12  11]
- [  3 133   6   4   4   4   5]
- [  8  20 118  40  43  24  52]
- [  6   3  11 107   8   9  18]
- [  2   2   3   1  64   1   5]
- [  8   0   3   0   1  50   4]
- [  9   2   6   2   5  23  71]]
-Node Classification on random seed  7067 -> 0.627
-Confusion Matrix:
- [[ 74   2   0   3   2  19   4]
- [  0 124   3   0  14   2   4]
- [ 21  20 137  33  47  31  34]
- [ 13   7   8  89  10  10  12]
- [  1   3   4   1  55   0   5]
- [  2   0   0   0   2  52   6]
- [  8   0   3  13   6  20  96]]
-Node Classification on random seed  7068 -> 0.618
-Confusion Matrix:
- [[ 77   1   4   2   4  11  10]
- [  7 116   9   5   8   8   4]
- [ 24  13 124  38  25  27  49]
- [ 10   3  15 114   4  10  10]
- [  0   4   5   2  68   1   4]
- [  4   0   2   3   0  46   4]
- [ 15   2   8   8   4  15  73]]
-Node Classification on random seed  7069 -> 0.61
-Confusion Matrix:
- [[ 69   2   3   1   6  13  10]
- [  2 116   8   9   1   2   1]
- [ 30  32 129  36  18  22  42]
- [  8   9   9 123   7   4  19]
- [  1   9   3   5  57   1   2]
- [  5   3   1   4   0  50   3]
- [  9   6  12   7  13  12  66]]
-Node Classification on random seed  7070 -> 0.628
-Confusion Matrix:
- [[ 61   1   8   4   3  17  13]
- [  6 139   7   3   5   0   5]
- [ 21  25 153  38  30  27  25]
- [  5   0  22 111   3   8   5]
- [  1   9   3   7  50   2   2]
- [  6   1   3   1   3  45   8]
- [  1   4   9  12   4  15  69]]
-Node Classification on random seed  7071 -> 0.583
-Confusion Matrix:
- [[ 56   4  10   6   7   2  27]
- [  7 118   9   3  15   1   7]
- [ 26  23 113  35  35  25  45]
- [  8  15  13 113   5   2  15]
- [  3   5   3   2  59   0   2]
- [ 13   2   1   0   1  48   0]
- [ 10   4  12   7   5   2  76]]
-Node Classification on random seed  7072 -> 0.637
-Confusion Matrix:
- [[ 71   3   3   5   6  11   7]
- [  9 139   3   3   5   1   5]
- [ 19  30 143  40  24  19  36]
- [  9   4  16 106   0   3  28]
- [  1   8   4   2  46   0   3]
- [  3   0   5   2   0  52   5]
- [ 11   2   9   7   2  10  80]]
-Node Classification on random seed  7073 -> 0.638
-Confusion Matrix:
- [[ 78   2  10   2   3   7  16]
- [  4 122   3   2   3   5   1]
- [ 22  22 164  36  24  27  33]
- [  6   0  21  87   8   6  15]
- [  1   5   6   8  56   0   1]
- [  4   1   0   1   0  54   8]
- [  8   1  15   2   4  19  77]]
-Node Classification on random seed  7074 -> 0.587
-Confusion Matrix:
- [[ 65   1   1   3   5  10  26]
- [  4 128   7   3   4   8   4]
- [ 31   8 107  78  32  13  39]
- [ 12   3  13 101   8   4  19]
- [  2   3   4   4  62   2   3]
- [  4   0   3   3   2  44   5]
- [ 12   4   9   7   6   4  80]]
-Node Classification on random seed  7075 -> 0.613
-Confusion Matrix:
- [[ 59   4   6  10   2  23   8]
- [  7 109   2   2   9   1   0]
- [ 27  18 142  31  32  19  42]
- [  8   2  13 110   6   9  10]
- [  1   7   1   2  74   0   3]
- [  7   1   4   1   1  42   2]
- [ 11   1  13   9  10  22  77]]
-Node Classification on random seed  7076 -> 0.594
-Confusion Matrix:
- [[ 68   2   5   7   7   8   7]
- [  2 124   5   2   3   2   8]
- [ 19  18 116  25  82  21  37]
- [  9   3  17 102   6   8   2]
- [  0   6   2   2  66   2   1]
- [  3   3   1   2   0  50   6]
- [ 11   3  15  25   6  13  68]]
-Node Classification on random seed  7077 -> 0.614
-Confusion Matrix:
- [[ 83   3  14   3   4  11   4]
- [  4 127   2   1   6   1   7]
- [ 33  21 144  18  30  12  55]
- [ 12   5  24  92   4   8   9]
- [  3  10   3   5  57   2   2]
- [  0   2   2   2   2  43   5]
- [ 12   4   9  10   4  18  68]]
-Node Classification on random seed  7078 -> 0.646
-Confusion Matrix:
- [[ 94   2   1   6   3   6   7]
- [  6 120   2   5  16   2   1]
- [ 30  15 170  18  24  10  35]
- [ 19   0  24  98   5   5  16]
- [  1   2   7   0  44   1   1]
- [  8   1   3   4   0  43   6]
- [ 26   2   7  11   8   8  77]]
-Node Classification on random seed  7079 -> 0.622
-Confusion Matrix:
- [[ 76   3   5   1   5  11   3]
- [  2 129   5   2  13   2   9]
- [ 17  25 148  26  49  16  28]
- [ 15   9  11  97   9   4  16]
- [  1   8   3   0  64   0   1]
- [  7   1   2   0   3  45   7]
- [ 24   4   9   7   5  10  63]]
-Node Classification on random seed  7080 -> 0.607
-Confusion Matrix:
- [[ 51   0   9   6   3  21  18]
- [  8 120   6   4  13   2   3]
- [ 12  21 154  52  24   8  45]
- [  6   3  15 102   6   9   7]
- [  4   9   3   0  50   1   3]
- [  3   3   1   5   1  44   6]
- [  9   5  10   6   8  15  86]]
-Node Classification on random seed  7081 -> 0.612
-Confusion Matrix:
- [[ 81   5   3   2   3  14  12]
- [  4 119   5   2  16   3   2]
- [ 17  29 150  31  28  19  39]
- [  8   4  12 101  10   6  18]
- [  1   6   7   2  56   0   3]
- [  4   1   9   0   1  39   3]
- [ 11   3   5   7  15  18  66]]
-Node Classification on random seed  7082 -> 0.603
-Confusion Matrix:
- [[ 65   0   5  18   4  14   4]
- [  5 119  13   2  18   4   6]
- [ 20   8 139  38  16  30  50]
- [  7   0  24 100   2   5   8]
- [  0   2   3   2  65   1   5]
- [  6   2   2   6   3  38   7]
- [ 14   2  10   6  10  15  77]]
-Node Classification on random seed  7083 -> 0.585
-Confusion Matrix:
- [[ 63   2  10   8   3  21   3]
- [  5 121   6   1   7   1   5]
- [ 30  26 123  47  35  26  33]
- [  7   2  17  88   4   4  20]
- [  1   4   8   0  76   1   1]
- [  4   1   0   4   2  50   4]
- [  9   3  15   4  10  21  64]]
-Node Classification on random seed  7084 -> 0.628
-Confusion Matrix:
- [[ 76   2   1   5   1  10   4]
- [  2 121   4   5  10   1   1]
- [ 27  30 168  19  17  29  27]
- [ 13   1  17  94  22   6  14]
- [  0   7   5   3  60   1   1]
- [  6   2   1   2   1  44   6]
- [ 16   4  17   3   8  21  65]]
-Node Classification on random seed  7085 -> 0.635
-Confusion Matrix:
- [[ 81   2   6   2   1   7   7]
- [  7 128   3   2   1   2   2]
- [ 24  35 153  28  19   9  50]
- [ 19   7   9  92   4   9  15]
- [  2  11   9   1  58   0   1]
- [ 11   1   2   3   0  39   5]
- [ 16   0   7   4   4  18  84]]
-Node Classification on random seed  7086 -> 0.62
-Confusion Matrix:
- [[ 72   2   3   3   4  12   8]
- [  4 131   1   6   6   3   4]
- [ 37  22 138  50  18  17  36]
- [ 15   2   7  92  12   6  25]
- [  0   5   4   3  56   0   5]
- [  2   1   1   4   3  46   7]
- [ 14   5  10   1   5   7  85]]
-Node Classification on random seed  7087 -> 0.619
-Confusion Matrix:
- [[ 64   2  13   3   3   8   9]
- [ 12 122   9   4   4   2   3]
- [ 27  21 156  25  36  39  22]
- [ 14   6  10  92   8   6  15]
- [  1   5   5   0  54   1   1]
- [  2   3   2   0   0  57   7]
- [  7   2  15   6   7  16  74]]
-Node Classification on random seed  7088 -> 0.564
-Confusion Matrix:
- [[ 59   4   7  10   2  13  13]
- [  9 125   1   4   7   1   4]
- [ 14  17 121  32  34  31  51]
- [ 21   6  25 102   3   6   8]
- [  0  12   2   5  55   2   5]
- [  9   1   6   6   0  35   8]
- [  7   6  15   5   7  17  67]]
-Node Classification on random seed  7089 -> 0.607
-Confusion Matrix:
- [[ 72   2   0   2   3  26   5]
- [  4 113   8   4   6   3   1]
- [ 28  25 141  49  22  26  43]
- [  8   1  18  96   6  10  10]
- [  2   5   1   1  64   2   3]
- [ 14   2   2   1   0  45   1]
- [ 14   2   8   6   8  11  76]]
-Node Classification on random seed  7090 -> 0.62
-Confusion Matrix:
- [[ 70   0   1   5   4  15  10]
- [  1 122   8   3  10   2   5]
- [ 23  26 149  39  12  23  48]
- [  8   6  16 103   7   5  28]
- [  2   2   2   3  60   4   4]
- [  2   2   1   2   0  42   2]
- [ 15   4   5   3   8  14  74]]
-Node Classification on random seed  7091 -> 0.603
-Confusion Matrix:
- [[ 74   2   1   3   2  11  13]
- [  2 126   9   2   1   3   3]
- [ 25  34 124  37  27  29  40]
- [  6   5  10  98   7   6  32]
- [  1  11   1   2  56   0   0]
- [  4   2   0   0   0  59   5]
- [ 14   2   7  10   5  23  66]]
-Node Classification on random seed  7092 -> 0.645
-Confusion Matrix:
- [[ 67   5   2   2   8  18  14]
- [  1 130   7   3   9   0   2]
- [ 18  15 135  29  28  28  38]
- [  7   5  12 103   0   7  10]
- [  3   2   8   0  73   1   0]
- [  1   2   3   5   1  47  12]
- [ 12   6  14   7   5   5  90]]
-Node Classification on random seed  7093 -> 0.626
-Confusion Matrix:
- [[ 68   5   3   6   1  13  20]
- [  4 125  13   5   5   1   6]
- [ 20  27 153  29  26  15  28]
- [  5   4  20 107   6   8   6]
- [  5   6   4   1  51   0   2]
- [  8   3   5   0   0  56   3]
- [ 17   6   8   8  10  12  66]]
-Node Classification on random seed  7094 -> 0.616
-Confusion Matrix:
- [[ 77   1   2   6   6  12  10]
- [  5 132  13   0   8   4   3]
- [ 13  20 123  35  50  19  34]
- [ 24   2  15  88  12   4   6]
- [  0   5   1   0  70   0   5]
- [  3   1   3   4   0  51   4]
- [  9   4   6   9  11  15  75]]
-Node Classification on random seed  7095 -> 0.624
-Confusion Matrix:
- [[ 67   1   8   5   3  10   7]
- [  4 126   8   5  12   8   1]
- [ 18  19 153  44  13  22  45]
- [ 13   4   7 111   3   8   8]
- [  1   3   3   6  56   1   3]
- [  4   2   4   9   1  34   0]
- [ 11   2   5  15   9  21  77]]
-Node Classification on random seed  7096 -> 0.62
-Confusion Matrix:
- [[ 59   3   3   9   4  12   8]
- [  5 131   6   4  13   3   2]
- [ 17  18 129  49  17  30  45]
- [ 16   4   9 111   4   7   9]
- [  2   8   5   0  70   0   2]
- [  1   2   1   1   0  45   3]
- [  6   5  11   8   9  19  75]]
-Node Classification on random seed  7097 -> 0.631
-Confusion Matrix:
- [[ 57   3   5   4   9  11  10]
- [  3 124   8   6  10   3   6]
- [ 16  21 165  34  37  14  49]
- [ 15   0  11 114   7   6  14]
- [  1   3   5   5  52   0   2]
- [  4   3   0   1   1  45   6]
- [  4   3   7  11   5   6  74]]
-Node Classification on random seed  7098 -> 0.606
-Confusion Matrix:
- [[ 65   1   2   5   5   5   5]
- [  5 134   4   1   7   2   3]
- [ 30  24 147  29  31  30  32]
- [ 10   4  25  96   5   2  13]
- [  2   4   7   5  68   0   3]
- [ 11   2   3   5   4  32   7]
- [ 17   2  16   6  12   8  64]]
-Node Classification on random seed  7099 -> 0.615
-Confusion Matrix:
- [[ 88   5  12   6   1   7   6]
- [  4 131   9   3   5   1   5]
- [ 30  15 161  34  13  19  37]
- [ 10   6  19  91   6   7  12]
- [  1   5   3   3  55   1   3]
- [  8   4   1   2   2  37   7]
- [  9   4  13  14   4  29  52]]
-Node Classification on random seed  7100 -> 0.611
-Confusion Matrix:
- [[ 64   5   4   2   4  16  10]
- [  5 120   9   2  11   7   2]
- [ 12  18 154  30  23  26  61]
- [ 12   2  17  83   6   2  19]
- [  2   4   5   2  53   1   1]
- [  7   0   1   5   2  41   1]
- [  4   2   2  18   7  20  96]]
-Node Classification on random seed  7101 -> 0.607
-Confusion Matrix:
- [[ 61   4   2  16   6   7  11]
- [  6 130   4   2   5   4   7]
- [ 16  18 152  24  37  23  31]
- [ 21   7  19  74   6  17  19]
- [  1   6   2   0  66   0   4]
- [  7   0   4   6   0  38  11]
- [ 12   0   8   5   7   8  86]]
-Node Classification on random seed  7102 -> 0.645
-Confusion Matrix:
- [[ 74   1   5   9  10  11  10]
- [  5 136   4   3   9   0   2]
- [ 11  18 153  16  36  28  43]
- [  9   9  18 105   5   5   7]
- [  1   3   2   6  56   1   3]
- [  6   1   0   3   0  51   2]
- [ 10   5   2   7   9  20  70]]
-Node Classification on random seed  7103 -> 0.622
-Confusion Matrix:
- [[ 70   4   9   8   6   5   4]
- [  5 142   3   0   2   1   7]
- [ 27  35 135  21  35  25  43]
- [ 10   8  15 100   4   6   6]
- [  2   4   3   1  67   0   3]
- [  2   1   2   5   0  43   7]
- [ 11   3   8  12   8  17  65]]
-Node Classification on random seed  7104 -> 0.617
-Confusion Matrix:
- [[ 65   2   3   5   7   9  20]
- [  6 131   5   0   4   1   5]
- [ 22  28 141  34  14  28  29]
- [ 16   3  13  86   6  16  12]
- [  4  10   4   1  59   1   2]
- [  5   4   1   1   0  50   7]
- [ 14   2   9   7   9  14  85]]
-Node Classification on random seed  7105 -> 0.61
-Confusion Matrix:
- [[ 77   0   2   2   3   7  13]
- [  6 121   8   5   5   8   1]
- [ 42  22 113  50  30  23  27]
- [ 10   0   9 110   4   5  11]
- [  3   4   2   6  57   0   0]
- [  9   1   3   3   1  47   7]
- [ 20   5   8  11   3  11  85]]
-Node Classification on random seed  7106 -> 0.588
-Confusion Matrix:
- [[ 57   2  15   0   5  18  13]
- [  9 123   4   0  15   4   3]
- [ 25  11 125  30  15  40  50]
- [  6   3  27  89   3  13  17]
- [  2   8   4   2  59   2   1]
- [  4   2   5   1   2  50   4]
- [  5   3  17   2   4  16  85]]
-Node Classification on random seed  7107 -> 0.591
-Confusion Matrix:
- [[ 61   1   1   3   4  11  13]
- [  5 129  11   3   7   2   2]
- [ 24  38 123  17  38  17  51]
- [ 16   5  11  90   5   4  20]
- [  0  12   2   0  59   4   2]
- [  9   1   2   2   1  47   7]
- [ 13   3   7   9   7  19  82]]
-Node Classification on random seed  7108 -> 0.639
-Confusion Matrix:
- [[ 80   1   3   9   5   9   9]
- [  1 123   4   4   8   2   9]
- [ 15   9 142  41  35  31  26]
- [  5   1  15 116   3   8  15]
- [  0   5   5   0  66   2   2]
- [  3   1   3   6   1  42   7]
- [ 10   5   9  10  10  14  70]]
-Node Classification on random seed  7109 -> 0.614
-Confusion Matrix:
- [[ 61   4   7   5  10   2  22]
- [  9 132   6   1   5   1   4]
- [ 34  17 135  36  26  22  37]
- [  4   5  14 103  12   2  11]
- [  0   9   8   2  62   2   3]
- [  5   1   2   3   1  45   7]
- [  5   2  14  10   5  11  76]]
-Node Classification on random seed  7110 -> 0.593
-Confusion Matrix:
- [[ 73   7   7   6   2  11   4]
- [  2 122   6   2   4   6   6]
- [ 28  16 116  46  26  33  39]
- [  3   6  20 114   7  10  13]
- [  3   7   1   2  60   0   3]
- [  2   1   4   7   0  47   5]
- [  6   3   9  10  14  20  61]]
-Node Classification on random seed  7111 -> 0.604
-Confusion Matrix:
- [[ 72   3   5  14   3   9   6]
- [  7 105   5   4  21   5   3]
- [ 17   9 146  36  22  38  27]
- [ 11   4  16 100   7  12  17]
- [  1   7   2   4  72   2   0]
- [  6   0   3   0   2  51   5]
- [ 13   4  10  15   4  17  58]]
-Node Classification on random seed  7112 -> 0.602
-Confusion Matrix:
- [[ 61   6   3  13   9   9   8]
- [  2 126   6   3  10   6   5]
- [ 21  31 132  15  26  25  46]
- [  9   2  25 115   6  10  11]
- [  4   9   6   0  59   0   1]
- [  7   1   3   3   2  38   7]
- [ 12   2   8   2  18   6  71]]
-Node Classification on random seed  7113 -> 0.627
-Confusion Matrix:
- [[ 68   4   9   7   1   9  13]
- [  3 112   5   1   7   2   4]
- [ 18  32 161  33  15  22  30]
- [  9   4  16 108   2   5  16]
- [  5  10   3   6  65   1   0]
- [  5   5   0   1   1  41  10]
- [  3  11  11   4  15  15  72]]
-Node Classification on random seed  7114 -> 0.602
-Confusion Matrix:
- [[ 71   4   5   2   3  19  18]
- [  3 121   7   1   7   3   3]
- [ 11  18 129  47  45  25  32]
- [  8   3  19  92  13   7  14]
- [  1   7   7   1  57   6   1]
- [  2   2   2   1   0  51   2]
- [  6   4  11   8   5  15  81]]
-Node Classification on random seed  7115 -> 0.627
-Confusion Matrix:
- [[ 68   0   2   9   2  12   6]
- [  3 123   5   1   7   2   7]
- [ 16  21 152  40  17  31  42]
- [ 15   7  16 121   7   6   6]
- [  2   4   6   2  60   0   5]
- [  3   1   2   5   1  41   7]
- [ 15   1   8  13   5  13  62]]
-Node Classification on random seed  7116 -> 0.581
-Confusion Matrix:
- [[ 63   2   2   8   3  19   4]
- [  0 117   2   9  13   2   5]
- [ 17  23 121  58  28  32  40]
- [  9   6  11 107   3  10  10]
- [  0   4   4   1  54   2   7]
- [  4   1   0   3   3  55   4]
- [  6   4   7   8  20  25  64]]
-Node Classification on random seed  7117 -> 0.582
-Confusion Matrix:
- [[ 68   8   6   5   2  21  15]
- [  4 128   3   3  19   4   4]
- [ 22  19 121  40  37  47  31]
- [ 10   2  16  84   7   6  10]
- [  0   4   3   1  56   0   3]
- [  2   2   2   4   0  47   6]
- [ 13   0  22   3   4   8  78]]
-Node Classification on random seed  7118 -> 0.608
-Confusion Matrix:
- [[ 70   5   8   5   2  17   8]
- [  4 135   3   6   5   3   5]
- [ 18  26 134  33  24  30  40]
- [  8   1  21  95   5   6  26]
- [  3   4   6   4  57   1   3]
- [  4   1   1   3   2  42   0]
- [  8   4   3   6  10  20  75]]
-Node Classification on random seed  7119 -> 0.612
-Confusion Matrix:
- [[ 55   8   5   2   3  13  12]
- [  5 140   8   3   9   2   3]
- [ 26  27 138  33  30  23  40]
- [ 12   3   8  89   1  15  17]
- [  1   7   4   2  65   1   5]
- [  1   2   6   0  10  39   1]
- [  3   1  10   4   7  15  86]]
-Node Classification on random seed  7120 -> 0.608
-Confusion Matrix:
- [[ 85   3   2   1   3  17   2]
- [  6 118   6   0  11   3   7]
- [ 13  21 123  29  30  35  44]
- [  6   4  16 115   2   8  12]
- [  3  12   5   5  54   0   3]
- [  7   1   4   4   0  43   3]
- [ 21   5   2   4  13  19  70]]
-Node Classification on random seed  7121 -> 0.622
-Confusion Matrix:
- [[ 59   4   2   8   2   9  24]
- [  3 124   1   6   3   3   6]
- [ 27  18 143  53  16  29  28]
- [  4   3  21 120   1   7   8]
- [  3   3   1   2  52   2   5]
- [  5   2   3   0   0  42  19]
- [  4   0  15   9   5  14  82]]
-Node Classification on random seed  7122 -> 0.599
-Confusion Matrix:
- [[ 87   0  10   2   8   9   3]
- [  3 132  11   3   3   5   1]
- [ 27  19 127  27  32  35  25]
- [ 15   3  14 105   3  23  14]
- [  1   4   0   2  50   3   3]
- [  7   0   3   0   0  48   8]
- [ 22   2  17   9   7  18  50]]
-Node Classification on random seed  7123 -> 0.626
-Confusion Matrix:
- [[ 59   3   2   1   2   8  13]
- [  4 126   1   1   5   2   5]
- [ 15  37 133  45  21  46  38]
- [ 10   4  18 100   9  13   6]
- [  1   6   3   0  74   1   0]
- [  5   2   3   0   0  50   8]
- [  4   5   9   4   3  11  84]]
-Node Classification on random seed  7124 -> 0.596
-Confusion Matrix:
- [[ 72   7   5  16   3   3  16]
- [  7 128   5   3   8   0   2]
- [ 19  38 143  49  17  16  27]
- [  7   9  22  89   7   5  19]
- [  1  12   6   2  62   0   2]
- [  7   2   1   4   0  40   8]
- [ 12   5  10   5   5  12  62]]
-Node Classification on random seed  7125 -> 0.622
-Confusion Matrix:
- [[ 79   5   5   6   0   2  15]
- [  8 123   7   7   5   3   3]
- [ 27  14 147  37  35  15  38]
- [  6   4   7 103   3   9  24]
- [  0   7   2   3  60   0   3]
- [  7   4   1   1   1  46   5]
- [  9   9   8  10  15   8  64]]
-Node Classification on random seed  7126 -> 0.635
-Confusion Matrix:
- [[ 58   7  14   3   5   5   7]
- [  4 148   5   2   3   3   2]
- [ 21  27 138  35  26  24  31]
- [ 10   3  15 113   3   6  13]
- [  2   7   3   3  54   0   2]
- [  3   6   3   0   1  51   3]
- [  6   4  12  10   8  18  73]]
-Node Classification on random seed  7127 -> 0.652
-Confusion Matrix:
- [[ 76   6   5   2   4  12  11]
- [  5 131   3   3   4   2   4]
- [ 23  23 160  39  20  18  35]
- [  9   4   9 100   7   4  14]
- [  1   7   2   1  56   0   3]
- [  8   1   3   0   4  42   4]
- [ 11   2  12   4   5  14  87]]
-Node Classification on random seed  7128 -> 0.592
-Confusion Matrix:
- [[ 45   9   6   8   7  17   8]
- [  2 114   9   4  10   1   4]
- [ 18  28 143  35  20  30  38]
- [ 11   8  18 113   7   6  14]
- [  0   5   4   0  65   2   0]
- [ 11   2   4   2   2  44   4]
- [ 13   3  10   3  14  11  68]]
-Node Classification on random seed  7129 -> 0.64
-Confusion Matrix:
- [[ 71   2   2   3   1  12   8]
- [ 10 142   3   3   5   3   5]
- [ 19  15 179  38  11  24  39]
- [  7   7  21  95   6   6  10]
- [  2   5   4   4  50   0   3]
- [  6   1   1   0   2  35  14]
- [ 12  11   9   7   2  17  68]]
-Node Classification on random seed  7130 -> 0.633
-Confusion Matrix:
- [[ 68   5   4   0   0  17   9]
- [  5 132   5   7   4   2   1]
- [ 17  16 144  38  21  13  60]
- [ 14   2   7 100   7  12  20]
- [  0   7   2   0  64   0   4]
- [  2   4   0   1   1  46  10]
- [  9   3   4   8   5  21  79]]
-Node Classification on random seed  7131 -> 0.634
-Confusion Matrix:
- [[ 78   5   2   5   6  10   1]
- [  8 121   2   2  13   2   1]
- [ 37  21 153  30  16  22  36]
- [ 15   7  11 103   4  10  11]
- [  2  14   2   1  63   1   1]
- [  3   0   2   3   0  43   4]
- [ 16   6  10   4   4  16  73]]
-Node Classification on random seed  7132 -> 0.601
-Confusion Matrix:
- [[ 47   1   9   5  12  11  16]
- [  5 124   3   1  15   3   2]
- [ 21  17 147  32  33  24  58]
- [  4   0  21 108   3   6  12]
- [  2   4   4   0  61   2   0]
- [  1   3   2   1   1  41   3]
- [ 14   4   9   9  11  15  73]]
-Node Classification on random seed  7133 -> 0.623
-Confusion Matrix:
- [[ 68  10   2   2   4   7  13]
- [  3 149   6   2   3   4   8]
- [ 43  22 132  25  33   9  43]
- [  6   9   3 102   4   7  21]
- [  0   9   8   2  65   0   2]
- [  5   2   4   0   1  38   4]
- [ 20   1   7   3   8  12  69]]
-Node Classification on random seed  7134 -> 0.639
-Confusion Matrix:
- [[ 75   3   8   3   2  10   6]
- [  6 133   2   1  10   9   0]
- [ 21  28 148  24  18  31  39]
- [ 14   4  10  97  13   6  16]
- [  0   5   8   1  62   0   1]
- [  5   2   4   2   0  41   2]
- [  8   4  13   3   3  16  83]]
-Node Classification on random seed  7135 -> 0.594
-Confusion Matrix:
- [[ 60   5   3   5   5  13  14]
- [  3 128   2  15  19   1   1]
- [ 19  17 141  37  17  22  48]
- [ 11   3  14  99   4   3  19]
- [  0   6   8   3  51   0   3]
- [  8   2   1   1   4  39   7]
- [ 15   2   4  13   8  21  76]]
-Node Classification on random seed  7136 -> 0.593
-Confusion Matrix:
- [[ 78   0   6   4   2   4  14]
- [  3 117   6  10   6   1   4]
- [ 30  18 132  54  34  21  38]
- [  8   1  29  97   2   2  19]
- [  1   3   4   8  50   1   2]
- [ 10   1   2   1   0  46   9]
- [ 18   2   8   4   9   8  73]]
-Node Classification on random seed  7137 -> 0.61
-Confusion Matrix:
- [[ 73   4   4   7   5  11   4]
- [  2 138   3   1  14   2   2]
- [ 24  31 138  27  24  24  34]
- [ 10   2   9 123   3   8  12]
- [  1   4   6   0  55   1   3]
- [  6   1   4   6   1  44   4]
- [ 11   2  15  19  25  14  39]]
-Node Classification on random seed  7138 -> 0.608
-Confusion Matrix:
- [[ 77   2  12   4   2   5  10]
- [  1 120   8   3   7   4   8]
- [ 26  21 133  46  38  14  26]
- [  9   2  19 103  12   7  15]
- [  1   4   4   1  68   0   3]
- [  8   0   1   2   2  53   3]
- [  9   3  18   7  10  15  54]]
-Node Classification on random seed  7139 -> 0.61
-Confusion Matrix:
- [[ 74   1   3   6   3   7   8]
- [  4 140   7   2  10   7   5]
- [ 31  18 132  42  15  31  45]
- [ 11   4  18  99   3   3  18]
- [  0   5   4   0  62   3   6]
- [  8   0   1   1   1  36   4]
- [ 24   2  10   2   9   8  67]]
-Node Classification on random seed  7140 -> 0.612
-Confusion Matrix:
- [[ 81   5   3   0   2  10   8]
- [  7 112  10   2  12   4   2]
- [ 20  27 125  35  39  33  32]
- [  9   4  27  95   2   4  17]
- [  1   8   3   0  71   1   3]
- [  5   1   1   1   1  49   2]
- [  9   8   7   2   4  17  79]]
-Node Classification on random seed  7141 -> 0.573
-Confusion Matrix:
- [[ 68   5   5   6   7  13  10]
- [  6 118   6   9   9   2   6]
- [ 38  26 123  31  22  29  31]
- [ 12  13  17  99   7   5   9]
- [  2   5   2   2  54   1   5]
- [ 11   2   2   1   2  39   4]
- [ 16   6   7  14   5  16  72]]
-Node Classification on random seed  7142 -> 0.618
-Confusion Matrix:
- [[ 56   2   3  11   3  23   4]
- [  0 138   8   2  18   1   3]
- [ 26  20 170  28  21  21  35]
- [  8   1  27  86   9   8  15]
- [  1   4   5   2  62   1   3]
- [  6   2   0   2   2  38   3]
- [ 24   6   2   6   3  13  68]]
-Node Classification on random seed  7143 -> 0.651
-Confusion Matrix:
- [[ 80   5   6   2   1  14   3]
- [  4 124   2   6   8   0   0]
- [ 19  26 141  43  22  15  46]
- [  6   0  20 112   4   6   9]
- [  2   6   8   3  68   0   2]
- [  4   2   3   0   1  57   1]
- [ 11   5   0  11   6  17  69]]
-Node Classification on random seed  7144 -> 0.58
-Confusion Matrix:
- [[ 67   1   3   3   4  14   5]
- [  1 139   9   2   0   2   0]
- [ 26  34 116  48  23  24  37]
- [ 11   5  27  90   6  11  16]
- [  5   9   2   2  55   2   4]
- [  4   2   2   1   1  45   5]
- [ 12   6  18   3   8  22  68]]
-Node Classification on random seed  7145 -> 0.633
-Confusion Matrix:
- [[ 79   1   5   6   3   2   9]
- [  4 130   0   3   4   1  20]
- [ 31  21 157  33  22  21  36]
- [  7   5  11  97  10   6  22]
- [  2   7   1   0  60   0   3]
- [  8   0   3   4   2  32   7]
- [  7   3  11   7  16   3  78]]
-Node Classification on random seed  7146 -> 0.618
-Confusion Matrix:
- [[ 64  12   5   6   2  11  10]
- [  2 109  11   2   9  11   5]
- [ 22   9 167  33  19  31  21]
- [ 18   0  17  93   8   3  13]
- [  1   5   6   1  59   1   6]
- [  9   2   1   2   0  42   6]
- [ 22   4   9  10   6  11  84]]
-Node Classification on random seed  7147 -> 0.634
-Confusion Matrix:
- [[ 70   1   3   5   3  11  12]
- [  5 132   2   1   7   6  10]
- [ 32  13 151  30  29  13  41]
- [ 10   6  20  86   0   9  21]
- [  4   3   3   0  62   3   1]
- [  7   0   2   0   2  50   4]
- [ 16   2   5   2   5  17  83]]
-Node Classification on random seed  7148 -> 0.667
-Confusion Matrix:
- [[ 78   1   3   4   1  13   5]
- [  3 140   2   5   3   5   2]
- [ 17  24 146  26  22  23  30]
- [  7   2  25 114   3   7   9]
- [  1   6   4   2  50   4   3]
- [  5   0  11   3   0  54   4]
- [  0   2  10   5   9  22  85]]
-Node Classification on random seed  7149 -> 0.569
-Confusion Matrix:
- [[ 55   7   7  13   2  10   8]
- [  9 116   2   5  10  10   7]
- [ 18  13 139  43  37  24  25]
- [ 25   3  17  88   7  11  10]
- [  1   5   3   7  63   1   1]
- [ 13   0   2   3   5  47   3]
- [ 14   4   9  19  11   7  61]]
-Node Classification on random seed  7150 -> 0.595
-Confusion Matrix:
- [[ 68   4   6   9   3   7  11]
- [  5 111   5   6  16   2   6]
- [ 32  21 127  39  40  14  39]
- [  7   3   9  89   2   7  23]
- [  1   4   2   3  71   0   4]
- [ 10   1   2   1   1  43   6]
- [ 14   1  14  10   5  10  86]]
-Node Classification on random seed  7151 -> 0.652
-Confusion Matrix:
- [[ 77   3   5   3   3  10  14]
- [  4 122   6  11  10   1   4]
- [ 24  26 156  31  18  16  31]
- [ 11   3  13 117   3   3   7]
- [  2   8   4   2  69   0   3]
- [  4   0   2   4   0  48   8]
- [ 10   3  10   9   8  11  63]]
-Node Classification on random seed  7152 -> 0.635
-Confusion Matrix:
- [[ 69   4   8   2   3   7   3]
- [  3 132  13   0  10   7   3]
- [ 28  18 153  47  24  17  30]
- [ 10  10   9 102   5   5  11]
- [  1   7   4   2  56   3   2]
- [  6   0   5   3   7  34   5]
- [ 14   1   4  17   1   6  89]]
-Node Classification on random seed  7153 -> 0.602
-Confusion Matrix:
- [[ 67   4   6   1   7  10  12]
- [  2 113  12   0   6   3   3]
- [ 21  15 132  31  15  30  67]
- [ 13   1  12 109   6   4  15]
- [  0   7   5   1  53   2   2]
- [  3   1   1   3   6  44   8]
- [ 12   8  15   5   7  16  84]]
-Node Classification on random seed  7154 -> 0.616
-Confusion Matrix:
- [[ 62   2   6   3   6  13  17]
- [  0 128  19   2  16   0   4]
- [  7  17 142  30  40  19  53]
- [  9   4  11 104   6   5  12]
- [  0   8   3   0  61   0   4]
- [  1   2   1   0   2  50   1]
- [  5   2   8   7   8  31  69]]
-Node Classification on random seed  7155 -> 0.626
-Confusion Matrix:
- [[ 79   2   0   8   2   8  17]
- [  5 139   6   0  17   3   5]
- [ 29  18 139  25  28  29  37]
- [ 12   5   8 105   6  11  16]
- [  1   3   3   3  53   1   5]
- [ 10   1   4   3   1  38   5]
- [  8   4   4   7   7   7  73]]
-Node Classification on random seed  7156 -> 0.605
-Confusion Matrix:
- [[ 74   4   3   5   1  15   8]
- [  3 111   7   6  12   4   4]
- [ 17  17 150  44  24  29  38]
- [ 11   3  16 113   9   6   9]
- [  0   6   5   2  46   1   6]
- [  2   0   3   2   0  37   7]
- [  7   4  13  10  12  20  74]]
-Node Classification on random seed  7157 -> 0.57
-Confusion Matrix:
- [[ 63   1   5  15   6  18   0]
- [  7 123   5   0   8   4   6]
- [ 36  34 101  40  31  38  36]
- [  7   4  17 106   1   8   8]
- [  3   4   3   2  61   0   6]
- [  7   0   3   4   2  44   6]
- [  8   3   7   8  11  18  72]]
-Node Classification on random seed  7158 -> 0.616
-Confusion Matrix:
- [[ 58   4   4   5   6   6  32]
- [  1 120   8   6  13   6   5]
- [ 24  25 154  23  27  23  32]
- [ 11   3  10 112   4   6  10]
- [  0   3   2   3  62   0   1]
- [  5   3   0   0   3  45  12]
- [ 12   2   6   3  11  24  65]]
-Node Classification on random seed  7159 -> 0.571
-Confusion Matrix:
- [[ 73   3   4   3   7  16   9]
- [  2 141   2   1   7   1   4]
- [ 19  35 119  43  38  28  48]
- [  6   6  15  87   1   7  13]
- [  0  10   4   3  54   1   1]
- [  8   2   3   0   0  47   4]
- [ 16   4  14   8  22  11  50]]
-Node Classification on random seed  7160 -> 0.641
-Confusion Matrix:
- [[ 69   2   7   5   2   8  14]
- [  8 134   1   2   4   1   7]
- [ 18  17 145  30  37  15  42]
- [ 10   1  11 116   6   7  16]
- [  3  10   4   1  55   1   1]
- [  6   6   3   2   1  36   5]
- [ 12   2  10   8   6   7  86]]
-Node Classification on random seed  7161 -> 0.628
-Confusion Matrix:
- [[ 75   4   4   6   4  10   8]
- [  2 124   5   3   9   4   5]
- [ 23  16 146  23  30  25  33]
- [ 19   8  18 110   1   6  12]
- [  0   6   7   1  56   1   5]
- [  7   1   1   4   5  43   5]
- [ 15   4   3   3   5  21  74]]
-Node Classification on random seed  7162 -> 0.643
-Confusion Matrix:
- [[ 77   0   1   2   2  17   8]
- [  2 105   9   3  12   2   6]
- [ 28  20 144  32  20  27  39]
- [ 10   4  13 118   2   7   7]
- [  3   3   1   2  64   2   5]
- [  5   1   2   1   0  56   4]
- [ 16   2   7   7   5  18  79]]
-Node Classification on random seed  7163 -> 0.621
-Confusion Matrix:
- [[ 58   3   3   5   2  12   2]
- [  1 116   8   3   7   6   3]
- [ 29  17 173  45  29  23  25]
- [ 17   4  12 106   2   7  14]
- [  2   8   5   1  56   0   3]
- [  4   1   1   0   0  42   7]
- [ 25   0  12   9   1  21  70]]
-Node Classification on random seed  7164 -> 0.656
-Confusion Matrix:
- [[ 87   1   1   2   3  14   4]
- [  5 140   3   0   8   5   1]
- [ 19  20 149  26  18  22  42]
- [ 12   6  29  90   2   9   5]
- [  4   8   5   1  50   3   2]
- [  5   0   1   0   1  56   3]
- [ 14   3   5   6   5  21  84]]
-Node Classification on random seed  7165 -> 0.592
-Confusion Matrix:
- [[ 75   1   6   6   1   5  14]
- [  4 119   5   2  17   2   3]
- [ 24  27 117  23  22  35  40]
- [ 11   4  17 108   5   6  15]
- [  2   5   6   2  70   0   3]
- [ 10   1   1   5   0  43   2]
- [ 15   6  16  11   9  19  60]]
-Node Classification on random seed  7166 -> 0.607
-Confusion Matrix:
- [[ 73   3   5   3   6   7   7]
- [  4 133  13   4   8   1   3]
- [ 27  26 125  62  13  12  52]
- [ 11   4  12  95  15   3  18]
- [  3   6   4   0  52   1   1]
- [  7   1   1   3   4  38   2]
- [ 13   3   3   1   5  16  91]]
-Node Classification on random seed  7167 -> 0.586
-Confusion Matrix:
- [[ 67   4   0   5   2  11  18]
- [  9 115   2   5  16   2   1]
- [ 34  17 105  39  55  16  44]
- [ 18   3  11 107   6   5  18]
- [  2   3   2   0  60   0   2]
- [  6   0   5   1   0  33   8]
- [  7   2   4  10  11  10  99]]
-Node Classification on random seed  7168 -> 0.588
-Confusion Matrix:
- [[ 80   5   9   2   3   6   6]
- [  5 150   3   3   5   3   2]
- [ 29  41 111  30  25  26  45]
- [ 12   5  12  96   2   7  19]
- [  0  13   0   1  59   3   2]
- [ 10   1   1   1   0  44   3]
- [ 27   2   6   4   8  25  48]]
-Node Classification on random seed  7169 -> 0.603
-Confusion Matrix:
- [[ 66   3  10   9   6   3  10]
- [  3 131   7   3   4   2   2]
- [ 32  11 160  28  31  29  27]
- [ 16   3  17  81   8   9  11]
- [  3   7   1   5  63   4   6]
- [ 10   4   1   1   0  41   9]
- [ 23   8   9   9   1  12  61]]
-Node Classification on random seed  7170 -> 0.624
-Confusion Matrix:
- [[ 82   3   6   7   1   6  11]
- [  0 128   7   4  15   2   5]
- [ 36  20 131  41  29  10  42]
- [ 11   8  13  95   6   1  10]
- [  1   3   6   2  56   1   1]
- [  3   2   2   0   2  50   6]
- [ 13   3  14   4  13   6  82]]
-Node Classification on random seed  7171 -> 0.652
-Confusion Matrix:
- [[ 61   0   3   4   6  16  13]
- [  4 126   7   2   3   1   2]
- [ 16  26 144  27  24  29  31]
- [  7   3  10 124   2  11  14]
- [  1   2  10   2  55   1   1]
- [  4   3   4   1   0  55   6]
- [  7   6   7   3   9  20  87]]
-Node Classification on random seed  7172 -> 0.6
-Confusion Matrix:
- [[ 67  11  20   6   2   9   7]
- [  4 126   7   2   9   0   9]
- [ 14  21 152  35  33  31  34]
- [ 21   3  15  85   6   5   6]
- [  1   4   4   1  62   0   0]
- [ 10   1   5   2   4  36   4]
- [ 12   1   9   6   8  18  72]]
-Node Classification on random seed  7173 -> 0.611
-Confusion Matrix:
- [[ 76   1   4   4   4   4  21]
- [  0  99   4   8  14   1   2]
- [ 30  15 147  37  25  38  25]
- [ 17   4  22 101   5   6   7]
- [  1   9   6   3  55   4   0]
- [  2   2   2   1   4  49  15]
- [  7   2  13   9   3   8  84]]
-Node Classification on random seed  7174 -> 0.582
-Confusion Matrix:
- [[ 63   4   3   4  14  11   9]
- [  8 121   4   4  10   3   5]
- [ 30  28 102  41  28  23  49]
- [  8   3   9  95   4  15  13]
- [  1   7   3   4  65   1   1]
- [  4   3   2   2   0  53   3]
- [ 11   4  10   8   5  19  83]]
-Node Classification on random seed  7175 -> 0.618
-Confusion Matrix:
- [[ 77   6   4   3   3  12  16]
- [  3 129   7   4   4   3   4]
- [ 37  30 125  26  14  16  42]
- [ 17   1  14 105   7   4   6]
- [  1  13   4   4  49   1   2]
- [  6   3   6   1   0  43   5]
- [ 16   7   5   6   0  19  90]]
-Node Classification on random seed  7176 -> 0.619
-Confusion Matrix:
- [[ 55   5  11   8  15   8   3]
- [  1 142   8   2   4   5   5]
- [ 27  28 129  32  34  24  34]
- [ 15  10   6 109  10   1  14]
- [  4   8   2   0  63   0   1]
- [  3   1   2   0   4  44   1]
- [ 15   4  10   4   4   8  77]]
-Node Classification on random seed  7177 -> 0.581
-Confusion Matrix:
- [[ 74   2  13   5   1   6   4]
- [ 10 105   6   2  16   7   1]
- [ 25  26 132  20  59  25  29]
- [  9   3  25  87  13   5   9]
- [  2   9   3   1  64   1   2]
- [  1   4   4   1   0  49   2]
- [ 10   8  14   9   9  18  70]]
-Node Classification on random seed  7178 -> 0.617
-Confusion Matrix:
- [[ 66   4   4   2  11   6   8]
- [  4 161   7   4   3   1   6]
- [ 17  30 126  49  19  25  47]
- [ 15   5  14 103   6   2   5]
- [  1   8   8   0  45   1   3]
- [  8   1   1   0   0  38   8]
- [ 12   5  13   3   3  14  78]]
-Node Classification on random seed  7179 -> 0.572
-Confusion Matrix:
- [[ 57   2   2   8   9  18  14]
- [  7 116   6   0  15   4   0]
- [ 26  19 120  30  35  33  50]
- [ 14   3  10 101  10   8  11]
- [  1   5   4   0  54   1   0]
- [  8   2   1   5   2  44   1]
- [ 18   5  11   5   5  20  80]]
-Node Classification on random seed  7180 -> 0.628
-Confusion Matrix:
- [[ 93   8   4   7   5   7   6]
- [  6 130   6   3   8   3   5]
- [ 34  21 129  23  19  55  29]
- [  7   3  13  98   6   3   7]
- [  4   7   5   2  63   0   3]
- [  8   0   0   1   1  38   5]
- [  6   4   6   2   8  22  77]]
-Node Classification on random seed  7181 -> 0.591
-Confusion Matrix:
- [[ 55   0  12   6   2   8  11]
- [ 20 120   6   0   3   4   9]
- [  9  16 143  32  38  40  40]
- [  5   5  13 100   5   6  19]
- [  2   6   2   2  64   1   6]
- [  5   2   7   1   2  36   8]
- [  8   2   3  15   3  25  73]]
-Node Classification on random seed  7182 -> 0.579
-Confusion Matrix:
- [[ 60   0   3  16   4   7  16]
- [  3 143   5   2   4   0   1]
- [ 33  29 114  41  45  30  23]
- [ 15   9   8  96   4   4  24]
- [  1   5   4   0  63   2   3]
- [  9   2   1   1   0  42   7]
- [ 11   4   6  14   4  21  61]]
-Node Classification on random seed  7183 -> 0.59
-Confusion Matrix:
- [[ 66   2   5   1   7  14  19]
- [  4 133   5   3  12   3   4]
- [ 26  21 131  37  33  12  43]
- [ 15   5  19  95   8   1  15]
- [  2   6   5   2  53   4   4]
- [  2   2   9   2   0  40   8]
- [  7   7   7  11   5  13  72]]
-Node Classification on random seed  7184 -> 0.576
-Confusion Matrix:
- [[ 58   0   8  13   8   5   3]
- [  2 129   5   5   6   3   3]
- [ 15  26 110  62  43  19  45]
- [ 22   2  25  92   4   7   8]
- [  1   5   1   0  72   2   5]
- [  5   2   2   3   1  44   4]
- [  7   4  20   6   4  13  71]]
-Node Classification on random seed  7185 -> 0.61
-Confusion Matrix:
- [[ 78   2   0   3   5  17   7]
- [  7 117   3   4   6   2   3]
- [ 30  11 146  55  24  20  43]
- [ 15   5  12 112   3   7  13]
- [  1   6   2   1  55   1   1]
- [  2   3   1   0   3  46   3]
- [ 20   2   8  12   4  23  56]]
-Node Classification on random seed  7186 -> 0.58
-Confusion Matrix:
- [[ 58   0   5   8   1  13  17]
- [  4 116   8   3   8   1  10]
- [ 37  30 118  45  17  36  29]
- [ 10   5  22  98   6   5   9]
- [  1  13   2   0  62   3   2]
- [  6   1   4   7   0  45   4]
- [  5   5  11   9   5  13  83]]
-Node Classification on random seed  7187 -> 0.613
-Confusion Matrix:
- [[ 62   1   3  12   2   3  18]
- [  5 137   4   2   9   4   4]
- [ 29  19 162  20  21  11  45]
- [ 12   5  27  80   8   8   6]
- [  4  12   6   0  63   0   2]
- [  7   2   1   0   2  37  13]
- [ 10   2  16  16   6  10  72]]
-Node Classification on random seed  7188 -> 0.609
-Confusion Matrix:
- [[ 59   2   4   4   4  12  19]
- [  5 123   7   2   5   7   5]
- [ 27  23 122  41  25  23  46]
- [  8   5  19  99   2   8  15]
- [  2   3   3   5  67   0   2]
- [  2   5   2   0   0  58   6]
- [  3   4   6   8   6  16  81]]
-Node Classification on random seed  7189 -> 0.646
-Confusion Matrix:
- [[ 64   3   6   5  11  14   8]
- [  3 141   2   1   4   2   4]
- [ 21  35 152  37  15  30  37]
- [  4   6   8  97   6   3  18]
- [  1   7   4   5  60   2   1]
- [  5   0   0   4   0  55   5]
- [  5   4   4   5   2  17  77]]
-Node Classification on random seed  7190 -> 0.613
-Confusion Matrix:
- [[ 68   1  10  13   4   3   9]
- [  2 127   8   0  10   1   5]
- [ 47  14 148  20  23  12  44]
- [ 12   4  30  90   1   3  14]
- [  2   9   5   3  59   1   2]
- [  4   1   2   1   1  48   7]
- [ 14   4   7   5  13  16  73]]
-Node Classification on random seed  7191 -> 0.617
-Confusion Matrix:
- [[ 67   4   4   5   4  16   4]
- [  3 120   7   1   4   0   6]
- [ 25  49 148  25  12  27  38]
- [  7   5   9 116   4  14   7]
- [  1   5   8   2  51   3   2]
- [  4   2   2   8   3  36   6]
- [  7   3   4  15   5  23  79]]
-Node Classification on random seed  7192 -> 0.606
-Confusion Matrix:
- [[ 70   2   4   1   5  23   2]
- [  3 123   5   0  14   5   5]
- [ 13  37 144  33  27  23  38]
- [  7   7  24 101   2  11  13]
- [  1   3   6   2  53   0   0]
- [  5   0   1   4   5  35   3]
- [  7   5  20   4   7  17  80]]
-Node Classification on random seed  7193 -> 0.615
-Confusion Matrix:
- [[ 80   0   6   4   3   7  16]
- [  2 118   9   4  12   4  11]
- [ 21  19 147  38  19  18  46]
- [  9   1  10 105   3  12  15]
- [  2   9   5   2  54   2   5]
- [ 10   1   3   0   0  35   7]
- [ 15   0  12   7   6  10  76]]
-Node Classification on random seed  7194 -> 0.593
-Confusion Matrix:
- [[ 59   1   5   6   7  10  13]
- [  8 111  15   2   4   3   9]
- [ 23  17 162  30  44  15  22]
- [  4   5  25  95  11   6  19]
- [  1   7   8   0  58   2   2]
- [  4   0   4   1   2  40   5]
- [  6   3  15  13  15  15  68]]
-Node Classification on random seed  7195 -> 0.561
-Confusion Matrix:
- [[ 54   2  10   5   3  32   7]
- [ 13 115   3   4   5  10  10]
- [ 23   9 109  25  47  31  37]
- [ 10   1  14  98   3  16  17]
- [  6   2   3   5  68   2   6]
- [ 10   1  12   0   1  40   4]
- [  8   4   7   8   6  17  77]]
-Node Classification on random seed  7196 -> 0.598
-Confusion Matrix:
- [[ 72   8   1   6   6   6   7]
- [  9 127   7   0   6   2   4]
- [ 35  23 139  37  27  26  33]
- [  6  11  20  87  12  11   8]
- [  1   1   9   0  54   1   4]
- [ 11   2   2   6   1  36   4]
- [ 22   3   9   6   1   8  83]]
-Node Classification on random seed  7197 -> 0.62
-Confusion Matrix:
- [[ 67   0   2  10   3  12   8]
- [  4 127   5   5  10   6   2]
- [ 21  16 152  36  24  22  36]
- [ 15   4  22  88   3  10  11]
- [  0   3   5   2  65   3   2]
- [  8   4   1   2   1  41   4]
- [ 14   0  13   5   8  18  80]]
-Node Classification on random seed  7198 -> 0.631
-Confusion Matrix:
- [[ 86   3   0   7   3  14   2]
- [  3 152   6   2   7   7   4]
- [  8  28 128  20  29  32  45]
- [ 27   3  13  86   4   7   3]
- [  1   8   2   1  66   1   2]
- [  6   2   1   4   3  44   2]
- [ 21   3   5   7   9  14  69]]
-Node Classification on random seed  7199 -> 0.591
-Confusion Matrix:
- [[ 62   1   4   6   5  20   9]
- [  3 129   8   0  12   0   2]
- [ 27  35 122  11  36  25  41]
- [  8   5  22  94   3   5  18]
- [  1   8   2   0  71   0   3]
- [  6   1   3   2   2  44   7]
- [ 21   7   9   3  19   9  69]]
-Node Classification on random seed  7200 -> 0.576
-Confusion Matrix:
- [[ 71   4   5   3   4   4  12]
- [  3 129  10   2   7   0   6]
- [  9  19 116  44  57  14  48]
- [ 12   6  16  82  13   2  21]
- [  3   5   2   1  62   0   3]
- [  4   0   6   2   5  42  10]
- [ 13   3  14  11   9  12  74]]
-Node Classification on random seed  7201 -> 0.61
-Confusion Matrix:
- [[ 78   5   1   3   6   4  10]
- [  2 112   7   5  11   3   5]
- [ 33  33 119  29  32  14  36]
- [ 15   8  13 106   1   2  16]
- [  0   5   3   0  63   1   1]
- [  7   1   4   3   7  42  14]
- [ 15   3   8   3   7  14  90]]
-Node Classification on random seed  7202 -> 0.636
-Confusion Matrix:
- [[ 67   6   1   6   2   9   5]
- [  6 143   2   2   5   3   1]
- [ 26  22 155  27  23  22  32]
- [ 23  11   9 110  11   6   3]
- [  4   5   7   2  60   1   4]
- [  6   3   5   3   0  39   4]
- [ 15   4   7  13   6  12  62]]
-Node Classification on random seed  7203 -> 0.624
-Confusion Matrix:
- [[ 62   3   9  10   5   7  16]
- [  5 123   5   0   7   3   4]
- [ 16  18 136  29  30  18  65]
- [  5   4  17 118   4   4  18]
- [  1   0   1   2  67   0   4]
- [  5   0   5   3   0  51   8]
- [ 13   3   9   3   8   9  67]]
-Node Classification on random seed  7204 -> 0.672
-Confusion Matrix:
- [[ 68   1   7   4   1  13  15]
- [  1 139   4   4   7   2   7]
- [ 16  16 166  36  21  18  27]
- [ 14   2  17 121   0   3  16]
- [  1   6   3   2  59   2   2]
- [  2   4   2   0   0  36  11]
- [  6   6   7   8   2  12  83]]
-Node Classification on random seed  7205 -> 0.599
-Confusion Matrix:
- [[ 61   3  10   3   5  21   4]
- [  6 125   7   1   3   4   5]
- [ 30  19 127  40  24  26  36]
- [ 17   4   7 111   4   1  13]
- [  0   5   7   0  56   2   4]
- [  9   1   2   6   1  37   4]
- [ 12   1  13   8   6  27  82]]
-Node Classification on random seed  7206 -> 0.597
-Confusion Matrix:
- [[ 75   6   1   2   3   9   8]
- [  8 120  15   4  12   3   2]
- [ 29  23 125  44  19  24  34]
- [ 10   5  12  97   3   8  20]
- [  0   4   3   4  52   3   2]
- [  5   0   7   1   0  49  12]
- [ 14   4  10  10   7  13  79]]
-Node Classification on random seed  7207 -> 0.625
-Confusion Matrix:
- [[ 69   3   3   9   6   5  18]
- [  4 121   5   2  11   4   3]
- [ 28  18 157  28  28  11  30]
- [ 11   1  19 103  10   7  14]
- [  2   6   5   1  59   2   3]
- [ 14   0   0   0   1  39   6]
- [ 17   3   9  12   5  11  77]]
-Node Classification on random seed  7208 -> 0.514
-Confusion Matrix:
- [[ 52   3   8   6  11  16   8]
- [  6 117   1   5  18   6   5]
- [ 38  21  86  65  45  21  36]
- [ 15   6  22  91  11   3   8]
- [  0   6   2   0  55   0   3]
- [  9   0   5   2  13  41   3]
- [ 20   2   5   9   5  18  72]]
-Node Classification on random seed  7209 -> 0.578
-Confusion Matrix:
- [[ 73   4   0   3   5  14  10]
- [  5 116   1   2  11   3   5]
- [ 20  31 131  41  35  24  51]
- [ 13   3  17  97   3   7  20]
- [  2   9   2   2  66   0   2]
- [  8   4   4   0   3  34   6]
- [ 14   3   9   3   8  15  61]]
-Node Classification on random seed  7210 -> 0.634
-Confusion Matrix:
- [[ 85   4   2   7   2   7   9]
- [  6 124   3   3   4   2   4]
- [ 22  29 154  26  20  18  46]
- [ 19   4  27  93   3   5   9]
- [  0   5   4   4  68   0   0]
- [  8   0   0   1   0  37   3]
- [ 10   6   5  12  12  15  73]]
-Node Classification on random seed  7211 -> 0.617
-Confusion Matrix:
- [[ 64   5   5   5   6  15   5]
- [  2 148   3   1   9   4   8]
- [ 10  20 140  42  36  19  28]
- [  9   1  25  90  11  12  12]
- [  0   8   5   1  66   2   0]
- [  6   0   1   0   3  49   3]
- [  4   2  21   2   9  23  60]]
-Node Classification on random seed  7212 -> 0.569
-Confusion Matrix:
- [[ 82   5  12   2   5  13   3]
- [  4 117   6   1  14   0   3]
- [ 21  39  89  63  40  19  54]
- [ 11   3  10 104   7   4   8]
- [  0   8   3   1  63   0   1]
- [  7   1   1   2   0  39   8]
- [ 18   2   8   2   9  13  75]]
-Node Classification on random seed  7213 -> 0.61
-Confusion Matrix:
- [[ 79   2   7   1   8   5  11]
- [  4 137  10   1  11   2   4]
- [ 30  23 164  27  30  14  30]
- [ 30   7  12  79   9   7  15]
- [  2   5   3   3  44   1   1]
- [  1   1   2   4   3  38   4]
- [ 12   8  13   8   7  12  69]]
-Node Classification on random seed  7214 -> 0.609
-Confusion Matrix:
- [[ 78   4   5   4   0  25  17]
- [  4 127   2   4   8   4   0]
- [ 29  14 152  34  15  24  37]
- [  8   6  11  98  14   8  11]
- [  2   9   3   4  55   5   2]
- [  4   0   3   4   0  35   7]
- [ 14   4   4   7  10  21  64]]
-Node Classification on random seed  7215 -> 0.62
-Confusion Matrix:
- [[ 65   4   5   8   1  18   3]
- [  1 119  12   1   7  13   0]
- [  9  14 130  45  30  45  45]
- [ 12   2  11 118   0   8  12]
- [  0   8   0   2  55   3   2]
- [  8   0   2   0   1  53  10]
- [  7   3   5   6   5  12  80]]
-Node Classification on random seed  7216 -> 0.6
-Confusion Matrix:
- [[ 72   2   2   2   2  10  12]
- [  7 121   7   3   8   1   7]
- [ 28  17 134  58  23  24  32]
- [ 11   4  25  93   8   7  15]
- [  1   6   1   2  55   0   2]
- [  7   2   1   3   3  57   2]
- [ 12   4  10  12   4  13  68]]
-Node Classification on random seed  7217 -> 0.636
-Confusion Matrix:
- [[ 75   4   6   7   1  10  14]
- [  9 139   4   0   6   2   3]
- [ 12  26 145  32  17  21  43]
- [ 15   7  17 100   3   7   4]
- [  2   6   8   1  58   1   2]
- [  5   0   0   2   3  47   8]
- [  7   3  19   7   3  17  72]]
-Node Classification on random seed  7218 -> 0.62
-Confusion Matrix:
- [[ 66   1   4   7   6  11  13]
- [  7 133  12   3  14   6   5]
- [ 18  25 149  48  17  22  38]
- [ 14   4  11 109   7   9  11]
- [  3   3   4   1  49   1   2]
- [  3   0   1   4   0  39   3]
- [ 15   2  11   4   4   6  75]]
-Node Classification on random seed  7219 -> 0.62
-Confusion Matrix:
- [[ 69   2   5   9   3   4   5]
- [  5 131   6   3   2   0   5]
- [ 20  33 145  19  33  14  44]
- [ 13   3  32  97   2   2  14]
- [  2   9   4   3  53   1   2]
- [  8   0   2   6   0  47   4]
- [ 14   4   5  10   6  22  78]]
-Node Classification on random seed  7220 -> 0.616
-Confusion Matrix:
- [[ 60   1   1   4   5  10  16]
- [  6 117  12   3   8   1  11]
- [ 26  14 122  34  32  14  53]
- [ 12   4   8 111   7   6  15]
- [  1   6   2   0  61   2   3]
- [  9   0   2   0   8  41   9]
- [ 10   4   4   4   6  11 104]]
-Node Classification on random seed  7221 -> 0.596
-Confusion Matrix:
- [[ 84   1   8   4   4   8  12]
- [  0 121  14  10   2   6   1]
- [ 21  25 136  24  18  33  32]
- [ 10   2  21  93  25   5  16]
- [  0   5   5   2  51   0   3]
- [  8   2   2   0   1  41   4]
- [ 11   2   8   8  15  26  70]]
-Node Classification on random seed  7222 -> 0.639
-Confusion Matrix:
- [[ 65   1   2   5   4  22   9]
- [  3 131   5   2  10   7   7]
- [ 25   9 164  36  21  25  43]
- [ 11   4  17 107   7  10   8]
- [  1   2   4   0  61   1   1]
- [  4   2   8   0   0  39   6]
- [  9   2   9   2   7  10  72]]
-Node Classification on random seed  7223 -> 0.59
-Confusion Matrix:
- [[ 74   3   9   6   4   8  13]
- [  5 135   3   2   4   1   3]
- [ 24  28 121  38  18  29  49]
- [ 19   7  18  93   2   4  18]
- [  0   6   8   1  45   1   2]
- [  6   2   7   2   0  45   3]
- [ 17   6   5   7  11  11  77]]
-Node Classification on random seed  7224 -> 0.612
-Confusion Matrix:
- [[ 67   3  10   3   7  14   6]
- [  3 123   3   2  22   6   0]
- [ 24  28 146  27  41  23  25]
- [  8   3  12 109  15   6  12]
- [  1   0   7   0  57   1   1]
- [  4   2   2   2   1  39   5]
- [ 10   5  11   2  12  19  71]]
-Node Classification on random seed  7225 -> 0.625
-Confusion Matrix:
- [[ 95   2   6   4   3   8   4]
- [  7 123   2   2   4   1   3]
- [ 25  21 137  43  38  14  36]
- [ 13   2  16 100  13   4  10]
- [  2   9   4   0  62   0   0]
- [  4   2   2   1   5  44   2]
- [ 13   8  15   4   8  15  64]]
-Node Classification on random seed  7226 -> 0.608
-Confusion Matrix:
- [[ 80   1   1   9   1  15   7]
- [  9 125   2   3   8   2  12]
- [ 19  20 129  39  40  22  40]
- [  8   2  29 104   2  12  14]
- [  1   4   2   1  62   2   4]
- [  2   2   2   1   0  54   3]
- [  3   2   1  11  13  21  54]]
-Node Classification on random seed  7227 -> 0.602
-Confusion Matrix:
- [[ 58   4   1   2   3  20  19]
- [  6 136   5   1   7   1   0]
- [ 27  29 122  32  23  42  34]
- [ 11   7  12 100   7  12   9]
- [  3   6   3   1  54   0   1]
- [  6   1   4   2   0  49   2]
- [  3   5  11   3   8  25  83]]
-Node Classification on random seed  7228 -> 0.613
-Confusion Matrix:
- [[ 67   2   5  13   5  13   5]
- [  4 113  16   2   5   3   0]
- [ 19  14 147  51  28  23  45]
- [ 16   7   8 109   8   3  13]
- [  1   2   3   1  50   1   2]
- [  4   3   0   3   0  60   7]
- [  8   3   3  11  11  16  67]]
-Node Classification on random seed  7229 -> 0.598
-Confusion Matrix:
- [[ 86   3   2   3   8   5   5]
- [  6 136   5   4   7   0   2]
- [ 32  14 102  30  50  10  54]
- [ 23   4  11 111   4  10  12]
- [  3   6   2   3  59   1   3]
- [ 10   4   1   1   6  42   3]
- [ 16   1  12   9   5  12  62]]
-Node Classification on random seed  7230 -> 0.604
-Confusion Matrix:
- [[ 75   2   9  16   2   8   7]
- [  4 108   5   5  11   3   3]
- [ 14  19 142  53  20  23  50]
- [ 13   7  11 102   6   3   9]
- [  0   4   3   2  62   2   3]
- [  4   2   6   2   3  42   5]
- [  9   5   4  19   6  14  73]]
-Node Classification on random seed  7231 -> 0.604
-Confusion Matrix:
- [[ 61   1   4   3   6  18  11]
- [  3 109   1   3  25   1  10]
- [ 17  17 141  26  38  34  41]
- [  8   6  27  94   8   8  16]
- [  1   2   3   3  58   0   2]
- [  2   0   2   0   0  51   5]
- [  6   3   9   8   9   9  90]]
-Node Classification on random seed  7232 -> 0.634
-Confusion Matrix:
- [[ 68   2   6  10   3   9  17]
- [  2 131   4   3  11   3   9]
- [ 16   9 147  53  22  18  43]
- [  9  10   8 100   8   7   8]
- [  1   1   4   2  58   1   3]
- [  2   0   1   5   0  44   4]
- [  8   5   7   8   5  19  86]]
-Node Classification on random seed  7233 -> 0.608
-Confusion Matrix:
- [[ 57   6   9   0   1  12  14]
- [  9 133   1   0  12   6   1]
- [ 31  29 140  33  29  24  32]
- [ 17   6  16 105   1   5  13]
- [  3   2   4   0  55   2   4]
- [  4   3   0   3   8  31   8]
- [ 12   1  10   5   6  10  87]]
-Node Classification on random seed  7234 -> 0.581
-Confusion Matrix:
- [[ 73   3   7   6   5   9  13]
- [  4 104   3   3  17   4   7]
- [ 26  22 134  31  44  24  43]
- [  8   6  27  87   2   4  18]
- [  0   4   8   0  57   2   0]
- [  4   0   3   2   1  46   8]
- [  9   5  12   9   7   9  80]]
-Node Classification on random seed  7235 -> 0.617
-Confusion Matrix:
- [[ 59   2   8   7   5  14  13]
- [  4 110  10   1   6   5   5]
- [ 33  20 152  28  14  32  38]
- [ 12   3  14 109   2   6  16]
- [  2   5   4   7  54   3   3]
- [  8   0   2   2   0  48   6]
- [  9   3  14   6   6   5  85]]
-Node Classification on random seed  7236 -> 0.562
-Confusion Matrix:
- [[ 55   4   8   0   3  19  22]
- [  7 124   4   4   4   2   2]
- [ 24  20 127  49  40  17  39]
- [ 26   6   6  89   8   8  12]
- [  0   5   2   0  60   2   6]
- [  2   1   6   1   0  46   5]
- [ 11   4  22   9   8  20  61]]
-Node Classification on random seed  7237 -> 0.611
-Confusion Matrix:
- [[ 76   2   4   4   2   6   4]
- [  5 135   9   1   4   2   1]
- [ 18  37 117  49  32  20  34]
- [ 19   8  19 108   9   1  12]
- [  4   9   5   0  57   0   7]
- [  7   3   1   1   1  38   8]
- [ 14   3   8   1   8   7  80]]
-Node Classification on random seed  7238 -> 0.598
-Confusion Matrix:
- [[ 87   2   5   3   3   6  15]
- [  5 106  10   1   9   4   1]
- [ 28  45 134  28  12  22  41]
- [ 13   4  24  94   3   1  17]
- [  1   5   9   4  55   1   1]
- [  9   2   3   0   0  41   3]
- [ 21   3  17   5   7   9  81]]
-Node Classification on random seed  7239 -> 0.581
-Confusion Matrix:
- [[ 76   4   2   1  10   5   6]
- [  5 128   8   0   9   2   3]
- [ 24  13 125  46  28  25  63]
- [ 24   7  24  76   3   8  15]
- [  1   2   1   2  58   3   2]
- [  8   1   1   2   0  47   3]
- [ 23   7   6   7   5  10  71]]
-Node Classification on random seed  7240 -> 0.636
-Confusion Matrix:
- [[ 63   1  12   2   3  12   6]
- [  6 139   4   4   4   0   4]
- [ 24  36 134  28  28  13  41]
- [  8   1  12 110   7   5  19]
- [  0  13   2   2  62   0   2]
- [  2   3   9   2   0  45   6]
- [  5   4  21   0   3  10  83]]
-Node Classification on random seed  7241 -> 0.66
-Confusion Matrix:
- [[ 61   1   7   6   2   7  15]
- [  5 139   1   0   5   2   5]
- [ 28  13 158  18  42  17  28]
- [ 11   2  13 117   5   9  11]
- [  1   7   6   1  57   1   1]
- [  5   2   3   0   3  49   5]
- [  7   4  12   4   7  18  79]]
-Node Classification on random seed  7242 -> 0.641
-Confusion Matrix:
- [[ 60   7   1   8   2  10   8]
- [ 12 114   7   5   8   3   2]
- [ 21  16 187   9  26  24  47]
- [  5   5  14 107   8   9  13]
- [  4   1   2   1  56   0   7]
- [  5   1   1   0   3  36  10]
- [ 16   3  10   6  11   8  81]]
-Node Classification on random seed  7243 -> 0.613
-Confusion Matrix:
- [[ 56   4  13   2   4  16  18]
- [  1 120   5   4   7   2   4]
- [ 12  23 152  46  15  36  31]
- [  3   2  22  98   4   3  18]
- [  1   4   5   1  65   0   6]
- [  6   7   1   0   1  41   8]
- [  5   6  15   6   5  15  81]]
-Node Classification on random seed  7244 -> 0.577
-Confusion Matrix:
- [[ 58   0  12  17   1  12   2]
- [  1 115   7   4  16   6   4]
- [ 25  10 135  46  38  35  43]
- [  9   2  24  86   6   6  18]
- [  1   4   4   0  60   0   5]
- [  3   3   2   5   1  48   6]
- [  7   6   6  11   6   9  75]]
-Node Classification on random seed  7245 -> 0.618
-Confusion Matrix:
- [[ 68   2   5   6   7   8  18]
- [  7 132   7   1   4   1   2]
- [ 24  21 131  29  37  16  47]
- [ 14   4  14 104   9   5  12]
- [  3   7   0   1  65   0   1]
- [  5   2   1   3   0  40   4]
- [ 13   8  14   7   2  11  78]]
-Node Classification on random seed  7246 -> 0.626
-Confusion Matrix:
- [[ 57   5  14   8   3   9  12]
- [  2 130  11   2  10   2   2]
- [ 23  22 136  45  20  18  46]
- [  3   5  19 101   6   3  11]
- [  0   2   6   0  64   0   2]
- [ 13   0   0   0   2  52   5]
- [ 15   2   6   7   5   8  86]]
-Node Classification on random seed  7247 -> 0.657
-Confusion Matrix:
- [[ 59   2   3   2   2  10  17]
- [  5 126   9   7   2   5   2]
- [ 21  10 192  44  17   9  45]
- [  4   2  11 105   6   9   8]
- [  3   9   3   3  53   0   3]
- [  2   1   6   2   0  41  11]
- [  9   3  14  10  10   2  81]]
-Node Classification on random seed  7248 -> 0.583
-Confusion Matrix:
- [[ 44   4  15  10   7  13  17]
- [  3 116   9   2   8   8   6]
- [ 36  10 140  44  23  32  23]
- [  5   3  13 110   7   6  20]
- [  2   6   4   1  62   1   3]
- [  5   1   6   0   1  50   2]
- [ 19   2  18   2   4  16  61]]
-Node Classification on random seed  7249 -> 0.617
-Confusion Matrix:
- [[ 76   0   2   2   7  11   5]
- [  3 142   3   1  16   0   3]
- [ 15  23 136  66  31  20  21]
- [ 10   5  28  85  18   5   4]
- [  1   3   2   1  60   0   5]
- [  2   0   1   4   1  56   4]
- [ 10   4   8  15   9  14  62]]
-Node Classification on random seed  7250 -> 0.575
-Confusion Matrix:
- [[ 59   3  12   3   3  23   7]
- [  7 141   4   4   6   2   4]
- [ 21  19 114  47  41  22  48]
- [  8   8  16  85   7   5  12]
- [  2   7   4   1  64   0   5]
- [  1   0   1   1   0  48  10]
- [  6   4   8   9  15  19  64]]
-Node Classification on random seed  7251 -> 0.609
-Confusion Matrix:
- [[ 67   0   6   5   2  16   6]
- [ 13 115  12   3  17   3   1]
- [ 21  21 139  65  17  18  25]
- [ 10   5  11  89   3  10  18]
- [  1   6   2   5  66   0   3]
- [  4   1   6   0   0  44   6]
- [  6   3  12   8   5  15  89]]
-Node Classification on random seed  7252 -> 0.621
-Confusion Matrix:
- [[ 73   8   8   3  11  11   6]
- [  3 117   1   7   9   0   5]
- [ 12  21 147  42  21  16  51]
- [ 16   6  11  86  11   7  20]
- [  1   6   5   0  60   0   3]
- [ 11   0   0   1   2  50   4]
- [ 12   2   7   4   8   7  88]]
-Node Classification on random seed  7253 -> 0.604
-Confusion Matrix:
- [[ 63   8   8   1   7  10   8]
- [  6 119   6   2   9   1   5]
- [ 13  32 126  39  30  17  59]
- [  8   7   8 109   8   3  21]
- [  1   6   1   2  62   0   6]
- [  5   2   1   0   0  46  12]
- [ 12   3   2   7   7  13  79]]
-Node Classification on random seed  7254 -> 0.622
-Confusion Matrix:
- [[ 69   7   3   3   4   9  10]
- [  2 131   5   5   7   0   2]
- [ 19  18 131  33  51  15  32]
- [ 16   4  23  98   8   8  17]
- [  2   6   0   2  66   1   2]
- [  1   5   5   1   0  47   6]
- [ 18   6   2   3   7  10  80]]
-Node Classification on random seed  7255 -> 0.594
-Confusion Matrix:
- [[ 67   1   0  11   2  10  16]
- [  3 116  12   5   6   5   3]
- [ 29  17 125  24  30  34  44]
- [  9   5  13  97   6   5  21]
- [  1   4   2   2  60   4   4]
- [  9   0   2   1   0  49  12]
- [ 15   1   7   5   9  17  80]]
-Node Classification on random seed  7256 -> 0.58
-Confusion Matrix:
- [[ 59   1  12  10   6   5  11]
- [  6 128   7   4  16   4   4]
- [ 43  31 120  23  32  19  41]
- [ 20   1  22  95   4   5   9]
- [  3   6   2   1  50   0   3]
- [  8   1   0   0   0  43   6]
- [ 16   4   6  12   6  10  85]]
-Node Classification on random seed  7257 -> 0.614
-Confusion Matrix:
- [[ 78   4  13   3   1  13  13]
- [  7 119   9   4  10   1   0]
- [ 26  27 151  30  18  17  37]
- [  7   2  15 104   3   5  10]
- [  5   5   8   0  51   2   1]
- [  2   3   4   3   0  46   3]
- [ 21   8  19   5   8  14  65]]
-Node Classification on random seed  7258 -> 0.607
-Confusion Matrix:
- [[ 75   1   4  11   6  17   7]
- [  1 143  12   2   3   3   0]
- [ 20  24 111  59  22  10  53]
- [  4   3  25  97   0   1  14]
- [  5  10   2   1  62   1   0]
- [  4   3   1   8   5  44   2]
- [ 10   4   8  10   4  13  75]]
-Node Classification on random seed  7259 -> 0.611
-Confusion Matrix:
- [[ 61   0  10   9   5  10   8]
- [  3 107  13   2  21   2   4]
- [ 18  18 141  33  51  14  37]
- [  5   3  11 121   3   4  16]
- [  0   3   4   2  66   1   6]
- [  5   2   2   0   1  44   8]
- [ 11   3  12  12   6  11  71]]
-Node Classification on random seed  7260 -> 0.614
-Confusion Matrix:
- [[ 72   0   6   4   5   3  20]
- [  4 135   4   0   7   3   3]
- [ 22  27 126  31  26  22  44]
- [  8   5  19 107   4   4   9]
- [  0  12   4   0  62   3   3]
- [  5   1  10   2   0  36   8]
- [ 12   2  14  11   8  11  76]]
-Node Classification on random seed  7261 -> 0.631
-Confusion Matrix:
- [[ 80   7   2   4   4  12   5]
- [  6 119   9   3  14   0   5]
- [ 34  26 144  30  23   8  35]
- [ 10   4  16 108   5   8  24]
- [  1   5   2   0  61   1   2]
- [  5   1   2   0   0  45   6]
- [  9   7   3   9   5  17  74]]
-Node Classification on random seed  7262 -> 0.634
-Confusion Matrix:
- [[ 73   1   5  10   9  10   4]
- [  1 124   5   1   8   3   3]
- [ 16  23 153  26  30  25  33]
- [ 15   2  20  95   4   8  17]
- [  2   6   3   1  64   4   2]
- [  6   1   0   6   1  46   1]
- [ 15   6   7   2   4  20  79]]
-Node Classification on random seed  7263 -> 0.642
-Confusion Matrix:
- [[ 76   1   8  12   2  10  10]
- [  0 134   3   2   3   1   5]
- [ 16  18 141  27  47  21  32]
- [ 17   1  23  93  16   3   5]
- [  1   1   5   3  67   0   4]
- [  2   1   0   3   6  43   5]
- [  3   5  13   8   7   8  88]]
-Node Classification on random seed  7264 -> 0.586
-Confusion Matrix:
- [[ 63   0   1   4  11  10  10]
- [  2 156   6   2  11   2   1]
- [ 24  33  98  41  31  27  65]
- [ 10   4  16 101   3   7  14]
- [  0   4   3   2  63   1   3]
- [  5   2   2   2   4  46   5]
- [  7   4   7   3  10  15  59]]
-Node Classification on random seed  7265 -> 0.643
-Confusion Matrix:
- [[ 70   5   8   4   3  12   5]
- [  5 132   8   4   8   3   4]
- [ 26  13 148  21  13  29  40]
- [  4   5  24 102   7   5  10]
- [  2   6   2   4  61   0   2]
- [  4   1   0   0   0  47  12]
- [ 18   2  16   5   4  13  83]]
-Node Classification on random seed  7266 -> 0.649
-Confusion Matrix:
- [[ 72   6   2   6   0  14   9]
- [  2 127   2   2   4   4   3]
- [ 27  24 136  39  38  18  33]
- [  4   7   9 118   4   1  19]
- [  1   4   3   1  70   0   1]
- [  3   3   0   2   1  41   6]
- [ 12   4   3  11   6  13  85]]
-Node Classification on random seed  7267 -> 0.593
-Confusion Matrix:
- [[ 66  12   4   2  10  16  13]
- [  9 114  11   3   3   0   6]
- [ 26  31 147  34  18  13  48]
- [  8   5   9  88  19   1  16]
- [  2  10   3   1  50   1   2]
- [  4   3   0   0   0  47   7]
- [ 17   7  10  10  10   3  81]]
-Node Classification on random seed  7268 -> 0.63
-Confusion Matrix:
- [[ 76   4   2   9   5   8   7]
- [  3 139   2   7   1   5   1]
- [ 34  31 132  50  20  16  55]
- [  7   3   5 121   2   2  13]
- [  0   4  10   1  53   0   3]
- [  4   4   1   1   0  37  10]
- [  5   2  12  12   5   4  72]]
-Node Classification on random seed  7269 -> 0.632
-Confusion Matrix:
- [[ 70   0   1   8   2   7  12]
- [  1 123   6   3   8   2   9]
- [ 21  22 131  31  33  19  43]
- [ 13   1  19 119   2   6  11]
- [  2   7   5   0  53   0   1]
- [  5   2   5   2   0  49   7]
- [ 17   5  10   3   2  15  87]]
-Node Classification on random seed  7270 -> 0.646
-Confusion Matrix:
- [[ 72   3   7  10   3   9  11]
- [  6 129   8   2   8   1   2]
- [ 19  19 179  28  15  10  42]
- [  9  11  10  91   3   4  18]
- [  4   9   3   0  54   0   2]
- [  3   0   4   4   1  47   3]
- [ 18   4  16   9   6  10  74]]
-Node Classification on random seed  7271 -> 0.607
-Confusion Matrix:
- [[ 75   2   2   5   4  11  11]
- [  4 134   6   2   7   3   9]
- [ 38  24 149  19  32  40  30]
- [ 18   4   8  87   7   8  14]
- [  1   7   1   2  62   0   3]
- [  4   3   0   2   0  38   7]
- [ 13   3  13   7   6  13  62]]
-Node Classification on random seed  7272 -> 0.618
-Confusion Matrix:
- [[ 68   3   4   5   3  16   5]
- [  6 120   7   3   0   5   3]
- [ 29  31 157  27  22  26  32]
- [  6   5  14 104   9   6  19]
- [  0   9   3   1  53   2   4]
- [  5   1   5   1   0  54   7]
- [  5   3  26   3   8  13  62]]
-Node Classification on random seed  7273 -> 0.614
-Confusion Matrix:
- [[ 57   6   5   5   1  11   6]
- [  1 140   5   2   2   2   1]
- [ 34  24 138  37  40  16  32]
- [  9   6  20 113  10   3  10]
- [  2   4   3   3  51   1   5]
- [  5   1  15   1   0  33   3]
- [ 17   3  11  14   5   5  82]]
-Node Classification on random seed  7274 -> 0.631
-Confusion Matrix:
- [[ 76   5   3   4   2  15  10]
- [  4 125  10   8  10   1   3]
- [ 24  13 142  23  30  25  53]
- [  5   4  15 122   6   9   4]
- [  4   2   6   0  51   0   2]
- [  6   1   2   1   2  40   8]
- [ 11   3   3   8   9  15  75]]
-Node Classification on random seed  7275 -> 0.602
-Confusion Matrix:
- [[ 64   7  10   5   1  12   9]
- [  4 119   3   0   8   2   1]
- [ 22  18 154  25  29  30  31]
- [ 14   4  20  83   6  15  20]
- [  1   9   1   5  54   0   4]
- [ 10   1   5   0   1  41   4]
- [ 13   7  14   7   4  16  87]]
-Node Classification on random seed  7276 -> 0.632
-Confusion Matrix:
- [[ 62   3   3   8   0  17  14]
- [  5 126   6   2  10   1   3]
- [ 42   7 146  46  10  21  36]
- [  9   0  15 112   3   7  18]
- [  2   7   3   1  58   1   3]
- [  5   2   2   0   2  49   6]
- [ 12   4  10   6   5  11  79]]
-Node Classification on random seed  7277 -> 0.63
-Confusion Matrix:
- [[ 75   4   6   3   0   4  16]
- [  3 133   5   2   5   3   7]
- [ 19  24 131  28  33   9  41]
- [  9   4  20 113   5   7  14]
- [  1   7   7   2  60   0   3]
- [  8   3   2   2   1  40  11]
- [  8   5   8   7   7  17  78]]
-Node Classification on random seed  7278 -> 0.65
-Confusion Matrix:
- [[ 70   3   1   6   3  10   4]
- [  2 136   3   2  20   1   4]
- [ 25   8 167  25  31  20  52]
- [  8   9  10  87   2   5  13]
- [  2   1   1   2  62   1   4]
- [ 14   0   5   0   4  40   5]
- [ 10   1   9  10   3  11  88]]
-Node Classification on random seed  7279 -> 0.605
-Confusion Matrix:
- [[ 76   8   5   8   0   4  14]
- [  3 130   3   1   6   5   6]
- [ 38  17 137  49  25  16  35]
- [ 11   5  11 101   3   6  11]
- [  5  10   3   3  55   3   6]
- [  5   0   1   4   0  44   7]
- [ 21   2   8  14   0  13  62]]
-Node Classification on random seed  7280 -> 0.63
-Confusion Matrix:
- [[ 53   4   0   5   4   9  27]
- [  4 129  13   2   5   2   3]
- [ 23  20 136  19  33  15  43]
- [ 17   3  21 109   6   5   7]
- [  0   6   5   4  57   2   2]
- [  5   1   1   1   1  50   8]
- [  9   3  10   8   3  11  96]]
-Node Classification on random seed  7281 -> 0.636
-Confusion Matrix:
- [[ 67   4   1   1   3  23  11]
- [  2 121   6   1   2   3   8]
- [ 26  15 152  51  12  26  30]
- [  9   4  14 124   1   6  17]
- [  0   6   6   5  60   3   2]
- [  6   1   0   1   0  44   3]
- [ 12   5  10   8   5  15  68]]
-Node Classification on random seed  7282 -> 0.607
-Confusion Matrix:
- [[ 62   7   3   7   3   3  19]
- [  3 131   6   5   9   6   3]
- [ 15  36 144  33  31  12  36]
- [  4   4  18 100   2  13  15]
- [  0   5   2   2  51   3   1]
- [  2   1   3   2   6  48   9]
- [ 15   5   8   7  11  18  71]]
-Node Classification on random seed  7283 -> 0.646
-Confusion Matrix:
- [[ 65   2   0   3   5  13  17]
- [  7 119   4   1   8   2   3]
- [ 21  13 175  22  18  22  34]
- [  5   3  13 108  12  11  10]
- [  0   2   2   0  58   0   4]
- [  4   0   6   2   2  55   9]
- [  5   4  10  17   7  31  66]]
-Node Classification on random seed  7284 -> 0.631
-Confusion Matrix:
- [[ 87   1   0   7   4   9   1]
- [  2 140   4   4   3   1   9]
- [ 20  20 133  46  21  17  49]
- [  6  14  15 100   6   2   8]
- [  2   9   4   2  54   1   8]
- [  6   4   3   3   2  39   7]
- [ 11   3  13   9   3  10  78]]
-Node Classification on random seed  7285 -> 0.574
-Confusion Matrix:
- [[ 74   9   1   3   3  10   1]
- [  7 127   7   2   4   3   5]
- [ 37  29 112  47  34  25  29]
- [ 10  10  11  98   5   6  10]
- [  5  10   8   4  48   1   6]
- [ 13   4   1   1   0  41   8]
- [ 22   9   0   9   7  10  74]]
-Node Classification on random seed  7286 -> 0.591
-Confusion Matrix:
- [[ 59   8   2   3   2   9  19]
- [  6 132   5   1  12   1   3]
- [ 23  27 121  52  22  19  39]
- [ 11   4  12  92   7  13  19]
- [  1   4   8   2  71   0   1]
- [ 15   1   1   1   2  43   5]
- [ 19   0   8   0   8  14  73]]
-Node Classification on random seed  7287 -> 0.625
-Confusion Matrix:
- [[ 58   5   7   7   5  10   7]
- [  7 126   4   3  13   0   2]
- [ 21  20 139  33  21  26  35]
- [ 15   4  26 107   4   5   8]
- [  1   5   3   2  63   2   0]
- [  6   2   3   0   0  50   2]
- [  7   5  13   6   7  23  82]]
-Node Classification on random seed  7288 -> 0.619
-Confusion Matrix:
- [[ 69   4   7  10   5   8  14]
- [  5 136   2   2  14   2   5]
- [ 26   9 133  26  60  22  25]
- [ 18   3  12  96  11   3   8]
- [  5   3   2   2  51   0   2]
- [  5   4   3   4   1  50   5]
- [ 15   3   6   9   5   6  84]]
-Node Classification on random seed  7289 -> 0.623
-Confusion Matrix:
- [[ 62   2   1   4   4  17  11]
- [  7 122   4   2   6   0   9]
- [ 27  18 141  31  25  19  46]
- [  4   2  24 113   3   7  16]
- [  3   7   3   3  56   0   4]
- [  8   1   2   0   1  45   3]
- [ 16   3   9   3   7  15  84]]
-Node Classification on random seed  7290 -> 0.637
-Confusion Matrix:
- [[ 73   3   5   7   1  18  13]
- [  3 146   5   5   5   1   0]
- [ 23  11 134  39  18  33  40]
- [  9   5   8 123   3   2   4]
- [  4   7   7   1  50   0   1]
- [ 10   3   2   1   0  39   4]
- [ 12   1   7   7  15  20  72]]
-Node Classification on random seed  7291 -> 0.596
-Confusion Matrix:
- [[ 73   1   4  13   5   9   9]
- [  6 116   5   6   6   6   6]
- [ 31  15 152  41  27  25  42]
- [  6   3  28  93   1  11  10]
- [  0   7   2   2  50   2   2]
- [ 11   0   4   2   0  36   3]
- [ 18   2  11   5   9   8  76]]
-Node Classification on random seed  7292 -> 0.654
-Confusion Matrix:
- [[ 70   4   4   0   5  14   7]
- [  2 143   4   2   6   4   4]
- [ 22  17 151  36  11  33  34]
- [  5   5   3 113   4   7  24]
- [  0   8   5   1  55   1   1]
- [  7   0   0   0   1  51   8]
- [ 13   2  11   3   7  21  71]]
-Node Classification on random seed  7293 -> 0.645
-Confusion Matrix:
- [[ 81   3   0   4   4   9   5]
- [  9 117   7   0  11   4   2]
- [ 18  17 167  34  24  14  36]
- [  8   1  22 102   6   2  14]
- [  0   6   6   0  53   2   3]
- [ 12   2   5   1   2  33   6]
- [ 10   0  14   3  10  19  92]]
-Node Classification on random seed  7294 -> 0.58
-Confusion Matrix:
- [[ 65   7   7   6   2  12  13]
- [  5 129   6   5   4   7   0]
- [ 24  28 133  58  22  21  28]
- [ 14   2  28  93   4   3  18]
- [  2   3   2   4  56   0   1]
- [  1   1   1   4   2  37   9]
- [ 10   9  10  16   3  18  67]]
-Node Classification on random seed  7295 -> 0.614
-Confusion Matrix:
- [[ 72   6   7   6   2  10  15]
- [  3 132   9   0   8   2   1]
- [ 26  20 129  33  33  24  33]
- [  8   2  10 108   3  15   8]
- [  3   8   2   2  64   0   1]
- [ 11   1   0   3   0  50   6]
- [ 20   2  20   6   4  13  59]]
-Node Classification on random seed  7296 -> 0.593
-Confusion Matrix:
- [[ 65   7   4   8   3  14  18]
- [  7 116   3   1   7   2   4]
- [ 22  28 156  36  16  18  41]
- [ 29   7   7  87   1   7  18]
- [  2   7   6   1  62   0   8]
- [  8   2   1   1   1  33   2]
- [ 15   6  10   6   9  14  74]]
-Node Classification on random seed  7297 -> 0.593
-Confusion Matrix:
- [[ 76   1   7   2   4  12  18]
- [  3 125   3   0  10   1   7]
- [ 21  33 107  43  37  24  58]
- [  4   2  11 104   1   9   3]
- [  0  10   5   1  53   0   4]
- [  5   2   3   0   1  36   8]
- [  6   2  14   2   7  23  92]]
-Node Classification on random seed  7298 -> 0.618
-Confusion Matrix:
- [[ 75   4   3   1   4   8   4]
- [  2 133   2   4   4   0   4]
- [ 17  15 148  56  34  19  38]
- [ 13   3  27  86   8   7   7]
- [  2   6   6   4  57   0   1]
- [  3   2   2   6   2  56   3]
- [ 10   9   9  12   4  17  63]]
-Node Classification on random seed  7299 -> 0.599
-Confusion Matrix:
- [[ 71   5   4   8   5  15   9]
- [  3 123   7   4   9   5   5]
- [ 16  24 124  46  25  15  44]
- [ 10   4  20  98   9   2  11]
- [  1   8   2   0  66   1   3]
- [  6   1   1   2   2  51   7]
- [  8   2   5  10   9  28  66]]
-Node Classification on random seed  7300 -> 0.622
-Confusion Matrix:
- [[ 62   0   2   5   5   9  16]
- [  2 131   6   5   5   3   4]
- [ 30  13 150  22  37  11  48]
- [ 13   4  21  94  16   4  11]
- [  3  10   1   0  61   2   1]
- [  6   3   2   0   2  41   4]
- [ 13   1  10   6  11  11  83]]
-Node Classification on random seed  7301 -> 0.597
-Confusion Matrix:
- [[ 90   6   6   4   1  14  10]
- [  8 121   2   6   5   3   1]
- [ 32  26  99  54  30  19  28]
- [  7   2   6  99  12   2  16]
- [  3  11   4   1  60   1   3]
- [  3   0   6   1   1  51   1]
- [ 14   8  15   7  11  13  77]]
-Node Classification on random seed  7302 -> 0.597
-Confusion Matrix:
- [[ 68   3   3   5   7   5  18]
- [  6 129   7   0   8   3   6]
- [ 26   9 121  39  14  23  63]
- [ 24   5  13  95   6   6  13]
- [  3   4   4   1  64   2   2]
- [  9   3   0   1   2  48   2]
- [ 16   4  12   9   6  11  72]]
-Node Classification on random seed  7303 -> 0.627
-Confusion Matrix:
- [[ 63   3   3  11   9   2   9]
- [  2 124   6   3   4   2   1]
- [ 41  28 156  32  26  14  27]
- [ 13   2  14 113  10   2  18]
- [  1   7   4   2  66   0   3]
- [  6   1   4   4   1  35   2]
- [ 18   3  15   2  11   7  70]]
-Node Classification on random seed  7304 -> 0.603
-Confusion Matrix:
- [[ 57   0   7   8   8  14   8]
- [  4 132   3   2   5   2  11]
- [ 26  17 133  29  33  28  36]
- [  6   5  20 105   4  12  18]
- [  3   8   4   2  53   2   1]
- [  6   1   0   3   1  49   5]
- [ 15   1   4  14   8  13  74]]
-Node Classification on random seed  7305 -> 0.612
-Confusion Matrix:
- [[ 75   4  10   4   2  10   6]
- [  2 112   8   2  24   5   7]
- [ 33  18 169  41  21   6  26]
- [ 15   4  22  87   1   7  11]
- [  3   2   4   2  67   1   3]
- [  5   1   1   4   0  47   3]
- [ 18   5   8   1  28  10  55]]
-Node Classification on random seed  7306 -> 0.612
-Confusion Matrix:
- [[ 71   1   5   6   2   8  19]
- [  5 115   2   5   7   1  14]
- [ 20  20 133  30  26  20  56]
- [ 19   6  11 111   0   5  18]
- [  0  12   5   1  60   0   1]
- [  3   0   3   2   0  47   2]
- [ 14   4  12   4  10   9  75]]
-Node Classification on random seed  7307 -> 0.596
-Confusion Matrix:
- [[ 65   0   1   3   7   7  26]
- [  8 132  11   4   7   2   3]
- [ 25  22 129  38  32  28  43]
- [ 17   7   8  88   8   3  15]
- [  1   7   2   2  61   0   2]
- [  8   2   1   2   2  42   5]
- [ 17   5   3   6   6   8  79]]
-Node Classification on random seed  7308 -> 0.623
-Confusion Matrix:
- [[ 80   4   0   7   1   9   4]
- [  3 132  14   0   5   3   1]
- [ 37  24 142  33  21  22  26]
- [ 11   7  15 102   6   3  11]
- [  2  10   7   5  56   0   2]
- [  7   2   3   0   0  45   6]
- [ 25   4  15   2   8  12  66]]
-Node Classification on random seed  7309 -> 0.569
-Confusion Matrix:
- [[ 73   2   3   2   3  10  26]
- [  3 121   2  11  11   2   6]
- [ 33  37 112  22  41  23  40]
- [ 10   5  15  80  11   5  24]
- [  3   2   6   2  59   0   1]
- [  2   2   3   1   2  41  13]
- [  6   4   6   8  13  10  83]]
-Node Classification on random seed  7310 -> 0.63
-Confusion Matrix:
- [[ 90   5   2   0   3  14  15]
- [  4 126   5   0  15   5   1]
- [ 19  19 146  35  24  20  40]
- [  8   2  17  85   2   8  20]
- [  1   9   3   1  54   2   2]
- [  4   2   1   1   1  54   6]
- [  9   2   5   6   5  27  75]]
-Node Classification on random seed  7311 -> 0.644
-Confusion Matrix:
- [[ 78   3   3   9   7  11   7]
- [  3 122  10   1   7   6   0]
- [ 25  16 138  38  34  20  28]
- [ 14   1  16 112   3   5  13]
- [  1   5   1   0  59   2   0]
- [  6   2   0   4   3  43   4]
- [  5   3  10   5  11  14  92]]
-Node Classification on random seed  7312 -> 0.611
-Confusion Matrix:
- [[ 67   4   1   0   2  10  22]
- [  6 124   6   3   9  15   2]
- [ 24  12 160  29  15  35  26]
- [ 15   6  18  98   2   7  15]
- [  1   8   3   3  50   2   1]
- [  6   0   2   1   1  36   9]
- [ 13   5  18   3   7  22  76]]
-Node Classification on random seed  7313 -> 0.585
-Confusion Matrix:
- [[ 68   1   7   3   7  10  15]
- [  3  98   8   6  17   2   5]
- [ 11  31 139  24  27  47  41]
- [ 18   0  19  84  10   7  16]
- [  1   0   2   1  62   2   5]
- [ 10   0   2   1   0  50   9]
- [ 12   4   2   5   9  15  84]]
-Node Classification on random seed  7314 -> 0.635
-Confusion Matrix:
- [[ 75   1   5   8   5  12   6]
- [  3 134   4   2   9   1   4]
- [ 25  22 156  23  22  14  43]
- [ 11   3  31  90   3   4  11]
- [  3   6   7   4  51   0   1]
- [  3   2   4   0   2  43   5]
- [ 16   2  15   4   2  17  86]]
-Node Classification on random seed  7315 -> 0.598
-Confusion Matrix:
- [[ 62   1   8   2   3  22  14]
- [  6 134   5   2  10   1   3]
- [ 25  24 148  22  15  19  51]
- [ 17  10   7  89   7   9  12]
- [  1   5   8   3  54   3   1]
- [  9   3   4   1   3  51   4]
- [ 18   5   8   8   6  17  60]]
-Node Classification on random seed  7316 -> 0.609
-Confusion Matrix:
- [[ 55   3   6   4   6   9   6]
- [ 12 122   8   4   6   3   3]
- [ 34  10 136  38  32  18  39]
- [  8   2  11 107   9   5  30]
- [  3   0   4   0  67   2   3]
- [  1   2   2   1   1  48   6]
- [ 13   2  10  11  11  13  74]]
-Node Classification on random seed  7317 -> 0.642
-Confusion Matrix:
- [[ 80   2   2   2   4  19   1]
- [  3 124   9   1   4   1   8]
- [  9  26 153  31  25  21  55]
- [  6   5   9  94   2  11  10]
- [  1  10   0   2  70   0   7]
- [  6   1   3   5   2  46   3]
- [ 14   5   5  11   9   8  75]]
-Node Classification on random seed  7318 -> 0.634
-Confusion Matrix:
- [[ 81   0   4   6   5   6   5]
- [  2 120   2   1   9   2   4]
- [ 34  42 139  25  24  12  46]
- [ 16   6  11 104   4   3   9]
- [  0   6   2   1  67   0   1]
- [  3   3   6   5   0  42   6]
- [ 10   3  17   9   5  11  81]]
-Node Classification on random seed  7319 -> 0.609
-Confusion Matrix:
- [[ 64   3   8   4   3  12  10]
- [  5 123   7   1  12   3   6]
- [ 24  25 134  13  38  35  38]
- [ 14   5  19  89  12  10   7]
- [  3   6   2   0  61   1   2]
- [  3   0   3   4   0  48   7]
- [  6   1  15   1   7  16  90]]
-Node Classification on random seed  7320 -> 0.584
-Confusion Matrix:
- [[ 53   0   4   7   7   6  34]
- [ 12 120   4   3   4   3   3]
- [ 25  21 127  51  35  31  28]
- [  6   1  18  84   5   4  18]
- [  3   3   6   4  58   0   3]
- [  2   1   5   3   1  51   5]
- [  4   1   8   5  15  17  91]]
-Node Classification on random seed  7321 -> 0.657
-Confusion Matrix:
- [[ 71   1   1   0   2  16  17]
- [  3 133   4   5   6   0   4]
- [ 28  24 146  21  21  28  39]
- [ 11   2  19 108   3   4  11]
- [  0   2   6   1  67   0   3]
- [  4   1   0   1   0  46   6]
- [  6   2   9   7   7  18  86]]
-Node Classification on random seed  7322 -> 0.616
-Confusion Matrix:
- [[ 79   0   8   8   2   6   5]
- [  6 120   6   2  12   4   5]
- [ 25  30 145  38  22  24  30]
- [  9   7  26  91   2  14   8]
- [  1   3   4   3  57   1   3]
- [  2   2   8   0   0  52   2]
- [  5   3  13   7   5  23  72]]
-Node Classification on random seed  7323 -> 0.626
-Confusion Matrix:
- [[ 75   5   1   7   1   8  11]
- [  4 137   5   1  11   2   3]
- [ 18  31 137  32  34  28  33]
- [  9   3  12  95   9   8  11]
- [  0   3   3   0  59   0   2]
- [  6   1   4   2   1  43  12]
- [ 11   6   6   0  10  20  80]]
-Node Classification on random seed  7324 -> 0.573
-Confusion Matrix:
- [[ 65   2   5   4   6  12   6]
- [  5 122   5   0   9   4  10]
- [ 27  28 108  71  44  17  28]
- [  5   2  25  93   5   2  19]
- [  0   5   1   0  71   0   2]
- [  8   3   2   1   0  44   5]
- [  9   1  17   7   9  16  70]]
-Node Classification on random seed  7325 -> 0.624
-Confusion Matrix:
- [[ 74   2   8   6   4  12   5]
- [  8 114   3   3   4   8   7]
- [ 16  20 160  41  27  13  40]
- [  4   6  19 120   6   6  17]
- [  0   4   7   1  57   0   1]
- [  1   4   1   3   5  35   6]
- [  9   5   7  10   5  22  64]]
-Node Classification on random seed  7326 -> 0.604
-Confusion Matrix:
- [[ 54   1   3   7   8   5  22]
- [  1 135   2   3   6   1   8]
- [ 39  18 120  40  24  27  40]
- [ 10   1  12 111   4   6   9]
- [  3   7   4   4  58   2   2]
- [  3   1   4   3   1  47   7]
- [  1   5   6  11  14  21  79]]
-Node Classification on random seed  7327 -> 0.587
-Confusion Matrix:
- [[ 64   1   5   6   8  19   9]
- [  4 151   5   3   0   3   5]
- [ 24  19 113  45  24  29  38]
- [ 14   4  10 115   7  10  11]
- [  1   4   4   4  52   3   4]
- [  8   0   6   0   1  38   3]
- [ 16   3   7  14   9  23  54]]
-Node Classification on random seed  7328 -> 0.601
-Confusion Matrix:
- [[ 65   0   6   4   3  14   9]
- [  9 117   4   0   5   4   4]
- [ 35  19 159  43  19  25  34]
- [ 12   6  11  95  14   7  19]
- [  2   5   3   2  48   0   6]
- [  6   4   1   1   0  44   6]
- [ 21   1   7   8   5  15  73]]
-Node Classification on random seed  7329 -> 0.624
-Confusion Matrix:
- [[ 59   1   6   4   3   7  18]
- [  6 116   5   2   8   6   3]
- [ 20  24 149  25  26  36  42]
- [ 10   1  13 115   5   2   8]
- [  2   3   3   3  65   1   3]
- [ 12   0   5   0   0  42   7]
- [ 13   3  11   6   6  17  78]]
-Node Classification on random seed  7330 -> 0.637
-Confusion Matrix:
- [[ 63   8   7  13   4   4   9]
- [  3 119  12   4   8   0   5]
- [ 24  31 151  26  16  15  38]
- [  6   0  18 109   3   4   7]
- [  2   7   2   1  63   3   4]
- [  4   4   1   1   0  45   1]
- [ 13   3  12  18   9  13  87]]
-Node Classification on random seed  7331 -> 0.58
-Confusion Matrix:
- [[ 60   4   4   9   4  14  13]
- [  4  92   6   5  12   9   2]
- [ 26  21 143  34  32  22  38]
- [  6   4  24 104  15   5   5]
- [  2   0   1   2  61   0   4]
- [  9   3   1   3   2  52   7]
- [ 16   5  11  10  17   9  68]]
-Node Classification on random seed  7332 -> 0.58
-Confusion Matrix:
- [[ 62   1   8   5   5  18  12]
- [  4 104   7   3  11   4   9]
- [ 32  18 126  48  20  25  46]
- [ 11   2  19 116   0   7   9]
- [  1   2   9   1  55   1   2]
- [  5   1   6   1   0  49   6]
- [ 12   6  18   6   4  15  68]]
-Node Classification on random seed  7333 -> 0.615
-Confusion Matrix:
- [[ 67   0   6   0   1  20  15]
- [  7 121   5   3  16   5   5]
- [ 17  12 162  38  25  28  43]
- [  6   3  14  99   5   6  15]
- [  2   6   1   3  57   2   1]
- [  4   1   1   0   1  56   5]
- [ 13   2   7  10   5  26  53]]
-Node Classification on random seed  7334 -> 0.613
-Confusion Matrix:
- [[ 79   4   5   5   2  11   7]
- [  6 130   4   3   6   4   2]
- [ 12  29 134  21  42  18  41]
- [  6   7  29  78   2  11  15]
- [  3   2   5   3  64   2   3]
- [  3   2  10   2   0  42   3]
- [ 13   3  18   2   7  14  86]]
-Node Classification on random seed  7335 -> 0.67
-Confusion Matrix:
- [[ 64   6   3   1   1  22   7]
- [  5 133   2   1   9   0   2]
- [  9  20 151  23  21  34  38]
- [ 11   3  17 128   3   3   9]
- [  3  11   0   0  74   1   1]
- [  2   2   1   0   1  47   6]
- [  9   5   5   7   6  20  73]]
-Node Classification on random seed  7336 -> 0.624
-Confusion Matrix:
- [[ 75   4   3   9   7  13   1]
- [  0 136   2   2   6   3   3]
- [ 23  35 152  37  26  27  27]
- [ 10   4  10 112  10   5  15]
- [  0   9   0   4  55   3   1]
- [  7   1   5   4   1  27   8]
- [  6  12   5  10   5  13  67]]
-Node Classification on random seed  7337 -> 0.629
-Confusion Matrix:
- [[ 67   7   7  14   3  10  11]
- [  3 131   8   1   6   1   7]
- [ 11  17 158  37  17  18  58]
- [  3   3   9 100   6   9   7]
- [  1   4   8   2  56   2   3]
- [  3   2   1   3   0  45   4]
- [ 15   7   4  19   5  15  72]]
-Node Classification on random seed  7338 -> 0.541
-Confusion Matrix:
- [[ 69   1   2   3   2  19  15]
- [  6 130  10   6  10   0   9]
- [ 24  30 107  28  21  31  54]
- [  9   2  46  77   7  11  15]
- [  2   8   2   0  63   0   2]
- [  9   3   6   0   1  31   2]
- [ 15   3  24   4   4  13  64]]
-Node Classification on random seed  7339 -> 0.628
-Confusion Matrix:
- [[ 82   2   9   5   3   6   4]
- [  3 130   8   4  12   1   4]
- [ 19  20 151  39  19  30  36]
- [ 11   5  13 102   3   7   8]
- [  0   7   6   2  48   2   3]
- [  4   1   2   4   3  51   4]
- [  7   1   8  18  13  16  64]]
-Node Classification on random seed  7340 -> 0.619
-Confusion Matrix:
- [[ 82   3   2   6   2  14   3]
- [  4 127   1   3  17   3   3]
- [ 17  18 161  41  27  11  38]
- [ 22   3  25  64   9   8  13]
- [  2   4   6   4  60   1   1]
- [  5   5   2   5   0  50   1]
- [ 11   3  10   6  10  12  75]]
-Node Classification on random seed  7341 -> 0.598
-Confusion Matrix:
- [[ 64   1   2   4   9  12  21]
- [  6 106   4   2   4   6   8]
- [ 22  18 141  52  26  18  42]
- [ 11   2  13 104   6   4  25]
- [  1   6   2   4  56   4   2]
- [  8   0   1   2   0  44   8]
- [ 13   4   9   5   8   7  83]]
-Node Classification on random seed  7342 -> 0.599
-Confusion Matrix:
- [[ 53   0  12  11   5   6   7]
- [  7 128   3   1   9   1   5]
- [ 50  31 154  39  14   3  42]
- [ 11   4  10 104  17   6   8]
- [  3   6   1   1  49   0   5]
- [  7   0   5   4   2  35   8]
- [ 21   3   7   7   8  11  76]]
-Node Classification on random seed  7343 -> 0.632
-Confusion Matrix:
- [[ 62   2   6   7   5  16  11]
- [  6 119  11   1   7   0   2]
- [ 10  14 173  18  33  22  35]
- [ 11   3  19  93   7   9  11]
- [  5   4   8   0  58   2   1]
- [ 11   0   0   1   1  43   4]
- [ 18   5   9   5   7  21  84]]
-Node Classification on random seed  7344 -> 0.625
-Confusion Matrix:
- [[ 64   8   6   9   2  11  15]
- [  3 133   4   1  10   3   2]
- [ 19  15 146  54   6  14  38]
- [  5   3  11 108  11   7   9]
- [  2   7   6   3  59   0   2]
- [  7   3   0   1   2  40   5]
- [  9   3   8  20   6  25  75]]
-Node Classification on random seed  7345 -> 0.621
-Confusion Matrix:
- [[ 70   3   4   4   2  19  12]
- [  3 129   7   2   8   1   1]
- [ 21  25 153  35  13  40  36]
- [ 11   4  21  98   1   3  10]
- [  4   6   6   2  48   0   3]
- [  9   1   6   3   1  47   4]
- [ 13   4   7   4   6  14  76]]
-Node Classification on random seed  7346 -> 0.605
-Confusion Matrix:
- [[ 74   6   7   3   9   9   8]
- [  4 112   1   3  16   6   0]
- [ 40  14 145  39  24  32  27]
- [ 20   4   6 107   9   7   7]
- [  3   5   5   2  55   1   2]
- [  8   6   0   0   1  41   3]
- [ 12  11  11   2   3  19  71]]
-Node Classification on random seed  7347 -> 0.643
-Confusion Matrix:
- [[ 55   4   8   5   1   9  20]
- [ 11 113   6   1   6   1   2]
- [ 14  15 171  14  36  25  38]
- [ 17   1  17  99   2  11   6]
- [  0   3   8   4  75   1   2]
- [  4   2   0   0   2  46   4]
- [ 11   4   4   6  13  19  84]]
-Node Classification on random seed  7348 -> 0.553
-Confusion Matrix:
- [[ 62   2   4  12   5  17   8]
- [  1 127   9   1   1   5  11]
- [ 27  26  84  47  46  31  50]
- [  7   2  10  97   4   9  18]
- [  0   7   3   4  57   3   2]
- [  6   2   2   0   2  49   1]
- [ 12   4  10   5  11  20  77]]
-Node Classification on random seed  7349 -> 0.576
-Confusion Matrix:
- [[ 60   0   1  11   4  14  13]
- [  9 118   4   3   5  12   8]
- [ 19  27 119  38  30  43  38]
- [ 12   1  12 101  11  10   8]
- [  1   4   2   5  60   3   2]
- [  1   0   1   3   0  52  10]
- [  4   5  10   3   8  29  66]]
-Node Classification on random seed  7350 -> 0.609
-Confusion Matrix:
- [[ 63   5   3   4   2  14   3]
- [ 12 134   0   6   8   2   2]
- [ 14  19 123  63  39  20  24]
- [ 16   1  28  93   8   3   8]
- [  2   8   3   0  65   0   2]
- [  6   0   3   3   2  51   2]
- [ 24   2   3   7   6  14  80]]
-Node Classification on random seed  7351 -> 0.624
-Confusion Matrix:
- [[ 71   2   4   6   3   6  22]
- [  4 120   3   1   8   2  10]
- [ 25  26 157  26  31  17  36]
- [ 11   7  13  91   6   8   9]
- [  2   8   2   4  68   1   1]
- [  3   3   2   0   0  41   7]
- [ 12   2   8  10  13  12  76]]
-Node Classification on random seed  7352 -> 0.646
-Confusion Matrix:
- [[ 65   2   2  12   7   6   5]
- [  1 122   5   1  11   2   1]
- [ 20  14 157  36  21  35  39]
- [  7   3  13 105   5   9  14]
- [  1  12   2   2  62   0   2]
- [ 10   2   0   0   1  58   7]
- [  9   1   6   6   7  15  77]]
-Node Classification on random seed  7353 -> 0.64
-Confusion Matrix:
- [[ 84   1   4  11   6   8  13]
- [  5 146   2   2  10   2   0]
- [ 26  32 120  33  22  21  44]
- [  6   8  15 115   2   3   5]
- [  0   3   4   5  55   1   2]
- [  6   0   7   1   1  42   2]
- [ 10   9   2  12   4  10  78]]
-Node Classification on random seed  7354 -> 0.596
-Confusion Matrix:
- [[ 71   3   1   5   5  14   6]
- [  3 122   4   2   3   4   3]
- [ 33  19 148  43  33  28  39]
- [ 23   0   5  88   4  15  18]
- [  1   8   1   3  52   3   7]
- [  6   2   1   1   0  44   3]
- [ 14   7   9   7   5  13  71]]
-Node Classification on random seed  7355 -> 0.598
-Confusion Matrix:
- [[ 67   0   7  11   0  13   8]
- [  3 153   8   1   3   0   3]
- [ 23  38 105  44  34  15  37]
- [ 17   4   9 116   3   2  15]
- [  1  13   1   1  52   1   6]
- [  6   0   4   2   1  45   4]
- [  8   5  27   9   1  14  60]]
-Node Classification on random seed  7356 -> 0.626
-Confusion Matrix:
- [[ 76   5   2   5   1  13   4]
- [  6 132   3   2   6   7   2]
- [ 40  19 146  23  30  22  38]
- [ 10   6  16 109   5   7   6]
- [  1  13   1   1  52   1   7]
- [  3   0   1   8   0  42   3]
- [  8   4   9  17   3  16  69]]
-Node Classification on random seed  7357 -> 0.599
-Confusion Matrix:
- [[ 74   1   4   3   6  13  14]
- [  4 128   7   5   3   1   2]
- [ 21  20 154  36  22  19  39]
- [ 20   6  25  82   6  16   6]
- [  2   5   1   6  56   2   5]
- [  9   3   3   0   1  41   4]
- [ 15   4   4  16   4  18  64]]
-Node Classification on random seed  7358 -> 0.617
-Confusion Matrix:
- [[ 76   2   5   9   2   3  14]
- [  5 129   3   5   5   4   3]
- [ 30  21 127  41  34  36  35]
- [ 13   5  12 102   5   1  10]
- [  0   7   4   4  58   1   1]
- [  3   1   1   4   0  47   7]
- [  2   3  13   6   5  18  78]]
-Node Classification on random seed  7359 -> 0.615
-Confusion Matrix:
- [[ 60   5  18   6   3  18   4]
- [  4 127   5   1   4  10   1]
- [ 24  20 144  40  24  45  26]
- [  9   6   9 113   2  13   4]
- [  0   6   9   0  59   0   0]
- [  4   3   2   5   0  46   3]
- [  8   4  13   5   5  17  66]]
-Node Classification on random seed  7360 -> 0.588
-Confusion Matrix:
- [[ 83   5   2  15   0  18   8]
- [  5 115   5   1   3   5   1]
- [ 22  24 126  25  62  16  36]
- [ 14   4  22  91   7   3   6]
- [  4   7   3   3  72   2   1]
- [  8   2   4   0   1  46   4]
- [ 21   2   8  13   6  14  55]]
-Node Classification on random seed  7361 -> 0.614
-Confusion Matrix:
- [[ 62   2   4   6   3  23   8]
- [  2 139   5   0   9   3   4]
- [ 30  17 130  31  38  25  47]
- [  9   0  16 114   0  11  14]
- [  3   6   1   3  50   2   3]
- [  6   2   2   0   0  51   6]
- [ 12   3   6   5   4  15  68]]
-Node Classification on random seed  7362 -> 0.607
-Confusion Matrix:
- [[ 81   3   6   7   0  10  11]
- [  5 120   7   2   4  10   6]
- [ 35  23 131  30  16  26  32]
- [  4   3  11 108   5   7  22]
- [  3   5   8   0  53   2   2]
- [ 12   0   5   1   0  38  14]
- [ 15   3  11   3   9  15  76]]
-Node Classification on random seed  7363 -> 0.633
-Confusion Matrix:
- [[ 64   0   6   6   5   8  13]
- [  8 140   2   0  11   4   4]
- [ 32  27 142  37  14  10  40]
- [  8   1  17  89   3   7  18]
- [  0  10   3   1  62   1   1]
- [  7   3   4   1   1  60   6]
- [ 10   2  11   3   9  13  76]]
-Node Classification on random seed  7364 -> 0.645
-Confusion Matrix:
- [[ 85   1   6   1   4  12   6]
- [  3 129   8   1  16   2   4]
- [ 29  14 161  33  19  19  26]
- [ 14   1  19  95  12   6   9]
- [  4   4   7   3  55   1   2]
- [ 10   0   2   1   0  37   8]
- [  6   2   5   3  15  17  83]]
-Node Classification on random seed  7365 -> 0.576
-Confusion Matrix:
- [[ 59   3   5   4  11  16   4]
- [  3 126  11   4   7   3   0]
- [ 24  19 128  67  23  27  25]
- [ 25   4  10  99   8  11   9]
- [  1   5   5   0  64   4   2]
- [  4   0   2   2   2  38   1]
- [  4   2   7  23   9  28  62]]
-Node Classification on random seed  7366 -> 0.651
-Confusion Matrix:
- [[ 67   1   8   4   0   5  13]
- [  5 132  10   3   7   1   0]
- [ 22  15 155  43  35   8  46]
- [  8   0  14 108   3   7  16]
- [  2   2   1   1  68   3   4]
- [  3   0   0   1   1  52   2]
- [ 17   3   3  13   6  13  69]]
-Node Classification on random seed  7367 -> 0.63
-Confusion Matrix:
- [[ 69   0   5  11   4  10   8]
- [  6 107   3   8   5   5   2]
- [ 16  14 159  34  15  35  43]
- [  5   4  17 112   5   3  12]
- [  2   4  11   1  61   5   1]
- [  4   1   5   2   0  46   2]
- [ 15   4   4  12   4  23  76]]
-Node Classification on random seed  7368 -> 0.604
-Confusion Matrix:
- [[ 65   4   3   3   6   6  16]
- [  2 109  11   2   3   2   8]
- [ 21  29 150  46  34  10  46]
- [ 10   5  11  98  16   4  11]
- [  1   5   1   2  68   2   3]
- [  3   3   9   0   0  37   8]
- [  7   8  12  11   4   8  77]]
-Node Classification on random seed  7369 -> 0.607
-Confusion Matrix:
- [[ 75   2   7   2   4  12   6]
- [  3 127  13   2   4   1   4]
- [ 26  26 112  58  25  19  42]
- [  9   0   4  88  14   6  19]
- [  2  11   3   0  80   0   1]
- [ 11   2   2   0   1  43   3]
- [ 17   3  14   5   2   8  82]]
-Node Classification on random seed  7370 -> 0.59
-Confusion Matrix:
- [[ 57   2  15   5   3  17   6]
- [  1 134   3   5   3   2   4]
- [ 27  15 146  34  37  19  37]
- [ 17   6  25 102   3   3  11]
- [  0  12   3   4  46   0   4]
- [  9   0   4   3   2  36   8]
- [  5   3  11  20  14   8  69]]
-Node Classification on random seed  7371 -> 0.592
-Confusion Matrix:
- [[ 66   5   0   8   4  10  19]
- [  5 131  17   5   4   0   5]
- [ 40  24 130  29  15  21  38]
- [ 16   5  14 107   7   0  14]
- [  1  10   6   0  55   3   1]
- [  5   1   3   1   1  32  12]
- [ 16   5   9   8   8  13  71]]
-Node Classification on random seed  7372 -> 0.584
-Confusion Matrix:
- [[ 62   1   3   3   6  17  14]
- [  5 105   8   2  11  11   2]
- [ 29  28 141  33  27  30  39]
- [ 16   9   7 102   4   7  22]
- [  0   7   4   1  56   0   3]
- [  3   0   0   1   0  37  10]
- [ 10   2   6   3  15  17  81]]
-Node Classification on random seed  7373 -> 0.645
-Confusion Matrix:
- [[ 77   2   3   1   3   9  14]
- [  1 121   5   4   7   0   1]
- [ 21  26 169  41  23  17  29]
- [ 11   4  22  95  15   3  11]
- [  1   4   1   2  56   0   3]
- [  4   2   3   1   0  46   7]
- [ 13   4  15   6   7   9  81]]
-Node Classification on random seed  7374 -> 0.619
-Confusion Matrix:
- [[ 75   1   8   8   4  10   6]
- [  3 133   9   0  11   6   7]
- [ 24  23 152  32  12  18  39]
- [ 11   3  20 103   0  10   3]
- [  1   8   6   3  57   1   1]
- [  9   0   0   2   2  40   5]
- [ 28   5  12   8   7  15  59]]
-Node Classification on random seed  7375 -> 0.588
-Confusion Matrix:
- [[ 54   1   5   4   8  19  15]
- [  6 114   2   0  13   0  13]
- [ 20  17 144  34  23  34  37]
- [  9   2  19 104  15   5  16]
- [  5   3   3   0  63   1   5]
- [ 10   2   2   1   2  45   4]
- [ 13   3   7  11  11  12  64]]
-Node Classification on random seed  7376 -> 0.635
-Confusion Matrix:
- [[ 80   7   0   5   2   7   1]
- [ 10 126   3   3   6   2   2]
- [ 34  13 140  21  62  14  38]
- [  9   5  11 117   5   5  11]
- [  2   6   1   5  58   0   1]
- [  7   4   1   2   0  35   2]
- [ 20   8   4   7   7  12  79]]
-Node Classification on random seed  7377 -> 0.608
-Confusion Matrix:
- [[ 70   2   2   6   7  19   6]
- [  7 117   8   6  18   2   1]
- [ 17  18 137  46  22  35  27]
- [ 19   2  14 108   3   5   9]
- [  0   4   3   2  73   1   1]
- [  0   1   1   8   3  28  11]
- [ 14   4   4   3  13  18  75]]
-Node Classification on random seed  7378 -> 0.641
-Confusion Matrix:
- [[ 85   3   3   3   4   8   8]
- [  7 122   4   1   6   1   0]
- [ 24  21 149  50  21  26  22]
- [ 19   1  11 108   7  14   4]
- [  1  10   1   1  65   2   2]
- [  9   1   3   5   1  49   1]
- [ 15   7   9   7   3  13  63]]
-Node Classification on random seed  7379 -> 0.614
-Confusion Matrix:
- [[ 70   1   4   4   7  14  12]
- [  6 118   1   3  15   2   6]
- [ 24  14 161  37  28  30  26]
- [  8   2  22 110   5   5   8]
- [  0   6   6   4  55   2   4]
- [  3   4   3   1   4  39   8]
- [  6   5  15   6  13  12  61]]
-Node Classification on random seed  7380 -> 0.644
-Confusion Matrix:
- [[ 72   3   2   0   4  19   4]
- [  4 131   6   2   6   0   0]
- [ 24  20 135  35  21  29  48]
- [ 13   2  11 117   6   7  10]
- [  1   4   3   3  56   0   5]
- [  1   6   3   2   0  48   2]
- [ 10   8   2   4   5  21  85]]
-Node Classification on random seed  7381 -> 0.616
-Confusion Matrix:
- [[ 61   4   3   5   8  10  16]
- [  5 150   0   3   6   1   9]
- [ 41  21 152  27  19  16  53]
- [ 14   0  13  99   6   3  12]
- [  0  10   7   0  53   2   2]
- [  9   4   4   2   0  27   2]
- [ 13   9   6   3   4  12  74]]
-Node Classification on random seed  7382 -> 0.59
-Confusion Matrix:
- [[ 65   5   3   4   2   9  25]
- [  3 117   1   2   8   5   1]
- [ 23  19 150  56  27  14  43]
- [ 13  14  23  79   8   5  16]
- [  4   7   7   0  66   0   1]
- [  6   1   4   0   0  30  10]
- [ 11   3  14   1   5   7  83]]
-Node Classification on random seed  7383 -> 0.627
-Confusion Matrix:
- [[ 74   4   7   3   2  24  10]
- [  7 121   6   0  10   3   3]
- [ 19  27 146  36  26  18  38]
- [  8   7  19 104   3   4  10]
- [  2   9   6   0  69   2   0]
- [  3   2   1   5   0  49   1]
- [  1   3  10  13   5  16  64]]
-Node Classification on random seed  7384 -> 0.634
-Confusion Matrix:
- [[ 81   5   6   7   3   9  12]
- [  5 141   4   2   4   3   0]
- [ 17  16 132  45  14  26  27]
- [  5   6  14  84   3  10  23]
- [  1  13   5   0  64   2   2]
- [  4   1   8   1   1  47   3]
- [ 16   3  15   4   8  13  85]]
-Node Classification on random seed  7385 -> 0.572
-Confusion Matrix:
- [[ 63   1   6   2   5   8  12]
- [  8 133   2   3   4   4   3]
- [ 18  32 131  43  46  24  24]
- [ 11   9  22  83  10   6  23]
- [  2   6   6   0  58   1   1]
- [ 10   1   2   4   1  33   4]
- [ 19   4  12   9   4  16  71]]
-Node Classification on random seed  7386 -> 0.612
-Confusion Matrix:
- [[ 62   5   6   4   3  19   7]
- [  0 126   4   1   4   4   7]
- [ 13  20 141  43  28  12  44]
- [  5   2  33  98   4   2  17]
- [  0  15   2   6  48   4   3]
- [  7   3   1   3   0  46   1]
- [  6   7  11   5   6  21  91]]
-Node Classification on random seed  7387 -> 0.608
-Confusion Matrix:
- [[ 87   4   2   3   2   6  12]
- [ 12 134   2   1   9   4   5]
- [ 36  16 118  31  34  22  34]
- [ 19   3  16  94   5   8   8]
- [  5  12   2   1  54   0   6]
- [  9   0   2   2   1  44   2]
- [ 16   0   4  12   7  17  77]]
-Node Classification on random seed  7388 -> 0.588
-Confusion Matrix:
- [[ 70   3   4   3   4  15   8]
- [  1 136   7   4  12   4   4]
- [ 53  32 102  37  28  28  16]
- [ 14   6  17  84   6   9  11]
- [  1   6   0   3  58   2   7]
- [  4   1   2   0   2  53   6]
- [  8   5  11   6   3  19  85]]
-Node Classification on random seed  7389 -> 0.628
-Confusion Matrix:
- [[ 76   3   1   5   6  12  15]
- [  5 121   2   9  13   6   3]
- [ 18  19 165  31  24  30  41]
- [ 11   5  15 101   6  13  11]
- [  1   9   3   4  52   1   2]
- [  3   1   2   0   0  33   5]
- [  5   0   4   6  11  11  80]]
-Node Classification on random seed  7390 -> 0.625
-Confusion Matrix:
- [[ 84   3   1  10   2  11   8]
- [  8 122   7   4   1   1   3]
- [ 38  22 134  37  18  38  38]
- [ 12   2  17  92   5  11  10]
- [  1  10   0   1  62   3   3]
- [  2   1   2   1   0  53   2]
- [ 10   1   8   9   4  10  78]]
-Node Classification on random seed  7391 -> 0.601
-Confusion Matrix:
- [[ 78   1   9  13   1   8   7]
- [  6 123   7   2  12   1   2]
- [ 20  11 135  40  46  24  43]
- [ 13   3  13  94  11   2  14]
- [  1   3   2   2  57   3   5]
- [  5   0   1   1   0  52   5]
- [  7   1  14  21   4  15  62]]
-Node Classification on random seed  7392 -> 0.546
-Confusion Matrix:
- [[ 51   1  15   1   7  12  11]
- [  9 109   9   4  11   1   1]
- [ 27  30 116  47  40  37  27]
- [ 12   5  17  79   8  14  21]
- [  0   2   7   2  63   0   2]
- [  2   3   5   0   0  52   3]
- [  2   8  11   7   3  30  76]]
-Node Classification on random seed  7393 -> 0.626
-Confusion Matrix:
- [[ 83   2   3   5   4  15   3]
- [  6 106   6   3  12   5   9]
- [ 34  19 165  32  23   8  32]
- [ 23   8  10  97   5   3  14]
- [  4   4   2   1  64   2   1]
- [  1   0   5   0   1  48   7]
- [ 18   5   5   6   5  23  63]]
-Node Classification on random seed  7394 -> 0.606
-Confusion Matrix:
- [[ 69   5   6   6   2  15   8]
- [  4 137  13   0   5   1   1]
- [ 26  13 124  27  47  29  34]
- [  5   6  17  91  13   7  22]
- [  1  10   2   2  65   1   2]
- [  2   2   0   1   0  47   3]
- [  9   8   7  11   6  15  73]]
-Node Classification on random seed  7395 -> 0.634
-Confusion Matrix:
- [[ 83   2   4   6   0  12   6]
- [  6 139  10   3   8   3   2]
- [ 29  18 129  39  29  15  21]
- [ 19   1  17 102   5   3  16]
- [  4   3   5   3  48   1   3]
- [  6   1   2   3   0  43  10]
- [  5   3  10  11   7  15  90]]
-Node Classification on random seed  7396 -> 0.6
-Confusion Matrix:
- [[ 74   3   1   4   5   5  10]
- [  3 125   9   3   6   3   1]
- [ 24  32 116  31  43  42  36]
- [  5   5  18 100   3   9  15]
- [  2   8   4   0  65   0   0]
- [  6   0   3   1   1  49   4]
- [ 11   8  10   2  14  10  71]]
-Node Classification on random seed  7397 -> 0.647
-Confusion Matrix:
- [[ 73   5   5   7   4   9  12]
- [  0 128   9   1   1   3   5]
- [ 12  27 149  13  21  36  60]
- [  4   2  20 107   6   4   7]
- [  0   3   1   1  65   2   5]
- [  4   2   5   0   0  50   5]
- [  7   4  12   4   9  16  75]]
-Node Classification on random seed  7398 -> 0.611
-Confusion Matrix:
- [[ 57   3   4   1   3  17  15]
- [  3 139   6   0   8   5   2]
- [ 21  22 156  37  17  29  39]
- [ 13   1  14  92   4   9  14]
- [  2   7   2   6  53   0   6]
- [  6   0   1   1   2  43   5]
- [ 20   1   5  11   4  23  71]]
-Node Classification on random seed  7399 -> 0.629
-Confusion Matrix:
- [[ 73   1   2   3   3  10  13]
- [  6 137   6   2   1   1   3]
- [ 27  26 153  30  22  17  30]
- [ 24   6  15  94   7   6   5]
- [  4   8   4   1  68   4   2]
- [  8   0  14   1   1  33   7]
- [  9   1  12   5   9  15  71]]
-Node Classification on random seed  7400 -> 0.627
-Confusion Matrix:
- [[ 63   4   2   2   6  24  12]
- [  2 142   4   0   1   1   7]
- [ 15  24 158  31  32  32  31]
- [  9   7  13  90   1   6  11]
- [  2   8   2   3  57   1   1]
- [  3   0   5   0   1  42   6]
- [  7   9   6   9  13  20  75]]
-Node Classification on random seed  7401 -> 0.614
-Confusion Matrix:
- [[ 69   1   1   6   3   8  14]
- [  3 127   4   3   4   9   5]
- [ 12  21 138  29  34  28  43]
- [ 17   4  16 101   7   6  10]
- [  0  14   4   4  62   1   5]
- [  9   0   2   2   0  42   8]
- [ 17   2   6   5   8  11  75]]
-Node Classification on random seed  7402 -> 0.648
-Confusion Matrix:
- [[ 62   7   1   6   6  11   6]
- [  3 131   1   0   3   1   4]
- [ 28  19 148  54  37  22  18]
- [  7   1  14 109   7   5  12]
- [  1   2   3   1  69   1   1]
- [  4   2   1   0   0  45   4]
- [ 13   1   8   6   6  25  84]]
-Node Classification on random seed  7403 -> 0.616
-Confusion Matrix:
- [[ 56   0   3   8   1  12  16]
- [  5 123   5   1  16   1   0]
- [ 27  36 154  35  37  18  24]
- [  5   2  16 101   3   3  11]
- [  5   8   3   0  63   2   1]
- [  8   2   8   2   4  46   1]
- [ 11   6   9   9   4  16  73]]
-Node Classification on random seed  7404 -> 0.627
-Confusion Matrix:
- [[ 60   1   8   3   4   9  15]
- [  6 128   8   4   5   2   4]
- [ 30  27 152  30  23  29  34]
- [ 19   1  11 108   2   4  11]
- [  5   5   3   3  65   0   0]
- [  6   1   4   3   4  45   5]
- [ 14   2   9   2   3  14  69]]
-Node Classification on random seed  7405 -> 0.582
-Confusion Matrix:
- [[ 79   2   5   3  10   8   6]
- [  3 117   6   2   5   4  11]
- [ 26  21 129  44  28  19  50]
- [  7   8  16  87  11  11  18]
- [  1   9   4   0  51   0   2]
- [ 13   0   0   3   0  45   0]
- [ 16   5   6   8   5  22  74]]
-Node Classification on random seed  7406 -> 0.626
-Confusion Matrix:
- [[ 78   1   1   2   4  14   7]
- [  1 135   7   4   4   4   1]
- [ 29  27 143  27  39  19  38]
- [ 14   3  22  82   4   6  14]
- [  0   7   7   1  64   4   4]
- [  5   0   2   2   1  46   3]
- [  5   1  16   5   3  16  78]]
-Node Classification on random seed  7407 -> 0.636
-Confusion Matrix:
- [[ 79   0   2   3   1   6   9]
- [  7 133   3   9   8   2   6]
- [ 38  25 152  33  29  28  19]
- [ 13   5  14  98   3   8   8]
- [  1   2   2   1  61   1   2]
- [  8   0   2   1   0  39   8]
- [ 20   4   8   6   7  12  74]]
-Node Classification on random seed  7408 -> 0.616
-Confusion Matrix:
- [[ 83   4   5   9   1   6   4]
- [  6 133   9   0   7   4   1]
- [ 16  24 133  35  42  17  36]
- [ 11   3   7  98  12  13  21]
- [  1   4   6   2  55   4   3]
- [  4   0   3   2   1  41   5]
- [ 14   2   7   8   8  17  73]]
-Node Classification on random seed  7409 -> 0.615
-Confusion Matrix:
- [[ 81   7   3   7   2   6  18]
- [  1 124   8   0   6   2   6]
- [ 19  13 148  40  24  22  46]
- [  5  10  17  94   3   9  14]
- [  3   5   3   3  54   0   1]
- [  5   1   8   2   3  36   1]
- [ 16   3   6  12   6  19  78]]
-Node Classification on random seed  7410 -> 0.618
-Confusion Matrix:
- [[ 72   1   7   2   4  14   7]
- [ 11 125   4   1   3   2   6]
- [ 36  24 149  17  34  19  37]
- [  9  10  18 105  13   5   9]
- [  6   8   2   1  46   1   2]
- [  6   2   2   0   1  51   2]
- [ 18   6  12   5   6   9  70]]
-Node Classification on random seed  7411 -> 0.682
-Confusion Matrix:
- [[ 84   7   3   4   5   7   5]
- [  1 140   5   0   4   2   3]
- [ 34  18 159  26  21  14  20]
- [ 14  11  17 107   1   6   8]
- [  0   8   1   0  60   0   4]
- [  2   4   3   0   0  44   2]
- [ 16   6   6   2  15  13  88]]
-Node Classification on random seed  7412 -> 0.61
-Confusion Matrix:
- [[ 69   4   4   3   9  16  19]
- [  2 112   4   1  11   3   8]
- [ 30  18 159  20  22  27  37]
- [  8   7  13 107   3   1  21]
- [  0   6   3   0  56   0   3]
- [  6   2   2   0   2  41   7]
- [ 11   6   9   4  20  18  66]]
-Node Classification on random seed  7413 -> 0.596
-Confusion Matrix:
- [[ 73   1   0   1   3  12  16]
- [  0 136   6   3   5   4   6]
- [ 19  22 122  30  19  41  61]
- [ 11   7  14  94   1   8  13]
- [  3   9   3   0  53   2   2]
- [  5   2   5   1   1  48   3]
- [ 18   3  10   1  15  18  70]]
-Node Classification on random seed  7414 -> 0.624
-Confusion Matrix:
- [[ 75   4   1   1  10  13   8]
- [  2 128   4   2  15   5   3]
- [ 17  18 144  43  14  29  42]
- [ 15   5   6  92   7  11  17]
- [  2  10   2   1  59   1   4]
- [  4   0   0   1   0  58   4]
- [  8   9   7  10   6  15  68]]
-Node Classification on random seed  7415 -> 0.61
-Confusion Matrix:
- [[ 64   1   6   2   4  17   9]
- [  3 115  10   4  10   1  13]
- [ 17  12 150  30  30  20  53]
- [ 13   1  18  86   8   4  22]
- [  1   5   2   4  67   3   2]
- [  6   0   4   1   0  40   7]
- [  9   5   8   1  10  14  88]]
-Node Classification on random seed  7416 -> 0.613
-Confusion Matrix:
- [[ 71   1   7   5   3   6  13]
- [  2 118   2   0   7   3   6]
- [ 20  27 135  19  29  37  52]
- [ 16   2  22  93  12   8  16]
- [  0   7   4   1  54   3   4]
- [  3   0   0   2   0  50   7]
- [ 12   5   6   2   6  10  92]]
-Node Classification on random seed  7417 -> 0.588
-Confusion Matrix:
- [[ 58   2  10   9  10   8   4]
- [  3 132   4   4  16   4   6]
- [ 12  16 146  29  50  26  40]
- [  9   2  27 100  10   4   7]
- [  2   5   3   2  57   1   3]
- [  2   2   6   0   6  39   5]
- [ 15   5  11  12  14   6  56]]
-Node Classification on random seed  7418 -> 0.61
-Confusion Matrix:
- [[ 62   0   3   5   5  12  13]
- [  2 155   7   1   5   2   6]
- [ 16  20 114  42  34   9  68]
- [ 15   3  10 104   7   4  11]
- [  0   6   4   4  61   1   1]
- [  3   8   1   1   1  42   4]
- [ 11  13   8   3  12   9  72]]
-Node Classification on random seed  7419 -> 0.631
-Confusion Matrix:
- [[ 64   0   0   3   9  13  15]
- [  1 125   5   2  11   6   4]
- [ 26  11 140  48  38  18  33]
- [  7   1  16 103   4   2  17]
- [  0   6   5   2  63   0   2]
- [  3   0   2   2   1  50   5]
- [ 14   1   3  15   6  12  86]]
-Node Classification on random seed  7420 -> 0.608
-Confusion Matrix:
- [[ 64   6   1  10   7  11  12]
- [  7 124   7   4   4   1   2]
- [ 19  23 154  33   7  36  55]
- [  9   5  22 103   3   5   9]
- [  0  11   9   1  50   1   1]
- [ 10   2   3   2   1  32   8]
- [  1   4  21   6   5   8  81]]
-Node Classification on random seed  7421 -> 0.611
-Confusion Matrix:
- [[ 80   7   2   6   5  12   9]
- [  6 134   4   2   9   7   4]
- [ 30  13 137  18  29  29  40]
- [ 14   8  22  85   4   8  15]
- [  0   1   2   0  62   0   4]
- [  4   3   2   2   0  45   1]
- [ 12   4   3  17  12  19  68]]
-Node Classification on random seed  7422 -> 0.606
-Confusion Matrix:
- [[ 79   2   3   4   1  22   1]
- [  2 141   3   2   9   2   5]
- [ 25  21 140  30  17  25  36]
- [ 21   2  18  77   7  22  10]
- [  1   8   4   0  72   0   3]
- [ 12   2   0   1   8  39   1]
- [ 10   3  12   6   6  27  58]]
-Node Classification on random seed  7423 -> 0.642
-Confusion Matrix:
- [[ 63   9   0   5   7   9  12]
- [  6 127   3   1   9   1   4]
- [ 18  13 188  25  17  38  35]
- [  6   5  17  87  10   6  10]
- [  0   3   4   2  57   3   4]
- [  5   2   0   0   3  49   4]
- [ 26   1   9   5   9  12  71]]
-Node Classification on random seed  7424 -> 0.626
-Confusion Matrix:
- [[ 73   2   2   2   1   7   9]
- [  2 128  10   1   9   5   2]
- [ 30  29 155  18  19  24  57]
- [ 13   6  16 100   4   5  14]
- [  3   9   6   3  55   0   5]
- [  5   1   1   2   2  45   8]
- [ 11   1   7   7   4  12  70]]
-Node Classification on random seed  7425 -> 0.631
-Confusion Matrix:
- [[ 74   5   3   4   7   9   7]
- [  2 134   3   1   8   7   5]
- [  9  25 160  37  29  26  34]
- [ 11   6  16  92   7   7   7]
- [  1   3   2   3  52   2   1]
- [  9   3   9   2   0  36   7]
- [  8   2   9   7  14  12  83]]
-Node Classification on random seed  7426 -> 0.596
-Confusion Matrix:
- [[ 55   7  18   3   4   4  11]
- [ 10 123  15   1   7   4   1]
- [ 39  25 137  31  21  36  38]
- [  4   0  13 102   3  11  20]
- [  0   4   5   4  52   0   4]
- [  3   2   3   5   0  40   7]
- [  8   2   9   1  10  11  87]]
-Node Classification on random seed  7427 -> 0.63
-Confusion Matrix:
- [[ 73   5   1  16   8  11   8]
- [  3 118   4   1  12   1   7]
- [ 26  19 147  27  19  13  57]
- [  1   6   7 127   6   4  17]
- [  3   2   5   2  62   0   1]
- [  8   5   2   2   2  43   3]
- [ 11   6  10   9  11   9  60]]
-Node Classification on random seed  7428 -> 0.602
-Confusion Matrix:
- [[ 73   6   5   8   4   8   5]
- [  2 125   4   2  13   2   1]
- [ 20  18 131  53  25  27  42]
- [ 17   4  15 107   8  10  15]
- [  0   6   3   1  63   2   1]
- [  3   2   4   3   1  34   1]
- [  5   4  10  10   9  19  69]]
-Node Classification on random seed  7429 -> 0.621
-Confusion Matrix:
- [[ 79   5   8   5   4   9   7]
- [  3 110   6   2  11   3   2]
- [ 19   7 171  40  20  21  45]
- [ 13   2  28  95   5   3  12]
- [  0   5   7   1  55   0   3]
- [  2   1   6   2   2  40   3]
- [ 20   7  10   9  11  10  71]]
-Node Classification on random seed  7430 -> 0.596
-Confusion Matrix:
- [[ 77   2   3   8   3  10   5]
- [  9 135   6   3   8   1   2]
- [ 32  13 106  41  27  41  46]
- [  7   6  19 110   4   4   5]
- [  2  12   4   2  53   2  10]
- [  4   0   2   0   1  50   5]
- [  9   7   4   7   6  22  65]]
-Node Classification on random seed  7431 -> 0.63
-Confusion Matrix:
- [[ 67   3   2   7   2  17   1]
- [  2 124   7   2   4   6   4]
- [ 10  14 172  40  32  29  29]
- [  5   5  16  96   7  10  12]
- [  1   8   8   1  62   2   3]
- [  5   1   2   2   0  47   3]
- [ 13   6   6   6  10  27  62]]
-Node Classification on random seed  7432 -> 0.675
-Confusion Matrix:
- [[ 87   1   2   5   0   9   6]
- [  1 140   5   1  11   1   4]
- [ 15  23 161  35  13  26  28]
- [  5   7   8 119   2   8   1]
- [  1   4   7   4  57   3   4]
- [  9   2   1   2   0  38   2]
- [ 12   6  11  11   7  22  73]]
-Node Classification on random seed  7433 -> 0.629
-Confusion Matrix:
- [[ 62   3   7  10   4   4   5]
- [  8 112   6   3   8   4   7]
- [ 25  10 132  41  26  17  55]
- [  8   3  11 130   1   5  10]
- [  3   3   3   4  68   0   1]
- [  4   0   4   2   2  48   2]
- [ 12   5   7  18  10  10  77]]
-Node Classification on random seed  7434 -> 0.616
-Confusion Matrix:
- [[ 72   4   0   5   1  17  12]
- [  5 117   8   7   5   4   7]
- [ 24  13 137  56  30  26  27]
- [ 11   1  21 105   2   5   5]
- [  3   8   1   1  70   2   4]
- [  3   0   1   2   4  51   4]
- [ 24   1   6   4   5  15  64]]
-Node Classification on random seed  7435 -> 0.582
-Confusion Matrix:
- [[ 56   6   6   4   5   7  11]
- [  5 124  10   6  13   0   4]
- [ 21  23 138  33  13  47  29]
- [  9   2  24  92   8   7  14]
- [  0   4   5   3  62   2   4]
- [  6   1   3   5   0  40   4]
- [  5   2  23  19   6  19  70]]
-Node Classification on random seed  7436 -> 0.618
-Confusion Matrix:
- [[ 60   2   3   6   6   5  14]
- [  6 118   6   5   6   1   5]
- [ 29  11 134  31  28  38  45]
- [  6   1  25 109   6   4  13]
- [  6   7   4   3  65   0   2]
- [  2   3   0   0   3  45   4]
- [ 10   1  11   6   8  10  87]]
-Node Classification on random seed  7437 -> 0.601
-Confusion Matrix:
- [[ 70   3   7   6   5   9   7]
- [  3 115   9   6  17   2   8]
- [ 19  14 146  18  31  23  43]
- [ 21   1  20  94  13   6  15]
- [  3   4   4   2  67   1   3]
- [  3   0   4   2   2  42   7]
- [ 13   1   7   8  16  13  67]]
-Node Classification on random seed  7438 -> 0.628
-Confusion Matrix:
- [[ 84   1   2   1   7  13   0]
- [  7 120  15   2  17   2   3]
- [ 38  20 145  22  33  19  27]
- [ 12   8  30  97   4   3   5]
- [  1   3   1   1  65   0   1]
- [  5   2   4   3   2  44   2]
- [ 10   3   5   9  10  19  73]]
-Node Classification on random seed  7439 -> 0.621
-Confusion Matrix:
- [[ 68   2   5  11   4  16   6]
- [  5 113   8   0   6   1   8]
- [ 18  20 150  27  17  25  38]
- [ 13   6  28  85   5   6  10]
- [  1   6   4   0  79   2   5]
- [  5   0   1   0   2  47   5]
- [  9   3  13   7  19  12  79]]
-Node Classification on random seed  7440 -> 0.587
-Confusion Matrix:
- [[ 74   4   4   2   7   3  10]
- [  6  97   7   2   8   2   7]
- [ 15  25 108  49  24  36  54]
- [ 11   2  18 110  17   2  13]
- [  1   3   2   2  69   1   3]
- [  6   1   6   4   0  50   3]
- [  9   3   9  13   5  14  79]]
-Node Classification on random seed  7441 -> 0.642
-Confusion Matrix:
- [[ 58   2   3  11   4  14  12]
- [  7 128   3   1  11   2   6]
- [ 18  21 161  49  13  14  41]
- [ 12   3   7 109   5   5   9]
- [  1   8   5   3  54   0   4]
- [  1   0   4   2   2  48   5]
- [  6   5   7   6   8  18  84]]
-Node Classification on random seed  7442 -> 0.635
-Confusion Matrix:
- [[ 58   3  11   4   5  11   5]
- [ 14 127   6   3   8   6   5]
- [ 21  14 156  29  20  20  36]
- [ 12   3   6 122   5   6  13]
- [  5   9   7   1  57   2   0]
- [  9   3   7   0   1  34   1]
- [  7   5  11  10   7  14  81]]
-Node Classification on random seed  7443 -> 0.584
-Confusion Matrix:
- [[ 90   3   2   5   3  15   3]
- [  8 114   1   2   8   4   3]
- [ 23  26 131  44  39  14  54]
- [ 13   2  23  94   6   3   6]
- [  3   7   4   1  52   0   5]
- [ 11   3   5   6   2  34   4]
- [ 17   8   5  12   5   8  69]]
-Node Classification on random seed  7444 -> 0.639
-Confusion Matrix:
- [[ 76   3   6   1   2   9   5]
- [  1 130   9   0  10   2   1]
- [ 22  19 146  41  27  20  38]
- [ 19   5  11 104  10   5   9]
- [  0  10   1   2  62   1   3]
- [  8   5   0   0   0  43   5]
- [ 16   5   5   5   6  14  78]]
-Node Classification on random seed  7445 -> 0.602
-Confusion Matrix:
- [[ 60   1   7   9   2  14  13]
- [  3 133   4   0   6   2   6]
- [ 18  20 148  30  15  42  46]
- [  8   7  19  78   6   7  18]
- [  1   8   6   2  60   0   4]
- [  2   4   1   4   1  51   4]
- [ 11   6   8   7   5  21  72]]
-Node Classification on random seed  7446 -> 0.618
-Confusion Matrix:
- [[ 73   0   9   5   1  11   3]
- [ 11 115  10   6   6   1   7]
- [ 18  14 150  22  20  24  73]
- [ 10   1  23  93   4   6  12]
- [  5   5   6   1  60   1   6]
- [  5   2   2   2   0  42   3]
- [ 13   0   6   4   6  18  85]]
-Node Classification on random seed  7447 -> 0.648
-Confusion Matrix:
- [[ 73   3   1   6   6  10  13]
- [  1 137   9   9   2   1   4]
- [ 16  17 148  49  10  16  39]
- [ 12   6  13 113   3   5  10]
- [  1   8   5   1  55   0   6]
- [  5   4   3   0   1  43   6]
- [ 16   6   2  11   2  14  79]]
-Node Classification on random seed  7448 -> 0.645
-Confusion Matrix:
- [[ 61   5   6   8   6  11  10]
- [  5 136   6   0   3   3   0]
- [ 18  17 140  36  42  13  38]
- [  6   4  16 113   2   3  15]
- [  0   8   2   0  60   1   4]
- [  3   3   1   4   0  48   6]
- [  7   3  11   9   5  15  87]]
-Node Classification on random seed  7449 -> 0.631
-Confusion Matrix:
- [[ 68   1   2   4   3  26   4]
- [  2 115   6   5   8   0   3]
- [ 19  18 169  31  22  30  42]
- [ 11   2  26 106   4   3   9]
- [  2   5   8   0  52   1   8]
- [  1   3   1   0   2  53   2]
- [ 14   5  11   5   1  19  68]]
-Node Classification on random seed  7450 -> 0.63
-Confusion Matrix:
- [[ 72   2   4   9   0  13  14]
- [  2 126   1   3   1   4   3]
- [ 30  19 156  27  33  15  36]
- [ 10   2  17  89   3   8  23]
- [  3   8   2   0  62   0   4]
- [  9   0   2   2   0  50  12]
- [ 14   8   1   8   8  10  75]]
-Node Classification on random seed  7451 -> 0.636
-Confusion Matrix:
- [[ 71   5   0  12   2  18  13]
- [  8 111   2   1  24   3   2]
- [ 29  11 154  19  24  24  42]
- [  8   5   7 123   3   6  14]
- [  3   1   2   2  61   2   1]
- [  5   2   2   3   0  41   7]
- [  7   0  15   5   4  21  75]]
-Node Classification on random seed  7452 -> 0.613
-Confusion Matrix:
- [[ 63   2   7   1   0  14  11]
- [ 14 112   2   3   6   0   7]
- [ 27  30 154  23  22  37  43]
- [ 11   7  14  93   7   9  15]
- [  3   8   3   0  68   1   2]
- [  3   0   1   0   0  45   3]
- [ 19   1   7   2   8  14  78]]
-Node Classification on random seed  7453 -> 0.615
-Confusion Matrix:
- [[ 72   3   8   5   3   8   6]
- [  3 114   4   8  18   3   0]
- [ 16  23 143  31  30  26  52]
- [ 14   0  26  89  10   4   6]
- [  0   3   6   2  66   1   1]
- [  5   0   5   0   1  45   4]
- [ 10   1  12   4   4  19  86]]
-Node Classification on random seed  7454 -> 0.601
-Confusion Matrix:
- [[ 77   0   8   5   1  23   7]
- [  5 122   2   2  14   3   4]
- [ 39  22 107  32  39  20  31]
- [ 22   0  12  89  10   5  11]
- [  1   6   1   2  76   1   6]
- [  6   2   2   0   1  51   2]
- [  6   4  11   7   3  21  79]]
-Node Classification on random seed  7455 -> 0.594
-Confusion Matrix:
- [[ 74   6   0   2   5  11  12]
- [  8 128   4   1  15   1   1]
- [ 28  38 102  51  29  21  35]
- [  6   2  14 108   7   4  11]
- [  2  10   5   1  60   2   4]
- [  5   0   2   2   0  48   5]
- [  5   4  17   7  10  13  74]]
-Node Classification on random seed  7456 -> 0.635
-Confusion Matrix:
- [[ 72   7   6   5   6  10   6]
- [  7 117   2   4   9   2   2]
- [ 37  24 154  18  21  27  34]
- [  8   7  24 109   3   5  10]
- [  0   2   5   3  64   0   2]
- [ 10   2   1   0   1  49   1]
- [ 22   2  15   6   4   5  70]]
-Node Classification on random seed  7457 -> 0.64
-Confusion Matrix:
- [[ 88   3   3   6   5   5  11]
- [  6 117   2   5   3   5   6]
- [ 22  24 146  29  23  28  40]
- [ 10   8  16  95  12   4  15]
- [  1   8   4   0  67   0   1]
- [  3   2   1   2   1  40   3]
- [ 13   3  10   0  14   3  87]]
-Node Classification on random seed  7458 -> 0.593
-Confusion Matrix:
- [[ 68   0   3  13   7  14  10]
- [  7 112   5   7  13   1   2]
- [ 33   9 144  42  21  20  45]
- [ 23   2  17  94  11   4   6]
- [  2   2   6   0  65   0   3]
- [  9   2   2   0   6  32   6]
- [ 10   1   9   9  15  10  78]]
-Node Classification on random seed  7459 -> 0.612
-Confusion Matrix:
- [[ 62   2   1   6   2  17  16]
- [  7 134   4   6   3   2   2]
- [ 29  22 128  49  42  10  32]
- [ 12   3  13  97   5   7  14]
- [  5   8   3   0  65   0   2]
- [  7   0   3   2   3  41   5]
- [ 16   3   5   4   6  10  85]]
-Node Classification on random seed  7460 -> 0.602
-Confusion Matrix:
- [[ 63   3   1   2   3  13  13]
- [  5 137   4   1  15   1   3]
- [ 31  17 170  30  11  36  27]
- [ 11   8  18  86   8   6  20]
- [  4   6   9   3  48   0   1]
- [  3   1   0   4   1  48   2]
- [  9   6   4  12  23  23  50]]
-Node Classification on random seed  7461 -> 0.648
-Confusion Matrix:
- [[ 67   3   5   8   3  10   9]
- [  4 132   5   4   6   1   5]
- [ 15  13 150  35  25  37  40]
- [  5   4  15 114   2   3   8]
- [  1   9   3   2  57   1   1]
- [  5   2   1   0   1  49   7]
- [  8   4   9  15   5  13  79]]
-Node Classification on random seed  7462 -> 0.647
-Confusion Matrix:
- [[ 67   3   5   3   1   5  11]
- [  1 111   6   2  15   0   5]
- [ 13  16 167  35  28  28  33]
- [  2   4  18 110   9   8  18]
- [  0   6   0   1  66   0   3]
- [ 11   1   8   1   2  41   3]
- [  4   7   5   9  12  11  85]]
-Node Classification on random seed  7463 -> 0.596
-Confusion Matrix:
- [[ 55   9   3   6   4  12  11]
- [  5 114  10   2   6   2   7]
- [ 21  17 137  22  37  23  44]
- [  6   2  24  94  16   5  13]
- [  1   4   7   2  65   1   1]
- [  8   1   6   1   1  41   7]
- [ 13   9  11   2   6  16  90]]
-Node Classification on random seed  7464 -> 0.6
-Confusion Matrix:
- [[ 66   9   5   4   1   7   7]
- [  4 120   3   3  13   7   2]
- [ 43  25 141  20  30  23  34]
- [ 20   7  15 108   2   5  11]
- [  2   6   1   7  61   2   1]
- [ 14   3   6   1   0  34   1]
- [ 17   4  10   6   7  12  70]]
-Node Classification on random seed  7465 -> 0.587
-Confusion Matrix:
- [[ 71   2   4   3   8   9   5]
- [  5 129   6   4  15   5   3]
- [ 30  15 125  45  31  15  39]
- [ 26   1  10  98   6  11  15]
- [  0   6   6   5  49   0   2]
- [  1   3   2   1   5  42   3]
- [ 16   2  15  10   9  14  73]]
-Node Classification on random seed  7466 -> 0.605
-Confusion Matrix:
- [[ 65   4   4   6   6  18   9]
- [  0 133   4   4   4   3   7]
- [ 27  29 127  62  16  18  30]
- [ 11   3  18  91  13   9  15]
- [  0   8   5   3  58   0   3]
- [  4   2   1   1   0  48   4]
- [  6   3   5   2  10  18  83]]
-Node Classification on random seed  7467 -> 0.623
-Confusion Matrix:
- [[ 60   2   2   4   6   8  29]
- [  3 133   9   5  12   1   4]
- [ 29  10 131  27  39  21  25]
- [ 14   4  13 122   1   5   6]
- [  1   7   3   0  60   3   3]
- [  7   1   4   5   0  45   4]
- [ 15   1   2  13  12  17  72]]
-Node Classification on random seed  7468 -> 0.655
-Confusion Matrix:
- [[ 95   1   3   6   1   8   5]
- [  4 117  11   0  17   1   2]
- [ 28  15 161  34  21  26  33]
- [ 12   3  17  92   7   2   8]
- [  1   0   1   4  61   0   6]
- [ 10   0   0   0   3  51   3]
- [ 19   1   8   5   7  12  78]]
-Node Classification on random seed  7469 -> 0.672
-Confusion Matrix:
- [[ 79   0   6   1   3   6  11]
- [  1 119   4   1  15   1   5]
- [ 32  29 154  16  31  21  34]
- [  9   2  14 114   7   3   9]
- [  2   6   0   1  62   0   1]
- [  5   2   2   1   1  46   6]
- [  9   2   6   5   9   9  98]]
-Node Classification on random seed  7470 -> 0.6
-Confusion Matrix:
- [[ 65   0   4   8   0  25   7]
- [  6 113   4   5   6   1   7]
- [ 20  17 161  36  16  25  36]
- [  9   3  15  81  15  15  34]
- [  1   4   3   1  59   2   1]
- [  7   0   0   3   0  43  10]
- [ 10   3  12   3   3  23  78]]
-Node Classification on random seed  7471 -> 0.61
-Confusion Matrix:
- [[ 60   5   2   5   4  16  14]
- [  3 118   7   0   9   2   5]
- [ 16  16 145  36  46  20  31]
- [ 20   3  13  97   9  10  16]
- [  1   2   1   0  65   4   4]
- [  3   2   4   1   3  37   2]
- [  6   3   8   5  12  21  88]]
-Node Classification on random seed  7472 -> 0.633
-Confusion Matrix:
- [[ 72   5   6  10   1   9   6]
- [  4 122   8   3  14   3   3]
- [ 33  20 151  39  27  14  28]
- [  5   0  18 111   6   5  18]
- [  6   3   1   0  66   1   0]
- [  3   2   5   0   1  36   4]
- [  8   7   8   8  10  15  75]]
-Node Classification on random seed  7473 -> 0.645
-Confusion Matrix:
- [[ 85   2   1   2   6   2   7]
- [  4 136   5   4   1   3   4]
- [ 24  22 167  35  22  11  34]
- [ 17   4  10  84  20   5  19]
- [  1   9   2   1  55   1   3]
- [  6   1   5   5   1  40   2]
- [  8   7  13   5   8  13  78]]
-Node Classification on random seed  7474 -> 0.59
-Confusion Matrix:
- [[ 79   3   4   4   8  11   4]
- [  6 104  12   4   7   8   2]
- [ 37  31 114  28  49  26  56]
- [  7   4  15 109   2   4  12]
- [  3   4   1   0  57   3   6]
- [  7   1   3   0   1  40   4]
- [  6   3   8   3   6   7  87]]
-Node Classification on random seed  7475 -> 0.603
-Confusion Matrix:
- [[ 59   2  11   9   3  16   4]
- [  5 130   5   1  11   3   1]
- [ 15  21 124  38  14  34  49]
- [ 10   6  27 109   2  10   8]
- [  2   5   7   3  55   1   2]
- [  3   1   1   1   2  56   6]
- [ 10   5   6   6  17  14  70]]
-Node Classification on random seed  7476 -> 0.624
-Confusion Matrix:
- [[ 75   4   1   0   7   7  19]
- [ 10 128   3   2   3   1   0]
- [ 18  15 132  50  32  21  48]
- [  9   1  19 112   3   5   8]
- [  2   5   4   4  57   1   2]
- [  4   1   1   3   0  38  13]
- [ 12   2   4  11   6  15  82]]
-Node Classification on random seed  7477 -> 0.598
-Confusion Matrix:
- [[ 60   3   0   4   5  13  16]
- [  6 145   9   4  11   2   6]
- [ 22  21 141  24  45  36  29]
- [  7   3  25  98  12  12   7]
- [  2   5   8   0  55   1   2]
- [  4   0   1   5   1  41   3]
- [  4   2   7   6  14  15  58]]
-Node Classification on random seed  7478 -> 0.611
-Confusion Matrix:
- [[ 74   2   6   5   2  15   9]
- [  4 116   6   5   5   1   2]
- [ 31  21 151  38  23  22  39]
- [ 13   2  13 102   2   5  19]
- [  1  11   7   2  57   0   2]
- [ 11   3   2   2   0  35  10]
- [ 15   2  14   2   6   9  76]]
-Node Classification on random seed  7479 -> 0.616
-Confusion Matrix:
- [[ 61   2   4   5   6  14  16]
- [  1 136   4   0  16   3   1]
- [ 15  26 138  33  27  25  32]
- [ 10   4  20 109   8   7  14]
- [  1   5   5   4  55   0   2]
- [ 12   2   5   1   1  38   4]
- [ 12   3  16   1   6  11  79]]
-Node Classification on random seed  7480 -> 0.586
-Confusion Matrix:
- [[ 85   4   3   7   6   5   2]
- [  5 119  15   2  14   2   3]
- [ 29  15 116  35  31  24  42]
- [ 32   4   9  98   2  11   4]
- [  2   3   2   3  55   0   3]
- [  6   3   3   1   1  51   4]
- [ 15   4   9  22   8  19  62]]
-Node Classification on random seed  7481 -> 0.603
-Confusion Matrix:
- [[ 67   0   4   8   5   7  13]
- [  4 119   5   1  17   5   7]
- [ 27  24 137  31  17  27  36]
- [ 17   4  18 105   6   4   9]
- [  2   4   6   1  60   0   1]
- [  9   1   2   0   1  42   6]
- [ 28   2   9   7  15   7  73]]
-Node Classification on random seed  7482 -> 0.634
-Confusion Matrix:
- [[ 79   2   3   1   1   5  14]
- [  1 125   9   1   8   3   5]
- [ 35  17 154  34  23  24  22]
- [ 16   3  14  95   8   7  19]
- [  2   4   2   1  61   6   2]
- [  1   1   2   0   1  43  18]
- [  8   2  17   3   9  12  77]]
-Node Classification on random seed  7483 -> 0.61
-Confusion Matrix:
- [[ 73   3   3   4   3  21   3]
- [  2 127   5   0   1   7   5]
- [ 22  18 137  44  19  25  43]
- [ 13   5   8 115   5   6  16]
- [  1  12   7   0  54   0   5]
- [  8   1   5   4   1  40   5]
- [  3   4  16  11   9  17  64]]
-Node Classification on random seed  7484 -> 0.612
-Confusion Matrix:
- [[ 68   2   2   1   7  21  16]
- [  6 112   2   1  12   2   5]
- [ 13  33 155  25  33  27  41]
- [  8  11   8  93   4   7  16]
- [  0   8   3   2  57   0   3]
- [  7   1   1   0   0  39   3]
- [ 10  10   3   3  13  18  88]]
-Node Classification on random seed  7485 -> 0.621
-Confusion Matrix:
- [[ 65   2   2  12   5  16   8]
- [  3 121   9   0   5   3  12]
- [ 17  16 144  49  23  34  23]
- [ 10   3  12 112  11   5  11]
- [  1   4   2   2  61   1   1]
- [  8   1   0   2   0  49   6]
- [ 12   2   5   8  13  20  69]]
-Node Classification on random seed  7486 -> 0.6
-Confusion Matrix:
- [[ 70   2   7   9   7  13   4]
- [  4 138   3   4   3   2   7]
- [ 48  17 108  36  35  24  39]
- [  5   3  12 101  12   6   9]
- [  0  11   4   1  60   1   3]
- [  1   1   3   1   2  50   5]
- [ 12   1   7  12  10  14  73]]
-Node Classification on random seed  7487 -> 0.621
-Confusion Matrix:
- [[ 61   4   4   5   8   6  11]
- [ 12 124   4   5   4   2   2]
- [ 16  18 133  28  28  37  56]
- [  6   4  15 107   2   2  17]
- [  1  11   3   3  64   1   1]
- [  8   2   2   3   1  42   6]
- [  9   3   2   5  10  12  90]]
-Node Classification on random seed  7488 -> 0.586
-Confusion Matrix:
- [[ 63   3  15   4   2  11   9]
- [  6 116   5   5   5   5   5]
- [ 24  10 113  60  27  45  46]
- [  4   4  16 127   2   8  10]
- [  2   5   1   3  53   2   5]
- [  2   1   2   6   3  44   2]
- [ 14   3   5   5   5  17  70]]
-Node Classification on random seed  7489 -> 0.616
-Confusion Matrix:
- [[ 88   0   2   6   2  10   6]
- [  3 113   4   3   7   6   5]
- [ 26  15 134  34  37  13  27]
- [ 16   4  13  96   6   5  22]
- [  2   2   3   7  66   1   2]
- [  3   2   0   1   1  57   7]
- [ 17   6   5  20  22  11  62]]
-Node Classification on random seed  7490 -> 0.614
-Confusion Matrix:
- [[ 73   3  12   3   2   8   5]
- [  9 131  11   0   3   0   3]
- [ 18  39 121  17  36  43  20]
- [  7   5  16 104   7   5   9]
- [  0   7   6   2  78   0   2]
- [  9   4   7   3   0  36   3]
- [  7  11  11   7   5  21  71]]
-Node Classification on random seed  7491 -> 0.647
-Confusion Matrix:
- [[ 84   2   2   2   4   9   9]
- [ 10 135   2   4   2   4   4]
- [ 11  35 145  30  26  22  28]
- [  4   6  18 116   9   5  10]
- [  3  12   4   2  57   1   1]
- [  2   0   0   0   4  36  14]
- [ 13   6   9   8   4  12  74]]
-Node Classification on random seed  7492 -> 0.593
-Confusion Matrix:
- [[ 63   2   4   2  10  23   8]
- [  9 116  10   1   7   2   5]
- [ 21  17 142  39  31  19  58]
- [ 14   1  16 100   3   8  11]
- [  1   5   6   0  63   0   7]
- [  6   1   1   0   1  41   6]
- [ 17   3   9   1   6  16  68]]
-Node Classification on random seed  7493 -> 0.641
-Confusion Matrix:
- [[ 79   3   7   0   2   0  17]
- [  7 150   5   1   7   0   6]
- [ 21  26 131  35  47   9  27]
- [  7   2  13  95  10   4  17]
- [  3   7   3   1  62   0   1]
- [  5   3   3   1   1  47   6]
- [ 17   1  18   3   6   7  77]]
-Node Classification on random seed  7494 -> 0.64
-Confusion Matrix:
- [[ 71   3   9   1   5  14   7]
- [  3 122   7   1   9   2   8]
- [ 23  15 165  17  30  16  35]
- [ 13   5  14  95  18   5  14]
- [  1   4   3   2  65   0   4]
- [  3   0   4   1   3  55   2]
- [ 10   0  15   8   6  20  67]]
-Node Classification on random seed  7495 -> 0.556
-Confusion Matrix:
- [[ 63   1   6   4   2  15  22]
- [  6 129   6   4  12   7   4]
- [ 37  23 116  29  26  32  42]
- [ 22   1  15  80   4   9  15]
- [  6   6   1   0  51   1   0]
- [ 13   0   1   3   4  43   3]
- [ 19   4  14   4   8  13  74]]
-Node Classification on random seed  7496 -> 0.613
-Confusion Matrix:
- [[ 65   2   5   5   5  19   7]
- [  2 131   5   1   5   1   2]
- [ 16  24 156  43  29  26  22]
- [ 22   8   9  97   4   8   8]
- [  1   5   3   1  69   2   2]
- [  4   1   1   8   0  41   3]
- [ 12   8   9  10  13  26  54]]
-Node Classification on random seed  7497 -> 0.616
-Confusion Matrix:
- [[ 76   3   3   3   4   5  12]
- [  3 125  11   1   0   6   4]
- [ 23  20 127  47  14  39  42]
- [ 14   9  20  87   1   7  18]
- [  2   1   4   2  63   1   1]
- [  4   3   1   1   1  47  11]
- [  7   4   8   4   4  16  91]]
-Node Classification on random seed  7498 -> 0.609
-Confusion Matrix:
- [[ 67   1   8   2   6  13  15]
- [  3 120   5   2   4   9   3]
- [ 27  28 136  35  40  28  20]
- [  7   4  32  95   3   5   6]
- [  2   6   1   0  72   3   2]
- [  6   1   3   0   1  49   4]
- [  5   3  14   9   6  19  70]]
-Node Classification on random seed  7499 -> 0.643
-Confusion Matrix:
- [[ 64   7   2   3   4  14   7]
- [  6 116   3   3  14   2   6]
- [ 31  15 154  30  19  22  43]
- [ 12   7   8 112   8   6   7]
- [  3   2   4   4  59   2   3]
- [  3   1   2   1   0  50   4]
- [ 14   4   5   6   4  16  88]]
-Node Classification on random seed  7500 -> 0.6
-Confusion Matrix:
- [[ 84   2   1   2   1  16   9]
- [  4 126   4   6   4   2   2]
- [ 23  18 117  38  20  45  41]
- [  9   4  11  93   5  16  20]
- [  3   6   5   3  68   1   6]
- [  5   0   1   2   1  44   5]
- [ 16   2   4   7   8  22  68]]
-Node Classification on random seed  7501 -> 0.599
-Confusion Matrix:
- [[ 75  10   6  11   4   9   4]
- [  1 124   7   3  11   3   2]
- [ 22  37 128  18  29  24  42]
- [ 18   4  13 106   3   4  13]
- [  1   5   6   2  61   0   0]
- [ 10   2   2   1   1  38   1]
- [ 16   3  10   9  12  22  67]]
-Node Classification on random seed  7502 -> 0.644
-Confusion Matrix:
- [[ 58   0   8   5   4  13  16]
- [  2 131   1   8   7   2   3]
- [ 12  25 161  28  28  20  44]
- [ 10   3  18 105   6   7  14]
- [  1   5   0   1  59   1   2]
- [  2   2   2   0   1  34  22]
- [  4   3   7   4   3  12  96]]
-Node Classification on random seed  7503 -> 0.579
-Confusion Matrix:
- [[ 57   2   3   4   3  13  21]
- [  5 126  11   0  16   1   5]
- [ 18  20 133  36  30  24  45]
- [  4   3  12 111   5   9  13]
- [  1  10   1   1  53   0   5]
- [  2   3   2   1   2  35  13]
- [ 12   4   9  11  22  19  64]]
-Node Classification on random seed  7504 -> 0.592
-Confusion Matrix:
- [[ 52   5   8   8   6  14   3]
- [  4 135   5   0   6   3  13]
- [ 12  24 149  48  25  26  36]
- [ 15   5  19  76  12  12  12]
- [  2   2   3   1  71   1   1]
- [  3   1   2   1   0  40  10]
- [  8   7  12   8   7  18  69]]
-Node Classification on random seed  7505 -> 0.606
-Confusion Matrix:
- [[ 77   1   3  14   5  18   8]
- [  4 124   2   1  10   4   6]
- [ 30  33 128  32  27  11  42]
- [  4   1  15 122   7  10  20]
- [  1   7   5   2  57   0   2]
- [  7   2   8   0   0  35   5]
- [ 16   6  10   2   4   9  63]]
-Node Classification on random seed  7506 -> 0.598
-Confusion Matrix:
- [[ 76   3   5   3   4  11   1]
- [  5 136   3   2   6   4   1]
- [ 30  23 149  34  29  27  43]
- [ 24   8  15  89   4  15   4]
- [  0  10   0   0  45   3   3]
- [ 11   1   2   0   1  40   3]
- [ 21   7  12   6   6  12  63]]
-Node Classification on random seed  7507 -> 0.643
-Confusion Matrix:
- [[ 64   2   4   2   1   5  11]
- [  4 143   2   7  11   2   3]
- [ 20  36 144  35  26  16  51]
- [  5   5  15 116   2   4  11]
- [  3   1   3   3  59   0   5]
- [  5   2   4   0   1  43   4]
- [  5   3  10   5   5  18  74]]
-Node Classification on random seed  7508 -> 0.679
-Confusion Matrix:
- [[ 72   4   2   3   2  11   6]
- [  4 130   3   3   3   4   4]
- [ 16  24 153  29  21  21  38]
- [ 10   1  10 118   7   8  10]
- [  5   7   3   0  57   1   1]
- [  3   4   1   3   2  49   3]
- [ 10   2  10   3   2  17 100]]
-Node Classification on random seed  7509 -> 0.607
-Confusion Matrix:
- [[ 73   7   3   3   1  16  13]
- [  1 121  13   3   2   1   3]
- [ 25  10 136  38  34  30  29]
- [ 19   0  19  96   2  14  16]
- [  2   4   9   0  50   2   2]
- [  9   0   0   0   0  51   7]
- [  6   7  16   2   8  17  80]]
-Node Classification on random seed  7510 -> 0.616
-Confusion Matrix:
- [[ 66   0   5  12   2   6   7]
- [  2 121   7   7  17   1   5]
- [ 34  23 138  43  25  10  35]
- [ 17   1  18 104   2   3  19]
- [  2   3   3   2  55   0   4]
- [  3   1   1   3   0  52   4]
- [  9   1  10  10  13  14  80]]
-Node Classification on random seed  7511 -> 0.642
-Confusion Matrix:
- [[ 56   6   5   7   2   8  10]
- [  2 143   6   0   9   2   6]
- [ 12  17 165  30  15  34  31]
- [ 12   4  18 107   3   6  11]
- [  2   6   4   5  64   0   1]
- [  1   1   6   1   1  44   6]
- [ 13   5  12   6  10  22  63]]
-Node Classification on random seed  7512 -> 0.643
-Confusion Matrix:
- [[ 77   3   5  11   4   7  13]
- [  1 121  14   2  11   3   2]
- [ 17  16 144  30  33  23  35]
- [  7   1   5 122   7  11  18]
- [  1   4   1   1  60   0   4]
- [  0   0   2   4   2  43   6]
- [  8   0  11  12  10  12  76]]
-Node Classification on random seed  7513 -> 0.601
-Confusion Matrix:
- [[ 64   5   3  11   5  14   5]
- [  5 131   9   8  12   6   1]
- [ 17  19 131  32  23  37  35]
- [  8   5  24  86   5   8  16]
- [  1   8   6   3  57   2   2]
- [  7   0   5   3   1  48   6]
- [ 12   5   7   3   4  11  84]]
-Node Classification on random seed  7514 -> 0.636
-Confusion Matrix:
- [[ 73   0   3   3   0  14   8]
- [  2 118   5   5   3   3   3]
- [ 20  26 163  23  27  24  29]
- [ 11   3  20 106   8   9  11]
- [  3  13   6   1  52   0   3]
- [  4   0   1   3   1  45   4]
- [  8   2   8   4  12  31  79]]
-Node Classification on random seed  7515 -> 0.622
-Confusion Matrix:
- [[ 76   2   2   3   6  14   5]
- [  0 130  11   8   2   5   7]
- [ 17  17 125  37  29  14  53]
- [ 22   6   9 105   4  11  12]
- [  1   7   5   3  66   2   1]
- [  3   3   1   0   0  47   2]
- [ 11   9   9   3   6  16  73]]
-Node Classification on random seed  7516 -> 0.594
-Confusion Matrix:
- [[ 67   1   6   5   6  10   8]
- [  2 127   4   1   9   6   5]
- [ 34   8 148  33  34  32  42]
- [ 23   4  14  89   2   3  19]
- [  0   4   4   4  58   2   1]
- [  5   3   4   0   2  40   3]
- [  7   4  16   5   6  25  65]]
-Node Classification on random seed  7517 -> 0.595
-Confusion Matrix:
- [[ 60   6   1   4   6   8  25]
- [  1 143   2   2  11   1   0]
- [ 13  17 134  37  34  35  42]
- [ 11   4  27 100  11   9   3]
- [  0   5   4   4  60   0   1]
- [  9   0   3   0   0  37   2]
- [  6   6   8   8  15  24  61]]
-Node Classification on random seed  7518 -> 0.622
-Confusion Matrix:
- [[ 61   2   3   4   2  15  16]
- [  8 128   4   1  12   5   0]
- [ 19  17 150  50  19  32  23]
- [  1   7  12 109   2   7  23]
- [  0   9   4   3  56   1   3]
- [ 21   0   3   0   0  42   3]
- [  7   4  10   3   8  15  76]]
-Node Classification on random seed  7519 -> 0.643
-Confusion Matrix:
- [[ 80   0   0   9   1   8   7]
- [  4 135   8   5   9   2   2]
- [ 23  19 162  10  22  34  32]
- [ 13   4  25 106   2   7  10]
- [  3   6   6   2  50   3   1]
- [  7   2   1   5   0  43   2]
- [ 23   1   9   7   3  20  67]]
-Node Classification on random seed  7520 -> 0.595
-Confusion Matrix:
- [[ 69  10   3   7   7  17   2]
- [  1 111  15   5   5   1  10]
- [ 31  14 128  38   8  38  38]
- [ 16   2  16 104   4  10   9]
- [  0   8   2   1  60   3   3]
- [  5   1   3   2   1  47   5]
- [ 14   4  11  10   4  21  76]]
-Node Classification on random seed  7521 -> 0.636
-Confusion Matrix:
- [[ 75   2   4   8   1  12  14]
- [  5 145   3   1   5   1   1]
- [ 26  19 142  40  17  29  33]
- [ 10   1  17 115   2  10  15]
- [  1   6   7   5  54   1   0]
- [  6   1   2   2   0  47   6]
- [ 15   1   9   7   5  14  58]]
-Node Classification on random seed  7522 -> 0.647
-Confusion Matrix:
- [[ 61   4   2   7   7   8  13]
- [  6 126   3   3   8   2   3]
- [ 11  12 174  43  27  26  36]
- [  5   3   9 113   7   9  12]
- [  2   3   5   4  64   0   2]
- [  3   1   1   0   3  49   3]
- [ 12   3   6  12  12  15  60]]
-Node Classification on random seed  7523 -> 0.61
-Confusion Matrix:
- [[ 74   2   4   4   5  11  19]
- [  6 156   4   2   3   1   4]
- [ 25  15 108  51  47  18  27]
- [ 16   2  19 100   9   8   6]
- [  1   6   2   1  63   0   2]
- [  4   1   8   0   0  52   6]
- [ 10   3  17   3   5  13  57]]
-Node Classification on random seed  7524 -> 0.589
-Confusion Matrix:
- [[ 54   5   1   3   5  11  17]
- [  5 124   7   5   3   8  11]
- [ 28  24 130  42  26  35  43]
- [ 16   3  17 114   6   5   6]
- [  3   4   3   5  54   0   2]
- [  4   0   0   0   1  54   5]
- [  8   1   3  21   4  15  59]]
-Node Classification on random seed  7525 -> 0.624
-Confusion Matrix:
- [[ 78   1   3   3   4  15   7]
- [  1 124   6   0   7   3   4]
- [ 14  13 147  40  34  16  43]
- [ 16   6  11  98  15   6   7]
- [  1   4   3   3  57   3   4]
- [  4   2   3   7   4  42   5]
- [  5   1  10  16   8  18  78]]
-Node Classification on random seed  7526 -> 0.641
-Confusion Matrix:
- [[ 75   1   1   1   4  10  11]
- [  4 145   4   2   6   1   9]
- [ 26  20 136  42  24  18  31]
- [  6   6   7 112   7  11  17]
- [  4   3   3   1  68   0   3]
- [  9   2   0   3   1  33   9]
- [ 18   4  11   5   7   7  72]]
-Node Classification on random seed  7527 -> 0.594
-Confusion Matrix:
- [[ 70   1   5   7   1  12  10]
- [  3 121  18   2   8   0   5]
- [ 19  23 137  37  24  33  48]
- [  6   2  21  92   5  18   9]
- [  1  10   3   1  63   0   4]
- [  5   1   0   1   0  42   4]
- [ 14   6   6   7   3  23  69]]
-Node Classification on random seed  7528 -> 0.613
-Confusion Matrix:
- [[ 73   1   3   3   2  12  15]
- [  5 126   1   0  11   4   4]
- [ 23  34 141  20  37  23  38]
- [ 10   4  18  99   8   8  17]
- [  2  10   5   0  59   0   1]
- [  9   1   0   0   1  36  11]
- [ 15   2   5   4  10  10  79]]
-Node Classification on random seed  7529 -> 0.61
-Confusion Matrix:
- [[ 85   1   1   2   3   4   6]
- [  1 126   7   4   3   4   1]
- [ 32  20 122  37  41  30  36]
- [  6   5  25  99   5   8  12]
- [  0   6   1   5  72   1   2]
- [ 12   1   4   0   0  42  14]
- [  5   5   9   4  11  16  64]]
-Node Classification on random seed  7530 -> 0.647
-Confusion Matrix:
- [[ 65   2   3   4   3   6  13]
- [ 10 130   5   7   2   3   1]
- [ 18  23 166  31  24  19  25]
- [  8   2  26 114   2  13  13]
- [  2   5   3   4  55   1   3]
- [  6   3   2   2   2  46   4]
- [  8   3  16   8   4  14  71]]
-Node Classification on random seed  7531 -> 0.626
-Confusion Matrix:
- [[ 56   3   4   3   3  18  14]
- [  1 115  11   3  14   4   9]
- [ 18  17 149  30  16  20  63]
- [  9   3  10 103   6   3  20]
- [  1   3   2   1  64   2  10]
- [  2   2   2   1   3  49   3]
- [  3   7   9   1   6  14  90]]
-Node Classification on random seed  7532 -> 0.573
-Confusion Matrix:
- [[ 61   8   1   3   7   8  14]
- [ 13 101   3   1  15   6   4]
- [ 28  33 139  26  25  33  38]
- [ 18   6  21 102   3   7   8]
- [  1   4   6   1  56   7   0]
- [ 17   0   1   3   0  47   3]
- [ 18   2   6   5   7  17  67]]
-Node Classification on random seed  7533 -> 0.615
-Confusion Matrix:
- [[ 71   2  16   8   7   5   8]
- [  4 120   7   4   4   5   2]
- [ 24  11 157  45  17  16  45]
- [ 15   1  13  96   5   8  11]
- [  1   3   8   0  52   1   1]
- [  9   1   4   1   0  49   4]
- [ 18   3  22   3   8  15  70]]
-Node Classification on random seed  7534 -> 0.593
-Confusion Matrix:
- [[ 48   5   2  10   1  23  14]
- [  9 132   5   4  10   6   3]
- [ 20  10 144  34  33  13  44]
- [ 12   1  14 101   4  12  15]
- [  7   5   1   3  60   0   2]
- [  7   5   1   4   6  33  10]
- [ 11   5   7  15   2  12  75]]
-Node Classification on random seed  7535 -> 0.621
-Confusion Matrix:
- [[ 65   3   1   2   3  12  13]
- [  9 136   6   4   6   4   3]
- [ 26  14 149  36  14  22  47]
- [ 11   4  13 101  11  11  12]
- [  3   7   4   0  65   3   5]
- [  9   1   2   1   3  35   5]
- [  8   3   5   4   5  24  70]]
-Node Classification on random seed  7536 -> 0.628
-Confusion Matrix:
- [[ 84   3   1   5   5   7  14]
- [  3 137   2   2   3   6  10]
- [ 12  27 133  37  21  30  32]
- [  9   1  12  97   5   6  21]
- [  0  13   1   4  52   2   4]
- [  0   2   3   1   1  44  11]
- [  7   1  11  13  10  14  81]]
-Node Classification on random seed  7537 -> 0.601
-Confusion Matrix:
- [[ 71   3   3   4   3  10   7]
- [  6 125   3   1   2   3   4]
- [ 34  14 138  26  18  25  55]
- [ 13   6  13  90  17  10  18]
- [  1   3   3   5  52   1   4]
- [  7   0   4   0   1  52   6]
- [ 16   5   1  15   7  22  73]]
-Node Classification on random seed  7538 -> 0.642
-Confusion Matrix:
- [[ 79   3   3   2   5  10   6]
- [  6 124   7   3   6   7   2]
- [ 22  24 151  34  18  14  42]
- [  7   5   8  99  11   3  18]
- [  0   5   2   0  72   2   6]
- [ 10   1   3   1   0  49   3]
- [ 17   3   9   5   7  18  68]]
-Node Classification on random seed  7539 -> 0.647
-Confusion Matrix:
- [[ 79   1   8   5   7  16   1]
- [  5 139   3   2   6   4   2]
- [ 19  14 169  24  25  24  29]
- [ 22   4  13 108   1   9   2]
- [  2   7   5   1  56   2   4]
- [ 13   0   0   1   1  30  10]
- [ 17   0  11  15   6  12  66]]
-Node Classification on random seed  7540 -> 0.607
-Confusion Matrix:
- [[ 63   2   7   6   4  11  13]
- [  2 124  12   1   6   6   0]
- [ 18  22 136  41  31  20  39]
- [  7  12   7 101  14   5  13]
- [  0   4   8   3  62   1   4]
- [ 14   0   3   2   0  39   3]
- [  9   3   7   6  10  17  82]]
-Node Classification on random seed  7541 -> 0.595
-Confusion Matrix:
- [[ 87   1   9   8   6  13   4]
- [  3 128   6   3  11   1   2]
- [ 23  23 119  35  31  27  30]
- [ 17   5  19  91   4   8  15]
- [  0   5   5   1  61   3   3]
- [  2   1   5   1   0  48   4]
- [  6   4  19   9  10  23  61]]
-Node Classification on random seed  7542 -> 0.628
-Confusion Matrix:
- [[ 76   0   9   7   2  14  10]
- [  5 124   4   2   6   2   0]
- [ 27  19 130  45  30  18  43]
- [ 11   1  13 120   4   4  10]
- [  0   8   2   4  50   1   2]
- [ 10   1   3   0   0  43   5]
- [  5   4  14   4  14   9  85]]
-Node Classification on random seed  7543 -> 0.664
-Confusion Matrix:
- [[ 90   2   3   2   6   9   9]
- [  7 124   9   1  10   0   1]
- [ 20  11 155  30  29  15  28]
- [ 17   3  18 103  10   6  13]
- [  1   2   3   0  64   3   2]
- [  7   1   3   4   1  43   6]
- [  9   2   9   5   9  10  85]]
-Node Classification on random seed  7544 -> 0.581
-Confusion Matrix:
- [[ 60   5   0   4   6  22  10]
- [  6 120   9   1   3   7   2]
- [ 43  16 119  47  27  33  19]
- [ 15   1  16 104   3   8  14]
- [  2   5   4   3  59   0   2]
- [  7   1   4   3   1  42  12]
- [ 12   3   5  10   8  20  77]]
-Node Classification on random seed  7545 -> 0.593
-Confusion Matrix:
- [[ 55   4   6  13   6  13   8]
- [  9 103  13   5   5   0   5]
- [ 31  23 153  15  21  17  49]
- [ 17  12  13  94   5   3  22]
- [  1   5   4   1  64   2   2]
- [ 11   4   8   0   0  39   8]
- [ 14   5  14   3   5   5  85]]
-Node Classification on random seed  7546 -> 0.634
-Confusion Matrix:
- [[ 69   1   3   4   8   8  17]
- [  2 142   3   4   5   6  10]
- [ 20  24 135  53  27  10  31]
- [  9   4   9  98   7   6  23]
- [  0   5   3   1  60   0   2]
- [  7   1   3   0   1  37   7]
- [  9   9   6   5   3  10  93]]
-Node Classification on random seed  7547 -> 0.617
-Confusion Matrix:
- [[ 69   6  10   8   2  16   6]
- [  3 114   6   2   7   3   3]
- [ 22  28 158  33  31  18  32]
- [  8   9  22 102   5   8   8]
- [  1   5   3   1  59   0   3]
- [  3   1   3   4   0  46   6]
- [ 14   2   7   9   7  18  69]]
-Node Classification on random seed  7548 -> 0.638
-Confusion Matrix:
- [[ 66   3   9   7   4  14   9]
- [ 11 140   4   6   3   5   0]
- [ 16  28 148  44  13  19  34]
- [ 11  10  13 104   7   7   6]
- [  0  10   6   1  60   1   1]
- [  9   1   2   1   0  43   6]
- [  7   1   4   6   7  16  77]]
-Node Classification on random seed  7549 -> 0.633
-Confusion Matrix:
- [[ 66   4   0   8   1  12  11]
- [  2 143   3   4   8   4   2]
- [ 23  21 141  36  33  11  39]
- [  4   7  15 105   6   7  16]
- [  6  10   2   0  46   1   0]
- [  6   1   1   1   1  53   6]
- [ 16   6   3  15   6   9  79]]
-Node Classification on random seed  7550 -> 0.619
-Confusion Matrix:
- [[ 60   2   6   7   4  13  10]
- [  7 125   7   5   6   6   3]
- [ 33  18 153  30  12  31  31]
- [  9   4  15  91   8   4  26]
- [  1   3   3   1  62   1   3]
- [  4   0   0   1   4  51   3]
- [ 12   5   9  14   1  19  77]]
-Node Classification on random seed  7551 -> 0.627
-Confusion Matrix:
- [[ 60   5   4   9   1  13  14]
- [ 11 115  10   3   4   5   5]
- [ 27  14 154  40  17  25  37]
- [ 14   3   8 111   1   6   6]
- [  2  10   2   2  63   1   1]
- [  7   1   1   3   0  49   7]
- [ 12   3   3   9   8  19  75]]
-Node Classification on random seed  7552 -> 0.565
-Confusion Matrix:
- [[ 67   1   4   5   3  12  18]
- [  5 129   8   6   1   2   5]
- [ 20  15 127  34  41  18  54]
- [  6   1  31  66  19  10  11]
- [  0   8   6   2  71   3   4]
- [  2   2   4   5   1  48   4]
- [  7   3  13  12  10  19  57]]
-Node Classification on random seed  7553 -> 0.608
-Confusion Matrix:
- [[ 66   3   4   3   1  11  16]
- [  0 135   7   4   3   3  10]
- [ 31  25 104  54  29  14  44]
- [ 11   4  11 116   5   3  12]
- [  0   8   1   3  65   1   5]
- [  4   4   3   1   0  49   5]
- [  6   2  12  12   0  17  73]]
-Node Classification on random seed  7554 -> 0.601
-Confusion Matrix:
- [[ 68   1   3   2   4  21  13]
- [  1 135   9  11  11   3   1]
- [ 25  15 130  41  19  29  46]
- [ 10   5  24 100   3   5  16]
- [  4   3   3   3  50   4   1]
- [  5   2   2   0   0  48   4]
- [  3   2   6   6  13  20  70]]
-Node Classification on random seed  7555 -> 0.596
-Confusion Matrix:
- [[ 85   5   3   4   6   7  13]
- [  3 126   7   5   4   4   6]
- [ 36  23 153  39  14  10  33]
- [ 20   4  24  83   5   5  20]
- [  3  11   1   0  47   0   3]
- [  9   0   2   1   0  37  10]
- [ 26   9  12   6   1  10  65]]
-Node Classification on random seed  7556 -> 0.638
-Confusion Matrix:
- [[ 60   3   2   5   6  13   5]
- [  5 116   6   3  19   4   3]
- [ 21  18 151  49  23  25  32]
- [  9   4   4 129   5   4   7]
- [  1   4   2   1  60   1   2]
- [  3   2   2   5   1  49   3]
- [  5   2  16   6   9  22  73]]
-Node Classification on random seed  7557 -> 0.624
-Confusion Matrix:
- [[ 72   2   6   9   0  16  13]
- [ 11 119   4   1   7   0   0]
- [ 14  30 159  24  22  39  34]
- [ 20   2  15  99   3   5  11]
- [  0   6   5   3  53   1   1]
- [  5   1   1   2   4  53   5]
- [  6   5   7   7   7  22  69]]
-Node Classification on random seed  7558 -> 0.592
-Confusion Matrix:
- [[ 59   4   7   6   1  20   6]
- [  3 120  13   0   6   1   2]
- [ 33  12 130  37  48  21  42]
- [ 10   4  20 114   8   8  14]
- [  1   7   3   0  56   1   1]
- [  4   1   3   3   0  43   9]
- [ 11   6   4   8   7  13  70]]
-Node Classification on random seed  7559 -> 0.645
-Confusion Matrix:
- [[ 69   3  10   3   0   7  13]
- [  6 118   6   0   5   0   9]
- [ 28  28 160  17  28  16  39]
- [ 10   7  12 110   8   5  10]
- [  3   7   9   0  63   0   4]
- [ 12   1   1   2   1  53   5]
- [  3   3  10   7   8   9  72]]
-Node Classification on random seed  7560 -> 0.616
-Confusion Matrix:
- [[ 59   3   2  12   3  28  11]
- [  5 131   5   0  13   4   2]
- [ 20  18 147  33  36  19  26]
- [ 14   3  11  97   5   9  16]
- [  4   4   4   1  57   0   0]
- [  3   1   0   3   1  46   8]
- [ 10   2  13   3   8  21  79]]
-Node Classification on random seed  7561 -> 0.609
-Confusion Matrix:
- [[ 76   2   2   4   5   7   4]
- [  4 116  10   1  11   6   1]
- [ 37  19 140  32  38  22  34]
- [ 12   2  17  95   6  14  10]
- [  1   3   6   0  62   1   5]
- [  3   1   2   2   0  49   6]
- [  9   7  10   3   9  23  71]]
-Node Classification on random seed  7562 -> 0.622
-Confusion Matrix:
- [[ 94   2   1   9   3   7   1]
- [  1 117   2   4  11   2   9]
- [ 31  11 141  42  33  16  33]
- [ 22   5   3 101   3   2  12]
- [  1   6   0   1  61   1   7]
- [ 10   1   4   2   1  40   7]
- [ 33   5   5   5  12  12  68]]
-Node Classification on random seed  7563 -> 0.594
-Confusion Matrix:
- [[ 65   3   4   4   5  17  21]
- [  0 115   8   1   4   3   5]
- [ 39  22 142  12  22  26  40]
- [  7   5  23  94   1  11  22]
- [  3   8   8   1  63   1   1]
- [  6   2   1   1   4  41   2]
- [ 18   7   6   4  10  18  74]]
-Node Classification on random seed  7564 -> 0.575
-Confusion Matrix:
- [[ 64   2   6   6   9  20   6]
- [  5 127   4   8   3   1   4]
- [ 23  25 112  34  64  24  28]
- [  6   8  19 110  11   6  10]
- [  1   3   5   0  56   0   4]
- [  3   2   2   3   5  50   0]
- [  8   1  10  13   1  32  56]]
-Node Classification on random seed  7565 -> 0.601
-Confusion Matrix:
- [[ 58   3   9  10   2  19  13]
- [  7 131   5   5   8   7   3]
- [ 29  27 140  41  20  23  37]
- [  9   1  20  94   4   8   9]
- [  7   5   5   3  59   0   4]
- [  5   1   3   3   0  47   1]
- [ 11   6   5   7   1  13  72]]
-Node Classification on random seed  7566 -> 0.597
-Confusion Matrix:
- [[ 79   0   4   6   2   8   4]
- [  9 120  12   0   6   3  14]
- [ 26  25 108  40  31  18  55]
- [ 12   3  14 105   0   5  21]
- [  5   4   5   4  61   1   2]
- [  7   0   3   1   1  47   2]
- [ 12   6   9   1   3  19  77]]
-Node Classification on random seed  7567 -> 0.655
-Confusion Matrix:
- [[ 74   2   5   5   4   7  17]
- [  5 125   5   4   6   4   5]
- [ 12  12 154  22  23  22  55]
- [  9   4  16 119   6   4  20]
- [  2   9   6   1  51   1   3]
- [  7   0   0   2   0  43   4]
- [  3   2   6   4   5  16  89]]
-Node Classification on random seed  7568 -> 0.595
-Confusion Matrix:
- [[ 84   0   3   5   3  14  10]
- [  3 113   9   1  16   0   7]
- [ 36  15 148  27  33  20  48]
- [  5   8   8  98   8   1  29]
- [  1   4   7   2  50   1   3]
- [  2   0   1   1   0  47   4]
- [  9   5  18  13   8  17  55]]
-Node Classification on random seed  7569 -> 0.582
-Confusion Matrix:
- [[ 70   2  11   2   5  13   8]
- [  6 126   5   1   3   1   3]
- [ 28  15 123  33  52  25  38]
- [ 18   5  17  95   9   7  14]
- [  4   7   4   0  60   0   1]
- [  4   2   5   6   0  47   3]
- [ 10   3   8   4   9  27  61]]
-Node Classification on random seed  7570 -> 0.624
-Confusion Matrix:
- [[ 71   2   3   4   8  17   8]
- [  7 129   2   2   4   3   3]
- [ 16  30 172  24  21  25  37]
- [ 11   9  17  86   9   9  16]
- [  1   8   2   1  62   5   1]
- [  3   0   4   2   0  44   5]
- [  8   3  13  14   4  15  60]]
-Node Classification on random seed  7571 -> 0.609
-Confusion Matrix:
- [[ 55   0   3  11   2  12   9]
- [  3 108   4   5  11   3  12]
- [ 22  15 149  39  34  27  38]
- [ 13   4  19 110   6   3  14]
- [  1   6   2   2  59   3   2]
- [  5   1   2   2   0  51   5]
- [  9   3   9  10   9  11  77]]
-Node Classification on random seed  7572 -> 0.606
-Confusion Matrix:
- [[ 74   1   2   3   6  19   6]
- [  6 135   5   1   7   1   1]
- [ 28  28 138  48  18  17  34]
- [ 18  10  19  74   9  12  11]
- [  1   4   5   1  56   1   1]
- [  5   1   1   1   2  49   9]
- [ 15   5  11   0   5  16  80]]
-Node Classification on random seed  7573 -> 0.596
-Confusion Matrix:
- [[ 65   5   8   5   7   9   6]
- [  6 140   6   0   5   1   3]
- [ 39  19 126  46  28  14  38]
- [ 10   8  17 102   3   5  20]
- [  2   5   4   0  55   0   3]
- [  9   2   2   3   3  51   4]
- [ 10   9  12   4   9  15  57]]
-Node Classification on random seed  7574 -> 0.606
-Confusion Matrix:
- [[ 77   2   3   3   8   7   6]
- [  3 118   2   6  11   4   6]
- [ 21  16 162  20  39  22  49]
- [ 15   2  25  85  14   8  12]
- [  2   2   4   4  55   0   4]
- [  5   0   6   1   3  34   9]
- [ 10   1   8   1  16  14  75]]
-Node Classification on random seed  7575 -> 0.639
-Confusion Matrix:
- [[ 73   1   7   6   0  12   7]
- [  4 133   3   1   2   2   6]
- [ 24  15 150  47  28  15  47]
- [  9   2  22  91   6  12  11]
- [  1   5   0   1  66   1   0]
- [  0   1   5   0   0  47  12]
- [  3   3   6  12   4  18  79]]
-Node Classification on random seed  7576 -> 0.64
-Confusion Matrix:
- [[ 74   0   1   8   4   6   9]
- [  7 112   4   4   6   3   5]
- [ 23  19 157  39  36  14  40]
- [  6   3  13 117   2   3   8]
- [  1   5   1   2  66   0   2]
- [  8   1   4   3   0  38   9]
- [ 19   5   7  16   0  14  76]]
-Node Classification on random seed  7577 -> 0.616
-Confusion Matrix:
- [[ 80   1  10   6   5  14   7]
- [  2 110   7   3   9   2   3]
- [ 18  12 157  31  32  36  30]
- [  8   2  24  95   6   8  12]
- [  2   9   1   4  54   0   1]
- [  8   4   3   4   3  44   3]
- [ 12   3  10   9   6  14  76]]
-Node Classification on random seed  7578 -> 0.644
-Confusion Matrix:
- [[ 66   3   5   4   3   9  10]
- [  0 134   3   4   9   2   5]
- [ 21  16 159  27  19  37  35]
- [  6   4  21 104   3   4  20]
- [  2  10   6   0  54   0   1]
- [  6   3   0   2   3  39   4]
- [  4   3  13  12   5  12  88]]
-Node Classification on random seed  7579 -> 0.622
-Confusion Matrix:
- [[ 78   1   7   2   2   7  11]
- [  3 122   8   7  10   2   6]
- [ 21  27 117  26  39  30  42]
- [ 10   8   3 120   3   8   7]
- [  2   5   2   0  65   1   1]
- [  6   1   1   6   2  34  11]
- [ 11   1   9   6  10  13  86]]
-Node Classification on random seed  7580 -> 0.648
-Confusion Matrix:
- [[ 51  10   7   9   1  14   9]
- [  2 135   8   4   7   2   3]
- [ 24  12 176  19  17  27  47]
- [ 14   4  15 109   8   2  10]
- [  2   1   8   0  62   0   2]
- [  1   0   3   2   1  50   2]
- [  8   2  12  11   9  13  65]]
-Node Classification on random seed  7581 -> 0.626
-Confusion Matrix:
- [[ 73   5   3   1   6  19   3]
- [  3 140   4   1   7   1   5]
- [ 27  22 135  27  32  27  39]
- [  6   3  20  91   3   6  13]
- [  4  12   1   0  59   0   0]
- [  5   0   4   3   2  46   5]
- [  5   6   8   6  12  18  82]]
-Node Classification on random seed  7582 -> 0.62
-Confusion Matrix:
- [[ 57   7  14   3   1  19   2]
- [  7 128   6   4  11   1   2]
- [ 20  30 142  34  21  27  35]
- [  8   2  13  93   2  10  16]
- [  0   5   5   2  75   0   1]
- [ 16   0   1   0   1  45   1]
- [ 19   1   7   2   5  19  80]]
-Node Classification on random seed  7583 -> 0.589
-Confusion Matrix:
- [[ 75   3   4   4   5  14  15]
- [  5 127   7   8   3   0   1]
- [ 17  29 129  39  37  14  38]
- [ 18   5  15 102   3  14   6]
- [  2  15   1   0  56   0   5]
- [  5   2   2   1   2  39   3]
- [ 14   1   9   9  22  14  61]]
-Node Classification on random seed  7584 -> 0.586
-Confusion Matrix:
- [[ 72   3   2  10   3  13   6]
- [  8 121   1   0   9   3   0]
- [ 22  20  97  29  57  33  45]
- [  6   1  28 108   6   6  15]
- [  0   8   3   3  58   1   7]
- [  7   0   3   2   1  51   3]
- [ 12   4   8   3   9  14  79]]
-Node Classification on random seed  7585 -> 0.604
-Confusion Matrix:
- [[ 77   2   3   9   0   5   5]
- [  5 120  11   7   2   5   3]
- [ 34  19 114  48  21  21  47]
- [  9   1  17 119   4   5   8]
- [  3   9   4   1  65   1   2]
- [  5   2   2   3   0  48  10]
- [ 15   2  10   7   7  22  61]]
-Node Classification on random seed  7586 -> 0.617
-Confusion Matrix:
- [[ 65   1   6   2   2   7  24]
- [  9 131   2   7   4   1   2]
- [ 14  19 158  27  19  34  37]
- [ 24   2  18  82  11  13   5]
- [  2   8   6   4  62   0   1]
- [  7   0   4   0   0  42   8]
- [  9   2  12   6  11  13  77]]
-Node Classification on random seed  7587 -> 0.589
-Confusion Matrix:
- [[ 67   5   5  10   6  16   3]
- [  4 143   5   0   7   3   5]
- [ 36  12 102  45  35  34  45]
- [ 10   2  20 105   7   9   8]
- [  2   9   2   2  62   1   2]
- [  4   4   5   0   3  32   4]
- [ 10   3   5   6   7  10  78]]
-Node Classification on random seed  7588 -> 0.656
-Confusion Matrix:
- [[ 72   3   2   1   4  12  12]
- [  7 134   5  10   4   3   3]
- [ 22  29 164  35  12  20  29]
- [ 15   5  10  95   4   8  10]
- [  2   8   8   0  53   0   5]
- [  2   1   3   1   0  47   4]
- [ 11   3   2  11   9   9  91]]
-Node Classification on random seed  7589 -> 0.599
-Confusion Matrix:
- [[ 80   6   8   3   6   7   9]
- [ 14 127   4   3  10   5   6]
- [ 31  20 137  26  17  36  36]
- [  9   0  15 115   2   3  13]
- [  3   4   3   3  52   1   6]
- [ 12   1   2   1   1  38   8]
- [ 15   1   2  10  15  24  50]]
-Node Classification on random seed  7590 -> 0.635
-Confusion Matrix:
- [[ 66   7   8   5   3  11  12]
- [  5 123   4   0   5   2   5]
- [ 17  28 136  31  34  19  39]
- [ 13   2  10 100   9   9   6]
- [  1  12   0   2  67   0   3]
- [  6   1   2   5   1  48   5]
- [  3   4   6   8   6  16  95]]
-Node Classification on random seed  7591 -> 0.651
-Confusion Matrix:
- [[ 79   6   8   9   0  10   4]
- [  8 130   2   2  10   0   3]
- [ 31  18 148  55  24  11  33]
- [  6   7  11 111  10   4   8]
- [  4   7   3   0  54   0   3]
- [  8   0   3   0   0  49   5]
- [  7   0   9   7   5   8  80]]
-Node Classification on random seed  7592 -> 0.595
-Confusion Matrix:
- [[ 66   1   3  12   9  10   7]
- [  6 113   8   5  11   2   4]
- [ 36   8 133  37  35  23  41]
- [ 13   7  18 101  10   3  10]
- [  1   3   4   2  61   4   6]
- [  7   1   1   2   0  51   0]
- [ 14   2   6   3  14  16  70]]
-Node Classification on random seed  7593 -> 0.625
-Confusion Matrix:
- [[ 74   1   3   2   6  16   9]
- [  5 125   3   6   4   2   7]
- [ 31  24 157  39  13  32  35]
- [  9   2  18  90   0  12  15]
- [  0  12   4   4  60   0   1]
- [  8   1   1   1   2  43   3]
- [  5   7  11   2   1  18  76]]
-Node Classification on random seed  7594 -> 0.598
-Confusion Matrix:
- [[ 73   4   8   7   2   9   9]
- [  1 127   9   1   4   3   8]
- [ 26  26 121  36  31  26  52]
- [ 10   2  14 102   5   4   7]
- [  2  11   3   0  59   2   2]
- [  6   0   4   0   0  41  13]
- [ 16   0  16   6   6  11  75]]
-Node Classification on random seed  7595 -> 0.639
-Confusion Matrix:
- [[ 76   5   7   9   6  13   3]
- [  5 128   3   0  16   3   3]
- [ 19  21 133  31  24  27  39]
- [  7   5   8 104   4   8  15]
- [  1   8   6   1  75   2   2]
- [  6   2   3   1   0  49   5]
- [  9   4   6   3   3  18  74]]
-Node Classification on random seed  7596 -> 0.616
-Confusion Matrix:
- [[ 72   1   4   4   1  10  12]
- [  5 123  13   9   4   9   4]
- [ 23  16 120  44  43  29  29]
- [ 11   1  14 110   6   4   9]
- [  1   2   3   4  64   2   2]
- [  5   2   3   2   0  50   7]
- [ 14   4   7   8   6   7  77]]
-Node Classification on random seed  7597 -> 0.592
-Confusion Matrix:
- [[ 55   4  24   3   1  12   1]
- [  3 113   9   3  11   0   6]
- [ 15  27 139  57  42  26  26]
- [  3   3  16 114   6  16  10]
- [  0   7   3   3  50   1   3]
- [  5   1   1   1   0  50   4]
- [ 10   6  15   6   7  11  71]]
-Node Classification on random seed  7598 -> 0.666
-Confusion Matrix:
- [[ 81   6   1   6   4   6  11]
- [  0 130   1   3   9   1   0]
- [ 25  19 161  32  25   8  36]
- [ 20   1  16 104   3   4   9]
- [  0   6   2   0  63   1   1]
- [  9   5   2   2   4  42   6]
- [ 10  11   3  14   5   7  85]]
-Node Classification on random seed  7599 -> 0.59
-Confusion Matrix:
- [[ 77   5   7   2   5   4   6]
- [ 11 133   1   3   2   2   6]
- [ 29  49 120  32  33  14  38]
- [ 15   8  19  91   2   4   9]
- [  0   8   1   2  59   3   0]
- [  9   5   0   0   1  51   3]
- [ 27   2  13   9   4  17  59]]
-Node Classification on random seed  7600 -> 0.623
-Confusion Matrix:
- [[ 73   2   1   2   2  10   6]
- [  2 138   1   2  12   1   7]
- [ 15  48 136  27  20  23  30]
- [  7  11  27  99   3   1  17]
- [  0  13   0   0  70   0   0]
- [  3   3   1   1   0  49   4]
- [ 10   4  12   7  23  19  58]]
-Node Classification on random seed  7601 -> 0.623
-Confusion Matrix:
- [[ 65   5   3   7   4   7   9]
- [  0 126   7   4  10   2   2]
- [ 21  19 148  33  27  26  38]
- [ 17   0  14 112   2   9  13]
- [  2   9   0   3  60   1   4]
- [  2   3   2   7   0  40   3]
- [ 14   4  11  10  11  12  72]]
-Node Classification on random seed  7602 -> 0.621
-Confusion Matrix:
- [[ 54   2   1   5   5  18  20]
- [  9 122   5   6   2   1   2]
- [ 13  25 144  32  28  24  42]
- [  6   4  17 114   5   8  13]
- [  4   9   5   5  60   4   1]
- [  3   0   2   1   0  49   7]
- [  7   5  12   1   8  12  78]]
-Node Classification on random seed  7603 -> 0.628
-Confusion Matrix:
- [[ 44   4   9   2   5  12  14]
- [  8 140   5   0   5   4   2]
- [ 21  17 141  57  19  10  49]
- [  7   3  15 110   2   7  15]
- [  1   4   1   4  67   4   3]
- [  4   0   3   1   1  49   6]
- [  8   4   8   4   5  19  77]]
-Node Classification on random seed  7604 -> 0.605
-Confusion Matrix:
- [[ 73   2   4   8   5  17   9]
- [  7 133  19   6  10   4   2]
- [ 29  12 140  48  12  20  31]
- [ 14   8  12 102   3   2  13]
- [  4   6   3   1  57   2   2]
- [ 13   0   5   2   1  37   3]
- [ 10   4  14   7   3  18  63]]
-Node Classification on random seed  7605 -> 0.636
-Confusion Matrix:
- [[ 65   1   3   4  13   8   8]
- [  4 135   3   2  15   2   6]
- [ 20  28 131  40  16  17  58]
- [  8   2  10 109   5   7  16]
- [  0   9   4   3  63   0   2]
- [  6   0   1   2   2  43   4]
- [  9   0   8   7   7   4  90]]
-Node Classification on random seed  7606 -> 0.615
-Confusion Matrix:
- [[ 68   0   7   1   4  14  14]
- [  4 114   5   1  14   1   1]
- [ 43  18 140  39  21  12  47]
- [ 17   4  17  91   6   3   6]
- [  2   7   3   2  72   0   0]
- [  3   1   0   1   0  52   5]
- [ 16   1  15   9   6  15  78]]
-Node Classification on random seed  7607 -> 0.625
-Confusion Matrix:
- [[ 76  10   3  12   6   4  11]
- [  1 135   5   4   5   4   3]
- [ 25  13 146  33  31  18  34]
- [  5   5  25 101   5   3   9]
- [  2   3   3   4  58   0   3]
- [ 14   2   1   6   0  42   5]
- [ 26   1   8  13   5   5  67]]
-Node Classification on random seed  7608 -> 0.636
-Confusion Matrix:
- [[ 73   1   2   6   5   8   5]
- [  5 129   7   0  10   0   0]
- [ 18  28 139  25  35  33  47]
- [  6   5  22 100   3   5   5]
- [  0   5   2   0  80   2   1]
- [ 14   1   1   0   0  46   6]
- [ 10   2   3   7  12  17  69]]
-Node Classification on random seed  7609 -> 0.651
-Confusion Matrix:
- [[ 84   3   1  10   2  16   3]
- [  3 123   2   2   8   2   1]
- [ 17  15 151  48  27  16  41]
- [  9   1  10 105   7  14  10]
- [  1   6   5   0  49   0   0]
- [  2   0   3   3   1  56   7]
- [ 13   5   7   6   5  17  83]]
-Node Classification on random seed  7610 -> 0.583
-Confusion Matrix:
- [[ 54   1   3   2   4  26   5]
- [  5 119   3   3   8   1   4]
- [ 30  15 145  62  14  27  45]
- [ 16   3   9 110   1   4  18]
- [  1   9   9   1  49   1   1]
- [  1   0   3   4   0  51   4]
- [ 15   6  12  18   6  17  55]]
-Node Classification on random seed  7611 -> 0.597
-Confusion Matrix:
- [[ 65   1   5   2   2  12  17]
- [  5 135   4   4  11   1   3]
- [ 27  16 101  42  29  31  58]
- [ 15  11  12 102   1   6  12]
- [  5   5   3   1  71   0   2]
- [  3   0   3   4   1  44   2]
- [ 11   2  10  10   6   8  79]]
-Node Classification on random seed  7612 -> 0.607
-Confusion Matrix:
- [[ 64   5   9   2   0  11  11]
- [  4 137   4   0   4   2   6]
- [ 29  17 130  38  31  42  20]
- [ 14   9   8  99   5  11   9]
- [  3   6   3   0  58   0   8]
- [  3   4   3   1   2  45   7]
- [ 13   9  17   5   7  11  74]]
-Node Classification on random seed  7613 -> 0.591
-Confusion Matrix:
- [[ 61   2   4   9   8  14  13]
- [  4 110  11   2  13   3   4]
- [ 22  13 141  19  37  16  55]
- [  6   7  32  95   5   4   7]
- [  1   0   0   0  71   2   2]
- [  3   0   2  13   7  43  11]
- [  7   2   5  16  15  13  70]]
-Node Classification on random seed  7614 -> 0.613
-Confusion Matrix:
- [[ 61   2  10   1   5  18  16]
- [  3 121   1   2  15   6   8]
- [ 19  11 160  21  38  26  32]
- [ 15   4   8  95   5   8  18]
- [  0   5   3   0  48   0   3]
- [  4   3   4   1   1  46   7]
- [  3   7  18   5  10  21  82]]
-Node Classification on random seed  7615 -> 0.598
-Confusion Matrix:
- [[ 58   7   9   3   3  14   9]
- [  6 136   8   2   7   3   5]
- [ 18  38 136  40  23  22  39]
- [  8   5  20  87   3  17  14]
- [  2   7   2   1  59   3   2]
- [  7   2   1   0   1  48   3]
- [ 15   8   6   3   5  11  74]]
-Node Classification on random seed  7616 -> 0.602
-Confusion Matrix:
- [[ 72   1  10   4   6   9  11]
- [  2 106   9   4  13   2   7]
- [ 20  17 149  35  31  21  45]
- [  9   1  17  99   7  15  18]
- [  0   1   6   1  57   2   1]
- [  7   3   2   1   3  44   4]
- [  6   4  10   4  10  19  75]]
-Node Classification on random seed  7617 -> 0.587
-Confusion Matrix:
- [[ 74   3   5   3   1   8  13]
- [  1 125   9   3   0   7   4]
- [ 34  28 115  32  44  22  37]
- [  8   3  19 104   7  12  15]
- [  1  12   4   0  55   1   3]
- [  8   0   3   1   0  49   6]
- [ 10   4   7  10   6  19  65]]
-Node Classification on random seed  7618 -> 0.611
-Confusion Matrix:
- [[ 65   1   0   4   2   5  35]
- [  4 130   5   6   6   0   3]
- [ 15  23 128  36  38  42  28]
- [  9   5  20  96   2   5  17]
- [  6   3   7   5  53   0   0]
- [  2   1   0   7   0  45  12]
- [  6   7   7   3   4   8  94]]
-Node Classification on random seed  7619 -> 0.68
-Confusion Matrix:
- [[ 75   4   6   3   3   3   6]
- [  7 141   5   1   1   0   0]
- [ 15  27 170  16  28  20  35]
- [  3   7  17  93   4   8  20]
- [  0   7   6   1  68   1   2]
- [ 10   5   0   0   5  44   6]
- [  9   5  11   2   3   8  89]]
-Node Classification on random seed  7620 -> 0.591
-Confusion Matrix:
- [[ 78   3   3   3   2  10  22]
- [  9 125   2   3   7   3   3]
- [ 30  34 126  23  15  21  60]
- [  8   6  13  85   6   5  35]
- [  1   6   2   3  59   1   2]
- [  4   7   0   0   2  53   1]
- [ 14   1   7  12   9  11  65]]
-Node Classification on random seed  7621 -> 0.655
-Confusion Matrix:
- [[ 72   1   7   3   3  15   4]
- [  3 149   3   0   2   3   1]
- [ 28  26 117  31  46  18  26]
- [  6   0  11 116   9   4   7]
- [  1   6   2   3  64   0   4]
- [  6   1   1   2   0  45   5]
- [ 18   2   9   4   9  15  92]]
-Node Classification on random seed  7622 -> 0.57
-Confusion Matrix:
- [[ 75   5   2   3   3   9  16]
- [  5 126   8   3   6   0   5]
- [ 34  19 116  62  29  19  50]
- [ 25   2   8  84   3   7  15]
- [  2   7   4   2  63   1   5]
- [  6   2   2   0   0  46   3]
- [ 13   5  13   7   5  15  60]]
-Node Classification on random seed  7623 -> 0.641
-Confusion Matrix:
- [[ 63   1   5  17   4   8   6]
- [  4 132  13   3  12   0   5]
- [ 10  16 184  33  16  20  39]
- [ 12   1  23 100   6   7   9]
- [  0   4   5   1  57   1   2]
- [  2   0   2   7   0  49   7]
- [  0   1   7  25   5  20  56]]
-Node Classification on random seed  7624 -> 0.621
-Confusion Matrix:
- [[ 66   2   7   3   2   5  23]
- [  3 113   6   4   5   0   1]
- [ 29  26 153  36  37  10  36]
- [  6   8  25  95   4   8  11]
- [  1  10   2   2  55   0   2]
- [  2   1   1   2   0  46   8]
- [  4   3  23   2   9  10  93]]
-Node Classification on random seed  7625 -> 0.597
-Confusion Matrix:
- [[ 69   2   3  10   9   5   9]
- [  7 120   5   6   4   5   4]
- [ 24  26 126  43  27  28  48]
- [  8   5  17 103   3   6  11]
- [  3  11   4   0  56   0   2]
- [  4   3   0   6   1  46   7]
- [  9   5  11   2   4  16  77]]
-Node Classification on random seed  7626 -> 0.634
-Confusion Matrix:
- [[ 85   3   3   2   5  12  15]
- [  3 132   4   8   7   3   4]
- [ 19  16 153  44  17  30  26]
- [  8   3  15  93   8   3  22]
- [  0   8   2   1  65   1   3]
- [ 14   2   1   0   2  27   4]
- [  5   3   9   8   6  17  79]]
-Node Classification on random seed  7627 -> 0.566
-Confusion Matrix:
- [[ 74   5   4   4   5  10   8]
- [  3 106   5   5  14   6  12]
- [ 17  26 134  52  28  17  38]
- [ 26   3  23  89   9   5  10]
- [  1   6   4   0  52   4   8]
- [  9   3   3   2   2  41   5]
- [  8   4   7   9   7  17  70]]
-Node Classification on random seed  7628 -> 0.609
-Confusion Matrix:
- [[ 74   5   3   3   8   9   7]
- [  2 126   4   2  12   5   5]
- [ 31  24 143  32  24  11  45]
- [ 19   6  25  79   9   3  16]
- [  0   3   5   1  67   2   3]
- [  7   0   3   6   5  39   2]
- [ 10   8   5   6   3  12  81]]
-Node Classification on random seed  7629 -> 0.582
-Confusion Matrix:
- [[ 67   3   5   6   4  10  15]
- [ 10 138   6   1   3   0   4]
- [ 35  22  78  55  60  11  32]
- [  6   5  13 117  10  11   9]
- [  0   2   2   2  58   1   2]
- [  3   1   3   0   4  48   8]
- [ 11   6  10   7   8  12  76]]
-Node Classification on random seed  7630 -> 0.606
-Confusion Matrix:
- [[ 70   3   5  14   5  10  11]
- [  9 123   8   2   7   3  10]
- [ 22  19 124  42  25  28  34]
- [  5   7  10 104   1   7  13]
- [  1   5   3   2  70   2   5]
- [ 11   0   1   3   0  36   4]
- [ 19   2   8   9   9  10  79]]
-Node Classification on random seed  7631 -> 0.588
-Confusion Matrix:
- [[ 73   2   4   2   3  12   5]
- [  4 130  15   1   8   1   5]
- [ 17  21 128  31  37  49  30]
- [ 11   4  12  91   5  13  22]
- [  2   9   4   2  56   2   2]
- [ 14   1   4   0   0  50   4]
- [  8   7   6   6  13  14  60]]
-Node Classification on random seed  7632 -> 0.582
-Confusion Matrix:
- [[ 72   1   5   2   4  14  10]
- [  5 140   6   3   8   1   2]
- [ 33  37 114  50  18  14  41]
- [ 17   5  13 105   7   5  17]
- [  1   5   1   1  60   1   2]
- [  7   2   5   2   0  36   5]
- [  6   7  14  14   8  19  55]]
-Node Classification on random seed  7633 -> 0.58
-Confusion Matrix:
- [[ 66   1   6   5   3  17  10]
- [  2 122   6   5  20   5   5]
- [ 28  26 137  31  31  17  42]
- [  4  12  17  94   2  12  14]
- [  4   6   3   6  50   1   5]
- [  6   2   0   1   2  41   5]
- [  8   9  12   5   9  15  70]]
-Node Classification on random seed  7634 -> 0.625
-Confusion Matrix:
- [[ 61   1   7   8   2  22   6]
- [  6 131   3   2  16   7   3]
- [ 18  25 161  23  20  21  38]
- [ 21   2  14  90   3   8  20]
- [  2   3   9   1  64   0   3]
- [  4   1   7   0   0  47   6]
- [  9   7   9   5   3  10  71]]
-Node Classification on random seed  7635 -> 0.613
-Confusion Matrix:
- [[ 82   3   8   5   2  12   5]
- [  2 128  14   2   3   5   2]
- [ 27  18 142  36  16  35  36]
- [ 19   2  20  96   2  13   8]
- [  0  17   9   3  53   0   2]
- [  5   2   1   1   0  46   3]
- [ 12   3   9   7   4  14  66]]
-Node Classification on random seed  7636 -> 0.627
-Confusion Matrix:
- [[ 75   3   5   9   5  11   5]
- [  2 135   6   2   7   0   6]
- [ 13  23 128  43  32  34  28]
- [  2  10  11 107  11   4  17]
- [  1   8   5   1  52   4   3]
- [  1   1   5   2   0  44   7]
- [  9   4   5  11   6  11  86]]
-Node Classification on random seed  7637 -> 0.651
-Confusion Matrix:
- [[ 64   1   4   3   4   9  16]
- [  3 124   4   2   4   1   7]
- [ 10  25 176  32  23  19  40]
- [ 15   5  10 100   2   7  18]
- [  2   7   3   2  69   0   3]
- [  6   1   3   1   0  37  14]
- [ 12   1   9   3   8  10  81]]
-Node Classification on random seed  7638 -> 0.585
-Confusion Matrix:
- [[ 65   0   7   1   4  14  14]
- [  6 142   2   2  15   4   2]
- [ 30  36 111  37  29  19  40]
- [ 23   3   6 102  10   3  14]
- [  2   3   3   0  53   2   5]
- [  5   0   0   1   0  47   7]
- [ 13   8   8  11  14  12  65]]
-Node Classification on random seed  7639 -> 0.605
-Confusion Matrix:
- [[ 71   2   2  10   5   6   4]
- [  4 127   1   1  17   0   4]
- [ 25  28 140  38  38  13  47]
- [ 15  10  13  84  13   3  15]
- [  1   4   1   1  72   2   0]
- [  7   1   2   3   3  41   2]
- [ 13   7   9   7   6  12  70]]
-Node Classification on random seed  7640 -> 0.605
-Confusion Matrix:
- [[ 65   2   7   4   3  13  10]
- [  5 142   5   1   2   3   1]
- [ 17  26 124  53  22  26  34]
- [ 10   8  20 102   5   8  14]
- [  1   7   3   2  54   0   5]
- [  3   4   5   2   0  45   6]
- [ 13   2  15   9   5  14  73]]
-Node Classification on random seed  7641 -> 0.607
-Confusion Matrix:
- [[ 60   7   6  11   3   7   8]
- [  3 139   2   1   2   1   3]
- [ 49  12 125  15  24  24  41]
- [ 14   3  14 107   5   7  20]
- [  2  14   4   0  54   4   4]
- [  2   3   4   2   1  47   8]
- [ 29   2   8   2   4  18  75]]
-Node Classification on random seed  7642 -> 0.596
-Confusion Matrix:
- [[ 77   2   2   6  11  10   4]
- [  6 118   9   1  10   2   4]
- [ 22  21 117  18  58  21  39]
- [ 18   3  18  84  14   4  12]
- [  1   2   4   0  70   0   2]
- [ 11   2   5   1   1  45   4]
- [ 12   6  11   9   4  14  85]]
-Node Classification on random seed  7643 -> 0.613
-Confusion Matrix:
- [[ 71   6   2   2   4   2  26]
- [  4 121  12   4   6   7   2]
- [ 28  22 143  29  14  23  55]
- [ 14   3   8  91   7  12  14]
- [  4   2  10   5  68   1   2]
- [  2   4   2   2   0  41  10]
- [ 14   1   6   9   2   5  78]]
-Node Classification on random seed  7644 -> 0.601
-Confusion Matrix:
- [[ 64   3   5   2   4  16  12]
- [  3 127  10   1   9   4   1]
- [ 28  15 138  59  41  16  34]
- [ 15   7  13 103   6   3  13]
- [  0   8   4   0  52   0   0]
- [  3   0   2   0   0  44   5]
- [  5   7  11  12  10  12  73]]
-Node Classification on random seed  7645 -> 0.596
-Confusion Matrix:
- [[ 80   4   0   7   3   6   9]
- [ 11 126   5   1   6   2   1]
- [ 36  10 124  48  28  21  41]
- [ 10   3  35  98   2   2   3]
- [  7   4   2   1  57   0   1]
- [ 10   1   1   4   1  39   3]
- [ 15   1  10  22  12  15  72]]
-Node Classification on random seed  7646 -> 0.59
-Confusion Matrix:
- [[ 70   0   2   5   0  18   9]
- [  4 124   3   2   5   4   3]
- [ 21  23 125  52  35  26  34]
- [ 17   5   4  87   8  12  18]
- [  1   8   2   1  67   0   3]
- [  4   1   3   4   1  39   9]
- [ 11   6   8  13   5  20  78]]
-Node Classification on random seed  7647 -> 0.629
-Confusion Matrix:
- [[ 66   3   9   2   5  10  12]
- [  6 120   9   0   5   4  10]
- [ 28  22 155  31  28  21  30]
- [ 12   1  10 114   9   3   6]
- [  1   7   3   0  58   1   3]
- [  8   1   1   1   0  40   4]
- [ 22   8   6  13   8   8  76]]
-Node Classification on random seed  7648 -> 0.601
-Confusion Matrix:
- [[ 77   5   1   7   7   8   4]
- [  5 127  15   4  15   3   4]
- [ 38  18 113  35  30  21  45]
- [  5   2  14 100  10   7  10]
- [  2   3   1   2  51   0  12]
- [  6   1   0   2   0  62   3]
- [ 19   1   5   9   6  14  71]]
-Node Classification on random seed  7649 -> 0.605
-Confusion Matrix:
- [[ 63   3   2   7   5   6  12]
- [  3 135   0   6   5   2   7]
- [ 24  24 135  36  28  27  32]
- [ 20   5  11 100  10   4  14]
- [  1   9   4   0  70   1   3]
- [  1   2   2   1   2  41   2]
- [ 13   4  17   3  18  19  61]]
-Node Classification on random seed  7650 -> 0.602
-Confusion Matrix:
- [[ 65   7   6   3   2   5  10]
- [  4 122  12   2   7   1   6]
- [ 21  28 146  45  26  20  34]
- [ 11   5  20 109   9   3  16]
- [  0   9   5   0  47   2   4]
- [  5   0   0   4   0  45   2]
- [ 15   3  13   4  16  13  68]]
-Node Classification on random seed  7651 -> 0.596
-Confusion Matrix:
- [[ 78   2   3   2   1   5  17]
- [  3 145   7   3   4   3   2]
- [ 24  33 120  64  18  22  41]
- [ 25   7  15  89   5   2   9]
- [  0   7   2   1  58   1   1]
- [  9   0   1   3   0  38   2]
- [ 11   4   7  17   9  12  68]]
-Node Classification on random seed  7652 -> 0.604
-Confusion Matrix:
- [[ 72   5   5   5   9   8  10]
- [  6 117   5   3   6   2   2]
- [ 30  19 133  52  22  28  13]
- [ 17   3  11 103  12   9  11]
- [  3   8   4   4  52   0   1]
- [  9   2   3   0   0  64   5]
- [ 17   3   7  11   9  17  63]]
-Node Classification on random seed  7653 -> 0.607
-Confusion Matrix:
- [[ 65   4   3   9   0  17  11]
- [  2 114  10  13   5   2   5]
- [ 15  18 137  22   7  44  61]
- [  9   7  20 103   3   3  11]
- [  2   4  10   1  57   0   2]
- [  2   2   2   1   1  54   4]
- [  4   6   5  21   6  19  77]]
-Node Classification on random seed  7654 -> 0.624
-Confusion Matrix:
- [[ 57   2   6   2   3   5  19]
- [  2 127   5   1   6   3   6]
- [ 24  35 139  44  16  16  44]
- [  8   5  18 113   5   4  24]
- [  1   6   5   2  68   1   1]
- [  1   2   5   2   0  44  10]
- [  3   2   8   8   4  12  76]]
-Node Classification on random seed  7655 -> 0.595
-Confusion Matrix:
- [[ 62   0   9   5   7  10  17]
- [  3 142   4   3   9   7   2]
- [ 18  14 117  36  59  17  30]
- [ 17   3  12  99   8   5  16]
- [  0   5   4   1  55   2   2]
- [  4   1   2   0   0  48   6]
- [  8   7  16   8   9  19  72]]
-Node Classification on random seed  7656 -> 0.635
-Confusion Matrix:
- [[ 92   3   1   4   1   8   0]
- [  3 136   4   2  13   0   2]
- [ 31  23 132  38  25  14  35]
- [ 17   6  15  97   7  12   8]
- [  2  12   2   1  55   0   1]
- [  9   7   4   4   1  48   1]
- [ 19   3   3   7   9   8  75]]
-Node Classification on random seed  7657 -> 0.644
-Confusion Matrix:
- [[ 61   3   7   4   3  11  12]
- [  4 128   3   6   2   1  12]
- [ 19  27 170  31  21  17  53]
- [  7   0  11  90   5   3  20]
- [  2   3   2   3  64   2   3]
- [  2   3   4   5   0  41   7]
- [  0   6   2   5   6  19  90]]
-Node Classification on random seed  7658 -> 0.617
-Confusion Matrix:
- [[ 81   4   1   1   1   8   8]
- [  9 115   9   1   4   0   4]
- [ 34  26 167  26  15  20  51]
- [ 10   3  29  80   1   5  30]
- [  2   6   3   1  58   0   5]
- [  5   2   3   0   1  41   8]
- [ 15   4  10   7   3   8  75]]
-Node Classification on random seed  7659 -> 0.634
-Confusion Matrix:
- [[ 82   2   6   4   2  19   3]
- [  3 123   4   3  14   3   8]
- [ 19  27 142  34  21  25  34]
- [  9   9  14 113   6   5  12]
- [  0   7   4   1  50   0   4]
- [  5   3   2   0   2  46   2]
- [  5   8  11   1  10  15  78]]
-Node Classification on random seed  7660 -> 0.597
-Confusion Matrix:
- [[ 79   2   5   7   3  15   6]
- [  2 131   4   3   9   2   3]
- [ 21  22 120  41  34  30  47]
- [ 14   5  22  91   4   5   8]
- [  4   8   2   1  67   5   1]
- [  5   0   3   0   1  39   7]
- [ 12   3   8   9  12   8  70]]
-Node Classification on random seed  7661 -> 0.659
-Confusion Matrix:
- [[ 77   4   3   6   9  14   6]
- [  2 140  11   7   4   1   4]
- [ 11  14 197  33  24  18  33]
- [  9   9  27  81   6  11   9]
- [  0   5   6   0  60   0   1]
- [  4   4   1   4   0  48   4]
- [ 11   2   6   4   7   7  56]]
-Node Classification on random seed  7662 -> 0.633
-Confusion Matrix:
- [[ 49   2  11   8   8  12  10]
- [  6 125   9   0   4   2   2]
- [ 15  19 165  34  24  31  36]
- [ 10   2  17 105   5   2  18]
- [  1   7   6   0  62   1   3]
- [  1   2   5   1   1  42   7]
- [ 11   4   4   7  12   7  85]]
-Node Classification on random seed  7663 -> 0.624
-Confusion Matrix:
- [[ 83   1   6   3   1   8  15]
- [  4 124   8   2  13   2   2]
- [ 26  22 126  38  35  24  37]
- [  8   0   7 111   3   3  19]
- [  1   5   5   3  60   3   5]
- [  7   3   1   0   0  50   4]
- [ 16   2   7  11   4  12  70]]
-Node Classification on random seed  7664 -> 0.581
-Confusion Matrix:
- [[ 81   8   2   4   3  10  10]
- [  8 128   6   3   8   4   4]
- [ 37  29 119  52  25  16  29]
- [  8   6  30  89   8   5  12]
- [  2   8   2   3  50   1   1]
- [  5   1   3   3   0  43   5]
- [ 13   6  10   9   4  16  71]]
-Node Classification on random seed  7665 -> 0.611
-Confusion Matrix:
- [[ 52   7   8   5   1  17  10]
- [  1 114  10   3   6   3   2]
- [ 32  10 168  24  11  19  57]
- [ 10   2  24 105   1   5  12]
- [  1   8   4   2  64   2   2]
- [  4   1   2   6   0  36   9]
- [ 14   1   8   8  16  21  72]]
-Node Classification on random seed  7666 -> 0.63
-Confusion Matrix:
- [[ 72   1   3   6   1   9  13]
- [  6 140   4   4  10   3   1]
- [ 16  14 156  25  19  41  51]
- [  9   2  15  88   5  11  14]
- [  0   8   7   2  56   1   5]
- [  7   0   6   2   2  28  11]
- [  7   3   5   2   8  11  90]]
-Node Classification on random seed  7667 -> 0.646
-Confusion Matrix:
- [[ 74   1   7   5   1  10   9]
- [  1 116   8   0   6   3   5]
- [ 21  24 180  26  32  15  34]
- [  8   4  19 105   4   5  18]
- [  3   5   2   3  71   0   1]
- [  5   4   3   0   0  38  11]
- [  6   1  12   7  23   2  62]]
-Node Classification on random seed  7668 -> 0.598
-Confusion Matrix:
- [[ 76   1   2  12   5  12  12]
- [  1 127   6   3   4   3   1]
- [ 26  14 100  56  52  21  35]
- [  4   4  20 109   7   6  13]
- [  0   3   2   4  64   4   3]
- [  2   0   1   2   2  41   6]
- [ 13   4   8   4   8  16  81]]
-Node Classification on random seed  7669 -> 0.623
-Confusion Matrix:
- [[ 62   3   5   4   5  11  17]
- [  7 123   3   1   6   4   7]
- [ 15  14 159  50  31  14  42]
- [  5   2  12 107   3   4  14]
- [  4   4   6   5  51   0   3]
- [  5   0   2   1   1  38   6]
- [ 24   1  12  11   4   9  83]]
-Node Classification on random seed  7670 -> 0.616
-Confusion Matrix:
- [[ 60   6   4   8   1  15  15]
- [  8 119  11   1   8   1   2]
- [ 30  25 162  35  19  12  37]
- [  8   8  12 107   3   5  12]
- [  2   4   4   3  65   0   7]
- [  3   1   7   0   1  47  12]
- [  5   7   9   2  15  16  56]]
-Node Classification on random seed  7671 -> 0.623
-Confusion Matrix:
- [[ 58   1   3   1   1   9  21]
- [  6 135   5   2   9   3   3]
- [ 30  21 147  30  13  13  32]
- [ 17   0  28 103  13   4   6]
- [  2  11   5   1  58   2   1]
- [  2   0   3   1   2  52   4]
- [  8   3  19  10   6  26  70]]
-Node Classification on random seed  7672 -> 0.628
-Confusion Matrix:
- [[ 61   2   0  22   6   8   8]
- [  5 131   6   2   7   3   2]
- [ 20  19 150  38  35  22  35]
- [ 11   5   7 112   4   8   6]
- [  0   2   1   4  67   4   2]
- [  3   1   2   5   4  38   8]
- [  9   1   8  13   7  17  69]]
-Node Classification on random seed  7673 -> 0.607
-Confusion Matrix:
- [[ 71   1   4   8   3  16   3]
- [  8 130   1   8   5   0   4]
- [ 26  21 121  61  20  21  36]
- [ 22   3  15 106   3   8  14]
- [  1   8   3   1  62   1   2]
- [  3   1   1   8   0  39   4]
- [  9   4  12   8   1  15  78]]
-Node Classification on random seed  7674 -> 0.648
-Confusion Matrix:
- [[ 76   4   4   1   7   3   6]
- [  4 115   5   5  10   0   6]
- [ 20  15 137  36  32  26  44]
- [  5   2  13 129   1   6  10]
- [  0   6   4   3  67   0   3]
- [ 11   3   0   0   1  35   9]
- [ 12   3  13   8   4   7  89]]
-Node Classification on random seed  7675 -> 0.626
-Confusion Matrix:
- [[ 62   5   1   3   3  23   9]
- [  0 132   9  11   6   6   2]
- [ 18  20 155  32  18  20  38]
- [ 12   6  15  85   7   7  15]
- [  0   5   6   3  62   2   1]
- [  0   1   4   2   1  56   9]
- [  9   5   4  13   3  20  74]]
-Node Classification on random seed  7676 -> 0.602
-Confusion Matrix:
- [[ 62   8   5   6   5  15   4]
- [  5 137   4   2   8   1   4]
- [ 21  28 131  28  43  24  30]
- [  9   3  16  91   8  13  18]
- [  0   7   3   0  61   1   4]
- [  5   4   2   1   1  52   3]
- [ 11   8   4  15  11  10  68]]
-Node Classification on random seed  7677 -> 0.63
-Confusion Matrix:
- [[ 62   4  15   3   2  13   4]
- [ 11 146   6   2  10   3   1]
- [ 30  33 143  22  17  29  33]
- [  6   7  12  99   4   2   8]
- [  3   7   3   1  59   1   3]
- [  5   4   2   3   1  49   1]
- [ 16   2  10   9   3  19  72]]
-Node Classification on random seed  7678 -> 0.614
-Confusion Matrix:
- [[ 69   2   4  14   5   5  15]
- [  1 140   2   6   4   2   4]
- [ 30  11 120  38  27  23  35]
- [ 18   6  18  95   7   6   9]
- [  2   6   6   1  63   3   3]
- [  4   3   5   2   0  43  11]
- [ 12   6   7   9   5   9  84]]
-Node Classification on random seed  7679 -> 0.624
-Confusion Matrix:
- [[ 81   1   1   3   2  11  13]
- [  4 127  10   1   3   1   4]
- [ 28  20 157  40  16  30  24]
- [ 19   1  18 111   5   4  13]
- [  0   2   7   1  63   3   2]
- [ 10   2   4   1   0  30   5]
- [ 24   1  20   3   4  15  55]]
-Node Classification on random seed  7680 -> 0.646
-Confusion Matrix:
- [[ 52   6   4   7   4  11   7]
- [  1 137   6   2   1   2   5]
- [ 21  20 188  36  18  12  22]
- [  8   3  14 100  10  11  18]
- [  2   4   7   0  61   1   3]
- [ 13   0   5   1   0  40   5]
- [ 19   3  24   3   2  13  68]]
-Node Classification on random seed  7681 -> 0.572
-Confusion Matrix:
- [[ 69   2   3   7   1   8  12]
- [  6 124   3   1  12   3   5]
- [ 35  21 115  23  31  28  61]
- [ 13   4   9 103  10   3  23]
- [  1   9   4   1  53   1   2]
- [  9   3   5   1   0  37   9]
- [ 13   7   9   7   8  15  71]]
-Node Classification on random seed  7682 -> 0.645
-Confusion Matrix:
- [[ 80   0   3  12   5   8   3]
- [  5 126   7   0   6   0   5]
- [ 15  24 168  28  18  12  51]
- [  9   8  17 109   5   4   7]
- [  1   5   6   6  56   1   3]
- [  5   0   1   1   3  44  10]
- [  8   3  13  17   4  16  62]]
-Node Classification on random seed  7683 -> 0.559
-Confusion Matrix:
- [[ 65   1   1   6   9   2   7]
- [  1 136   3   6  14   5   2]
- [ 32  27 101  42  33  31  40]
- [ 13   2   9  82  23   9  17]
- [  3   5   6   3  57   0   3]
- [  5   0   4   2   0  40   9]
- [ 17   0  20  11  11   7  78]]
-Node Classification on random seed  7684 -> 0.618
-Confusion Matrix:
- [[ 95   2   2   4   1   4   7]
- [  6 133   5   3   0   1   0]
- [ 15  30 120  41  24  29  35]
- [ 11   5  19  86   7   5  13]
- [  2  14   4   1  72   1   4]
- [  4   2   0   7   0  47   1]
- [ 21   5  11  10   8  18  65]]
-Node Classification on random seed  7685 -> 0.627
-Confusion Matrix:
- [[ 65   5   3   2   7   9  13]
- [  5 119   8   1   9   2   4]
- [ 21  42 149  39  22  16  33]
- [  7   1  16 100   5   7  11]
- [  0   7   2   5  63   2   4]
- [  4   0   2   1   1  50   8]
- [ 11   2   9   5   8  14  81]]
-Node Classification on random seed  7686 -> 0.666
-Confusion Matrix:
- [[ 79   3   6   7   3  12  15]
- [  1 130   8   3   2   1   2]
- [ 22  17 168  38   8   8  39]
- [ 10   2  19 113   7   7   7]
- [  1   9   5   2  48   2   2]
- [  7   1   1   3   2  45   4]
- [  5   1  15   8   3  16  83]]
-Node Classification on random seed  7687 -> 0.62
-Confusion Matrix:
- [[ 83   2   1   4   6   3   5]
- [  1 138   6   3   7   4   3]
- [ 34  27 131  26  51  18  30]
- [ 17   2  25 102   1   6  14]
- [  0   7   3   1  53   2   4]
- [  7   1   1   2   0  48   6]
- [ 16   5   5  12   6   6  65]]
-Node Classification on random seed  7688 -> 0.619
-Confusion Matrix:
- [[ 45   2   2  11   2  14  18]
- [  0 130   5   2   6   5   5]
- [ 25  16 133  29  20  37  33]
- [ 16   6  15 118   5   5  11]
- [  0   7   2   2  69   1   2]
- [  8   1   3   3   0  41  11]
- [ 10   5   8   7   3  18  83]]
-Node Classification on random seed  7689 -> 0.613
-Confusion Matrix:
- [[ 60   3   2   6   5   9  15]
- [  6 134  10   2   6   5   1]
- [ 31  17 147  25  22  22  59]
- [ 15   0  16  92   4   8  12]
- [  0   4   3   3  61   1   5]
- [  6   0   3   1   0  44  10]
- [ 15   3  11   2  10   9  75]]
-Node Classification on random seed  7690 -> 0.622
-Confusion Matrix:
- [[ 78   2   4   7   5  13   7]
- [  4 122   9   5   4   2  10]
- [ 20  26 168  36  25  19  17]
- [  9   1  16  80  15  17  13]
- [  1   4   4   3  61   2   3]
- [  1   1   2   1   1  46   6]
- [ 11   2   7  21   9  13  67]]
-Node Classification on random seed  7691 -> 0.568
-Confusion Matrix:
- [[ 67   2   4   4   3   5   8]
- [  1 122   7   1   7   1   6]
- [ 31  31 133  46  11  27  51]
- [ 23   5  23  89   4  11  13]
- [  1   6   5   2  56   0   3]
- [  4   3   4   0   0  47   5]
- [  8   2  14   7   8  35  54]]
-Node Classification on random seed  7692 -> 0.625
-Confusion Matrix:
- [[ 51   4   7   6   1  13  15]
- [  6 142   5   1   4   3   2]
- [ 15  28 148  44  19  30  46]
- [  5   9   6  99   4   6  14]
- [  1   6   3   1  63   1   1]
- [  5   0   5   4   1  42   4]
- [ 22   4   8   4   3   9  80]]
-Node Classification on random seed  7693 -> 0.623
-Confusion Matrix:
- [[ 59   5   9   1   6  14  11]
- [  3 138   8   0  10   1   1]
- [ 18  19 137  50  15  31  40]
- [ 21   2  10 106   5   6  13]
- [  1   3   6   2  55   2   1]
- [  2   0   1   0   2  53   6]
- [  4   2  10   9  11  16  75]]
-Node Classification on random seed  7694 -> 0.605
-Confusion Matrix:
- [[ 70   3   3   3   4  19   7]
- [  1 138   5   1  14   2   6]
- [ 17  21 127  53  31  17  31]
- [ 19   7  17  97   5  11  14]
- [  3   7   6   0  49   2   2]
- [  6   0   0   0   0  48   7]
- [  8   1  18   2   5  17  76]]
-Node Classification on random seed  7695 -> 0.557
-Confusion Matrix:
- [[ 48   1   2   8   8  18  17]
- [  6 125   8   3  14   6   4]
- [ 17  27 106  29  43  23  44]
- [  7   3  26  99   2   7  20]
- [  5   7   3   2  67   0   1]
- [  4   0   2   3   1  44   7]
- [  5   3  11  12  12  22  68]]
-Node Classification on random seed  7696 -> 0.614
-Confusion Matrix:
- [[ 70   3  11   3   9   7   6]
- [  1 124   7   2   7   2  13]
- [ 26  23 137  35  31  25  34]
- [  6   2  29 101   4   1  11]
- [  2   6   4   0  63   1   1]
- [  3   4   5   1   1  44   4]
- [  6   4  12   7  14  13  75]]
-Node Classification on random seed  7697 -> 0.616
-Confusion Matrix:
- [[ 62   4   4   6  10   8   8]
- [  3 138   4   0   3   7   5]
- [ 37  15 157  15  41  30  38]
- [ 19   9  13  84   0   4  26]
- [  0   8   5   2  49   0   5]
- [  7   0   0   0   0  48   2]
- [ 16   4   5   4   5  12  78]]
-Node Classification on random seed  7698 -> 0.57
-Confusion Matrix:
- [[ 69   2   3  12   3   6   8]
- [  3 125  10   4   5   1  11]
- [ 26  26 115  61  23  19  26]
- [ 13   3  12  96  11  11  25]
- [  1   5   6   2  57   2   2]
- [  8   2   4   2   0  34   6]
- [ 10   2  23   6   4  21  74]]
-Node Classification on random seed  7699 -> 0.602
-Confusion Matrix:
- [[ 76   1  10   3   4  13   6]
- [  4 134   9   2   4   5   2]
- [ 25  17  99  68  38  17  32]
- [  9   6   7  99   8   9  18]
- [  1   6   0   3  61   0   3]
- [  6   0   4   2   0  51   3]
- [ 11   3  11   7   2  19  82]]
-Node Classification on random seed  7700 -> 0.588
-Confusion Matrix:
- [[ 77   2  10   9   8  11  13]
- [  6 123   8   3   8   3   5]
- [ 15  19 117  48  40  22  32]
- [ 17  10  14 107   5   6   9]
- [  3   6   8   2  51   1   0]
- [ 13   1   4   2   2  39   6]
- [ 10   3   7   4   4  13  74]]
-Node Classification on random seed  7701 -> 0.614
-Confusion Matrix:
- [[ 76   2   4   3   6   6   8]
- [  6 118   5   3  15   1   0]
- [ 22  16 140  53  26  19  32]
- [ 11   3  20 112   3   2  13]
- [  2   6   3   0  62   0   0]
- [  5   1   1   2   0  43   5]
- [ 13   6  18  16  10  19  63]]
-Node Classification on random seed  7702 -> 0.631
-Confusion Matrix:
- [[ 78   3   1   7   1   7  14]
- [  3 142   6   5   4   1   9]
- [ 24  38 151  30  11  24  27]
- [ 11  12  15 109   4   4  19]
- [  2   7   6   3  57   0   0]
- [  3   2   4   5   0  36   4]
- [ 10   2  14   8   7  12  58]]
-Node Classification on random seed  7703 -> 0.58
-Confusion Matrix:
- [[ 53   3  10  12  10  19   8]
- [  4 125  11   0   8   1   6]
- [ 36   9 115  40  34  32  35]
- [  7   7  12 126   5   5   9]
- [  1   4   1   2  62   2   1]
- [  8   3   2   0   0  47   0]
- [ 19  12   9   4   5  24  52]]
-Node Classification on random seed  7704 -> 0.598
-Confusion Matrix:
- [[ 68   4   4   4   3   5  19]
- [  3 124  11   2   6   2   4]
- [ 24  30 116  39  54  23  28]
- [ 10   5  20 103   8   4  17]
- [  2   5   1   4  64   3   0]
- [  2   2   3   4   0  42   5]
- [ 12   4  11   4   2   9  81]]
-Node Classification on random seed  7705 -> 0.619
-Confusion Matrix:
- [[ 61   3  19   9   3  12   5]
- [  5 118   7   1   7   3   3]
- [ 27  27 131  30  18  24  35]
- [  6  11  14 111   1   7  21]
- [  3   6   3   0  69   0   1]
- [  2   1   4   1   0  48  10]
- [  8   2  11   6   7  18  81]]
-Node Classification on random seed  7706 -> 0.633
-Confusion Matrix:
- [[ 66   2   5   5   3  12  12]
- [  0 129   4   1  10   2   5]
- [ 35  18 139  23  43  23  25]
- [ 11   6  24 106   3   1   8]
- [  2   5   4   5  54   1   2]
- [  6   5   2   0   2  45   8]
- [ 11   1  11   5   8   8  94]]
-Node Classification on random seed  7707 -> 0.59
-Confusion Matrix:
- [[ 63   4   1   2  10   7   7]
- [ 10 124  13   2  11   0   4]
- [ 27  27 149  26  26  15  35]
- [ 18   7   8 100   0   6  20]
- [  5   7   6   1  57   2   3]
- [  9   1   3   2   2  38   3]
- [ 14   5   8   7  23  23  59]]
-Node Classification on random seed  7708 -> 0.616
-Confusion Matrix:
- [[ 66   1  11   5   4   7  12]
- [  5 128  11   1   4   3   6]
- [ 27  11 137  37  21  28  42]
- [  9   3  25 105   4   4  17]
- [  2  12   2   2  64   0   3]
- [  5   1   3   3   0  45   5]
- [  6   3   9   7   3  20  71]]
-Node Classification on random seed  7709 -> 0.638
-Confusion Matrix:
- [[ 62   7  15   6   2   4   8]
- [  1 125   5   3   8   2   4]
- [ 12  18 172  43  23  20  30]
- [  9   7  13  92   7   7  20]
- [  4   5   2   0  62   0   2]
- [ 13   2   1   0   0  44  10]
- [ 10   4  12   7   5  11  81]]
-Node Classification on random seed  7710 -> 0.6
-Confusion Matrix:
- [[ 68   2   1  10  11   5  17]
- [  3 109   3   6   6   0   4]
- [ 27  12 146  28  33  29  43]
- [ 16   2  13 107  12   5   9]
- [  0   8   4   2  55   1   2]
- [  7   1   3   5   0  51   6]
- [  9   2   9  27   4  13  64]]
-Node Classification on random seed  7711 -> 0.597
-Confusion Matrix:
- [[ 73  10  12   3   3  15   2]
- [ 11 131   5   0   5   1   4]
- [ 27  28 141  21  13  16  60]
- [ 18   2  19  85  17   5  16]
- [  1   6   2   0  54   1   4]
- [  6   1   5   2   1  32  11]
- [ 13   2   7   6   9  13  81]]
-Node Classification on random seed  7712 -> 0.587
-Confusion Matrix:
- [[ 71   1  10   7  10   3  10]
- [  9 119  14   1  12   0   2]
- [ 22  20 136  30  27  27  60]
- [ 21   4  10 102   7   1  20]
- [  0   4   6   2  45   1   0]
- [  6   1   3   1   2  35   7]
- [ 19   7   2   3   3  18  79]]
-Node Classification on random seed  7713 -> 0.62
-Confusion Matrix:
- [[ 80   6  13   4   0   9   8]
- [  0 113   5   1   9   4   3]
- [ 24  22 136  24  46  26  35]
- [  8  12  15 115   8   1   5]
- [  1   8   1   0  62   3   2]
- [ 11   0   1   3   1  46   2]
- [ 10   3  12  15   1  18  68]]
-Node Classification on random seed  7714 -> 0.636
-Confusion Matrix:
- [[ 65   6   1   3   3   6  14]
- [  3 137   8   8   3   0   6]
- [ 21  14 152  34  23  33  31]
- [ 16  12   4 122   3   3   5]
- [  1   9   6   2  61   3   0]
- [  6   0   3   1   2  49   7]
- [ 14   3   5  11  14  17  50]]
-Node Classification on random seed  7715 -> 0.649
-Confusion Matrix:
- [[ 71   2   3   4   3   9   8]
- [  7 104  14   1   6   1   0]
- [ 15  19 156  38  28  22  50]
- [  9   2  11 131   4   9   5]
- [  1   8   4   0  62   2   2]
- [  5   1   2   0   2  37   2]
- [  6   5   6  13   5  17  88]]
-Node Classification on random seed  7716 -> 0.638
-Confusion Matrix:
- [[ 68   6   5   6   0   6   7]
- [  6 140   3   2   2   7   4]
- [ 15  45 153  37  18  21  24]
- [  7   7  18 112   6   2   8]
- [  2   6   3   3  53   4   4]
- [ 10   0   2   0   0  42   5]
- [ 15   1  14   7   6  18  70]]
-Node Classification on random seed  7717 -> 0.601
-Confusion Matrix:
- [[ 65   1   1   5   0  14   5]
- [  5 127   2   5  21   2   4]
- [ 22   6 126  52  32  43  42]
- [ 12   4  11 105   0  11   9]
- [  0   3   4   3  60   1   3]
- [  2   1   2   2   2  36   9]
- [  8   4  10  14   6  16  82]]
-Node Classification on random seed  7718 -> 0.631
-Confusion Matrix:
- [[ 94   0   7   6   1  14   3]
- [  6 129   6   6   8   1   6]
- [ 39  19 159  38  26  10  34]
- [  4   1  14 107   9   7  20]
- [  5   7   4   5  52   0   1]
- [  2   2   5   1   0  35   3]
- [ 23   4   2   8   3   9  55]]
-Node Classification on random seed  7719 -> 0.621
-Confusion Matrix:
- [[ 66   2  12   6   6  12   4]
- [  2 112   9   4  15   2   1]
- [ 28   8 158  28  23  28  32]
- [ 25   4  13  95  12   8   8]
- [  1   1   8   0  77   1   4]
- [  9   3   0   1   0  45   4]
- [ 15   2   4   6  15  13  68]]
-Node Classification on random seed  7720 -> 0.662
-Confusion Matrix:
- [[ 70   5   2   6   8   6  14]
- [ 11 135   3   3  13   3   1]
- [ 16  14 165  15  23  27  39]
- [  3   2  20 100   5   3  17]
- [  2   8   3   3  62   0   0]
- [  8   2   4   0   0  48   4]
- [ 10   3   6   5   7  14  82]]
-Node Classification on random seed  7721 -> 0.544
-Confusion Matrix:
- [[ 65   5   3   8   3  18   9]
- [  7 126   6   1   7   2   0]
- [ 17  38 118  52  50  20  32]
- [ 17   3  19  64  18   6  10]
- [  5   5   3   0  57   1   1]
- [ 16   3   1   4   0  37   6]
- [ 12   6  11   4   7  20  77]]
-Node Classification on random seed  7722 -> 0.61
-Confusion Matrix:
- [[ 53   0  10   2   2  18   8]
- [  9 125   9   9   3   0   6]
- [ 29  16 160  25  25  14  37]
- [ 13   7  14  85  11   7  16]
- [  3   5   1   6  58   0   4]
- [  7   0   1   7   0  33  13]
- [ 15   3   3  12   3  17  96]]
-Node Classification on random seed  7723 -> 0.628
-Confusion Matrix:
- [[ 81   2   2   9   8   9   9]
- [  3 110   6   1   7   6   2]
- [ 20  22 144  47  18  27  38]
- [  8   4   9  99   8   4  20]
- [  0   6   2   5  58   1   2]
- [ 10   0   2   2   0  51   7]
- [ 19   1   5   3   5  13  85]]
-Node Classification on random seed  7724 -> 0.57
-Confusion Matrix:
- [[ 55   2  15  13   1  11  13]
- [  5 104   3   5   7   5   7]
- [ 33  14 148  40  15  11  51]
- [ 11   5  20  89  13   9  21]
- [  3   8   5   2  56   2   2]
- [  7   3   3   0   1  44   9]
- [ 15   5  10   4  12   9  74]]
-Node Classification on random seed  7725 -> 0.62
-Confusion Matrix:
- [[ 61   2   2   9   3  13   7]
- [  4 104  17   1   3   5   7]
- [ 16  25 173  27  24  25  34]
- [  4   6  13 101   6   8  22]
- [  0   6   6   3  57   4   1]
- [  5   2   5   2   0  56   6]
- [ 14   2  11   4  12  14  68]]
-Node Classification on random seed  7726 -> 0.636
-Confusion Matrix:
- [[ 56   3   2  12   1   9  23]
- [  1 133   3   3   3   4   2]
- [ 17  23 177  23  22  13  52]
- [  2   1  15  96   7   6  23]
- [  5  14   4   1  47   1   1]
- [  7   6   2   2   4  41   8]
- [  4   1   4   3   7  20  86]]
-Node Classification on random seed  7727 -> 0.616
-Confusion Matrix:
- [[ 76   2   8   4   6   4  12]
- [  4 148  10   4   9   1   2]
- [ 13  26 112  59  25  11  55]
- [  8   5  10 109   4   1  15]
- [  2   6   4   1  53   0   0]
- [  9   1   4   6   1  39   8]
- [ 13   1  12   3   4  11  79]]
-Node Classification on random seed  7728 -> 0.632
-Confusion Matrix:
- [[ 59   7   0   1  15   5  14]
- [  3 132  14   0  12   5   2]
- [ 20  19 139  29  26  15  54]
- [ 13   2  20 117   8   4  12]
- [  1   3   1   1  70   1   1]
- [  4   3   2   2   0  41   5]
- [  7   2   7   3   8  17  74]]
-Node Classification on random seed  7729 -> 0.623
-Confusion Matrix:
- [[ 80   5   2   6   4   6  10]
- [  1 118   9   1   7   5   0]
- [ 24  27 129  48  13  31  41]
- [  9   3  16 117   1  11  11]
- [  2  14   6   0  48   0   2]
- [  5   1   2   2   0  46   7]
- [ 11   8   6   9   3   8  85]]
-Node Classification on random seed  7730 -> 0.632
-Confusion Matrix:
- [[ 76   2  11   3   0  12  11]
- [  2 121   3   3   5   2  12]
- [  8  22 152  39  14  33  36]
- [  5   2  12 131   2   8  14]
- [  0   9   6   2  48   6   2]
- [  7   4   5   6   0  38   5]
- [  7   5   6  14   4  19  66]]
-Node Classification on random seed  7731 -> 0.638
-Confusion Matrix:
- [[ 65   2   5   6   3   8   4]
- [  7 121   4   3  13   3   3]
- [ 27  23 162  18  15  35  41]
- [ 14   2  18  89   4  10  15]
- [  1   4   4   0  61   1   7]
- [ 11   0   5   0   2  52   1]
- [ 12   0   3   6   9  13  88]]
-Node Classification on random seed  7732 -> 0.644
-Confusion Matrix:
- [[ 62   3   4   8   4  10   6]
- [  3 135   7   4   5   0   2]
- [ 21  27 161  30  27  19  43]
- [  6   6  13 102   4  13  13]
- [  1   4   7   2  54   0   0]
- [  1   1   2   4   0  55   7]
- [ 12   5  15   5   3   9  75]]
-Node Classification on random seed  7733 -> 0.591
-Confusion Matrix:
- [[ 61   3  14   5   2   9  20]
- [  1 129   8   2   6   1  12]
- [ 22  19 127  41  30  21  41]
- [ 11   4  18 102  10   5  15]
- [  1   6   2   1  53   1   6]
- [  7   1   4   0   0  52   0]
- [  8   2  11  17   5  17  67]]
-Node Classification on random seed  7734 -> 0.644
-Confusion Matrix:
- [[ 64   5   2   7   5   7  11]
- [  0 145   7   2   1   4   4]
- [ 24  44 164  28  12  16  30]
- [ 10   5  17 105   6   3  13]
- [  1  15   3   3  51   3   2]
- [  6   3   1   1   0  37   1]
- [ 10   4  10   8   5  17  78]]
-Node Classification on random seed  7735 -> 0.576
-Confusion Matrix:
- [[ 71   1   3   9   3   9  14]
- [  7 100   8   2  15   1   9]
- [ 16  26 154  50  20  28  30]
- [ 20   3   6  89   6  10  22]
- [  0   8  10   4  48   1   1]
- [  2   0   7   2   0  51   3]
- [  9   1  14  19  13  12  63]]
-Node Classification on random seed  7736 -> 0.605
-Confusion Matrix:
- [[ 66   2   1   1   3  26  10]
- [  3 121   2   2  19   6   4]
- [ 38  28 142  29  17  29  26]
- [ 19   2  13  99  12   9   2]
- [  0   3   3   1  73   3   3]
- [  7   4   3   1   6  50   4]
- [ 11   5  10   7   5  16  54]]
-Node Classification on random seed  7737 -> 0.636
-Confusion Matrix:
- [[ 67   2   7   1   3   9  10]
- [  4 126   2  11  11   1   6]
- [ 15  18 175  33  22  22  32]
- [ 28   5   8  85  16   9  12]
- [  1   8   4   0  62   1   2]
- [  3   2   3   3   1  40   3]
- [ 12   2  14   4   3  11  81]]
-Node Classification on random seed  7738 -> 0.602
-Confusion Matrix:
- [[ 72   3   2   4   4  10  18]
- [  3 139   4   4   6   4   4]
- [ 32  17 137  29  23  32  35]
- [ 10   2  20  87   4  11  13]
- [  0  10   2   1  59   1   2]
- [ 10   2   4   1   0  45   2]
- [ 23   7   9   2   4  24  63]]
-Node Classification on random seed  7739 -> 0.615
-Confusion Matrix:
- [[ 87   6   4   2   2   9   8]
- [  6 112   6   0   9   2   1]
- [ 33  14 133  40  48  18  42]
- [ 13   7  17 100   2  13  11]
- [  2   6   2   0  53   1   2]
- [  3   0   3   4   1  44   3]
- [  8   2  11   2   9  13  86]]
-Node Classification on random seed  7740 -> 0.618
-Confusion Matrix:
- [[ 62   1   2   4   2  15   8]
- [  3 112   6   1  14   1   6]
- [ 14  12 162  35  23  26  60]
- [ 13   1   8  99   4  12  17]
- [  1   3   6   4  65   3   4]
- [  7   0   3   1   0  37   7]
- [  9   1   9   5   6  25  81]]
-Node Classification on random seed  7741 -> 0.605
-Confusion Matrix:
- [[ 65   3  11   6   4  12   6]
- [  3 134   8   2   8   6   6]
- [ 23  28 124  31  27  22  36]
- [  1   3  26 105   8   7  12]
- [  0   3   3   3  57   1   3]
- [  9   3   3   1   0  49   9]
- [ 13   1   8   9   6  21  71]]
-Node Classification on random seed  7742 -> 0.61
-Confusion Matrix:
- [[ 64   5   4   7   2   8  18]
- [  4 118   3   2   8   2   6]
- [ 32  17 159  31  19  20  50]
- [  7   5  18 103   3   4  19]
- [  2   6   5   2  44   0   3]
- [  4   0   2   1   0  49   3]
- [ 14   4   7  12   9  22  73]]
-Node Classification on random seed  7743 -> 0.627
-Confusion Matrix:
- [[ 75   1   4   4   7  12   5]
- [  3 124   6   5  10   6   4]
- [ 13  21 126  51  33  22  31]
- [  5   5  14 118   5   7  11]
- [  0   3   4   2  65   0   5]
- [  5   1   5   0   2  49   4]
- [  9   3   9  11   6  19  70]]
-Node Classification on random seed  7744 -> 0.586
-Confusion Matrix:
- [[ 76   2   3   2   7  17  16]
- [  1 123   7   5   9   1   4]
- [ 16  31 121  40  19  20  59]
- [ 20   4  19  93   2   4  13]
- [  1  10   5   1  64   0   1]
- [  6   0   2   1   1  41  12]
- [  5   3  15   3   5  22  68]]
-Node Classification on random seed  7745 -> 0.583
-Confusion Matrix:
- [[ 75   0   5   1   0  19   8]
- [  2 125   5   8   2   6   3]
- [ 29  21 135  36  35  38  36]
- [ 12   3  26  84   1  10  24]
- [  3   4   2   3  59   1   2]
- [  4   0   3   0   2  44   4]
- [ 11   1  17   5   6  19  61]]
-Node Classification on random seed  7746 -> 0.655
-Confusion Matrix:
- [[ 76   0   2   3   4  12  10]
- [  9 148   9   2  10   0   0]
- [ 18  24 167  28  25  20  26]
- [ 10   7  17  87   5   2  15]
- [  0  12   4   0  69   1   2]
- [  5   4   3   1   0  41   2]
- [  8   1  11   3   6  24  67]]
-Node Classification on random seed  7747 -> 0.631
-Confusion Matrix:
- [[ 74   1   2   3  10  15   6]
- [  7 139   3   2   8   0   2]
- [ 38  19 144  25  20   9  42]
- [ 15   8  15  95   4   5  19]
- [  0   8   4   0  63   1   3]
- [  3   1   4   0   2  35   8]
- [ 18   8   8   4   9  10  81]]
-Node Classification on random seed  7748 -> 0.584
-Confusion Matrix:
- [[ 60   6   3   0   1  15  25]
- [  5  99   7   5   4   6  17]
- [ 15  13 132  50  16  45  32]
- [ 12   7   4 114   5  10  12]
- [  4   7   7   5  50   2   5]
- [  5   3   2   1   2  53   5]
- [ 10   5   8   2   7  21  76]]
-Node Classification on random seed  7749 -> 0.571
-Confusion Matrix:
- [[ 50   3   3   7   3  17  20]
- [ 10 137  10   4  14   1   4]
- [ 25  25 117  19  44  29  55]
- [  4  10  24  84   2   2  10]
- [  3   1   7   1  58   3   3]
- [  3   0   0   4   0  36  13]
- [  8   4  12   4   2  16  89]]
-Node Classification on random seed  7750 -> 0.601
-Confusion Matrix:
- [[ 76   1   4  10   3   8   2]
- [  1 139   5   7   6   0   6]
- [ 36  32 114  39  14  33  32]
- [ 10   3  21 106   5   5  18]
- [  0  11   1   2  55   2   4]
- [ 14   3   1   0   1  35   6]
- [ 11   4   7   9   7  15  76]]
-Node Classification on random seed  7751 -> 0.635
-Confusion Matrix:
- [[ 69   4   2  11   4  17   3]
- [  1 115  11  13   4   4   4]
- [ 30  12 167  34  24  27  28]
- [ 14   3  16 111   6   4  14]
- [  2   3   2   4  61   1   1]
- [  4   1   0   4   1  45   4]
- [  7   1   6   7   8  19  67]]
-Node Classification on random seed  7752 -> 0.624
-Confusion Matrix:
- [[ 64   2   0   2   5  17   8]
- [  6 114   2   2  12   5   6]
- [ 33  22 150  43  22  22  27]
- [ 10   9  18 108   7   5   5]
- [  1   7   5   2  60   2   0]
- [  3   4   3   1   2  55   2]
- [ 14   5   7   7  13   8  73]]
-Node Classification on random seed  7753 -> 0.653
-Confusion Matrix:
- [[ 66   2   1   4   5   8  12]
- [  6 125  10   3   2   4   5]
- [ 28  20 152  38  21  16  30]
- [ 16   1   8 114   3   2  13]
- [  0   4   4   4  68   1   1]
- [  4   0   2   1   1  44   6]
- [ 17   6  10   6   4  18  84]]
-Node Classification on random seed  7754 -> 0.588
-Confusion Matrix:
- [[ 70   1   3   9   7  10  15]
- [  3 128   6   5   5   1   9]
- [ 23  16 128  71  16  30  25]
- [ 14   1  16 108   3   3  16]
- [  5   7   3   3  49   1   3]
- [ 13   2   4   2   1  34   3]
- [ 14   3   9   4  11  16  71]]
-Node Classification on random seed  7755 -> 0.645
-Confusion Matrix:
- [[ 68   2   5   1   0  11   6]
- [  8 130   4   4  13   2   9]
- [ 20  14 159  33  17  22  38]
- [  6   1  11 111  10  11  19]
- [  2   4   2   6  54   1   4]
- [  4   3   3   0   0  43   0]
- [ 11   4   6  12   1  25  80]]
-Node Classification on random seed  7756 -> 0.58
-Confusion Matrix:
- [[ 64   0   7   4   3  15  19]
- [  5 118   1   8  17   2   7]
- [ 25  28 101  30  69  19  25]
- [  3   4  18  96   3   6  13]
- [  2   5   3   1  67   1   2]
- [  8   0   4   2   2  42   5]
- [  6   6   4   7   9  22  92]]
-Node Classification on random seed  7757 -> 0.621
-Confusion Matrix:
- [[ 64   6   6   0   3  18  11]
- [  3 135   2   1   6   4   4]
- [ 23  24 131  42  37  32  30]
- [  2   6   9  93   4   5   8]
- [  1   8   3   0  63   2   2]
- [  3   1   1   5   3  43   5]
- [  5   9   4   6   7  28  92]]
-Node Classification on random seed  7758 -> 0.569
-Confusion Matrix:
- [[ 90   1   5   8   4   2   4]
- [  7 124   5   5  10   0   9]
- [ 23  20 110  38  37  23  55]
- [ 17   2  21  96   2   6  20]
- [  4   2   4   2  50   1   3]
- [  8   3   0   0   0  42   3]
- [ 18   1  20  12  16  10  57]]
-Node Classification on random seed  7759 -> 0.632
-Confusion Matrix:
- [[ 81   2   0   4   5  11   5]
- [  1 133   4   1   7   1   1]
- [ 27  28 156  24  19  38  46]
- [ 14   0  26  87   2   9  10]
- [  1   3   3   0  53   2   3]
- [  8   0   3   3   5  47   1]
- [  8   0   9   9   6  19  75]]
-Node Classification on random seed  7760 -> 0.624
-Confusion Matrix:
- [[ 72   4   6  11   4  15   7]
- [ 11 136   5   2   4   1   5]
- [ 20  17 146  38  27  21  41]
- [  4   8  17 108   5   4  15]
- [  1   3   3   0  55   0   6]
- [  9   2   1   1   4  41   3]
- [ 10   5   5  15   2  14  66]]
-Node Classification on random seed  7761 -> 0.598
-Confusion Matrix:
- [[ 73   5   1   8   0  17  13]
- [ 10 120  13   1  12   3   3]
- [ 20  11 121  35  47  15  46]
- [ 15   2  19 104   6   8  11]
- [  2   6   3   2  69   0   0]
- [  1   0   3   2   0  43  10]
- [ 15   3  11   3   8  12  68]]
-Node Classification on random seed  7762 -> 0.528
-Confusion Matrix:
- [[ 69   2   5   4   5  14  12]
- [  4 117  11   3   2   5  10]
- [ 20  20  98  55  37  24  67]
- [ 15   4  33  67   6   1  18]
- [  2   6   5   2  67   2   2]
- [  4   3   3   1   1  43   7]
- [  8   3  15   9   3  19  67]]
-Node Classification on random seed  7763 -> 0.575
-Confusion Matrix:
- [[ 81   4   9   2   4  14   9]
- [  2 128  20   2   4   3   3]
- [ 21  20 108  38  22  21  57]
- [  5   3  25  88   2   6  26]
- [  1   8   3   1  69   1   0]
- [  1   5   3   0   5  35   8]
- [  6   7  19   3  19  13  66]]
-Node Classification on random seed  7764 -> 0.636
-Confusion Matrix:
- [[ 79   4   2   3   1   4   6]
- [  0 136   4   2   1   4   3]
- [ 22  27 145  46  11  32  35]
- [ 24   4   9 103   2   4  13]
- [  2   7   6   2  52   2   5]
- [  4   1   0   7   1  52   3]
- [ 13   7  12  12   4  13  69]]
-Node Classification on random seed  7765 -> 0.604
-Confusion Matrix:
- [[ 78   1   6   9   3  14   9]
- [  2 124   4   1  12   2   7]
- [ 35  14 129  36  30  29  43]
- [ 10   4  13  96  18   6  19]
- [  3   5   1   1  51   0   3]
- [  3   0   3   1   0  44   4]
- [ 12   4   8   4   6  11  82]]
-Node Classification on random seed  7766 -> 0.619
-Confusion Matrix:
- [[ 71   8   3   1  10   6   7]
- [  2 134   2   6   8   1   3]
- [ 33  18 136  45  27  14  32]
- [ 25   1  23  96   6   6   9]
- [  1   5   3   0  67   1   0]
- [  9   2   4   1   0  42   2]
- [ 16   1  16   9   5  10  73]]
-Node Classification on random seed  7767 -> 0.572
-Confusion Matrix:
- [[ 46  11   6   2   3  14  22]
- [  1 134  10   3   7   5   3]
- [ 22  27 117  50  34  25  36]
- [  8   3  21 101   2   4  13]
- [  1   8   7   2  60   1   1]
- [ 12   1   3   1   1  43   4]
- [  3   0  18   8   7  18  71]]
-Node Classification on random seed  7768 -> 0.638
-Confusion Matrix:
- [[ 68   5   2   1   3   7  11]
- [  7 113  15   1   9   7   0]
- [ 26  14 168  19  28  15  47]
- [ 16   6  11 105   5   3  13]
- [  1   8   6   5  56   0   2]
- [  9   2   1   1   0  48   2]
- [ 25   6   3   5   7   8  80]]
-Node Classification on random seed  7769 -> 0.604
-Confusion Matrix:
- [[ 63   1   2   4   9  14  17]
- [  4 125   2   5  15   1   4]
- [ 18  24 144  39  35  19  31]
- [ 12   6  10  89   9   0  23]
- [  1   4   2   1  65   0   2]
- [  2   2   4   7   2  38   2]
- [ 12   9  12   4   7  19  80]]
-Node Classification on random seed  7770 -> 0.598
-Confusion Matrix:
- [[ 65   4   7   6   5  10   3]
- [  6 142   5   3   4   0   3]
- [ 25  24 123  36  19  19  36]
- [ 10   6  34  99   4   2  13]
- [  0   9   4   0  59   2   3]
- [  9   3   4   2   2  47   1]
- [ 15   5  14  18   9  18  63]]
-Node Classification on random seed  7771 -> 0.579
-Confusion Matrix:
- [[ 61   3   4   6   5  13  15]
- [  3 122   6   6   7   3   2]
- [ 27  28 138  12  15  24  52]
- [ 13   0  18  89  16   4  19]
- [  1   6   7   1  50   1   2]
- [  5   3   2   2   3  60   2]
- [ 16   3  11   7  30  18  59]]
-Node Classification on random seed  7772 -> 0.622
-Confusion Matrix:
- [[ 81   5   4   4   9   8  10]
- [  8 125   1   7   3   1   5]
- [ 27  27 152  21  23  17  43]
- [ 14   6  18  96   4   3  14]
- [  1   8   6   3  61   1   1]
- [  7   4   3   1   0  41   3]
- [ 14   3  20   6   6   9  66]]
-Node Classification on random seed  7773 -> 0.646
-Confusion Matrix:
- [[ 86   2   1   4   3  12   7]
- [  5 123   6   0   6   2   6]
- [ 30  16 143  52  17  30  36]
- [ 10   4   8 117   2   2  16]
- [  0   7   3   2  59   2   2]
- [  3   1   3   5   1  40   2]
- [ 12   5  11   2   5  11  78]]
-Node Classification on random seed  7774 -> 0.6
-Confusion Matrix:
- [[ 82   2   2   5   9  11  12]
- [  2 127  15   2  17   4   5]
- [ 16  22 132  45  36  26  30]
- [ 13   4  15 104   1   7  12]
- [  0   3   1   5  54   0   2]
- [  7   0   2   1   3  34   2]
- [ 14   4  16   4   3  20  67]]
-Node Classification on random seed  7775 -> 0.636
-Confusion Matrix:
- [[ 79   3   5   4   7   5   5]
- [ 12 141   7   2   3   0   6]
- [ 23  20 154  30  30  21  31]
- [ 17   5  16  89   2   5  10]
- [  2   6   3   3  74   0   3]
- [ 12   1   3   1   0  35   3]
- [ 20   5   7  13   6   7  64]]
-Node Classification on random seed  7776 -> 0.599
-Confusion Matrix:
- [[ 76   2   8   4   3  13   6]
- [  3 127  13   1   8   2   4]
- [ 26  23 127  53  19  26  37]
- [ 16   1  18  78   5  13  13]
- [  1   5   9   4  61   1   2]
- [  3   5   2   2   0  45  10]
- [  4   4   9   5   5  13  85]]
-Node Classification on random seed  7777 -> 0.651
-Confusion Matrix:
- [[ 63   2   4   3   2  10  10]
- [  2 140   3   3   8   3   3]
- [ 26  26 157  30  23  28  31]
- [ 12   5  16 110   4   5   4]
- [  0   6   4   1  67   1   6]
- [  7   1   1   2   0  44   5]
- [  7   6  10   7   2  20  70]]
-Node Classification on random seed  7778 -> 0.641
-Confusion Matrix:
- [[ 70   6   4   6   3  12   6]
- [  2 125  16   3  10   5   1]
- [ 20  17 155  26  29  27  28]
- [ 13   2  13 108   3   3  10]
- [  1   3   7   0  62   3   4]
- [  4   3   2   1   1  47   7]
- [ 13   2  13   9   5  16  74]]
-Node Classification on random seed  7779 -> 0.598
-Confusion Matrix:
- [[ 67   2   2   7   7  14  15]
- [  7 113   4   0   5   3   6]
- [ 34  18 111  25  55  14  48]
- [  8   2  30 102   4   7  17]
- [  1   8   6   0  60   1   5]
- [  4   1   0   1   0  55   6]
- [ 10   1   1   6   8   9  90]]
-Node Classification on random seed  7780 -> 0.609
-Confusion Matrix:
- [[ 65   2   0  10   5  24   1]
- [  6 143   0   2  12   1   3]
- [ 21  28 122  44  22  18  44]
- [ 11   6  15  97  11   5  17]
- [  1   8   1   1  56   2   3]
- [  7   0   3   1   3  45   4]
- [ 15   5   2   5   9  13  81]]
-Node Classification on random seed  7781 -> 0.621
-Confusion Matrix:
- [[ 67   5   2   1   4  12  12]
- [  2 129   7   6  10   6   4]
- [ 25  29 150  27  17  16  42]
- [ 14   5  14  89  14   6  12]
- [  2   6  10   0  53   3   2]
- [  5   1   1   3   0  50   4]
- [ 18   3   4   4   3  18  83]]
-Node Classification on random seed  7782 -> 0.639
-Confusion Matrix:
- [[ 62   4   3   1   4  25   3]
- [  2 133   3   3   8   1   2]
- [ 20  20 141  24  25  21  45]
- [ 21   4  11 111   9   6  14]
- [  1   3   4   2  70   0   4]
- [  9   4   1   1   3  45   4]
- [  5   4   8   1   4  24  77]]
-Node Classification on random seed  7783 -> 0.585
-Confusion Matrix:
- [[ 77   4   0   6  12   6  10]
- [  1 123   8   2  12   5   4]
- [ 38  17 131  33  47  11  41]
- [ 14   6  16 103   1   4  11]
- [  1   4   4   6  46   1   0]
- [  9   0   2   4   2  40   5]
- [ 14   1   7  16   8  22  65]]
-Node Classification on random seed  7784 -> 0.602
-Confusion Matrix:
- [[ 67   3   8   4   4  12  12]
- [  0 129   6   7   6   1   3]
- [ 12  24 120  45  41  28  43]
- [  6   5  13 104   4  13  15]
- [  0   5   5   2  68   1   1]
- [  0   2   5   2   0  39  15]
- [  4   5   8   4   6  18  75]]
-Node Classification on random seed  7785 -> 0.622
-Confusion Matrix:
- [[ 70   1   1   5   4  17   1]
- [  3 134  10   3   6   0   6]
- [ 18  19 123  31  54  26  31]
- [  5   3  14 113  10   7  11]
- [  0   6   0   0  59   2   3]
- [  5   2   1   0   0  45   1]
- [ 13   5   9  10   9  26  78]]
-Node Classification on random seed  7786 -> 0.595
-Confusion Matrix:
- [[ 68   6  13   5   5  12   2]
- [  4 112   2   1   7   3   1]
- [ 21  22 137  42  22  46  41]
- [  9   6  15 109   6   8   5]
- [  0   7   4   4  58   2   8]
- [  2   1   2   3   1  42   3]
- [ 13   6  12   8   3  22  69]]
-Node Classification on random seed  7787 -> 0.628
-Confusion Matrix:
- [[ 81   3   0   2   2  14   7]
- [  5 122   8   4   3   1   2]
- [ 13  26 137  36  21  17  40]
- [ 20   5  21  93   2   5  14]
- [  1   7   4   4  62   1   3]
- [  7   3   1   1   1  54   2]
- [  6   7   7  11   4  31  79]]
-Node Classification on random seed  7788 -> 0.612
-Confusion Matrix:
- [[ 81   6   2   8   3   9   5]
- [  6 131   1   4   7   1   2]
- [ 31  17 129  24  34  38  35]
- [ 14   7   9  96  16  11  20]
- [  0  10   1   2  66   0   1]
- [  5   2   2   1   0  47   3]
- [ 17   3   2   7  13   9  62]]
-Node Classification on random seed  7789 -> 0.577
-Confusion Matrix:
- [[ 60   1   1   3   1  18  27]
- [  5 122   4   4   6   1  10]
- [ 21  41 107  59  20  27  38]
- [ 14   8  14 104   5   4  17]
- [  0   3   1   2  62   3   1]
- [  6   0   0   0   0  47   4]
- [ 13   4  10   2  10  15  75]]
-Node Classification on random seed  7790 -> 0.611
-Confusion Matrix:
- [[ 61   1  10   2   3  20  10]
- [ 13 135   7   1   7   2   2]
- [ 25  23 140  30  23  34  28]
- [ 10   8  13  91   4   8  10]
- [  2   8   2   5  64   2   2]
- [  2   3   5   0   1  45  11]
- [  6   4  11   2   4  25  75]]
-Node Classification on random seed  7791 -> 0.633
-Confusion Matrix:
- [[ 59   7   6   5   2   5  20]
- [  1 118   7   1   7   4   3]
- [ 22  13 163  29  35  19  28]
- [ 13   6  28 104   5   7   6]
- [  0   8   3   1  62   2   4]
- [  4   2   2   0   1  42   9]
- [ 12   2   8   5  10  15  85]]
-Node Classification on random seed  7792 -> 0.624
-Confusion Matrix:
- [[ 58   4   6   7   1   9  10]
- [  2 133   3   2  10   8   2]
- [ 28  20 148  38  22   9  45]
- [ 14   5   8  93   8  11  21]
- [  1   1   3   2  70   3   3]
- [  3   0   2   1   1  51   6]
- [  8   2   6  26   6   9  71]]
-Node Classification on random seed  7793 -> 0.615
-Confusion Matrix:
- [[ 77   0   1   4   5  16   6]
- [  1 129  10   6   7   6   1]
- [ 33  25 121  53  37  12  33]
- [ 15   2  16 103   3   5  16]
- [  0   7   1   2  70   0   1]
- [  1   1   6   2   0  46   3]
- [  9   7   7   4   4  17  69]]
-Node Classification on random seed  7794 -> 0.625
-Confusion Matrix:
- [[ 62   1   6   5   2   7  15]
- [  2 135   6   2   8   5   2]
- [ 27  23 125  47  29  31  31]
- [  8   6  10 110   6   3  16]
- [  2   6   5   4  67   0   1]
- [  4   2   4   4   1  39   6]
- [  7   0  11   8   9   3  87]]
-Node Classification on random seed  7795 -> 0.629
-Confusion Matrix:
- [[ 88   6   4   8   2   7   6]
- [  6 117   6   5  16   8   1]
- [ 29  11 155  24  28  19  31]
- [  9   4  20  98   8   6  17]
- [  0   1   5   1  67   5   1]
- [  8   0   1   2   2  31  15]
- [ 11   1   7   7  11  12  73]]
-Node Classification on random seed  7796 -> 0.627
-Confusion Matrix:
- [[ 63   2   9   6   2  11   7]
- [  2 131   1   3  13   1   4]
- [ 47  25 133  40  33  17  32]
- [  7   2   9 103   5   4  12]
- [  1   5   3   1  55   1   2]
- [  4   0   0   2   0  55   7]
- [ 17   0   9   8   6  13  87]]
-Node Classification on random seed  7797 -> 0.616
-Confusion Matrix:
- [[ 76   1   6  11   3   5  12]
- [  4 134   7   1   4   5   7]
- [ 23  21 144  36  16  24  57]
- [ 10   7  22  89   2   2  24]
- [  1   8   6   0  54   1   2]
- [  5   2   5   0   0  47   4]
- [  9   1   8   7   5  10  72]]
-Node Classification on random seed  7798 -> 0.58
-Confusion Matrix:
- [[ 49   5   8   8   6  14  15]
- [ 12 129   5   0  10   5   4]
- [ 20  20 148  46  22  24  45]
- [  4   2  23  88   2   9  22]
- [  2   4   2   4  59   0   2]
- [  3   2   2   0   0  43   8]
- [  7   3  16   3  11  20  64]]
-Node Classification on random seed  7799 -> 0.606
-Confusion Matrix:
- [[ 60   8   3   5   7  15  12]
- [  6 112   3   2  18   1   2]
- [ 49  22 143  27  20  27  29]
- [ 14   4  19 117   4   5   7]
- [  1   7   2   0  57   3   2]
- [  9   2   0   3   2  41   5]
- [  9   3   5   5   9  18  76]]
-Node Classification on random seed  7800 -> 0.582
-Confusion Matrix:
- [[ 69   1  11  10   3   6  12]
- [  5 134   3   3   5   1   1]
- [ 22  46  82  54  44  25  22]
- [  9   5   8 109   3  14  12]
- [  4  11   1   1  68   0   4]
- [  5   2   1   2   0  46   2]
- [ 10   7  14   5   3  21  74]]
-Node Classification on random seed  7801 -> 0.598
-Confusion Matrix:
- [[ 71   4   7   4   3  15  10]
- [  1 126  12   2   4   3   1]
- [ 22  14 131  55  34  37  28]
- [ 18   6   8  94   6   6  16]
- [  2   4   3   3  65   1   1]
- [ 12   2   1   1   1  44   7]
- [  8   4   5   8   7  16  67]]
-Node Classification on random seed  7802 -> 0.633
-Confusion Matrix:
- [[ 57   1   3  10   3   9  17]
- [  5 134   2   1  11   1   4]
- [ 21  17 147  30  34  17  49]
- [ 13   0  12 101   7   7  16]
- [  1   7   3   1  67   0   2]
- [  5   2   6   0   4  45   3]
- [  8   3   9   8   7   8  82]]
-Node Classification on random seed  7803 -> 0.625
-Confusion Matrix:
- [[ 77   1   4   4   3   4   5]
- [  1 124  14   2   8   1   4]
- [ 38  14 130  57  31  13  43]
- [  4   2  19  97   5   7  10]
- [  1   3   5   5  71   0   6]
- [  4   3   4   3   0  53   3]
- [ 10  11   7   6   2   8  73]]
-Node Classification on random seed  7804 -> 0.634
-Confusion Matrix:
- [[ 86   4   5   8   3   9   1]
- [  4 124   7   3   6   5   1]
- [ 26  26 129  32  24  15  38]
- [ 20   7  11 100   2   6   6]
- [  2   6   4   4  65   0   6]
- [ 11   3   0   1   0  52   8]
- [  9   2   9  11  12   9  78]]
-Node Classification on random seed  7805 -> 0.608
-Confusion Matrix:
- [[ 65   8   2   7   7  13  13]
- [  2 115   7   5  18   2   2]
- [ 31  19 159  23  13  30  46]
- [ 11   3  13  91   1   8  15]
- [  2   5   8   1  61   0   3]
- [  7   1   0   0   0  33  14]
- [ 13   3  10   5  10  11  84]]
-Node Classification on random seed  7806 -> 0.624
-Confusion Matrix:
- [[ 61   1   5   8   4  17   5]
- [  3 114  13   4   5   2   0]
- [  9  30 148  37  23  33  45]
- [  9   6  17 110   2   5  12]
- [  1   7   4   3  66   3   2]
- [  1   1   3   5   0  49   1]
- [  2   8  12   8   1  19  76]]
-Node Classification on random seed  7807 -> 0.638
-Confusion Matrix:
- [[ 93   0   6   1   4  11   7]
- [  4 126   9   5   1   4   4]
- [ 22  26 147  28  15  22  49]
- [  8   0  15 108   8  16  11]
- [  1   7   4   2  54   0   3]
- [  8   1   4   0   2  39   1]
- [ 16   1  12   7   3  14  71]]
-Node Classification on random seed  7808 -> 0.603
-Confusion Matrix:
- [[ 72   2   7   3   3   7  13]
- [  2 131  11   8   6   3   3]
- [ 19  20 148  29  26  21  33]
- [ 21   6  22  95  12   5   5]
- [  1   7   2   1  55   1   2]
- [ 14   3   2   3   0  34   2]
- [ 17   9   8   9   5  24  68]]
-Node Classification on random seed  7809 -> 0.603
-Confusion Matrix:
- [[ 53   5   9   3   2  28   9]
- [  2 121   4   7   5   1   3]
- [ 20  22 159  31  28  18  45]
- [ 11   4  17  90  22   5  15]
- [  0   6   7   2  60   4   3]
- [  1   0   4   2   0  47   5]
- [  7   3   6  11  10  10  73]]
-Node Classification on random seed  7810 -> 0.624
-Confusion Matrix:
- [[ 73   4  10   0   0   6   7]
- [  4 141   2   3   2   4   0]
- [ 21  25 146  36  30  25  43]
- [  6   4  21 100   7   8  13]
- [  2   7   5   1  55   1   2]
- [  7   6   1   0   0  37   9]
- [ 17   9   5   2   8  13  72]]
-Node Classification on random seed  7811 -> 0.631
-Confusion Matrix:
- [[ 74   5  10   5   5  13   9]
- [  3 133   8   3   2   2   4]
- [ 30  20 143  39  32  20  29]
- [  5   1  17 106   3   9  12]
- [  0   7   0   0  53   3   2]
- [  0  11   8   0   1  41   1]
- [  8   4  10   6   7  15  81]]
-Node Classification on random seed  7812 -> 0.614
-Confusion Matrix:
- [[ 72   4   5   7   1   9  10]
- [  5 116   6   0   4   8   7]
- [ 29  23 117  18  34  45  31]
- [ 16   3  14 107   1   6  13]
- [  3   2   0   3  72   1   1]
- [  9   0   4   0   4  58   2]
- [  6   4  24   5   4  15  72]]
-Node Classification on random seed  7813 -> 0.568
-Confusion Matrix:
- [[ 63   7  13   4   7  23   8]
- [  3 139   3   1   7   5   4]
- [ 43   9 106  64  23  29  28]
- [ 15   0  13  90   6   9  11]
- [  2   4   4   0  54   1   6]
- [  8   4   4   4   0  44   4]
- [  9   2   7   5   5  28  72]]
-Node Classification on random seed  7814 -> 0.615
-Confusion Matrix:
- [[ 67   2   5   3   4  16   9]
- [  4 135   1   2   8   1   9]
- [ 21  29 146  16  30  28  32]
- [  3   2  21 101  11  13   9]
- [  1   9   0   1  69   2   4]
- [  9   1   1   6   1  43   6]
- [ 12   3  15   7  12  16  54]]
-Node Classification on random seed  7815 -> 0.635
-Confusion Matrix:
- [[ 67   3   1   9  11  14   4]
- [ 10 135   7   4   5   2   2]
- [ 40  21 153  34  34   9  28]
- [  7   3  14 110   3   7  10]
- [  0   5   3   4  66   3   1]
- [  7   0   2   2   0  33   4]
- [ 17   3   4   8   7  13  71]]
-Node Classification on random seed  7816 -> 0.602
-Confusion Matrix:
- [[ 65   2  11   6   5  14   8]
- [  8 119   7   1  12   3   0]
- [ 20  18 148  29  34  21  41]
- [  9   6  17  88  22   7  14]
- [  1   7   2   1  55   0   5]
- [  1   1   9   1   0  41   4]
- [  5   7  16   2  10  11  86]]
-Node Classification on random seed  7817 -> 0.623
-Confusion Matrix:
- [[ 61   3  11   1   5   8  10]
- [  3 134   2   2   2   6   0]
- [ 19  34 148  45  25  23  35]
- [ 13  11   9 108   4   5  10]
- [  3   7   4   0  52   2   1]
- [  5   3   4   0   2  50   4]
- [  9   5   5   6   9  22  70]]
-Node Classification on random seed  7818 -> 0.625
-Confusion Matrix:
- [[ 87   2  11   3   5   3  11]
- [  6 116   7   3   5   0   7]
- [ 26  28 136  37  35  16  29]
- [  8   9  12 107   5  11  10]
- [  3   5   4   8  59   0   2]
- [  7   1   2   0   0  45   6]
- [ 16   2   7   8  10   5  75]]
-Node Classification on random seed  7819 -> 0.608
-Confusion Matrix:
- [[ 77   2  11   3   5   7   5]
- [  3 110   6   1  14   0   3]
- [ 25  21 127  23  41  31  37]
- [ 13   7  17 109   8   8  12]
- [  1   5   5   1  58   0   1]
- [  5   1   1   0   2  53  11]
- [ 11   0   8   8  21   8  74]]
-Node Classification on random seed  7820 -> 0.564
-Confusion Matrix:
- [[ 67   1  11   1   3  10  17]
- [  3 136  11   2   7   2   3]
- [ 23  19 126  33  27  18  57]
- [ 10  21  20  80   6  14  19]
- [  4   4   3   3  54   0   3]
- [  5   0   4   3   0  31  13]
- [ 13   2   8  13  13   7  70]]
-Node Classification on random seed  7821 -> 0.583
-Confusion Matrix:
- [[ 68   5   2  14   4   4   8]
- [  6 121   7   5   4   5   2]
- [ 40  17 103  41  51  23  34]
- [ 14   5  10  93  12   7  12]
- [  0   6   7   1  65   1   0]
- [  4   0   3   1   0  51  12]
- [ 11   2  10   7   6  14  82]]
-Node Classification on random seed  7822 -> 0.656
-Confusion Matrix:
- [[ 71   3   6  11   4   6  13]
- [  6 125   3   0   0   1   2]
- [ 11  17 161  44  28  13  37]
- [  9   2  16 114  10   2  13]
- [  2   8   7   2  54   1   4]
- [  6   0   4   7   0  44   5]
- [  6   5  10   5   5  10  87]]
-Node Classification on random seed  7823 -> 0.651
-Confusion Matrix:
- [[ 69   4   0   7   4   6  12]
- [  5 143   2   5   3   3   5]
- [ 31  19 154  31  23  11  41]
- [ 14  10  17  95   7   5  11]
- [  0   5   3   0  60   1   3]
- [  6   0   2   1   1  57   4]
- [  6   5   9   5   7  15  73]]
-Node Classification on random seed  7824 -> 0.605
-Confusion Matrix:
- [[ 63   4   8   3   3  11  15]
- [  3 134   4   6   9   4   1]
- [ 23  18 127  34  19  17  53]
- [ 19   1  12  98   9   8  21]
- [  2   3   3   5  63   0   1]
- [  6   1   5   1   1  52   4]
- [ 11   5  10   9  14   9  68]]
-Node Classification on random seed  7825 -> 0.615
-Confusion Matrix:
- [[ 60   3   3   4   4   9  11]
- [  5 132   7   2   1   1   5]
- [ 19  30 144  47  27  16  49]
- [  8   3  11  98   2   6   9]
- [  2   6   5   4  57   0   5]
- [  9   1   5   1   1  46   8]
- [ 11   3  12  13   7  10  78]]
-Node Classification on random seed  7826 -> 0.664
-Confusion Matrix:
- [[ 87   3   2   5   3   9   8]
- [  3 115   2   2   3   3   1]
- [ 24   7 166  24  23  27  54]
- [ 10   2  14 108   3   2  18]
- [  2   7   5   0  56   0   2]
- [  4   2   3   1   3  55   8]
- [  9   5  14   1   4  14  77]]
-Node Classification on random seed  7827 -> 0.611
-Confusion Matrix:
- [[ 87   1   2   2   5   3  12]
- [ 11 113   6   1   7   1   5]
- [ 38  28 134  33  27  10  35]
- [ 11   6  24  90   8   9  10]
- [  1   6   4   0  64   1   5]
- [ 10   0   2   5   2  41   7]
- [ 20   6   8   4  11   2  82]]
-Node Classification on random seed  7828 -> 0.586
-Confusion Matrix:
- [[ 55   2  17  30   0  12   6]
- [  6 124   6   1   9   5   4]
- [ 18  18 155  27  34  24  31]
- [ 12   1  21 104   4  16  11]
- [  2   8   3   1  54   0   4]
- [  4   1   5   2   0  34   3]
- [ 13   2  17  19   2  13  60]]
-Node Classification on random seed  7829 -> 0.6
-Confusion Matrix:
- [[ 50   5  10   7   6  21   9]
- [  0 136   4   0   9   2   9]
- [ 30  32 142  47  20  23  28]
- [ 12   6  15  94   4   4  10]
- [  0   9   2   5  56   0   5]
- [  8   1   1   0   0  43   2]
- [ 11   3   4   4  11  21  79]]
-Node Classification on random seed  7830 -> 0.639
-Confusion Matrix:
- [[ 77   4   0   2   3   7   7]
- [ 11 129   5   1   3   1   6]
- [ 28  16 168  25  26  22  36]
- [ 13   5  19  90   5   4  21]
- [  3   6   5   3  60   1   4]
- [ 10   1   6   0   0  42   4]
- [ 23   0   5   6   6   8  73]]
-Node Classification on random seed  7831 -> 0.624
-Confusion Matrix:
- [[ 80   1   3   8   5  12  11]
- [  3 129   4   4  10   4   9]
- [ 25  25 137  33  31  28  37]
- [ 14   5  16  99   4   6   7]
- [  2   3   0   0  56   1   3]
- [  6   5   1   1   2  52   3]
- [ 14   4   5   6   5  10  71]]
-Node Classification on random seed  7832 -> 0.61
-Confusion Matrix:
- [[ 78   5   2  16   2  10   2]
- [  3 114   7   2   7   2   7]
- [ 29  15 132  30  26  26  51]
- [ 21   9  15 110   3   2  13]
- [  1   6   2   0  60   0   9]
- [  9   2   1   0   0  42   9]
- [ 17   1   5   9   3  11  74]]
-Node Classification on random seed  7833 -> 0.63
-Confusion Matrix:
- [[ 65   1   6   6   4   9  11]
- [  1 136   6   0   9   5   3]
- [ 28  22 145  27  36  18  32]
- [ 10   2  19 112   4   4  19]
- [  0   4   4   1  61   1   2]
- [ 10   1   4   2   1  42   3]
- [ 15   1  14   7   9   9  69]]
-Node Classification on random seed  7834 -> 0.549
-Confusion Matrix:
- [[ 67   1  14   6   8  18   3]
- [  2 119   7   5  14   1   6]
- [ 28  23 138  47  25  24  27]
- [ 21   4  32  61   8  20  11]
- [  2   8   6   1  51   0   2]
- [  7   3   0   4   1  44   1]
- [ 16   2   4  10   7  22  69]]
-Node Classification on random seed  7835 -> 0.63
-Confusion Matrix:
- [[ 79   4   4   6   4   5   2]
- [  3 133   6   5   9   1   1]
- [ 19  28 166  40  24  33   7]
- [ 11   5  16  97   9   2  12]
- [  0   6   5   4  60   2   1]
- [  3   2   5   3   7  42   2]
- [ 12   7  12  20   4  19  53]]
-Node Classification on random seed  7836 -> 0.612
-Confusion Matrix:
- [[ 81   2   7   5   2   7  18]
- [  2 129   5   2   3   3   3]
- [ 25  32 136  47  20  14  44]
- [  8   3  13  92  12   4  22]
- [  1   7   6   0  51   6   0]
- [  0   1   3   1   0  40  11]
- [  5   7  14  10   6   7  83]]
-Node Classification on random seed  7837 -> 0.645
-Confusion Matrix:
- [[ 79   2   7   2   8  10   2]
- [  2 129   4   2  12   5   2]
- [ 20  15 148  30  21  28  55]
- [  6   4   8  93   5  12  17]
- [  3   5   4   1  44   4   2]
- [  2   2   0   1   3  57   4]
- [  7   0   6   5   9  18  95]]
-Node Classification on random seed  7838 -> 0.591
-Confusion Matrix:
- [[ 70   9   7   2   7   8  10]
- [  8 119   5   2   3   3   5]
- [ 32  19 133  41  37  16  48]
- [ 15   3  13 108   5   6   8]
- [  0   8   4   0  51   1   2]
- [  4   3   5   1   2  33   7]
- [ 13   7   8  11   6  15  77]]
-Node Classification on random seed  7839 -> 0.605
-Confusion Matrix:
- [[ 75   8   6   5   4   8   5]
- [  5 117  17   0   5   1   7]
- [ 35  25 140  42  37  16  35]
- [ 11   6   3 114   3   4  10]
- [  2   8   5   3  58   0   1]
- [  5   0   4   6   3  40   2]
- [  8   5  14   7  12  12  61]]
-Node Classification on random seed  7840 -> 0.571
-Confusion Matrix:
- [[ 81   4   9   3   5   9   6]
- [  4 112   6   0  13   3  12]
- [ 25  40  91  15  42  38  53]
- [ 18   3  17 110   8   4   8]
- [  1   4   2   0  68   1   2]
- [  4   0   3   1   0  48   5]
- [ 12   3   2   9  13  22  61]]
-Node Classification on random seed  7841 -> 0.64
-Confusion Matrix:
- [[ 70   1   1   6   4  15   5]
- [  4 124   8   2  18   4   6]
- [ 31  14 151  32  27  30  20]
- [  8   2  13 121   7   8   9]
- [  3   4   5   3  59   2   1]
- [  6   1   2   3   0  45   2]
- [ 16   4  12  10   1  10  70]]
-Node Classification on random seed  7842 -> 0.617
-Confusion Matrix:
- [[ 70   2   2   5   1  12  10]
- [  5 120   9   4   2   3   4]
- [ 28  22 134  35  40  31  38]
- [ 11   3   9  99   2   5  28]
- [  0   6   3   2  57   1   0]
- [  1   3   0   2   0  53   7]
- [ 10   4   5   4   7  17  84]]
-Node Classification on random seed  7843 -> 0.587
-Confusion Matrix:
- [[ 87   2   6   1   7   4   9]
- [  3 128   3   3  17  10   1]
- [ 27  15 103  39  44  27  45]
- [  9   2   9 107   8   5  18]
- [  1   5   3   0  57   1   1]
- [  7   4   4   2   4  42   3]
- [ 14   4  10  11  12  13  63]]
-Node Classification on random seed  7844 -> 0.581
-Confusion Matrix:
- [[ 88   3   5   4   1  11   9]
- [  4 128   7   1   7   3   3]
- [ 32  24 119  43  33  29  32]
- [ 23   1  29  95   9   3  14]
- [  1   9   0   0  48   0   2]
- [  6   4   0   1   0  39   3]
- [  9   6  18   6   5  19  64]]
-Node Classification on random seed  7845 -> 0.617
-Confusion Matrix:
- [[ 58   2  11  10   3  15   7]
- [  6 136   2   3   4   3   1]
- [ 18  23 124  35  27  30  39]
- [  2   6  18 111   6  10  11]
- [  2  12   2   0  54   1   1]
- [  4   2   2   1   2  51   5]
- [  6   2  14  10   7  18  83]]
-Node Classification on random seed  7846 -> 0.586
-Confusion Matrix:
- [[ 74   9   4   4   2  10   1]
- [  5 122   2   8  10   5   2]
- [ 15  24 124  33  31  41  50]
- [ 21   2   9  98   4   7  13]
- [  1   7   1   0  56   2   5]
- [  4   3   1   4   2  40   7]
- [ 19   7  12   5   5  17  72]]
-Node Classification on random seed  7847 -> 0.599
-Confusion Matrix:
- [[ 64   1   1   6   3  22   9]
- [  5 132   3   5  10   5   3]
- [ 20  18 134  33  35  30  51]
- [ 12   2  10  89  14  20  11]
- [  1   4   1   0  64   0   5]
- [  5   1   3   3   0  46   3]
- [ 16   3   6  10   3   8  70]]
-Node Classification on random seed  7848 -> 0.64
-Confusion Matrix:
- [[ 68   1   1   4   0   5  15]
- [ 10 139   3   2   6   9   0]
- [ 31  29 135  55  15  10  44]
- [ 11   8  11 105   3   2  13]
- [  1   5   4   2  58   1   2]
- [  3   2   3   5   1  50   5]
- [ 11   6   6   5   5   5  85]]
-Node Classification on random seed  7849 -> 0.633
-Confusion Matrix:
- [[ 85   7   5   5   3   7   3]
- [  6 129   5   4   7   6   2]
- [ 32  21 104  54  32  12  29]
- [  7   5   9 128   6   5  11]
- [  3   9   2   0  71   2   1]
- [  5   4   1   4   1  44   8]
- [ 20   3   2  10   3   6  72]]
-Node Classification on random seed  7850 -> 0.605
-Confusion Matrix:
- [[ 63   1   3  10   1   6   8]
- [ 11 114   8   3   8   5   3]
- [ 12  21 144  28  37  34  49]
- [ 13   2  17 106   9   9   9]
- [  1   3   6   2  56   0   3]
- [  5   4   2   1   3  48   4]
- [  8   3  11   9   7  16  74]]
-Node Classification on random seed  7851 -> 0.615
-Confusion Matrix:
- [[ 69   1   1   7   7   9  15]
- [  3 128   9   5   4   5   6]
- [ 15  13 133  42  15  23  54]
- [ 10   3  12  99   9  11  11]
- [  1   4   6   0  65   3   4]
- [  8   0   4   2   0  38  14]
- [  9   1   7  11   8  13  83]]
-Node Classification on random seed  7852 -> 0.597
-Confusion Matrix:
- [[ 75   3   2   2   6  15   8]
- [  9 119  16   2   2   4   3]
- [ 43  20 111  45  17  26  34]
- [ 16   2  14  95   7   4  15]
- [  1   9   4   1  61   1   5]
- [  5   0   4   1   1  45   2]
- [  9   9   6   2   7  21  91]]
-Node Classification on random seed  7853 -> 0.623
-Confusion Matrix:
- [[ 83   0   6  10   4   4  17]
- [  2 118   3   7   4   6   3]
- [ 19  23 150  25  40  30  29]
- [ 11   4  11 105   4   6  14]
- [  5   8   7   0  66   0   0]
- [  9   1   1   0   0  38   8]
- [  7   8   8   9  11  13  63]]
-Node Classification on random seed  7854 -> 0.6
-Confusion Matrix:
- [[ 65   5   2   3  12  14  13]
- [  2 144   7   0   4   4   1]
- [ 29  39 120  29  28  20  40]
- [ 11   2  11  96   3   7  14]
- [  1   7   8   2  62   3   3]
- [  7   1   6   3   0  40   5]
- [ 15   4   8   8   9  10  73]]
-Node Classification on random seed  7855 -> 0.615
-Confusion Matrix:
- [[ 63   0   2   6   2  20  17]
- [  2 124   4   7  10   1   5]
- [ 21  22 134  41  35  18  51]
- [ 16   6   8 103   5   8  11]
- [  1   6   7   2  52   1   2]
- [  2   1   2   1   0  51   4]
- [ 12   2   2   2   9  11  88]]
-Node Classification on random seed  7856 -> 0.62
-Confusion Matrix:
- [[ 81   2   3   5   4   4   6]
- [  2 126   8   1   5   2   6]
- [ 29  33 129  26  40  16  48]
- [ 11   7  17  96   9   7  16]
- [  1   6   2   0  59   0   5]
- [  4   2   1   2   0  51  10]
- [  8   2   7   9   8   6  78]]
-Node Classification on random seed  7857 -> 0.675
-Confusion Matrix:
- [[ 81   1   3   4   3   3   8]
- [  4 146   4   2   8   0   4]
- [ 15  25 134  33  33  27  26]
- [ 17   3   8 104   5   3   6]
- [  3   7   5   3  69   0   2]
- [  4   0   3   4   1  49   7]
- [ 12   4   5   3   8   9  92]]
-Node Classification on random seed  7858 -> 0.646
-Confusion Matrix:
- [[ 73   7   1   5   3  10   7]
- [  1 127   2   5  10   3   2]
- [ 30  17 172  40  14  25  22]
- [ 25   5  10  95   6   7   9]
- [  0   3   4   2  55   0   3]
- [  4   1   1   5   1  42   4]
- [ 11   4   9  10   7  19  82]]
-Node Classification on random seed  7859 -> 0.599
-Confusion Matrix:
- [[ 75   4   7   9   7   7  11]
- [  4 118   5   5  17   2   0]
- [ 12  29 125  38  29  12  56]
- [ 12   1  18 108   6   4  14]
- [  1   5   2   5  66   3   2]
- [  4   2   2   0   1  47   9]
- [ 12   3  11   5  11  14  60]]
-Node Classification on random seed  7860 -> 0.629
-Confusion Matrix:
- [[ 73   1   8   3   1  15  13]
- [  6 117   2   2  17   1  10]
- [ 31  18 161  47  13  17  39]
- [  8   3   9  97   9   5  13]
- [  1   7   5   1  54   1   0]
- [  4   0   4   1   4  44   3]
- [ 14   3  13   1   7  11  83]]
-Node Classification on random seed  7861 -> 0.58
-Confusion Matrix:
- [[ 78   1   2   1   5  13  15]
- [  9 134   7   2   0   2   5]
- [ 30  26 110  37  35  17  54]
- [ 12   3  17  98   6  15  13]
- [  2   9   2   1  54   0   4]
- [ 11   1   3   1   1  38  10]
- [  9   5   9  10   7   8  68]]
-Node Classification on random seed  7862 -> 0.613
-Confusion Matrix:
- [[ 68   1   0   5   3  34  14]
- [  4 124   2   0   6   4   5]
- [ 23  13 127  30  26  45  37]
- [  9   4  15 109   3  11  18]
- [  0   8   3   2  61   2   5]
- [  6   1   2   0   0  38   9]
- [  6   2   5   4   5  15  86]]
-Node Classification on random seed  7863 -> 0.613
-Confusion Matrix:
- [[ 56   5   0   4   5  19   7]
- [  5 110   6   0  18   5   5]
- [ 25  14 150  45  24  26  37]
- [  4   0  33 100   6   7  11]
- [  3   1   2   0  69   2   5]
- [  0   1   2   1   1  51   4]
- [  7   3  10   6  11  17  77]]
-Node Classification on random seed  7864 -> 0.628
-Confusion Matrix:
- [[ 66   2  11   2   2   8  15]
- [  1 136   4   3   4   0   6]
- [ 18  14 153  30  41  25  26]
- [  6   2  13  94   3  17  19]
- [  1  10   3   6  58   1   1]
- [  3   0   4   0   4  47   6]
- [  8   3  12   7  13  18  74]]
-Node Classification on random seed  7865 -> 0.604
-Confusion Matrix:
- [[ 77   3  10   2   0  12  10]
- [  6 122  14   2   3   4   4]
- [ 28  42 136  24  19  18  37]
- [ 10   8  26  99   5   5  10]
- [  0  12   5   0  51   0   3]
- [  7   2   2   0   0  48   3]
- [ 10   5   4   7  10  24  71]]
-Node Classification on random seed  7866 -> 0.597
-Confusion Matrix:
- [[ 69   6   1   2   2  11  14]
- [  6 126   9   1   3   4   7]
- [ 37  21 123  42  19  36  51]
- [  7   4  11 102   2   8   7]
- [  4   7   5   2  56   1   0]
- [ 11   0   2   1   0  48   3]
- [ 15   2   6   7   5  21  73]]
-Node Classification on random seed  7867 -> 0.629
-Confusion Matrix:
- [[ 88   2   9   5   4   8   3]
- [  7 104   8   0   9   2   3]
- [ 32  20 138  60  19  14  28]
- [ 15   3   5 107   8   9  10]
- [  1   6   4   1  63   0   2]
- [ 10   1   4   0   1  53   3]
- [ 26   0  11   6   4   8  76]]
-Node Classification on random seed  7868 -> 0.63
-Confusion Matrix:
- [[ 82   2   2   3   2  19   2]
- [  5 136   5   4   4   0   1]
- [ 19  28 123  45  36  22  34]
- [ 13   1  10  93  10   7  13]
- [  2   7   5   2  62   1   3]
- [  4   2   3   1   0  49   2]
- [ 16   0   3   3  11  18  85]]
-Node Classification on random seed  7869 -> 0.574
-Confusion Matrix:
- [[ 64   3   6   6   2  12   8]
- [  5 116  11   7   7   3   6]
- [ 22  31 127  42  35  16  54]
- [ 16   3  13  93   5   4  23]
- [  1   3   6   1  59   3   1]
- [  5   1   4   2   1  45   2]
- [  7   5  16  10   5  13  70]]
-Node Classification on random seed  7870 -> 0.632
-Confusion Matrix:
- [[ 74   5   5   2   3  10  13]
- [  4 131  18   2   3   6   1]
- [ 24  22 158  24  16  23  43]
- [ 10   5  15  82   3   6  21]
- [  4   7   4   4  67   0   1]
- [  7   3   1   2   3  39   3]
- [  9   4   9   0  13  10  81]]
-Node Classification on random seed  7871 -> 0.605
-Confusion Matrix:
- [[ 67   5   8   4   2  12   7]
- [  4 114   1   0   9   0   3]
- [ 21  19 152  36  19  30  44]
- [ 14   7  16  90   1  12  18]
- [  2   8   3   7  65   0   3]
- [  3   3   0   1   1  54   4]
- [ 13   2   9   5   4  35  63]]
-Node Classification on random seed  7872 -> 0.639
-Confusion Matrix:
- [[ 66   3   1   6   0  13  16]
- [  4 117   4   0  22   4   9]
- [ 14  17 180  36  36  21  23]
- [ 11   6  16 111   1   4  10]
- [  0   4   1   3  63   1   3]
- [  4   2   1   2   2  43   4]
- [  6   3   8   5  14  21  59]]
-Node Classification on random seed  7873 -> 0.617
-Confusion Matrix:
- [[ 56   5   6   3   2   8  16]
- [  9 126   3   2   5   5   1]
- [ 28  22 163  32  21  20  37]
- [ 22   8  17 100   3   9   4]
- [  0   6   7   0  61   3   1]
- [  7   1   1   1   2  29   3]
- [ 23   4  16   3   3  14  82]]
-Node Classification on random seed  7874 -> 0.608
-Confusion Matrix:
- [[ 79   3   5   5   4  14  10]
- [  5 114   2   4   7   9   2]
- [ 24  24 128  48  34  24  32]
- [  4   2  14 121  12   6  13]
- [  0   7   2   0  66   2   2]
- [  5   4   5   0   0  44   5]
- [  6   2  12   8   5  20  56]]
-Node Classification on random seed  7875 -> 0.651
-Confusion Matrix:
- [[ 74   3   5   5   2  11   5]
- [  6 125   9   4   6   8   3]
- [ 20  20 167  49  19  18  15]
- [ 11   2  15 114   2   4   5]
- [  3   4   1   7  51   0   5]
- [  6   0   3   3   1  47   3]
- [ 14   2   9  12   5  24  73]]
-Node Classification on random seed  7876 -> 0.62
-Confusion Matrix:
- [[ 78   3   1   4   6  13  16]
- [  4 124   3   0   4   4   7]
- [ 27  18 147  24  40  19  34]
- [  9   4  25  82   7  12   6]
- [  3   4   2   5  51   2   3]
- [  4   0   1   2   4  62   2]
- [  8   5   9   7   9  20  76]]
-Node Classification on random seed  7877 -> 0.619
-Confusion Matrix:
- [[ 76   1   0   3   5  12   4]
- [  5 123   5   5   8   2   3]
- [ 19  23 126  40  25  21  55]
- [ 23   4   5 103   5   4  27]
- [  2   7   1   6  53   2   2]
- [  4   0   2   4   0  51   3]
- [  4   6   8   2   2  22  87]]
-Node Classification on random seed  7878 -> 0.607
-Confusion Matrix:
- [[ 75   0   5   4   1  14  12]
- [  9 138   1   3   3   1   2]
- [ 56  21 134  30  22  27  34]
- [ 14   2  23  91   4   8   6]
- [  0   8   8   1  56   0   2]
- [  6   4   1   3   0  48   3]
- [  9   6   9   6   7  18  65]]
-Node Classification on random seed  7879 -> 0.61
-Confusion Matrix:
- [[ 54   1   5   4   3   4  25]
- [  2 132   5   2  12   6   2]
- [ 29  19 129  37  22  21  57]
- [ 20   2   8 123   2   2  14]
- [  0   7   5   0  54   2   1]
- [  6   0   0   1   7  35   5]
- [ 20   2   2   5   9  14  83]]
-Node Classification on random seed  7880 -> 0.605
-Confusion Matrix:
- [[ 76   2   1   3   5  13   6]
- [  3 136   6   3  13   0   6]
- [ 31  12 121  54  32  21  37]
- [ 11   8  18 103   4   7  13]
- [  1   4   1   4  69   1   2]
- [  3   3   2   0   1  35   5]
- [ 12   3   6   8  15  15  65]]
-Node Classification on random seed  7881 -> 0.593
-Confusion Matrix:
- [[ 73   1   5   3   5  10   8]
- [  3 151   4   4   1   8   4]
- [ 17  32 103  58  20  29  42]
- [ 21   2  17  91  16   6  11]
- [  3   6   2   3  66   0   3]
- [  3   0   2   0   1  40   4]
- [ 14   2   0  16   6  15  69]]
-Node Classification on random seed  7882 -> 0.631
-Confusion Matrix:
- [[ 77   4   4   6   7   7   2]
- [  2 130   5   2  10   3   0]
- [ 26  17 130  32  47  15  44]
- [ 10   1  17 113   2   7  13]
- [  0   4   8   3  69   1   3]
- [  9   0   2   0   1  40   5]
- [ 13   3   4  10   6  14  72]]
-Node Classification on random seed  7883 -> 0.633
-Confusion Matrix:
- [[ 67   3   5  10   6  12   9]
- [  6 134   1   2   9   2   5]
- [ 30  21 157  20  31  18  27]
- [ 13   2  15 104  10   6   4]
- [  0   4   3   3  67   0   1]
- [ 11   0   1   0   3  44   3]
- [  9   3  21  17   8  13  60]]
-Node Classification on random seed  7884 -> 0.622
-Confusion Matrix:
- [[ 63   3   1   4   1  20  19]
- [  1 114   6   0  11   7   2]
- [ 22  12 155  23  22  21  54]
- [ 11   4   9 120   5   8  16]
- [  2   4   6   1  56   0   2]
- [ 11   1   5   2   2  34   6]
- [ 18   6   7   5   5  13  80]]
-Node Classification on random seed  7885 -> 0.582
-Confusion Matrix:
- [[ 71   6   5   3   5  15   6]
- [  4 130   8   2   2   8   4]
- [ 17  19 116  48  36  18  62]
- [ 10   4   8  87  10  11  16]
- [  1   8   2   0  57   1   3]
- [  4   2   2   0   1  41   4]
- [ 10   5  12  13   6  17  80]]
-Node Classification on random seed  7886 -> 0.599
-Confusion Matrix:
- [[ 84   2   1  10   3  12   9]
- [  2 127  10   5   8   7   5]
- [ 22  13 117  59  32  28  27]
- [ 29   4   6  82   5   6  11]
- [  2   5   2   1  75   4   4]
- [  3   1   2   3   0  49   1]
- [ 13   5   9   4   8  18  65]]
-Node Classification on random seed  7887 -> 0.66
-Confusion Matrix:
- [[ 67   0   6  11   2  20   6]
- [  5 137   6   7   2   6   4]
- [ 13  14 156  35  22  34  26]
- [  3   2   7 117   7  11   8]
- [  0   8   3   1  65   1   1]
- [  4   1   0   4   0  47   5]
- [ 11   3   6   8   9  18  71]]
-Node Classification on random seed  7888 -> 0.593
-Confusion Matrix:
- [[ 60   6   1   4   3  14  16]
- [  4 135   3   1  17   3   8]
- [ 18  30 103  30  47  28  36]
- [ 12  10  24 104   4   5   6]
- [  1   7   2   1  56   2   1]
- [  7   2   0   3   1  50   2]
- [  4   8  10   9   7  10  85]]
-Node Classification on random seed  7889 -> 0.607
-Confusion Matrix:
- [[ 67   2  16   4   4   7   8]
- [  1 144   7   3   5   4   9]
- [ 24  22 143  39  30  18  35]
- [ 11   7  16  86   9   2  20]
- [  0   5   1   2  68   2   2]
- [  6   3   1   0   0  31   5]
- [ 21   0  13   9  10  10  68]]
-Node Classification on random seed  7890 -> 0.62
-Confusion Matrix:
- [[ 74   2   1   7   2  12   9]
- [  4 121   2   4  15   2   1]
- [ 33  19 150  46  23  27  19]
- [ 18   0   7  98   2  10   8]
- [  1  10   5   1  59   1   1]
- [  5   2   6   0   3  40   5]
- [ 18   7  11  13   7  11  78]]
-Node Classification on random seed  7891 -> 0.611
-Confusion Matrix:
- [[ 70   4  13   2   3  12  16]
- [  4 122  11   4   4   2   3]
- [ 24  30 131  45  26  20  27]
- [ 13   2  11 111   7   5  13]
- [  1   6   5   5  56   1   2]
- [  9   0   1   1   0  42   7]
- [ 19   1   7   3  10  10  79]]
-Node Classification on random seed  7892 -> 0.618
-Confusion Matrix:
- [[ 67   1   5  10   5   8  10]
- [  7 127   7   2  10   3   8]
- [ 21  27 159  32  26  36  37]
- [ 11   4  11  87   3   9  17]
- [  4   4   2   0  63   0   3]
- [  5   2   1   2   1  46   2]
- [ 10   2   6  11   6  11  69]]
-Node Classification on random seed  7893 -> 0.619
-Confusion Matrix:
- [[ 78   1   2   2   5   8  19]
- [  2 139   6   3  10   1   2]
- [ 17  33 125  49  19  16  41]
- [ 20   3   7 103   9   5  12]
- [  0   8   6   0  49   0   0]
- [  4   2   2   1   1  52   8]
- [ 15   6   5  12   6  13  73]]
-Node Classification on random seed  7894 -> 0.641
-Confusion Matrix:
- [[ 75   2   2   2   1   7   8]
- [  6 126   7   4   5   4   3]
- [ 24  16 149  38  20  25  42]
- [  7   3  14  97   4   3  20]
- [  1   9   2   1  69   2   3]
- [  5   2   3   0   0  52   1]
- [ 13   2   9   9  11  19  73]]
-Node Classification on random seed  7895 -> 0.587
-Confusion Matrix:
- [[ 72   1   2   1   6  11  16]
- [  7 121   3   9   6   0  11]
- [ 34  19 129  56  26  16  43]
- [ 21   3  21  64   8   7  15]
- [  2   2   6   4  72   0   2]
- [  1   1   3   0   2  49  10]
- [ 10   1   8   3   8   8  80]]
-Node Classification on random seed  7896 -> 0.598
-Confusion Matrix:
- [[ 61   7   3   5   1  17   8]
- [  4 121   5   2   8   2  15]
- [ 19  13 133  45  15  33  48]
- [ 12   6  14  97   3  15  11]
- [  4   8   5   2  61   1   5]
- [  3   0   3   1   0  54   7]
- [ 11   2   4   7   7  21  71]]
-Node Classification on random seed  7897 -> 0.584
-Confusion Matrix:
- [[ 60   3   6   1   3  10  21]
- [ 10 131   3   2   8   4   1]
- [ 22  30 122  43  30  29  24]
- [ 22  11  16  94   6  10   7]
- [  2   8   5   2  63   1   0]
- [  6   1   0   0   1  48   6]
- [  9   4  11  11   8  19  66]]
-Node Classification on random seed  7898 -> 0.631
-Confusion Matrix:
- [[ 77   5   3   8   5   7  11]
- [  9 111   3   2   8   2   1]
- [ 36  32 170  28  14  21  22]
- [ 14   6  15 100   1   6  11]
- [  3   6   4   3  59   2   0]
- [  8   1   2   4   0  38   4]
- [ 12   4  12  11   2  21  76]]
-Node Classification on random seed  7899 -> 0.658
-Confusion Matrix:
- [[ 79   2   2   0   1  14  12]
- [  4 145   2   3  10   1   9]
- [ 22  15 168  30  14  15  36]
- [ 10   6  16  89   6   5  19]
- [  1  14   1   2  46   0   5]
- [ 11   1   2   2   2  41   3]
- [  5   4   9   1   5  20  90]]
-Node Classification on random seed  7900 -> 0.586
-Confusion Matrix:
- [[ 57   3   4   6   3  25  10]
- [  6 122   7   4   7   2  12]
- [ 39  14 154  46  25  14  41]
- [ 13   5  15  88  10   8  16]
- [  1   2   2   0  53   2   4]
- [  7   0   2   1   1  38   5]
- [  9   0   9   5  12  17  74]]
-Node Classification on random seed  7901 -> 0.555
-Confusion Matrix:
- [[ 71   3   6   6   3  13   8]
- [  4 119   3   0   7   6   3]
- [ 14  17 116  72  33  21  48]
- [ 11   5  19  79   9  18  15]
- [  0  11   4   3  65   2   2]
- [  7   3   1   1   1  42   7]
- [  3   6  17  14   4  15  63]]
-Node Classification on random seed  7902 -> 0.604
-Confusion Matrix:
- [[ 63   4   2   2   1  24  18]
- [  3 131   7   4   7   1   3]
- [ 31  31 135  33  26  33  34]
- [ 15   5   5  99   4  12  17]
- [  2  11   6   2  54   2   1]
- [  4   0   0   0   0  44   5]
- [  9   2  13   3   4  10  78]]
-Node Classification on random seed  7903 -> 0.611
-Confusion Matrix:
- [[ 71   2   1  12   6  18   9]
- [  8 137  12   2   3   3   2]
- [ 33  13 130  52  11  21  40]
- [ 11   3   8  83  15  12  10]
- [  3   5   4   3  58   1   0]
- [  2   0   4   2   2  63   4]
- [  8   2  19   3   2  18  69]]
-Node Classification on random seed  7904 -> 0.643
-Confusion Matrix:
- [[ 72   3   6   5   5   9  11]
- [  0 122   3   3  14   2   3]
- [ 13  18 175  19  19  32  39]
- [ 10   6  16  79  13   6  17]
- [  1   3   2   2  69   1   3]
- [  4   3   6   0   0  50   5]
- [ 17   6  16   9   5   2  76]]
-Node Classification on random seed  7905 -> 0.616
-Confusion Matrix:
- [[ 45   6   3  11   1  15  15]
- [  4 128   1   1  10   4   2]
- [ 17  19 165  33  34  24  27]
- [ 12   3  13  96  12  11  17]
- [  2   8   4   0  68   0   2]
- [  0   5   3   2   6  40   6]
- [ 10   3   7   2   9  20  74]]
-Node Classification on random seed  7906 -> 0.615
-Confusion Matrix:
- [[ 72   3   2   6   3   7  17]
- [  4 115  11   3  13   2   6]
- [ 14  22 146  32  44  13  44]
- [  7   5  27  94  10   2  13]
- [  5   3   3   0  63   0   1]
- [  9   0   3   1   2  43   8]
- [ 14   2   3   8   5   8  82]]
-Node Classification on random seed  7907 -> 0.638
-Confusion Matrix:
- [[ 57   1   9   6   7  14   8]
- [  6 121   9   4   8   0   6]
- [ 27  17 175  17  29  27  19]
- [ 14   4  14 118   4   4  15]
- [  1   5   5   1  50   0   3]
- [  7   4   0   2   0  38   5]
- [ 11   3  12  12  10  12  79]]
-Node Classification on random seed  7908 -> 0.64
-Confusion Matrix:
- [[ 75   1   3   2   2  10   9]
- [  6 108   4   9   3  10   3]
- [ 13  25 154  34  32  33  33]
- [ 11   5  11 116   4   8  11]
- [  1   4   1   0  65   1   1]
- [  3   3   0   2   1  47   3]
- [  5   3  10   5  13  22  75]]
-Node Classification on random seed  7909 -> 0.596
-Confusion Matrix:
- [[ 54   6  16   7   3  19   8]
- [  3 128   6   5   6   1   8]
- [ 32  17 127  23  31  42  36]
- [  3   2  11 111   4   7  15]
- [  4  11   4   0  47   0   6]
- [  4   1   1   4   1  47   3]
- [ 13   1   7   3   9  21  82]]
-Node Classification on random seed  7910 -> 0.562
-Confusion Matrix:
- [[ 48   0   6  15   8  15  18]
- [ 10 111   9   1  14   2   3]
- [ 16  19 116  36  39  31  42]
- [  6   5  20 107   8   7  11]
- [  1   2   3   1  74   0   2]
- [  4   1   1   6   0  42   4]
- [ 10   4  12  24   6  16  64]]
-Node Classification on random seed  7911 -> 0.584
-Confusion Matrix:
- [[ 64   2   0   6   7  14  16]
- [  5 129   3   8   4   0   8]
- [ 26  18 124  34  49  20  51]
- [ 21   3  11  81  10   5  18]
- [  0   7   2   0  56   0   4]
- [  6   2   3   1   0  48   5]
- [  9   0   2  12   8  16  82]]
-Node Classification on random seed  7912 -> 0.624
-Confusion Matrix:
- [[ 73   2   3   8   3   6  13]
- [  6 135   5   3   2   1   2]
- [ 23  33 120  46  22  22  45]
- [  7   2  11 109   1   5  15]
- [  2   6   8   3  57   0   3]
- [  7   3   2   1   0  47   2]
- [ 12   7   9   2   0  23  83]]
-Node Classification on random seed  7913 -> 0.626
-Confusion Matrix:
- [[ 73   1   0   4   4  17   5]
- [  6 121   2   4   5   1   4]
- [ 26  22 138  47  26  16  41]
- [ 11   6  13  98   5   3  10]
- [  3   7   3   1  78   2   3]
- [  6   2   6   1   2  34   5]
- [ 12   2   6   9   7  18  84]]
-Node Classification on random seed  7914 -> 0.626
-Confusion Matrix:
- [[ 79   6   1   5   2  18   4]
- [  5 124   3   1  17   2   6]
- [ 26  23 155  16  20  26  38]
- [ 15   5  14  93   2  12  10]
- [  6   5   3   0  57   0   5]
- [ 12   0   8   2   0  43   3]
- [  5   6   6   7   5  24  75]]
-Node Classification on random seed  7915 -> 0.647
-Confusion Matrix:
- [[ 73   3   2   7   2  10  18]
- [  8 126   5   4   8   0   3]
- [ 24  26 151  28  24  17  36]
- [ 12   5   6 126   2   5  12]
- [  4   6   3   1  60   0   0]
- [  7   2   3   9   4  34   3]
- [ 12   7   7   4   8   6  77]]
-Node Classification on random seed  7916 -> 0.641
-Confusion Matrix:
- [[ 72   1   2   6   6   4  12]
- [  6 138   2   1  12   1   7]
- [ 31  21 133  48  24  16  22]
- [ 15   5   8 109   4  10  13]
- [  1   7   3   0  72   0   2]
- [  3   4   3   6   4  37   2]
- [ 11   2   7   4   6  17  80]]
-Node Classification on random seed  7917 -> 0.609
-Confusion Matrix:
- [[ 64   1   2   8   7   9  15]
- [  3 130   4   2  10   3  11]
- [ 27  14 127  43  19  22  49]
- [ 12   0  18 108   6   3  17]
- [  2   0   2   0  50   3   5]
- [  3   0   3   5   1  44   8]
- [ 14   1  14  11   2  12  86]]
-Node Classification on random seed  7918 -> 0.551
-Confusion Matrix:
- [[ 76   3   4   6   5  11   6]
- [  4 106  13   6   7   5   4]
- [ 23  13 112  51  34  22  51]
- [ 25   5  12  83   8  12  17]
- [  1   5  12   4  50   1   1]
- [  5   0   3   1   0  49   3]
- [  6   3  23   3  10  21  75]]
-Node Classification on random seed  7919 -> 0.617
-Confusion Matrix:
- [[ 77   3   1   2   5  11   6]
- [  6 125   9   2   4   7   9]
- [ 31  20 118  53  16  26  36]
- [  8   8   5 115   2  11  18]
- [  3   6   0   2  60   1   4]
- [  3   1   2   2   1  44  10]
- [ 19   0   7   4   5  14  78]]
-Node Classification on random seed  7920 -> 0.624
-Confusion Matrix:
- [[ 58   2   9   2   3  18  13]
- [  4 151  10   4   3   2   0]
- [ 15  34 135  53  18  24  36]
- [  1   8  13 111   7   3  12]
- [  0   6   3   1  55   0   2]
- [  4   0   3   2   4  39   0]
- [  6   6   7   9   7  22  75]]
-Node Classification on random seed  7921 -> 0.666
-Confusion Matrix:
- [[ 90   5   2   6   2  12   3]
- [  3 127   3   3  11   2   8]
- [ 21  18 161  17  21  16  41]
- [ 10   1  16  93   3  14  27]
- [  1   4   1   1  70   1   1]
- [  4   0   1   0   1  44  15]
- [ 14   3   5   7   6   4  81]]
-Node Classification on random seed  7922 -> 0.63
-Confusion Matrix:
- [[ 84   3   0   5   4   8  12]
- [  8 126   4   3  12   0   3]
- [ 27  18 132  37  37  12  38]
- [ 12   3  11 106  12   8  13]
- [  0   4   3   1  55   3   4]
- [  2   1   4   1   0  42   5]
- [  9   3   9   7   7  17  85]]
-Node Classification on random seed  7923 -> 0.611
-Confusion Matrix:
- [[ 55   1  15   6   3  10  12]
- [  6 136   4   0  12   0  11]
- [ 19  41 133  25  36  16  40]
- [ 13   0  28  85   5   3  12]
- [  1   4   0   0  72   0   1]
- [  1   7   2   2   2  51   4]
- [ 13   3   7   2   8  14  79]]
-Node Classification on random seed  7924 -> 0.597
-Confusion Matrix:
- [[ 72   1   8  10   0   8   6]
- [  5 109  12   4   5   3   3]
- [ 14  24 144  58  35  16  41]
- [  0   4  29 110   3   5  11]
- [  1   9   3   1  54   1   6]
- [  0   3   3   5   2  40   4]
- [  9   5  17  13   4  12  68]]
-Node Classification on random seed  7925 -> 0.629
-Confusion Matrix:
- [[ 77   0  10   4   0   7  15]
- [  7 115   3   5  11   3  10]
- [ 18  22 154  31  29  21  37]
- [  9   5  14 108   6   6  20]
- [  6   6   2   1  59   0   0]
- [  8   0   2   2   0  42   7]
- [  4   2  13   7   4  14  74]]
-Node Classification on random seed  7926 -> 0.616
-Confusion Matrix:
- [[ 71   2   1  12   4  12   9]
- [  8 124   5   1   6   0   3]
- [ 27  34 127  35  26  16  37]
- [  8   2  11 116   6   5  16]
- [  4  10   0   1  69   1   0]
- [  4   5   2   1   1  42  14]
- [  9   7   7  11   9  12  67]]
-Node Classification on random seed  7927 -> 0.613
-Confusion Matrix:
- [[ 84   1   7  10   4   6  13]
- [  5 123  10   3   4   4   7]
- [ 16  13 150  47   9  28  47]
- [ 16   0   9  98   2  12  17]
- [  2   9   5   2  55   3   4]
- [  6   1   2   1   0  33   6]
- [ 20   4  14   5   4   9  70]]
-Node Classification on random seed  7928 -> 0.638
-Confusion Matrix:
- [[ 71   5   3   7   6   5  14]
- [  1 109   2   4  11   3   7]
- [ 34  18 154  35  29  10  35]
- [ 13   1  10 112   7   7  16]
- [  0   4   2   1  61   2   4]
- [  8   0   1   1   4  50   3]
- [  7   0  10  10   3  19  81]]
-Node Classification on random seed  7929 -> 0.63
-Confusion Matrix:
- [[ 74   2   3   4   3  14  12]
- [ 15 118   9   2   8   1   4]
- [ 31  12 165  32  18  13  38]
- [ 17   5  20 105   5   5  11]
- [  3   2   2   3  51   0   4]
- [  6   0   7   1   1  40   8]
- [ 10   2   3  10  11  13  77]]
-Node Classification on random seed  7930 -> 0.609
-Confusion Matrix:
- [[ 70   2   1   3   3   6  15]
- [  3 119   4   3  15   3   5]
- [ 30  20 141  32  18  21  47]
- [ 16   4   8 101   7   7  26]
- [  2   3   6   2  54   1   3]
- [  4   2   2   1   1  43   7]
- [ 22   2   9   5   5  15  81]]
-Node Classification on random seed  7931 -> 0.583
-Confusion Matrix:
- [[ 72   1   5   5   2  15  16]
- [  8 131   9   1   2   1   8]
- [ 34  19 121  38  21  27  50]
- [ 21   8  11  85   4   6  18]
- [  0  11   1   2  64   1   4]
- [  4   2   1   1   2  45   2]
- [  7   5  10   9   7  18  65]]
-Node Classification on random seed  7932 -> 0.64
-Confusion Matrix:
- [[ 71   4   5   5   3  18   9]
- [  2 129   6   5   6   2   3]
- [ 14  12 149  35  30  15  37]
- [  7   4  12 108  10   6  14]
- [  2  13   6   1  61   1   2]
- [  3   2   3   2   4  37  10]
- [  8   3  10  11   6   9  85]]
-Node Classification on random seed  7933 -> 0.605
-Confusion Matrix:
- [[ 80   3   1   5   4   6   0]
- [  7 112   9   5   5   4   4]
- [ 36  22 148  48  21  24  33]
- [ 10   2  24 121   3   6  15]
- [  2   6  12   1  52   0   2]
- [  6   0   8   2   1  38   4]
- [ 15   3   7   7   6  16  54]]
-Node Classification on random seed  7934 -> 0.577
-Confusion Matrix:
- [[ 56   6   6   5   1  15  20]
- [  9 127   5   3   5   0   8]
- [ 29  30 111  49  48  19  43]
- [ 12  18   8 104   8   7  11]
- [  2   4   1   3  51   3   3]
- [  5   1   0   3   0  47   5]
- [  2   3   3   8   2  10  81]]
-Node Classification on random seed  7935 -> 0.663
-Confusion Matrix:
- [[ 65   5   2   0   2  12  13]
- [  6 142   2   2   5   2   2]
- [ 17  30 151  28  24   7  32]
- [ 19   3  14  99  12  10  12]
- [  1  10   2   2  72   1   2]
- [  5   2   2   0   2  38  13]
- [ 10   2   4   3   5  10  96]]
-Node Classification on random seed  7936 -> 0.582
-Confusion Matrix:
- [[ 63   2  12   7   3  14   7]
- [  5 123   6   1  10   6   3]
- [ 15  39 147  21  18  31  41]
- [ 24   4  19  78   7   6  20]
- [  1   8   2   3  52   4   3]
- [  9   2   7   1   1  44   5]
- [ 15   4   7   2   6  17  75]]
-Node Classification on random seed  7937 -> 0.577
-Confusion Matrix:
- [[ 71   2   5   8   4  22   8]
- [ 10 125   1   1  14   5   0]
- [ 37  33 105  32  50  21  29]
- [  7   7  14  83   5   6  16]
- [  8   1   5   1  65   1   2]
- [ 10   0   0   2   1  47   3]
- [ 14   1   3   5  11  18  81]]
-Node Classification on random seed  7938 -> 0.6
-Confusion Matrix:
- [[ 59   4   7  11   3  14  10]
- [  2 127  17   6   3   2   3]
- [ 17  21 113  35  34  36  37]
- [  9   2  13 107   6   3  11]
- [  1   4   3   0  74   0   5]
- [  7   0   2   1   2  48   4]
- [ 11   4   5  10  10  25  72]]
-Node Classification on random seed  7939 -> 0.643
-Confusion Matrix:
- [[ 72   0   1   2   5  13  16]
- [  5 120   6   1   3   3   3]
- [ 30  18 169  45  15  17  28]
- [ 17   2   9  99   6   5  17]
- [  3   9   4   1  62   1   3]
- [  7   1   3   2   2  48   1]
- [ 17   3   8   5   6  14  73]]
-Node Classification on random seed  7940 -> 0.603
-Confusion Matrix:
- [[ 67   1   1   4   6  14  13]
- [  5 131   4   5  13   3   5]
- [ 29  17 110  40  25  20  55]
- [ 14   3  18 105   2   5  10]
- [  2   2   4   3  68   0   3]
- [  4   1   1   5   0  40  11]
- [ 16   1   4   4  12  12  82]]
-Node Classification on random seed  7941 -> 0.584
-Confusion Matrix:
- [[ 52   2   3   9   6  15  19]
- [ 10 111   4   5  12   4   1]
- [ 21  27 135  35  39  26  24]
- [ 11   8   8 119   4   3  13]
- [  3   6   2   2  68   2   1]
- [  9   0   2   4   2  43   4]
- [  9   5   9  21  11  15  56]]
-Node Classification on random seed  7942 -> 0.635
-Confusion Matrix:
- [[ 67   2   1  11   4  12  14]
- [  2 127   9   8   8   3   1]
- [ 20  27 148  40  18  24  29]
- [ 22   2  18 105   4   2  10]
- [  1   3  10   0  57   0   4]
- [ 11   1   1   1   0  49   2]
- [  7   4   5   2   5  17  82]]
-Node Classification on random seed  7943 -> 0.62
-Confusion Matrix:
- [[ 69   2   5   0   5  15   5]
- [  3 124   3   2   6   1   6]
- [ 20  27 138  55  27  28  26]
- [  8   5  29 110   9   5   8]
- [  1   4   4   0  54   3   0]
- [  7   1   0   2   1  51   2]
- [ 12   1  15   8   4  15  74]]
-Node Classification on random seed  7944 -> 0.63
-Confusion Matrix:
- [[ 81   2   0   7   1   7  10]
- [  3 130   9   0   9   2  10]
- [ 18  14 142  31  24  18  65]
- [ 13   3  12 104   6   9  18]
- [  7   6   5   0  49   3   4]
- [  8   0   1   7   1  38   5]
- [  7   4   2   4   5  10  86]]
-Node Classification on random seed  7945 -> 0.622
-Confusion Matrix:
- [[ 75   3   5   2   6   9  14]
- [  7 111   3   1  14   7   3]
- [ 30   9 146  26  34  21  33]
- [ 13   2  11 102  10  11  12]
- [  0   7   3   1  63   1   4]
- [ 10   1   1   2   3  41  10]
- [ 14   1   3   6  14  11  84]]
-Node Classification on random seed  7946 -> 0.597
-Confusion Matrix:
- [[ 75   6  11   6   2   6   6]
- [  2 117   3   9   7   2   4]
- [ 17  24 125  42  24  23  45]
- [ 21   6  10  99  15   4  12]
- [  2   6   4   3  60   1   3]
- [  5   5   1   2   0  43   5]
- [ 18   8  10   2  10  11  78]]
-Node Classification on random seed  7947 -> 0.608
-Confusion Matrix:
- [[ 76   2   3  10   3  10  16]
- [  3 144   8   2   0   5   2]
- [ 22  20 121  20  33  22  63]
- [ 10   5  29  86   1   8  11]
- [  2   8   2   0  58   2   3]
- [  1   2   0   2   2  47   3]
- [  8   3   7   8  11  20  76]]
-Node Classification on random seed  7948 -> 0.603
-Confusion Matrix:
- [[ 64   5   4   4   5  13  11]
- [  6 118  16   3   7   2   5]
- [ 30  14 123  51  36  22  43]
- [ 13   7  10  97   4   4  13]
- [  2   3   4   4  64   1   0]
- [  4   1   1   0   2  46   6]
- [  7   0   6   4   9  15  91]]
-Node Classification on random seed  7949 -> 0.629
-Confusion Matrix:
- [[ 64   4   5   3   2  18  12]
- [  3 127  13   1   3   0   2]
- [ 15  21 153  44  26  16  30]
- [ 12   9  18  94   2   6  12]
- [  1   4   6   2  63   2   0]
- [  4   0   3   0   2  43   5]
- [ 16   6  15   5  10  13  85]]
-Node Classification on random seed  7950 -> 0.604
-Confusion Matrix:
- [[ 72   3   0  11   2  21  11]
- [  5 120   1   5   9   6   1]
- [ 26  30 146  38  15  35  33]
- [ 15   6   8  85   2   2  23]
- [  2   8   4   0  60   3   3]
- [  6   1   0   2   0  48  12]
- [  4   2  12   3   6  20  73]]
-Node Classification on random seed  7951 -> 0.594
-Confusion Matrix:
- [[ 75   5  11   4   4   7   6]
- [  6 136   1   1   6   1   0]
- [ 26  42 112  38  38  19  44]
- [  4   3  16 103   6   8   5]
- [  2   8   4   1  58   2   0]
- [  7   2   5   2   2  51   3]
- [  7   2  18  15   7  18  59]]
-Node Classification on random seed  7952 -> 0.601
-Confusion Matrix:
- [[ 65  13   8  11   2  13  13]
- [  5 117   6   7   7   3   3]
- [ 28  16 161  34  30  22  34]
- [ 16   5  18  89   3   6   9]
- [  0   4   4   5  61   0   2]
- [ 10   1   2   1   0  43   4]
- [  5   4  18   9   5  13  65]]
-Node Classification on random seed  7953 -> 0.626
-Confusion Matrix:
- [[ 73   1  10   4   1   7   6]
- [  2 137   6   4  12   3   4]
- [ 29  13 147  34  27  18  33]
- [ 13   5  21  88   5   9   8]
- [  2  10   3   1  62   0   1]
- [  5   2   5   1   0  45   2]
- [ 13   7  19   6   9  13  74]]
-Node Classification on random seed  7954 -> 0.61
-Confusion Matrix:
- [[ 62  10   3  10   3   9  18]
- [  2 134   4   2  13   1   3]
- [ 33  19 148  35  44  24  27]
- [  6   3  12  94   1   6  12]
- [  4   5   3   2  50   0   1]
- [  5   0   4   2   1  43  10]
- [  6   2  17   5   4  19  79]]
-Node Classification on random seed  7955 -> 0.602
-Confusion Matrix:
- [[ 79   3   2   3   6  14   1]
- [  5 141   4   2   9   5   3]
- [ 28  29 121  36  30  37  27]
- [ 13  10  14 101   5   4   7]
- [  0  12   0   0  51   2   1]
- [  5   0   1   8   1  38   7]
- [ 18   8   6   5  11  16  71]]
-Node Classification on random seed  7956 -> 0.634
-Confusion Matrix:
- [[ 77   3   8   2   4  10   6]
- [  4 129   3   4   7   0   0]
- [ 25  27 116  52  30  19  36]
- [ 12   1   7 115   6   3  16]
- [  1   5   1   0  66   2   3]
- [  5   1   4   0   0  47   5]
- [ 14   0   7  12   6  15  84]]
-Node Classification on random seed  7957 -> 0.598
-Confusion Matrix:
- [[ 81   3   6   8   5   6   7]
- [  2 129  10   3   3   3  16]
- [ 25  19 116  22  34  31  38]
- [ 16   3  21  97   5   2  19]
- [  0   7   0   4  60   0   5]
- [  7   2   3   0   2  37   8]
- [ 10   4  11  10  14   8  78]]
-Node Classification on random seed  7958 -> 0.636
-Confusion Matrix:
- [[ 61   2   4   5   2  16  10]
- [  9 122   4   2  16   2   5]
- [ 21  18 179  27  19  20  36]
- [  8   1  18  91  12   7  11]
- [  4   5   8   0  59   0   4]
- [  2   0   2   1   5  54   5]
- [ 10   2  14   6   3  18  70]]
-Node Classification on random seed  7959 -> 0.617
-Confusion Matrix:
- [[ 65   1   1   9   5   7  10]
- [  3 136   5   1   5   1   4]
- [ 33  29 138  30  28  27  33]
- [  9   1  23  92   9   4  17]
- [  2   7   3   3  62   1   1]
- [  9   3   1   1   0  38   5]
- [ 23   2   8   6   3  10  86]]
-Node Classification on random seed  7960 -> 0.645
-Confusion Matrix:
- [[ 66   3   1   4   2  22  14]
- [  5 132   7   4   4   2   1]
- [ 13  17 186  34  17  25  31]
- [  7   3  17  89  15  10   3]
- [  3  12   3   1  58   1   0]
- [  3   1   2   3   0  42   6]
- [ 10   3  19   7   4  16  72]]
-Node Classification on random seed  7961 -> 0.565
-Confusion Matrix:
- [[ 71   1   4   7   1  17   6]
- [  5 113   9   3   5   6   7]
- [ 29  27 127  37  34  31  45]
- [ 19   9  18  74   5   5  19]
- [  2   5   2   1  69   2   3]
- [  6   2   0   4   2  35   5]
- [ 10   7   9   5  11  10  76]]
-Node Classification on random seed  7962 -> 0.584
-Confusion Matrix:
- [[ 75   1   2   4   5  10  14]
- [ 13 109   4   4  20   5   2]
- [ 33  12 128  30  32  16  59]
- [ 32   5  11  93  16   9   7]
- [  2   7   1   0  62   2   1]
- [  4   2   1   2   0  46   7]
- [ 16   1   3   8   3  10  71]]
-Node Classification on random seed  7963 -> 0.609
-Confusion Matrix:
- [[ 81   2   2   5   5   6  10]
- [  2 125   3   6   5   6   6]
- [ 31  15 133  34  28  37  46]
- [  9   2  16  99   4   9  13]
- [  2   3   3   2  60   1   2]
- [  4   1   5   4   2  33   2]
- [ 15   1  17  11   9   5  78]]
-Node Classification on random seed  7964 -> 0.637
-Confusion Matrix:
- [[ 79   1   6   3   4  12  12]
- [  4 127   4   5   9   5   6]
- [ 25  26 148  37  26  22  34]
- [ 10   4  21  95   7   2  10]
- [  1   3   2   0  68   0   3]
- [  7   1   1   0   0  38   7]
- [ 18   3   4   6   5   7  82]]
-Node Classification on random seed  7965 -> 0.612
-Confusion Matrix:
- [[ 65   2   7   5   3  11  17]
- [  1 114   3   3  10   3   2]
- [ 21  36 132  28  13  30  44]
- [ 20   3   9 102   6   6  19]
- [  2   5   2   2  67   0   5]
- [  3   1   2   6   0  47   2]
- [ 13   4   6   9   5  19  85]]
-Node Classification on random seed  7966 -> 0.648
-Confusion Matrix:
- [[ 66   3   2   4   4   6  15]
- [  8 131   3   1   4   3  10]
- [ 30  18 165  31  14  27  33]
- [  6   4  20  98   3   3  12]
- [  1   7   3   0  55   2   6]
- [  2   4   1   2   0  39  12]
- [  4   1   8  13   9  13  94]]
-Node Classification on random seed  7967 -> 0.59
-Confusion Matrix:
- [[ 73   4   3   8   6   6  18]
- [  3 126   6   4   2   0   5]
- [ 14  18 131  42  19  38  46]
- [ 11   3  19 102   6   7  11]
- [  1   7   7   0  43   1   5]
- [  5   5   4   0   3  46   7]
- [ 10   4  12   8  14  18  69]]
-Node Classification on random seed  7968 -> 0.639
-Confusion Matrix:
- [[ 73   2   3  12   6  12   7]
- [  2 114   2   5   1   0   5]
- [ 15  20 134  38  19  30  41]
- [  7   9  20 109   5  10  10]
- [  0   4   2   0  66   2   0]
- [  6   1   3   0   2  62   6]
- [  7   6  13   6   5  17  81]]
-Node Classification on random seed  7969 -> 0.597
-Confusion Matrix:
- [[ 78   3   1   4   2   5   8]
- [  4 136   2   3   4   1   4]
- [ 26  26 110  67  17  22  41]
- [ 15   5   7 108   7   6   5]
- [  1  16   3   5  60   1   0]
- [  7   1   5   4   1  50   6]
- [ 11   7  13  11   8  18  55]]
-Node Classification on random seed  7970 -> 0.624
-Confusion Matrix:
- [[ 78   4  10   6   4  16   5]
- [  4 124   7   3   8   5   1]
- [ 34  28 151  30  23  17  33]
- [  9   6  23  85   7   9  16]
- [  2   2   1   3  73   1   7]
- [  1   0   1   1   4  46   6]
- [  3   3  16   3   0  14  67]]
-Node Classification on random seed  7971 -> 0.615
-Confusion Matrix:
- [[ 78   1   1   4   2  17   3]
- [  6 138   2   5  13   5   3]
- [ 31  26 144  40  30  27  16]
- [ 15   1  17  88   4   6  12]
- [  3   5   3   3  65   2   1]
- [  5   1   0   0   1  42   8]
- [ 18   5   7   7  16  13  60]]
-Node Classification on random seed  7972 -> 0.609
-Confusion Matrix:
- [[ 72   2   5   4   2  12  15]
- [ 10 120  12   0  11   2   2]
- [ 24  18 146  19  40  12  45]
- [ 23   5  22  84   6   6  11]
- [  0   5   4   2  66   0   3]
- [  4   1   2   1   0  46   7]
- [ 19   2  15   3   3  12  75]]
-Node Classification on random seed  7973 -> 0.621
-Confusion Matrix:
- [[ 71   3  13   8   4   6  11]
- [  8 130   0   6   7   3   1]
- [ 24  32 139  37  33  22  32]
- [ 12   4   9  98   7   1  13]
- [  1   5   1   2  67   0   4]
- [  6   4   3   1   0  47   4]
- [ 11   7   9   5   8  12  69]]
-Node Classification on random seed  7974 -> 0.631
-Confusion Matrix:
- [[ 56   3  12   7   9  13   7]
- [  4 135   3   2   7  10   6]
- [ 25  13 152  42  15  13  35]
- [ 12   7  13 104   3  10  10]
- [  0  10   5   0  58   1   4]
- [  1   0   6   1   0  52   1]
- [  8   5  16   8   6  16  74]]
-Node Classification on random seed  7975 -> 0.652
-Confusion Matrix:
- [[ 76   2   0   2   2   7  16]
- [  6 133   2   2  10   5   2]
- [ 15  36 153  21  31  20  28]
- [  9   4   9 112  12   6  14]
- [  0   6   2   5  64   1   3]
- [  5   3   3   0   1  44  12]
- [  2   3   7  11  10  13  70]]
-Node Classification on random seed  7976 -> 0.615
-Confusion Matrix:
- [[ 66   2   8   9   6  15  10]
- [  2 128  11   1  14   2   4]
- [ 20  28 131  19  30  17  47]
- [  6   1  20  99   4   4  13]
- [  1   9   1   3  69   2   0]
- [  8   1   2   2   0  50   3]
- [ 20   8   5   2  14  11  72]]
-Node Classification on random seed  7977 -> 0.667
-Confusion Matrix:
- [[ 86   6   2   5   1   7   5]
- [  4 127   4   4   6   4   1]
- [ 30  12 149  32  22  16  36]
- [ 13   1  10 108   4   2  13]
- [  0  12   2   0  64   2   1]
- [ 10   1   2   1   1  47   4]
- [ 19   2   8   2   8  18  86]]
-Node Classification on random seed  7978 -> 0.607
-Confusion Matrix:
- [[ 72   6   5   4   2  14  19]
- [  2 123   3   5  11   3   4]
- [ 31  26 130  28  31  13  40]
- [  7   7  10 112   9   6  23]
- [  1  11   3   0  56   0   6]
- [  5   0   2   0   0  42   6]
- [ 12   3  10   6  11   8  72]]
-Node Classification on random seed  7979 -> 0.604
-Confusion Matrix:
- [[ 72   0   3   7   7   8   5]
- [  2 129   7   2  13   5   5]
- [ 33  34 125  34  25  33  34]
- [  3   2  18 110   8   5  10]
- [  0  10   3   0  57   0   2]
- [  3   1   0   4   1  37   1]
- [ 14   1  18  12   7  16  74]]
-Node Classification on random seed  7980 -> 0.601
-Confusion Matrix:
- [[ 76   3   2  14   4   2   5]
- [  8 138   7   4   4   1   2]
- [ 27  16 152  31  24  20  36]
- [ 28   6  15  88   7   9  11]
- [  2  10   3   4  52   0   4]
- [ 11   4   1   3   1  36   4]
- [ 14   3  11  21   3  14  59]]
-Node Classification on random seed  7981 -> 0.611
-Confusion Matrix:
- [[ 80   2   6  10   4  11   3]
- [  0 125   2   7   4   5   3]
- [ 24  16 150  41  22  19  42]
- [ 10  11  12  98   3   3   9]
- [  1   7   5   3  63   1   1]
- [  5   2   2   4   1  43   6]
- [ 14   3  14  16   6  29  52]]
-Node Classification on random seed  7982 -> 0.594
-Confusion Matrix:
- [[ 78   4   4   3   5  10   5]
- [  6 135   5   5   6   1   3]
- [ 21  31  93  43  46  25  43]
- [  7   6  12 102   3  13  18]
- [  1   8   0   0  73   1   7]
- [  7   1   0   1   0  48   1]
- [ 17   4   9   4   9  11  65]]
-Node Classification on random seed  7983 -> 0.635
-Confusion Matrix:
- [[ 76   1   6   6   3  14   3]
- [  6 130   6   1   6   5   0]
- [ 37  13 138  32  19  21  36]
- [ 15   5   9 103   7  11  21]
- [  1   7   3   1  66   1   1]
- [  2   1   0   3   3  48   2]
- [ 10   3   5  13   4  22  74]]
-Node Classification on random seed  7984 -> 0.608
-Confusion Matrix:
- [[ 70   5   9   9   1   6   8]
- [  4 119   6   5   9   4   1]
- [ 24  50 154  30  25  26  28]
- [  7   4  13  96  22   2  11]
- [  3   5   8   1  61   3   0]
- [  5   0   1   4   0  40   5]
- [  8   2   8   9  10  11  68]]
-Node Classification on random seed  7985 -> 0.565
-Confusion Matrix:
- [[ 58   3   3   5   5  24  14]
- [  3 125  13   1   6   3   4]
- [ 32  30 111  32  45  19  48]
- [ 12  12  19  78   5   6  14]
- [  4   4   1   0  62   0   2]
- [  2   2   0   2   2  52   2]
- [  4  11   5  11   5  20  79]]
-Node Classification on random seed  7986 -> 0.609
-Confusion Matrix:
- [[ 86   0   5   3   1   6   4]
- [  5 125   2   7   6   5   3]
- [ 30  32 141  40  30  20  41]
- [  8   3   9  94   6   3  21]
- [  2  10   6   0  60   2   1]
- [  2   2   1   5   3  35  10]
- [ 13   2  18  12   4   8  68]]
-Node Classification on random seed  7987 -> 0.66
-Confusion Matrix:
- [[ 71   2   2   9   2  14   9]
- [  3 130   4   3   8   6   0]
- [ 23  19 172  38  16  21  24]
- [  9   5  14 118   4   5  10]
- [  1   8   4   2  58   2   6]
- [  4   1   0   0   1  48   1]
- [  9   8  11   7   2  23  63]]
-Node Classification on random seed  7988 -> 0.569
-Confusion Matrix:
- [[ 67   5   8   8   1  14  10]
- [  7 108  10   3   4   0   5]
- [ 16  22 137  36  60  15  45]
- [  9   2  18  84  18  13  10]
- [  1  10   4   3  54   0   7]
- [  9   2   3   3   0  40   5]
- [ 10   3  10   8   3  11  79]]
-Node Classification on random seed  7989 -> 0.614
-Confusion Matrix:
- [[ 67   1   3   1   1  10  17]
- [  5 139   1   2   2   2  11]
- [ 26  15 133  43  23  27  48]
- [ 17   2  22  90   2   6  31]
- [  2   2   2   0  64   0   2]
- [  8   0   2   0   1  39   5]
- [  6   3  11   2   7  15  82]]
-Node Classification on random seed  7990 -> 0.622
-Confusion Matrix:
- [[ 68   1  13   8   2  13   9]
- [  5 126   4   5  12   1   9]
- [ 30  20 118  38  17  11  49]
- [ 11   2   7 112   8  10  10]
- [  0   8   6   2  66   0   3]
- [  2   3   2   1   1  49   5]
- [  8   5  16   4   7  10  83]]
-Node Classification on random seed  7991 -> 0.548
-Confusion Matrix:
- [[ 64   7  11   1   4   9  14]
- [  8 106   3   3  19   6   2]
- [ 26  24 112  63  37  18  44]
- [ 16   4  19  83   8   3  13]
- [  1   3   1   0  69   6   0]
- [ 10   8   2   1   1  44   3]
- [ 15   4  13   5   4  13  70]]
-Node Classification on random seed  7992 -> 0.615
-Confusion Matrix:
- [[ 66   4   8   5   7  17   4]
- [  7 137  10   3   1   2   2]
- [ 16  22 150  37  17  31  33]
- [ 11  10  14  97   2  10  12]
- [  1  10   5   3  54   1   3]
- [ 10   2   1   1   1  48   0]
- [ 14   6  14   4   7  17  63]]
-Node Classification on random seed  7993 -> 0.614
-Confusion Matrix:
- [[ 73   2   1   7   5   3  15]
- [  9 132   1   4   9   2   2]
- [ 32  29 129  33  18  23  49]
- [  7   5  17  97   5   6  22]
- [  0  10   4   1  58   0   1]
- [  6   1   3   3   0  39   5]
- [ 12   2  12   8   6   6  86]]
-Node Classification on random seed  7994 -> 0.629
-Confusion Matrix:
- [[ 84   6   4   2   9  13   7]
- [  2 117  15   0  11   2   1]
- [ 22  21 151  34  34  28  34]
- [  9   1  13 101   2   9  11]
- [  0   3   5   0  56   2   1]
- [  6   1   2   0   2  44   3]
- [ 11   3   8  11   8  15  76]]
-Node Classification on random seed  7995 -> 0.615
-Confusion Matrix:
- [[ 79   1   1   7   2   6  14]
- [  2 120  10   6   5   7   5]
- [ 34  26 144  39  29  20  30]
- [ 12   2  11 102   7   3  18]
- [  1   5   3   0  59   2   0]
- [  4   1   0   2   1  41  12]
- [ 12   5   8  11   6  15  70]]
-Node Classification on random seed  7996 -> 0.606
-Confusion Matrix:
- [[ 66   5   4   9   4  12   6]
- [  5 111   9   2  13   6   3]
- [ 24  16 139  37  39  24  37]
- [ 15   3   8 126   4   5   6]
- [  2   4   6   5  47   3   5]
- [  7   0   2   5   1  45   0]
- [ 10   4   8  12   6  18  72]]
-Node Classification on random seed  7997 -> 0.611
-Confusion Matrix:
- [[ 63   3   5   6   6   8  13]
- [  5 131  12   4   3   3   7]
- [ 28  18 155  35  21  17  38]
- [ 13   3  21  87   1   3  25]
- [  1   6   2   2  68   3   4]
- [  8   1   1   1   2  43   3]
- [  8   4  19   6   3  17  64]]
-Node Classification on random seed  7998 -> 0.614
-Confusion Matrix:
- [[ 75   2   4  11   6  15   3]
- [  2 126   7   5   6   0   1]
- [ 25  25 151  17  35  16  55]
- [ 16   2  15 106   4  10  10]
- [  2   7   6   1  66   2   1]
- [  6   1   3   4   1  32   3]
- [  9   3   5  11  10  19  58]]
-Node Classification on random seed  7999 -> 0.638
-Confusion Matrix:
- [[ 67   2   9  13   3   5  12]
- [  6 134   3   7   4   8   2]
- [ 30  21 149  39  27  21  29]
- [ 14   1   7 107   1   3  11]
- [  0  11   2   1  64   0   1]
- [  8   2   3   7   0  44   9]
- [  6   3   9   8   2  12  73]]
-Node Classification on random seed  8000 -> 0.604
-Confusion Matrix:
- [[ 63   3   6  12   4   8  11]
- [  6 135   7   1  11   0   4]
- [ 29  23 135  23  16  32  32]
- [ 17   1  31  85   2   8   6]
- [  1   7  10   2  67   0   2]
- [  3   0   4   5   2  40   5]
- [ 13   4   9   2   6  28  79]]
-Node Classification on random seed  8001 -> 0.615
-Confusion Matrix:
- [[ 79   0   0   8   3  16   8]
- [  7 124   3   2  20   4   2]
- [ 31  21 141  36  21  21  25]
- [ 16   2  13 102   3   5  10]
- [  2   6   2   0  61   3   0]
- [  3   6   7   7   1  40   5]
- [ 15   1  10  19   4  17  68]]
-Node Classification on random seed  8002 -> 0.626
-Confusion Matrix:
- [[ 76   2   0   8   8  12   3]
- [  4 135  12   2   9   1   1]
- [ 16  20 118  32  34  12  58]
- [  6   4  21 112   2  17  13]
- [  1  10   2   4  69   2   1]
- [  6   1   1   0   0  46   7]
- [ 12   2   4  12   5   7  70]]
-Node Classification on random seed  8003 -> 0.615
-Confusion Matrix:
- [[ 58   4   2   7   4  11   1]
- [  1 115  10   1  23   0   3]
- [ 19  20 152  27  41  20  55]
- [ 14   5   8 104   5   5  14]
- [  1   6   1   1  61   2   0]
- [  4   5   3   1   0  44  10]
- [ 11   6   7   9   7  11  81]]
-Node Classification on random seed  8004 -> 0.628
-Confusion Matrix:
- [[ 72   1   8   3   2   6  16]
- [  3 118   2   3   4   2   3]
- [ 22  22 155  34  42  25  36]
- [  8   1  20 106   5   2  22]
- [  6   5   2   5  57   0   1]
- [  4   1   1   4   1  43   7]
- [ 11   0  17   3   4   8  77]]
-Node Classification on random seed  8005 -> 0.652
-Confusion Matrix:
- [[ 79   0   3   4   4  16   5]
- [  3 137   7   1   3   4   4]
- [ 14   7 148  39  23  40  26]
- [  7   6  21 112   8   8  13]
- [  0  10   1   1  67   3   2]
- [  1   1   0   2   3  44   7]
- [  9   2  10   7   1  22  65]]
-Node Classification on random seed  8006 -> 0.627
-Confusion Matrix:
- [[ 71   1   3   5   0   9   6]
- [  6 124   8   1   8   0   5]
- [ 19  16 141  45  42  22  32]
- [ 10   0   7 106   8  16  13]
- [  2   7   5   2  50   2   2]
- [  7   2   2   0   1  48   5]
- [ 20   3   4   7   4  16  87]]
-Node Classification on random seed  8007 -> 0.59
-Confusion Matrix:
- [[ 73   2   3   2   2  19  13]
- [  7 124   8   5  10   5   5]
- [ 26  26 116  49  31  20  26]
- [ 12   4  10 106   3  10  14]
- [  1   9   3   1  64   0   2]
- [  6   2   2   5   2  50   4]
- [ 14   2  17  12   2  14  57]]
-Node Classification on random seed  8008 -> 0.613
-Confusion Matrix:
- [[ 66   4   5   2   6   9   6]
- [  5 129   2   3  14   4   3]
- [ 14  10 155  50  29  35  25]
- [ 24   2  12  85   9   7  21]
- [  1   4   5   2  66   3   6]
- [  8   3   1   1   1  36   5]
- [ 10   4   2  12   2  16  76]]
-Node Classification on random seed  8009 -> 0.615
-Confusion Matrix:
- [[ 42   2  17  13   3   8  10]
- [ 10 126   3   2  12   2   5]
- [ 17  15 151  53  12  24  41]
- [ 10   2   7 109   2   7  21]
- [  0   6   4   1  56   2   0]
- [  7   2   3   3   1  54   7]
- [  8   6  11   9   8   9  77]]
-Node Classification on random seed  8010 -> 0.61
-Confusion Matrix:
- [[ 71   3   2   8   1   6   7]
- [  2 124   3   4   5   3   2]
- [ 34  37 142  40  20  10  53]
- [ 15   7  16  82   4   2  29]
- [  1   3   6   1  65   0   2]
- [  6   1   1   2   0  41   8]
- [ 13   6   4   8   8   7  85]]
-Node Classification on random seed  8011 -> 0.624
-Confusion Matrix:
- [[ 60   2   9   0   4  15  11]
- [  2 128  15   3   2   2   8]
- [ 14  14 142  24  39  24  47]
- [  7   2  20  98  12   3  14]
- [  0   8   7   0  63   0   7]
- [  2   1   2   1   0  46   9]
- [  7   5  12   3   5  14  87]]
-Node Classification on random seed  8012 -> 0.643
-Confusion Matrix:
- [[ 60   2   3   9   2  11  16]
- [  8 128   8   1   4   5   1]
- [ 17  18 155  35  18  16  41]
- [  7   3  22 103   7  11   4]
- [  1   6   3   0  67   3   2]
- [  5   3   0   4   1  48   5]
- [  8   5   7  18   2  15  82]]
-Node Classification on random seed  8013 -> 0.637
-Confusion Matrix:
- [[ 67   1   3   4   4  18   6]
- [  9 135   3   4   3   2   3]
- [ 21  20 141  26  17  18  41]
- [ 12   7  16 115   3   7  16]
- [  3   7   3   3  64   1   7]
- [ 14   7   0   2   2  40   2]
- [ 10   6   6   1   6  19  75]]
-Node Classification on random seed  8014 -> 0.616
-Confusion Matrix:
- [[ 72   2  11   0   4  12   8]
- [  6 139   5   2   7   8   2]
- [ 31  21 128  41  25  27  43]
- [  5   6  11 105   8   4  10]
- [  1   8   3   1  59   3   5]
- [  9   1   0   0   0  39   7]
- [ 16   3   5   3   6  14  74]]
-Node Classification on random seed  8015 -> 0.595
-Confusion Matrix:
- [[ 76   3   4   9   2   9   6]
- [  4 123   7   2   4   3   0]
- [ 28  17 114  65  17  23  46]
- [ 14   2  25 101  11  10  15]
- [  0   6   3   2  56   1   1]
- [  7   2   3   3   0  44   2]
- [ 17   1   5   4   8  14  81]]
-Node Classification on random seed  8016 -> 0.612
-Confusion Matrix:
- [[ 63   5   2   5   8  12  23]
- [  4 127   4   6   7   0   4]
- [ 18  20 140  33  33  32  34]
- [ 13   5   9 102   3   9  19]
- [  0   7   3   0  67   0   0]
- [  7   2   2   2   0  51   4]
- [ 13   5   9   8   7  11  62]]
-Node Classification on random seed  8017 -> 0.636
-Confusion Matrix:
- [[ 76   1   1   6   1  19  16]
- [  2 127  12   4   3   1   3]
- [ 13  11 154  29  50  24  48]
- [  9   7   9  93   4   5  10]
- [  2   2  12   0  69   1   0]
- [  3   3   0   0   0  48   7]
- [  9   4   9   5   9  10  69]]
-Node Classification on random seed  8018 -> 0.621
-Confusion Matrix:
- [[ 64  11   5   3   2   6   8]
- [  7 109   4   5  13   6   6]
- [ 29  16 144  21  31  24  37]
- [ 25   5  17  96   3   0  10]
- [  4   3   8   4  61   0   5]
- [ 10   0   1   0   0  51   2]
- [ 14   7   0   9   7  11  96]]
-Node Classification on random seed  8019 -> 0.617
-Confusion Matrix:
- [[ 61   4  25   6   3  16   6]
- [  2 123   9   2   8   5   6]
- [ 15  11 143  33  23  12  69]
- [  7   5   8 120   1   8  13]
- [  2   2   2   1  66   1   3]
- [  5   1   4   0   6  41   4]
- [  5   1   6  13   0  30  63]]
-Node Classification on random seed  8020 -> 0.6
-Confusion Matrix:
- [[ 69   4   8   4   3   6   2]
- [  9 138   5   2   6   1   3]
- [ 28  48 115  38  25   9  52]
- [ 11   2  24  98   5   8   8]
- [  1  14   0   3  58   1   4]
- [  3   1   6   0   4  43   2]
- [ 12   2  11   2   6  17  79]]
-Node Classification on random seed  8021 -> 0.573
-Confusion Matrix:
- [[ 48   6   5   2   3   2  27]
- [  6 112  10   3   6   5   5]
- [ 37  28 143  27  25  22  47]
- [ 10   5  20  88  12   5  13]
- [  0   8   6   6  69   1   1]
- [  9   1   2   3   1  35   4]
- [  7   3  19   9   4  12  78]]
-Node Classification on random seed  8022 -> 0.665
-Confusion Matrix:
- [[ 71   3   2   6   4   2  16]
- [  2 135   7   3   2   0   9]
- [ 12  13 153  31  25  15  49]
- [  3   7  15 109   5   3  18]
- [  0   5   6   0  52   0   2]
- [ 11   2   2   2   1  50   9]
- [  5   2  10  17   7   2  95]]
-Node Classification on random seed  8023 -> 0.624
-Confusion Matrix:
- [[ 73   1   1   6   3  11   4]
- [  9 125   2   2  18   2   7]
- [ 20  17 142  39  30  31  30]
- [ 12   1   8 105   5  18  16]
- [  2   4   3   1  54   1   5]
- [  4   0   3   3   4  41   5]
- [ 19   4   4   9   3   9  84]]
-Node Classification on random seed  8024 -> 0.619
-Confusion Matrix:
- [[ 60   5   2   4   0  10  23]
- [  3 141   8   2  10   0   2]
- [ 17  27 137  38  23  26  46]
- [  9   2  12  87   4   4  11]
- [  0   8   2   1  62   0   4]
- [  1   0   7   5   7  41   7]
- [  5   2   9   5   7  23  91]]
-Node Classification on random seed  8025 -> 0.616
-Confusion Matrix:
- [[ 59   1  13   7   3   4   7]
- [  3 121   4  11   6  10   5]
- [ 14  10 152  43  46  28  31]
- [  5   2  14 109   4  11   3]
- [  0   4   4   2  51   1   2]
- [  4   3   4   0   1  56   6]
- [ 11   6  13  12   4  22  68]]
-Node Classification on random seed  8026 -> 0.625
-Confusion Matrix:
- [[ 60   3   3   2   7  13  10]
- [  1 119   6   1   7   1   5]
- [ 21  14 149  36  30  15  39]
- [ 24   4  11  98   5   8  23]
- [  1   5   3   3  71   1   1]
- [  4   1   5   0   0  53   4]
- [  8   6  14   1   5  24  75]]
-Node Classification on random seed  8027 -> 0.642
-Confusion Matrix:
- [[ 84   1   2   5   6  10   4]
- [  5 124   3   1  10   3   4]
- [ 23  36 148  29  21  23  44]
- [  7   2  15 110   7   4   8]
- [  1   1   7   2  49   0   4]
- [  8   1   4   1   0  50   3]
- [ 15   6   4  10   5  13  77]]
-Node Classification on random seed  8028 -> 0.651
-Confusion Matrix:
- [[ 89   3   3   4   3   6   8]
- [  4 134   8   2   7   2   4]
- [ 22  22 145  33  11  21  38]
- [ 19   4  18  91   4   7  12]
- [  0   8   5   5  67   3   4]
- [ 11   1   3   0   1  46   1]
- [ 15   2   9   4   2  10  79]]
-Node Classification on random seed  8029 -> 0.61
-Confusion Matrix:
- [[ 60   6   3   5   1  12  18]
- [  6 126   6   1   5   1   5]
- [ 13  26 144  52  21  18  30]
- [ 15   3  25 100   5   4  11]
- [  1  15   2   0  53   0   2]
- [  2   5   5   1   1  45  10]
- [ 11  10  10   5   6  12  82]]
-Node Classification on random seed  8030 -> 0.635
-Confusion Matrix:
- [[ 66   7   6   7   2   5  10]
- [  4 136   1   3   6   2   3]
- [ 31  20 139  27  25  35  21]
- [ 16   7   8 113   5   8  10]
- [  3   7   9   1  50   0   1]
- [  4   2   0   4   0  49   8]
- [  7   3   8   9   6  24  82]]
-Node Classification on random seed  8031 -> 0.635
-Confusion Matrix:
- [[ 73   6  10   4   3  10   7]
- [  4 125   4   1   4   2   1]
- [ 22  17 135  34  19  14  54]
- [  7   3  12 104   6   4  24]
- [  0   9   2   1  58   0   5]
- [  8   0   4   6   1  50   6]
- [ 14   7  10   8   2  10  90]]
-Node Classification on random seed  8032 -> 0.624
-Confusion Matrix:
- [[ 63   3   1  10   2  10   8]
- [  8 118   5   3  13   0   8]
- [ 23  14 161  25  13  31  26]
- [ 15   6  24  93   4  10  23]
- [  1   9   2   1  59   2   1]
- [ 12   1   1   3   0  48   3]
- [ 21   5   7   9   2  11  82]]
-Node Classification on random seed  8033 -> 0.611
-Confusion Matrix:
- [[ 65   0   3   6   2   8  13]
- [  0 142   7   2   6   3   2]
- [ 37  23 131  29  19  37  31]
- [ 24   3  21  84   3   6   9]
- [  3   5   5   1  60   2   3]
- [ 13   0   3   0   0  36  12]
- [  7   1  13   8   4  15  93]]
-Node Classification on random seed  8034 -> 0.66
-Confusion Matrix:
- [[ 83   6   1   4   2  11   7]
- [  2 130   1   0   2   1   3]
- [ 16  44 163  34  21  14  22]
- [ 10   9  17 104   4  10   8]
- [  2   7   3   3  62   0   5]
- [  5   0   6   1   2  42   4]
- [ 14   4  12   3   6  14  76]]
-Node Classification on random seed  8035 -> 0.599
-Confusion Matrix:
- [[ 57   0   7   5   4   8  19]
- [  6 131   4   2   4   5   4]
- [ 21  36 122  45  48  19  28]
- [ 15   9  14  92   1   8  12]
- [  2   5   3   0  71   0   3]
- [  5   0   2   6   0  42   7]
- [ 12   2   5   6   8  11  84]]
-Node Classification on random seed  8036 -> 0.562
-Confusion Matrix:
- [[ 58   4   6   3   4  18   7]
- [  5 119   8   3  14   8   9]
- [ 22  23 114  26  56  28  42]
- [ 11   7  10 110   8  15  19]
- [  1   4   5   3  56   0   1]
- [  6   2   2   0   4  33   3]
- [ 11   2   4   1   9  24  72]]
-Node Classification on random seed  8037 -> 0.602
-Confusion Matrix:
- [[ 57   3   8   1   0  15   7]
- [  4 126   9   5   2   1   3]
- [ 21  20 122  37  34  21  44]
- [ 17   5  13 110   1   7  29]
- [  4   7  11   3  63   0   5]
- [  3   0   2   5   0  45   8]
- [ 10   4   5   3   8  13  79]]
-Node Classification on random seed  8038 -> 0.614
-Confusion Matrix:
- [[ 65   4   6  13   5   4  11]
- [  3 133   7   6  10   1  11]
- [ 18  32 125  38  11  40  39]
- [ 11   1   6 109   8  17  11]
- [  2   2   6   3  54   1   1]
- [  3   0   0   0   2  55   4]
- [ 10   4   6   5   7  17  73]]
-Node Classification on random seed  8039 -> 0.58
-Confusion Matrix:
- [[ 74   1   1   0   4   9  10]
- [  5 121  13   0   6   5   5]
- [ 26  18 109  50  45  24  50]
- [ 11   4  16 104   7  13   5]
- [  1   8   2   2  62   1   2]
- [  5   1   0   1   7  40   6]
- [  9   4   8  12   4  19  70]]
-Node Classification on random seed  8040 -> 0.649
-Confusion Matrix:
- [[ 78   1   6   2   6  14   0]
- [  7 139   5   0   4   3   3]
- [ 21  30 135  28  43  24  22]
- [  4   4  19 109   4   8  10]
- [  0   9   4   1  60   0   2]
- [  4   0   3   1   2  51   2]
- [ 10   4  10   7  10  14  77]]
-Node Classification on random seed  8041 -> 0.601
-Confusion Matrix:
- [[ 53   3   1   8  10  11   5]
- [  7 121   1   0   5   3  10]
- [ 30  25 143  35  33  14  45]
- [ 13  10   7 115   6   4  14]
- [  2   4   7   1  61   2   3]
- [  6   2   1   5   2  39   7]
- [ 12   1   7   7  11  19  69]]
-Node Classification on random seed  8042 -> 0.645
-Confusion Matrix:
- [[ 58   1   7   5   9   8  14]
- [  5 157   2   3  12   2   3]
- [ 23  24 160  29  15  12  26]
- [ 10   7  15 111   4   3  17]
- [  1  10   4   2  53   2   3]
- [  8   2   2   0   0  48   8]
- [  7   1   9  11  10  19  58]]
-Node Classification on random seed  8043 -> 0.602
-Confusion Matrix:
- [[ 71   1   2   5   4  16  13]
- [  3 130   4   3   2   2   3]
- [ 31  22 139  52  24  27  45]
- [ 12   3  15  91   8   4  15]
- [  1   6   4   0  57   1   2]
- [  8   3   1   0   0  42  10]
- [  3   4  15   6   3  15  72]]
-Node Classification on random seed  8044 -> 0.645
-Confusion Matrix:
- [[ 77   2   4   1   4   9  17]
- [  4 133   5   4   6   8   4]
- [ 22  19 163  20  19  24  33]
- [ 17   1  17  99   6   2  11]
- [  0   7   3   1  53   2   1]
- [  7   0   3   1   1  35  16]
- [  7   5  11   9   3  19  85]]
-Node Classification on random seed  8045 -> 0.621
-Confusion Matrix:
- [[ 67   4   1   8   2   8  11]
- [  4 118  12   1   9   4   6]
- [ 15  21 160  26  43  13  47]
- [  8   2  14  98   1   8  16]
- [  4   6   3   2  47   1   3]
- [  9   0   5   2   0  43   4]
- [ 18   2   8   9   7  12  88]]
-Node Classification on random seed  8046 -> 0.606
-Confusion Matrix:
- [[ 67   2   4  14   7   6  11]
- [  4 113  12   1  17   1   2]
- [ 17  26 131  40  28  24  33]
- [ 11   0  13 107  10   6  12]
- [  2   6   1   0  63   3   4]
- [  7   3   1   1   0  48   6]
- [ 12   0   5  17  10  15  77]]
-Node Classification on random seed  8047 -> 0.622
-Confusion Matrix:
- [[ 73   8   0   3   2   7   7]
- [  1 152   6   5   3   5   1]
- [ 35  14 121  32  29  20  39]
- [ 20   6   8 106   6   4  11]
- [  4   4   2   4  62   1   1]
- [  5   1   2   0   1  47   4]
- [ 23   6  11   6   6  25  61]]
-Node Classification on random seed  8048 -> 0.587
-Confusion Matrix:
- [[ 84   7   2   4   4  16   3]
- [  5 116  11   4   7  10   1]
- [ 19  13 125  56  12  29  36]
- [ 10   1  11 109   4  16  17]
- [  1   8   1   4  58   0   1]
- [  3   5   2   3   1  46   5]
- [ 12   6  20  19   8  16  49]]
-Node Classification on random seed  8049 -> 0.625
-Confusion Matrix:
- [[ 80   1   5   4   8   7  12]
- [  3 132   2   5   5   0   3]
- [ 41  30 158  29  25  16  37]
- [  5   6  13  85   8   4  19]
- [  0   4   5   0  52   1   4]
- [  7   3   3   1   0  43   6]
- [ 10   2  11   8   5  17  75]]
-Node Classification on random seed  8050 -> 0.626
-Confusion Matrix:
- [[ 62   0   2   5   7  14  10]
- [  2 124   6   8   2   0   3]
- [ 11  18 151  38  27  24  49]
- [  9   2   7 108   9   8  18]
- [  0  14   4   4  62   1   1]
- [  4   5   1   4   2  41   6]
- [  9   5   3  14   4  14  78]]
-Node Classification on random seed  8051 -> 0.576
-Confusion Matrix:
- [[ 71   2   5   2   6  13   7]
- [  2 114  13   4   8   2   5]
- [ 18  25 138  33  42  19  51]
- [ 13   4  27  91   4   8  13]
- [  0   6   4   1  54   0   6]
- [  1   5   3   2   0  51   4]
- [ 11   3   9  21   4  18  57]]
-Node Classification on random seed  8052 -> 0.587
-Confusion Matrix:
- [[ 70   4   3   4   2  15   8]
- [  0 124   4   3   6   8   7]
- [ 19  36 137  24  33  37  46]
- [  8   2  26 100   8  11   9]
- [  0   6   6   1  55   0   2]
- [  0   0   4   4   0  38   3]
- [  7   1  11   7   8  30  63]]
-Node Classification on random seed  8053 -> 0.64
-Confusion Matrix:
- [[ 77   2   8   3   2  17   5]
- [  3 137   5   1   5   1   1]
- [ 29  22 157  27  32   9  29]
- [ 17   7  11  94   6   5  15]
- [  1  10   2   3  61   0   2]
- [  6   0   2   2   0  48   5]
- [ 12   6  17  10   3  17  66]]
-Node Classification on random seed  8054 -> 0.617
-Confusion Matrix:
- [[ 59   5   5   6   3  15  12]
- [  7 146   6   2   6   1   2]
- [ 30  16 129  32  32  23  32]
- [ 12   2  29  88   9   4  13]
- [  0   4   2   0  75   1   3]
- [  4   0   2   0   0  47   4]
- [ 13   4  11   7   7  17  73]]
-Node Classification on random seed  8055 -> 0.638
-Confusion Matrix:
- [[ 66   4   8   4   6   8  13]
- [  8 118  11   4   5   5   1]
- [ 19  24 161  18  17  26  40]
- [ 13   8  10  99   1  16  12]
- [  1   3   3   1  79   0   2]
- [  5   0   2   1   0  38   7]
- [ 13   7  12   7   6  11  77]]
-Node Classification on random seed  8056 -> 0.616
-Confusion Matrix:
- [[ 69   1   1   3  11   8   8]
- [  1 120   5   2  11   4   3]
- [ 10  47 135  30  36  13  46]
- [ 15   6  18 109   2   4  17]
- [  0   5   3   1  61   0   0]
- [  0   3   2   1   1  44   5]
- [ 13   3   3  12   5  25  78]]
-Node Classification on random seed  8057 -> 0.587
-Confusion Matrix:
- [[ 74   1  13   3   0  17   9]
- [  3 124   1   7  11   3   4]
- [ 20  21 126  33  43  18  40]
- [  7   1  19  97  23   2  18]
- [  2   5   6   3  57   0   6]
- [  1   4   6   0   1  43   8]
- [ 10   3  15   3   7  16  66]]
-Node Classification on random seed  8058 -> 0.62
-Confusion Matrix:
- [[ 57   4   6   3   5   5  22]
- [  2 115   5   1  10   3   4]
- [ 24  35 133  24  28  28  49]
- [  8   3  15 113   2   3  21]
- [  2   7   2   1  85   1   0]
- [  6   4   0   0   2  41   4]
- [  9   5   6   1  10  10  76]]
-Node Classification on random seed  8059 -> 0.639
-Confusion Matrix:
- [[ 70   9   9   6   2   4   9]
- [  3 126   7   2  11   5   6]
- [ 22   6 173  26  16  20  34]
- [ 11   4  19 110   6   7   9]
- [  3   2   1   2  57   1   4]
- [  5   0   6   3   1  34   6]
- [ 22   9  14   4  12  13  69]]
-Node Classification on random seed  8060 -> 0.588
-Confusion Matrix:
- [[ 50  10  11   7   5   9  14]
- [  0 114   7   4  18   9   5]
- [ 21  21 136  36  33  17  50]
- [ 16   5  13 108   3   6  10]
- [  1   6   4   2  73   1   1]
- [  5   1   3   4   0  40   9]
- [ 12   3   7   7   6  10  67]]
-Node Classification on random seed  8061 -> 0.628
-Confusion Matrix:
- [[ 73   2   2   3   1  17   7]
- [  3 135   4   7   9   1   2]
- [ 31  20 141  31  32  27  36]
- [ 15   2  21  96   3   6  20]
- [  1  10   1   2  65   0   1]
- [  9   2   1   1   0  44   1]
- [ 19   1   6   2   2  11  74]]
-Node Classification on random seed  8062 -> 0.629
-Confusion Matrix:
- [[ 82   2   4   6   3   9   4]
- [ 12 135   8   3   5   0   3]
- [ 21  21 147  36   9  14  50]
- [ 16   2  25 106   2   1  15]
- [  2   9   9   2  48   0   3]
- [ 14   2   0   2   3  37   6]
- [ 15   5   9   4   5  10  74]]
-Node Classification on random seed  8063 -> 0.613
-Confusion Matrix:
- [[ 80   0   2   3   3   4  12]
- [  3 128  13   6  11   3   7]
- [ 25  18 129  52  36  21  50]
- [ 13   2  10 104  12   1   7]
- [  3   2   4   1  59   0   5]
- [  1   3   1   0   1  42   9]
- [ 10   3   7   5   9   9  71]]
-Node Classification on random seed  8064 -> 0.614
-Confusion Matrix:
- [[ 73   2   2   5   2  12   6]
- [  0 124   5   2  14   2   4]
- [ 17  17 146  36  56  14  33]
- [  7   1  33  85   8   2  11]
- [  0   8   2   3  66   3   4]
- [  2   3   4   4   1  37   2]
- [  8   1   9   8   6  27  83]]
-Node Classification on random seed  8065 -> 0.609
-Confusion Matrix:
- [[ 39   7   7  11   3  12  20]
- [  6 139   9   4   1   0   6]
- [ 34  25 146  24  20  24  35]
- [  7   3  12 107   6   4  10]
- [  2   3   5   4  64   0   1]
- [  3   0   1   7   0  46   7]
- [ 14   6  11  15   8  14  68]]
-Node Classification on random seed  8066 -> 0.586
-Confusion Matrix:
- [[ 55   3   5   2   0  17  24]
- [ 11 100   6   2  23   5   2]
- [ 19  32 152  39  18  33  24]
- [ 11   4  13 115   6  11   8]
- [  5   5   6   2  58   1   2]
- [  7   2   5   1   1  36   0]
- [  9   8  10   5  11  16  70]]
-Node Classification on random seed  8067 -> 0.634
-Confusion Matrix:
- [[ 76   4   2   4   1  19   6]
- [  4 133   6   1   8   6   4]
- [ 17  29 141  38  13  17  47]
- [ 13   4  15 110   5   9   5]
- [  0   6   7   3  63   1   5]
- [  4   1   1   2   0  47   5]
- [ 18   4  10   5   2  15  64]]
-Node Classification on random seed  8068 -> 0.641
-Confusion Matrix:
- [[ 73   1   7   3   4  14  16]
- [  4 132   8   6  10   2   2]
- [ 20  17 155  37  27  16  32]
- [  7   5  17  94   2   3  17]
- [  1   7   3   1  57   3   1]
- [  5   1   4   0   1  54   5]
- [  6   4  15   7   5  13  76]]
-Node Classification on random seed  8069 -> 0.633
-Confusion Matrix:
- [[ 76   4   1  11   4  12  13]
- [  4 133   5   4   3   0   1]
- [ 27  19 140  28  23  18  46]
- [ 10   1   9  92   6  10  21]
- [  1   7   4   1  59   4   0]
- [  3   0   0   3   1  53   7]
- [ 16   5  17   2   7   9  80]]
-Node Classification on random seed  8070 -> 0.571
-Confusion Matrix:
- [[ 53   3   1   9   2   8  20]
- [  9 139   2   3   6   5   1]
- [ 28  25 135  33  22   9  62]
- [ 22   4  18  82  17   2  14]
- [  3   3   5   0  56   0   4]
- [  6   4   1   2   1  34   9]
- [ 11   3  10  15  16  11  72]]
-Node Classification on random seed  8071 -> 0.606
-Confusion Matrix:
- [[ 68   2   5   6   5  16   2]
- [  4 135   2   2  10   6  10]
- [ 26  21 132  40  37  31  28]
- [ 17   6  13  95   3   6  12]
- [  1   7   1   4  57   3   1]
- [  8   3   1   2   0  49   1]
- [ 15   1   5  13   5  13  70]]
-Node Classification on random seed  8072 -> 0.579
-Confusion Matrix:
- [[ 64   8   3  10   3   5  13]
- [  7 123   4   0   9   3   7]
- [ 38  25 108  60  38  19  33]
- [  1   3  19 106   3   6  10]
- [  3   7   1   0  65   2   4]
- [  5   0   8   3   2  36   5]
- [ 18   3   6   9  13   5  77]]
-Node Classification on random seed  8073 -> 0.618
-Confusion Matrix:
- [[ 57   5   6   6   7  12  14]
- [  3 107  15   1   6   5   4]
- [ 21   7 144  48  15  49  30]
- [ 14   2  11 123   2   3  10]
- [  1  11   6   1  57   0   3]
- [  8   1   1   2   0  51   5]
- [ 18   3  13   3   4   6  79]]
-Node Classification on random seed  8074 -> 0.634
-Confusion Matrix:
- [[ 70   6   3   3   0  16   3]
- [  5 118   7   2   9   2   3]
- [ 35  22 147  28  18  30  34]
- [ 16   1  13 111   8   0  14]
- [  4   1   3   2  66   1   4]
- [  7   2   3   0   2  55   3]
- [ 16   5   6   3   8  18  67]]
-Node Classification on random seed  8075 -> 0.617
-Confusion Matrix:
- [[ 72   1   6   4   2  12   1]
- [  9 123   2   3  10   1   1]
- [ 27  30 146  31  24  13  41]
- [ 16   5   9  95  12   7  17]
- [  2   9   1   1  74   0   6]
- [  7   1   4   3   1  37   2]
- [ 11   7  21   4   7  12  70]]
-Node Classification on random seed  8076 -> 0.62
-Confusion Matrix:
- [[ 68   6   2   9   6  13   9]
- [  7 135   5   6   4   1   6]
- [ 22  19 130  34  34  15  44]
- [ 18   1  15  95   5   4  14]
- [  2   5   3   1  61   2   4]
- [  2   0   0   7   1  42  11]
- [ 18   3   6   7   4   5  89]]
-Node Classification on random seed  8077 -> 0.583
-Confusion Matrix:
- [[ 63   6   4   6   5  15   3]
- [  2 129   7   1  10   8   4]
- [ 25  37 138  39  31  14  42]
- [ 15  14   9 100   2   4  14]
- [  1   6   6   1  48   0   2]
- [  4   2   5   0   6  44   6]
- [ 15   7   5  12  13   9  61]]
-Node Classification on random seed  8078 -> 0.665
-Confusion Matrix:
- [[ 73   2   3   2   4   9  26]
- [ 11 136   2   5   5   2   3]
- [ 24  15 150  40  20  10  43]
- [  5   2  13 108   2   6  12]
- [  4   3   4   0  57   0   2]
- [  4   0   4   2   0  40   8]
- [  8   5   8   2   5  10 101]]
-Node Classification on random seed  8079 -> 0.616
-Confusion Matrix:
- [[ 70   2   1  10   2   8   4]
- [  8 134   3   1  14   3   1]
- [ 21  22 141  49  25  24  26]
- [ 24   5  20  93   5   5  13]
- [  0   7   8   0  60   1   2]
- [  6   4   1   2   1  40   3]
- [ 12   1   8   2   6  24  78]]
-Node Classification on random seed  8080 -> 0.581
-Confusion Matrix:
- [[ 59   6   3   4   2  14  13]
- [  5 114  15   2   3   4   6]
- [ 32  15 124  52  23  30  39]
- [ 16   6  16 104   3   9  18]
- [  1   3   4   2  53   0   1]
- [  5   3   2   1   0  41  15]
- [ 16   4   6   2   5  13  86]]
-Node Classification on random seed  8081 -> 0.607
-Confusion Matrix:
- [[ 71   3   1  11   6   8  16]
- [  5 129   8   3  11   2   2]
- [ 35  31 149  27  19  16  41]
- [ 15   3   7  90   6   6  13]
- [  2   9   5   0  65   0   3]
- [  4   4   0   5   0  34   8]
- [ 16   4   7   9   8  14  69]]
-Node Classification on random seed  8082 -> 0.634
-Confusion Matrix:
- [[ 71   3   5  12   6  10   8]
- [  2 143   3   2   4   0   0]
- [ 29  31 159  19  29  19  32]
- [ 10   1  23  89   5   9  21]
- [  0   7   5   1  61   2   3]
- [ 14   1   1   3   1  40   4]
- [ 12   5   7   6   7   4  71]]
-Node Classification on random seed  8083 -> 0.621
-Confusion Matrix:
- [[ 85   6   3   1   5   5   8]
- [  6 132   9   2   6   8   7]
- [ 38  22 128  38  16  14  46]
- [  7   3  17  89   2   8   6]
- [  1   2   7   7  67   0   3]
- [  6   2   5   1   0  47  11]
- [  9   4  10   6  10  12  73]]
-Node Classification on random seed  8084 -> 0.638
-Confusion Matrix:
- [[ 67   5  10   2   7   5   8]
- [  4 117   3   2  12   0   8]
- [ 26  20 163  36  22  18  27]
- [ 14   3  27 110   3   2   2]
- [  1   5   6   2  69   0   7]
- [  1   1   6   2   0  52   5]
- [ 17   3  20   2   4  14  60]]
-Node Classification on random seed  8085 -> 0.556
-Confusion Matrix:
- [[ 50   7   7   6   3  21  18]
- [  6 120   2   4  11   6   1]
- [ 33  24 110  49  24  12  63]
- [ 12   2   6 108   4   3  26]
- [  3   8   6   5  54   0   1]
- [  3   1   2   1   1  52   4]
- [ 10   4   8  14  10  13  62]]
-Node Classification on random seed  8086 -> 0.586
-Confusion Matrix:
- [[ 67   0  12   8   3   9  17]
- [  3 116   8   1  12   2   5]
- [ 25  17 118  35  39  35  43]
- [ 14   0  13 104   3   7  13]
- [  1   1   3   1  69   0   2]
- [  3   1   2  10   1  44   2]
- [  8   6  11  10   8  20  68]]
-Node Classification on random seed  8087 -> 0.577
-Confusion Matrix:
- [[ 58   4  10  12   5  12  12]
- [  3 103   7   4   3   7   4]
- [ 24  42 131  37  15  34  39]
- [ 10   6  28 102   3   2  13]
- [  0   9   9   1  52   0   3]
- [ 17   1   3   3   0  45   6]
- [  9   4   7   6   1   8  86]]
-Node Classification on random seed  8088 -> 0.594
-Confusion Matrix:
- [[ 61   2   5   3  10  14  11]
- [  2 124  10   1  15   5   3]
- [ 19  23 150  28  31  29  38]
- [ 16   5  12  89   6   9  19]
- [  1   4   3   1  59   4   1]
- [  8   4   1   2   0  44   7]
- [ 15   1   8   3  16  11  67]]
-Node Classification on random seed  8089 -> 0.57
-Confusion Matrix:
- [[ 62   9   3   6   6  16  11]
- [  6 120   2   2   6   5   2]
- [ 34  25 106  53  18  39  38]
- [ 14   3   6 120   2   3  11]
- [  0   8   6   3  53   2   0]
- [  6   2   2   6   1  32   7]
- [ 11  12  16   9   8  11  77]]
-Node Classification on random seed  8090 -> 0.631
-Confusion Matrix:
- [[ 66   2   2   9   1   4   8]
- [  7 132   3   6   9   2   4]
- [ 28  11 150  43  37  25  28]
- [ 12   1  11 109   6   6  12]
- [  1   5   1   1  64   1   3]
- [  3   2   1   8   1  41   2]
- [ 20   3   8   4   8  20  69]]
-Node Classification on random seed  8091 -> 0.624
-Confusion Matrix:
- [[ 69   4  12   3   3  10   6]
- [  6 139   5   2   5   2   7]
- [ 31  23 129  33  22  19  51]
- [ 17   6   8 124   2   3   7]
- [  2   7   5   0  47   2   7]
- [  4   2   6   0   2  41   5]
- [  5   3   5  10   7  17  75]]
-Node Classification on random seed  8092 -> 0.614
-Confusion Matrix:
- [[ 76   2   7   7   5  13   6]
- [  5 128   5   1   5   4   7]
- [ 22  23 148  33  10  28  50]
- [  6   5  18 101   5   4  15]
- [  2   7   7   1  56   1   1]
- [  5   2   7   2   2  42   5]
- [ 12   6   3   6  10  21  63]]
-Node Classification on random seed  8093 -> 0.617
-Confusion Matrix:
- [[ 72   4  15   2   5   6  11]
- [  5 117   5   6   8   2   9]
- [ 34  27 146  37  20  17  33]
- [ 14   1  17  97   7   6  12]
- [  0   9   9   3  62   0   0]
- [  6   0   4   0   0  52   6]
- [  4   2  20   5   3   9  71]]
-Node Classification on random seed  8094 -> 0.617
-Confusion Matrix:
- [[ 61   4   7   3   7  24  12]
- [  3 126   7   2  15   1   5]
- [ 22  10 135  21  53  18  49]
- [ 11   3  13 109   4   8   5]
- [  0   6   2   1  58   3   1]
- [  1   0   3   4   0  42   1]
- [ 12   4   3   7  11  17  86]]
-Node Classification on random seed  8095 -> 0.596
-Confusion Matrix:
- [[ 67   4   5   2   3  11  19]
- [  3 133   4   6   4   1   2]
- [ 22  41 135  31  35  23  28]
- [  6   1  22  94   2   4  24]
- [  4  12   2   0  52   1   1]
- [  2   3   6   1   3  45   6]
- [ 14   4  24   3   3  12  70]]
-Node Classification on random seed  8096 -> 0.631
-Confusion Matrix:
- [[ 57   1   9  10   4   6  10]
- [  1 138   5   3   4   3   3]
- [ 33  19 158  30  13  22  51]
- [ 12   4  14  91   8   4  10]
- [  0  11   6   3  54   0   1]
- [  2   0   1   0   0  49   6]
- [  8   4  14  14   6  14  84]]
-Node Classification on random seed  8097 -> 0.612
-Confusion Matrix:
- [[ 84   1   3   4   4   5  11]
- [  6 136   5   3   3   3   4]
- [ 14  30 125  24  50  16  44]
- [ 17   8  24  96   2   5   7]
- [  2   8   3   2  56   0   4]
- [ 10   2   2   0   0  43   7]
- [  9   2   7   7  20  10  72]]
-Node Classification on random seed  8098 -> 0.6
-Confusion Matrix:
- [[ 69   2   2   6   2  11   5]
- [  8 119   2   5   6   1   7]
- [ 30  22 122  63  32   9  34]
- [ 12   0   9  97   6  11  15]
- [  2   8   1   6  71   1   3]
- [  7   1   4   5   6  41   6]
- [ 17   5   8   4   2  14  81]]
-Node Classification on random seed  8099 -> 0.664
-Confusion Matrix:
- [[ 88   0   9   1   1  11   7]
- [  2 139   2   6   9   2   0]
- [ 20  22 160  13  46  18  23]
- [ 17   4  15  99   6   4  14]
- [  0   8   4   0  72   1   2]
- [  6   0   2   0   8  34   3]
- [ 15   3   5   5   4  18  72]]
-Node Classification on random seed  8100 -> 0.614
-Confusion Matrix:
- [[ 70   1   6   1   1  14   6]
- [  3 135   7   1   6   7   3]
- [ 36  28 152  14  26  37  18]
- [ 12   3  11 104   3   8  13]
- [  2  10   4   2  48   2   4]
- [  5   1   1   5   2  43   5]
- [ 17   2  13  10   8  28  62]]
-Node Classification on random seed  8101 -> 0.613
-Confusion Matrix:
- [[ 78   1   7   3   6  11   1]
- [  4 118   8   5   5   4   7]
- [ 25  18 130  64  35  21  23]
- [  6   2  14 116   5   6   7]
- [  2   6   2   3  64   1   0]
- [  9   1   3   2   0  42   3]
- [ 18   4  12   7   9  17  65]]
-Node Classification on random seed  8102 -> 0.607
-Confusion Matrix:
- [[ 71   1   8   2   6  10   6]
- [  3 123   4   5  16   1   4]
- [ 16  26 145  46  25  15  43]
- [ 16   6  11  88  10   4  18]
- [  1   7   4   0  59   1   4]
- [  7   2   5   1   2  39   7]
- [ 11   1  19   7   5   7  82]]
-Node Classification on random seed  8103 -> 0.625
-Confusion Matrix:
- [[ 73   3   4   8   3   6   3]
- [  3 150   9   2  15   0   6]
- [ 33  20 130  35  38  11  39]
- [ 15   7   7 107   8   5  15]
- [  2   3   3   2  52   0   0]
- [  7   1   5   1   1  44   5]
- [ 18   2   9  10   5   6  69]]
-Node Classification on random seed  8104 -> 0.609
-Confusion Matrix:
- [[ 74   3   1   6   3  10  16]
- [  3 113   9   3   4   2   3]
- [ 46  22 147  27  19  20  44]
- [ 10   4  18  98   6   3  21]
- [  5   9   5   2  62   0   6]
- [  4   0   1   4   1  37   6]
- [ 10   3   4   5  16   7  78]]
-Node Classification on random seed  8105 -> 0.649
-Confusion Matrix:
- [[ 89   3   6   7   3  10   3]
- [  5 141   6   3   0   4   3]
- [ 22  17 162  32  25  18  28]
- [  4   4  23  83  13   3  16]
- [  0  16   7   2  57   0   1]
- [  4   1   1   4   0  34   9]
- [ 13   5   7   2   7  14  83]]
-Node Classification on random seed  8106 -> 0.621
-Confusion Matrix:
- [[ 70   8   2   3   6   7  10]
- [ 11 136   5   3   8   5   8]
- [ 29  16 140  36  35  30  25]
- [  6   5   8 114   6   4  15]
- [  0   6   2   5  59   0   3]
- [ 15   0   6   1   0  34   1]
- [ 21   0   6   6   3  13  68]]
-Node Classification on random seed  8107 -> 0.625
-Confusion Matrix:
- [[ 65   6   3   1   3  13  19]
- [  3 123   3   4   3   1   6]
- [ 28  33 137  27  45  19  37]
- [  9   1  14 119   4   3  14]
- [  3   6   4   4  51   0   2]
- [  4   1   1   0   0  50   5]
- [ 10   5  11   4   6  10  80]]
-Node Classification on random seed  8108 -> 0.615
-Confusion Matrix:
- [[ 64   3   3   1  16  13   6]
- [  6 132   7   0  13   2   0]
- [ 21  17 149  39  24  21  37]
- [ 13  10  15 105   8   5   6]
- [  0   6   5   1  56   1   5]
- [  9   3   2   1   2  43   6]
- [  7   4   9  10   4  24  66]]
-Node Classification on random seed  8109 -> 0.627
-Confusion Matrix:
- [[ 60   1   4   9   4   7  11]
- [  9 117   3   3   3   5   8]
- [ 21  20 160  30  34  15  35]
- [ 14   3  22 115   4   5  11]
- [  4   9   4   1  53   0   2]
- [  4   3   3   3   1  40   8]
- [ 17   6   4   7   6  10  82]]
-Node Classification on random seed  8110 -> 0.579
-Confusion Matrix:
- [[ 81   4   5   5   5   9   9]
- [  2 113   6   5   6   2   5]
- [ 26  37 112  40  36  26  40]
- [ 12   1  25  97   8   7   6]
- [  0   7  12   1  53   0   5]
- [  8   2   1   6   2  43   6]
- [  9   5   6   7   3  14  80]]
-Node Classification on random seed  8111 -> 0.609
-Confusion Matrix:
- [[ 68   6   4   4   6   3  16]
- [  5 134   8   3   9   7   0]
- [ 17  12 127  54  21  25  34]
- [ 15   4  11  90   3   6  22]
- [  1  12   3   0  67   0   2]
- [  5   2   7   3   0  42   2]
- [  9   3   7   9  10  21  81]]
-Node Classification on random seed  8112 -> 0.605
-Confusion Matrix:
- [[ 60   2   1   6   4  13  18]
- [  5 116   6   0  11   2   3]
- [ 25  27 147  27  21  22  44]
- [ 16   3  17  90   5   6   6]
- [  0   7   3   0  69   3   2]
- [  9   3   5   0   8  42   6]
- [ 10   5  11   7   9  17  81]]
-Node Classification on random seed  8113 -> 0.603
-Confusion Matrix:
- [[ 79   2   3   3   1   8  10]
- [ 11 138   1   1   8   0   5]
- [ 26  35 124  44  33  15  39]
- [ 20   5  11  94   4   7   5]
- [  1   5   9   0  56   1   4]
- [  7   2   0   0   2  44   5]
- [ 19   9   9   9   5  13  68]]
-Node Classification on random seed  8114 -> 0.603
-Confusion Matrix:
- [[ 79   2   9   2   5  11  14]
- [  4 125  12   5   7   0   4]
- [ 26  33 117  46  14  17  40]
- [ 16   1   8  97   1   8  15]
- [  1  13   4   1  59   3   1]
- [  1   0   3   6   0  46   6]
- [  8   3  13   5   4  25  80]]
-Node Classification on random seed  8115 -> 0.638
-Confusion Matrix:
- [[ 58   5   7   8   8   3  10]
- [  3 132   3   2   7   3   5]
- [ 17  28 131  23  46  16  48]
- [  7   5   9 122   6  12   9]
- [  3   3   1   3  63   1   2]
- [  4   0   1   1   0  51   7]
- [ 12   2  15   8   4   5  81]]
-Node Classification on random seed  8116 -> 0.618
-Confusion Matrix:
- [[ 69   4   5   2   3   3  11]
- [  1 134  12   5   5   5   6]
- [ 25  10 109  63  38  20  40]
- [ 11   7  11 107   2   2  12]
- [  3   8   0   2  69   0   2]
- [  4   2   1   4   0  49   6]
- [  9   6   7   8   6  11  81]]
-Node Classification on random seed  8117 -> 0.624
-Confusion Matrix:
- [[ 86   1  10   3   4   4   7]
- [  8 124   2   1   9   2   7]
- [ 35  21 141  30  17  20  40]
- [  7   1  28  95   5   2  16]
- [  4   5   6   1  63   1   1]
- [  5   4   2   0   1  45   7]
- [ 23   4   9   7   4  12  70]]
-Node Classification on random seed  8118 -> 0.665
-Confusion Matrix:
- [[ 68   3  11   2   5  13   8]
- [  3 137   2   7   9   0   2]
- [ 26  14 161  32  18  16  23]
- [ 15   2  15 115   4   4  17]
- [  0   7   4   3  58   1   3]
- [  6   1   1   0   3  40   2]
- [ 20   3   8   5   6  11  86]]
-Node Classification on random seed  8119 -> 0.644
-Confusion Matrix:
- [[ 76   1   1   4   5  14  17]
- [  5 137   7   1   5   1   2]
- [ 16  23 140  39  14  25  46]
- [ 12   2  15 100   1  12   6]
- [  0   9   9   4  62   0   1]
- [  6   8   1   0   0  53   4]
- [  4   4   4   6   7  15  76]]
-Node Classification on random seed  8120 -> 0.633
-Confusion Matrix:
- [[ 79   1   1   2   6   9   5]
- [  6 138   3   8   3   0   1]
- [ 24  25 149  39  22  18  26]
- [ 20   3  11  87   8  15   4]
- [  0   6   2   6  56   2   1]
- [  6   3   3   4   0  52   6]
- [ 23   4   8   7   6  20  72]]
-Node Classification on random seed  8121 -> 0.632
-Confusion Matrix:
- [[ 73   2   5   3   5   9  10]
- [  8 130   4   3   6   2   1]
- [ 14  22 143  21  38  20  54]
- [ 17   5  14  90   6  12  15]
- [  0   7   8   1  58   2   2]
- [  7   1   2   1   1  46   2]
- [ 10   3   8   1   7   9  92]]
-Node Classification on random seed  8122 -> 0.641
-Confusion Matrix:
- [[ 66   4   8   5   2  12   4]
- [ 15 140   5   5   4   1   2]
- [ 20  30 172  18  13  28  20]
- [ 12   3  25  98   9   7  10]
- [  1  10   5   2  55   2   1]
- [  8   0   4   3   0  37   1]
- [ 17   3   8   5   9  18  73]]
-Node Classification on random seed  8123 -> 0.59
-Confusion Matrix:
- [[ 75   3   1  18   9   8  10]
- [  4 123   2   3   8   0   4]
- [ 26  22 137  54  27   5  50]
- [ 10   2  24  82   8  10  17]
- [  2   6   1   1  55   0   2]
- [  7   3   0   4   3  43   3]
- [ 17   7   5  13   4   7  75]]
-Node Classification on random seed  8124 -> 0.625
-Confusion Matrix:
- [[ 73   1   4   2   4  13  11]
- [  3 117   5   7  16   4   3]
- [ 20  22 127  65  11  30  37]
- [  8   3   5 113   5   6  14]
- [  0   7   8   1  63   2   2]
- [  3   2   0   1   2  46   3]
- [  4   7  13   7   7   7  86]]
-Node Classification on random seed  8125 -> 0.663
-Confusion Matrix:
- [[ 72   4   7   4   3   6   5]
- [  8 141   4   5   3   1   1]
- [ 40  24 145  18  29  20  26]
- [ 10   4  10 119   8   2   2]
- [  3   7   5   0  69   1   1]
- [ 10   1   2   0   0  44   5]
- [ 19   2  12   7   6  12  73]]
-Node Classification on random seed  8126 -> 0.655
-Confusion Matrix:
- [[ 71   3   3   5   3  18   8]
- [  2 136   1   3  12   2   4]
- [ 21  18 157  44  25  13  32]
- [ 10   0  11 103   5   6  17]
- [  2   2   5   0  63   1   1]
- [  8   2   1   2   2  49   4]
- [ 12   4   6   5   7  15  76]]
-Node Classification on random seed  8127 -> 0.611
-Confusion Matrix:
- [[ 74   8   1   1   0  11  16]
- [  2 131   5   2   3   1   6]
- [ 34  25 146  26  14  30  52]
- [ 12   2  19  93   2   8  12]
- [  1   8   5   1  50   2   5]
- [  5   2   3   0   2  40  16]
- [ 15   2  11   3   3  13  77]]
-Node Classification on random seed  8128 -> 0.581
-Confusion Matrix:
- [[ 55   9   8   3   5  18   8]
- [  5 122   4   1  19   3   3]
- [ 36  40 109  19  46  35  23]
- [ 10   7  13 100  11   3  16]
- [  2   6   2   1  66   0   1]
- [  6   1   5   0   0  53   3]
- [  9   5   4  10   5  14  76]]
-Node Classification on random seed  8129 -> 0.61
-Confusion Matrix:
- [[ 71   2   4   4   3  12   7]
- [  3 123   8   1   9   1   5]
- [ 19  23 150  32  38  21  43]
- [ 11   1  13 111   5   7  17]
- [  0  11   3   2  43   1   7]
- [  5   3   1   1   0  41   8]
- [ 14   6  11   5   8  15  71]]
-Node Classification on random seed  8130 -> 0.577
-Confusion Matrix:
- [[ 70   1   6   3   3   6  10]
- [  5 135   2   0   3   3   8]
- [ 29  37 121  15  60  35  37]
- [ 17   9  14  86   5   7  18]
- [  1   6   0   0  61   1   2]
- [  1   1   2   3   0  42   9]
- [ 14   7   6   6  11  20  62]]
-Node Classification on random seed  8131 -> 0.614
-Confusion Matrix:
- [[ 73   5   7   4   3   8   8]
- [  8 122  19   6   6   2   4]
- [ 19  22 137  49  28  23  39]
- [ 13   8   9  97   6   4  12]
- [  0   6   1   1  61   1   2]
- [  8   2   1   2   0  43   3]
- [ 11   2   9   8   6  11  81]]
-Node Classification on random seed  8132 -> 0.608
-Confusion Matrix:
- [[ 65   1   6   6   5  15   7]
- [  6 122   2   3   8   1   5]
- [ 27  16 136  44  38  20  49]
- [ 15   2  10 118   4   4   6]
- [  3   8   1   2  50   1   4]
- [  5   1   2   1   0  42  12]
- [ 11   4   9   9   4  15  75]]
-Node Classification on random seed  8133 -> 0.595
-Confusion Matrix:
- [[ 75   0   7   2   3  15  12]
- [  0 102  13   3  28   4   1]
- [ 35  17 135  21  35  16  48]
- [ 20   2  26  95   3   4   9]
- [  4   4   1   3  65   0   4]
- [  8   0   1   0   0  38   9]
- [ 11   2   6   9   9  10  85]]
-Node Classification on random seed  8134 -> 0.528
-Confusion Matrix:
- [[ 50   2   4   4   6  13  20]
- [  7 120  10   1  10   7   3]
- [ 21  17  91  52  47  34  42]
- [ 24   2  10  88   7  10  20]
- [  4   5   5   1  56   0   3]
- [  4   1   6   3   1  49   6]
- [  7   3  10   3  19  18  74]]
-Node Classification on random seed  8135 -> 0.643
-Confusion Matrix:
- [[ 67   1   5   8   4  14  17]
- [  2 132   2   4   6   1   1]
- [ 19  26 159  32  25  17  32]
- [ 13   7   8  94   9   2  22]
- [  0   3   7   1  56   1   2]
- [  6   1   2   1   1  51   6]
- [ 10   1   4   9  12  13  84]]
-Node Classification on random seed  8136 -> 0.63
-Confusion Matrix:
- [[ 72   0   3   3   4  15   6]
- [  4 130   3   8   1   4   4]
- [ 28  18 143  61  10  29  37]
- [  7   4   8 120   6   6   7]
- [  9   9   6   1  45   0   3]
- [  6   2   1   9   2  47   2]
- [ 11   3  11   4   2  13  73]]
-Node Classification on random seed  8137 -> 0.628
-Confusion Matrix:
- [[ 62   4   3   2   7  14   4]
- [  5 116   8   5   7   0   4]
- [ 27  22 142  47  17  23  30]
- [ 15   4  18 111   1   7   9]
- [  0   5   3   3  67   0   2]
- [  0   1   1   1   4  49   2]
- [ 12   4   8  15  13  15  81]]
-Node Classification on random seed  8138 -> 0.614
-Confusion Matrix:
- [[ 81   1   4   3   9   8   4]
- [  5 136   2   3  17   3   2]
- [ 35  19 118  36  23  25  41]
- [ 23   6  20 103   4   6   7]
- [  0  10   3   0  67   0   4]
- [  8   3   1   3   2  40   4]
- [ 11   3   8   9   5   6  69]]
-Node Classification on random seed  8139 -> 0.611
-Confusion Matrix:
- [[ 82   3   1   2   3   7   9]
- [  3 143   6   1  14   1   9]
- [ 25  12 127  31  39  19  49]
- [ 24   5   9 111   5   4  10]
- [  0   4   6   0  48   0   2]
- [  7   2   1   1   4  38   7]
- [ 20   3   5  13   8  15  62]]
-Node Classification on random seed  8140 -> 0.61
-Confusion Matrix:
- [[ 66   3   1   6   9  14  11]
- [  5 129   3   0  11   2   6]
- [ 23  19 135  36  31  31  39]
- [  9   6  10  97   6  11  20]
- [  1   2   2   0  55   4   2]
- [  3   2   0   1   2  54   3]
- [ 15   1   4  14   6  16  74]]
-Node Classification on random seed  8141 -> 0.594
-Confusion Matrix:
- [[ 56   3  10   3   8   6  11]
- [  4 125   4   1  10   0   3]
- [ 37  24 143  37  33  16  32]
- [ 11   1  31 111   8   8  13]
- [  2   5   2   3  57   0   2]
- [ 11   1   6   0   2  36   4]
- [  8   3  17   9  10   7  66]]
-Node Classification on random seed  8142 -> 0.637
-Confusion Matrix:
- [[ 73   3   1   5   1  15  13]
- [  1 128   4   0   2   3   3]
- [ 24  22 150  37  18  31  30]
- [ 20   3  16 113   1   4  12]
- [  1  10   5   8  53   1   5]
- [  9   1   0   3   0  53   6]
- [ 13   4   5   2   5  16  67]]
-Node Classification on random seed  8143 -> 0.598
-Confusion Matrix:
- [[ 64   2  11   4   9  14   4]
- [ 16 116   2   0  14   3   2]
- [ 26  17 157  27  22  31  32]
- [  9   7  15  93   3  16   5]
- [  3   5   2   4  70   1   0]
- [ 16   1   0   3   1  40   0]
- [ 19   1   4  16   9  26  58]]
-Node Classification on random seed  8144 -> 0.628
-Confusion Matrix:
- [[ 72   1   5   5   4   6  17]
- [ 10 135   4   2   6   4   3]
- [ 28  21 142  35  25  25  29]
- [ 13   7   9 122   2  13  13]
- [  0   7   1   2  50   2   1]
- [  9   0   3   2   1  40   6]
- [  7   9  10   3   5  17  67]]
-Node Classification on random seed  8145 -> 0.63
-Confusion Matrix:
- [[ 76   2   2   2   3  13   9]
- [  3 129   7   4   7   1   3]
- [ 15  21 149  34  14  35  39]
- [ 11   7  24  93   3  11  11]
- [  5  10   3   1  65   1   1]
- [  2   0   3   0   2  50   7]
- [ 14   4  12   1   2  21  68]]
-Node Classification on random seed  8146 -> 0.599
-Confusion Matrix:
- [[ 68   3   4  11   3   5  11]
- [  3 136   5   0   2   1   9]
- [ 27  24 128  37  29  22  37]
- [ 19   6   9 112   1   7  23]
- [  3  10   4   0  58   2   1]
- [ 12   4   1   1   1  36  10]
- [ 23   4   9   1   3  14  61]]
-Node Classification on random seed  8147 -> 0.636
-Confusion Matrix:
- [[ 77   3  13   5   5   4  17]
- [  2 133   5   5   3   2   7]
- [ 25  17 167  22  37  13  29]
- [  9   3   9  79  17   8  13]
- [  2   4   4   3  68   0   4]
- [  4   1   3   3   1  36   5]
- [ 14   6  18   4   6   9  76]]
-Node Classification on random seed  8148 -> 0.661
-Confusion Matrix:
- [[ 55   2   1   7   3   6  19]
- [  9 120   2   0   9   5   2]
- [ 26  15 179  33  24  18  30]
- [  9   2  21 118   9   5   8]
- [  0   6   4   1  62   0   0]
- [  2   1   0   1   2  40   6]
- [ 12   3  11   8   4  13  87]]
-Node Classification on random seed  8149 -> 0.659
-Confusion Matrix:
- [[ 72   1   0   5   0   7  17]
- [  3 142   8   1   2   1   3]
- [ 18  27 157  30  27  17  38]
- [  7   4  11 108   9   5  16]
- [  1   7   2   5  57   0   3]
- [  3   3   2   5   1  41   7]
- [  5   3   4   7   9  17  82]]
-Node Classification on random seed  8150 -> 0.631
-Confusion Matrix:
- [[ 80   3   5   8   2   8  16]
- [  4 118   8   4  13   3   4]
- [ 11  22 157  33  22  21  29]
- [ 20   6  17  95   2   5  14]
- [  0   5   4   2  69   0   1]
- [  3   0   4   4   1  45  11]
- [  7   0  15   8   7  17  67]]
-Node Classification on random seed  8151 -> 0.607
-Confusion Matrix:
- [[ 68   3   3   4   6   9  13]
- [  5 140   4   2   9   8   7]
- [ 19  20 137  51  22  35  29]
- [ 14   2  11  86   6   9   8]
- [  0   9   9   0  64   0   1]
- [ 11   1   3   3   0  32   7]
- [ 15   6  13   1   5  10  80]]
-Node Classification on random seed  8152 -> 0.578
-Confusion Matrix:
- [[ 63   3   3   3   1  12  20]
- [ 11 121   2   0   6   5   6]
- [ 27  22 131  30  38  37  44]
- [ 13   1  11  97   3   4  25]
- [  0   4   3   0  63   0   2]
- [  7   3   0   3   0  39   5]
- [ 23   8   9   6  14   8  64]]
-Node Classification on random seed  8153 -> 0.639
-Confusion Matrix:
- [[ 85   0   5   4   2  19   5]
- [  5 119  12   3   2   3   2]
- [ 19  17 138  40  29  15  42]
- [ 10   0  20 112   2   3  16]
- [  1   8   4   4  58   2   7]
- [  4   1   0   4   0  41   5]
- [ 10   1   9   4   8  14  86]]
-Node Classification on random seed  8154 -> 0.6
-Confusion Matrix:
- [[ 63   0   6   6   1   8   8]
- [  9 131   4   7  13   8   4]
- [ 18  14 134  38  30  32  26]
- [ 12   2  18  84   7  18  21]
- [  2   4   2   4  63   4   3]
- [  9   0   1   2   0  47   7]
- [ 16   2   3   5  12  14  78]]
-Node Classification on random seed  8155 -> 0.601
-Confusion Matrix:
- [[ 72   3   5   2   2   6   8]
- [  4 123   7   4  14   7   5]
- [ 16  27 119  41  53  28  25]
- [ 12   2  18 106   6   4   5]
- [  1   9   1   2  61   1   4]
- [  2   3   2   1   0  44   3]
- [ 27   4   2   5   8  20  76]]
-Node Classification on random seed  8156 -> 0.644
-Confusion Matrix:
- [[ 87   8   3   8   1   8   7]
- [  6 140   4   4   7   1   2]
- [ 15  26 133  34  26  22  32]
- [ 11   3  18 109   6   5   5]
- [  1   8   4   2  67   3   1]
- [ 11   0   3   6   0  31   1]
- [ 18   7   7   3   7  12  77]]
-Node Classification on random seed  8157 -> 0.612
-Confusion Matrix:
- [[ 77   3  14   2   5   9   4]
- [  4 144   6   0   4   4   1]
- [ 23  32 128  37  35  22  41]
- [  6   5  12 100   9  13  15]
- [  2   5   1   1  57   0   3]
- [  8   3   2   1   0  42   4]
- [ 16   5  13   4   5   9  64]]
-Node Classification on random seed  8158 -> 0.617
-Confusion Matrix:
- [[ 62   2   4   5   5  22  13]
- [  5 133   5   0  11   1   4]
- [ 24  13 137  38  33  24  60]
- [  9   4   9  99   3   8  10]
- [  0   7   2   1  66   1   2]
- [  2   1   0   3   0  45   6]
- [ 14   2   6   6   3  15  75]]
-Node Classification on random seed  8159 -> 0.629
-Confusion Matrix:
- [[ 68   0   6   3   5   6  10]
- [  5 111   2   3  13   3  11]
- [ 22  11 154  32  39  22  32]
- [ 14   6  13 104  11   6  17]
- [  2   3   2   0  65   1   0]
- [  6   1   5   2   3  56   4]
- [  4   1   8   6  13  18  71]]
-Node Classification on random seed  8160 -> 0.594
-Confusion Matrix:
- [[ 80   2   4   3   4   8  15]
- [  7 105   2   4  18   5   5]
- [ 16  18 112  53  30  33  44]
- [ 14   4  11 105   5   3  25]
- [  2   2   6   1  62   1   2]
- [  4   0   3   0   2  40   7]
- [  7   6   9   1   4  16  90]]
-Node Classification on random seed  8161 -> 0.62
-Confusion Matrix:
- [[ 77   2   5   8   2   5   9]
- [  4 140   2   7   2   4   3]
- [ 27  28 123  33  41  23  38]
- [ 10   3  10  94  12  14   7]
- [  1   8   4   0  61   5   2]
- [  5   1   3   4   0  45   2]
- [ 11   3   8   9   2  13  80]]
-Node Classification on random seed  8162 -> 0.629
-Confusion Matrix:
- [[ 76   5   6   4   1  15  12]
- [  4 138   3   0   9   7   9]
- [ 18  27 133  34  36  13  35]
- [ 14   3  15  91   5   4  12]
- [  1   5   5   2  62   1   2]
- [  4   0   3   1   1  52   5]
- [ 12   2   8   3  13  12  77]]
-Node Classification on random seed  8163 -> 0.587
-Confusion Matrix:
- [[ 88   1   2   5   5   9   3]
- [  1 133   5   3   6   3   8]
- [ 42  30 120  37  21  28  32]
- [  9   5  19  88  14  10  22]
- [  2   4   7   4  55   0   4]
- [  6   4   1   0   2  44   2]
- [ 16   2  12   8   2  17  59]]
-Node Classification on random seed  8164 -> 0.63
-Confusion Matrix:
- [[ 75   1   7   4   3   9  10]
- [  3 124   3   4  12   0   5]
- [ 30  25 131  25  16  29  60]
- [  9   6  11 105   0   4  13]
- [  1   6   2   3  59   1   2]
- [  4   1   4   3   2  52   5]
- [  6   2   6   5   4  24  84]]
-Node Classification on random seed  8165 -> 0.595
-Confusion Matrix:
- [[ 65   3   1   7  16   4  10]
- [  7 128   6   2   9   2   4]
- [ 26  26 141  28  14  40  40]
- [ 16   3  18 103   6   4  11]
- [  0   9   5   2  48   0   2]
- [  8   1   4   1   1  40   3]
- [ 19   6  11   5  13  12  70]]
-Node Classification on random seed  8166 -> 0.611
-Confusion Matrix:
- [[ 77   4   3   0   3  16  11]
- [  7 141   5   0  17   0   1]
- [ 20  14 126  39  29  28  53]
- [ 17   1  11 101   5   4  18]
- [  1   6   8   0  55   2   0]
- [  6   2   2   2   0  46   0]
- [  7   3  11   2   5  26  65]]
-Node Classification on random seed  8167 -> 0.631
-Confusion Matrix:
- [[ 79   4   8   5   3  20   2]
- [  3 111   6   2   8   2   5]
- [ 17  24 157  26  38  26  47]
- [ 16   0  17 116   9   3   3]
- [  0   6   2   2  53   0   4]
- [  3   0   2   4   0  38   5]
- [  3   1   8  13   4  18  77]]
-Node Classification on random seed  8168 -> 0.611
-Confusion Matrix:
- [[ 88   1   3   7   2   9  12]
- [ 12 120   6   7   5   4   1]
- [ 42  14 133  50  15  21  28]
- [ 24   6  13  99   6   4  10]
- [  6   2   7   1  53   0   4]
- [  6   2   3   1   1  60   0]
- [ 15   3  12   9   3  12  58]]
-Node Classification on random seed  8169 -> 0.653
-Confusion Matrix:
- [[ 73   3   1   6   2   9   1]
- [  4 134   3   0   3   9   3]
- [ 33  22 142  31  19   8  52]
- [  9  12   9 119   4  12  10]
- [  1   7   1   0  50   4   4]
- [  3   1   2   2   0  59   4]
- [  9   1   6  14   9  14  76]]
-Node Classification on random seed  8170 -> 0.597
-Confusion Matrix:
- [[ 69   1   3   3   2  15  16]
- [ 11 110   1   2   9   5   9]
- [ 22  20 151  25  24  27  53]
- [ 29   3  14 100   4  11   8]
- [  2   8   4   1  56   1   3]
- [  7   1   4   1   1  42  10]
- [ 10   4  10   4   3  12  69]]
-Node Classification on random seed  8171 -> 0.603
-Confusion Matrix:
- [[ 67   0   4   8   9   5  11]
- [  2 128   2   5   4   4   8]
- [ 27  52 129  25  29  14  47]
- [ 14   2  14 110   3   5  15]
- [  1  11   5   0  51   1   2]
- [  7   0   9   2   2  39   5]
- [ 12   1  14   6   4   6  79]]
-Node Classification on random seed  8172 -> 0.662
-Confusion Matrix:
- [[ 70   3   3   2   4   9   4]
- [  6 138   2   3  12   4   4]
- [ 30  20 171  20  29  24  27]
- [ 15   6   9 111   4   9   6]
- [  2   4   2   2  63   0   4]
- [  5   3   2   3   0  42   6]
- [  9   1  18   6   4  12  67]]
-Node Classification on random seed  8173 -> 0.623
-Confusion Matrix:
- [[ 74   1   3   5   8  14  26]
- [  3 131   7   0   1   9   4]
- [ 22  15 148  32  17  22  48]
- [  7   1  18  99   5   6   8]
- [  1   5   4   3  59   2   5]
- [  8   2   2   2   0  44   7]
- [ 13   4   4   8   6  19  68]]
-Node Classification on random seed  8174 -> 0.607
-Confusion Matrix:
- [[ 70   5   9   7   2  11   4]
- [  4 139   5   2   2   5   5]
- [ 26  33 133  26  39  16  36]
- [ 11   5  14 101   9  10  15]
- [  5   6   6   0  54   1   1]
- [  9   3   5   1   0  39   7]
- [  2   2  16   7   7  14  71]]
-Node Classification on random seed  8175 -> 0.613
-Confusion Matrix:
- [[ 66   1   3   6   2  29   8]
- [ 15 112   3   4   5   3   3]
- [ 26  22 137  22  29  32  53]
- [  5   3   5 113   6   5  17]
- [  2   3   2   1  66   1   6]
- [  1   3   4   1   2  45   0]
- [ 11   6   2   3  11  21  74]]
-Node Classification on random seed  8176 -> 0.59
-Confusion Matrix:
- [[ 47   2  10   3   4  13  18]
- [  8 138   7   3   3   2   1]
- [ 19  21 121  49  19  38  40]
- [ 15   3  17 120   8   3  10]
- [  1   8   2   2  58   1   3]
- [  6   3   3   2   1  48   4]
- [  1   6  11  11   6  23  58]]
-Node Classification on random seed  8177 -> 0.609
-Confusion Matrix:
- [[ 75   1   2   2   3   9  10]
- [  5 127   4   4   1   3   9]
- [ 24  30 135  18  12  40  46]
- [  5   7  11  94  10  14  16]
- [  1   9   2   0  55   1   6]
- [  3   1   1   1   0  57   4]
- [  8  10  14  13   8  23  66]]
-Node Classification on random seed  8178 -> 0.613
-Confusion Matrix:
- [[ 75   3   2   2   3  13   4]
- [  2 119   9   2  10   7   2]
- [ 20  25 130  34  38  30  38]
- [ 12   5  12 110   4  14   9]
- [  4  10   2   1  62   0   1]
- [  5   2   2   2   0  49   3]
- [ 11   3   5  11   6  19  68]]
-Node Classification on random seed  8179 -> 0.621
-Confusion Matrix:
- [[ 66   3   4   7   4  10   9]
- [  3 139   5   3   3   0   3]
- [ 17  21 148  28  40  14  59]
- [ 17   5  18 105   2   3   7]
- [  0  10   3   3  55   1   1]
- [  4   1   5   0   2  47   4]
- [ 20   4  15   2   7  12  61]]
-Node Classification on random seed  8180 -> 0.624
-Confusion Matrix:
- [[ 72   0   3  10   4  15  11]
- [  3 115  10   2  20   2   3]
- [ 22  19 137  30  49  12  37]
- [  2   4  29  93   9   7  14]
- [  0   6   5   1  58   1   6]
- [  3   0   0   2   1  62   3]
- [  3   1   4   6   8   9  87]]
-Node Classification on random seed  8181 -> 0.618
-Confusion Matrix:
- [[ 71   2   4   7   1  15  23]
- [  7 140   2   4   5   4   3]
- [ 18  25 133  36  24  17  39]
- [ 12   3  10  85   6   4  24]
- [  4  16   2   0  58   0   2]
- [  5   4   3   2   2  47   2]
- [  4   5  11   5   5  15  84]]
-Node Classification on random seed  8182 -> 0.639
-Confusion Matrix:
- [[ 69   2   5   4   2  11  12]
- [  7 139   1   1   3   1   4]
- [ 30  22 142  41  16  20  46]
- [  8   5  19 113   2   9   5]
- [  0   8   3   2  61   1   4]
- [  7   0   0   2   0  45   4]
- [ 14   4   5   6   8  17  70]]
-Node Classification on random seed  8183 -> 0.636
-Confusion Matrix:
- [[ 76   3   3   1   3  11   6]
- [  8 128   5   2   4   1   6]
- [ 28  19 143  39  18  36  32]
- [ 14   3  11  99   2  12  12]
- [  2   4   6   1  61   2   4]
- [  5   0   4   1   0  44   2]
- [ 18   3   8  10   1  14  85]]
-Node Classification on random seed  8184 -> 0.623
-Confusion Matrix:
- [[ 70   0   2   3   6   7  10]
- [  2 126  12   0   5   0   2]
- [ 23  23 158  18  36  18  60]
- [ 10   3   9 105   9   9  22]
- [  0   5   7   1  54   0   3]
- [  8   0   2   1   2  43   4]
- [ 12   2   8   6   9  18  67]]
-Node Classification on random seed  8185 -> 0.622
-Confusion Matrix:
- [[ 63   0   4   8   0  17   6]
- [  7 125   4   4   4   3   3]
- [ 31  22 155  36  26  40  28]
- [ 16   3  10  97   5   6  10]
- [  0   9   6   2  54   0   2]
- [  2   2   0   0   1  54   4]
- [ 12   6   7   7   9  16  74]]
-Node Classification on random seed  8186 -> 0.604
-Confusion Matrix:
- [[ 68   2   2   4   7  13  13]
- [  2 118   9   3   4   6  12]
- [ 24   8 151  28  45  26  39]
- [ 15  10  22  83   3   3  20]
- [  2   5   8   0  47   2   3]
- [  7   1   2   0   3  55   1]
- [ 13   3  10   4   6   6  82]]
-Node Classification on random seed  8187 -> 0.598
-Confusion Matrix:
- [[ 71   1   5   0   4  19   6]
- [  5 127   5   1   8   3  13]
- [ 26  18 136  21  32  25  34]
- [  8   4  24  77   8  21  17]
- [  0   4   8   1  58   1   2]
- [  3   2   4   0   1  50   2]
- [  6   4  17   7   6  26  79]]
-Node Classification on random seed  8188 -> 0.622
-Confusion Matrix:
- [[ 73   3   3   2   3  15  13]
- [  3 133   3   4   4   3   2]
- [ 19  40 134  32  31  21  44]
- [  5   6  14  96   2   7  12]
- [  3   7   2   0  67   0   3]
- [  5   0   1   2   1  50   4]
- [ 12   8   8   6   8  17  69]]
-Node Classification on random seed  8189 -> 0.683
-Confusion Matrix:
- [[ 67   0   1   5   1   3  11]
- [  1 132   6   2   2   0   7]
- [ 23  17 194  25  23  24  36]
- [  6   2  18 103   6   0  14]
- [  0   7  14   3  53   0   1]
- [  5   1   0   3   1  44   5]
- [  2   5   7   4   4  22  90]]
-Node Classification on random seed  8190 -> 0.582
-Confusion Matrix:
- [[ 49   6  10  11   7  21  11]
- [  5 132   7   5   7   4   2]
- [ 17  35 150  56  14  16  28]
- [ 18   3   6 108  13   6   7]
- [  3   4   5   2  50   0   4]
- [  7   3   3   2   2  44   6]
- [  5   3  15  16   7  16  49]]
-Node Classification on random seed  8191 -> 0.613
-Confusion Matrix:
- [[ 71   4   9   1   5  22   9]
- [  9 118   4   5   9   4  10]
- [ 24  27 136  26  25  14  47]
- [ 12   7  12 110   2   8  14]
- [  1   7   3   1  68   1   3]
- [  4   1   2   2   1  43   5]
- [ 15   4   6   8   5   9  67]]
-Node Classification on random seed  8192 -> 0.627
-Confusion Matrix:
- [[ 79   2   6   4   3  14   7]
- [ 15 113   8   4   4   2   9]
- [ 19  21 141  39  20  19  44]
- [  8  14   6  97   0   5  17]
- [  0   7   4   2  56   0   2]
- [  3   2   3   1   0  48  10]
- [  7   7   7   9   2  17  93]]
-Node Classification on random seed  8193 -> 0.622
-Confusion Matrix:
- [[ 65   3   0   7   6   9   5]
- [  6 129   8   4  10   2   3]
- [ 28  12 158  13  31  33  41]
- [ 15   8  10  90   3   0  19]
- [  4  12   3   2  66   0   7]
- [  6   1   3   3   0  36   4]
- [ 20   9   8   6   5   9  78]]
-Node Classification on random seed  8194 -> 0.641
-Confusion Matrix:
- [[ 74   3   4   2   0  10  14]
- [  4 132   6   0  11   2   3]
- [ 22  23 144  21  27  20  44]
- [ 15   1  19  99   4   2  16]
- [  2   2   2   1  70   1   3]
- [ 10   0   2   4   1  50   5]
- [ 13   4   9   2   8  17  72]]
-Node Classification on random seed  8195 -> 0.612
-Confusion Matrix:
- [[ 79   4   4  13   2  14   4]
- [  4 142   8   0   8   1   2]
- [ 29  15 119  42  37  31  35]
- [  6   4  12 117   3   5   6]
- [  3  11   7   1  50   2   0]
- [  7   3   3   1   1  44   4]
- [ 14   9   2  10   4  17  61]]
-Node Classification on random seed  8196 -> 0.608
-Confusion Matrix:
- [[ 58   0   8   8   7   9   9]
- [  6 134   2   2   5   6   4]
- [ 32  26 132  27  36  23  38]
- [ 15   2  18  97   6   4   8]
- [  0   3   3   0  59   0   4]
- [  9   0   2   2   0  48   7]
- [ 10   4  15   9   6  17  80]]
-Node Classification on random seed  8197 -> 0.602
-Confusion Matrix:
- [[ 79   2   1   8   1  13  10]
- [  8 119   1   2   5   5   7]
- [ 36  24 132  21  18  35  41]
- [ 17   4  13  94   6   9   7]
- [  2   9   5   2  66   0   1]
- [  9   2   5   3   0  37   7]
- [  9   4   7   7   2  30  75]]
-Node Classification on random seed  8198 -> 0.587
-Confusion Matrix:
- [[ 78   0   1   9   6  22   6]
- [ 13 111   4   2  11   0   8]
- [  8  21 123  46  30  34  37]
- [  6   7  12 104   9   4   9]
- [  2   7   6   2  63   2  10]
- [ 11   1   2   1   0  44   3]
- [ 14   5   6  11   7  18  64]]
-Node Classification on random seed  8199 -> 0.642
-Confusion Matrix:
- [[ 79   3   4   6   3   3  13]
- [  2 121   7   4   8   2   2]
- [ 30  19 150  35  27  19  43]
- [ 16   0  18  99   9   4   9]
- [  4   4   1   2  56   1   1]
- [  2   2   2   5   3  35   4]
- [  9   1   8   6   5  12 102]]
-Node Classification on random seed  8200 -> 0.614
-Confusion Matrix:
- [[ 59   2  15   2   4  16   6]
- [  2 116  15   1   4   5   7]
- [ 28  11 153  58  19  13  35]
- [  8   1  19 111   1   8  16]
- [  0   8   4   3  57   1   2]
- [  3   1   2   4   1  44   7]
- [ 15   5   9  10   8   7  74]]
-Node Classification on random seed  8201 -> 0.594
-Confusion Matrix:
- [[ 58   5   0   8   1  11  12]
- [  4 141   0   1   8   6   7]
- [ 19  23 132  32  37  25  49]
- [  6  12  11  95   6   3  28]
- [  0   2   3   1  58   4   5]
- [  2   0   0   1   1  44  10]
- [ 10   2  10  24   2  15  66]]
-Node Classification on random seed  8202 -> 0.6
-Confusion Matrix:
- [[ 56   5   7  13   7   6  11]
- [  2 114   5   1  13   3   4]
- [ 21  17 150  48  26  26  24]
- [  8   3  22 108   6   2  11]
- [  1   5   0   3  57   0   7]
- [  5   0   3   4   0  46   1]
- [ 19   3   3  20   8  27  69]]
-Node Classification on random seed  8203 -> 0.611
-Confusion Matrix:
- [[ 77   7   2   0   1   6   8]
- [  4 123  15   0   5   3   5]
- [ 23  37 143  30  21  28  47]
- [  8  10  20  89   4   7  14]
- [  0   7   4   1  46   1   6]
- [  5   1   0   0   0  46   4]
- [ 18   4   6   5   6  16  87]]
-Node Classification on random seed  8204 -> 0.605
-Confusion Matrix:
- [[ 64   2   0  12   9  17   8]
- [  3 121  11   5   7   2   3]
- [ 24  18 147  29  43  17  38]
- [  7   5  27 102   4   9   8]
- [  2   0   2   2  60   3   1]
- [  2   1   0   3   1  54   1]
- [  8   1  10  16  13  21  57]]
-Node Classification on random seed  8205 -> 0.653
-Confusion Matrix:
- [[ 71   1   1   0   3  13  12]
- [  2 134   4   3   5   3  11]
- [ 17  18 154  40  21  26  39]
- [  8   0  13 110   2   5  17]
- [  3   6   2   1  56   0   5]
- [  7   0   2   1   1  50   9]
- [  9   3   6   7   7  14  78]]
-Node Classification on random seed  8206 -> 0.62
-Confusion Matrix:
- [[ 59   1   8   9   8  24   2]
- [  4 132   3   3   8   1   2]
- [ 19  18 134  32  23  21  55]
- [  9   4  11  98   7   5  18]
- [  1   6   5   1  64   3   2]
- [  2   3   2   5   0  47   7]
- [ 10   3   5   9   7  14  86]]
-Node Classification on random seed  8207 -> 0.638
-Confusion Matrix:
- [[ 85   3   3   2   5   7   5]
- [  4 146   7   1   5   2   3]
- [ 21  26 126  32  23  27  37]
- [ 16   4  21 113   1   6   9]
- [  0  10   1   4  51   6   6]
- [  2   5   4   2   2  36   4]
- [ 10   4   1   3  11  17  81]]
-Node Classification on random seed  8208 -> 0.608
-Confusion Matrix:
- [[ 79   4   6   3   4   7   6]
- [  1 115   6   3  23   3   0]
- [ 17  19 137  38  18  42  40]
- [ 19   6  22  93   1   6  15]
- [  0   6   9   2  53   1   1]
- [  7   3   2   0   4  54   3]
- [  6   3   7   4   3  22  77]]
-Node Classification on random seed  8209 -> 0.623
-Confusion Matrix:
- [[ 79   0   7   5   3  19   4]
- [  7 124   3   1   2   1   2]
- [ 16  15 119  40  27  35  52]
- [ 16   4  10 118   7   6  10]
- [  3  11   2   4  59   0   3]
- [  6   0   0   4   0  43   5]
- [  6   3   4  14   4  16  81]]
-Node Classification on random seed  8210 -> 0.6
-Confusion Matrix:
- [[ 78   3   3   7   5  11   6]
- [  1 120   8   2  13   5   6]
- [ 26  18 126  27  33  38  58]
- [ 11   4  12 100   2   8  16]
- [  0   5   2   1  68   3   1]
- [  4   0   2   2   0  35  10]
- [  4   7   1   9  12  14  73]]
-Node Classification on random seed  8211 -> 0.606
-Confusion Matrix:
- [[ 68   2   1   3   8  14  28]
- [  4 131   3   3   8   1   1]
- [ 17  22 145  25  14  32  55]
- [  8   9  28  70   2   6  18]
- [  1   2   9   0  66   1   2]
- [  4   2   1   0   1  54  10]
- [  9   5   8   5  12  10  72]]
-Node Classification on random seed  8212 -> 0.584
-Confusion Matrix:
- [[ 63   2   1   6  10  11  14]
- [  8 125   3   0   6   2   6]
- [ 21  22 113  28  55  28  49]
- [  7   8  11 102   4  12  12]
- [  0   8   7   0  43   1   2]
- [  5   1   2   1   2  57   2]
- [ 13   5  12  11   4  14  81]]
-Node Classification on random seed  8213 -> 0.614
-Confusion Matrix:
- [[ 67   2  15   6   4   9   9]
- [  2 148   2   2   4   1   4]
- [ 26  18 127  37  38  19  55]
- [  5   0   6 116   7   8  10]
- [  3  10   3   1  53   1   6]
- [  5   7   2   0   1  36   4]
- [ 17   4   5   9   9  10  67]]
-Node Classification on random seed  8214 -> 0.559
-Confusion Matrix:
- [[ 67   1   4   5   4  13   9]
- [  7 124   7   1   7   1   5]
- [ 26  19 113  44  50  21  46]
- [ 18   7  11  77   8   5  20]
- [  0  11   2   1  64   0   2]
- [  3   4   2   1   2  47   8]
- [  9   5  18   3  14  17  67]]
-Node Classification on random seed  8215 -> 0.6
-Confusion Matrix:
- [[ 67   1   4   6   3  22   7]
- [  9 130  10   0   4   2   3]
- [ 19  22 124  36  30  27  42]
- [  8   4  15 103   4   5  22]
- [  0  12   6   1  72   0   1]
- [ 10   4   4   3   0  32   0]
- [  7   3  10  11   7  16  72]]
-Node Classification on random seed  8216 -> 0.585
-Confusion Matrix:
- [[ 68   2   1   2   5  12  11]
- [  4 131  13   2   5   5   7]
- [ 22  12 120  36  37  24  63]
- [  7   3   8 103  16   8  13]
- [  2   8   9   2  55   1   3]
- [  6   0   4   5   0  39   5]
- [ 14   3   7   5  10  13  69]]
-Node Classification on random seed  8217 -> 0.6
-Confusion Matrix:
- [[ 85   2   0   9   9  15   3]
- [  3 128   2   7   0   2   2]
- [ 15  33 121  53  36  15  36]
- [ 11   2  12  95  17   3   9]
- [  1  10   1   0  56   2   5]
- [ 10   1   3   5   0  43   1]
- [ 15   9   0  13   8  20  72]]
-Node Classification on random seed  8218 -> 0.56
-Confusion Matrix:
- [[ 67   8   1   4   6  10   1]
- [ 18 104   9   2   9   5   4]
- [ 32  29 130  24  44  24  30]
- [  4  11  26  96  11   8  13]
- [  1   6   8   1  65   0   5]
- [ 11   3   0   0   3  46   2]
- [ 19  10   3  14   9  12  52]]
-Node Classification on random seed  8219 -> 0.573
-Confusion Matrix:
- [[ 77   5  13   4   5   9   1]
- [ 12 129   3   0   9   0   7]
- [ 14  19  97  29  62  25  52]
- [  4   4  19 102   9  10  16]
- [  1  10   0   7  55   2   2]
- [  3   1   1   2   3  40   3]
- [ 10   3  10  18   6  14  73]]
-Node Classification on random seed  8220 -> 0.597
-Confusion Matrix:
- [[ 77   1  10   6   4  16  11]
- [  7 117  10   6   7   0   6]
- [ 30  13 149  42  15  18  42]
- [ 17   3  22  84   2   6   9]
- [  4   4   7   3  61   0   4]
- [  6   2   2   2   1  44   4]
- [ 23   3   7   9   4  15  65]]
-Node Classification on random seed  8221 -> 0.632
-Confusion Matrix:
- [[ 84   4   1   2   5   7   9]
- [  2 123   8   2  10   1   1]
- [ 25  20 135  38  19  34  38]
- [ 14   3   8 101   4   6  20]
- [  0   7   3   6  53   0   2]
- [  6   3   0   0   0  51   8]
- [ 17   6   7  12   4   6  85]]
-Node Classification on random seed  8222 -> 0.593
-Confusion Matrix:
- [[ 73   1   6   0   4   3  16]
- [  7 118   8   2   6   2   8]
- [ 31  36 132  29  19  26  47]
- [ 13   7   3  99   7   8  14]
- [  1  13   2   1  46   2   4]
- [  4   1   1   2   0  48  10]
- [ 12   7  14   3  11  16  77]]
-Node Classification on random seed  8223 -> 0.585
-Confusion Matrix:
- [[ 68   4   3   2   0  16  12]
- [  4 132   2   7   9   2   1]
- [ 18  29 128  35  30  28  57]
- [ 13   3  11  88   6   9  22]
- [  0   9   2   2  67   0   2]
- [ 10   1   1   2   0  34  10]
- [ 11   4  16   6   8   8  68]]
-Node Classification on random seed  8224 -> 0.632
-Confusion Matrix:
- [[ 80   2   1   1   4  16   2]
- [  4 130   3   2  11   5   4]
- [ 32  21 140  28  30  31  23]
- [ 21   3  11  99   5   8   9]
- [  0   5   2   1  66   2   3]
- [  1   0   2   1   1  55   3]
- [  9   4   7  13  16  21  62]]
-Node Classification on random seed  8225 -> 0.602
-Confusion Matrix:
- [[ 64   2   2  10   1  23   5]
- [  6 103   6   3  26   2   2]
- [ 37  10 149  31  34  53  25]
- [  5   4   6 109  12   8  10]
- [  2   1   2   2  61   1   3]
- [  5   1   2   1   1  44   1]
- [  9   4   7   7   8  18  72]]
-Node Classification on random seed  8226 -> 0.642
-Confusion Matrix:
- [[ 68   0   1  18   8   5  16]
- [  3 124  20   4   2   2   4]
- [ 27  14 167  24  15  22  37]
- [ 12   2  18 102   4   5  10]
- [  3   8   5   3  54   1   2]
- [  4   0   2  10   0  48   2]
- [ 14   4   5   5   8   9  79]]
-Node Classification on random seed  8227 -> 0.627
-Confusion Matrix:
- [[ 79   6  10   6  10   7   1]
- [  3 119   7   7   9   1   3]
- [ 25  15 164  27  24  28  43]
- [ 11   3  28  95   9   3  12]
- [  0   5   3   0  75   2   1]
- [  6   1   3   1   2  35   7]
- [ 12   1  11   4   8   8  60]]
-Node Classification on random seed  8228 -> 0.63
-Confusion Matrix:
- [[ 86   2   3   3   1  11   3]
- [  6 120   3   4  16   2   4]
- [ 29  10 143  50  17  19  42]
- [ 12   5  13 112   3   4  16]
- [  1   6   1   4  55   0   5]
- [  9   1   2   0   0  41   0]
- [ 10   3   5  16   8  21  73]]
-Node Classification on random seed  8229 -> 0.644
-Confusion Matrix:
- [[ 74   3   5   5   2  16   6]
- [  2 124   8   5   9   0   5]
- [ 14  28 153  35  17  22  36]
- [ 11   2   9 118   7   8   6]
- [  1   3   5   3  62   1   6]
- [  3   0   3   1   1  39   6]
- [ 12   5   7  13   6  19  74]]
-Node Classification on random seed  8230 -> 0.633
-Confusion Matrix:
- [[ 78   2   2   6   7   5   5]
- [ 12 116   7   1   2  11   2]
- [ 35  17 147  29  29  17  43]
- [  8   2  17 102   3   6   9]
- [  5   4   5   4  61   2   1]
- [  6   0   1   4   0  43   7]
- [ 21   4   4   6  10   6  86]]
-Node Classification on random seed  8231 -> 0.641
-Confusion Matrix:
- [[ 87   5   5   3   2   6   9]
- [  4 136   4   0   7   2   4]
- [ 31  23 165   9  34  24  22]
- [ 26   9  17  79   6   6  22]
- [  2   9   2   3  59   0   0]
- [  6   2   3   2   2  44   4]
- [  7   5   9   9   5   9  71]]
-Node Classification on random seed  8232 -> 0.591
-Confusion Matrix:
- [[ 76   4   1   5   2   9  16]
- [  7 134   2   1   3   5   3]
- [ 32  22 108  32  52  20  50]
- [  5   1  24  88   3  10  13]
- [  4   6   4   5  64   1   1]
- [  5   2   0   3   0  44  11]
- [ 12   5   6   5   6  11  77]]
-Node Classification on random seed  8233 -> 0.58
-Confusion Matrix:
- [[ 73   6   1   3   4  19  12]
- [  0 131   5   3   4   6   7]
- [ 22  40 115  24  21  34  34]
- [  6   6  21  94  14   8  13]
- [  0  12   3   3  50   1   3]
- [  8   3   0   0   1  54   4]
- [ 10  10  14   7   9  19  63]]
-Node Classification on random seed  8234 -> 0.602
-Confusion Matrix:
- [[ 71   4   5   3   4  11  23]
- [  3 103   4   2   8   4   7]
- [ 15  30 141  24  43  35  32]
- [ 16   5   6 105   9   3  12]
- [  2   4   3   1  67   0   6]
- [  5   2   0   1   2  57   2]
- [  2   2   9  12  11  26  58]]
-Node Classification on random seed  8235 -> 0.568
-Confusion Matrix:
- [[ 70   5   7   3   1  20  15]
- [  6 122   8   5   4   3   5]
- [ 23  16 110  33  42  22  36]
- [ 16   4  17 100   7   6   9]
- [  3   8   4   1  59   0   4]
- [ 12   0   3   2   2  40   3]
- [  9   4  10  15  12  27  67]]
-Node Classification on random seed  8236 -> 0.629
-Confusion Matrix:
- [[ 72   3   4   6   3  15  11]
- [ 10 130   4   4   9   0   3]
- [ 21  15 178  28  16  20  43]
- [  8  10  19  81   3   7  15]
- [  1   4   6   2  56   1   2]
- [  7   5   2   1   1  46   5]
- [ 12   8  13   6   6  12  66]]
-Node Classification on random seed  8237 -> 0.603
-Confusion Matrix:
- [[ 71   2   2   5   1  13   8]
- [  4 129   4   2  11   6   5]
- [ 33  18 154  31  15  22  50]
- [ 14   4  15  85   7   7  20]
- [  3   8   1   4  50   2   3]
- [  7   1   2   0   2  36   4]
- [ 18   3   9   2   8  21  78]]
-Node Classification on random seed  8238 -> 0.619
-Confusion Matrix:
- [[ 64   0   9   9   3   4  22]
- [  6 107  11   7  11   2   5]
- [ 19  15 164  29  13  30  44]
- [  7   4  17 123   9   6  10]
- [  3   3   5   0  62   0   2]
- [  5   2   1   2   3  44   4]
- [  9   2  14  13   3  18  55]]
-Node Classification on random seed  8239 -> 0.67
-Confusion Matrix:
- [[ 75   5   3   2   1  20   4]
- [  2 114   3   5   5   4   5]
- [  9  28 177  33  17  21  35]
- [  5   4  13 108   8   6   7]
- [  0   7   3   3  59   1   1]
- [  5   1   2   1   1  48   8]
- [  6   5  11   4   8  18  89]]
-Node Classification on random seed  8240 -> 0.593
-Confusion Matrix:
- [[ 71   2   3   9   2   4  13]
- [  5 112   8   2   7   4   8]
- [ 24  22 141  40  35  25  37]
- [  3   1  19  91   8   8  16]
- [  4   7   6   0  68   2   6]
- [  8   1   2   4   1  40   3]
- [ 10   5  14   4   8  17  70]]
-Node Classification on random seed  8241 -> 0.649
-Confusion Matrix:
- [[ 79   3   4   6   3   8   6]
- [  6 128   5   4   1   1   0]
- [ 24  19 175  16  17  14  36]
- [ 20   9  18 100   7   1  11]
- [  3  10   6   0  51   1   4]
- [ 10   2   4   0   0  51   6]
- [ 14   3  10   8   9  22  65]]
-Node Classification on random seed  8242 -> 0.604
-Confusion Matrix:
- [[ 72   2   4   9   4  15  10]
- [  6 128   3   1   9   5   9]
- [ 24  15 116  53  19  24  50]
- [  3   2  15 106   8   5  16]
- [  0   2   0   4  63   1   3]
- [  8   3   1   1   1  43   8]
- [ 12   2   6  10   8  15  76]]
-Node Classification on random seed  8243 -> 0.604
-Confusion Matrix:
- [[ 75   7   2   1   3   6  17]
- [  4 105   9   2   9   2  10]
- [ 42  29 130  28  11  35  42]
- [  9   0  17 129   4   4  14]
- [  2  10   6   2  45   1   3]
- [  8   2   3   3   0  50   3]
- [ 13   2   1   8  10  12  70]]
-Node Classification on random seed  8244 -> 0.651
-Confusion Matrix:
- [[ 82   1   3  11   0  12  11]
- [  5 122  10   2  12   9   2]
- [ 18   7 151  27  18  33  29]
- [  3   6  14 109   7  13  11]
- [  2   5   2   3  62   1   2]
- [  3   2   4   2   0  52   6]
- [ 10   1   9   5   7  21  73]]
-Node Classification on random seed  8245 -> 0.631
-Confusion Matrix:
- [[ 72   3   1   3   4  12  12]
- [  1 127   1   0   6   1   4]
- [ 22  26 155  47  16  27  21]
- [  4   2  18 111   4   1  19]
- [  3   8   4   2  62   1   4]
- [  1   4   0   8   2  33   9]
- [ 14  14   8   6  15  11  71]]
-Node Classification on random seed  8246 -> 0.584
-Confusion Matrix:
- [[ 64   3   2   3   1  21  10]
- [  7 136   3   1  10   2   7]
- [ 16  29 128  36  19  35  27]
- [ 26   4  22  82   3   5  27]
- [  4   6  10   3  56   0   4]
- [  6   3   2   2   0  49   3]
- [ 14   4  12   2   7  15  69]]
-Node Classification on random seed  8247 -> 0.59
-Confusion Matrix:
- [[ 78   3   4   3   3   7  10]
- [  2 135   4   5  15   2   3]
- [ 25  15 108  43  30  20  56]
- [ 18   3  16  77   5  15  12]
- [  3   3   2   3  71   3   8]
- [  2   1   4   3   0  49   6]
- [ 13   1   8  13   8  10  72]]
-Node Classification on random seed  8248 -> 0.595
-Confusion Matrix:
- [[ 62   9   4   2   3  17   9]
- [  4 111   8   5   5   4   6]
- [ 31  35 147  46   7  27  42]
- [ 17   1  14 114   0   7   3]
- [  1   1   4   2  52   2   2]
- [ 12   2   0   0   1  47   1]
- [ 19   5  10   9   7  21  62]]
-Node Classification on random seed  8249 -> 0.582
-Confusion Matrix:
- [[ 63   8   3  12   4   7  11]
- [  4 114   3   3  14   4  13]
- [ 15  25 134  45  35  28  35]
- [  4   3  22  96   3   9  25]
- [  0   6   1   1  71   1   2]
- [  3   0   9   3   2  33   5]
- [  7   2   3   2  12  24  71]]
-Node Classification on random seed  8250 -> 0.641
-Confusion Matrix:
- [[ 76   4   6   8   7   8  14]
- [  7 134   4   1   3   2   4]
- [ 20  30 155  29  19  19  41]
- [  9   2  15 107   4   3  11]
- [  1  10   2   3  54   1   4]
- [  7   3   2   1   4  44   5]
- [  8   3  10   3   9  13  71]]
-Node Classification on random seed  8251 -> 0.632
-Confusion Matrix:
- [[ 72   2   4   5   3  13   9]
- [  4 133   8   1   8   1   5]
- [ 19  26 130  24  26  38  56]
- [ 11   0  19 102   4   6  10]
- [  1   6   2   2  60   0   2]
- [  5   1   2   1   1  48   4]
- [  5   5   3  10   6  10  87]]
-Node Classification on random seed  8252 -> 0.656
-Confusion Matrix:
- [[ 86   2   3   5   1   7  10]
- [  6 123   4   2   4   1   2]
- [ 20  19 168  37  20  35  27]
- [ 11   5  12 111   5   3  10]
- [  0   8   6   2  61   0   1]
- [  5   2   3   2   0  33   8]
- [ 11   6  11   7   6  15  74]]
-Node Classification on random seed  8253 -> 0.596
-Confusion Matrix:
- [[ 57   3   1   9   1  17  11]
- [  6 132  10   1   1   1   5]
- [ 38  20 116  27  28  28  48]
- [  4   7  19 107   5   4  13]
- [  0   6   5   3  59   2   4]
- [ 10   0   1   5   1  44   8]
- [  8   3  11   9   7  14  81]]
-Node Classification on random seed  8254 -> 0.623
-Confusion Matrix:
- [[ 55   2   4   6   4  13  24]
- [  6 136   9   2   5   4   3]
- [ 13  20 156  40  21  29  25]
- [ 22   9  11  89   7   2  15]
- [  1   7   2   2  63   1   2]
- [  5   2   5   2   0  41   4]
- [  3   3  10   7   9  16  83]]
-Node Classification on random seed  8255 -> 0.602
-Confusion Matrix:
- [[ 59   3   3   4   5  15  10]
- [  7 130   5   0   6   2   8]
- [ 24  36 145  40  26  13  22]
- [  5   6  19  79  13   6  19]
- [  2  11   4   1  59   0   0]
- [ 11   1   1   1   0  51   4]
- [ 18   9  16   3   9  10  79]]
-Node Classification on random seed  8256 -> 0.635
-Confusion Matrix:
- [[ 83   7   2   5   5   8   2]
- [  6 127   5   3   8   4  10]
- [ 29  28 162  18  24  14  37]
- [  6   6  24  94   5   4  18]
- [  0   5   6   0  62   1   0]
- [  6   1   4   0   3  39   2]
- [ 10   8  14   5   6  16  68]]
-Node Classification on random seed  8257 -> 0.616
-Confusion Matrix:
- [[ 67   2  11   5  11  15  12]
- [  1 109   9   1  16   0   5]
- [ 30  29 143  21  20  19  28]
- [  7   3  16  99   1   7  12]
- [  2  10   1   1  65   2   1]
- [  4   0   2   4   0  51  10]
- [ 12   9  17   5   4  19  82]]
-Node Classification on random seed  8258 -> 0.612
-Confusion Matrix:
- [[ 66   4   4   9   6   9   7]
- [  3 138   6   3  11   3   1]
- [ 22  33 115  47  20  17  37]
- [  8   8  12 113   6   5  11]
- [  1   7   3   2  51   2   2]
- [  2   1   7   1   1  48   8]
- [ 16   8   8  10   8   9  81]]
-Node Classification on random seed  8259 -> 0.629
-Confusion Matrix:
- [[ 71   1   9   1  10  11   2]
- [  3 131   1   3  11   2   3]
- [ 16  21 155  32  20  23  33]
- [  6   7  17 108  13   4  15]
- [  1   6   6   3  50   2   3]
- [  8   4   2   0   1  46   4]
- [ 14   7  15   9   7  15  68]]
-Node Classification on random seed  8260 -> 0.565
-Confusion Matrix:
- [[ 58   3   5   3   4  15  11]
- [ 14 108  16   0  13   7   3]
- [ 16  15 123  34  32  31  55]
- [ 13   4  14 100  14   7  10]
- [  0   6   6   0  59   0   1]
- [  8   2   4   0   2  42  10]
- [ 14   7  15   2  12   7  75]]
-Node Classification on random seed  8261 -> 0.617
-Confusion Matrix:
- [[ 78   6   3   3   5  11   7]
- [  6 137   2   4   4   3   1]
- [ 24  32 128  36  30  26  33]
- [ 10   4  22 104   4   8  15]
- [  2   6   3   4  59   0   1]
- [ 13   0   1   3   1  31   2]
- [ 13   2   9   3  12   9  80]]
-Node Classification on random seed  8262 -> 0.623
-Confusion Matrix:
- [[ 72   4   2   7   0   9  11]
- [  8 118   2   1  15   0   2]
- [ 34  17 151  20  40  14  35]
- [ 24   1  22 114   7   8   5]
- [  2   3   4   2  56   0   2]
- [  8   1   0   1   6  38   9]
- [ 19   1   9   3  10   9  74]]
-Node Classification on random seed  8263 -> 0.632
-Confusion Matrix:
- [[ 77   2   3   1   1   8   4]
- [  3 135  10   6   3   0   4]
- [ 30  42 129  30  28  21  31]
- [ 11   6  13 105   7   9   5]
- [  1   0   4   1  62   4   2]
- [  5   2   2   0   2  51   2]
- [ 10   4  19  11   5  16  73]]
-Node Classification on random seed  8264 -> 0.662
-Confusion Matrix:
- [[ 89   6   1   7   3   8   5]
- [  3 126   6   1   6   1   5]
- [ 32  22 179  20  14  31  25]
- [  5   4  24 103   3   7   9]
- [  3   2   5   0  56   2   3]
- [ 10   0   0   3   2  43   5]
- [ 18   7  11   2   7  10  66]]
-Node Classification on random seed  8265 -> 0.57
-Confusion Matrix:
- [[ 55   1  12  10   3  29  10]
- [  8 125   3   6   4   3   5]
- [ 31  21 133  54  28  31  29]
- [ 16   4  13  93   4  15   8]
- [  2   7   1   3  49   2   1]
- [  1   1   1   4   0  44   7]
- [ 16   2   6   7   6  15  71]]
-Node Classification on random seed  8266 -> 0.626
-Confusion Matrix:
- [[ 74   5   2   4   2   1  10]
- [  4 123   2   4   8   0   8]
- [ 28  14 151  34  19  18  54]
- [ 13   5  14 105   5   5  15]
- [  6   3   3   0  57   3   2]
- [  3   2   6   3   1  45   4]
- [ 13   5  17  11   7  11  71]]
-Node Classification on random seed  8267 -> 0.618
-Confusion Matrix:
- [[ 69   6   1   5   4  16   7]
- [  8 124   9   3   2   3   1]
- [ 13  36 144  57  16  22  32]
- [  7   7  15 113   2   2  14]
- [  2   7   5   0  44   4   4]
- [  2   2   3   1   0  52   5]
- [ 10   6  15  14   4  10  72]]
-Node Classification on random seed  8268 -> 0.641
-Confusion Matrix:
- [[ 73   0   4   2   4   4  16]
- [  1 127   7   1   4   3   4]
- [ 21  26 136  27  33  32  29]
- [ 20   6   5 119   2   4  16]
- [  2   5   2   1  58   0   4]
- [  6   1   2   0   0  51   6]
- [  7   7  10   4  10  21  77]]
-Node Classification on random seed  8269 -> 0.621
-Confusion Matrix:
- [[ 75   2   7   2   2   7  10]
- [  5 128   2   3   8   7   5]
- [ 30  19 157  34  20  22  48]
- [ 13   6  22  95   4   6  11]
- [  2   7   4   3  52   1   0]
- [  3   1   4   1   4  37   7]
- [  5   5  12   2   8  15  77]]
-Node Classification on random seed  8270 -> 0.638
-Confusion Matrix:
- [[ 68   1   6   4   4   8  12]
- [  1 128   8   1   7   1   3]
- [ 28  26 147  21  17  12  60]
- [ 14   6  19 101   5   7  13]
- [  1   4   3   3  67   1   3]
- [ 11   0   3   0   0  50   4]
- [  6   3  10   2  10  14  77]]
-Node Classification on random seed  8271 -> 0.623
-Confusion Matrix:
- [[ 83   3   5   4   2  13   5]
- [  4 133   3   1   3  10   2]
- [ 22  25 143  46  15  29  34]
- [ 14   5  14  94   2   5  11]
- [  4   8   3   7  50   0   4]
- [  6   3   0   3   1  48   8]
- [ 13   8  10   2   3  17  72]]
-Node Classification on random seed  8272 -> 0.609
-Confusion Matrix:
- [[ 65   5   7   6   1  11  14]
- [  6 124  10   4   5   6   3]
- [ 25  17 134  29  47  11  40]
- [  7  10  12 118   4   6   8]
- [  3   5   2   6  59   3   0]
- [ 15   1   2   0   1  37  12]
- [ 20   2   9   8   3   5  72]]
-Node Classification on random seed  8273 -> 0.611
-Confusion Matrix:
- [[ 79   3   1   9   2  11  11]
- [  8 110  15   1  15   5   1]
- [ 26  18 179   7  14  27  50]
- [ 15   7  11  75  10   9  19]
- [  3   6   6   1  55   2   1]
- [  6   2   3   5   0  49   2]
- [ 17   3  13   8   3  13  64]]
-Node Classification on random seed  8274 -> 0.595
-Confusion Matrix:
- [[ 76   2   7   6   6  10   9]
- [  5 122  10   6   8   7   2]
- [ 25  24 129  23  22  18  75]
- [ 10   3  16  99  11   3  11]
- [  2   8   7   1  69   1   1]
- [  6   3   3   5   1  30   7]
- [ 10   3   1   4   5  18  70]]
-Node Classification on random seed  8275 -> 0.593
-Confusion Matrix:
- [[ 60   4   6  10   1   6  13]
- [  8 136   8   3   0   3   3]
- [ 22  51 120  46  27  13  33]
- [ 22   5  28  91   6  14   4]
- [  4   5   3   0  59   0   3]
- [ 10   1   1   0   1  44   2]
- [  5   3  14   2   3  14  83]]
-Node Classification on random seed  8276 -> 0.61
-Confusion Matrix:
- [[ 62   4   2   2   4   8   9]
- [  4 119   8   2  14   2   1]
- [ 25  14 140  46  26  18  40]
- [  9   7  20 100   7   6  12]
- [  2   2   4   7  63   1   4]
- [  4   1   6   0   2  43   7]
- [ 17   4  12   9   4  14  83]]
-Node Classification on random seed  8277 -> 0.62
-Confusion Matrix:
- [[ 81   5   1   5   2  12   4]
- [  3 130  10   1   5   4   0]
- [ 31  24 149  48  32  16  26]
- [ 11   4  26  73   6  10  10]
- [  0   6   1   1  57   2   2]
- [  7   4   1   1   0  49   1]
- [ 14   0  10  12   4  18  81]]
-Node Classification on random seed  8278 -> 0.602
-Confusion Matrix:
- [[ 71   6   1  11   9  11  13]
- [  4 103  12   2  15   2   4]
- [ 38  16 144  25  38  27  32]
- [ 19   1  10 112  11   2   3]
- [  0   4   2   3  64   0   3]
- [  9   0   1   2   1  46   4]
- [  7   6   4  10  15  15  62]]
-Node Classification on random seed  8279 -> 0.634
-Confusion Matrix:
- [[ 86   1   5   6   4   3  10]
- [  3 111   2   2  10   2   6]
- [ 30  26 167  24  19  11  45]
- [ 11   7  22  93   7   5  18]
- [  3   9   5   2  53   1   3]
- [  1   2   0   1   1  34  17]
- [ 11   6  10   6   6   3  90]]
-Node Classification on random seed  8280 -> 0.611
-Confusion Matrix:
- [[ 76   2   9   2   2   8  10]
- [  8 128  13   4   2   0   1]
- [ 31  28 137  39  16  16  42]
- [ 29   2  10  95   1   8  16]
- [  1  11   9   3  54   5   3]
- [  6   0   4   2   0  38  10]
- [  8   3   6   7   2  10  83]]
-Node Classification on random seed  8281 -> 0.592
-Confusion Matrix:
- [[ 70   1   8   5   2   5  16]
- [  6 126   8   2   9   5   8]
- [ 40  30 130  28  30  23  36]
- [  6  10  17 112   3   3  11]
- [  2   9   8   3  55   1   1]
- [  4   0   2   0   1  44   4]
- [  5   3  18   6   3  26  55]]
-Node Classification on random seed  8282 -> 0.633
-Confusion Matrix:
- [[ 69   2  12   3   4  14   2]
- [  5 128   6   1  12   3   3]
- [ 17  11 160  29  26  31  36]
- [  6   5  19 116   2   5   9]
- [  3   2   4   1  61   0   3]
- [  6   2  11   0   3  45   2]
- [ 10   5  12  10  17  13  54]]
-Node Classification on random seed  8283 -> 0.622
-Confusion Matrix:
- [[ 85   3   2   3   1  19   8]
- [  2 132   6   3   4   0   6]
- [ 24  28 117  44  38  23  38]
- [ 13   7   8 111   6   6  10]
- [  3   5   4   1  59   1   0]
- [  4   2   2   1   2  41   4]
- [ 11   5   5   6  10  10  77]]
-Node Classification on random seed  8284 -> 0.591
-Confusion Matrix:
- [[ 70   6  13   9   4   7   9]
- [  0 128   5   3  12   0   2]
- [ 26  22 144  30  24  20  52]
- [ 20   6  16  84   8  12   7]
- [  1   3   6   4  54   0   1]
- [  5   1   2  10   0  44   7]
- [ 12   3  10   9  11  11  67]]
-Node Classification on random seed  8285 -> 0.625
-Confusion Matrix:
- [[ 81   1   9   3   2   6   3]
- [  5 121   4   3   2   2   6]
- [ 34  30 137  30  38  15  39]
- [  7   6  13 105   3   5  10]
- [  2  10   2   2  62   1   2]
- [  8   4   1   1   1  46   6]
- [  9   6   7   8   3  26  73]]
-Node Classification on random seed  8286 -> 0.668
-Confusion Matrix:
- [[ 82   1   1   5   2  13   4]
- [  4 137   7   0   2   0   2]
- [ 32  14 154  30  23  24  34]
- [  9   3   9 104   7   4  18]
- [  2  10   8   3  50   1   3]
- [  8   0   0   2   0  58   1]
- [  7   3   8   5   5  18  83]]
-Node Classification on random seed  8287 -> 0.595
-Confusion Matrix:
- [[ 66   2   5   8  12   6  23]
- [  2 112   7   0   9   1   5]
- [ 11  21 152  31  41  20  60]
- [ 12   8  11  98   8   2  12]
- [  1  11   1   4  53   0   2]
- [  7   3   5   1   5  42   7]
- [  1   4   7  15   5   9  72]]
-Node Classification on random seed  8288 -> 0.613
-Confusion Matrix:
- [[ 72   3   2   6   4  19   7]
- [  2 131   8   3   9   2   4]
- [ 21  18 132  36  34  23  35]
- [  6   2  21 110   1   4   8]
- [  0   4   2   5  59   2   2]
- [  7   3   0   1   7  43   8]
- [  8   2   8   4  16  30  66]]
-Node Classification on random seed  8289 -> 0.628
-Confusion Matrix:
- [[ 68   4   3   3   8  16  12]
- [  0 136   5   3   6   3   5]
- [ 21  22 144  31  12  22  44]
- [ 20   4  18 101   2   1  12]
- [  0   9   7   4  55   0   3]
- [  9   0   2   1   1  43   4]
- [  7   1  13   8   8  18  81]]
-Node Classification on random seed  8290 -> 0.574
-Confusion Matrix:
- [[ 79   2  11   4   7  18   5]
- [  9 108   4   0  20   4   9]
- [ 34  24 116  32  36  14  51]
- [ 28   4   8  91   4   4   6]
- [  0   6   5   0  66   1   1]
- [  6   2   3   3   1  52   2]
- [ 25   4  12   4   2  11  62]]
-Node Classification on random seed  8291 -> 0.636
-Confusion Matrix:
- [[ 63   7   0   8   3  12  13]
- [  8 129   5   7   1   3   2]
- [ 14  35 154  39  23  21  37]
- [ 10   3  11 112   1   6  15]
- [  0   9   2   3  65   2   3]
- [  1   1   3   3   0  42  10]
- [  2   3   6  13   6  13  71]]
-Node Classification on random seed  8292 -> 0.573
-Confusion Matrix:
- [[ 64   1   8   3   4  16  11]
- [  2 112  10   3  11   6   9]
- [ 26  18 127  30  25  32  52]
- [ 31   4  12  96   6   3   9]
- [  1   2   4   1  59   4   5]
- [  6   1   2   1   3  34   9]
- [ 16   3   5   7  10  15  81]]
-Node Classification on random seed  8293 -> 0.619
-Confusion Matrix:
- [[ 85   5   1   7   5  10  13]
- [  5 128   4   2   3   5   5]
- [ 24  21 132  19  20  34  47]
- [  7   6  16  87   2  11  34]
- [  0   7   4   1  67   2   2]
- [  8   0   2   3   2  52   3]
- [  9   0  11   1   5  15  68]]
-Node Classification on random seed  8294 -> 0.616
-Confusion Matrix:
- [[ 76   1   1   8   2  10  14]
- [  9 105   4   8  12   1  10]
- [ 27  27 155  33  17  21  41]
- [ 13   5  10 112   2   6   6]
- [  2   7   9   1  57   1   5]
- [  5   0   2   0   1  43  14]
- [ 12   1   6   9   7  14  68]]
-Node Classification on random seed  8295 -> 0.618
-Confusion Matrix:
- [[ 82   3   7   9   7  12   1]
- [  7 134   5   2  10   4   4]
- [ 27  11 150  20  12  19  35]
- [  4   1  25  94   7  13  14]
- [  5   6   5   0  67   0   6]
- [  7   1   6   5   5  28   7]
- [ 17   4  14   8   8  19  63]]
-Node Classification on random seed  8296 -> 0.619
-Confusion Matrix:
- [[ 76   5   1   1   7   5   8]
- [  4 138   6   4   2   3   1]
- [ 32  30 145  34  18  14  45]
- [ 15   6  11 100  11   3  12]
- [  2   5   6   2  50   4   1]
- [ 15   2   2   1   0  37  10]
- [ 21   7  14   2   4   5  73]]
-Node Classification on random seed  8297 -> 0.549
-Confusion Matrix:
- [[ 68   3   5  13   4   9   5]
- [ 13 121   7   3  10   3   3]
- [ 34  21  99  55  40  29  34]
- [ 13   3  27  89   7   5  12]
- [  1   8   5   2  57   0   8]
- [ 10   0   2   2   0  43   3]
- [ 17   5   5   8   5  12  72]]
-Node Classification on random seed  8298 -> 0.605
-Confusion Matrix:
- [[ 76   2   2   2   6  14   8]
- [  3 103   3   4   8   2   1]
- [ 21  20 139  27  32  40  52]
- [ 11   6  16  99   7  12  12]
- [  0   5   4   1  61   1   1]
- [  3   2   4   0   2  58   7]
- [  6   7   6  11   7  17  69]]
-Node Classification on random seed  8299 -> 0.649
-Confusion Matrix:
- [[ 72   4   4   5   4   8  10]
- [  7 126   3   6   1   1   3]
- [ 31  13 148  37  16  20  42]
- [  8   0  14 117   8   3  14]
- [  2  11   4   0  56   0   3]
- [  3   3   2   5   0  46   5]
- [  9   6   8   8   7  13  84]]
-Node Classification on random seed  8300 -> 0.593
-Confusion Matrix:
- [[ 62   7   6   7   5   4  15]
- [  6  99   7  14  12   0   9]
- [ 22  23 153  33  44  11  39]
- [ 10   8  11  98  10   4   9]
- [  1   3   1   0  64   1   6]
- [  3   9   7   0   0  43   9]
- [  7   7  13  10   7   7  74]]
-Node Classification on random seed  8301 -> 0.645
-Confusion Matrix:
- [[ 74   2   5   1   3  12  11]
- [  2 118   9   2   8   3   4]
- [ 25  19 182  25  21  19  23]
- [ 15   9  22  91   6   5   5]
- [  2   9   6   2  59   1   1]
- [  8   0   4   0   1  49   4]
- [ 12   1  19   5   6  18  72]]
-Node Classification on random seed  8302 -> 0.593
-Confusion Matrix:
- [[ 57   3   9   3   5  16   6]
- [  3 135   1   4  19   6   3]
- [ 19  21 135  21  37  36  38]
- [  8   4  20  90   6   6  17]
- [  1   9   3   3  49   1   5]
- [  3   4   1   7   0  48   4]
- [  9   3   8   1   7  27  79]]
-Node Classification on random seed  8303 -> 0.592
-Confusion Matrix:
- [[ 65   2   3   6   4  10   8]
- [  2 113   4   3   7   4   2]
- [ 43  22 140  40  24  34  21]
- [ 20   6  16 102   3   3  13]
- [  0   7  10   4  57   2   2]
- [  9   3   0   5   0  39   4]
- [ 21   2   9   6   6  18  76]]
-Node Classification on random seed  8304 -> 0.634
-Confusion Matrix:
- [[ 75   5   9   3   4   5  10]
- [  1 122   8   4   6   5   4]
- [ 28  10 154  28  21  30  31]
- [  3   8  16  98   3   5  30]
- [  2   5   3   0  58   2   0]
- [  4   0   4   3   2  48   7]
- [ 15   3  17   5   7  10  79]]
-Node Classification on random seed  8305 -> 0.621
-Confusion Matrix:
- [[ 66   2   3   3   7  13  18]
- [  3 106   3   3  13   1   4]
- [ 19  28 140  39  34   9  53]
- [  7   7  11 116   3   7  10]
- [  0   8   4   0  63   1   1]
- [  2   2   1   4   0  46   9]
- [  7   5   6   8  12   9  84]]
-Node Classification on random seed  8306 -> 0.583
-Confusion Matrix:
- [[ 46   2   1  17   8  10   7]
- [ 11 131   5   2   3   0   0]
- [ 22  13 135  28  31  32  46]
- [  4   1  25  96  11   4  28]
- [  2   9   6   0  53   1   1]
- [ 11   4   3   5   1  52   3]
- [ 14   3   5   4  13  21  70]]
-Node Classification on random seed  8307 -> 0.642
-Confusion Matrix:
- [[ 74   4   4   5   1   1  19]
- [  1 118   8   6   5   3   6]
- [ 23  14 154  41  28  12  40]
- [  8   3  22 105   6   5  17]
- [  2   3   4   2  66   1   1]
- [  8   1   1   1   0  45   9]
- [ 17   2  12   1   3   8  80]]
-Node Classification on random seed  8308 -> 0.627
-Confusion Matrix:
- [[ 78   1   4   6   7  10  11]
- [ 13 103   3   4  16   1   2]
- [ 22  17 159  38  21  20  44]
- [  6   4  10 121   4   4  14]
- [  5   3   2   0  61   2   2]
- [  1   0   2   0   1  49   5]
- [ 10   4   9  15   9  21  56]]
-Node Classification on random seed  8309 -> 0.607
-Confusion Matrix:
- [[ 88   3   3   2   7  16   5]
- [  2 129   7   0   2   0   1]
- [ 30  28 118  29  51  20  37]
- [ 13   4  23 100   4   5  13]
- [  1   3   0   1  61   1   4]
- [ 11   1   2   0   2  36   4]
- [ 15   2   7   6  10  18  75]]
-Node Classification on random seed  8310 -> 0.594
-Confusion Matrix:
- [[ 74   2   6   7   4   7  12]
- [ 10 125   4   2   6   4   5]
- [ 30  21 132  41  28  39  33]
- [ 24   3  16  88   3   3  20]
- [  5   4   1   4  55   1   0]
- [  4   0   2   4   3  51   2]
- [  6   1   7   7   9  16  69]]
-Node Classification on random seed  8311 -> 0.625
-Confusion Matrix:
- [[ 82   2   2   8   3  12   4]
- [  6 132   6   4   4   3   3]
- [  9  22 136  41  30  28  41]
- [ 18   3  21  98   5   5   6]
- [  2   8   2   2  61   1   1]
- [  6   1   3   3   0  45   6]
- [  7   2   6  13   7  19  71]]
-Node Classification on random seed  8312 -> 0.626
-Confusion Matrix:
- [[ 58   2   3   1   2  14  12]
- [  1 122   8   1  10   5   4]
- [ 23  25 182  28  14  19  42]
- [ 10   2  13  93   4   9  23]
- [  0   9   5   1  51   3   5]
- [  2   2  10   0   0  44   8]
- [  9   2  12  10   9  12  76]]
-Node Classification on random seed  8313 -> 0.613
-Confusion Matrix:
- [[ 57   3   2   5   2  13   9]
- [  6 110   4   1  13   3  13]
- [ 27  14 137  37  39  19  45]
- [ 12   3  13 114   2   8  10]
- [  1  10   3   1  56   1   1]
- [  2   2   0   0   3  53   6]
- [ 10   3   7   6   7  21  86]]
-Node Classification on random seed  8314 -> 0.61
-Confusion Matrix:
- [[ 64   2  12   6   3  14   5]
- [  4 145   3   2   7   1   4]
- [ 24  32 133  41  19  22  42]
- [ 13   4   8 109  13   5  12]
- [  1   6   4   2  60   0   1]
- [  4   2   6   6   0  33   9]
- [  9   6  12   1   3  20  66]]
-Node Classification on random seed  8315 -> 0.604
-Confusion Matrix:
- [[ 90   6   3   5   3  10   4]
- [  5 137   8   3   2   1   2]
- [ 29  19 130  50  19  23  55]
- [ 17   5  13  92   3   9  10]
- [  0  10   4   1  63   0   3]
- [  7   1   0   1   3  35   9]
- [  6   3  20  11   3  10  57]]
-Node Classification on random seed  8316 -> 0.587
-Confusion Matrix:
- [[ 76   1   6   3   0   6  11]
- [  6 138   3   2   8   2   1]
- [ 19  23 120  40  74  18  33]
- [  5   6  16  99   8   4  15]
- [  2   9   5   2  61   0   1]
- [  6   2   3   0   0  42   3]
- [ 17   6   9  16  12  10  51]]
-Node Classification on random seed  8317 -> 0.637
-Confusion Matrix:
- [[ 67   1   4   2   5   9  23]
- [  6 129   7   2   9   5   1]
- [ 19  15 175  36  33  11  30]
- [  5   4  19  89  11   7   9]
- [  1   6   6   1  57   2   4]
- [  6   5   2   0   2  42   4]
- [ 10   5  10   7   6  13  78]]
-Node Classification on random seed  8318 -> 0.628
-Confusion Matrix:
- [[ 74   0   8   2   5  11   8]
- [  7 120   8   0   9   2   5]
- [ 23   8 162  27  22  27  48]
- [ 11   2  26  86   5   6  19]
- [  0   7   4   3  64   1   1]
- [  3   0   3   6   0  38   7]
- [ 12   1   3   4  10  18  84]]
-Node Classification on random seed  8319 -> 0.604
-Confusion Matrix:
- [[ 68   5   2   2   6  16  16]
- [  6 109   2   0   6   1  10]
- [ 12  21 147  32  19  18  64]
- [  4   1  20  95   4   8  23]
- [  1   9   7   1  59   0   3]
- [  2   1   3   1   0  47   2]
- [  9   5   7  15  14  18  79]]
-Node Classification on random seed  8320 -> 0.623
-Confusion Matrix:
- [[ 69   1   8   3   3   6  16]
- [ 12  98   7   2   7   0   1]
- [ 20  21 148  39  21  17  47]
- [  3   2  26 115   4   5  17]
- [  4   4   4   3  64   1   3]
- [  4   0   3   8   0  44   3]
- [  8   3   9   3  11  18  85]]
-Node Classification on random seed  8321 -> 0.614
-Confusion Matrix:
- [[ 79   2   3   2   2  11   7]
- [  3 116   5   5  22   2   1]
- [ 33  19 135  33  36  31  31]
- [ 11   5   9 109   9   2   8]
- [  1   4   3   0  63   0   2]
- [  7   1   1   2   4  39   3]
- [ 16   0  12   5  11  22  73]]
-Node Classification on random seed  8322 -> 0.611
-Confusion Matrix:
- [[ 74   1   2   9   5   5  11]
- [  2 104   5   0   6   5   7]
- [ 18  25 170  32  34  24  43]
- [ 15   6  19  79   8   8   8]
- [  2   8   0   2  61   1   5]
- [ 14   0   6   1   3  37   7]
- [ 11   6   6   6   6   7  86]]
-Node Classification on random seed  8323 -> 0.649
-Confusion Matrix:
- [[ 71   4   1   4   3  14   5]
- [  6 130   5   0   6   3   4]
- [ 24  22 150  35  35  15  36]
- [  5   0  18 131   5   7   3]
- [  1   6   2   3  47   1   1]
- [ 10   1   2   2   0  50   0]
- [  9   3  12  13   8  17  70]]
-Node Classification on random seed  8324 -> 0.582
-Confusion Matrix:
- [[ 66   3   6   5   2   9  16]
- [  4 141   7   2   2   8   0]
- [ 19  22 112  43  25  39  50]
- [ 14   0  15  78   3  16  11]
- [  1  10   1   2  62   2   2]
- [  7   2   2   4   1  42   2]
- [ 20   3   2  17   5  14  81]]
-Node Classification on random seed  8325 -> 0.627
-Confusion Matrix:
- [[ 72   3   3   2   2  14   4]
- [  6 127   8   2  11   1   0]
- [ 30  21 136  36  38  23  25]
- [  6   4  12 120   5   6  16]
- [  2  12   5   1  56   4   2]
- [ 12   3   0   2   0  43   5]
- [ 19   2   7   5   8   6  73]]
-Node Classification on random seed  8326 -> 0.62
-Confusion Matrix:
- [[ 62   0   4   3   5   4  22]
- [ 10 112   7   1  18   1   2]
- [ 37  14 140  41  16  17  46]
- [ 14   3  11 115   5   4  15]
- [  3   7   5   1  60   0   2]
- [  9   1   1   3   2  46   2]
- [ 17   3   6   7   4   7  85]]
-Node Classification on random seed  8327 -> 0.609
-Confusion Matrix:
- [[ 64   0   0   9   7   4  22]
- [  3 140   9   0   7   2   1]
- [ 20  22 120  41  30  36  27]
- [ 19  11   4  94   9   5  21]
- [  1   7   4   1  69   0   1]
- [ 10   3   0   0   3  43   6]
- [ 12   4  13   3  12   2  79]]
-Node Classification on random seed  8328 -> 0.622
-Confusion Matrix:
- [[ 73   1   3  10   4  24   4]
- [  3 109   6   3  10   4  12]
- [ 27  24 143  46  21  24  25]
- [  7   3  19 100   2   8   8]
- [  3   6   5   0  64   2   3]
- [  2   3   1   3   0  50   1]
- [ 11   1  10   4   4  21  83]]
-Node Classification on random seed  8329 -> 0.637
-Confusion Matrix:
- [[ 81  14   8   6   4  11   4]
- [  8 112   4   4  11   4   1]
- [ 22  22 143  37  20  24  35]
- [  9   3  15 121   3   6  10]
- [  1   4   8   0  65   1   4]
- [  2   0   2   0   0  47   6]
- [ 12   2  12   3   3  18  68]]
-Node Classification on random seed  8330 -> 0.635
-Confusion Matrix:
- [[ 57   4   6   6   5   5  14]
- [  3 131   2   3   4   4   2]
- [ 17  27 166  45  32  15  50]
- [ 12   5  18 106   3   6  12]
- [  1   5   2   1  66   0   4]
- [  1   3   4   1   1  44   6]
- [  6   2  12   4   5   7  65]]
-Node Classification on random seed  8331 -> 0.629
-Confusion Matrix:
- [[ 78   8   5  10   2  14   8]
- [  7 120  10   3   5   3   7]
- [ 20   7 135  59  40  18  36]
- [  9   2   9 116   5   6   6]
- [  0   6   1   1  62   5   1]
- [  2   0   0   3   0  46   8]
- [  9   2   5  12   3  14  72]]
-Node Classification on random seed  8332 -> 0.616
-Confusion Matrix:
- [[ 71   2   6  14   4  11   7]
- [  7 124   2   2   5   2   3]
- [ 35  25 126  23  33  21  40]
- [  6   5  26 115  12   1   9]
- [  1   9   3   1  70   3   2]
- [  3   1   0   2   0  32   4]
- [  8   3   8   7   4  24  78]]
-Node Classification on random seed  8333 -> 0.575
-Confusion Matrix:
- [[ 70   5   4   5   1   5   2]
- [  5 113  10   9   9   6   4]
- [ 58  21 119  43  24  26  43]
- [ 16   3   9 104  15   4   1]
- [  2   2   3   4  49   0   3]
- [ 13   1   2   0   1  49   1]
- [ 33   2   6   9   6   9  71]]
-Node Classification on random seed  8334 -> 0.592
-Confusion Matrix:
- [[ 52   5  10   9   4   9  19]
- [ 10 118   4   4   7   9   8]
- [ 25  18 100  46  55  26  34]
- [  4   3  14 134   3   3   4]
- [  0   5   2   1  74   1   2]
- [  6   2   0   4   0  46   6]
- [ 11   3  10  10   3   9  68]]
-Node Classification on random seed  8335 -> 0.591
-Confusion Matrix:
- [[ 75   0   4   7   6  13   3]
- [ 15 115   6   3  12   2   6]
- [ 28  12 125  43  45  30  34]
- [ 14   0  15 117   4   6   3]
- [  5   5   2   1  57   5   0]
- [  7   2   2   3   0  40   6]
- [ 21   4   9   4  10  12  62]]
-Node Classification on random seed  8336 -> 0.623
-Confusion Matrix:
- [[ 83   0   3   0   5  12  10]
- [ 14 151   3   1   5   2   8]
- [ 29  29 142  28  33  22  36]
- [  8   3   9  93   6   4  10]
- [  2   5   2   2  53   2   5]
- [  4   1   1   0   5  39   4]
- [  5   1  22   7   9  20  62]]
-Node Classification on random seed  8337 -> 0.593
-Confusion Matrix:
- [[ 83   6   4   6   3   5   5]
- [  6 138   3   6   4   2   0]
- [ 14  44 108  53  44  16  32]
- [ 16   3  13  94   8   6  15]
- [  1  10   2   1  52   0   2]
- [  7   0   3   2   3  54   2]
- [ 14   2  19   2  10  13  64]]
-Node Classification on random seed  8338 -> 0.616
-Confusion Matrix:
- [[ 66   0   4   4   4  13   8]
- [  4 140   3   1   4   4   2]
- [ 36  23 161  38  26  11  31]
- [ 17   3  12  90  10  14  14]
- [  4  13   1   2  54   1   2]
- [  4   0   2   2   1  45   8]
- [ 13   3   3  14   4  21  60]]
-Node Classification on random seed  8339 -> 0.624
-Confusion Matrix:
- [[ 71   2  10   5   2   7  13]
- [  7 128   8   4  10   0   4]
- [ 21  30 163  28  30  19  24]
- [ 25   3  14  86   6   9  13]
- [  3   4   5   0  65   0   1]
- [  2   0   2   0   0  44   7]
- [ 12   2   7   2   7  28  67]]
-Node Classification on random seed  8340 -> 0.6
-Confusion Matrix:
- [[ 59   1   1   3   4   8  23]
- [  8 129   7   3   4   3   3]
- [ 18  23 136  51  15  21  44]
- [  9   5   7 103  15   9  12]
- [  1   9   8   1  56   4   3]
- [  1   1   9   0   1  37   9]
- [  9   4  17   7   4  15  80]]
-Node Classification on random seed  8341 -> 0.616
-Confusion Matrix:
- [[ 57   1   1   3   9  27   0]
- [  5 123   5   3  12   3   4]
- [ 32  18 128  36  43  18  30]
- [ 15   8  16 105   9   4   7]
- [  3   6   1   1  65   2   4]
- [  1   1   2   6   0  52   3]
- [  7   2   9   7   7  13  86]]
-Node Classification on random seed  8342 -> 0.631
-Confusion Matrix:
- [[ 77   6   4   2   3   4   2]
- [  4 129   3   2  10   7   2]
- [ 26  10 155  33  18  26  56]
- [ 12   2  21 100   2  18   6]
- [  1  10   4   1  56   1   1]
- [  5   1   0   1   1  53   5]
- [  4   4  13   6   6  26  61]]
-Node Classification on random seed  8343 -> 0.635
-Confusion Matrix:
- [[ 67   2   3   1   3   9  13]
- [  1 129   9   0   6   5   5]
- [ 16  20 159  32  25  21  44]
- [ 11   3  15  96   5   9  16]
- [  1   6   8   1  63   0   3]
- [  3   1   0   3   1  40   5]
- [ 16   6   7   8   4  18  81]]
-Node Classification on random seed  8344 -> 0.592
-Confusion Matrix:
- [[ 60   2   9  12   5  11  16]
- [  0 123  10   5  12   3   7]
- [ 30  23 136  23  24  14  38]
- [  8   8  16  95  12   7  10]
- [  2   5   2   2  62   3   2]
- [  2   4   2   1   3  44   5]
- [ 21  10   5  15   6  13  72]]
-Node Classification on random seed  8345 -> 0.613
-Confusion Matrix:
- [[ 70   1   4   2   2  12  10]
- [  5 123  16   5   8   5   1]
- [ 19  14 138  31  17  26  63]
- [ 11   6  21  92   5   6  17]
- [  2   3   6   0  62   4   2]
- [  3   3   5   1   1  46   6]
- [  9   2   5   2   7  19  82]]
-Node Classification on random seed  8346 -> 0.61
-Confusion Matrix:
- [[ 60   3   8   4   3   8  19]
- [  4 117   8   1  21   1   2]
- [ 17   8 149  30  43  20  42]
- [  9   3  21 102   4   3  17]
- [  2   3   8   2  59   1   3]
- [  8   2   2   1   2  44   9]
- [  7   1  10  18   3   9  79]]
-Node Classification on random seed  8347 -> 0.626
-Confusion Matrix:
- [[ 65   5   5   0   2  12  11]
- [  4 129   5   3   7   4   4]
- [ 33  22 146  27  17  28  41]
- [ 15   2  12 110  12  10   3]
- [  1   5   5   0  67   1   1]
- [  1   3   1   5   1  49   3]
- [ 15   4   6   5  11  22  60]]
-Node Classification on random seed  8348 -> 0.632
-Confusion Matrix:
- [[ 64   3   5   9   3   4   7]
- [  1 140  11   3   5   0   3]
- [ 32  26 147  31  27  20  46]
- [  9   3   9 104   2   2  14]
- [  1   6  10   0  57   0   2]
- [  9   1   1   3   2  37   3]
- [ 18   3  11   4   6  13  83]]
-Node Classification on random seed  8349 -> 0.559
-Confusion Matrix:
- [[ 55   2   7   5   4   8   9]
- [  8 134   5   4   5   2  10]
- [ 27  26 102  57  30  15  53]
- [ 31   3  23  70  14   5   7]
- [  0   8   2   1  58   1   2]
- [  5   2   1   4   0  49   3]
- [ 12   4   5   8   5  18  91]]
-Node Classification on random seed  8350 -> 0.587
-Confusion Matrix:
- [[ 61   2   9   2   5  12  12]
- [  4 115  13   4   9  14   4]
- [ 34   6 126  33  47  26  43]
- [ 11   2  18 100   6   4   5]
- [  1   7   2   0  67   4   1]
- [  8   1   1   0   1  45   9]
- [ 13   4  14   5   5  12  73]]
-Node Classification on random seed  8351 -> 0.619
-Confusion Matrix:
- [[ 77   3   6   5   3   7  14]
- [  6 124   8   2   5   3   3]
- [ 16  26 141  44  32  13  30]
- [ 12   5  21  80   8  13  16]
- [  1   5   4   2  71   1   1]
- [  4   0   5   5   0  47   6]
- [ 19   1   9   4   9   4  79]]
-Node Classification on random seed  8352 -> 0.672
-Confusion Matrix:
- [[ 82   3   1   5   3   3  10]
- [  4 141   5   5   4   2   2]
- [ 30  34 146  25  17  24  18]
- [ 13   2   8 112   2   5  12]
- [  2   3   3   0  73   0   2]
- [  9   0   4   1   0  40  13]
- [  8   2  20   6   7  11  78]]
-Node Classification on random seed  8353 -> 0.611
-Confusion Matrix:
- [[ 65   3   4   1   5  10   6]
- [  7 132   3   3   7   7   8]
- [ 38  20 129  38  47  26  24]
- [ 12   1  12  99   8   5  16]
- [  0   4   1   4  68   2   2]
- [  2   1   1   0   1  40   1]
- [ 16   3  11   4   7  18  78]]
-Node Classification on random seed  8354 -> 0.598
-Confusion Matrix:
- [[ 84   3   5   2   3   4  16]
- [  6 133   7   4   1   2   1]
- [ 17  32 118  25  55  15  41]
- [ 17   5  18  96   4   4  13]
- [  0   5   3   4  58   0   4]
- [  5   1   0   0   0  49   4]
- [  9   8   6  21  19  13  60]]
-Node Classification on random seed  8355 -> 0.621
-Confusion Matrix:
- [[ 70   8   5   8   1  14  12]
- [  3 135   4   2  14   2   5]
- [ 28  30 143  23  36  19  40]
- [ 10  12  14  89   4   1  10]
- [  2   4   3   1  66   2   4]
- [  1   1   1   2   5  45   4]
- [  8   6   5  10   5  10  73]]
-Node Classification on random seed  8356 -> 0.609
-Confusion Matrix:
- [[ 63   3   4  12   4   7  17]
- [  1 129   3  10   9   2   3]
- [ 35  33 138  16  28  21  46]
- [  3   8  21 104   2   7   9]
- [  1   1   3   4  56   0   2]
- [  6   4   2   9   0  45   4]
- [  6   4   9  10   3  19  74]]
-Node Classification on random seed  8357 -> 0.639
-Confusion Matrix:
- [[ 85   0   3   7   4  11   8]
- [  4 110   6   6   9   0   1]
- [ 22  22 150  36  34  20  33]
- [  9   0  19 107   2   4  11]
- [  2   9   7   0  58   0   2]
- [  8   1   1   4   0  45   5]
- [  7   2  12   3   7  20  84]]
-Node Classification on random seed  8358 -> 0.626
-Confusion Matrix:
- [[ 67   2   4   5   8  10   9]
- [  1 112  11   3  14   6   2]
- [ 25  37 152  20  24   9  41]
- [  5   1  13 122   3  13   8]
- [  2   5   4   5  54   4   3]
- [  4   1   6   2   0  39   8]
- [  8   2  17  17   3   9  80]]
-Node Classification on random seed  8359 -> 0.617
-Confusion Matrix:
- [[ 81   3   3   4   2   5  12]
- [  4 144   7  10   5   1   5]
- [ 29  27 141  30  17   5  65]
- [ 18   1   7  86  11   7   2]
- [  1   4   8   2  61   1   1]
- [  7   4   1   0   0  44   5]
- [ 14   3  13   7  12  20  60]]
-Node Classification on random seed  8360 -> 0.572
-Confusion Matrix:
- [[ 56   4   5   1   3  28   8]
- [  3 119  16   6   1   6   3]
- [ 25  23 107  38  37  29  36]
- [ 14   3  22 101   5   7  19]
- [  5   1   1   0  55   2   4]
- [  7   0   2   2   1  51   0]
- [  8   4  10   5  14  20  83]]
-Node Classification on random seed  8361 -> 0.621
-Confusion Matrix:
- [[ 70   3   1   8   2  14   8]
- [  8 134  13   3   5   2   1]
- [ 14  19 146  35  16  35  42]
- [ 16   7   9  91  13   4   4]
- [  2   8   4   0  63   2   1]
- [  1   1   2   0   1  45   5]
- [  4   4   6  13   4  39  72]]
-Node Classification on random seed  8362 -> 0.63
-Confusion Matrix:
- [[ 83  10   5   5   4   3   4]
- [  0 130   8   4   5   0   7]
- [ 34  16 120  35  18  18  53]
- [ 15   7   9 118   2   5   6]
- [  0   9   1   1  56   1   3]
- [  7   5   5   0   0  38  10]
- [ 11   7  11  13   5   8  85]]
-Node Classification on random seed  8363 -> 0.612
-Confusion Matrix:
- [[ 58   5   7  10   1  15   8]
- [  5 128   5   3   4   1   4]
- [ 26  22 130  44  19  19  44]
- [ 14   7  10 100  10  14   9]
- [  0   6   1   3  66   1   2]
- [  4   1   5   2   0  50   7]
- [ 12   2  11  16   5   4  80]]
-Node Classification on random seed  8364 -> 0.62
-Confusion Matrix:
- [[ 69   2   1   8   5   5  10]
- [  3 113   6   2  14   0   3]
- [ 28  24 146  27  33  14  56]
- [ 15  11  13 108   2   3  15]
- [  0   5   6   3  67   1   1]
- [  8   1   2   1   0  48   5]
- [ 15   0   8   8   4  12  69]]
-Node Classification on random seed  8365 -> 0.616
-Confusion Matrix:
- [[ 59   7   1   2   5  12  15]
- [  1 116   1   3  23   4   3]
- [ 24  11 152  22  38  22  41]
- [ 13   6  17 101  12   6   6]
- [  3   4   3   1  70   0   1]
- [  9   1   4   1   2  36   9]
- [ 12   5   8   5   6  15  82]]
-Node Classification on random seed  8366 -> 0.641
-Confusion Matrix:
- [[ 78   4   0   6   3  15   3]
- [  5 124  11   2   8   0   3]
- [ 21  15 138  57  34  14  18]
- [  8   7  18 105   3   4  14]
- [  3   1   3   1  66   2   3]
- [  3   1   4   2   0  49   0]
- [ 20   3  16   5   3  16  81]]
-Node Classification on random seed  8367 -> 0.615
-Confusion Matrix:
- [[ 62   5   1  11   4   6  10]
- [  4 126   5   7   3   4   5]
- [ 23  14 146  29  29  32  38]
- [  8   3  10  94   5   9  18]
- [  0   9   7   2  59   1   4]
- [  5   1   3   3   0  46   7]
- [ 18   2   8   6  13  13  82]]
-Node Classification on random seed  8368 -> 0.614
-Confusion Matrix:
- [[ 68   1   1   1   3   3  19]
- [ 19 119   5   4  13   3   2]
- [ 24  11 126  41  42  32  30]
- [  7   3  10 109   7   9  17]
- [  0   7   5   2  67   1   0]
- [  9   2   0   0   1  50   4]
- [ 13   1  18   1   5  10  75]]
-Node Classification on random seed  8369 -> 0.58
-Confusion Matrix:
- [[ 71   1   3   9   4  12   9]
- [  9 125   5   3  10   2   5]
- [ 16  14 127  46  35   9  49]
- [ 12   7  10 100  20   7  14]
- [  2  13   1   2  50   1   3]
- [ 15   1   1   6   0  33   5]
- [ 13   4  13  11   9   9  74]]
-Node Classification on random seed  8370 -> 0.607
-Confusion Matrix:
- [[ 66   4   7   6   6   4  16]
- [  6 122   6   6  12   1   4]
- [ 30  18 157  31  18  26  42]
- [ 11   4   8  92   5  10  14]
- [  2   5   4   0  59   0   3]
- [  5   3   0   3   0  35  13]
- [  9   3   8   9   7  24  76]]
-Node Classification on random seed  8371 -> 0.62
-Confusion Matrix:
- [[ 74   2   1   6   1   6  18]
- [  7 123   2   7   3   0   8]
- [ 34  18 148  20  30  20  39]
- [ 17   8   6  83   6   3  20]
- [  3   8   5   0  61   1   5]
- [  7   1   4   2   1  49   3]
- [  4   9   5  11  10  19  82]]
-Node Classification on random seed  8372 -> 0.565
-Confusion Matrix:
- [[ 56   3  12   7   3  10   9]
- [  0 129   5   1  11   5   1]
- [ 14  21 116  37  44  16  67]
- [ 23   5  14  80   6   3  17]
- [  2   6   3   0  68   0   2]
- [  7   2   2   2   1  43   8]
- [ 11   8  11   8  12  16  73]]
-Node Classification on random seed  8373 -> 0.624
-Confusion Matrix:
- [[ 67   5   6   6   3  10   5]
- [  4 147   4   1   4   3   3]
- [ 29  29 140  46  25  17  49]
- [ 11   8  15  88   3  11   4]
- [  1   9   3   2  56   1   1]
- [  6   2   0   0   0  49   3]
- [ 15   3  15   3   4   7  77]]
-Node Classification on random seed  8374 -> 0.575
-Confusion Matrix:
- [[ 74   1   3   3   1  11  14]
- [  3 130   8   6   4   3  10]
- [ 37  26  87  56  18  34  42]
- [ 16   4   6 110   8   3   8]
- [  1   6   3   0  66   0   3]
- [  3   1   2   1   1  39   7]
- [ 11   3  15   9  10  24  69]]
-Node Classification on random seed  8375 -> 0.584
-Confusion Matrix:
- [[ 76   3   7   2   4  12  12]
- [  8 127   4   2  10   3  11]
- [ 21  31 114  27  31  11  79]
- [  9   4  16  87   5   4  17]
- [  1  13   1   0  61   0   4]
- [  7   3   2   2   0  39   2]
- [  4   7  12   6   7  12  80]]
-Node Classification on random seed  8376 -> 0.639
-Confusion Matrix:
- [[ 85   3   2   3   3  10   5]
- [  2 126   0   1  11   2   8]
- [ 21  25 139  41  22  26  44]
- [  7   5  13 100   5   9   8]
- [  2  10   3   1  66   0   4]
- [  5   1   4   4   1  44   4]
- [ 12   4   7  12   3   8  79]]
-Node Classification on random seed  8377 -> 0.608
-Confusion Matrix:
- [[ 56   3   8   7   6  14   7]
- [  2 143   9   4   4   7   3]
- [ 31  24 123  41  31  22  29]
- [ 21   3  12 109   7   7  13]
- [  1   4   0   2  59   0   3]
- [  8   1   0   5   0  44   4]
- [  9   1   7   4   7  21  74]]
-Node Classification on random seed  8378 -> 0.612
-Confusion Matrix:
- [[ 48  12  11  15   5  20   2]
- [  7 122   1   0  10   3   2]
- [ 33  20 156  28  30  23  38]
- [  6   6  22 109   2   5  10]
- [  1   2   7   0  50   0   4]
- [  2   0   2   1   0  50   5]
- [ 17   2  15   4   3  12  77]]
-Node Classification on random seed  8379 -> 0.625
-Confusion Matrix:
- [[ 82   7   1   0   2  13  12]
- [  7 124   4   1   5   2   0]
- [ 16   5 143  42  18  26  51]
- [  6   6  17 115   7   7  12]
- [  2   5   4   0  55   0   4]
- [  5   2   5   2   0  46   2]
- [ 12   5   3   8  10  39  60]]
-Node Classification on random seed  8380 -> 0.583
-Confusion Matrix:
- [[ 57   5   3  13   2  30   3]
- [  3 116   7   5  10   5   9]
- [ 16  16 138  41  40  31  17]
- [  7   3  34 106   5   6   9]
- [  0   5   2   3  66   2   4]
- [  1   1   3   5   3  42   2]
- [  3   0   8  18  11  26  58]]
-Node Classification on random seed  8381 -> 0.594
-Confusion Matrix:
- [[ 60   2  13   8   3  12   3]
- [  9 120   3   1   6   1   5]
- [ 16  29 140  39  47  27  35]
- [  8   6  12 112   2   7  15]
- [  0   9   6   1  58   1   4]
- [  8   0   3   1   1  40   0]
- [  8   9  15  10   5  16  64]]
-Node Classification on random seed  8382 -> 0.584
-Confusion Matrix:
- [[ 73   2   3   2   5   5   9]
- [  7 139   2   4   8   2   3]
- [ 48  27 113  23  46  26  27]
- [ 15   7  11  92   4  10  17]
- [  3   4   9   8  55   1   1]
- [ 12   0   3   3   3  40   1]
- [ 11   4  13  13   2  12  72]]
-Node Classification on random seed  8383 -> 0.598
-Confusion Matrix:
- [[ 64   5   8   5   4  15  10]
- [  3 130   8   4   1   2   9]
- [ 20  35 153  38  24  15  33]
- [ 17   8  15  73   7  18  15]
- [  0   9   5   1  64   1   3]
- [  6   0   3   0   2  41   3]
- [  9   4  12   6   5  14  73]]
-Node Classification on random seed  8384 -> 0.611
-Confusion Matrix:
- [[ 75   2  11   1   0  26   6]
- [  0 131   6   4   6   3   2]
- [ 19  32 134  34  24  35  31]
- [ 13   3  11 103   9  10  17]
- [  0   9   7   3  48   2   5]
- [  6   1   2   0   0  56   2]
- [  7   4  12   3   5  16  64]]
-Node Classification on random seed  8385 -> 0.63
-Confusion Matrix:
- [[ 71   2   7   5   6  21   4]
- [  3 135   1   1   3   0   5]
- [ 13  19 139  41  37  24  30]
- [  7   3   8  94   8   4  28]
- [  0   6   5   3  64   1   4]
- [  2   3   3   4   8  39  12]
- [  6   2   4   8   7  12  88]]
-Node Classification on random seed  8386 -> 0.63
-Confusion Matrix:
- [[ 73   1   4   1   1  14  11]
- [  3 129  10   5   4   2   4]
- [ 30  25 145  36  24  22  50]
- [ 11   2  14 103   3   6   9]
- [  0  10   1   1  58   0   1]
- [  2   1   7   1   0  52   3]
- [ 13   1   6  10   2  19  70]]
-Node Classification on random seed  8387 -> 0.615
-Confusion Matrix:
- [[ 74   3   4   5   8   9  13]
- [  3 132   6   5   2   1   3]
- [ 25  15 140  27  35  28  35]
- [ 16   6  16 106  15   6  10]
- [  2   6   3   6  51   1   2]
- [  4   1   1   0   1  45   8]
- [ 13   2   6  10   5  18  67]]
-Node Classification on random seed  8388 -> 0.639
-Confusion Matrix:
- [[100   0   0  13   2   2   4]
- [  1 131   4   1   4   0   7]
- [ 23  18 155  39  24   8  36]
- [ 29   2  24  77  10   2   8]
- [  1   4   4   2  60   1   5]
- [  8   0   1   8   1  35   6]
- [ 12   3  10  12   5  17  81]]
-Node Classification on random seed  8389 -> 0.583
-Confusion Matrix:
- [[ 79   2   5   8   4   7   8]
- [  5 132   6   1   6   4   9]
- [ 30  19 102  53  42  12  54]
- [ 10   5  16  88   1   5  15]
- [  0   8   1   2  64   1   0]
- [  6   3   5   1   0  42   5]
- [ 10   3  10  11  15   9  76]]
-Node Classification on random seed  8390 -> 0.613
-Confusion Matrix:
- [[ 56   1   9  15   3   8   4]
- [  3 145   1   5   4   1   3]
- [ 25  23 142  35  17  21  48]
- [  7   2  25  99   4   5  26]
- [  5   5   3   2  54   0   2]
- [  8   2   2   5   3  43   5]
- [ 11   3   9   5   4  18  74]]
-Node Classification on random seed  8391 -> 0.643
-Confusion Matrix:
- [[ 52   1   4   1   2  14  22]
- [  3 136   5   0   5   1   6]
- [ 24  17 162  29  19  19  39]
- [ 10   4  14 105   1   2  21]
- [  1   7  11   6  64   0   3]
- [  8   1   1   2   2  43   6]
- [  6   3   5   7   5  20  81]]
-Node Classification on random seed  8392 -> 0.629
-Confusion Matrix:
- [[ 73   1   2   4   7  11   6]
- [  4 125   8   1   9   1   7]
- [ 10  19 143  30  47  20  32]
- [ 12   0  24 100   5   4  13]
- [  1   6   5   1  58   2   3]
- [  3   2   0   3   0  47   2]
- [ 14   6  10   7  12  17  83]]
-Node Classification on random seed  8393 -> 0.611
-Confusion Matrix:
- [[ 74   6   3  10   2   7   1]
- [  2 113   2   3  11   3   6]
- [ 13  23 139  47  28  36  27]
- [ 10   4  10 109   7   3  17]
- [  2   4   7   0  61   1   3]
- [  8   2   2   2   3  42   1]
- [ 17   0  14  12   4  26  73]]
-Node Classification on random seed  8394 -> 0.593
-Confusion Matrix:
- [[ 81   2   6   2   6   9   6]
- [  7 122   8   3   9   2   4]
- [ 26  18 138  24  29  36  50]
- [ 13   1  19  99   6   6  12]
- [  3   2   2   2  41   6   2]
- [ 11   2   4   0   1  49   4]
- [ 24   7  10   3   7  13  63]]
-Node Classification on random seed  8395 -> 0.587
-Confusion Matrix:
- [[ 62   0   5   9   4   5  14]
- [  3 125   4   3   7   7  10]
- [ 42  23 119  31  39  21  49]
- [ 13   4  10 102   6   6  15]
- [  1   3   0   4  53   0   2]
- [  4   1   1   9   1  40   7]
- [ 11   3   7  11   8  10  86]]
-Node Classification on random seed  8396 -> 0.624
-Confusion Matrix:
- [[ 57   2   3   3   7  23   6]
- [  4 133   5   2  17   0   6]
- [  8  10 153  40  23  40  25]
- [ 10   2  11 104  10  15   8]
- [  0   3   2   4  72   3   3]
- [  3   2   2   3   2  48   3]
- [ 18   4   8  13   8  15  57]]
-Node Classification on random seed  8397 -> 0.6
-Confusion Matrix:
- [[ 60   4   6  16  14   8   5]
- [  3 134   5   1   8   3   5]
- [ 17  19 155  32  24  33  33]
- [ 16   1  23  91  11   5  18]
- [  2   3  11   0  51   1   3]
- [  0   0   0   3   2  41   6]
- [  8   4   8  10  13  16  68]]
-Node Classification on random seed  8398 -> 0.624
-Confusion Matrix:
- [[ 73   2   1   1  10   6   9]
- [  4 122   7   0   9   5   7]
- [ 19  16 142  41  33  21  31]
- [ 16   2  16 108   4   6  11]
- [  2   6   3   1  56   2   3]
- [  2   1   4   2   0  46   8]
- [  9   0  17  11   9  19  77]]
-Node Classification on random seed  8399 -> 0.636
-Confusion Matrix:
- [[ 71   1   8  13   2   4   5]
- [  7 117   7   3  13   3   1]
- [ 35  13 161  25  18  15  46]
- [ 18   1  14 104   3   5  17]
- [  4   5   6   1  60   0   3]
- [  5   1   6   1   0  50   0]
- [ 16   0   7   7   8  17  73]]
-Node Classification on random seed  8400 -> 0.582
-Confusion Matrix:
- [[ 62   4  10   7   6  12  10]
- [ 12 120   3   5  10   2   4]
- [ 21  23 140  16  22  29  63]
- [ 15   7  14  88   7   6  16]
- [  2   3   8   0  65   2   1]
- [  4   0   1   6   0  34  11]
- [ 19   4   7   8   2  16  73]]
-Node Classification on random seed  8401 -> 0.623
-Confusion Matrix:
- [[ 84   1   4   3   2  16   3]
- [  1 141   8   1   2   3   3]
- [ 22  33 114  37  28  24  45]
- [ 11   6  12 105   5   5  14]
- [  2   9   2   2  61   0   2]
- [  3   2   1   0   0  41  11]
- [  3   5  10   5   6  25  77]]
-Node Classification on random seed  8402 -> 0.616
-Confusion Matrix:
- [[ 69   3  10   2   5   6  12]
- [  7 136   5   4   4   1   1]
- [ 32  32 127  30  12  25  44]
- [ 19   3  15 107   0   8  13]
- [  1   9   2   3  53   5   0]
- [  7   6   3   2   3  42   3]
- [ 11   4   8   7   7  10  82]]
-Node Classification on random seed  8403 -> 0.596
-Confusion Matrix:
- [[ 86   1   1   9   5   4   8]
- [  2 122  12   3   4  10   2]
- [ 25  15 131  21  47  23  38]
- [  6  10  21  83   8  19  12]
- [  1   8   1   1  61   3   1]
- [  5   0   4   0   4  49   5]
- [ 21   2  11  14   7  10  64]]
-Node Classification on random seed  8404 -> 0.601
-Confusion Matrix:
- [[ 70   0   9   5   8   8  14]
- [  5 122   7   3   9   2   6]
- [ 49  16 114  32  32  22  41]
- [ 15   2   6 117   6   4   9]
- [  1   5   4   0  56   2   2]
- [  5   1   1   1   0  46  11]
- [ 16   4   6   9   7  14  76]]
-Node Classification on random seed  8405 -> 0.652
-Confusion Matrix:
- [[ 81   3   4   6   2   5   8]
- [  4 129   4   0  15   2   1]
- [ 29  14 174  25  12  33  31]
- [  9   6  17  91   6   8  14]
- [  1   5   4   2  73   1   0]
- [  5   3   2   3   3  38   8]
- [ 13   6   8  10  13   3  66]]
-Node Classification on random seed  8406 -> 0.633
-Confusion Matrix:
- [[ 74   2   1   7   3   3  16]
- [  9 126  10   5   3   0   2]
- [ 16  18 154  45  27  26  34]
- [ 22   2  18 100   1   7  12]
- [  1  11   1   1  52   4   1]
- [  4   0   1   0   0  42  10]
- [  9   3  13  10   1   8  85]]
-Node Classification on random seed  8407 -> 0.636
-Confusion Matrix:
- [[ 81   1   2   3   4   5  11]
- [  8 118   4   0   5   5   1]
- [ 36  18 142  53  19  24  35]
- [  9   4  19  96   5   6   8]
- [  3   6   4   2  61   1   2]
- [  9   2   1   0   3  50   6]
- [  8   4  12   6   3   7  88]]
-Node Classification on random seed  8408 -> 0.623
-Confusion Matrix:
- [[ 59   0   3   5   3  10  23]
- [  6 117   6   1   7   6   2]
- [ 21  36 153  27  20  19  50]
- [ 11   3  22  96   7   1  13]
- [  0   8   1   3  64   4   2]
- [  3   5   1   0   1  53   3]
- [ 12   6   1   3   8  14  81]]
-Node Classification on random seed  8409 -> 0.631
-Confusion Matrix:
- [[ 82   8   3   3   1  12   9]
- [  4 123   7   4   2   3   1]
- [ 30  19 144  53  23  20  34]
- [ 10   3  18  88   3   2  15]
- [  1   7   4   2  60   0   3]
- [  4   0   2   0   0  50  10]
- [ 21   2   5   4   7  10  84]]
-Node Classification on random seed  8410 -> 0.619
-Confusion Matrix:
- [[ 65   4   6   4   5   7  23]
- [ 13 137   4   0   3   5   4]
- [ 31  30 133  22  18  34  36]
- [ 16   4  11 101   4   8   5]
- [  3  10   0   1  57   4   3]
- [  2   0   2   2   1  45  10]
- [  6   4  11   5   5  15  81]]
-Node Classification on random seed  8411 -> 0.633
-Confusion Matrix:
- [[ 73   5   4   2   0   6  18]
- [  2 123   6   3   5   2   2]
- [ 18  24 147  45  29  25  33]
- [  7   2  18  97   5   9  12]
- [  1   5   4   2  62   1   1]
- [  3   1   5   1   0  58   6]
- [ 17   2   9   5   7  15  73]]
-Node Classification on random seed  8412 -> 0.618
-Confusion Matrix:
- [[ 63   1   5   3   7  13   4]
- [  9 131   7   3   1   2   0]
- [ 32  17 142  15  42  15  50]
- [ 17   0  20 109   7   5  12]
- [  4   5   2   1  53   1   5]
- [  8   1   2   1   1  37   8]
- [  5   1  10   9   5  26  83]]
-Node Classification on random seed  8413 -> 0.618
-Confusion Matrix:
- [[ 76   0   5   2   9  10   9]
- [  7 144   6   1   4   0   4]
- [ 24  43 132  41  21  13  33]
- [ 18   8  14 106   5   5   4]
- [  4   7   3   3  49   0   2]
- [  9   2   9   3   0  36   4]
- [ 18   3   9   3   4  13  75]]
-Node Classification on random seed  8414 -> 0.615
-Confusion Matrix:
- [[ 93   1   6   3   4  10  13]
- [  0 119   9   3  11   7   7]
- [ 23  11 156  19  30  19  47]
- [ 11   2  13  82   5   5  29]
- [  3   3   4   3  64   2   1]
- [  3   6   7   3   0  40   9]
- [ 11   5   5   5  20   7  61]]
-Node Classification on random seed  8415 -> 0.629
-Confusion Matrix:
- [[ 79   1   4   2   7  15  12]
- [  1 135   4   1   2   1   1]
- [ 32  23 137  43  11  27  22]
- [ 13   3   8 106   6   7  15]
- [  3  13   3   4  55   1   4]
- [  7   1   2   3   1  42   9]
- [ 17   2  10   6   4  20  75]]
-Node Classification on random seed  8416 -> 0.627
-Confusion Matrix:
- [[ 55   1   5  11   1  16  11]
- [  1 143   7   5  11   1   7]
- [ 23  10 130  41  29  32  36]
- [  3   5  20 115   5  10   4]
- [  0   2   2   2  73   1   3]
- [  7   1   3   1   1  47   2]
- [  4   4   5  19   6  15  64]]
-Node Classification on random seed  8417 -> 0.588
-Confusion Matrix:
- [[ 76   3   5   2   1   7  11]
- [  4 122   7   1   8   5  10]
- [ 30  26 126  28  39  22  46]
- [ 15   4  26  77   9   8  17]
- [  1   4   3   4  57   2   0]
- [  0   2   2   1   1  51   4]
- [  8   2  12   5   8  19  79]]
-Node Classification on random seed  8418 -> 0.613
-Confusion Matrix:
- [[ 65   2   5   1   2  19  10]
- [  3 117   5   4  18   6   0]
- [ 22  19 151  31  32  18  42]
- [  6   8  11 122   4   5  10]
- [  0   8   2   2  60   0   8]
- [  4   6   2   3   1  47   4]
- [  7   8  16   8   6  19  51]]
-Node Classification on random seed  8419 -> 0.62
-Confusion Matrix:
- [[ 75   5   7   7   5  12   8]
- [  2 129   2   0   8   0   2]
- [ 23  16 141  28  38  22  48]
- [  8   3  16 114   6   2  14]
- [  0   6   3   0  63   1   1]
- [  5   3   3   8   1  26   6]
- [  8   2  11  13  10  17  72]]
-Node Classification on random seed  8420 -> 0.584
-Confusion Matrix:
- [[ 61   3   4  10   3  23   6]
- [  6 122   5   9  11   5   7]
- [ 14  30 141  45  45  14  28]
- [ 12   6  11 102   2   4  15]
- [  2  10   3   5  56   0   3]
- [ 10   2   1   5   1  30   1]
- [ 13   4   6  10   5  17  72]]
-Node Classification on random seed  8421 -> 0.625
-Confusion Matrix:
- [[ 55   1   9  10   6  20  11]
- [  5 117  11   3  11   0  11]
- [ 27  17 150  42  17  14  32]
- [  7   4  11 117   9  10   0]
- [  2  10   7   0  52   1   4]
- [  5   0   2   1   1  47   6]
- [  8   4   9   5   6  16  87]]
-Node Classification on random seed  8422 -> 0.645
-Confusion Matrix:
- [[ 85   1   3   2   2  11  11]
- [  1 124   3   6   5   5   2]
- [ 15  33 141  31  33  20  38]
- [  7   1  14 111   4   5  12]
- [  3   6   4   1  59   2   2]
- [  3   0   3   4   0  55   6]
- [ 11   2  12  10   8  13  70]]
-Node Classification on random seed  8423 -> 0.613
-Confusion Matrix:
- [[ 77   3   2  10   1  13   3]
- [  2 107   5   2  18  11   3]
- [ 32   4 149  37  42  19  39]
- [ 17   1  18  92  15   6   9]
- [  1   4   4   1  54   1   4]
- [  2   1   3   5   1  49   6]
- [  9   3  11   8   2   9  85]]
-Node Classification on random seed  8424 -> 0.635
-Confusion Matrix:
- [[ 64   5   6   5   3   5  13]
- [  1 136  11   4   9   1   8]
- [ 23   9 144  33  43  12  38]
- [  5   5  31  97   6   5  10]
- [  3   6   4   2  56   0   2]
- [  5   2   2   1   2  40   9]
- [  4   1  10   5   4  12  98]]
-Node Classification on random seed  8425 -> 0.611
-Confusion Matrix:
- [[ 68   2   8   5   5   8   8]
- [  8 138   3   0   7   5   9]
- [ 16  20 127  47  40  21  38]
- [  9   7  12 105  12   5   6]
- [  2   5   1   2  64   0   1]
- [  6   0   3   1   2  41   6]
- [ 11   4   7  11   9  17  68]]
-Node Classification on random seed  8426 -> 0.646
-Confusion Matrix:
- [[ 67   5   6  14   3   6   9]
- [  5 129   3   1   9   8   8]
- [  9  12 161  35  20  32  42]
- [  7   4  13 105   1  10  15]
- [  1   2   4   2  53   1  11]
- [  3   0   1   0   0  52  11]
- [ 10   0   7   5   7  12  79]]
-Node Classification on random seed  8427 -> 0.596
-Confusion Matrix:
- [[ 73   2   5   6   2  14  11]
- [  1 124   5   5   7   3   6]
- [ 20  20 138  23  63  18  45]
- [ 15   5  19  82   9   3  16]
- [  0   6   3   0  65   0   3]
- [  9   0   1   3   0  40   3]
- [ 15   2   5  13   5  13  74]]
-Node Classification on random seed  8428 -> 0.622
-Confusion Matrix:
- [[ 67   8   8   2   1  23   7]
- [  5 109  15   2   5   3   4]
- [ 11  30 138  33  28  27  30]
- [ 10   2   7 121   6   5  12]
- [  3   3   3   2  69   1   3]
- [  9   0   3   0   0  45   5]
- [  8   7  13   4   5  25  73]]
-Node Classification on random seed  8429 -> 0.626
-Confusion Matrix:
- [[ 73   2   3   0   4   5   9]
- [  8 109   1   5   6   4   7]
- [ 17  25 154  23  34  16  51]
- [ 10   2  11 107   9   7  11]
- [  2   5   4   2  58   2   5]
- [  5   1  12   0   0  44   8]
- [ 17   5   6   5   6  19  81]]
-Node Classification on random seed  8430 -> 0.565
-Confusion Matrix:
- [[ 62   4   4   4   5  10  20]
- [  4 137   4   3   3   1   5]
- [ 39  33  99  66  22  17  22]
- [ 25   6   9 106   6  10   8]
- [  3  10   3   2  52   0   1]
- [  6   3   3   1   0  49   4]
- [ 11   3  11  16   7  21  60]]
-Node Classification on random seed  8431 -> 0.603
-Confusion Matrix:
- [[ 65   4  10   3   2   6  12]
- [  4 120   1   2   6   6   7]
- [ 22  49 118  21  44  19  43]
- [  8   2  26 102   8   3  13]
- [  1   5   4   2  59   1   3]
- [  5   1   1   2   1  46   7]
- [ 15   2   6   2   8  10  93]]
-Node Classification on random seed  8432 -> 0.611
-Confusion Matrix:
- [[ 62   0   4   6   4  11  15]
- [  9 124   3   5   4   1   3]
- [ 12  23 161  30  33  21  47]
- [  6   1  11  94   4  14  24]
- [  1   4   3   3  61   1   1]
- [  3   1   0   2   1  54   4]
- [  7   2  12  15  23  15  55]]
-Node Classification on random seed  8433 -> 0.602
-Confusion Matrix:
- [[ 65   5   2   3   6  12  15]
- [  0 136   6   0  11   4   4]
- [ 29  25 139  34  38  17  29]
- [  8  10  15 104  14   1  18]
- [  1   7   3   1  61   0   2]
- [  8   5   1   0   0  33   8]
- [ 12   8   9   1   9  17  64]]
-Node Classification on random seed  8434 -> 0.614
-Confusion Matrix:
- [[ 68   3   3   2   0  20   8]
- [  3 132   5   5   3   2   6]
- [ 28  18 130  30  27  42  45]
- [  1   4  18  93   3   6  20]
- [  1   6   5   2  59   1   2]
- [  9   0   2   1   0  56   2]
- [  9   3   5   1  16  19  76]]
-Node Classification on random seed  8435 -> 0.598
-Confusion Matrix:
- [[ 78   2   1   5   3  10  13]
- [  3 113   9   2   5   2   4]
- [ 23  29 122  37  60  13  30]
- [ 10   4  10  91   4  12  17]
- [  3   8   6   3  61   0   1]
- [ 10   1   2   0   0  48   9]
- [ 17   3  14   7   3   7  85]]
-Node Classification on random seed  8436 -> 0.628
-Confusion Matrix:
- [[ 65   1   7   3   7   8  14]
- [  1 130   2   4   8   1   2]
- [ 20  18 150  52  32  14  30]
- [ 11   3  12 105   6   7  23]
- [  0   9   1   1  53   2   4]
- [  9   1   2   0   1  46   4]
- [  8   7   4   9  12  12  79]]
-Node Classification on random seed  8437 -> 0.609
-Confusion Matrix:
- [[ 64   6   7   6   5  23   3]
- [  1 149   6   5   3   0   1]
- [ 13  33 137  16  37  24  52]
- [ 10   2  27  99   5   5   9]
- [  0   8   4   3  50   2   0]
- [  1   2   0   2   0  45   5]
- [ 16   4   9  14   6  16  65]]
-Node Classification on random seed  8438 -> 0.603
-Confusion Matrix:
- [[ 59   6   5   6   3  16   9]
- [  2 127   6   4   5   1   3]
- [ 13  26 143  62  19  23  53]
- [  2   4  19  91  12   1   7]
- [  5   5   4   4  62   0   0]
- [  3   2   5   2   1  52   1]
- [  6   5   6  10   6  25  69]]
-Node Classification on random seed  8439 -> 0.637
-Confusion Matrix:
- [[ 76   2   3   5   2   6  17]
- [  6 114  12   4   8   4   3]
- [ 35  14 125  44  37  15  36]
- [  4   5   5 127   2   4  14]
- [  0   5   2   0  64   4   3]
- [  4   0   4   2   2  46   2]
- [ 11   1   7   9   8  12  85]]
-Node Classification on random seed  8440 -> 0.592
-Confusion Matrix:
- [[ 72   2   2   8   1   7  15]
- [  6 123  10   3   7   3   8]
- [ 29  25 120  61  19  19  55]
- [ 11   2   7  88  10   4  26]
- [  1   8   3   0  57   1   3]
- [  1   1   1   2   0  54   3]
- [ 11   2  10   5   5  11  78]]
-Node Classification on random seed  8441 -> 0.586
-Confusion Matrix:
- [[ 61   3  12   1   2  10  13]
- [  9 114   8   2  11  12   1]
- [ 33  13 157  26  47   8  51]
- [ 14   3  19  88   4   9  10]
- [  4   2   6   4  58   2   4]
- [  9   0   2   0   3  41   9]
- [ 13   6  10   6   7   6  67]]
-Node Classification on random seed  8442 -> 0.618
-Confusion Matrix:
- [[ 62   4   4   4   3   5  12]
- [  3 118   3   1  14   4  13]
- [ 27  18 139  24  29  12  49]
- [ 10   9  18  97   4   2  21]
- [  1   8   9   3  59   2   2]
- [  1   1   5   1   1  53  10]
- [ 12   2   5   5   6  15  90]]
-Node Classification on random seed  8443 -> 0.644
-Confusion Matrix:
- [[ 84   1   3   6   4  12   6]
- [  6 142   4   3   3   3   0]
- [ 18  23 136  44  19  25  38]
- [ 17   2  12 109   6   4  14]
- [  1  11   0   0  52   1   1]
- [  6   1   1   0   0  41   3]
- [ 26   2   5   5   3  17  80]]
-Node Classification on random seed  8444 -> 0.572
-Confusion Matrix:
- [[ 88  11   1   2   4   8   3]
- [  3 115   3   0  28   3   8]
- [ 20  24 106  27  38  26  48]
- [ 13   2   6  84  21   7  11]
- [  2   2   6   1  71   2   4]
- [  9   2   3   1   5  36   6]
- [ 20   6   4   2   9  27  72]]
-Node Classification on random seed  8445 -> 0.628
-Confusion Matrix:
- [[ 88   1   5   5   5   6   7]
- [  7 124   3   8   6   1   2]
- [ 33  28 146  50  17  27  27]
- [ 18   0   4 107  11   2   5]
- [  2   9   5   8  51   1   1]
- [  5   2   1   0   0  43   3]
- [ 16   8   6   9   4  14  69]]
-Node Classification on random seed  8446 -> 0.641
-Confusion Matrix:
- [[ 79   0   4   5   1   6  13]
- [  8 137   7   2   7   1  10]
- [ 36   9 144  22  30  31  42]
- [  4   4  10 112   7   3  11]
- [  3  11   2   2  66   0   2]
- [  9   0   2   0   1  40   0]
- [ 15   2   9   7   4  17  63]]
-Node Classification on random seed  8447 -> 0.607
-Confusion Matrix:
- [[ 60   2   5   8   2  15   6]
- [  5 125   3   2  17   0   4]
- [ 31  16 150  31  39  34  30]
- [  5   2  17 104  11   9   7]
- [  2   5   3   0  54   4   2]
- [  3   5   7   2   0  37   4]
- [ 12   1   8   5   9  20  77]]
-Node Classification on random seed  8448 -> 0.607
-Confusion Matrix:
- [[ 70   1   1   4   3  13  19]
- [  3 131   6   0  11   1  10]
- [ 23  30 142  25  21  31  30]
- [  9   1  25  94   4   5  13]
- [  1   8   9   2  61   0   2]
- [ 11   1   2   0   0  33   8]
- [ 10   1   6  11  10  22  76]]
-Node Classification on random seed  8449 -> 0.589
-Confusion Matrix:
- [[ 41   4  13   0   2  20  16]
- [  2 121   2   3   9   8   4]
- [ 15  32 146  25  25  23  46]
- [ 24   6   7 111   4   6  18]
- [  0   3   4   2  71   4   4]
- [  5   1   3   1   0  39  10]
- [ 14   3   7   3   9  24  60]]
-Node Classification on random seed  8450 -> 0.609
-Confusion Matrix:
- [[ 76   6   3   5   2  20   6]
- [  3 109   7   2   8   1   3]
- [ 18  31 146  23  24  17  50]
- [ 12   9  18  93   3   9  13]
- [  0   6   5   1  71   1   3]
- [  8   2  12   1   2  41  10]
- [  2   3   3   8  11  20  73]]
-Node Classification on random seed  8451 -> 0.6
-Confusion Matrix:
- [[ 78   2   2   3   1  12  13]
- [  8 126   6   2   3   6   4]
- [ 17  17 143  35  29  20  43]
- [ 12   7  16  89   7   9   8]
- [  1   7   5   1  62   3   1]
- [ 12   1   4   2   2  33   9]
- [ 14   3  11  15  17  10  69]]
-Node Classification on random seed  8452 -> 0.594
-Confusion Matrix:
- [[ 78   4   2   3   3   5   6]
- [  4 121   2   2  10   3   3]
- [ 31  24 112  34  33  40  40]
- [ 10   2  11 114   2  10  11]
- [  1  10   4   4  58   0   8]
- [  7   1   0   5   0  46   7]
- [ 22   4  11   8   7  12  65]]
-Node Classification on random seed  8453 -> 0.59
-Confusion Matrix:
- [[ 75   4   4   1   2  11   6]
- [  5 141  13   3   4   2   2]
- [ 35  38 112  42  47  12  29]
- [  6   8  13 103   8   7  13]
- [  3   7   1   3  49   0   3]
- [  3   2   0   2   0  40   1]
- [ 24  10  13   5   4  14  70]]
-Node Classification on random seed  8454 -> 0.624
-Confusion Matrix:
- [[ 55   7   4   4   5  15   9]
- [  3 150   3   6   3   0   3]
- [ 19  25 139  44  19  22  32]
- [ 10   6  18  85  17   5  19]
- [  1  14   5   4  61   1   4]
- [  6   0   0   1   1  51   4]
- [ 14   1   3   9   7   3  83]]
-Node Classification on random seed  8455 -> 0.603
-Confusion Matrix:
- [[ 64   0   0  16   6  21  12]
- [ 10 121   5   1  10   2   7]
- [ 12  20 135  28  25  23  45]
- [  8   6   9 100  17   9   8]
- [  0   8   2   5  67   1   6]
- [  4   2   1   0   0  47   8]
- [ 10   8   7   1  12  22  69]]
-Node Classification on random seed  8456 -> 0.603
-Confusion Matrix:
- [[ 68   3   4   8   3  16  12]
- [  7 114   7   2   2   7   1]
- [ 28  17 140  44  19  17  43]
- [ 17   5   6 103   5  11   8]
- [  1   7   5   2  66   1   4]
- [ 10   2   2   1   1  42   4]
- [ 10   4  13  12  13  13  70]]
-Node Classification on random seed  8457 -> 0.592
-Confusion Matrix:
- [[ 57   3   0   4   2  15  15]
- [  1 133   5   4   4   4   3]
- [ 20  43 122  42  36  17  41]
- [  6   2  11  98   6   4  22]
- [  2  10   1   2  69   0   2]
- [  3   2   0   5   2  35   8]
- [  5   9  13  13  10  11  78]]
-Node Classification on random seed  8458 -> 0.567
-Confusion Matrix:
- [[ 57   1   7  11   5   8   6]
- [  3 121   7   2  14   0   2]
- [ 38  31 145  24  33  15  41]
- [ 12   2  25  86  13  14   6]
- [  2   3   9   2  64   1   0]
- [  8   1   0   4   5  32   6]
- [ 16   6  16  12   7  15  62]]
-Node Classification on random seed  8459 -> 0.622
-Confusion Matrix:
- [[ 52   5   3   4   2  11  14]
- [  9 133   8   1   5   3   8]
- [ 32  26 142  28  20  19  29]
- [ 29   4   8 100   1   9  10]
- [  2   6   2   0  74   2   6]
- [  7   3   1   1   4  42   8]
- [  6   8   6  10   5  13  79]]
-Node Classification on random seed  8460 -> 0.609
-Confusion Matrix:
- [[ 84   4   6   4   5  10   8]
- [  4 114   2   2  14   0   3]
- [ 22  23 128  54  36  31  35]
- [  6   6  10 104   5   7  23]
- [  1   3   5   2  58   0   1]
- [ 11   4   3   1   0  30   7]
- [  6   4  10   3   2   8  91]]
-Node Classification on random seed  8461 -> 0.626
-Confusion Matrix:
- [[ 80   4   3   3   4   9   9]
- [  3 136   4   4   4   5   2]
- [ 24  25 130  37  41  26  30]
- [  9   3  20 113   4  10  13]
- [  1   8   2   0  61   2   1]
- [  7   2   1   0   0  30  10]
- [ 13   4   9   5   6   7  76]]
-Node Classification on random seed  8462 -> 0.574
-Confusion Matrix:
- [[ 61   2   9   8  12  25  12]
- [  2 116   8   1  12   2   0]
- [ 22  33 131  25  24  19  41]
- [ 10   5   5 100  12  10  22]
- [  0   6   5   1  64   3   2]
- [ 10   2   7   5   0  36   7]
- [ 17   3  14   6   4  13  66]]
-Node Classification on random seed  8463 -> 0.593
-Confusion Matrix:
- [[ 74   2   4  10   5   9  13]
- [  9 132   2   3  13   4   2]
- [ 28  15  99  51  30  34  34]
- [  7   2  24 108   8   6   9]
- [  1   2   2   1  68   0   1]
- [  4   2   2   2   1  44   7]
- [  8   2   7  15   8  18  68]]
-Node Classification on random seed  8464 -> 0.651
-Confusion Matrix:
- [[ 79   2   3   3   3   9   4]
- [  2 131   7   1   5   4   1]
- [ 15  31 141  31  35  29  22]
- [ 12   7  17 102   4   9  13]
- [  0   0   0   2  65   2   1]
- [  3   2   3   4   2  57   5]
- [ 11   4   5   2  13  21  76]]
-Node Classification on random seed  8465 -> 0.618
-Confusion Matrix:
- [[ 73   3   5   5   2   8  15]
- [  3 117  15   5   6   3   9]
- [ 30  29 141  21  33   7  48]
- [  8   5  14 102   6   6  11]
- [  2   8   4   3  57   0   4]
- [  4   0   3   1   1  53   6]
- [ 12   4  19   4   6   4  75]]
-Node Classification on random seed  8466 -> 0.595
-Confusion Matrix:
- [[ 79   3   8   0   2  11  16]
- [  0 114  11   4  11   3   4]
- [ 23  25 137  35  20  23  40]
- [  4   4  21  90   4  13  23]
- [  1  10   6   2  59   0   1]
- [ 12   0   4   3   3  39   2]
- [  7   5  11   9   8  13  77]]
-Node Classification on random seed  8467 -> 0.614
-Confusion Matrix:
- [[ 74   9   5   5   4  13  12]
- [  2 133   8   6  13   1   4]
- [ 26  24 119  26  24  21  35]
- [ 16   5  10 100   2   2  10]
- [  1   6   1   3  70   0   8]
- [  5   0   5   2   3  42   6]
- [ 13   5   7  16   6  16  76]]
-Node Classification on random seed  8468 -> 0.576
-Confusion Matrix:
- [[ 77   2   1   9   5  12   5]
- [ 11 119   7   1  14   1   4]
- [ 21  24 125  35  34  18  44]
- [ 15   3   8 102  13   8  15]
- [  1   4   8   1  57   1   5]
- [  6   6   1   2   6  43   2]
- [ 11   3  11  16   9  21  53]]
-Node Classification on random seed  8469 -> 0.599
-Confusion Matrix:
- [[ 53   8   6   2   3   9  23]
- [  3 146   4   0   4   3   3]
- [ 27  20 126  39  23  38  43]
- [ 15   4   4 101   6   8  19]
- [  1   5   1   2  61   1   1]
- [  1   4   1   1   1  34  10]
- [ 10   3  10  13   6  16  78]]
-Node Classification on random seed  8470 -> 0.635
-Confusion Matrix:
- [[ 86   1   3   5   0  10   4]
- [  3 120   6   3   9   3   3]
- [ 34  15 148  50  26  25  22]
- [ 14   3  16 107   4   4   8]
- [  1   1   2   5  57   0   5]
- [  2   0  13   0   1  43   3]
- [ 10   2  11   8   7  23  74]]
-Node Classification on random seed  8471 -> 0.621
-Confusion Matrix:
- [[ 63   1   9   5  10  10  18]
- [  6 101   9  10  16   3   6]
- [ 12  19 185  28  32  16  35]
- [  9   6   6  91   6   2  11]
- [  0   5   3   0  62   0   1]
- [  9   3   1   5   1  44   5]
- [  7   6   7  11  11  19  75]]
-Node Classification on random seed  8472 -> 0.651
-Confusion Matrix:
- [[ 80   3   3   8   2  11  10]
- [  3 129   4   2  10   0   7]
- [ 28  17 161  28  18  29  27]
- [ 10   8  21  98   4   5  12]
- [  0   7   8   2  64   0   1]
- [  7   1   1   2   0  40   3]
- [ 11   1   5   4   3  23  79]]
-Node Classification on random seed  8473 -> 0.622
-Confusion Matrix:
- [[ 83   1   3   5   0  13   8]
- [  9 128   5   0   9   9   3]
- [ 26  27 132  34  30  25  41]
- [  8   1   9 112   4   5  21]
- [  1   3   3   2  62   1   1]
- [  3   1   0   0   0  40   2]
- [ 12   3  11   4  24  11  65]]
-Node Classification on random seed  8474 -> 0.661
-Confusion Matrix:
- [[ 81   5  10   5   1   7   1]
- [  5 136   3   6   1   1   1]
- [ 15  19 152  42  31  17  38]
- [  7   3  20  95   6   3  23]
- [  1   4   3   0  62   0   2]
- [  2   0   1   0   2  49   7]
- [ 15   3   4   5  13   7  86]]
-Node Classification on random seed  8475 -> 0.629
-Confusion Matrix:
- [[ 80   2   2   5   3  16   8]
- [  5 133   3   1   7   3   3]
- [ 30  16 130  19  20  30  54]
- [ 11   2  13 107   2   6  17]
- [  1   5   3   3  55   0   2]
- [  7   1   4   1   2  43   2]
- [ 10   9   8   6   8  21  81]]
-Node Classification on random seed  8476 -> 0.635
-Confusion Matrix:
- [[ 82   0   5   4   4   7  22]
- [  0 130   3   6   6   3  11]
- [ 18  26 132  26  30  13  42]
- [ 16   8  17 105   6   3  12]
- [  3   8   6   3  62   0   3]
- [  7   2   2   1   0  44   8]
- [  9   3   6   4   2  10  80]]
-Node Classification on random seed  8477 -> 0.563
-Confusion Matrix:
- [[ 59   4  15   6   1  18  10]
- [  4 125   8   0   4   2   3]
- [ 26  30 129  33  22  29  47]
- [ 21   4   5  89   9  10  24]
- [  2   6   3   1  60   1   3]
- [  3   1   0   3   0  36  13]
- [  5   3  11  20   6  21  65]]
-Node Classification on random seed  8478 -> 0.654
-Confusion Matrix:
- [[ 88   2   6   6   4   1  11]
- [  5 126   6   0   7   5   4]
- [ 29  20 162  40  28  16  21]
- [ 10   5  10 114   3   8   7]
- [  4  10   3   4  50   0   1]
- [ 15   2   6   0   1  36   1]
- [ 10   6   8   4   8   9  78]]
-Node Classification on random seed  8479 -> 0.622
-Confusion Matrix:
- [[ 70   8   4   9   3  10   9]
- [  2 131   0   2   8   0   5]
- [ 20  28 127  41  18  34  40]
- [  4   9   7 114   7   9  10]
- [  0  10   5   0  57   1   2]
- [  6   3   6   2   1  44   7]
- [  8   5  12  10   5   8  79]]
-Node Classification on random seed  8480 -> 0.6
-Confusion Matrix:
- [[ 53   6   3   6   3  24   9]
- [  6 116  12   1  12   5   2]
- [ 23  15 136  27  52  20  39]
- [ 13   4   6 103   4  10  13]
- [  5   3   4   2  66   3   3]
- [  5   2   0   0   1  48   7]
- [  8   1  10   9  14   8  78]]
-Node Classification on random seed  8481 -> 0.613
-Confusion Matrix:
- [[ 79   1   8   6  10   5   6]
- [  2 114   8   6   7   6   8]
- [ 30  12 135  27  36  26  39]
- [ 16   5   9 113   5   5  13]
- [  2   6   9   7  55   0   1]
- [  9   1   1   1   0  38   7]
- [  8   2   8   7   9  13  79]]
-Node Classification on random seed  8482 -> 0.634
-Confusion Matrix:
- [[ 66   5   2  21   4  17   3]
- [  3 127   6   4   6   1   2]
- [ 13  27 149  34  33   9  48]
- [  2   6  10 126   7   4  10]
- [  0   9   5   0  54   1   1]
- [  4   2   7   6   2  32   5]
- [  8   0   6  15   4  14  80]]
-Node Classification on random seed  8483 -> 0.628
-Confusion Matrix:
- [[ 67   4   3   3   4   9  11]
- [  5 129   2   3  13   0   0]
- [ 28  21 155  50  16  20  36]
- [ 19   5  16 107  10   1   7]
- [  0   4   4   2  58   2   3]
- [  6   1   0   3   0  46   6]
- [ 14   1  11  12   7  10  66]]
-Node Classification on random seed  8484 -> 0.609
-Confusion Matrix:
- [[ 73   0   1   3   8   9   2]
- [  9 139   6   8   5   4   2]
- [ 18  21 125  41  43  27  40]
- [ 16   2  19  97   6   2  10]
- [  1   5   5   2  62   0   3]
- [  8   2   5   3   0  33   2]
- [ 13   4  13   6   5  12  80]]
-Node Classification on random seed  8485 -> 0.568
-Confusion Matrix:
- [[ 80   2   1   2   3   6   9]
- [  5 132   9   3   7   4   6]
- [ 28  26 123  46  19  34  33]
- [ 14   5   9  61  21  15  17]
- [  2   9   4   1  56   2   0]
- [ 13   1   1   1   3  41   2]
- [ 11   3  14  15   5  21  75]]
-Node Classification on random seed  8486 -> 0.617
-Confusion Matrix:
- [[ 71   8   4   7   3  10  14]
- [  4 136   4   4   1   0   5]
- [ 22  21 130  32  25  29  40]
- [  7   5   9  85   5  14  24]
- [  1  14   2   3  60   1   3]
- [  9   5   1   2   0  48   8]
- [ 17   6   2   2   5   5  87]]
-Node Classification on random seed  8487 -> 0.589
-Confusion Matrix:
- [[ 73   6   2   5   5  11  10]
- [  9 112   4   5  14   5   9]
- [ 23  25 143  41  16  28  32]
- [  8   4  20  90   7  12   6]
- [  4   6   4   0  62   1   1]
- [  0   2   1   2  10  40   5]
- [ 12   8  16   7   8  17  69]]
-Node Classification on random seed  8488 -> 0.612
-Confusion Matrix:
- [[ 62   3   3   3   4  17  11]
- [  8 109   5   0   7   2  14]
- [ 18  23 139  14  48  23  46]
- [  7   4  19 110   6   6  19]
- [  0   9   2   0  66   2   2]
- [  5   2   3   0   1  40   8]
- [  9   6   8   1   5  15  86]]
-Node Classification on random seed  8489 -> 0.578
-Confusion Matrix:
- [[ 63   4   9   4   5  14  12]
- [  7 128   2   1   5   0   6]
- [ 21  24 125  24  28  29  76]
- [  7   7  19  81   2   7  17]
- [  3  10   2   2  63   0   4]
- [ 10   1   2   2   5  48   5]
- [  9   2   2   5   9  19  70]]
-Node Classification on random seed  8490 -> 0.604
-Confusion Matrix:
- [[ 92   2   2   2   4   2  13]
- [  7 115   7   5   3   0   3]
- [ 29  15 126  45  22  25  35]
- [ 19   3  28  92   4   7  10]
- [  4   7   4   3  55   1   4]
- [  5   1   0   0   1  49   9]
- [ 19   4  13   6   6  17  75]]
-Node Classification on random seed  8491 -> 0.635
-Confusion Matrix:
- [[ 62   4   4   3   5   7  14]
- [  4 120   7  10   6   2   1]
- [ 32  26 151  37  19  21  29]
- [  8   8  21 109   2  11   9]
- [  0   4   3   0  63   1   2]
- [  6   1   0   0   0  46   4]
- [ 14   8  14   4   3  11  84]]
-Node Classification on random seed  8492 -> 0.595
-Confusion Matrix:
- [[ 69   3   6  10   1  10  14]
- [  4 117   8   2   8   1   6]
- [ 30  18 147  44  17  22  41]
- [  9   3  16  94   5   6  38]
- [  1   4   5   0  48   1   0]
- [  3   1   1   4   0  41   2]
- [ 19   4  10   2  12  14  79]]
-Node Classification on random seed  8493 -> 0.575
-Confusion Matrix:
- [[ 61   1   6   5   3  16  18]
- [  2 118   4   4   8   2   3]
- [ 26  26 122  40  43  28  39]
- [  8   7  18 108  13   7  10]
- [  0  10   3   2  54   1   1]
- [  5   3   1   5   2  41   7]
- [  3   3   5  10   4  23  71]]
-Node Classification on random seed  8494 -> 0.633
-Confusion Matrix:
- [[ 63   2   5  11   5  15  13]
- [  4 118   3   4  15   5   2]
- [ 20  18 144  29  27  28  35]
- [  7   5   6 127   6   5   5]
- [  1   3   6   0  56   1   3]
- [  4   3   1   1   0  56   4]
- [  6   4  20  11   4  20  69]]
-Node Classification on random seed  8495 -> 0.63
-Confusion Matrix:
- [[ 62   4   0   6   3  10  10]
- [ 10 126   4   4  14   2   2]
- [ 25  20 172  27  16  14  51]
- [  9   1   9 102  12   4   8]
- [  6   8   3   1  53   0   5]
- [ 10   3  10   2   0  37   5]
- [ 11   1  11   8   9  12  78]]
-Node Classification on random seed  8496 -> 0.609
-Confusion Matrix:
- [[ 76   5   4  13   9   9  10]
- [  4 121   3   3   5   4   4]
- [ 22  38 130  22  26  20  39]
- [  5   5  21  99   5   5  24]
- [  1   8   3   1  66   1   3]
- [ 12   1   3   0   0  43   6]
- [ 13   3   8   7   6  10  74]]
-Node Classification on random seed  8497 -> 0.641
-Confusion Matrix:
- [[ 80   5   6   6   6  11   3]
- [  4 120   4   2   4   4   3]
- [ 26  13 161  23  15  36  32]
- [ 12   4  16 100   4  17  13]
- [  1   6   4   3  61   4   4]
- [  3   2   3   1   4  42   6]
- [  6   3   5  10   3  22  77]]
-Node Classification on random seed  8498 -> 0.61
-Confusion Matrix:
- [[ 73   2   1   3   4  11  10]
- [  8 125   4   2  12   1   4]
- [ 30  24 115  41  24  35  28]
- [ 14   4  16  92   3   9  16]
- [  3   5   2   2  71   2   0]
- [  2   1   3   3   1  41   6]
- [  9   3  11   6   8  17  93]]
-Node Classification on random seed  8499 -> 0.62
-Confusion Matrix:
- [[ 60   2  14   4   5  14  21]
- [  4 118   8   1   6   1   2]
- [ 19  25 165  46  17  16  40]
- [ 23   4   9 102   4   7   7]
- [  0   8   5   1  61   1   3]
- [  5   0   3   0   0  46   6]
- [ 15   5   2  14   2  11  68]]
-Node Classification on random seed  8500 -> 0.607
-Confusion Matrix:
- [[ 61   1   1   4   6   7  12]
- [  9 129   6   3  10   3   2]
- [ 39  11 155  19  19  24  50]
- [ 11   5  16  99   9  12  23]
- [  3   5   2   0  47   2   2]
- [ 11   0   3   1   0  23  12]
- [  9   6  11   6   6  12  93]]
-Node Classification on random seed  8501 -> 0.605
-Confusion Matrix:
- [[ 73   3   4   2   2  10  10]
- [  5 123   9   7   5   5   3]
- [ 24  31 138  45  18  22  41]
- [ 10   3  31  98  10   6   7]
- [  1   2   4   0  62   0   6]
- [  7   3   3   1   5  36   3]
- [ 14   3   3  10   4  13  75]]
-Node Classification on random seed  8502 -> 0.613
-Confusion Matrix:
- [[ 77   3   7   7   1  12   6]
- [  9 129   2   0   7   2   6]
- [ 13  37 124  23  14  38  39]
- [ 13   9   5 115  10  10   7]
- [  0   6   5   1  65   1   2]
- [  3   4   5   8   0  35   4]
- [  6   3   3   7  13  36  68]]
-Node Classification on random seed  8503 -> 0.628
-Confusion Matrix:
- [[ 74   1  11   2   3   9  10]
- [  5 138   8   0   6   3   2]
- [ 26  14 152  27  19  39  27]
- [  7   8  22  99   3  13   8]
- [  4   6   4   2  49   2   3]
- [  7   2   5   1   0  44   5]
- [ 11   3  10   6   6  22  72]]
-Node Classification on random seed  8504 -> 0.568
-Confusion Matrix:
- [[ 71   3   4   4   2   3  11]
- [  4 125   4   1   8   4   2]
- [ 34  20  92  53  36  40  49]
- [  2   1   6 115   4  13  16]
- [  1   9   6   2  51   0   2]
- [ 17   0   2   2   0  37   5]
- [ 21   4  12  12   4   9  77]]
-Node Classification on random seed  8505 -> 0.566
-Confusion Matrix:
- [[ 62   2   9  11   4   8  13]
- [  4 122  12   3   8   2   7]
- [ 23  12 121  31  37  26  63]
- [ 13   4  22 109   3   8   7]
- [  2   3   3   1  65   0   2]
- [  5   1   2   0   2  45   5]
- [  6   1   9  17  20  23  42]]
-Node Classification on random seed  8506 -> 0.595
-Confusion Matrix:
- [[ 64   3   5  16   3   4  14]
- [  3 128  14   4   4   1   5]
- [ 21  38 123  34  26  27  37]
- [  9   2  22 117   4   2   5]
- [  1   4   2   2  61   1   4]
- [  9   0   3   7   1  41   5]
- [ 20   1  17   6   6  13  61]]
-Node Classification on random seed  8507 -> 0.6
-Confusion Matrix:
- [[ 71   2   3   5   5   8  10]
- [  6 130   6   2   7   2   8]
- [ 24  25 126  34  45  25  43]
- [ 10   6   8 117   5   2   8]
- [  1   7   4   0  53   4   0]
- [  4   0   4   2   0  45   5]
- [ 12   3  15  15  15  10  58]]
-Node Classification on random seed  8508 -> 0.621
-Confusion Matrix:
- [[ 71   0   3   7   6   5  14]
- [  7 131  15   6   4   2   2]
- [ 12  37 133  28  25  13  54]
- [  6   3  16  97   5  10  11]
- [  1   8   2   0  65   1   0]
- [  6   0   2   3   0  48   9]
- [  9   7   8   3  10  19  76]]
-Node Classification on random seed  8509 -> 0.619
-Confusion Matrix:
- [[ 55   5   4  11   4   7  14]
- [  4 132   9   0   3   4   7]
- [ 17  32 138  21  19  37  40]
- [  9   7  14 107   1   6  15]
- [  3   2   8   0  61   1   4]
- [  3   1   3   3   1  50   4]
- [  4   2   9  15   7  21  76]]
-Node Classification on random seed  8510 -> 0.655
-Confusion Matrix:
- [[ 77   4   2   8   6   7   9]
- [  3 116   8   1  11   1  10]
- [ 17  17 157  50  21  16  20]
- [  9   1  16 131   6   4   6]
- [  2   3   3   2  61   2   2]
- [  4   0   3   1   0  47   6]
- [ 12   5  15  12   7  13  66]]
-Node Classification on random seed  8511 -> 0.638
-Confusion Matrix:
- [[ 72   1   6   7   1   8   6]
- [  7 124   4   2   3   3  11]
- [ 16   9 160  42  21  27  43]
- [  8   4   9 123   3   7  16]
- [  1   3   4   5  52   2   5]
- [  4   0   6   3   0  38   9]
- [  7   3   7  10   6  23  69]]
-Node Classification on random seed  8512 -> 0.575
-Confusion Matrix:
- [[ 63   4   3   1   3   9   5]
- [  2 130   6   6  11   8   0]
- [ 29  17 100  47  47  28  30]
- [ 11   7  12 100   6  12  12]
- [  1   9   1   1  62   3   7]
- [  3   0   0   4   9  53   2]
- [ 10   2   9  12  14  22  67]]
-Node Classification on random seed  8513 -> 0.63
-Confusion Matrix:
- [[ 85   3   1   5   5   8   0]
- [  2 140   5   1   9   5   2]
- [ 26  16 126  56  21  11  46]
- [ 16   8  16 109   0  11  14]
- [  0   7   6   0  55   0   1]
- [  3   0   2   1   2  39   5]
- [ 21   2   7   8   5  13  76]]
-Node Classification on random seed  8514 -> 0.611
-Confusion Matrix:
- [[ 67   4   1   6   1   8  17]
- [ 12 137   6   1   5   4   3]
- [ 20  20 151  28  40  11  32]
- [ 13   3  25  84   9   3  19]
- [  1  10  10   1  57   0   2]
- [  3   1   3   8   1  41   2]
- [ 16   6   8   4   8  14  74]]
-Node Classification on random seed  8515 -> 0.635
-Confusion Matrix:
- [[ 74   1   3   5   2   6   9]
- [  5 133   8   0   9   1   5]
- [ 29  19 138  44  21   6  59]
- [ 14   4  14 101   4   2  12]
- [  1   6   6   2  62   4   2]
- [  6   2   6   3   1  37   3]
- [ 13   2   8   5   5   8  90]]
-Node Classification on random seed  8516 -> 0.611
-Confusion Matrix:
- [[ 61   3   0  12  11   8  18]
- [  5 128   4   4   7   2   2]
- [ 24  14 164  32  37  19  29]
- [  8   4  19  80   5   9  12]
- [  1   8   6   1  73   0   2]
- [  6   0   1   3   6  35   2]
- [ 13   4   7   7  12  22  70]]
-Node Classification on random seed  8517 -> 0.623
-Confusion Matrix:
- [[ 62   2   4   5   1  20  10]
- [  5 142   2   0   6   4   4]
- [  8  34 142  42  21  23  46]
- [ 15   7   7 102   3  10   8]
- [  0   9   3   4  60   0   0]
- [  2   2   0   1   2  37  12]
- [  6   6   4   6   8  25  78]]
-Node Classification on random seed  8518 -> 0.635
-Confusion Matrix:
- [[ 68   1   3   4   0   5  15]
- [  5 119  13   0   4   2   3]
- [ 19  30 141  32  25  16  48]
- [ 12   4   8 112   2   2  17]
- [  2  10  12   2  64   2   0]
- [  5   5   4   1   0  48   6]
- [  9   2   7   6  10  12  83]]
-Node Classification on random seed  8519 -> 0.641
-Confusion Matrix:
- [[ 68   3   6   0   2  11  16]
- [  7 127   6   2   4   5   3]
- [ 19  24 151  35  26  23  32]
- [  8   3  15 120   3   2  15]
- [  0   8   3   2  62   3   4]
- [  3   1   2   2   4  37   6]
- [  6   5  10  16   1  13  76]]
-Node Classification on random seed  8520 -> 0.643
-Confusion Matrix:
- [[ 76   1   9  10   6  19   3]
- [  5 140   5   0   2   2   1]
- [ 19  30 148  13  24  21  30]
- [ 10   8  16 112   5   3   9]
- [  2   8   5   3  57   1   2]
- [  8   2   4   1   0  39   3]
- [ 18  11  10   8   6  14  71]]
-Node Classification on random seed  8521 -> 0.642
-Confusion Matrix:
- [[ 81   3   2   2   5  10   9]
- [  4 127   8   3   7   1   1]
- [ 32  16 157  24  20  30  37]
- [ 16   3  14  98   8  12   8]
- [  1   6   7   1  49   5   3]
- [  6   2   1   0   0  51   6]
- [ 18   1   5   4   7  10  79]]
-Node Classification on random seed  8522 -> 0.626
-Confusion Matrix:
- [[ 85   3   3   4   2   7   8]
- [  7 120   3   2   7   1   5]
- [ 28  21 159  25  20  33  35]
- [ 14   2  24  91   0   8  11]
- [  3   3   7   2  53   5   1]
- [  4   2   0   5   1  43   3]
- [ 19   3   8  18   6  11  75]]
-Node Classification on random seed  8523 -> 0.634
-Confusion Matrix:
- [[ 77   2   5   2   5   5  11]
- [  3 123   5   3   6   4   5]
- [ 20  15 180  20  23  19  48]
- [ 18   4  19  84   4   7  20]
- [  4   6   3   4  57   0   4]
- [  6   2   3   2   0  40   5]
- [ 19   4  14   6   5   6  73]]
-Node Classification on random seed  8524 -> 0.645
-Confusion Matrix:
- [[ 66   2   3   2   1   9  17]
- [  4 130   5   0   9   0  14]
- [ 39  11 163  17  28  21  19]
- [ 30   1  14 101   7   4  15]
- [  2   4   3   1  66   1   2]
- [  4   2   4   1   0  43   6]
- [ 11   0   8  11   6  17  76]]
-Node Classification on random seed  8525 -> 0.591
-Confusion Matrix:
- [[ 59   1   1   2   1  15  18]
- [  8 133   7   4   5   3   3]
- [ 24  23 119  36  28  30  49]
- [ 17   5  23 109   8   5  13]
- [  1   5   3   1  57   6   2]
- [ 12   0   1   0   0  29  12]
- [  5   3   9   6   6   8  85]]
-Node Classification on random seed  8526 -> 0.658
-Confusion Matrix:
- [[ 80   3   5   1   2  16  13]
- [  7 112   2   2   3   2   6]
- [ 20  16 167  30  24  18  49]
- [ 10   2  11 118   4   7   7]
- [  1   6   3   1  56   1   3]
- [  2   3   1   1   0  48   5]
- [  9   2  15   5   4  20  77]]
-Node Classification on random seed  8527 -> 0.646
-Confusion Matrix:
- [[ 62   7   3   2   4  11  26]
- [  5 134   3   2   5   1   3]
- [ 14  23 162  20  28  14  58]
- [ 13   4  14  93   8   6  10]
- [  1   7   3   0  60   0   3]
- [  8   1   0   1   1  41   4]
- [ 12   2   1  12   9   5  94]]
-Node Classification on random seed  8528 -> 0.624
-Confusion Matrix:
- [[ 67   0   1   6   3  21   4]
- [  5 138   6   4   3   1   1]
- [ 26  11 129  42  35  35  41]
- [  9   3  16 107   2  11  16]
- [  0   5   1   1  72   0   1]
- [  3   1   3   1   0  34  15]
- [ 11   3   9   8   7   5  77]]
-Node Classification on random seed  8529 -> 0.63
-Confusion Matrix:
- [[ 85   2   1   6   4  23   5]
- [  3 128   1   2   7   0   4]
- [ 14  15 156  34  17  23  48]
- [ 16   1  14 104   4   4  17]
- [  0   8   5   2  50   0   0]
- [  8   4   2   4   0  38   4]
- [  8   6  13   5  11  25  69]]
-Node Classification on random seed  8530 -> 0.64
-Confusion Matrix:
- [[ 87   2   6   5   4   9   7]
- [  4 115  11   3  10   4   9]
- [ 20  16 139  52  11  12  40]
- [ 12   4  18 114   3   4  15]
- [  3   2   4   0  64   0   0]
- [  2   3   4   1   0  49   9]
- [ 12   4  17   4   5   9  72]]
-Node Classification on random seed  8531 -> 0.62
-Confusion Matrix:
- [[ 55   6   8   4   4   3   9]
- [  7 121   9   4  10   5   3]
- [ 13  16 141  33  22  30  50]
- [ 14   4  10 110   4   7  15]
- [  1   4   5   0  69   1   1]
- [  8   3   2   4   1  40   4]
- [ 16   4  10   5   2  19  84]]
-Node Classification on random seed  8532 -> 0.598
-Confusion Matrix:
- [[ 63  10   0   3   1  15  13]
- [  2 118  12   1   7   7   8]
- [ 11  25 130  61  23  24  41]
- [ 21   2  14  97  10   7  21]
- [  0   5   3   0  62   1   3]
- [  2   5   2   0   0  49   2]
- [  8   1   8  10   2  11  79]]
-Node Classification on random seed  8533 -> 0.63
-Confusion Matrix:
- [[ 74   2   7  11   5  10   5]
- [  5 118   6   2   9   2   5]
- [ 32  11 160  43  21  21  28]
- [  6   2  15  96  11   9  16]
- [  1   6   3   0  50   0   0]
- [  5   0   5   5   6  45   6]
- [ 18   3  11   3   2  12  87]]
-Node Classification on random seed  8534 -> 0.658
-Confusion Matrix:
- [[ 70   5   3   2   3   3  27]
- [  3 142   4   0   5   2   3]
- [ 25  27 155  33  29  12  22]
- [  5   6   9 111  10  15  10]
- [  2   9   8   3  64   0   2]
- [  6   0   3   1   1  41   4]
- [  7   4  15   6   6   2  75]]
-Node Classification on random seed  8535 -> 0.597
-Confusion Matrix:
- [[ 45   4   1   5  11  17  17]
- [  3 121   6   2  12   2   8]
- [ 11  20 158  30  42  30  28]
- [ 11   1  20  88   9   3  18]
- [  1   5   1   0  61   0   0]
- [  5   0   3   2   1  45   2]
- [ 19   2  12   4   7  28  79]]
-Node Classification on random seed  8536 -> 0.629
-Confusion Matrix:
- [[ 52   3   6   5  11  11  16]
- [  2 118   6  11   7   2  10]
- [ 11  20 162  31  16  24  54]
- [ 15   2  12 106   3   4  10]
- [  1   4   3   2  63   0   2]
- [  2   1   1   2   0  41  11]
- [ 10   5   9  10   5  11  87]]
-Node Classification on random seed  8537 -> 0.609
-Confusion Matrix:
- [[ 82   2   4   1   9  13   7]
- [  5 112   2   0  17   3   2]
- [ 16  16 129  43  46  18  35]
- [ 16   1  18 105   8   8  10]
- [  0   9   2   2  64   0   2]
- [  4   0   5   1   0  47   5]
- [  8   4  10   3  15  21  70]]
-Node Classification on random seed  8538 -> 0.607
-Confusion Matrix:
- [[ 74   3   6   5   2   3   5]
- [  2 135   5   1   4   3   7]
- [ 23  40 140  47  21  23  38]
- [ 17   2  15  84   6   7  17]
- [  2   6   9   1  56   0   1]
- [  3   3   5   3   0  47   3]
- [  6   4  17   8   3  17  71]]
-Node Classification on random seed  8539 -> 0.602
-Confusion Matrix:
- [[ 83   3   4   0   4   6   8]
- [  1 117   7   2  13   3   2]
- [ 13  40 138  22  29  19  47]
- [ 13  11  22 103   9   4  14]
- [  2  10   1   1  65   0   5]
- [  4   3   2   1   1  36   8]
- [ 15   5   6   8  21   9  60]]
-Node Classification on random seed  8540 -> 0.604
-Confusion Matrix:
- [[ 61   0   7  10   0  10  16]
- [  5 120   8   1   8   5   3]
- [ 46  14 130  51  24  23  20]
- [ 10   4  11 123   2   7  14]
- [  0   7   9   2  51   1   1]
- [  3   0   3   7   3  51  10]
- [ 17   1   8   7   3  15  68]]
-Node Classification on random seed  8541 -> 0.629
-Confusion Matrix:
- [[ 52   3  11   2   5  12  10]
- [  1 108   9   3   8   6   3]
- [ 43  15 156  43   7  39  30]
- [  7   2   8 122   8   6  11]
- [  2   6   6   3  57   0   4]
- [  5   2   1   0   0  52   4]
- [  7   6  10   4   4  15  82]]
-Node Classification on random seed  8542 -> 0.628
-Confusion Matrix:
- [[ 82   4   7   4   3   4  14]
- [  7 118   5   2  11   3   6]
- [ 11  29 157  42  13  19  39]
- [  7   4  21 101   4   7  10]
- [  0   2   2   3  60   0   5]
- [  6   2   0   2   5  37   9]
- [  9   6  12  15   4  14  73]]
-Node Classification on random seed  8543 -> 0.604
-Confusion Matrix:
- [[ 69   1   0   0   6  12  14]
- [  4 141   4   3   5   4   3]
- [ 47  10 147  34  26  26  34]
- [ 22   3  19  81   9   2  20]
- [  1   3   9   0  56   2   0]
- [ 10   1   1   4   0  47   3]
- [ 16   1   5   6  11  15  63]]
-Node Classification on random seed  8544 -> 0.582
-Confusion Matrix:
- [[ 67   2   4   4  10  10   9]
- [  4 125   1   2  12   3   7]
- [ 30  26 135  31  20  35  41]
- [  9   3  12 102   4   6  21]
- [  1   8   4   4  47   0   5]
- [  2   1   4   0   1  56   6]
- [  9   4   8   6  28  21  50]]
-Node Classification on random seed  8545 -> 0.62
-Confusion Matrix:
- [[ 66   3   2  10   7   8   3]
- [  1 131   8   2   5   1   5]
- [ 22  36 141  35  18  30  28]
- [  8   3  20 112   6   4   6]
- [  0  15   3   3  49   1   0]
- [  3   0   1   5   5  41   7]
- [ 13   6   8  15  12  12  80]]
-Node Classification on random seed  8546 -> 0.622
-Confusion Matrix:
- [[ 70   4   5   4   3  10   9]
- [  1 127   1   8   3   1   9]
- [ 17  35 145  43  27  18  26]
- [ 10   4  21 102  11   1  15]
- [  1   8   2   0  51   0   6]
- [  8   1   1   3   3  51   6]
- [  8   6  13   5  10  11  76]]
-Node Classification on random seed  8547 -> 0.675
-Confusion Matrix:
- [[ 77   3   5   4   2   8   3]
- [  5 135   4   1   3   1   9]
- [ 17  16 153  19  19  31  32]
- [  7   5  18 102   3   4  21]
- [  2   7   2   2  82   0   3]
- [  7   2   2   2   0  53   5]
- [ 17   5   2   5  10  12  73]]
-Node Classification on random seed  8548 -> 0.601
-Confusion Matrix:
- [[ 52   4  11   6   5   7  16]
- [  3 134  10   4   6   4   1]
- [ 23  20 145  16  42  30  37]
- [ 15   6  18  95  16   2   8]
- [  1  10   2   2  55   1   0]
- [  1   4   4   0   0  48   1]
- [  6   3   3   6  28  17  72]]
-Node Classification on random seed  8549 -> 0.626
-Confusion Matrix:
- [[ 72   1   5  15   6  13   3]
- [  6 134   7   4   5   4   4]
- [ 35  21 142  34  13  24  36]
- [  6   3  11  93   5   4   9]
- [  0   8   2   2  66   3   1]
- [  3   2   2   2   2  41   8]
- [ 15   3   7   9   5  26  78]]
-Node Classification on random seed  8550 -> 0.632
-Confusion Matrix:
- [[ 58   3   2   5   6  14  15]
- [  2 127   2   0  15   4   1]
- [ 17  23 142  23  43  48  30]
- [  6   5  12 110   4   6  13]
- [  1   1   4   2  70   1   1]
- [  4   1   5   1   0  49   5]
- [  2   1   4   3   6  27  76]]
-Node Classification on random seed  8551 -> 0.637
-Confusion Matrix:
- [[ 60   2   6  13   8   8  22]
- [  8 127   3   3   9   2   1]
- [ 28  20 146  29  17   8  37]
- [  8   4  19 109   4   4  21]
- [  0   8   4   1  65   2   2]
- [  4   1   2   1   3  44   7]
- [  7   2  11   4   7  13  86]]
-Node Classification on random seed  8552 -> 0.614
-Confusion Matrix:
- [[ 65   3  17   3   4   8  15]
- [ 11 143   6   1   6   3   5]
- [ 23  12 135  30  22  21  42]
- [ 10   2  22  79   4   4  10]
- [  2   6   9   2  60   2   4]
- [  5   2   2   0   0  48   4]
- [  9   2  20   6  12  15  84]]
-Node Classification on random seed  8553 -> 0.61
-Confusion Matrix:
- [[ 70   6   4  10   7   6  17]
- [  3 136   8   4   9   1   1]
- [ 31  21 130  47  22  25  31]
- [ 12   1  18 103   5   5  11]
- [  1   3   1   1  58   1   0]
- [  7   2   0   4   1  42   4]
- [ 13   3   9  12   6  17  71]]
-Node Classification on random seed  8554 -> 0.594
-Confusion Matrix:
- [[ 67   3   3   5   5  11  16]
- [  4 137   5   6   9   1   6]
- [ 21   9 123  49  20  46  35]
- [  7   4  20  80   7   7  21]
- [  2   4   5   1  63   0   2]
- [  1   3   1   1   3  45  10]
- [  5   2  11   8   7  20  79]]
-Node Classification on random seed  8555 -> 0.642
-Confusion Matrix:
- [[ 90   1   3   6   5  12   3]
- [  3 124   3   2  17   5   3]
- [ 16  34 138  28  24  16  44]
- [ 10   4  16 110   5   3   9]
- [  1   7   2   1  77   1   1]
- [  3   4   6   0   1  34  10]
- [  7   4   3  16   6  13  69]]
-Node Classification on random seed  8556 -> 0.593
-Confusion Matrix:
- [[ 62   0   5   3   7   6  12]
- [ 14 137   6   1   4   2   1]
- [ 25  24 124  50  29  23  21]
- [ 23   6  15  78   6   8  19]
- [  3   5   6   1  66   0   3]
- [ 12   4   2   3   1  49   2]
- [ 15   5   5   6  10  14  77]]
-Node Classification on random seed  8557 -> 0.602
-Confusion Matrix:
- [[ 61   6   3   4  11  20  13]
- [  4 119   7   2   5   5   4]
- [ 33  21 156  16  18  25  45]
- [ 13   8  11  94   3   5  25]
- [  2   5   9   0  44   0   5]
- [  9   6   1   0   1  50   5]
- [ 16   5   4   5   7  11  78]]
-Node Classification on random seed  8558 -> 0.633
-Confusion Matrix:
- [[ 80   2   4   5   3   8   6]
- [  2 131   3   1   4   4   6]
- [ 16  27 141  36  28  22  48]
- [ 13   7   7 111   4   7  11]
- [  3   7   2   3  43   3   1]
- [  8   2   5   0   0  42   3]
- [  7   6   2   8   7  26  85]]
-Node Classification on random seed  8559 -> 0.627
-Confusion Matrix:
- [[ 82   5   1   4   2   5   8]
- [  6 141   7   5   6   5   0]
- [ 24  17 145  33  24  19  39]
- [ 26   6  18  83   8  10  15]
- [  1   8   3   5  48   0   0]
- [ 10   0   1   3   1  43   4]
- [ 19   3   2   7   3  10  85]]
-Node Classification on random seed  8560 -> 0.663
-Confusion Matrix:
- [[ 76   1  12   1   5   9   6]
- [  8 123   7   0   7   1   4]
- [ 26  23 157  24  17  19  35]
- [ 21   2   9 100   4  12  12]
- [  2   5   2   1  68   2   2]
- [  8   0   4   1   0  51   4]
- [ 10   0   8   7   4  12  88]]
-Node Classification on random seed  8561 -> 0.594
-Confusion Matrix:
- [[ 63   2   8   3   3  16  10]
- [  2 128   3   2  13   1   1]
- [ 25  23 152  25  32  22  29]
- [ 24   4  16  80   7  24   3]
- [  1  13   1   3  56   3   2]
- [  5   1  11   5   0  45   3]
- [ 17   7   9   9   7  11  70]]
-Node Classification on random seed  8562 -> 0.59
-Confusion Matrix:
- [[ 63   1   5   9   7   8   7]
- [  1 122   6   5   5   3   3]
- [ 27  28 141  61  25  15  28]
- [ 18   2   7 104   4   2   5]
- [  3   8  10   0  57   0   2]
- [  7   1   4  12   5  40   8]
- [ 21   8  12  11   7   9  63]]
-Node Classification on random seed  8563 -> 0.582
-Confusion Matrix:
- [[ 53   4   7   0  10  12  24]
- [  5 120   6   0  14   3   5]
- [ 22  32 141  25  22  30  46]
- [ 10   8  25  94   5   3  13]
- [  1   6   2   1  48   1   5]
- [  6   2   2   1   0  34  15]
- [  4   9  13   2   9   8  92]]
-Node Classification on random seed  8564 -> 0.596
-Confusion Matrix:
- [[ 62   0   1  10   4  14  16]
- [  8 116   8   3  20   0   6]
- [ 20  16 150  44  21  10  36]
- [ 15   2  11 108   8   4  16]
- [  3   3   5   1  64   1   4]
- [ 13   0   2   2   0  43  10]
- [ 13   2  18  13   7  14  53]]
-Node Classification on random seed  8565 -> 0.557
-Confusion Matrix:
- [[ 66   1   2  13   6  18   7]
- [  2 100  10   1  12   7   1]
- [ 45  13 121  41  30  34  37]
- [ 13   3   5  99   1   6  14]
- [  0   3   8   1  65   1   5]
- [  5   1   1   6   0  51   3]
- [ 10   7   9  22   9  30  55]]
-Node Classification on random seed  8566 -> 0.608
-Confusion Matrix:
- [[ 71   4  13   4   3   7   7]
- [  8 112  20   5   9   0   9]
- [ 28  30 158  32  24  15  31]
- [ 16   2  18 108   3   7  13]
- [  1   5   4   3  56   1   3]
- [  5   3   3   0   0  40   6]
- [  8   4   9   6   6  17  63]]
-Node Classification on random seed  8567 -> 0.614
-Confusion Matrix:
- [[ 57   2   7   9   4  12   6]
- [  1 112   6   6   7   3   5]
- [ 33  18 156  22  36  25  43]
- [ 13   5  16  96   5   5  18]
- [  1   9   1   2  58   1   2]
- [  4   1   0   0   2  48   7]
- [  8   4   8   7  14   8  87]]
-Node Classification on random seed  8568 -> 0.614
-Confusion Matrix:
- [[ 54   1  12   3  10  16   4]
- [ 10 131   4   3  10   1   7]
- [ 17  34 141  36  27  19  28]
- [  5   1  17 104   4   4  19]
- [  2   7   3   0  63   4   4]
- [  8   1   3   2   0  44   8]
- [  8   3  13   5   5  18  77]]
-Node Classification on random seed  8569 -> 0.619
-Confusion Matrix:
- [[ 62   0   8   6   6  13   8]
- [  8 116   6   1  11   1   3]
- [ 21  11 163  23  29  32  23]
- [  8   3  29 100   6   3  21]
- [  1  10   4   2  60   1   1]
- [  7   1   3   2   2  40   5]
- [ 11   7  12   3   4  25  78]]
-Node Classification on random seed  8570 -> 0.613
-Confusion Matrix:
- [[ 60   0   2  11   9  14   6]
- [  3 148   5   0   3   5   4]
- [ 19  19 141  32  31  29  32]
- [ 11   6  21  89   7   6   8]
- [  3  10   1   1  66   1   3]
- [  7   0   1   4   3  30  15]
- [ 11   1  17   3   8  15  79]]
-Node Classification on random seed  8571 -> 0.577
-Confusion Matrix:
- [[ 60   2  13   7   1   9  11]
- [  6 138   8   2   3   1   2]
- [ 33  36 112  32  13  23  38]
- [ 15   2  30  98   5   4  13]
- [  3   8   8   0  67   2   1]
- [  6   4   5   4   0  44   3]
- [  5   9  15  13  15  13  58]]
-Node Classification on random seed  8572 -> 0.608
-Confusion Matrix:
- [[ 78   3   4   5   5   9   5]
- [  9 117   8   9   6   1   8]
- [ 26  11 137  36  19  21  45]
- [ 18   6  23  94   2   3  11]
- [  2   6   4   1  68   2   4]
- [  9   1   4   2   1  38   0]
- [ 18   1   8   9   7  20  76]]
-Node Classification on random seed  8573 -> 0.585
-Confusion Matrix:
- [[ 68   3   3   7   4  13   4]
- [  5 127   3   5   1   5   5]
- [ 26  13 141  38  39  15  62]
- [  6   8  21  93   4   9  22]
- [  4   6   5   4  51   0   2]
- [  4   2   1   8   0  34   4]
- [ 12   2   8  13   5  14  71]]
-Node Classification on random seed  8574 -> 0.615
-Confusion Matrix:
- [[ 67   3   2   5   0  14   7]
- [  4 119   8   2  19   3   0]
- [ 25  29 125  25  52  17  31]
- [ 11   3  12 105   3   2  15]
- [  1   3   6   0  65   2   4]
- [  6   0   0   4   5  48   6]
- [ 15   4   5   6  18   8  86]]
-Node Classification on random seed  8575 -> 0.621
-Confusion Matrix:
- [[ 75   0  19   3   4  10   5]
- [  7 129   4   0   6   1   3]
- [ 18  28 149  25  35  19  28]
- [ 14   7  21 108   5   6  13]
- [  1   7   5   0  49   0   2]
- [  7   0   6   1   0  43   5]
- [ 15   2  11   7   9  20  68]]
-Node Classification on random seed  8576 -> 0.63
-Confusion Matrix:
- [[ 62   2   5   3   4  23  13]
- [  8 129   6   3   2   2   6]
- [ 25  19 165  25  37  22  37]
- [  8   1  21  94   3   9   9]
- [  1   4   6   2  53   2   4]
- [  3   0   4   0   0  50   3]
- [ 10   1   3   9   1  24  77]]
-Node Classification on random seed  8577 -> 0.635
-Confusion Matrix:
- [[ 61   6   5   4  11  20  12]
- [  3 133   2   2   8   3   2]
- [ 22  22 146  20  14  22  50]
- [ 14   3  11 109   3   7  14]
- [  1   4   5   2  54   0   2]
- [  5   2   1   2   2  59   1]
- [ 10   2  11   8  12  15  73]]
-Node Classification on random seed  8578 -> 0.599
-Confusion Matrix:
- [[ 69   0   1   0   8  13  13]
- [  8 132   0   5  14   3   4]
- [ 28  26 133  48  23  36  23]
- [ 12   6   7  97   6   2  20]
- [  5   1   4   0  66   2   1]
- [  8   3   1   2   2  39   6]
- [  7   3  14   7   9  20  63]]
-Node Classification on random seed  8579 -> 0.613
-Confusion Matrix:
- [[ 63   3   8   2   2  20   7]
- [  5 120  13   1   7   7   1]
- [ 12  22 144  47  30  17  40]
- [ 24   3  12  98   8   8  15]
- [  1   7   0   2  65   1   2]
- [  2   0   4   1   1  42   4]
- [  7   2  12  10   9   8  81]]
-Node Classification on random seed  8580 -> 0.649
-Confusion Matrix:
- [[ 57   6  10   8   7  18   3]
- [  3 135   7   1  13   4   4]
- [ 11  19 171  43  16  26  27]
- [  4   2  10 114   3  19   6]
- [  0   4   4   2  67   1   3]
- [  1   1   3   1   2  45   0]
- [  1   1  15   8   9  25  60]]
-Node Classification on random seed  8581 -> 0.599
-Confusion Matrix:
- [[ 68  10   3   7   8   5   3]
- [  6 117   3   1  13   3   5]
- [ 38  15 133  47  30  10  47]
- [ 20   5  17 102   5   5  17]
- [  2   2   3   3  63   0   4]
- [  8   0   7   0   1  42   5]
- [ 16   5   6   2   4  10  74]]
-Node Classification on random seed  8582 -> 0.647
-Confusion Matrix:
- [[ 70   1   4   7   1  12   9]
- [  0 129   5   1   7   1  11]
- [ 21  29 155  31  21   9  47]
- [  9   5  16 113   2   7   7]
- [  0   4   2   2  61   0   4]
- [  6   1   3   1   0  50  10]
- [ 15   0  11   9   5  17  69]]
-Node Classification on random seed  8583 -> 0.59
-Confusion Matrix:
- [[ 63   2   4  14   2   2  15]
- [  8 114  19   4   7   4   2]
- [ 34   8 144  45  36  41  29]
- [  9   4  17  93   4   8   8]
- [  5   4   8   3  63   1   0]
- [  7   0   2   3   0  56   5]
- [  8   2   5  13   3  15  57]]
-Node Classification on random seed  8584 -> 0.597
-Confusion Matrix:
- [[ 70   2   5   6   7  10  10]
- [  1 116  11  11  18   5   4]
- [ 15  16 111  44  38  19  44]
- [ 15   2  22 117   4   2   9]
- [  0   3   3   3  69   1   2]
- [ 11   0   3   3   1  37   3]
- [ 11   5  14   9   2   9  77]]
-Node Classification on random seed  8585 -> 0.622
-Confusion Matrix:
- [[ 84   0   8   2   5  18   4]
- [  2 114   2  17   9   3   1]
- [ 16  15 131  28  49  16  47]
- [  6   2  19 104  11   9   6]
- [  1   6   1   2  65   0   3]
- [  4   0   1   1   3  45   5]
- [ 10   1   4  10  11  20  79]]
-Node Classification on random seed  8586 -> 0.639
-Confusion Matrix:
- [[ 78   2   2   4   4  16  12]
- [ 11 128   8   0  11   0   6]
- [ 35  30 158  14  23  15  34]
- [ 13   4  17 103   6   3  18]
- [  1   4   3   1  55   2   3]
- [  2   1   1   0   0  39   9]
- [ 14   6   4   2   4  16  78]]
-Node Classification on random seed  8587 -> 0.624
-Confusion Matrix:
- [[ 73   2   5  10   5   5   6]
- [  2 141   3   1   8   1   2]
- [ 22  22 141  37  24  33  42]
- [ 10   4  10 107   5  11   8]
- [  2   6   4   4  53   0   3]
- [  6   2   4   2   1  42   3]
- [ 13   6  19   7   8   8  67]]
-Node Classification on random seed  8588 -> 0.644
-Confusion Matrix:
- [[ 69   2   6   0   5  10  14]
- [  7 141   4   7   7   6   5]
- [ 20  33 131  31  25  15  41]
- [ 15   6  16  99   5   3  18]
- [  1   4   2   0  58   0   5]
- [  2   0   6   0   0  47   3]
- [  4   3   6   3   4  12  99]]
-Node Classification on random seed  8589 -> 0.633
-Confusion Matrix:
- [[ 76   1   1   7   6   8  14]
- [  3 130   5   0   6   3   6]
- [ 32  26 139  32  24  13  63]
- [ 10   2   8 106   4   4  15]
- [  0   8   0   2  58   0   0]
- [ 11   2   1   3   0  41  10]
- [  8   3  12   6   1   7  83]]
-Node Classification on random seed  8590 -> 0.641
-Confusion Matrix:
- [[ 74   6   3   3   6   9   3]
- [  4 130   9  10   8   4   4]
- [ 21  20 153  41  16  17  48]
- [ 21   5   4 115   2   7  10]
- [  1   5   3   1  55   2   1]
- [  3   4   3   1   1  43   2]
- [ 20   2  10   2   5  12  71]]
-Node Classification on random seed  8591 -> 0.64
-Confusion Matrix:
- [[ 72   5   1  10   2  17   2]
- [  4 132  10   1   6   2   2]
- [ 27  19 171  16  21  23  41]
- [ 11   5  13  94   5  11  12]
- [  1   6   6   1  55   2   3]
- [  0   2   2   0   4  31   8]
- [ 13   5   9   5   1  26  85]]
-Node Classification on random seed  8592 -> 0.614
-Confusion Matrix:
- [[ 63   7   6   7   7   8   8]
- [  3 106   8   7  12   3   6]
- [ 26  18 155  24  26   9  60]
- [ 13   2  16 109   5   5   9]
- [  0  10   3   0  62   2   1]
- [  3   0  11   2   3  39   4]
- [  8   5  10   7  11  11  80]]
-Node Classification on random seed  8593 -> 0.664
-Confusion Matrix:
- [[ 67   1  13   5   5   5  14]
- [ 10 137   8   1   6   0   7]
- [ 13  12 158  13  29  28  38]
- [  4   3  24 104   6   5  11]
- [  2   5   2   4  56   2   2]
- [  4   3   1   3   1  45   6]
- [ 11   1  10   4   2  12  97]]
-Node Classification on random seed  8594 -> 0.611
-Confusion Matrix:
- [[ 64   4   1  16   3   5   9]
- [  2 136   5   4   8   0   3]
- [ 29  27 144  45  20  13  34]
- [ 10   8  10  92   5   4  21]
- [  1   6   6   3  54   0   1]
- [  6   3   0   2   7  37   3]
- [ 16   8   8  12   4  17  84]]
-Node Classification on random seed  8595 -> 0.626
-Confusion Matrix:
- [[ 73   1   5   4   5  13   8]
- [  7 114   4   4   6   8   1]
- [ 34  14 159  36  23  44  22]
- [ 15   1   9  91   2   5  16]
- [  1   7   7   1  60   0   2]
- [  9   1   4   2   1  52   4]
- [  8   2  13   2   6  17  77]]
-Node Classification on random seed  8596 -> 0.552
-Confusion Matrix:
- [[ 73   2   6   5   4   6  11]
- [  2 125   6   1   4   2   2]
- [ 31  36 124  40  35  19  43]
- [ 21   4  19  67   5  10  19]
- [  1  11   2   2  68   2   0]
- [  7   2   2   0   6  34   5]
- [ 22   5   4  16   5  23  61]]
-Node Classification on random seed  8597 -> 0.617
-Confusion Matrix:
- [[ 49   0   9   7  11  11  17]
- [  9 114   3   6   1   6  12]
- [ 22  13 150  49  39  17  19]
- [  8   1  12 110   3   3  10]
- [  0   9   3   3  68   1   2]
- [  9   1   8   2   1  40   7]
- [ 14   2   4   9   6  14  86]]
-Node Classification on random seed  8598 -> 0.651
-Confusion Matrix:
- [[ 66   3  10   2   3   7  14]
- [  2 127  11   1  14   0   3]
- [ 19  13 163  21  34  25  33]
- [  7   8  21 109   7   5   6]
- [  1   6   4   1  60   0   0]
- [  6   4   5   2   0  40   4]
- [  8   1  10   8   4  16  86]]
-Node Classification on random seed  8599 -> 0.644
-Confusion Matrix:
- [[ 69   0   2   6   2  10  22]
- [ 10 123   1   5   2   1   8]
- [ 27  12 170  30  20   6  49]
- [ 14   2   8  97   3  18  11]
- [  1  11   5   1  56   0   4]
- [  6   0   5   1   0  46   8]
- [ 16   1  12   3   2  11  83]]
-Node Classification on random seed  8600 -> 0.657
-Confusion Matrix:
- [[ 83   9   4   4   1   8   8]
- [  2 108   2   5   9   3   2]
- [ 29  20 152  29  25  13  35]
- [ 10   9  17 109   0   5   8]
- [  2   6   3   1  63   0   2]
- [  0  10   3   0   2  51   5]
- [  9   5   7   9   8  14  91]]
-Node Classification on random seed  8601 -> 0.618
-Confusion Matrix:
- [[ 71   2   3   3   3  14  15]
- [  4 120   7   6   4  12   2]
- [ 21  27 133  38  29  17  50]
- [ 12   6  13 104   7   4  11]
- [  3  15   1   1  66   2   0]
- [  4   0   0   0   0  47   6]
- [  4   4   8   2   2  20  77]]
-Node Classification on random seed  8602 -> 0.606
-Confusion Matrix:
- [[ 64   2   8   7   2   9   4]
- [  1 140   5   4   0   5   5]
- [ 23  18 135  36  39  18  40]
- [ 18   2  24  84   8   4   9]
- [  2   9   1   2  60   1   1]
- [  5   1   5   6   2  39   7]
- [ 15   2  12   9   8  15  84]]
-Node Classification on random seed  8603 -> 0.606
-Confusion Matrix:
- [[ 61   4   3   4   9   8  18]
- [  8 120  15   2   5   4   5]
- [ 11  32 134  43  21  17  37]
- [ 20   8  14 103   8   1  14]
- [  1  12   3   2  61   0   1]
- [  8   3   0   1   4  46   3]
- [ 11   2  10   6   6  10  81]]
-Node Classification on random seed  8604 -> 0.655
-Confusion Matrix:
- [[ 82   1   2   2   1   7  12]
- [ 10 123   3   5  17   4   1]
- [ 17  15 147  25  33  31  43]
- [  8   2   3 111   8   8   7]
- [  0   9   3   0  58   4   1]
- [  7   2   0   3   0  54   4]
- [  6   5  10   5   7  14  80]]
-Node Classification on random seed  8605 -> 0.654
-Confusion Matrix:
- [[ 66   1   4   8   5   5  13]
- [  1 127   8   3  13   2   8]
- [ 19  15 170  22  20  29  40]
- [  8   2   5 113  10   1  11]
- [  0   4   5   0  69   1   1]
- [  0   3   1   7   0  35  13]
- [ 11   1  11  15   4  16  74]]
-Node Classification on random seed  8606 -> 0.629
-Confusion Matrix:
- [[ 63   5   5  10   2   8   9]
- [  9 131   6   4   4   0   2]
- [ 12  26 163  29  25  21  35]
- [ 13   8  34  98   3   2  14]
- [  0   5   6   2  48   0   3]
- [  7   0   1   2   0  38   4]
- [  9   4  10   7  13  12  88]]
-Node Classification on random seed  8607 -> 0.583
-Confusion Matrix:
- [[ 67   7   0   9   8   9   7]
- [  3 112   3   3   6   7   4]
- [ 30  37 123  44  32  21  37]
- [ 27   5   9 104   7   1   3]
- [  3   3   1   6  58   0   1]
- [  9   0   3   1   2  45   2]
- [ 14   8   9  14   4  18  74]]
-Node Classification on random seed  8608 -> 0.605
-Confusion Matrix:
- [[ 83   4   2   1   3   5   6]
- [  4 118  10   1   7   8   9]
- [ 23  20 157  44  18  24  46]
- [ 20   3  19  88  10   4  16]
- [  1   4   4   1  50   0   7]
- [  7   1   2   3   1  38   5]
- [ 14   3  10  10   5  10  71]]
-Node Classification on random seed  8609 -> 0.652
-Confusion Matrix:
- [[ 70   3   1   3   7   7  17]
- [  4 136   8   2   4   2   2]
- [ 14  20 179  31  27   8  39]
- [  9   6  24  81  14   6  11]
- [  2   7   4   0  68   1   1]
- [  5   2   5   0   0  41   9]
- [ 10   6  13   6   4   4  77]]
-Node Classification on random seed  8610 -> 0.609
-Confusion Matrix:
- [[ 69   3   2   4   0  12  15]
- [  3 129   8   0   8   3   3]
- [ 32  27 133  31  27  29  42]
- [ 10   3  17  89  10   5  10]
- [  3  11   1   2  70   2   3]
- [  7   1   0   2   1  48   5]
- [  3   3   9   3   7  24  71]]
-Node Classification on random seed  8611 -> 0.604
-Confusion Matrix:
- [[ 61   4   3   5   7   8  17]
- [  2 130   1   3   7   7   2]
- [ 21  38 110  25  56  24  36]
- [  9   7  16 117   8   3   6]
- [  0   8   3   1  59   0   2]
- [  6   2   3   2   0  50   2]
- [ 10   5   3   6  14  14  77]]
-Node Classification on random seed  8612 -> 0.628
-Confusion Matrix:
- [[ 71   0   2   4   2  19   4]
- [  5 114   7   4   9   3   2]
- [ 33  30 162  35  25  16  25]
- [ 18   1  15 100  16   6   6]
- [  2   5   0   0  57   3   5]
- [  6   4   2   0   1  42   5]
- [ 16   2   8   1  10  15  82]]
-Node Classification on random seed  8613 -> 0.635
-Confusion Matrix:
- [[ 67   2  13   5   5  11   9]
- [  2 115   7   0   5   2   3]
- [ 38  16 153  22  36  21  40]
- [  8   3   7 113   4   6  12]
- [  1   5   3   0  63   1   1]
- [  0   2   4   3   3  60   5]
- [  5   2   7   9  21  16  64]]
-Node Classification on random seed  8614 -> 0.665
-Confusion Matrix:
- [[ 85   3   3   5   3  10  10]
- [  5 135   4   3   8   7   2]
- [ 17  27 154  36  14  16  39]
- [  8   3  12 106   2   5  14]
- [  0   6   7   2  66   2   0]
- [  8   2   2   1   1  38   6]
- [  7   4  10  10   2   9  81]]
-Node Classification on random seed  8615 -> 0.595
-Confusion Matrix:
- [[ 73   2   4   2   1  16   5]
- [  0 122   3   4  11   1   6]
- [ 23  33 136  33  33  20  39]
- [  7   4  24  81  12   6  15]
- [  3   5   6   0  70   0   7]
- [  2   1   3   3   1  43   3]
- [ 12   3   9  14   9  20  70]]
-Node Classification on random seed  8616 -> 0.626
-Confusion Matrix:
- [[ 81   0   7   9   5   6   9]
- [  8 124   6   1  10   2   7]
- [ 29  13 141  28  23  32  33]
- [ 11   2  10  98   7   6  26]
- [  2   7   4   2  56   4   1]
- [  3   2   0   1   2  44   4]
- [ 11   2  16   8   5  10  82]]
-Node Classification on random seed  8617 -> 0.608
-Confusion Matrix:
- [[ 67   0  12   2   2  11  12]
- [  3 148  10   0   6   2   3]
- [ 21  28 127  24  51  20  44]
- [  9   4   5 108  10   4  14]
- [  1   6   5   1  52   1   1]
- [  4   6   2   3   0  33   9]
- [ 10   5   3  13  10  15  73]]
-Node Classification on random seed  8618 -> 0.576
-Confusion Matrix:
- [[ 56   2   4   7   6  13   8]
- [ 13 128  10   2   8   3   7]
- [ 31  31 133  31  36  23  43]
- [ 10   6   8  81   6   9  24]
- [  2   9   6   1  54   0   0]
- [  5   1   3   0   1  51   2]
- [  8   7   8  11   5  14  73]]
-Node Classification on random seed  8619 -> 0.63
-Confusion Matrix:
- [[ 82   3  31   4   6  18   4]
- [  5 127  15   4  11   0   2]
- [ 14  17 150  27  27  21  27]
- [ 21   0  12  95   3   5   4]
- [  0   7   5   1  60   1   2]
- [  5   4   2   2   0  49   3]
- [ 13   3  13   7   7  14  67]]
-Node Classification on random seed  8620 -> 0.639
-Confusion Matrix:
- [[ 77   0   9   6   3   7   9]
- [  2 130   4   4   7   2   3]
- [ 32  16 155  44  21  21  29]
- [ 13   2  11 114  11   1   5]
- [  1   6   2   2  53   1   5]
- [  8   0   0   6   0  49   4]
- [ 14   0  10  11   4  25  61]]
-Node Classification on random seed  8621 -> 0.611
-Confusion Matrix:
- [[ 86   0   1   5   7   6   5]
- [  6 127   9   5  11   1   8]
- [ 30  30 144  29  41  13  26]
- [  9   4  19  94   9  10  11]
- [  2   2   3   2  62   1   8]
- [ 14   0   2   2   0  34   3]
- [ 28   5  11   1   4   6  64]]
-Node Classification on random seed  8622 -> 0.556
-Confusion Matrix:
- [[ 54   1  13   4   5  11  15]
- [ 11 136   2   0   9   5   1]
- [ 11  19 118  36  52  35  38]
- [ 24   8  33  70   8  12  10]
- [  1   6   3   4  64   0   1]
- [  7   2   1   2   6  35   3]
- [  5   2  16   9   2  11  79]]
-Node Classification on random seed  8623 -> 0.615
-Confusion Matrix:
- [[ 79   2   3   3   6   9   8]
- [  5 127   9   1  12   4   0]
- [ 31   9 129  37  57  22  38]
- [ 10   3  10 100   9   4  12]
- [  0   3   3   1  51   1   2]
- [  8   1   6   0   0  50   3]
- [ 20   2  11  10   5   5  79]]
-Node Classification on random seed  8624 -> 0.621
-Confusion Matrix:
- [[ 78   2  10   4   5   8   4]
- [  4 132   4   3   6   5   6]
- [ 15  11 148  43  34  30  36]
- [ 12   8  11  94  16  13   9]
- [  1   9   2   0  59   2   1]
- [  5   1   2   0   4  41   1]
- [ 11   5  12   5   5  14  69]]
-Node Classification on random seed  8625 -> 0.589
-Confusion Matrix:
- [[ 72   1   7   5   3  11   7]
- [  6 126   9   4   4   0   5]
- [ 21  25 121  42  33  20  46]
- [ 15  14  11  82  11   3  12]
- [  0   9   2   1  65   3   7]
- [  6   0   0   0   0  49   9]
- [ 12   5  11   7  13  11  74]]
-Node Classification on random seed  8626 -> 0.616
-Confusion Matrix:
- [[ 83   0   3   3   6   4   5]
- [  5 136   5   3   6   1   9]
- [ 21  31 116  43  43  19  37]
- [ 12   9  11 106   5   4   8]
- [  1   6   2   1  59   0   7]
- [  9   1   0   0   0  44   4]
- [ 13   2  11  12   4  18  72]]
-Node Classification on random seed  8627 -> 0.601
-Confusion Matrix:
- [[ 81   2   1   5   3  20   3]
- [  0 113   7   5   5   3  10]
- [ 35  27 142  29  26  28  26]
- [ 13   9  15  90  20   4   9]
- [  0  12   4   0  51   2   2]
- [  9   1   1   1   0  51   3]
- [ 13   5   8   4  10  19  73]]
-Node Classification on random seed  8628 -> 0.654
-Confusion Matrix:
- [[ 94   5   3   2   3   6   8]
- [  9 141   5   0   4   0   2]
- [ 24  24 159  33  24  18  26]
- [  9   7  11  90   3   8  15]
- [  0  10   5   1  56   0   3]
- [  4   0   2   1   2  52   1]
- [ 26   3   7  15   7  10  62]]
-Node Classification on random seed  8629 -> 0.632
-Confusion Matrix:
- [[ 72   4   4  10   5  11   6]
- [  5 120   8  16   5   3   1]
- [ 16   7 151  36  39  11  41]
- [ 22   5  15  95   6   3  13]
- [  0   5   7   1  66   0   1]
- [  6   4   2   3   3  39  10]
- [  6   6   5   4   5   8  89]]
-Node Classification on random seed  8630 -> 0.641
-Confusion Matrix:
- [[ 67   0   2   4   5  15  11]
- [  2 129   4   2   8   6   1]
- [ 12  14 139  37  15  45  36]
- [ 10   3   8 112   3   8  19]
- [  4   5   6   1  68   1   1]
- [  8   3   0   2   1  48   5]
- [  6   3   8   4   7  24  78]]
-Node Classification on random seed  8631 -> 0.611
-Confusion Matrix:
- [[ 50   6   5  10   4  15  18]
- [  2 128   3   1  11   1   2]
- [ 21  14 150  35  28  20  46]
- [ 11   6  24 108   1   8   9]
- [  1   5   4   1  60   0   4]
- [ 13   2   4   0   0  36   3]
- [ 16   4  10   5   6  10  79]]
-Node Classification on random seed  8632 -> 0.622
-Confusion Matrix:
- [[ 53   3   2   5   4   9  25]
- [  6 133   6   4   1   5   3]
- [ 35  17 144  32  22  19  36]
- [  8   2  28 103   6   8  17]
- [  2   6   3   1  63   1   0]
- [  7   1   1   4   1  41   6]
- [ 10   4   5   5  10   8  85]]
-Node Classification on random seed  8633 -> 0.602
-Confusion Matrix:
- [[ 58   6  13   4   4  16   7]
- [  2 129   8   2   7   5   5]
- [ 29  15 133  42  22  19  52]
- [ 12   1  14 112   2   5  10]
- [  0   8   1   4  69   4   1]
- [  4   2   3   1   0  37   3]
- [  6   3   7  21   6  22  64]]
-Node Classification on random seed  8634 -> 0.629
-Confusion Matrix:
- [[ 80   1   3   5   6   4  13]
- [  2 124  12   2   3   3   5]
- [ 29  15 156  44  13  25  37]
- [  9   9  19  99  13   4   7]
- [  4   8   5   1  54   1   0]
- [  2   2   5   0   0  41  12]
- [ 12   4  10  13   3   6  75]]
-Node Classification on random seed  8635 -> 0.594
-Confusion Matrix:
- [[ 62   0   1   7   4  10  17]
- [  4 129   9   4   7   0   9]
- [ 26  12 118  58  26  34  34]
- [ 15   4  26 102   1   3   9]
- [  3   4   7   0  69   0   3]
- [  6   0   2   0   1  41   7]
- [ 10   0   7   8   9  19  73]]
-Node Classification on random seed  8636 -> 0.595
-Confusion Matrix:
- [[ 91   1   4   3   2  14   2]
- [  8 104   8   4  10   4   1]
- [ 28  23 108  83  21  18  31]
- [  7   2  12 132   3   4  12]
- [  1   5   3   0  48   6   2]
- [  7   4   2   2   0  39   2]
- [ 11   3  10  12   7  23  73]]
-Node Classification on random seed  8637 -> 0.579
-Confusion Matrix:
- [[ 66   2   8   7   2  10   4]
- [  7 125   7   6   6   4   7]
- [ 18   8 108  52  37  41  46]
- [ 22   1   5  94  10   5  21]
- [  0   7   1   3  54   5   5]
- [  6   2   1   3   1  46   3]
- [  6   5  12   6   2  17  86]]
-Node Classification on random seed  8638 -> 0.62
-Confusion Matrix:
- [[ 83   2   1   4   3   9  10]
- [  3 126  12   1  10   4   2]
- [ 17  18 134  36  22  21  52]
- [  7   6  15  90  15   5  25]
- [  2   3   4   2  67   0   1]
- [  2   1   1   0   3  37  10]
- [ 18   2  12   4   3  12  83]]
-Node Classification on random seed  8639 -> 0.643
-Confusion Matrix:
- [[ 81   3   2   9   0   8   5]
- [  0 148   7   2   5   1   5]
- [ 28  20 130  32  35  10  58]
- [  6   5  14 130   3   4   8]
- [  0  11   6   2  56   0   0]
- [  2   3   2   6   1  41   4]
- [  7   2  10  11   4  16  57]]
-Node Classification on random seed  8640 -> 0.64
-Confusion Matrix:
- [[ 72   0   6   3   8  12  15]
- [  2 137  10   5   1   2   3]
- [ 24  22 130  42  12  29  41]
- [ 10   3   8 105   4   4  18]
- [  1   8   6   1  63   1   0]
- [  7   0   1   0   0  50  11]
- [  5   5   8   6   5  11  83]]
-Node Classification on random seed  8641 -> 0.633
-Confusion Matrix:
- [[ 66   1   2   1   6  19  17]
- [  6 122   5   2   4   3   3]
- [ 25  21 155  28  22  26  40]
- [  5   5   8 104   8  16  18]
- [  2   8   0   1  55   2   2]
- [  2   0   1   4   1  48  10]
- [ 11   5   8   3   6  10  83]]
-Node Classification on random seed  8642 -> 0.581
-Confusion Matrix:
- [[ 74   4   7   2   2  11   8]
- [  3 120  14   3   7   3   4]
- [ 20  39 109  31  36  21  59]
- [  9   1  17  86   7   8  25]
- [  0   6   3   5  61   2   4]
- [  5   0   3   1   0  46   0]
- [  7   6  10   1   6  19  85]]
-Node Classification on random seed  8643 -> 0.614
-Confusion Matrix:
- [[ 85   1   5   9   8   5   1]
- [  6 114   3   0  10   2   6]
- [ 14  37 125  26  11  36  41]
- [  9   7  30 109   3   1  10]
- [  2   8   5   2  48   2   7]
- [  3   1   1   9   1  60   7]
- [ 17   7   4   4   9  16  73]]
-Node Classification on random seed  8644 -> 0.614
-Confusion Matrix:
- [[ 70   1   3   2   6   4  17]
- [  3 134   8   2  11   6   1]
- [ 14  25 151  25  27  26  39]
- [ 27   2  21  94   6   2  11]
- [  4   8   6   2  55   2   2]
- [  6   1   1   6   0  39   5]
- [ 12   3   7   5   9  18  71]]
-Node Classification on random seed  8645 -> 0.56
-Confusion Matrix:
- [[ 65   2   7   4   3  10  16]
- [  4 103   8   2  12   4   5]
- [ 31  33 111  45  53  27  40]
- [  7   4  20 116   1   8  14]
- [  1   5   2   1  53   1   2]
- [  9   1   2   0   0  36   4]
- [  7   3  14   3   4  21  76]]
-Node Classification on random seed  8646 -> 0.619
-Confusion Matrix:
- [[ 71   2   3   4   3   7  16]
- [  1 125   2   3  16   8   6]
- [ 22  26 148  41  27  20  45]
- [ 16   6   7  90   2   8  10]
- [  2   5   2   1  63   1   0]
- [  6   0   3   0   1  53   3]
- [ 11   6   6   6  10  17  69]]
-Node Classification on random seed  8647 -> 0.594
-Confusion Matrix:
- [[ 68   4   1  13   8  22   2]
- [  7 132   1   3   8   3   4]
- [ 22  11 123  30  37  34  38]
- [  3   5  17 116   2   8  20]
- [  1   5   7   2  63   3   3]
- [  3   2   2   1   0  36  11]
- [ 14   2   8   6  25   8  56]]
-Node Classification on random seed  8648 -> 0.645
-Confusion Matrix:
- [[ 74   4   5   4   5  15   6]
- [  3 121   3   2   6   3   5]
- [ 15  18 146  28  27  23  54]
- [ 10   6  15 102   6   4   9]
- [  2   9   3   0  66   0   2]
- [  9   1   2   0   0  48   7]
- [ 16   0   5   5   4  14  88]]
-Node Classification on random seed  8649 -> 0.593
-Confusion Matrix:
- [[ 60   4  10   5   5  12   8]
- [  4 128  10   2   6   3   3]
- [ 24  27 143  28  27  19  50]
- [  8   7  14 103   8   5  28]
- [  2   5   3   1  52   0   5]
- [  4   0   6   0   2  50   3]
- [  7   7  20   5   3  17  57]]
-Node Classification on random seed  8650 -> 0.65
-Confusion Matrix:
- [[ 86   3   3  14   4   8   8]
- [  5 133   4   3   6   6   0]
- [ 32  19 147  22  22  38  29]
- [ 11   3  15 100   6   8  12]
- [  2   4   5   5  56   1   1]
- [  7   0   0   0   1  54   3]
- [  9   3   9   5   3  11  74]]
-Node Classification on random seed  8651 -> 0.656
-Confusion Matrix:
- [[ 67   5   5   3   2  21   8]
- [  4 127   9   7   8   1   4]
- [ 19  36 149  32  20  13  37]
- [ 11   1   9 122   4   2   5]
- [  1   5   8   0  61   2   2]
- [  7   1   1   0   1  39   5]
- [  7   7   1   9   7  14  91]]
-Node Classification on random seed  8652 -> 0.585
-Confusion Matrix:
- [[ 76   3   9   7   2  11   1]
- [ 10 122   1   4  14   2   7]
- [ 23   7 121  35  39  19  60]
- [ 24   2  37  77   8   6   8]
- [  3   4   2   2  64   0   4]
- [  4   2   0   4   4  45   5]
- [ 13   2   3   5   6  13  80]]
-Node Classification on random seed  8653 -> 0.597
-Confusion Matrix:
- [[ 71   7   1   1   8   9   7]
- [  2 151   4   4   6   9   5]
- [ 33  15 141  38  31  21  30]
- [ 37   1   7  68   5   8  30]
- [  4   7   4   2  55   0   3]
- [  3   0   0   2   2  32  11]
- [  5   2  10  14   5  10  79]]
-Node Classification on random seed  8654 -> 0.601
-Confusion Matrix:
- [[ 66   3   4   5   4  24   9]
- [ 19 104   4   3   8   2   4]
- [ 24  27 158  13  22  26  49]
- [  8   0  24 110   2   4  13]
- [  4   4   4   1  59   0   2]
- [  8   2   3   0   2  42   6]
- [ 14   1   9  16  11  11  62]]
-Node Classification on random seed  8655 -> 0.648
-Confusion Matrix:
- [[ 53   1   6  11   2   6  15]
- [  4 113   8   6   4   7   6]
- [ 17  13 172  28  31  20  46]
- [  4   4  25 118   1   8   8]
- [  2   6   3   0  69   0   3]
- [  1   1   0   5   1  51   8]
- [  8   1   7  10   4  11  72]]
-Node Classification on random seed  8656 -> 0.626
-Confusion Matrix:
- [[ 68   2   1   3   4  14  14]
- [  6 140   2   1  13   3   1]
- [ 13  14 138  25  39  40  35]
- [  8   0  21 109   1   8   3]
- [  1   7   1   3  62   2   3]
- [  5   1   3   5   1  47   3]
- [ 19   1  10   3  14  21  62]]
-Node Classification on random seed  8657 -> 0.627
-Confusion Matrix:
- [[ 78   3   5   6   7  13   3]
- [  2 118   4   1  20   3   4]
- [ 21  25 169  30  25  18  30]
- [ 19   1  17  88   3   6  16]
- [  1   8   3   0  61   0   2]
- [  4   3   4   2   2  35   6]
- [ 14   2   8  10   4  18  78]]
-Node Classification on random seed  8658 -> 0.616
-Confusion Matrix:
- [[ 69   5  11   9   2   9   7]
- [  4 129   8   0   5   1   7]
- [ 16  36 135  21  27  21  45]
- [ 10   6  13 105   9   5   8]
- [  2   5   8   0  60   0   5]
- [ 11   3   2   4   0  45   5]
- [ 11   3  16  16   3   5  73]]
-Node Classification on random seed  8659 -> 0.589
-Confusion Matrix:
- [[ 71   2   1   3   7  15   4]
- [  5 117   1   2  26   5   0]
- [ 28  15 136  21  34  21  46]
- [ 20   2  18  95  10  14  11]
- [  3   3   3   0  60   3   4]
- [ 11   0   6   0   3  42   2]
- [  6   4   6  12  10  24  68]]
-Node Classification on random seed  8660 -> 0.625
-Confusion Matrix:
- [[ 68   1  12   8   3  15   1]
- [  8 108   7   4  16   1   6]
- [ 34  12 177  29  21  27  30]
- [  8   1  15  96   4   7  14]
- [  3   2   4   0  60   4   3]
- [  3   0   2   0   1  33   7]
- [ 22   2  12   7   5  14  83]]
-Node Classification on random seed  8661 -> 0.619
-Confusion Matrix:
- [[ 88  10   2   8   7   9   6]
- [  3 131   5   1  13   1   0]
- [ 15  28 133  36  33  33  43]
- [  9   4  10  80   6  10  16]
- [  1   7   2   0  58   0   1]
- [  6   0   0   1   0  51   8]
- [ 18   2   8   9   3   7  78]]
-Node Classification on random seed  8662 -> 0.589
-Confusion Matrix:
- [[ 55   3   7  12   5  16  16]
- [  4 125   1   6   8   7   3]
- [ 19  17 161  46  18  26  19]
- [ 21   1  18  85   4  20  15]
- [  7   3   3   1  53   0   5]
- [ 12   1   0   1   1  46   3]
- [  9   3   6   9  11  24  64]]
-Node Classification on random seed  8663 -> 0.613
-Confusion Matrix:
- [[ 69   4  13   3   3   8  12]
- [  2 127   6   4  10   2   1]
- [ 13   9 134  56  35  29  50]
- [ 12   4  14 109   4   2   8]
- [  1   1   1   2  59   0   6]
- [  4   2   0   0   1  54   5]
- [  8   2  19  13   5  13  61]]
-Node Classification on random seed  8664 -> 0.641
-Confusion Matrix:
- [[ 74   1   1   3   4  16   3]
- [  6 130   3   1   6   2   2]
- [ 17  18 143  25  23  27  56]
- [ 15   5   6 117   8   9  12]
- [  1  11   5   0  67   3   1]
- [  1   2   1   1   0  39   3]
- [ 14   8  13   3   8  15  71]]
-Node Classification on random seed  8665 -> 0.628
-Confusion Matrix:
- [[ 61   4  18   3   3  15   6]
- [  9 149   2   4   4   4   3]
- [ 11  21 145  44  20  18  33]
- [  6   2  19  99  12   4  22]
- [  3  15   3   1  51   1   1]
- [  3   2   5   1   2  47   6]
- [  6   4  12   5   0  15  76]]
-Node Classification on random seed  8666 -> 0.622
-Confusion Matrix:
- [[ 57   1   4   6   3  10  15]
- [  5 106   9   3  19   6   6]
- [ 22  27 150  40  31  14  24]
- [ 10   4  10 116   9   4   9]
- [  7   1   3   2  68   1   5]
- [  5   1   3   0   0  37   7]
- [  6   3   7   7  12  17  88]]
-Node Classification on random seed  8667 -> 0.596
-Confusion Matrix:
- [[ 57   0  14   1   5  19   7]
- [  8 136   4   3   5   2   1]
- [ 19  28 131  47  36  27  23]
- [ 26   1   6  94  14  11   6]
- [  3   2   3   0  68   0   2]
- [  6   1   2   4   1  49   3]
- [ 15   5  11   8   5  20  61]]
-Node Classification on random seed  8668 -> 0.648
-Confusion Matrix:
- [[ 77   3   2   5   5  11   3]
- [  4 124   9   7  14   1   2]
- [ 20  16 150  49  40   9  16]
- [  7   0  17 115   4   7  14]
- [  1   4   0   0  63   0   2]
- [  7   1   2   2   0  54   3]
- [ 23   6   9  11   7   9  65]]
-Node Classification on random seed  8669 -> 0.606
-Confusion Matrix:
- [[ 65   1   1   7   4   5  14]
- [  4 146   3   1   9   6   0]
- [ 26  25 129  34  29  27  41]
- [ 17   9  14  97   7   6   8]
- [  0   8   1   1  58   1   5]
- [  6   3   4   5   1  44   3]
- [ 12   3   4  14   7  18  67]]
-Node Classification on random seed  8670 -> 0.575
-Confusion Matrix:
- [[ 77   4   2  11   9   6  12]
- [  2 114   5   7   8   3   3]
- [ 23  43 119  43  26  19  42]
- [  1   2  17 107  11   6  10]
- [  0   4   2   2  47   0   4]
- [  6   5   6   5   3  38   5]
- [  6   5  14  19  18   6  73]]
-Node Classification on random seed  8671 -> 0.575
-Confusion Matrix:
- [[ 55   0  15  21   4  11   7]
- [ 11 124  12   0  11   0   2]
- [ 25  13 152  32  22  26  37]
- [ 13   7  24  79   6  12   8]
- [  0   1  10   0  73   1   1]
- [  4   3   2   2   2  34  16]
- [ 15   2  17  10   8  12  58]]
-Node Classification on random seed  8672 -> 0.647
-Confusion Matrix:
- [[ 69   6   3   3   3   9  18]
- [  5 131   5   2   3   2   4]
- [ 15  17 164  13  15  33  37]
- [ 15   3  19  87   4   6  23]
- [  3  10   6   1  50   1   1]
- [  1   0   3   3   1  49   5]
- [ 13   5  16   3  10   8  97]]
-Node Classification on random seed  8673 -> 0.594
-Confusion Matrix:
- [[ 58   2   1  13   6   9  14]
- [  6 128   4   3   7   2   3]
- [ 35  19 157  39  31  18  35]
- [  5   3  13  94   7  13  17]
- [  4   8   3   1  50   0   2]
- [  8   1   5   4   0  41   3]
- [ 14   7   5   7  12  17  66]]
-Node Classification on random seed  8674 -> 0.595
-Confusion Matrix:
- [[ 65   2   7  11   4  22  11]
- [  3 130   4   7   2   2   5]
- [ 23  27 137  40  14  13  42]
- [ 12   2  25  91   5  14  15]
- [  1   7   5   1  57   1   3]
- [ 11   4   2   0   2  36   2]
- [  9   8  12   5   4  16  79]]
-Node Classification on random seed  8675 -> 0.633
-Confusion Matrix:
- [[ 89   2   6   2   2  11   7]
- [  3 127   9   7   8   0   5]
- [ 19  24 142  23  20  23  47]
- [ 13   6   5  95  12   6  14]
- [  0   6   3   7  57   0   2]
- [  4   1   5   4   0  42   2]
- [ 16   2  15   5   7  14  81]]
-Node Classification on random seed  8676 -> 0.606
-Confusion Matrix:
- [[ 67   8   5   6   1   7  15]
- [  4 118   5   2  10   3  10]
- [ 31  17 129  40  18  20  40]
- [ 17   3  16 102   1   8  23]
- [  2   4   6   1  67   0   2]
- [  9   0   6   2   0  42   1]
- [ 11   2  11   9   7  11  81]]
-Node Classification on random seed  8677 -> 0.603
-Confusion Matrix:
- [[ 63   0   5   5   4  14  11]
- [  3 122  10   4   7   8   4]
- [ 18  14 141  50  46  17  30]
- [  3   4  14 109  10   6  17]
- [  1  10   6   0  54   1   2]
- [  7   1   4   0   0  38   8]
- [ 10   2  10   8   7  16  76]]
-Node Classification on random seed  8678 -> 0.592
-Confusion Matrix:
- [[ 69   3   4  12   8  12   3]
- [  5 123   4   5  10   9   0]
- [ 21  20 124  30  59  14  43]
- [ 16   1  27  87  11   6   9]
- [  1  10   2   1  59   0   3]
- [  2   1   0   0   0  49   6]
- [ 13   1   7   4   8  17  81]]
-Node Classification on random seed  8679 -> 0.619
-Confusion Matrix:
- [[ 59   1   4   3   6  14  11]
- [  7 124   6   1   2   2   8]
- [ 20  31 145  22  29  11  53]
- [ 19   5  23 100   6   8   9]
- [  0   6   5   2  52   1   2]
- [  9   1   0   0   0  51   3]
- [ 16   4   6   1   8  16  88]]
-Node Classification on random seed  8680 -> 0.632
-Confusion Matrix:
- [[ 69   2   4   2   9  16  16]
- [  0 132  15   0   6   1   2]
- [ 26  20 148  26  16  35  40]
- [  2   1  19 102   5   3  11]
- [  3   8   4   2  65   1   2]
- [  7   0   3   3   0  47   4]
- [ 17   0   2   7   6  22  69]]
-Node Classification on random seed  8681 -> 0.598
-Confusion Matrix:
- [[ 63   8   5   1   4  11  11]
- [  8 140   7   2   4   2   4]
- [ 27  39 115  24  28  33  37]
- [  7   2  17  98   4   9  22]
- [  3   5   3   3  60   1   3]
- [  0   0   4   0   1  40   9]
- [ 13   7  10   5   6  13  82]]
-Node Classification on random seed  8682 -> 0.57
-Confusion Matrix:
- [[ 63   1   3   3  10  11  11]
- [  4 120  16   1  12   8   5]
- [ 24  24 130  47  23  25  56]
- [ 13  10  19  89   7   9  14]
- [  2   6   6   1  60   0   5]
- [  3   2   4   0   1  32   5]
- [ 11   4   5   4   2  13  76]]
-Node Classification on random seed  8683 -> 0.591
-Confusion Matrix:
- [[ 62   7   0   1   6   6  32]
- [  9 125   8   2  13   5   5]
- [ 27   9 105  56  34  24  42]
- [  7   0  12 124   7   2  15]
- [  1   5   2   0  60   0   4]
- [  3   2   7   0   7  41   3]
- [ 11   2   9   2   9  13  74]]
-Node Classification on random seed  8684 -> 0.649
-Confusion Matrix:
- [[ 47   6   5   5   3  25   3]
- [  9 129   4   2   8   5   1]
- [ 19  16 163  23  29  21  34]
- [  7   2  21 114   2   7   5]
- [  1   5   4   7  68   3   1]
- [  1   3   2   4   3  53   2]
- [  6   3  11   6  12  15  75]]
-Node Classification on random seed  8685 -> 0.626
-Confusion Matrix:
- [[ 79   6   6   0   0   9   4]
- [  4 141   1   1   6   7   6]
- [ 26  20 130  33  16  32  51]
- [ 16   3  10  99   5   8  16]
- [  1   2   2   5  61   0   3]
- [ 11   0   3   1   0  54   6]
- [ 20   4   5   3   9  13  62]]
-Node Classification on random seed  8686 -> 0.628
-Confusion Matrix:
- [[ 60   1   9   2   2  15  16]
- [  5 137  10   1   3   3   6]
- [ 24  19 152  39  20  22  26]
- [ 26   6  10  98   9   9  11]
- [  1   1   2   2  57   2   1]
- [  0   2   1   0   9  52   3]
- [ 11   3   7  15   5  13  72]]
-Node Classification on random seed  8687 -> 0.591
-Confusion Matrix:
- [[ 64   3   7   5   4   9  18]
- [  2 147   8   3   3   3   7]
- [ 18  33 124  49  31  20  47]
- [ 10   7  16  77   5   4  19]
- [  0   5   2   5  65   0   2]
- [  3   1   3   1   2  43   6]
- [  5   6  12   3   9  13  71]]
-Node Classification on random seed  8688 -> 0.61
-Confusion Matrix:
- [[ 55   0   2   7   2  14  11]
- [  1 136   6   4   7   7   3]
- [ 28  33 125  32  25  28  36]
- [  8   3  10 109   1   9  12]
- [  5  10   6   3  57   1   2]
- [  7   4   3   1   0  47   1]
- [ 11   4  14   4   8  17  81]]
-Node Classification on random seed  8689 -> 0.595
-Confusion Matrix:
- [[ 66   2   1  18   6  13   7]
- [  8 116   9   5   6   4   0]
- [ 30  24 133  28  35  25  34]
- [ 17   1  24 100  10   5  13]
- [  1  10   1   3  58   2   2]
- [  4   1   1   4   0  41   7]
- [  8   3   7   4   7  15  81]]
-Node Classification on random seed  8690 -> 0.599
-Confusion Matrix:
- [[ 54   3  13   2   2  15  24]
- [  5 125   3   3  10   1   3]
- [ 14  19 132  20  44  27  49]
- [  5   5  17 106   4   4  15]
- [  4   9   4   0  62   2   3]
- [  6   3  10   0   0  39   1]
- [ 11   4  12  11   2  12  81]]
-Node Classification on random seed  8691 -> 0.599
-Confusion Matrix:
- [[ 62   3   3   3   2  11  12]
- [  3 125   7   0   6   7   3]
- [ 28  22 133  33  42  19  45]
- [  9   9  14  98   9  13   8]
- [  2   2   3   2  58   1   4]
- [  9   3   5   4   1  51   2]
- [ 11   2   2  14   8  15  72]]
-Node Classification on random seed  8692 -> 0.609
-Confusion Matrix:
- [[ 76   2   3   2   4   6  13]
- [  4 124  13   5   6   0   1]
- [ 38  16 132  39  51  15  32]
- [ 11   3   9  92  15   8   9]
- [  1   3   6   2  54   0   1]
- [  4   0   2   1   0  55   2]
- [ 22   3   8   2  11  18  76]]
-Node Classification on random seed  8693 -> 0.634
-Confusion Matrix:
- [[ 75   3   2   4   5   4  20]
- [  2 122   5   2   6   8   4]
- [ 36  24 151  19  25  28  44]
- [ 15   3  10 103   6   1   8]
- [  0   5   5   3  58   1   1]
- [  7   0   0   6   1  42   7]
- [  8   5   5   2  17   9  83]]
-Node Classification on random seed  8694 -> 0.628
-Confusion Matrix:
- [[ 67   2   5   9   2  12   6]
- [  1 144   9   0   4   3   1]
- [ 42  17 123  29  35  35  29]
- [ 13   3  13 100   9   9  11]
- [  0   9   1   1  76   1   3]
- [  5   2   1   2   0  40   5]
- [ 11   1   6   3   7  15  78]]
-Node Classification on random seed  8695 -> 0.643
-Confusion Matrix:
- [[ 68   6   2   7   5  20   9]
- [  0 122   5   1  13   2   4]
- [ 19  18 151  35  23  23  28]
- [  7   6  15 113   6  11   5]
- [  0   9   4   0  66   1   0]
- [  7   2   0   0   1  45   5]
- [ 12   6  13   7   8  12  78]]
-Node Classification on random seed  8696 -> 0.59
-Confusion Matrix:
- [[ 71   4   8   2  12   7   7]
- [  3 137   3   5   5   5   2]
- [ 31  24 139  52  24  17  38]
- [  6   3  16  74  12   5  14]
- [  2   7   6   0  58   0   3]
- [ 15   2  11   1   4  39   3]
- [ 14   4  15   3   2  13  72]]
-Node Classification on random seed  8697 -> 0.578
-Confusion Matrix:
- [[ 56   1   4  10   7  17  13]
- [  1 127   1   5  12   3   4]
- [ 33  33 113  62  25  28  31]
- [  8   4  13 105   1   6  16]
- [  2   7   5   1  59   0   0]
- [  7   1   3   1   0  51   3]
- [ 16   3  11   5   4  15  67]]
-Node Classification on random seed  8698 -> 0.618
-Confusion Matrix:
- [[ 69   2   2   3   6  13   7]
- [  6 122   2   0   9   0   3]
- [ 19  25 132  39  24  30  46]
- [ 14   2   9 105  10   2  12]
- [  3   8   7   1  69   1   4]
- [  7   1   3   2   0  44   5]
- [ 12   5  11   5   9  13  77]]
-Node Classification on random seed  8699 -> 0.611
-Confusion Matrix:
- [[ 83   3   7   4   4   9   9]
- [  6 133   5   2   2   2   5]
- [ 31  19 135  64  17  32  23]
- [  7   3  23  97   4   6  20]
- [  2   6   3   3  50   2   2]
- [  5   2   4   2   1  41   1]
- [  8   3  10   7   3  18  72]]
-Node Classification on random seed  8700 -> 0.6
-Confusion Matrix:
- [[ 64   4   5   9   6  12  10]
- [  3 120   8   8   7   9   0]
- [ 30  24 139  26  23  27  37]
- [  9   8  20  98   3  11  13]
- [  1   6   8   2  57   1   3]
- [  4   1   6   1   1  43   5]
- [  7   3   8   2  12  17  79]]
-Node Classification on random seed  8701 -> 0.607
-Confusion Matrix:
- [[ 69   2   5   7   2  12  11]
- [  5 121   5   1  10   4   1]
- [ 27  25 123  54  17  23  47]
- [  3   0  20 116   7  11  11]
- [  1   7   6   1  66   0   2]
- [  5   0   2   0   1  41   8]
- [ 14   2   1   9   5  19  71]]
-Node Classification on random seed  8702 -> 0.62
-Confusion Matrix:
- [[ 63   2   1   3   1   8  13]
- [  8 119   4   1  11   0   9]
- [ 42  20 151  21  33  22  26]
- [ 22   2  20 104   2  11  10]
- [  1   3   3   2  72   0   4]
- [  5   2   2   1   0  34  12]
- [ 13   2  10   0   8  20  77]]
-Node Classification on random seed  8703 -> 0.613
-Confusion Matrix:
- [[ 68   2   4   6   2  11  10]
- [  4 132   7   2   8   1   4]
- [ 25  26 151  56  16  16  26]
- [ 14  11  20  93   3   3   4]
- [  1   6   7   0  70   0   5]
- [  2   1   0   4   2  35   8]
- [ 18   6  12  20   5   9  64]]
-Node Classification on random seed  8704 -> 0.633
-Confusion Matrix:
- [[ 75   1   1   9   3  14  13]
- [  9 130   6   6  10   4   1]
- [ 17  12 140  23  35  36  36]
- [ 10   5  18 116   8   7   6]
- [  1   3   3   1  61   1   0]
- [  3   0   1   3   3  47   8]
- [  6   4  13   0  13  14  64]]
-Node Classification on random seed  8705 -> 0.612
-Confusion Matrix:
- [[ 64   1   7   2   4  13  14]
- [  8 118   4   5   8   3  13]
- [ 17  15 138  38  36  12  35]
- [ 15   7  10 106  23  10   5]
- [  0   6   4   5  62   1   3]
- [  5   1   5   0   1  42   5]
- [ 11   2   6   3  10  15  82]]
-Node Classification on random seed  8706 -> 0.609
-Confusion Matrix:
- [[ 86   6   2  15   6   6   3]
- [  5 123   7   1   6   0   5]
- [ 28  24 155  43  31  23  27]
- [ 14   2  26  90   8   8   9]
- [  2   5   5   2  54   0   1]
- [ 13   3   2   0   2  44   1]
- [ 21   3   3   8   6   9  57]]
-Node Classification on random seed  8707 -> 0.602
-Confusion Matrix:
- [[ 97   5   0   4   7  11  18]
- [  2 130   1   0   4   4  13]
- [ 19  38 109  19  44  28  39]
- [  4  12  26  81   3   4   8]
- [  1   4   5   0  62   0   2]
- [ 11   1   1   0   0  42   3]
- [ 21   6   7  11   4   8  81]]
-Node Classification on random seed  8708 -> 0.634
-Confusion Matrix:
- [[ 73   0   8   5   1  20  11]
- [  4 133   3   1   9   6   1]
- [ 17  23 144  49  30  13  36]
- [  5   2   8  96   3  11  11]
- [  2   9   3   2  63   2   6]
- [  0   0   3   3   1  54   5]
- [ 10   2  11  11  13   6  71]]
-Node Classification on random seed  8709 -> 0.627
-Confusion Matrix:
- [[ 71   3   5  11   4   6   7]
- [ 10 139   3   0   7   0   2]
- [ 25  17 150  36  24  22  35]
- [ 14   8  13  99  12   5   9]
- [  3   5   0   2  60   1   2]
- [  4   2   2   1   1  36   6]
- [ 21   4   8   5   8  20  72]]
-Node Classification on random seed  8710 -> 0.594
-Confusion Matrix:
- [[ 73   1   5   9   2  14   9]
- [  6 120   7   9   5   4   8]
- [ 11  13 148  48  23  15  36]
- [  8   6  18  99   8   5  18]
- [  1   5   6   3  57   2   4]
- [ 10   2   3   2   0  41  12]
- [  9   1   9   8  25  16  56]]
-Node Classification on random seed  8711 -> 0.608
-Confusion Matrix:
- [[ 78   5   3   3   2  14  13]
- [  4 120   7   3   3  10   1]
- [ 18  19 144  32  22  28  27]
- [  8   5  23  92  26  11  11]
- [  4   4   6   0  64   0   1]
- [  2   0   3   3   8  32   6]
- [ 12   6   7   7   8  17  78]]
-Node Classification on random seed  8712 -> 0.627
-Confusion Matrix:
- [[ 69   4   8   8   4  17  12]
- [  6 130   9   0  10   5   6]
- [ 19  23 115  33  33  17  38]
- [ 16   2  19 112   1   3   9]
- [  2   5   6   0  59   1   8]
- [  2   0   1   1   0  50   9]
- [  4   4  10   6   4   8  92]]
-Node Classification on random seed  8713 -> 0.611
-Confusion Matrix:
- [[ 75   0   2   2   7  12  13]
- [  3 110   7   9   1   2   3]
- [ 33  23 140  55  10  27  34]
- [ 12   1  15 100   4  12  20]
- [  3   6   6   1  42   4   0]
- [  1   0   0   2   0  52   5]
- [ 11   2   7   3   9  22  92]]
-Node Classification on random seed  8714 -> 0.597
-Confusion Matrix:
- [[ 62   1   5   2   5  12   7]
- [  4 131   1   4  11   1  12]
- [  6  27 132  32  23  39  61]
- [  7   3  12 103   2  13  10]
- [  0   8   2   4  57   3   2]
- [  3   1   5   0   2  46  13]
- [ 14   2   8   8   9  19  66]]
-Node Classification on random seed  8715 -> 0.629
-Confusion Matrix:
- [[ 66   1   5   5   3  16   6]
- [  5 122   5   5   5   1   1]
- [ 12  26 148  44  33  18  40]
- [ 14   1  19 110   4   2  12]
- [  1   9   1   1  65   0   3]
- [  5   1   1   3   3  37   8]
- [ 13   4   9   4  10  12  81]]
-Node Classification on random seed  8716 -> 0.623
-Confusion Matrix:
- [[ 67   3   3   9   0  15  21]
- [  2 117   7   2  14   5   5]
- [  6  20 156  26  33  25  42]
- [  5  10  20  97   6   5  20]
- [  0   3   6   1  71   1   1]
- [  2   1   6   2   1  45   7]
- [  6   2   8   7   7  12  70]]
-Node Classification on random seed  8717 -> 0.631
-Confusion Matrix:
- [[ 54   1   3   1   1  17   8]
- [ 11 111  14   1   9   0   3]
- [ 22  21 153  22  38  16  36]
- [ 10   7  16 113   4   6  16]
- [  1   5   3   3  63   0   2]
- [  4   1   0   1   3  48  10]
- [  9   5   6   8  10  15  89]]
-Node Classification on random seed  8718 -> 0.648
-Confusion Matrix:
- [[ 73   7   3   6   4  14   8]
- [  2 131   2   2   2   0   6]
- [ 20  15 162  25  26  18  48]
- [ 16   3  15  92  11  12  23]
- [  3   4   4   1  59   0   2]
- [  6   0   3   2   3  41   2]
- [  3   5  11   5   1   9  90]]
-Node Classification on random seed  8719 -> 0.631
-Confusion Matrix:
- [[ 59   2   6  12   3   9  13]
- [ 16 111   2   4  10   1   2]
- [ 26  16 151  38  17  15  61]
- [  7   4   7 124   3   1  16]
- [  2   4   3   1  62   0   5]
- [  6   2   1   1   0  46   5]
- [ 12   1  12  10   2  11  78]]
-Node Classification on random seed  8720 -> 0.611
-Confusion Matrix:
- [[ 76   1   3   7   3  10  10]
- [  7 137   4   3   2   4   2]
- [ 14  29 138  32  43  25  41]
- [  1   9  16  88   3   7  19]
- [  3  11   4   1  57   1   0]
- [  8   2   0   0   0  43  10]
- [  8   2  14   8  16   6  72]]
-Node Classification on random seed  8721 -> 0.613
-Confusion Matrix:
- [[ 58   2   5   6   2  13   5]
- [  5 146   1   3  11   5   6]
- [ 21  31 131  37   8  16  44]
- [  8   3  10  98  14  10  20]
- [  2   4   4   1  55   1   4]
- [  4   1   2   6   1  46   6]
- [ 12   3  13  11   2  24  79]]
-Node Classification on random seed  8722 -> 0.602
-Confusion Matrix:
- [[ 75   0   3   3   6  14   6]
- [  0 114   5   1   4   7   9]
- [ 31  18 141  22  45  25  34]
- [ 14   2  12  96   7   5  24]
- [  1   8   3   0  60   0   3]
- [  9   0   4   5   1  44  10]
- [ 17   3   3   8  10  16  72]]
-Node Classification on random seed  8723 -> 0.594
-Confusion Matrix:
- [[ 62   1   1  12   3  11  12]
- [  6 136   4   4   2   3   2]
- [ 30  28 132  23  25  19  70]
- [ 16   7  10 104   7   5  14]
- [  2   6   3   1  54   0   2]
- [  4   1   7   1   1  44   8]
- [  6   5   5  19   6  14  62]]
-Node Classification on random seed  8724 -> 0.668
-Confusion Matrix:
- [[ 85   1   0   3   3   9   5]
- [  5 132  14   2  10   2   2]
- [ 24  17 163  19  22  24  51]
- [  9   4   7 104  17   4   7]
- [  1   7   3   0  64   1   4]
- [  8   2   0   2   0  43   4]
- [ 11   2   7   2   6  11  77]]
-Node Classification on random seed  8725 -> 0.656
-Confusion Matrix:
- [[ 70   4   2   4   3  13   3]
- [  2 133   4   2   8   4   1]
- [ 22  31 164  22  17  18  41]
- [ 14   7  13 113   4   5   9]
- [  0   7   5   0  62   0   2]
- [ 10   2   0   0   2  48   5]
- [  7   7   9  10   4  21  66]]
-Node Classification on random seed  8726 -> 0.606
-Confusion Matrix:
- [[ 60   8   9  10   5  12  17]
- [  2 135   3   0   8   3   3]
- [ 24  21 144  41  23  25  30]
- [ 13   2  17  95  10  11   9]
- [  2   9   1   3  64   1   2]
- [  2   3   1   1   0  50   4]
- [ 13   4  13   9   5  15  58]]
-Node Classification on random seed  8727 -> 0.631
-Confusion Matrix:
- [[ 57   7   4   7   1  20  11]
- [  2 140   8   2   7   4   4]
- [ 20  20 147  38  20  31  34]
- [ 11   3  16 102   2  20   6]
- [  0   8   6   0  65   2   3]
- [  1   0   5   4   0  46  11]
- [  6   3   5   3   3  11  74]]
-Node Classification on random seed  8728 -> 0.622
-Confusion Matrix:
- [[ 66   0  13   6   4  10  17]
- [  5 121   4   2  12   1   6]
- [ 30  29 148  21  26  11  34]
- [  7   4  26  99   0   3  14]
- [  1  10   4   3  68   0   2]
- [  5   2   4   1   0  40   7]
- [  6   3  13   4   8  20  80]]
-Node Classification on random seed  8729 -> 0.591
-Confusion Matrix:
- [[ 66   2   4  14   2  15  21]
- [  4 115   3   2   5   2   8]
- [ 19  27 134  36  28  20  52]
- [  8   8  23  95  12   7   4]
- [  1   4   5   1  60   0   2]
- [  8   5   1   2   1  39   3]
- [ 16   1   7   9   9   8  82]]
-Node Classification on random seed  8730 -> 0.604
-Confusion Matrix:
- [[ 72   9   1   4   2  15  19]
- [  6 126   9   2   2   2   4]
- [ 21  24 131  26  25  36  41]
- [  8   6  18 110   5  14   7]
- [  2   2   2   0  55   0   1]
- [ 10   1   2   2   2  34  10]
- [ 10   7   7   9   5  18  76]]
-Node Classification on random seed  8731 -> 0.617
-Confusion Matrix:
- [[ 72   3   3   6   2  23   5]
- [  5 115   0   0  14   4   4]
- [ 19  23 162  20  20  19  51]
- [ 12   5  18  93  12   5  16]
- [  1   7   5   0  60   0   5]
- [  6   4   1   2   0  46   4]
- [  9   2   7  13   7  21  69]]
-Node Classification on random seed  8732 -> 0.623
-Confusion Matrix:
- [[ 64   6   2   1   3   7  18]
- [  2 123   7   3   8   4   4]
- [ 18  32 141  32  21  31  52]
- [ 10   4  14 106   8   6  17]
- [  0   9   7   0  59   2   1]
- [  4   2   2   0   0  47   9]
- [  5   2   7   1   5  11  83]]
-Node Classification on random seed  8733 -> 0.612
-Confusion Matrix:
- [[ 66   2  12   7   2  15   1]
- [  2 121   7   4  13   3   4]
- [ 28  28 133  37  24  30  30]
- [  7   1  21 115   1   7  10]
- [  0   7   2   7  61   2   4]
- [  3   0   8   0   1  47   4]
- [  7   3   9  12   1  22  69]]
-Node Classification on random seed  8734 -> 0.593
-Confusion Matrix:
- [[ 64   2   4   9   3  24   8]
- [  4 130   5   9   9   3   2]
- [ 28   7 124  39  46  23  29]
- [ 21   6  21  86   5   8  15]
- [  1   8   0   1  59   4   1]
- [  5   1   2   1   0  49   2]
- [ 11   3  10   4   9  14  81]]
-Node Classification on random seed  8735 -> 0.617
-Confusion Matrix:
- [[ 65   2   4   5   7  11  20]
- [ 10 129   5   2   7   3  11]
- [ 11  22 133  33  29  22  49]
- [  5   5  12 110  11   6  16]
- [  0   9   6   0  59   0   2]
- [  3   1   2   2   2  51   2]
- [  4   1   1  24   9   7  70]]
-Node Classification on random seed  8736 -> 0.619
-Confusion Matrix:
- [[ 76   5   4   3   8   3  25]
- [  4 134   8   1   7   0   1]
- [ 24  16 141  39  25  18  36]
- [ 11   2  24 110   0   6  11]
- [  1   4  12   3  50   2   1]
- [ 10   0   7   0   0  37   3]
- [ 15   7   9  10   5  11  71]]
-Node Classification on random seed  8737 -> 0.621
-Confusion Matrix:
- [[ 74   6   7   4   1   8   4]
- [  3 141   2   0  20  13   2]
- [ 24  20 119  37  45  19  29]
- [  9   3  12 111   5   6  12]
- [  2   4   2   1  61   1   3]
- [  3   2   1   0   2  49   3]
- [ 20   8  11   8   8   9  66]]
-Node Classification on random seed  8738 -> 0.601
-Confusion Matrix:
- [[ 58   1   1  14  11   5  15]
- [ 15 117   9   0  10   2   3]
- [ 39  22 146  18  21  14  51]
- [  8   5  11 110   9   4  13]
- [  3   7   4   1  60   0   4]
- [  3   3   4   0   0  47   5]
- [ 14   2   9  18   5  16  63]]
-Node Classification on random seed  8739 -> 0.622
-Confusion Matrix:
- [[ 68   5   1   8   4   6  14]
- [  5 124   5  11   8   4   3]
- [ 27  26 128  28  33  16  32]
- [ 28   4   8 102   6   3  11]
- [  1   9   6   1  57   2   3]
- [  1   1   1   5   0  52   9]
- [  5   6   6   6   9  11  91]]
-Node Classification on random seed  8740 -> 0.633
-Confusion Matrix:
- [[ 62   0   5  11   3  10  11]
- [  7 123   9   1   8   7   5]
- [ 12  29 140  24  46  18  55]
- [ 11   5   4 116   3   6  11]
- [  3   5   1   2  56   0   4]
- [  0   2   3   2   1  48   3]
- [  5   2   4   4  14  11  88]]
-Node Classification on random seed  8741 -> 0.612
-Confusion Matrix:
- [[ 57   2  18   4   0  11  16]
- [  5 123  13   3   3   2   0]
- [ 24  18 130  34  44  21  26]
- [ 10   4  14 118   1  10   9]
- [  1   4   3   1  64   1   3]
- [  6   4   4   0   2  45   2]
- [ 16   4  12  10   6  17  75]]
-Node Classification on random seed  8742 -> 0.602
-Confusion Matrix:
- [[ 55   6  13   9   4  10   8]
- [  9 126   7   5   8   0   1]
- [ 14  26 125  49  44  23  33]
- [  9   3  15 111   3   4  21]
- [  1   8   2   1  54   0   0]
- [  1   2   1   1   2  50   3]
- [  6   4   5  13   7  17  81]]
-Node Classification on random seed  8743 -> 0.566
-Confusion Matrix:
- [[ 60   5  10   8   2  11  15]
- [  1 108  10  13  10   2   1]
- [ 16  30 143  45  32  11  45]
- [ 14   5  22  89  10   7  12]
- [  0   6   4   2  52   1   4]
- [ 10   6   0   4   0  41   7]
- [  8   6   5   8   9  17  73]]
-Node Classification on random seed  8744 -> 0.636
-Confusion Matrix:
- [[ 85   2   1   5   2   6   7]
- [  4 116   4   4   3   5   3]
- [ 35  20 156  26  14  20  41]
- [ 12   8  17 106   6   7  23]
- [  5   7   6   1  53   2   2]
- [  6   2   0   1   0  48   3]
- [ 23   2   5   4   4  16  72]]
-Node Classification on random seed  8745 -> 0.59
-Confusion Matrix:
- [[ 70   1   6   4   4  19   6]
- [  1 141   5   6   5   1   1]
- [ 27  28 147  38  25  20  36]
- [ 21   5  20  75  18   5  14]
- [  0  11   6   0  50   2   3]
- [  7   0   6   2   2  39   4]
- [  8   3  10   4   3  23  68]]
-Node Classification on random seed  8746 -> 0.584
-Confusion Matrix:
- [[ 72   1   1   7   5   8   3]
- [  7 111  13   4  10   0   5]
- [ 19  24 130  48  41  20  47]
- [ 10   2  11 107   5   3  15]
- [  1   3   7   1  60   2   3]
- [  5   0   1   7   3  27  16]
- [  5   3   8   6  18  18  77]]
-Node Classification on random seed  8747 -> 0.606
-Confusion Matrix:
- [[ 67   3   1   4   4   3   6]
- [ 13 106   6   5  10   5   5]
- [ 23  31 158  32  22  21  40]
- [ 13   4   6 104   7   5  26]
- [  0   6   3   1  52   2   5]
- [  7   1   4   1   0  49   4]
- [ 21   2   5   5  18  14  70]]
-Node Classification on random seed  8748 -> 0.559
-Confusion Matrix:
- [[ 59   2   6   7   4  14  19]
- [  3 112  11   2  16   4   0]
- [ 29  24 119  34  28  20  56]
- [  8   5  11 103   7  12  27]
- [  2   7   3   1  56   1   1]
- [  6   0   5   2   5  48   6]
- [ 11   6   9   9   7  11  62]]
-Node Classification on random seed  8749 -> 0.611
-Confusion Matrix:
- [[ 73   1   3   7   4  12   2]
- [  5 132   1   3   5   1  12]
- [ 22  17 135  37  39  15  48]
- [  9   2  15  98   6   7  12]
- [  0   4   2   2  63   1   4]
- [  5   1   5   8   0  43   6]
- [  7   3  11  20   6  19  67]]
-Node Classification on random seed  8750 -> 0.622
-Confusion Matrix:
- [[ 47   9   6   5   3  19  16]
- [ 12 117   6   1   2   6   8]
- [ 10  25 175   7  30  38  45]
- [ 10   6  18  97   2   4  10]
- [  1   5   7   0  64   2   3]
- [  3   1   0   3   0  35  12]
- [  5   6   5   5   8  14  87]]
-Node Classification on random seed  8751 -> 0.624
-Confusion Matrix:
- [[ 83   5   3   2   3   7  16]
- [  9 133   0   4   6   5   3]
- [ 34  17 105  34  26  19  47]
- [ 11   0  11 122  10   4  14]
- [  3   4   5   3  58   0   2]
- [  8   1   0   3   0  40   4]
- [ 16   2  16   6   5   8  83]]
-Node Classification on random seed  8752 -> 0.626
-Confusion Matrix:
- [[ 77   0   3   4   1  20   7]
- [  5 120   7   2   7   4   2]
- [ 10  15 143  20  34  21  50]
- [ 17  10  13  98   3  11  12]
- [  3   7   3   3  72   0   1]
- [  6   0   5   0   0  50   4]
- [  7   4   9  22   8  14  66]]
-Node Classification on random seed  8753 -> 0.572
-Confusion Matrix:
- [[ 74   2  10   6   2  12   1]
- [  4 123   3   4  20   7   6]
- [ 25  36 118  50  25  24  41]
- [ 13   5  11 110   6   8   9]
- [  0   2   3   6  49   0   4]
- [  9   2   2   1   0  45   2]
- [ 20   5  16   4  12  10  53]]
-Node Classification on random seed  8754 -> 0.659
-Confusion Matrix:
- [[ 92   2   3   5   2   4   4]
- [  8 121   4   5  13   1   5]
- [ 28  11 146  48  22  14  27]
- [  9   1  17 116   8   3  12]
- [  1   3   3   0  57   0   1]
- [  3   3   4   3   4  43   7]
- [ 16   0  11   8   7  11  84]]
-Node Classification on random seed  8755 -> 0.635
-Confusion Matrix:
- [[ 80   3   8   4   1   6  15]
- [  5 119   1   2  11   2   2]
- [ 17  12 159  45  26   9  46]
- [ 11   4  17  93   6   1  15]
- [  0   3   3   0  61   0   4]
- [  6   2   4   2   0  48   4]
- [ 19   0  13   7   9  20  75]]
-Node Classification on random seed  8756 -> 0.616
-Confusion Matrix:
- [[ 77   2   5   9   0  13   6]
- [  6 129   7   3  15   3   6]
- [ 31  13 140  38  31  19  31]
- [  6   2  14 111   4   8  12]
- [  1   5   5   3  49   4   4]
- [  3   4   2   1   0  47   5]
- [ 12   4   4  13   7  23  63]]
-Node Classification on random seed  8757 -> 0.598
-Confusion Matrix:
- [[ 65   2   4  11   3   9  16]
- [  2 147   3   0   6   5   3]
- [ 20  27 144  39  21  46  32]
- [  9   3  23  84  12   2  10]
- [  1   1   8   3  45   0   1]
- [ 12   1   7   2   0  31   2]
- [  7   5  14   5   3  22  82]]
-Node Classification on random seed  8758 -> 0.629
-Confusion Matrix:
- [[ 66   1   8   4   4   9  12]
- [  7 139   6   5   9   3   2]
- [ 20  31 142  29  18  18  36]
- [ 11   5  24  95  10   3  16]
- [  1   6   5   1  53   0   4]
- [  6   2   1   0   0  49   3]
- [ 10   4  16   7   5   9  85]]
-Node Classification on random seed  8759 -> 0.584
-Confusion Matrix:
- [[ 73   1   6   5   3  15  11]
- [  9 112   7   1   9   3   8]
- [ 27  32 104  27  40  17  65]
- [  5   6   7 109   5   9  15]
- [  2   4   2   7  60   1   1]
- [  4   1   3   0   0  41   7]
- [ 15   3  15   6   4   8  85]]
-Node Classification on random seed  8760 -> 0.627
-Confusion Matrix:
- [[ 58   1   6   2   2  22  12]
- [  5 146   4   2   7   1   4]
- [ 32  32 140  31  20  16  32]
- [ 21   3  10  89   0  12  17]
- [  1   9   6   1  55   1   3]
- [  3   2   2   1   0  43   7]
- [ 12   7   1   2   5  16  96]]
-Node Classification on random seed  8761 -> 0.567
-Confusion Matrix:
- [[ 57   2   9   3   8  23   7]
- [ 23 102   7   1  17   6   3]
- [ 33  27 133  28  46  20  26]
- [  6   5  15  83  12   5   9]
- [  0   5   2   0  69   1   2]
- [  2   1   2   3   1  54   3]
- [ 11   3  14  19   6  17  69]]
-Node Classification on random seed  8762 -> 0.574
-Confusion Matrix:
- [[ 69   4   7  10   3  10  16]
- [  2 112   8   1  14   5   8]
- [ 23  19 123  30  43  28  40]
- [  8   3  29  95   1   6  19]
- [  1   6   4   0  73   1   4]
- [  5   1   1   6   0  39   8]
- [  8   4  15   4   6  15  63]]
-Node Classification on random seed  8763 -> 0.616
-Confusion Matrix:
- [[ 67   1   3   2   2  13  17]
- [  3 137   2   3   3   2   6]
- [ 24  28 121  67  25   6  54]
- [  7   6   2 110   4   5   9]
- [  1   6   2   1  59   1   2]
- [  5   1   2   5   1  36   7]
- [ 10   2   6  15  11  12  86]]
-Node Classification on random seed  8764 -> 0.619
-Confusion Matrix:
- [[ 70   4   7   6   1  10  16]
- [  1 116  10   5   7   2   2]
- [ 22  31 141  35  25  13  36]
- [ 10  11  17  99   1   8   5]
- [  4   9   2   3  57   0   2]
- [  4   4   6   0   0  56   2]
- [  5   7  15   7   5  21  80]]
-Node Classification on random seed  8765 -> 0.619
-Confusion Matrix:
- [[ 65   4   5   6   5   8   6]
- [  6 136  10   3   6   1   2]
- [ 27  21 150  30  32  31  28]
- [  7   3  13 115   6   5  14]
- [  3  11   4   3  61   2   0]
- [  7   0   2   0   4  37   3]
- [  7   4  17  11   3  21  55]]
-Node Classification on random seed  8766 -> 0.584
-Confusion Matrix:
- [[ 65   6   7   4   4  11  10]
- [  1 119  10   0  12   3   5]
- [ 37  17 135  18  37  25  49]
- [ 11   5  28 101   7   8  14]
- [  2   4   4   1  48   2   2]
- [ 10   2   9   1   0  36   4]
- [  9   1  13   2   6  15  80]]
-Node Classification on random seed  8767 -> 0.595
-Confusion Matrix:
- [[ 61   1   4  10   6  16  12]
- [  3 140   7   4   2   2   2]
- [ 26  19 127  52   7  22  36]
- [ 18   1  10  90  18   5  14]
- [  2   8   8   0  46   0   4]
- [  6   0   2   5   3  47  16]
- [ 18   4   8   9   7   8  84]]
-Node Classification on random seed  8768 -> 0.63
-Confusion Matrix:
- [[ 76  11   1   6   2   8  10]
- [  1 139   4   3   2   6   3]
- [ 17  12 144  28  21  26  47]
- [ 18   1  11 108   4   0  19]
- [  1   5   4   3  51   1   4]
- [  4   5   1   4   2  41   8]
- [ 11  10   2  19   8  17  71]]
-Node Classification on random seed  8769 -> 0.605
-Confusion Matrix:
- [[ 78   2   4   2   4  14  13]
- [  4 125   5   1   6   3  16]
- [ 22  22 114  26  59  22  28]
- [ 13   5  13 100   5   9  15]
- [  1   6   1   1  59   2   3]
- [  3   2   1   1   2  57   8]
- [ 14   5  16   3   5   8  72]]
-Node Classification on random seed  8770 -> 0.611
-Confusion Matrix:
- [[ 64   6   7  10   4   4  10]
- [  0 120  11   4  18   5   5]
- [ 27  14 141  53  15  12  49]
- [ 10   4  14 104   2   7  13]
- [  2   5   5   2  67   0   2]
- [  4   2   3   0   0  42   5]
- [ 11   8  13   9   4  10  73]]
-Node Classification on random seed  8771 -> 0.608
-Confusion Matrix:
- [[ 60   1   1  10   3  13  15]
- [  6 119  12   6   6   5   8]
- [ 29  25 126  33  25  44  11]
- [ 10   1   5 119   2  13  12]
- [  0   3   7   4  63   2   2]
- [ 10   0   0   3   1  44   7]
- [ 11   3  10  10   5  18  77]]
-Node Classification on random seed  8772 -> 0.627
-Confusion Matrix:
- [[ 66   2   3   3   1  11  12]
- [  3 121   3   2   8   2   6]
- [ 26  24 179  24  20  21  33]
- [  8   6  21  90  11   7  24]
- [  2   8   3   2  50   1   1]
- [  7   0   7   1   2  45   5]
- [ 13   1  10  15   8   6  76]]
-Node Classification on random seed  8773 -> 0.601
-Confusion Matrix:
- [[ 56   1   3   9   1   9  14]
- [  6 106   9  15  19   1  10]
- [ 24  15 144  44  22  27  29]
- [ 10   5  15  91  14   9  15]
- [  1   2   2   4  67   1   4]
- [  3   2   0   2   0  54   3]
- [ 10   3   2  11   6  17  83]]
-Node Classification on random seed  8774 -> 0.582
-Confusion Matrix:
- [[ 81   3   7   4   6  12   4]
- [  4 139   7   0   9   1   3]
- [ 28  24 116  38  37  21  42]
- [ 16   5  13  79  11  11  16]
- [  1  12   2   1  53   0   2]
- [ 11   3   6   0   1  47   3]
- [ 13   5   7   7   6  16  67]]
-Node Classification on random seed  8775 -> 0.613
-Confusion Matrix:
- [[ 69   3   5   3   7  13   4]
- [  6 114   6   0  12  10   3]
- [ 26  18 135  36  28  27  43]
- [  5   6   9 105   1   5  16]
- [  0   9   6   9  56   2   0]
- [  3   0   1   3   0  43  12]
- [  2   4   2  10  13  19  91]]
-Node Classification on random seed  8776 -> 0.609
-Confusion Matrix:
- [[ 74   3   1   8   3   8  13]
- [  6 112  11   4  11   3   1]
- [ 27  25 155  35  28  22  32]
- [ 11   4  22 106  13   1   9]
- [  4   9   4   2  56   2   1]
- [  6   1   2   0   1  42   6]
- [ 16   6   5   9   7   9  64]]
-Node Classification on random seed  8777 -> 0.626
-Confusion Matrix:
- [[ 71   1   2   4   1  11  22]
- [  2 117   5   7  19   4   1]
- [ 18  22 151  30  20  27  44]
- [  5   4  20  99   3   4  15]
- [  0   4   6   1  73   0   0]
- [  6   0   4   2   1  38  11]
- [  7   5   6  12   5  13  77]]
-Node Classification on random seed  8778 -> 0.601
-Confusion Matrix:
- [[ 79   4   7   9   2   8   3]
- [  5 133   3   4  10   2   4]
- [ 19  20 122  36  17  26  73]
- [ 14   3  13 104   3   6   8]
- [  3   8   3   1  56   1   2]
- [  4   3   3   2   1  44   5]
- [ 18   9   9  10   6  12  63]]
-Node Classification on random seed  8779 -> 0.638
-Confusion Matrix:
- [[ 91   4   3   2   3  11   3]
- [  3 135   4   1   5   3   0]
- [ 13  37 126  36  24  34  39]
- [ 12   4  17 106   5   5  13]
- [  1   6   6   1  59   0   1]
- [  6   1   2   0   0  49   1]
- [  9   2  13   9   7  16  72]]
-Node Classification on random seed  8780 -> 0.587
-Confusion Matrix:
- [[ 65   1  11   4   6  11  14]
- [ 12 107   7   7  16   2   1]
- [ 21  10 125  40  31  36  44]
- [ 20   1  12 118   5   7  13]
- [  5   3   3   0  62   0   2]
- [ 11   0   1   2   0  42   3]
- [ 11   0  10  11   6  13  68]]
-Node Classification on random seed  8781 -> 0.576
-Confusion Matrix:
- [[ 75   1   3   2   1  11  10]
- [  4 126  10   2  10   3   3]
- [ 24  26 130  43  14  35  38]
- [ 18   2  26  74   5  20  13]
- [  0   9   7   1  61   3   1]
- [  6   0   2   0   3  48   5]
- [ 13   1   8   9  16  16  62]]
-Node Classification on random seed  8782 -> 0.596
-Confusion Matrix:
- [[ 66   2   5   3   2  27   7]
- [  2 126   6   8   9   3   3]
- [ 37  17 143  41  21  21  44]
- [ 12   3  11  91   2   6  21]
- [  2   2   5   3  52   4   1]
- [  6   3   3   0   0  41   5]
- [ 14   4  13   4   5  17  77]]
-Node Classification on random seed  8783 -> 0.589
-Confusion Matrix:
- [[ 60   3   0   9   8  18   6]
- [  6 116   0   3  17   2  13]
- [ 30  26 146  24  25  20  43]
- [ 11   4  11  81   6  15  19]
- [  0   6   6   0  58   0   4]
- [  3   1   5   0   1  45   7]
- [ 16   3  12  10   8  10  83]]
-Node Classification on random seed  8784 -> 0.602
-Confusion Matrix:
- [[ 67   6   5   4   2  10  13]
- [  1 126   7   3   8   2   6]
- [ 24  25 127  31  46  27  37]
- [ 16   7  14 100   0   5  17]
- [  1   8   1   0  57   1   3]
- [  8   0   2   0   0  50   2]
- [ 21   5   7   8   5  10  75]]
-Node Classification on random seed  8785 -> 0.635
-Confusion Matrix:
- [[ 65   7   2   7   1  12  11]
- [  1 132   4   2   4   3   8]
- [ 25  23 155  38  28  27  25]
- [  7   5  16 105   4   7  13]
- [  1   4   1   3  63   0   3]
- [  4   0   1   1   1  49   3]
- [ 17   1  14  10   5  16  66]]
-Node Classification on random seed  8786 -> 0.589
-Confusion Matrix:
- [[ 75   7   2   4   5   3   4]
- [  0 138   5   6  10   0   4]
- [ 25  30 123  29  56  20  32]
- [ 21   8  12  76   6  11  10]
- [  3   6   8   2  64   0   1]
- [  7   1   6   2   0  52  12]
- [ 14  12  10   5   6   6  61]]
-Node Classification on random seed  8787 -> 0.608
-Confusion Matrix:
- [[ 75   3   6   4  11   7   5]
- [  3 132   9   2   3   5   0]
- [ 25  38 128  57  30  19  23]
- [ 26   1   9  93   7   3   9]
- [  1   5   4   1  66   0   0]
- [  5   0   0   3   1  39   5]
- [ 17   3  10  11   4  17  75]]
-Node Classification on random seed  8788 -> 0.592
-Confusion Matrix:
- [[ 63   6   5   6   2  11  12]
- [  6 117   6   3  10  15   6]
- [ 18  15 155  20  38  22  47]
- [ 11   5  14 101   2  10  13]
- [  0   6   6   3  55   0   3]
- [  3   1   7   0   1  31  16]
- [ 11   5  18   6   7  12  70]]
-Node Classification on random seed  8789 -> 0.629
-Confusion Matrix:
- [[ 73   2   5   0   5  16  17]
- [  5 147   3   1   8   2   3]
- [ 28  21 121  37  20  11  49]
- [  6   6  22 107   3   3  19]
- [  3   4   4   2  60   4   1]
- [  7   0   3   0   0  39   8]
- [  8   1   9   5   6  14  82]]
-Node Classification on random seed  8790 -> 0.61
-Confusion Matrix:
- [[ 71   2   2   5   1  18   7]
- [  4 130   1   4   9   0   6]
- [ 23  21 157  28  29  33  37]
- [ 17   1  18  77  10   5  23]
- [  1   9   0   3  57   1   5]
- [  2   0   6   3   3  44   5]
- [  6   3  16   4   4  15  74]]
-Node Classification on random seed  8791 -> 0.603
-Confusion Matrix:
- [[ 74   5   4   5   5   9   3]
- [  2 151   2   1   2   2   4]
- [ 16  42 124  38  30  16  56]
- [ 14   5  18  84  10   6  12]
- [  1   7   1   1  54   0   1]
- [ 10   0   5   3   0  43   4]
- [ 14   4  21   9   2   7  73]]
-Node Classification on random seed  8792 -> 0.624
-Confusion Matrix:
- [[ 75   2   6  11   3  15   2]
- [  5 137   5   0   5   5   7]
- [ 21  19 157  22  36  27  32]
- [  9   8  22  93   7   6   5]
- [  0   6   1   1  58   1   3]
- [  5   4   1   6   6  46   3]
- [ 10   7  18   4   2  18  58]]
-Node Classification on random seed  8793 -> 0.591
-Confusion Matrix:
- [[ 67   1   8   4   4  14  12]
- [  3 105   1   1   7   4   2]
- [ 27  28 128  43  42  12  41]
- [ 16   3  26  98  11   5  11]
- [  0   4   4   6  63   2   3]
- [  4   2   3   1   2  48   3]
- [  8   3   1   9  14  14  82]]
-Node Classification on random seed  8794 -> 0.63
-Confusion Matrix:
- [[ 75   3   5   3   3  25   8]
- [  4 121   2   2   4   2   4]
- [ 37  13 141  19  19  22  44]
- [ 11   3  12  98   6   7  12]
- [  2   5   7   3  63   0   2]
- [  2   2   5   6   0  49   4]
- [  7   5  11   5   9  25  83]]
-Node Classification on random seed  8795 -> 0.624
-Confusion Matrix:
- [[ 53   2   2  18   8  18  10]
- [  7 150   6   2  11   3   4]
- [ 20  27 144  28  18  29  27]
- [  3   8  14 127   3   6   7]
- [  2   5   4   3  56   1   4]
- [  9   2   0   1   2  50   1]
- [  8   2   7  16   5  23  44]]
-Node Classification on random seed  8796 -> 0.621
-Confusion Matrix:
- [[ 93   3   3   3   1   8  10]
- [  5 117  10   3   8   1   3]
- [ 19  23 142  30  23  21  41]
- [ 11   3  27  93   4   6  17]
- [  0   3   3   1  52   2   7]
- [  8   1   3   2   1  48   4]
- [ 13   2  17  10   6  13  76]]
-Node Classification on random seed  8797 -> 0.634
-Confusion Matrix:
- [[ 64   5   2  11   8  17   8]
- [  2 135   7   1  11   4   0]
- [ 16  33 144  35  59  15  31]
- [  4   6   9 112   4   6  11]
- [  0   3   2   0  65   1   4]
- [  2   0   2   2   0  42   4]
- [ 14   1   2   3  10  11  72]]
-Node Classification on random seed  8798 -> 0.595
-Confusion Matrix:
- [[ 68   2   9   0   1  16   6]
- [  9 125   7   2   5   4   7]
- [ 26  11 127  37  27  18  56]
- [ 10   8  21  94   2   9  16]
- [  2   4   4   0  65   0   0]
- [  5   1   2   0   0  58  10]
- [  8   2  14   7  17  20  58]]
-Node Classification on random seed  8799 -> 0.612
-Confusion Matrix:
- [[ 60   3   2   3   3  21   9]
- [  2 124  10   6   6   6   2]
- [ 29  20 142  37  38   9  37]
- [ 18   6  18  94  11   6   7]
- [  1   4   6   4  53   0   2]
- [  6   1   1   2   1  52   3]
- [ 11   5   3  12   5  12  87]]
-Node Classification on random seed  8800 -> 0.6
-Confusion Matrix:
- [[ 67   4  13   7   2  11  15]
- [  8 126   4   8   4   2   7]
- [ 22  30 113  50  19  20  54]
- [  9   3  13 104   2   6  13]
- [  1   4   3   1  75   2   1]
- [  4   1   4   1   1  42   4]
- [  8   4   6   5   9  15  73]]
-Node Classification on random seed  8801 -> 0.611
-Confusion Matrix:
- [[ 63   2  13   5   6  18   4]
- [  4 125  12   4   3   1   8]
- [ 37  17 149  47  22  17  23]
- [  9   1  21 106   3   2   9]
- [  0  13   5   2  57   1   4]
- [  7   3   3   7   2  40   3]
- [ 19   2  11   5   2  12  71]]
-Node Classification on random seed  8802 -> 0.65
-Confusion Matrix:
- [[ 89   4   4   2   4   5   9]
- [  7 145   6   3   8   2   3]
- [ 33  19 142  55  21  21  29]
- [  9   2   4 113   9   2  13]
- [  1   6   4   1  53   0   1]
- [  6   1   4   0   2  36   3]
- [  9   5  13  10   4   6  72]]
-Node Classification on random seed  8803 -> 0.642
-Confusion Matrix:
- [[ 70   4   3   3   0  13  10]
- [  4 117   2   3   3   1   2]
- [ 22  24 162  41  11  21  31]
- [ 13   2  16 102   5   7  22]
- [  1   7   5   2  63   2   2]
- [  6   2   4   8   0  42   6]
- [  7   5  12   5   3  18  86]]
-Node Classification on random seed  8804 -> 0.614
-Confusion Matrix:
- [[ 79   1   0   4   0  15   6]
- [  4 115   5   3  14   2   4]
- [ 26  24 124  26  45  24  44]
- [  5   5   8 109   4   8  18]
- [  2   8   5   3  58   2   2]
- [  3   1   4   0   1  53   1]
- [ 15   4  13   2   4  21  76]]
-Node Classification on random seed  8805 -> 0.592
-Confusion Matrix:
- [[ 66   2   1   3   5  13   6]
- [  8 128   7   6   5   5  12]
- [ 35  14 130  43  24  25  33]
- [ 19   8  14  91   4   7  11]
- [  1   1   0   7  52   1   1]
- [  9   2   2   3   2  50   1]
- [ 25   3   7   8   5  20  75]]
-Node Classification on random seed  8806 -> 0.618
-Confusion Matrix:
- [[ 69   4   6   7   2   6  10]
- [  3 136   6   2  19   1   6]
- [ 24  18 116  73  26  18  26]
- [  7   6  12 112   4   1  12]
- [  5   3   3   3  73   2   1]
- [  3   1   0   7   0  45   9]
- [ 10   3   7   6   7  13  67]]
-Node Classification on random seed  8807 -> 0.634
-Confusion Matrix:
- [[ 81   3   3   5   5  18   0]
- [  4 129   6   2   6   1   1]
- [ 16  19 161  28  23  28  32]
- [ 22   4  19  91   4   6  10]
- [  0   6   3   1  64   3   4]
- [  6   0   1   3   9  36   3]
- [ 10   1  15   7  12  17  72]]
-Node Classification on random seed  8808 -> 0.557
-Confusion Matrix:
- [[ 57   4   5  12   4   8  14]
- [  2 118  16   4  14   5   3]
- [ 37  33 120  25  29  16  59]
- [ 19   8   9  84   7  10   9]
- [  1  10   4   1  68   0   3]
- [  2   2   5   1   1  46   4]
- [ 20   3   6   6   3  19  64]]
-Node Classification on random seed  8809 -> 0.602
-Confusion Matrix:
- [[ 66   2   6   5   7   9   6]
- [  3 126   2   1  10   5   4]
- [ 26  26 135  35  42  17  33]
- [ 16   4  21  96   8  10  14]
- [  0   3  11   0  48   2   2]
- [  4   5   1   1   1  52   5]
- [  7   1   7   5   8  23  79]]
-Node Classification on random seed  8810 -> 0.63
-Confusion Matrix:
- [[ 70   5   4   5   6   8   3]
- [  5 137   2   2  12   0   0]
- [ 34  12 146  19  46  22  40]
- [  7   6  14 102   2   5  12]
- [  2   5   1   7  57   1   2]
- [ 12   0   1   4   1  51   4]
- [ 19   1   1  10  11  17  67]]
-Node Classification on random seed  8811 -> 0.635
-Confusion Matrix:
- [[ 71   3   0   2   8  10  11]
- [  1 129  13   3   3   2   4]
- [ 17  19 132  46  19  15  46]
- [ 16  10  10 119   4   5  18]
- [  2   7   4   0  55   2   0]
- [  6   0   1   3   0  48  13]
- [  8   5  13   2   2  12  81]]
-Node Classification on random seed  8812 -> 0.634
-Confusion Matrix:
- [[ 81   1   8   5   5   8   6]
- [  4 133   3   2   5   4   2]
- [ 20  27 147  22  32  19  34]
- [  6   5  15 107   5   7  21]
- [  1   4  10   7  56   1   2]
- [  4   1   4   1   4  39   4]
- [  8   7  11   9   9  13  71]]
-Node Classification on random seed  8813 -> 0.637
-Confusion Matrix:
- [[ 70   6   2   8   5  10   4]
- [  4 123   7   3  10   3  13]
- [ 29  15 139  29  21  22  47]
- [  2   3  11 111  10   3  21]
- [  2   3   2   1  62   1   3]
- [  8   3   1   4   0  51   5]
- [ 11   4   4   4   8  11  81]]
-Node Classification on random seed  8814 -> 0.615
-Confusion Matrix:
- [[ 77   3   0   5   6   6  13]
- [  5 106  12   8   5   4   6]
- [ 23  16 147  57  24  18  32]
- [ 10   3  10 113   4   1   7]
- [  0   9   5   4  68   2   4]
- [ 14   0   4   5   1  34   4]
- [ 14   7  11  10   3  10  70]]
-Node Classification on random seed  8815 -> 0.611
-Confusion Matrix:
- [[ 68   5   8   4   7  11   7]
- [  3 130   6   2   8   2   4]
- [ 33  17 126  44  41  14  37]
- [ 15   5   6 111   4   7  17]
- [  0   7   5   0  60   0   2]
- [  4   0   0   1   1  48   6]
- [ 13   6   5  10   9  13  68]]
-Node Classification on random seed  8816 -> 0.623
-Confusion Matrix:
- [[ 73   0   6   5   5  13   8]
- [  2 121   9   2   5   4   6]
- [ 27  14 154  23  28  24  52]
- [  9   4  12 102   4   5   9]
- [  1   7   3   0  63   2   2]
- [  7   0   2   2   2  47   7]
- [  8   3   1  13  24  17  63]]
-Node Classification on random seed  8817 -> 0.63
-Confusion Matrix:
- [[ 77   4   4   7   6  12  10]
- [  4 127   6   1   5   3   4]
- [ 26  19 161  30  19  22  39]
- [ 12   3  20  99   4   7  11]
- [  2   8   5   2  60   0   2]
- [  3   0   7   1   3  42   3]
- [  8   3   6  12   5  22  64]]
-Node Classification on random seed  8818 -> 0.585
-Confusion Matrix:
- [[ 71   9   3   7   2   7   5]
- [ 10 121   7   5  12   0   6]
- [ 31  25 117  44  30  24  30]
- [  5  11  13  91   8  11  19]
- [  1   7   3   0  70   0   3]
- [  7   3   0   0   1  40   9]
- [ 13   8  10  11   4  11  75]]
-Node Classification on random seed  8819 -> 0.614
-Confusion Matrix:
- [[ 72   2   8   5   2  10   3]
- [  4 140   7   2   5   1   5]
- [ 42  11 119  31  52  20  30]
- [ 16   2  18 101   5  16  10]
- [  3   6   3   0  54   2   3]
- [  5   1   3   0   0  58   5]
- [ 14   2  11   5   4  12  70]]
-Node Classification on random seed  8820 -> 0.598
-Confusion Matrix:
- [[ 73   2   9   5   1  10   4]
- [  2 142   9   5   3   1   5]
- [ 25  25 104  59  42  18  36]
- [  6   0  22 100   5   3   7]
- [  8   4   4   2  55   1   5]
- [  7   1   1   1   1  41   8]
- [ 17   3   6  11   8  10  83]]
-Node Classification on random seed  8821 -> 0.669
-Confusion Matrix:
- [[ 86   1   6   3   1  10  15]
- [  5 129   7   6   4   6   0]
- [ 22  19 145  18  27  16  36]
- [ 11   2  13 120   3   6  12]
- [  0  13   6   1  58   1   2]
- [  3   3   2   0   0  46   3]
- [  8   1   9   9   7  14  85]]
-Node Classification on random seed  8822 -> 0.612
-Confusion Matrix:
- [[ 74   3  10   8   5   7   8]
- [  8 116   6   3   8   1   3]
- [ 31  34 140  51  18  15  35]
- [  7   5  13 122   1   5   8]
- [  2   3   3   4  48   0   1]
- [  9   0   4   1   0  42   5]
- [ 12   5  16   9   3  18  70]]
-Node Classification on random seed  8823 -> 0.604
-Confusion Matrix:
- [[ 81   0   5   4   5   5  11]
- [ 13 105   4   1  14   4   1]
- [ 22  43 142  22  44  12  33]
- [ 17   4  16  93   5   6   9]
- [  2   7   2   2  60   2   2]
- [  8   0   2   0   2  57   5]
- [ 31   4   7   2   7  11  66]]
-Node Classification on random seed  8824 -> 0.578
-Confusion Matrix:
- [[ 62   3  14   8   2  20   3]
- [  6 133  11   1  11   4   2]
- [ 40  23 119  40  40  18  40]
- [ 13   1  22  89   3   5  11]
- [  2   6   2   4  54   0   2]
- [  5   2   2   2   1  55   3]
- [ 12   1  17   6   6   8  66]]
-Node Classification on random seed  8825 -> 0.584
-Confusion Matrix:
- [[ 72   2  11   1   9   4   7]
- [  7 114   8   4   6   0   6]
- [ 39  22 131  32  51  17  36]
- [ 17   6  15  94   9   6  14]
- [  1   5   4   1  57   0   4]
- [  2   1   3   2   1  44   8]
- [ 17   2  13   5   8  10  72]]
-Node Classification on random seed  8826 -> 0.569
-Confusion Matrix:
- [[ 65   3   4   6   2   6  10]
- [  7 117   7   2   3   2   6]
- [ 31  20 118  54  49  11  44]
- [ 10   7  20 110   6   2  15]
- [  2   7   1   0  49   3   6]
- [  9   3   4   2   0  34  10]
- [ 11   6  14   6   5  15  76]]
-Node Classification on random seed  8827 -> 0.591
-Confusion Matrix:
- [[ 64   4  10   6   3  14   5]
- [  4 113   3   5  10   3   3]
- [ 21  22 143  35  19  21  45]
- [ 28   3  12  99   7   8  17]
- [  1   5   4   2  71   4   3]
- [  2   2   3   4   0  40   3]
- [ 15   1  12   8   9  23  61]]
-Node Classification on random seed  8828 -> 0.598
-Confusion Matrix:
- [[ 67   1   4  13   4  13   5]
- [  8 125  10   4  12   6   4]
- [ 19  22 135  42  27  37  22]
- [ 22   3  11  97   2   4   7]
- [  1   2   3   2  66   1   4]
- [  5   0   4   1   2  42   1]
- [ 15   2  20  11   6  20  66]]
-Node Classification on random seed  8829 -> 0.58
-Confusion Matrix:
- [[ 81   2   2   3   5  19  13]
- [  7 129  10   9   1   5   4]
- [ 27  35 120  35  19  16  42]
- [ 29   5  12  84   9   3  10]
- [  1   5   4   2  64   1   4]
- [  0   1   3   4   1  44   5]
- [  7   8   9   7   9  27  58]]
-Node Classification on random seed  8830 -> 0.575
-Confusion Matrix:
- [[ 68   0   4   6   1   9  14]
- [  8 119   9   5  12   7   4]
- [ 36  24 121  34  24  17  49]
- [ 32   1   8  95  11  12   6]
- [  4   7   7   0  46   3   1]
- [ 14   1   1   0   0  45  11]
- [  8   5   7   5   3  15  81]]
-Node Classification on random seed  8831 -> 0.658
-Confusion Matrix:
- [[ 73   2   6   4   5   7  10]
- [  1 126   6   1  18   3   8]
- [ 33  13 155  19  23  16  40]
- [ 10   2  15 120   8   9   9]
- [  2   7   4   0  59   0   3]
- [  3   0   1   1   0  51   6]
- [ 13   5   4   1  13  11  74]]
-Node Classification on random seed  8832 -> 0.597
-Confusion Matrix:
- [[ 66   2   7   5   5  11  13]
- [  6 129   6   5   2   1   3]
- [ 28  14 131  53  23  33  29]
- [ 11   4  19 107   2   2  13]
- [  1  10   2   3  53   3   3]
- [  5   5   0   3   0  44   5]
- [  4   5   8  13  13  23  67]]
-Node Classification on random seed  8833 -> 0.599
-Confusion Matrix:
- [[ 61   3   8   4   7  13  14]
- [  7 106   3   4  11   1   5]
- [ 48  22 135  41  23  18  28]
- [ 10   8  16 108   3   8  18]
- [  0   4   1   1  64   2   3]
- [  5   0   3   1   1  40   7]
- [ 12   1  11   1   8  17  85]]
-Node Classification on random seed  8834 -> 0.629
-Confusion Matrix:
- [[ 73   1   0   2   1  10  10]
- [  5 129   5   2   5   0   4]
- [ 21  20 168  53  20  16  46]
- [ 16   3  22  93   3   6  17]
- [  1   8   6   3  52   0   1]
- [  4   0   2   0   1  40   9]
- [  5   1   8  11   6  17  74]]
-Node Classification on random seed  8835 -> 0.647
-Confusion Matrix:
- [[ 70   2   1   4   2   7   8]
- [  2 145   8   2   1   8   5]
- [ 14  26 149  23  20  17  54]
- [  7   7  17 100   3   5  25]
- [  3   9   5   0  62   1   2]
- [  5   3   4   4   0  40   7]
- [  6   0   7  10   5  14  81]]
-Node Classification on random seed  8836 -> 0.66
-Confusion Matrix:
- [[ 84   2   0   4   1   8   8]
- [  6 103  17   3   5   7   3]
- [ 16  13 165  35  23  26  36]
- [ 11   2  14 105   5   9   7]
- [  2   3   8   0  61   0   1]
- [  4   0   3   1   0  56   5]
- [ 13   3   8   4   4  20  86]]
-Node Classification on random seed  8837 -> 0.619
-Confusion Matrix:
- [[ 60   4   4   9   5  11  12]
- [  5 133   2   5   5   2   6]
- [ 17  19 136  32  26  32  37]
- [ 15   2  14 106   4  13   7]
- [  3   6   3   2  58   0   3]
- [ 17   1   1   1   0  42   6]
- [ 22   4   8   5   4   7  84]]
-Node Classification on random seed  8838 -> 0.601
-Confusion Matrix:
- [[ 70   3   6   3   6  19   2]
- [  3 120   4   5   5   4   3]
- [ 37  27 129  43  18  21  36]
- [ 12   3  15 106  10   7  14]
- [  1   6   3   0  67   2   2]
- [  7   1   1   2   2  44   7]
- [ 24   4   3  10   5  13  65]]
-Node Classification on random seed  8839 -> 0.611
-Confusion Matrix:
- [[ 60   1  10   5   4  13  14]
- [  4 119   4   6   4   4   7]
- [ 18  16 145  40  31  15  48]
- [  6   1  13  94  19  10  13]
- [  0   4   2   3  66   0   4]
- [  5   0   4   0   0  43   6]
- [  6   4  11   8   3  23  84]]
-Node Classification on random seed  8840 -> 0.641
-Confusion Matrix:
- [[ 78   5   5   8   7  17  15]
- [  2 134   7   1   5   5   5]
- [ 15  19 139  38  28  19  35]
- [  5   4  12 106  10   3  15]
- [  0   7   2   2  56   2   2]
- [  2   4   3   0   0  43   5]
- [  5   4  18   1   4  13  85]]
-Node Classification on random seed  8841 -> 0.636
-Confusion Matrix:
- [[ 67   4   6   2   4  15   2]
- [  5 131   3   0   9   4   8]
- [ 11  17 145  39  54  28  34]
- [  5   4  10 117   3   6   7]
- [  0   6   4   2  59   1   4]
- [  5   0   0   0   3  40  10]
- [  8   6   6   9   9  11  77]]
-Node Classification on random seed  8842 -> 0.618
-Confusion Matrix:
- [[ 58   1   1   8   5  14   8]
- [  2 139   0   0   7   1   5]
- [ 24  15 120  49  20  21  40]
- [ 16   3  25 114   3   7   6]
- [  0   8   1   0  69   3   4]
- [  4   1   2   1   0  55   4]
- [ 10   3  13  11   3  33  63]]
-Node Classification on random seed  8843 -> 0.586
-Confusion Matrix:
- [[ 62   5   2   1   2  18  13]
- [  8 120   3   6   9   0   0]
- [ 29  25 133  48  19  39  27]
- [ 17   4  19  94   5  11  19]
- [  0   6   7   1  64   4   2]
- [  6   1   1   1   0  42   8]
- [ 14   4   5   3   4  18  71]]
-Node Classification on random seed  8844 -> 0.649
-Confusion Matrix:
- [[ 74   2   0   2   2   4  11]
- [  7 125  11   2   8   1   6]
- [ 26  10 161  55  20  15  30]
- [ 12   3  14 100   4   6  13]
- [  3   6   3   1  71   1   5]
- [  6   1   1   5   0  48   2]
- [ 14   6   3  15   4  11  70]]
-Node Classification on random seed  8845 -> 0.615
-Confusion Matrix:
- [[ 60   3   4   5   3  18  21]
- [  2 110  13   2   7   3   3]
- [ 28  27 140  34  23  12  36]
- [ 17   5  19 108   3   4  23]
- [  3   8   4   1  60   1   1]
- [  3   7   1   1   5  37  12]
- [  4   2   7   2   4   4 100]]
-Node Classification on random seed  8846 -> 0.632
-Confusion Matrix:
- [[ 68   0   5   1   8  10  12]
- [  4 120   7   6   5   0   2]
- [ 25  18 160  51  15  15  48]
- [ 15   7  11  94   5   3  14]
- [  0  11  12   1  50   0   2]
- [  7   1   2   1   0  45  11]
- [  3   5   8   9   3   5  95]]
-Node Classification on random seed  8847 -> 0.638
-Confusion Matrix:
- [[ 80   4   3   9   5   6  15]
- [  1 139   3   0   9   7   3]
- [ 25  16 146  30  37  14  32]
- [ 17   4  16  94   5   7   7]
- [  0   5   1   1  64   0   0]
- [  6   0   4   0   4  40   6]
- [ 11   4   2   8  10  25  75]]
-Node Classification on random seed  8848 -> 0.581
-Confusion Matrix:
- [[ 77   3   6   3   6   7   8]
- [  5 122   7   7  20   0   6]
- [ 41  14 140  34  22  36  50]
- [ 11   6  11  92   4   2  21]
- [  1   3   2   2  58   0   1]
- [  6   1   4   1   4  34   4]
- [ 16   2   8  10  10  14  58]]
-Node Classification on random seed  8849 -> 0.586
-Confusion Matrix:
- [[ 83   1  11   7   1   5   5]
- [ 10 107  11   2  13   4   9]
- [ 17  21 143  39  11  25  67]
- [ 17   5   5  93   3  12  16]
- [  3   5   2   1  57   1   3]
- [  5   1   5   3   1  29   3]
- [ 18   4  15   4   7  16  74]]
-Node Classification on random seed  8850 -> 0.62
-Confusion Matrix:
- [[ 62   3   4   4   1  12  10]
- [  8 120   1   0   4   4   7]
- [ 28  32 127  22  26  34  40]
- [  9   7  13 106   1  10  14]
- [  5   5   5   3  65   2   2]
- [  4   3   0   2   0  63   3]
- [ 10   7   8   2  10  15  77]]
-Node Classification on random seed  8851 -> 0.637
-Confusion Matrix:
- [[ 56   2   6  11   8  11   9]
- [  3 139   5   1   3   5   5]
- [ 22  12 152  25  23  32  37]
- [  6   1  16 108   6   8  10]
- [  1   8   5   4  56   1   5]
- [  7   1   3   6   0  47   1]
- [  9   0  14   6   5  20  79]]
-Node Classification on random seed  8852 -> 0.604
-Confusion Matrix:
- [[ 71   3   8   3   8  14  10]
- [  4 117   7   2   7   7   5]
- [ 23  23 137  33  23  28  48]
- [ 10   5   9 109   5   6  14]
- [  2   5   2   1  65   1   0]
- [ 10   2   1   2   2  36   3]
- [ 17   2   6   4  11  20  69]]
-Node Classification on random seed  8853 -> 0.621
-Confusion Matrix:
- [[ 59   8  10   5   0  11  16]
- [ 11 118   1   0   8   5   5]
- [ 20  21 173  27  28  19  26]
- [ 25   5  10  97   6   5  11]
- [  2   6   3   0  60   1   6]
- [  6   2   3   0   0  45   8]
- [  9   5   5   9  11  20  69]]
-Node Classification on random seed  8854 -> 0.608
-Confusion Matrix:
- [[ 56   3   4  16   3   9  16]
- [  3 131   5   4   9   4   3]
- [ 21  23 149  52  13  26  37]
- [ 14   3  19  90   4   4  18]
- [  5   5   6   1  60   1   1]
- [  3   1   3   3   0  40   4]
- [  7   2  14   4   7  12  82]]
-Node Classification on random seed  8855 -> 0.593
-Confusion Matrix:
- [[ 52   0   4   7   4  27  11]
- [  4 131   4   2   3   2   5]
- [ 31  25 130  28  52  22  29]
- [ 14   5   8 103   5   5  17]
- [  2   5   6   0  54   0   3]
- [  2   1   6   0   0  40   5]
- [ 10   1  20   3   6  23  83]]
-Node Classification on random seed  8856 -> 0.643
-Confusion Matrix:
- [[ 78   0   3   9   8  15   3]
- [  6 130   2   3   8   4   2]
- [ 25   9 162  28  24  17  52]
- [  9   0  29  97   8   4  15]
- [  3   5   3   0  66   3   1]
- [  2   2   3   5   3  37   1]
- [  6   3   9   5   4  16  73]]
-Node Classification on random seed  8857 -> 0.653
-Confusion Matrix:
- [[ 78   1   0   4   4  14   6]
- [  6 130   2   4   6   6   4]
- [ 26  19 175  22  14  19  22]
- [ 21   3  20  96   6   5  17]
- [  3   2   3   4  62   1   4]
- [  1   1   2   1   0  46   5]
- [ 15   8  13   6   5  22  66]]
-Node Classification on random seed  8858 -> 0.599
-Confusion Matrix:
- [[ 79   1   3   6   3   6  13]
- [ 12 129   6   1   3   4   1]
- [ 34  25 129  33  52  34  26]
- [  4   3  21 100   3   5  17]
- [  0   4   3   0  57   4   0]
- [ 12   1   2   1   1  40   1]
- [ 14   9  10   2  10  11  65]]
-Node Classification on random seed  8859 -> 0.602
-Confusion Matrix:
- [[ 62   0  13   2  10  10   1]
- [  3 116   2   7   9   4   5]
- [ 14  24 135  67  19  17  48]
- [  4   3  15 101   5  10   9]
- [  1   8   6   1  59   0   6]
- [  3   3   0   4   1  54   8]
- [  8   6  14   5   5  18  75]]
-Node Classification on random seed  8860 -> 0.594
-Confusion Matrix:
- [[ 81   3   1   5   2  16  13]
- [  2 134   3   2   8   4   6]
- [ 21  21 122  28  41  27  42]
- [ 18   4  10  75   7  12  25]
- [  3   8   1   1  64   0   2]
- [  1   1   1   4   0  48   8]
- [  5   1  10   2  28   9  70]]
-Node Classification on random seed  8861 -> 0.625
-Confusion Matrix:
- [[ 78   0   2   9   2  10  12]
- [  5 134   6   3   2   3   1]
- [ 38  26 135  42  30  12  32]
- [ 11   6  14 107   3   6   6]
- [  0  10   3   3  54   1   2]
- [  3   1   3   1   0  52   4]
- [ 10   6  18  11  13   5  65]]
-Node Classification on random seed  8862 -> 0.593
-Confusion Matrix:
- [[ 81   5   4   1   3   7  14]
- [  2 122   2   1  10   1   4]
- [ 31  24 134  36  30  12  51]
- [ 16   0  10  93  11   6  12]
- [  0  14   7   0  49   1   3]
- [  1   7   7   3   5  34   4]
- [ 12   9  10   6   6  19  80]]
-Node Classification on random seed  8863 -> 0.59
-Confusion Matrix:
- [[ 76   1   1   2   5  10   8]
- [  5 111   7   6  22   2   0]
- [ 17  29 149  28  35  24  40]
- [ 12   4  17  80   6   7  23]
- [  1   7   3   0  61   0   4]
- [  7   1   6   2   4  38   5]
- [ 16   3   7   4   2  27  75]]
-Node Classification on random seed  8864 -> 0.564
-Confusion Matrix:
- [[ 78   4   5   3   0  17  22]
- [  4 112   7   1  12   3   5]
- [ 27  19 116  42  40  31  36]
- [ 13   3   9  84   6   7  21]
- [  2   7   4   1  49   0   5]
- [  1   0   3   3   0  53   4]
- [ 15   1   7  15   6  25  72]]
-Node Classification on random seed  8865 -> 0.602
-Confusion Matrix:
- [[ 70   2   0  11   6   7   7]
- [  4 115   9   0  16   4   9]
- [ 22  17 119  40  50  27  50]
- [ 12   2  11 112   0   9  17]
- [  0   0   4   3  59   1   2]
- [  4   1   1   4   2  46   3]
- [ 13   7   4   5   6   6  81]]
-Node Classification on random seed  8866 -> 0.58
-Confusion Matrix:
- [[ 83   2   9   0   5  12   8]
- [ 13 124   5   0  14   0   4]
- [ 15  25 103  74  13  24  46]
- [  3   2  21 100   3   8  16]
- [  1   1   7   1  62   4   2]
- [  3   2   4   2   6  40   2]
- [ 14   6   9   7   7  20  68]]
-Node Classification on random seed  8867 -> 0.627
-Confusion Matrix:
- [[ 78   2   8   3   3   9   6]
- [  0 121   8   4   9   2  11]
- [ 12  20 140  44  36  24  43]
- [  8   1  16 102   3   4  11]
- [  0   7   4   2  55   0   6]
- [  2   3   4   0   0  55   6]
- [  3   4   9   8   7  21  76]]
-Node Classification on random seed  8868 -> 0.604
-Confusion Matrix:
- [[ 67   1   5   2   7  11   2]
- [  3 135   7   2   8   2   3]
- [ 27  20 128  30  46  21  55]
- [ 21   4   9  97   7   6  10]
- [  0  11   2   1  62   2   1]
- [  3   0   4   5   4  42   4]
- [  9   2   8   8   8  15  73]]
-Node Classification on random seed  8869 -> 0.601
-Confusion Matrix:
- [[ 59   2   7   6   6  14   9]
- [  3 145   4   0   2   7   4]
- [ 20  20 112  45  48  23  25]
- [ 13   9  14 101   6  13   7]
- [  0   6   4   0  73   1   6]
- [  2   2   1   3   0  42   7]
- [  8   5  17   4   6  20  69]]
-Node Classification on random seed  8870 -> 0.609
-Confusion Matrix:
- [[ 81   6   2   7   3  10  14]
- [  4 114  11   3   5   0   3]
- [ 26  21 134  33  28  25  52]
- [ 10   4   9 104  11  11  15]
- [  5   2   0   3  56   1   2]
- [  6   0   0   0   1  44   7]
- [ 18   2   8   2  10  11  76]]
-Node Classification on random seed  8871 -> 0.621
-Confusion Matrix:
- [[ 75   3   5   2   3  13  11]
- [ 11 141   6   3  11   2   4]
- [ 28  13 132  24  44  24  26]
- [ 17   1  18 113   4   6  12]
- [  3   7   4   2  47   1   5]
- [  3   5   0   1   0  51   1]
- [ 11   2  12   7   7  17  62]]
-Node Classification on random seed  8872 -> 0.597
-Confusion Matrix:
- [[ 74   5   2   3   3   7  11]
- [  4 124  16   0   7   4   5]
- [ 30  18 137  36  45  20  27]
- [ 20   7  16  87   3  12   9]
- [  0  10   4   0  66   1   1]
- [  4   0   1   4   2  41   3]
- [ 17   3  10   7  14  12  68]]
-Node Classification on random seed  8873 -> 0.628
-Confusion Matrix:
- [[ 60   2   5  12   4   3  13]
- [  6 123   9   4   7   0   1]
- [ 12  34 148  35  22   7  50]
- [  6   2  14 117   5   9  16]
- [  3  11   5   0  56   0   1]
- [  3   6   3   2   2  39   9]
- [ 16   2   8   8   7   8  85]]
-Node Classification on random seed  8874 -> 0.613
-Confusion Matrix:
- [[ 62   2   2   5  12   7   6]
- [  4 122   7   2  12   5   3]
- [ 39  17 145   9  25  30  40]
- [ 17   4  31  97   1   5  16]
- [  3   9   3   0  62   0   2]
- [ 11   0   2   1   0  50   0]
- [ 12   5   7   4   7  20  75]]
-Node Classification on random seed  8875 -> 0.598
-Confusion Matrix:
- [[ 61   1   5   5   5   7  24]
- [  4 120   8   2  13   2  11]
- [ 32  33 129  49  24  17  20]
- [ 10   3  14 115   3   5  10]
- [  1   2   3   1  65   0   6]
- [  8   0   3   2   2  41   8]
- [  9   2   9  14  14  11  67]]
-Node Classification on random seed  8876 -> 0.664
-Confusion Matrix:
- [[ 71   2   1   6   5  13   6]
- [  5 121   4   1   5   4   3]
- [ 30  14 155  32  20  15  31]
- [ 10   9  10 111   1   2  10]
- [  7   6   3   4  61   3   0]
- [ 14   3   4   0   1  41   4]
- [ 14   3   7   2   6  16 104]]
-Node Classification on random seed  8877 -> 0.613
-Confusion Matrix:
- [[ 72   6   2   3   2  14   8]
- [ 11 124   3   4  13   6   1]
- [ 37  23 128  37  15  21  49]
- [ 11   4   9 118   7   0   7]
- [  1   6   5   1  52   3   4]
- [  1   7   6   0   3  33   5]
- [ 15  11   2  10   3  11  86]]
-Node Classification on random seed  8878 -> 0.641
-Confusion Matrix:
- [[ 72   1   3   2  10  12   7]
- [  2 127   6   3   3   6   5]
- [ 18  21 149  30  18  35  34]
- [ 15   3  14 112   6   4   6]
- [  1   9   3   1  65   1   6]
- [  2   3   1   1   1  48   7]
- [ 11   6  13   3   6  20  68]]
-Node Classification on random seed  8879 -> 0.595
-Confusion Matrix:
- [[ 82   3   1   3   4  13   3]
- [  4 138   5   3  10   7   5]
- [ 31  23 115  40  33  42  41]
- [ 12   5  25  81   8   6   4]
- [  0   0   0   1  79   0   7]
- [  5   3   1   4   2  46   3]
- [  3   6   9  11   8  11  54]]
-Node Classification on random seed  8880 -> 0.615
-Confusion Matrix:
- [[ 63   3   0   8   2  29   5]
- [  5 137   4   2   5   3   3]
- [ 20  19 133  32  20  26  40]
- [ 11   4  17  98  11  15   6]
- [  1   6   1   0  52   3   3]
- [  6   0   1   1   5  48   8]
- [ 10   3  10   6   7  24  84]]
-Node Classification on random seed  8881 -> 0.629
-Confusion Matrix:
- [[ 69   1   6   5  12   5   5]
- [  5 137   4   3   6   6   0]
- [ 27   9 157  25  27  16  40]
- [ 16   8  13 108   4   2  19]
- [  0   5   3   3  69   2   5]
- [  7   1   3   4   0  38   6]
- [ 13   4  27  10   6   8  51]]
-Node Classification on random seed  8882 -> 0.62
-Confusion Matrix:
- [[ 82   4   0   7   3  17  12]
- [  5 126   7   1  12   4   1]
- [ 13  17 123  43  27  22  37]
- [ 13   5  11 103   4  14   6]
- [  1   6   5   0  63   1   3]
- [ 14   0   2   1   0  49   6]
- [ 12   3   5  16   4  16  74]]
-Node Classification on random seed  8883 -> 0.602
-Confusion Matrix:
- [[ 69   4   6   3   3  16   6]
- [  4 119   6   1   6   2   7]
- [ 23  14 131  35  29  37  44]
- [  9   2  33  91   7   6  14]
- [  1   5   4   0  66   0   4]
- [  3   1   0   1   0  56   5]
- [ 17   2   3   3  13  19  70]]
-Node Classification on random seed  8884 -> 0.64
-Confusion Matrix:
- [[ 85   3   4   7   0   6  14]
- [  2 123   1   3  15   5   3]
- [ 20  19 148  37  26  26  42]
- [ 13   3  10 116   4   2  16]
- [  1   4   5   0  52   3   0]
- [  4   3   1   1   0  43   6]
- [  8   0   9  17   7  10  73]]
-Node Classification on random seed  8885 -> 0.6
-Confusion Matrix:
- [[ 58   2  10   4   3  10  14]
- [  2 110   5   9   3   0   8]
- [ 13  36 137  38  34  21  38]
- [  6   4  12 118  14   6  12]
- [  0   8   5   1  62   0   2]
- [  4   1   9   2   3  35   4]
- [  6   1  17  14   9  10  80]]
-Node Classification on random seed  8886 -> 0.655
-Confusion Matrix:
- [[ 75   1   5   0   2  14  15]
- [ 12 127   4   1   7   2   7]
- [ 23  19 177  28  12  21  33]
- [ 17   3  12  76   8   5  18]
- [  2   5   6   3  61   0   4]
- [  7   0   1   1   0  52   9]
- [  7   1  12   2   0  16  87]]
-Node Classification on random seed  8887 -> 0.599
-Confusion Matrix:
- [[ 90   6   4   1   4   5   7]
- [ 14 133  11   3   8   0   4]
- [ 31  22 118  45  27  20  40]
- [ 17   3  10  96   4   7  11]
- [  1   6   1   2  51   1   3]
- [ 14   1   3   0   0  39   6]
- [ 22   2   7  18   3   7  72]]
-Node Classification on random seed  8888 -> 0.577
-Confusion Matrix:
- [[ 64   2   6   8   6  11  15]
- [  1 141  12   6   1   1   2]
- [ 42  23  98  64  13  23  35]
- [ 14   4  13 113   6   3  10]
- [  1   6   5   4  54   2   4]
- [  8   3   1   3   0  40   3]
- [  9   7   9  15   7  15  67]]
-Node Classification on random seed  8889 -> 0.613
-Confusion Matrix:
- [[ 78   2   4   1   7   8   5]
- [  5 116  12   1  19   5   4]
- [ 20  20 164  45  31  19  31]
- [  8   7  14  85   9  22   8]
- [  1   1   1   2  51   0   2]
- [  5   2   7   1   0  44   2]
- [ 17   3   9   7   6  14  75]]
-Node Classification on random seed  8890 -> 0.611
-Confusion Matrix:
- [[ 86   0   0   6   7  16  14]
- [  3 139   5   2   5   2   3]
- [ 13  16 143  37  33  18  34]
- [ 26   9  18  83   5   4   5]
- [  2  11   5   3  58   1   1]
- [ 11   1   2   0   2  41   1]
- [ 16   4   4  15  13  16  61]]
-Node Classification on random seed  8891 -> 0.567
-Confusion Matrix:
- [[ 64   2  15   6   4   6  11]
- [  7 120   6   3   9   1   2]
- [ 15  11 108  46  42  26  59]
- [ 15   8  21  97  14   4   7]
- [  3   8   8   1  63   0   2]
- [ 12   1   0   4   2  32   6]
- [  9   4   4  13  10   6  83]]
-Node Classification on random seed  8892 -> 0.602
-Confusion Matrix:
- [[ 68   5   6  13   4   8  12]
- [  7 127   5   1   9   5   4]
- [ 21  23 143  32  24  28  38]
- [  9  13  18  85  12   3  14]
- [  1   7   8   1  58   1   4]
- [ 10   1   1   1   1  48   3]
- [ 17   9   3   8   3   5  73]]
-Node Classification on random seed  8893 -> 0.602
-Confusion Matrix:
- [[ 69   2   2   4   8   6  25]
- [  2 136   6   2  12   5   4]
- [ 31  17 114  60  31  21  37]
- [  6   2   5 113  12   5   9]
- [  2   8   3   3  54   1   0]
- [  5   1   2   0   3  40   5]
- [ 18   5   7   7   6   8  76]]
-Node Classification on random seed  8894 -> 0.609
-Confusion Matrix:
- [[ 65   1   0   2   7  27   5]
- [  5 121   9   9   5   5   3]
- [ 19  22 148  35  26  21  35]
- [ 23   5  16 106   6   6   8]
- [  0   8   4   2  61   0   2]
- [  2   3   1   1   5  40   6]
- [  9   6   3   9   7  23  68]]
-Node Classification on random seed  8895 -> 0.642
-Confusion Matrix:
- [[ 63   0   8   6   3  10   2]
- [  3 119   3   4   8   2  12]
- [ 25  20 154  37  35  19  29]
- [  7   2   9 114  16   7   6]
- [  0   3   3   0  62   2   3]
- [  1   1   1   4   3  64   1]
- [  7   4   7  15   7  23  66]]
-Node Classification on random seed  8896 -> 0.619
-Confusion Matrix:
- [[ 77   1   5  10   3  13   6]
- [  2 112   3   7   5   2   2]
- [ 11  16 139  56  32  25  50]
- [  8   0  11  96   6   9  17]
- [  0   6   2   6  65   1   4]
- [  8   0   2   5   0  50   5]
- [  1   7   6   6   4  18  80]]
-Node Classification on random seed  8897 -> 0.611
-Confusion Matrix:
- [[ 69   2   3   4   4  10   7]
- [  5 123   8  11   8   0   1]
- [ 35  24 139  56  12  17  39]
- [  7   6  10 105   8   4  18]
- [  0   8   2   2  57   2   0]
- [  8   2   2   4   1  39   3]
- [ 12   4   9   4  12  15  79]]
-Node Classification on random seed  8898 -> 0.592
-Confusion Matrix:
- [[ 70   3   5   1   5   6   8]
- [  7 123   7   1  13   2   2]
- [ 23  21 132  31  37  31  42]
- [ 13   1  24  93   3  13  12]
- [  2   5   4   0  65   2   4]
- [  9   1   9   1   5  33   2]
- [ 17   2   3   5  12  14  76]]
-Node Classification on random seed  8899 -> 0.616
-Confusion Matrix:
- [[ 82   6   7   3   5   6  12]
- [  3 133   3   0   9   2   3]
- [ 20  49 120  41  19  16  37]
- [ 14  12  10 108   7   5  13]
- [  0   9   1   0  53   0   2]
- [ 11   1   1   2   4  45   4]
- [ 14   5   4   4  14   6  75]]
-Node Classification on random seed  8900 -> 0.596
-Confusion Matrix:
- [[ 61   0   8   5   1   6  10]
- [  8 129   4   8   8   8   3]
- [ 37  20 153  36  27  15  41]
- [ 17   2  22  84   0  10  17]
- [  6   5   5   1  59   3   2]
- [  4   0   3   3   0  48   3]
- [ 12   2   9   7  13  13  62]]
-Node Classification on random seed  8901 -> 0.621
-Confusion Matrix:
- [[ 74   1   4   7   4  16  19]
- [  6 112   9   5  13   0   7]
- [ 14  24 128  43  18  20  44]
- [ 17   4  12 116   3   3  17]
- [  2   7   2   0  68   1   0]
- [  2   0   1   1   0  46   5]
- [  9   5   7   4   8  15  77]]
-Node Classification on random seed  8902 -> 0.669
-Confusion Matrix:
- [[ 81   4   1   4   3   6  12]
- [  3 139   5   5   8   4   1]
- [ 17  12 145  30  16  31  39]
- [ 13   2  18 109   4   2  19]
- [  2   4   1   1  62   0   2]
- [  5   1   0   1   1  41   9]
- [ 10   0   5   3   6  21  92]]
-Node Classification on random seed  8903 -> 0.596
-Confusion Matrix:
- [[ 78   6   4   3   4   3   6]
- [  5 133  12   0   6   3   1]
- [ 28  26 121  56  30  28  26]
- [ 14   6  15 113  16   5   5]
- [  0   8   8   0  63   0   2]
- [  6   1   3   3   0  32   6]
- [ 17   4  11  11   7   9  56]]
-Node Classification on random seed  8904 -> 0.589
-Confusion Matrix:
- [[ 71   2   2   2   6  14  14]
- [  1 127  12   2   7   3   4]
- [ 18  13 101  63  29  19  35]
- [ 24   5  14  88   5  18  18]
- [  2   2   5   1  67   5   1]
- [  9   0   1   0   0  56   4]
- [  9   1   9   5   5  22  79]]
-Node Classification on random seed  8905 -> 0.637
-Confusion Matrix:
- [[ 73   1   1   6   4   9   5]
- [  5 128   5   4   4   0   4]
- [ 30  21 146  45  20  18  24]
- [  9   4  19 122   6   8  10]
- [  3   4   5   3  57   0   3]
- [  6   1   2   0   0  43   3]
- [ 17   0  11  16   7  20  68]]
-Node Classification on random seed  8906 -> 0.636
-Confusion Matrix:
- [[ 53   3   4   3   5  19  11]
- [  3 122   3   2   5   4   1]
- [ 28  27 161  32  24  19  25]
- [  8   3  18 115   4   3  13]
- [  1   8   3   2  58   1   4]
- [  2   3   0   2   0  47   8]
- [  5   6   5   9  11  27  80]]
-Node Classification on random seed  8907 -> 0.59
-Confusion Matrix:
- [[ 76   9   4  17   6   4  11]
- [  5 120   2   1  10  11   7]
- [ 22  18 116  43  38  11  43]
- [ 18   6  15 105   6   5  10]
- [  3   5   3   0  65   3   4]
- [  2   4   2   1   0  33   7]
- [ 26   1   7  12   4   4  75]]
-Node Classification on random seed  8908 -> 0.593
-Confusion Matrix:
- [[ 72   2   2   2   7   9  20]
- [  6 127   2   7   8   2   4]
- [ 36  21 121  30  36  20  28]
- [ 10   1  16 102   6  13  20]
- [  0   9   3   3  59   1   1]
- [  8   0   1   3   0  45   6]
- [ 15   2  14   5   9  19  67]]
-Node Classification on random seed  8909 -> 0.618
-Confusion Matrix:
- [[ 75   5   6   9   0  15  10]
- [  2 123   6   1   1   4   3]
- [ 14  17 147  62  32  15  33]
- [ 16   2  13 102   4   6  19]
- [  1   8   4   3  56   1   3]
- [  7   0   4   3   0  42   3]
- [  4   2   8  18   6  12  73]]
-Node Classification on random seed  8910 -> 0.655
-Confusion Matrix:
- [[ 84   1   3   3   2   6   7]
- [  3 138   5   8   7   1   0]
- [ 27  15 161  25  25  21  30]
- [ 15   3  12 101   7   8  21]
- [  0   6   3   1  63   1   4]
- [  3   2   2   5   2  41   4]
- [ 13   5   6  11   4  18  67]]
-Node Classification on random seed  8911 -> 0.609
-Confusion Matrix:
- [[ 76   4   4  10   3   8   8]
- [  3 128   9  11   3   3   1]
- [ 19  22 137  40  27   8  43]
- [ 34   5  17  78   8   7  10]
- [  0   7   1   1  69   2   4]
- [  3   3   3   0   4  53   3]
- [ 12   2   8   8   8  15  68]]
-Node Classification on random seed  8912 -> 0.606
-Confusion Matrix:
- [[ 60  12   6   9   8   5  13]
- [  3 122   4   0   4   0   7]
- [ 27  28 142  28  23  21  37]
- [ 13  11   7  93   6   5  20]
- [  1   5   4   1  59   2   2]
- [  6   3   3   1   3  49   2]
- [ 16   5  11  16   7   9  81]]
-Node Classification on random seed  8913 -> 0.605
-Confusion Matrix:
- [[ 82   4   2   2   1   9  10]
- [  1 133  12   5   2   4   2]
- [ 25  25 111  57  31  16  40]
- [ 10   0  16  98   9   7   9]
- [  1   4   5   5  66   1   0]
- [  6   3   3   2   0  39   5]
- [ 10   3  11  11   5  21  76]]
-Node Classification on random seed  8914 -> 0.639
-Confusion Matrix:
- [[ 76   2   1   4   4   9  13]
- [  1 131   6   1   8   3   6]
- [ 19  24 162  26  23  22  22]
- [ 13   6  34 107   2   6   6]
- [  0   5   2   4  53   3   4]
- [  3   0   4   1   1  46  11]
- [  9   1  21  12   6  13  64]]
-Node Classification on random seed  8915 -> 0.651
-Confusion Matrix:
- [[ 74   7   1   6   2   3   9]
- [ 10 123   8   0  14   3   5]
- [ 21  20 148  28  19  15  46]
- [  5   4  17 122   4   4  17]
- [  0   9   4   0  63   0   0]
- [  6   0   4   2   0  45   6]
- [ 12   5   4  10   7  12  76]]
-Node Classification on random seed  8916 -> 0.601
-Confusion Matrix:
- [[ 64   2   2  12   3  15  17]
- [  3 125   7   3   6   4   4]
- [ 28  28 148  41  15  16  33]
- [ 17   1  11 100   3   4  24]
- [  0  10   5   1  50   1   3]
- [  6   1   2   3   0  43   8]
- [  7   4  13  12  10  14  71]]
-Node Classification on random seed  8917 -> 0.678
-Confusion Matrix:
- [[ 67   1   2   5   1   8   8]
- [  1 137   4   1   7   3   3]
- [ 34  25 167  19  21  11  32]
- [  7   2  17 120   0   7  13]
- [  2  11   2   2  64   0   2]
- [  5   0   4   2   0  53   1]
- [ 15   3   8  14   4  15  70]]
-Node Classification on random seed  8918 -> 0.581
-Confusion Matrix:
- [[ 64   3   2   7   2  20   3]
- [  4 121   7   2  13   0   1]
- [ 28  27 120  47  16  25  38]
- [  8   7  14 101   4   7  18]
- [  3   8   2   2  60   1   1]
- [  8   5   4   1   2  49   5]
- [ 17   5   9   8   4  31  66]]
-Node Classification on random seed  8919 -> 0.623
-Confusion Matrix:
- [[ 71   1   2  10   4   5  17]
- [  6 123   6   1   4   2   4]
- [ 24  17 160  27  22  19  44]
- [ 11   9  19  98   5   9  17]
- [  1   4   7   4  52   0   3]
- [ 11   2   2   2   0  39   1]
- [ 20   2  10   8   6   9  80]]
-Node Classification on random seed  8920 -> 0.601
-Confusion Matrix:
- [[ 65   1   5   5   5  14   8]
- [  7 124   3   1   7   1   2]
- [ 33  13 102  28  55  32  37]
- [  9   3  14 115   5   4  13]
- [  1   7   6   0  73   1   4]
- [  3   1   0   2   1  52   8]
- [ 16   5   7   5   8  19  70]]
-Node Classification on random seed  8921 -> 0.615
-Confusion Matrix:
- [[ 79   1   4   5   3   8   7]
- [  7 135   6   2   1   3   3]
- [ 26  28 149  38  16  21  31]
- [ 11   3  27  88   6   6  24]
- [  1   6   3   4  54   2   4]
- [ 13   1   1   5   0  47   3]
- [ 11   3   9   6  10  16  63]]
-Node Classification on random seed  8922 -> 0.617
-Confusion Matrix:
- [[ 72   0   4   3   4   8  12]
- [  8 131   3   3  10   4   8]
- [ 28  10 140  58  22  19  30]
- [ 18   4  11  90   7   2  21]
- [  2   3   1   5  64   0   3]
- [  5   0   4   2   0  42   2]
- [ 16   2   6   9   6  20  78]]
-Node Classification on random seed  8923 -> 0.56
-Confusion Matrix:
- [[ 54   3   6   5   8  15  13]
- [ 12 109   6   4   9   4   5]
- [ 28  37 121  19  27  37  42]
- [  9  12  27  94   4   6  12]
- [  3   5   4   0  65   1   3]
- [  6   1   3   2   2  48   3]
- [  5   5   4  14  17  12  69]]
-Node Classification on random seed  8924 -> 0.6
-Confusion Matrix:
- [[ 75   3   4   3   0  18   3]
- [  3 126   9   5   5   0   3]
- [ 23  29 127  48  33  15  45]
- [ 19   2  10 102   6   9  12]
- [  0   6   1   1  63   2   4]
- [  5   7  10   0   1  35   0]
- [ 17   5  10   7   3  14  72]]
-Node Classification on random seed  8925 -> 0.593
-Confusion Matrix:
- [[ 87   1   2   2   4  10  10]
- [  5 127  11   6  11   5   3]
- [ 19  21 112  19  58  18  58]
- [ 12   4  12  85  22   6   6]
- [  1   6   1   0  66   2   1]
- [  9   2   1   0   4  39   6]
- [ 14   1   7   6  15   6  77]]
-Node Classification on random seed  8926 -> 0.577
-Confusion Matrix:
- [[ 62   2   4   4   5  15  11]
- [  6 122   4   1  13   3   6]
- [ 18  18 124  35  60  20  44]
- [  7   1  28  88   8   9  16]
- [  0   8  11   0  45   1   3]
- [  2   0   3   2   4  52   3]
- [  2   5   5   6  10  20  84]]
-Node Classification on random seed  8927 -> 0.614
-Confusion Matrix:
- [[ 66   3   3   4   7  14  10]
- [  2 129   8   2  13   2   6]
- [ 37  22 138  28  37  30  21]
- [ 10   5  17 112   2   5   8]
- [  1   3   3   0  62   5   1]
- [  7   2   3   1   1  43   5]
- [ 16   3  12  11   6  10  64]]
-Node Classification on random seed  8928 -> 0.641
-Confusion Matrix:
- [[ 73   2   3   6   3  10   7]
- [  5 131  12   0   4   5   5]
- [ 37  19 156  38  19  14  23]
- [  9   8   9 107   3  10   9]
- [  2   6   4   1  63   0   1]
- [  8   0   0   0   2  45   5]
- [ 10   9   8  13   9  21  66]]
-Node Classification on random seed  8929 -> 0.557
-Confusion Matrix:
- [[ 65   0  14   5   1  11  13]
- [  4 108   5   9   7   2   5]
- [ 24  27 119  49  38  12  43]
- [  5   6  20 110   3   5  14]
- [  2   4   5   8  52   0   1]
- [  4   2   4   3   3  42   5]
- [ 18   3  29   8  12  10  61]]
-Node Classification on random seed  8930 -> 0.623
-Confusion Matrix:
- [[ 74   1  10   3   7   4  14]
- [  8 121   4   5   5   2   3]
- [ 22  26 156  25  25  15  43]
- [  9   5  15  93   3   9  27]
- [  2   5   3   1  62   1   4]
- [  1   0   9   1   0  42   9]
- [ 10   4  15   5   7  10  75]]
-Node Classification on random seed  8931 -> 0.59
-Confusion Matrix:
- [[ 66   4   1   1   3  11  12]
- [  7 144   5   5   6   0   3]
- [ 43  18 139  52  23  13  37]
- [ 24   5  14  82  17   5  10]
- [  4   5   3   2  57   0   3]
- [ 13   0   0   4   2  41   2]
- [  9   3  16   6   5  14  61]]
-Node Classification on random seed  8932 -> 0.613
-Confusion Matrix:
- [[ 55   3   6   8   7  17   2]
- [  5 136   3   6  10   0   5]
- [  9   9 156  22  34  14  58]
- [  9   0  14 102   5   7  33]
- [  2   6   4   0  50   1   4]
- [  6   0   5   1   2  35  15]
- [ 10   6  11   8   5  15  79]]
-Node Classification on random seed  8933 -> 0.641
-Confusion Matrix:
- [[ 78   2   0   6   1   4   8]
- [  7 124   6   1   6   5   9]
- [ 35  19 173  34  14  17  24]
- [  3   6  21  97   7   8  15]
- [  2   3   5   2  60   0   8]
- [ 11   0   2   1   0  42   2]
- [ 19   2  12   6   6  20  67]]
-Node Classification on random seed  8934 -> 0.613
-Confusion Matrix:
- [[ 77   1   4   4   2   9   8]
- [  0 141   4   6   5   3   1]
- [ 26  18 133  48  22  17  53]
- [ 18   5  21  85  20   3   8]
- [  4   2   3   3  60   1   3]
- [  1   0   3   0   2  44   8]
- [  5   4  10   9   5  18  73]]
-Node Classification on random seed  8935 -> 0.583
-Confusion Matrix:
- [[ 76   7   4   7   3   4  14]
- [  4 119   2   4   8   3   6]
- [ 19  37 113  32  48  14  50]
- [ 13   6  15 101   7   5  16]
- [  1   6   6   0  65   4   2]
- [  6   0   1   7   0  36   7]
- [ 13   4  14   2  11   5  73]]
-Node Classification on random seed  8936 -> 0.597
-Confusion Matrix:
- [[ 71   4   1   4   3  18   2]
- [  6 123  14   0   7   0   3]
- [ 22  25 133  32  18  28  36]
- [ 21   4  21  88   6  10  13]
- [  4  10  10   0  57   1   6]
- [  3   6   2   1   1  44   9]
- [ 13   8   9   3   5  14  81]]
-Node Classification on random seed  8937 -> 0.578
-Confusion Matrix:
- [[ 65   3   1   1   7  10  20]
- [  8 112   5   1  12   0   8]
- [ 33  22 144  22  30  24  39]
- [ 19   1  35  77   9   5  10]
- [  3   5  16   1  65   0   0]
- [  9   1   7   0   0  40   6]
- [ 11   0   2   2   4  30  75]]
-Node Classification on random seed  8938 -> 0.619
-Confusion Matrix:
- [[ 57   1   4   1   0  26  10]
- [ 10 131  10   3   3   1   6]
- [ 20  23 159  26  24  27  30]
- [ 10   6  12  75  10  10  17]
- [  0   8  10   2  65   2   1]
- [  2   4   3   1   1  46   6]
- [  2   3   5  18   6  17  86]]
-Node Classification on random seed  8939 -> 0.625
-Confusion Matrix:
- [[ 59   3  10   4   3  13  15]
- [  2 148   2   4  10   4   4]
- [ 25  19 155  28  26  24  49]
- [ 13   5  20  87   0   5  11]
- [  2   4   5   1  54   0   1]
- [  3   1   2   1   1  51   5]
- [  8   2  10   8   8  14  71]]
-Node Classification on random seed  8940 -> 0.651
-Confusion Matrix:
- [[ 82   5   1  11   2  14  12]
- [  5 104   2   3  11   3   4]
- [ 25  20 172  40  18  17  30]
- [  8   8  12 106   8   7   6]
- [  0   5   2   1  68   0   1]
- [ 10   1   3   0   0  48   3]
- [  8   3  11   6   9  14  71]]
-Node Classification on random seed  8941 -> 0.627
-Confusion Matrix:
- [[ 78   1   3  10   2   7   7]
- [  8 136   8   0   5   0   6]
- [ 14  21 143  32  46  24  33]
- [  6   6  13  96  10   6  12]
- [  1   9   5   3  51   1   2]
- [  5   0   2   2   0  60   2]
- [ 16   2   8  15   7  13  63]]
-Node Classification on random seed  8942 -> 0.595
-Confusion Matrix:
- [[ 59   4   7   8   3  12  17]
- [  1 135   3   1   2   4   3]
- [ 18  36 153  45  23  16  39]
- [  6   8  23  82  14   5   8]
- [  3  11   2   4  60   1   3]
- [  5   0  10   1   0  46   3]
- [  5  10   9   8   7  17  60]]
-Node Classification on random seed  8943 -> 0.612
-Confusion Matrix:
- [[ 69   9   9   3   6  10   7]
- [  6 122   2   3   4   3   5]
- [ 15  23 131  45  36  27  42]
- [ 18   3  10 102   3   4  15]
- [  4   6   0   1  70   1   0]
- [ 11   2   2   1   1  43   6]
- [ 11   3   8   7   4  12  75]]
-Node Classification on random seed  8944 -> 0.617
-Confusion Matrix:
- [[ 75   2   6  12   2  10   8]
- [  5 122   8   4  12   8   4]
- [ 22  17 147  32  31  28  40]
- [  7   3  14 107   2  17   7]
- [  0   4   4   0  66   1   2]
- [  7   3   2   2   2  35   2]
- [ 11   2  12   6   6  16  65]]
-Node Classification on random seed  8945 -> 0.615
-Confusion Matrix:
- [[ 55   4   7   7   3   7  11]
- [  7 141   4   0  11   0   5]
- [ 25  21 144  30  41  13  41]
- [ 12  11  23  87   4   8  12]
- [  0   6   4   1  66   0   2]
- [  5   1   2   2   4  45   6]
- [ 12   5   5   4   6  13  77]]
-Node Classification on random seed  8946 -> 0.606
-Confusion Matrix:
- [[ 84   3   8   2   4   6   1]
- [  5 124   4   1  16   0   7]
- [ 35  22 134  49  19   6  33]
- [ 20   5  17  92   8   9  13]
- [  2   8   5   0  66   1   4]
- [  8   2   6   4   2  36   4]
- [ 13   6   7   9  12   8  70]]
-Node Classification on random seed  8947 -> 0.61
-Confusion Matrix:
- [[ 68   0   3   3   4  15  10]
- [  0 123   2   0   8   6   9]
- [ 26  28 157  50  15  18  29]
- [ 11   9  22  90   6  13  12]
- [  0   7   4   2  55   3   2]
- [  3   1   3   4   6  42   5]
- [ 11   4   7   8   4  17  75]]
-Node Classification on random seed  8948 -> 0.609
-Confusion Matrix:
- [[ 65   0  11   5   5  10   9]
- [  4 118   7   2   7   2  10]
- [ 16  41 165  28  15  23  48]
- [  4   7  17  91   6   6  19]
- [  2   8   3   1  58   0   2]
- [  6   2   1   4   0  36   6]
- [ 11   6   7  10   4  16  76]]
-Node Classification on random seed  8949 -> 0.604
-Confusion Matrix:
- [[ 72   4   5   3   8   9  13]
- [  4 137   3   1   7   5   5]
- [ 29  26 129  30  32  22  35]
- [ 17   6  18  89  11   6   8]
- [  1  13   2   2  63   0   1]
- [  7   0   2   6   1  40   7]
- [ 21   2   6   5   4   9  74]]
-Node Classification on random seed  8950 -> 0.603
-Confusion Matrix:
- [[ 64   3   4   1   5  17   8]
- [  1 133   2   1   8   3   1]
- [ 26  45 135  61  24  13  37]
- [ 21   6  14  94   3   5  11]
- [  0   5   2   0  65   1   2]
- [  5   1   1   2   0  46   4]
- [ 10  17   3   4   5  15  66]]
-Node Classification on random seed  8951 -> 0.622
-Confusion Matrix:
- [[ 61   3  11  12   8  12  11]
- [  8 130   8   5   7   0   4]
- [ 19  17 168  41  22  15  35]
- [  4   7  12  98   4   0  15]
- [  1   6   6   1  56   0   4]
- [  6   1   2   5   1  40   7]
- [ 17   3  11  10   8   9  69]]
-Node Classification on random seed  8952 -> 0.614
-Confusion Matrix:
- [[ 58   5   7   4   3  14  10]
- [  7 116   3   0   8   2   9]
- [ 34  22 168  27  21  21  20]
- [ 23   8  20  98   7   2  10]
- [  0   3   5   1  63   1   1]
- [  4   1   2   6   1  36   8]
- [ 11   5  17  11   3  19  75]]
-Node Classification on random seed  8953 -> 0.608
-Confusion Matrix:
- [[ 64   4   0  18   6   7  17]
- [  5 136   3   4   2   1  10]
- [ 16  21 129  44  23  32  37]
- [ 16   2  16 103   2   3  12]
- [  5   4   0   2  61   4   0]
- [  7   1   0   2   0  38  12]
- [ 16   1   1  15   9  12  77]]
-Node Classification on random seed  8954 -> 0.661
-Confusion Matrix:
- [[ 65   3   6   3   2   5  22]
- [  0 133   5   1   2   3  13]
- [ 12  23 148  28  27  15  46]
- [ 10   1  11 114   5   7  10]
- [  1   8   1   2  56   2   5]
- [ 10   0   2   1   1  43  10]
- [  7   1   5   2   8  13 102]]
-Node Classification on random seed  8955 -> 0.633
-Confusion Matrix:
- [[ 72   3   2   1   2  16  12]
- [  2 124   8   0   2   3  15]
- [ 10  25 158  21   9  39  42]
- [  7   4  27  93   8   4  17]
- [  1   7   2   1  58   6   2]
- [ 11   4   1   1   1  38   7]
- [  6   2   4   3   4  25  90]]
-Node Classification on random seed  8956 -> 0.609
-Confusion Matrix:
- [[ 73   3   6   7   6  13   2]
- [  3 143   5   0   8   4   2]
- [ 23  25 111  63  37  16  38]
- [ 14   1  17 107  10   8   7]
- [  2   4   2   0  50   0   0]
- [  3   0   1   0   3  41   4]
- [ 14   6  11   7   1  15  84]]
-Node Classification on random seed  8957 -> 0.653
-Confusion Matrix:
- [[ 77   2   4   3   5   3  14]
- [  5 132  10   3   2   4   2]
- [ 23  20 176  32  16  20  45]
- [  6   2  20 103   7   2  13]
- [  1   5   4   3  56   2   1]
- [  8   2   2   4   1  39   8]
- [ 15   2  12   3   5   6  70]]
-Node Classification on random seed  8958 -> 0.618
-Confusion Matrix:
- [[ 66   1   7   3   7   8  11]
- [  3 148   1   1   7   4   6]
- [ 26  26 133  24  37  26  39]
- [  9   5   9 103   9   8   8]
- [  2  13   2   1  59   0   3]
- [  8   1   3   1   0  41   5]
- [ 13   3   7  18   9   8  68]]
-Node Classification on random seed  8959 -> 0.632
-Confusion Matrix:
- [[ 64   6   4   9   0   5  24]
- [  2 127   3   4   9   4   2]
- [ 11  20 158  38  16  22  41]
- [ 13   3  12  92   2  13  21]
- [  3   8   1   4  62   5   2]
- [  4   2   0   4   0  38  10]
- [ 12   8   6   4   3   8  91]]
-Node Classification on random seed  8960 -> 0.634
-Confusion Matrix:
- [[ 75   2   5   2   6   7  11]
- [  4 129   5   0   6   2   8]
- [ 19  35 116  41  28  24  30]
- [ 21   2   2 117   7   6  12]
- [  0   6   2   2  65   2   6]
- [  5   4   5   0   1  49   5]
- [ 19   8   6   3   3   4  83]]
-Node Classification on random seed  8961 -> 0.648
-Confusion Matrix:
- [[ 72   0   6   4   3  10  13]
- [  8 138   4   6   3   0   4]
- [ 20  29 163  26  29  19  28]
- [  8   7  18 104   3   9  15]
- [  2   5   2   3  55   0   2]
- [  6   1   1   4   0  38  13]
- [  7   3  13   5   6   7  78]]
-Node Classification on random seed  8962 -> 0.605
-Confusion Matrix:
- [[ 64   2   7   4   2   9   2]
- [ 10 110  15   3   9   9   1]
- [ 17  32 143  28  25  24  38]
- [  4  10  24 107   2  12  10]
- [  1   3   2   4  70   2   2]
- [  2   0   3   2   2  46   5]
- [ 17   5  10   9   3  24  65]]
-Node Classification on random seed  8963 -> 0.621
-Confusion Matrix:
- [[ 78   2   5   2   3  19  11]
- [  3 129   5   2   5   5   3]
- [ 23  24 140  31  23  10  58]
- [ 19   9  15  93   5   2  15]
- [  2   5   3   1  61   1   3]
- [  8   0   4   0   1  40   6]
- [ 13   3   3  10   6  11  80]]
-Node Classification on random seed  8964 -> 0.585
-Confusion Matrix:
- [[ 73   5   2   8   3   9  14]
- [  6 113   6   7   4   6   4]
- [ 31   8 123  43  29  26  51]
- [ 11   8  15 112   5   5  11]
- [  1   4   1   0  59   2   2]
- [ 10   1   2   0   0  43   5]
- [ 19   6   3  15   9  18  62]]
-Node Classification on random seed  8965 -> 0.636
-Confusion Matrix:
- [[ 82   6   3   6   1  12   7]
- [  6 118   0   2   2   0   1]
- [ 25  17 127  44  26  37  32]
- [ 12   3  18 122  13   5   3]
- [  1   4   4   1  61   3   2]
- [  8   2   5   3   0  45   4]
- [ 11   1  13   8   3  10  81]]
-Node Classification on random seed  8966 -> 0.62
-Confusion Matrix:
- [[ 64   8  10   9   4   5   2]
- [  4 125   8   5   3   4   1]
- [ 37  19 147  41  22  10  48]
- [ 16   6  13 101   2   4   8]
- [  1  10   8   1  53   0   1]
- [  8   0   1   3   3  45   5]
- [  7   2   9  10   7  15  85]]
-Node Classification on random seed  8967 -> 0.62
-Confusion Matrix:
- [[ 68   1   9   3   5   5   5]
- [  6 121   6   7  11   0   2]
- [ 19  18 143  23  36  19  41]
- [ 28   1   8 112   9   6  10]
- [  1   8   0   3  59   0   2]
- [ 10   1   3   0   3  54   9]
- [ 15   5  14   6  14   8  63]]
-Node Classification on random seed  8968 -> 0.613
-Confusion Matrix:
- [[ 65   3   4   7   5   7   8]
- [  3 127   1   2   7   2   8]
- [ 28  18 141  41  24  21  45]
- [ 11   4  14  91  10   7  23]
- [  1   9   4   0  70   1   4]
- [  5   1   2   1   4  42   6]
- [  8   5   8  10   3  12  77]]
-Node Classification on random seed  8969 -> 0.62
-Confusion Matrix:
- [[ 70   0   1   6   2  20  12]
- [ 11 126   1   3   8   0   1]
- [ 20  50 142  30  19  13  31]
- [ 17   7  11  98   5   2  18]
- [  1   8   2   0  58   0   1]
- [  3   3   2   6   0  46   5]
- [ 13   5  10  15   7  11  80]]
-Node Classification on random seed  8970 -> 0.656
-Confusion Matrix:
- [[ 70   3   7   3   4   7   9]
- [  5 119   7   6   7   4   8]
- [ 21  16 172  29  28  24  22]
- [ 15   3  18 110   7   6   7]
- [  0   3   4   2  58   2   2]
- [  9   0   1   3   0  49   1]
- [ 15   3   7   6   7  13  78]]
-Node Classification on random seed  8971 -> 0.611
-Confusion Matrix:
- [[ 80   2   3   5   7  16   9]
- [  1 124   5   4   6   4   3]
- [ 22  21 140  42  30  27  28]
- [ 12   5  24  90   2   9  19]
- [  2   4   2   1  52   1   3]
- [  6   1   1   1   1  47   8]
- [  9   2   9   7   5  20  78]]
-Node Classification on random seed  8972 -> 0.646
-Confusion Matrix:
- [[ 73   1   2   5   2  18   9]
- [  2 124  11   1   6   2   5]
- [ 26  26 138  49  17  18  36]
- [  6   5  10 112   1   6  11]
- [  1   4   0   6  66   3   2]
- [  3   4   0   2   2  44   6]
- [ 10   2   5  10   5  14  89]]
-Node Classification on random seed  8973 -> 0.586
-Confusion Matrix:
- [[ 74   2   2   6   1  13  10]
- [  2 124  10   6   2   4   3]
- [ 27  11 119  55  53  16  39]
- [ 17   4  12 105   9   3   9]
- [  1   7   1   0  58   0   2]
- [  5   1   5   4   7  37   5]
- [  9   3  11  17   7  13  69]]
-Node Classification on random seed  8974 -> 0.582
-Confusion Matrix:
- [[ 76   1   4   2   2  11  11]
- [  5 116   6   2  23   4   8]
- [ 32  21 139  30  32  40  24]
- [  8   7  15  86   8   7  12]
- [  2   7   5   3  54   1   2]
- [ 11   2   0   1   1  43   4]
- [ 10   4   8   6  12  24  68]]
-Node Classification on random seed  8975 -> 0.607
-Confusion Matrix:
- [[ 50   3   6   3   2  16  10]
- [  6 119  12   3   2   5   3]
- [ 19  27 145  23  35  42  45]
- [  8   3  13 103   3   7  15]
- [  1   4   4   5  60   3   2]
- [  4   0   4   1   0  53   6]
- [  3   0  16   2   5  22  77]]
-Node Classification on random seed  8976 -> 0.607
-Confusion Matrix:
- [[ 66   2   7   6   3   8  19]
- [  2 111   7   4  22   2   3]
- [ 21  13 151  36  29  18  46]
- [  6   2  18 102   8   9   7]
- [  3   1   6   3  63   1   8]
- [  4   2   6   0   0  51   6]
- [  5   6   6  10   8  20  63]]
-Node Classification on random seed  8977 -> 0.615
-Confusion Matrix:
- [[ 52   3   9   6   4  13  18]
- [  4 131  13   4   0   0   6]
- [ 24  23 146  39  11  32  30]
- [ 11  11  10 109   0   4  12]
- [  3   9   2   2  55   1   2]
- [ 11   2   3   0   1  45   4]
- [ 10   4  13   8   5  18  77]]
-Node Classification on random seed  8978 -> 0.621
-Confusion Matrix:
- [[ 79   7   2   6   3   4   8]
- [  5 133   4   2   9   5   1]
- [ 27  21 144  22  25  31  31]
- [ 11   5  24  85  10   1  14]
- [  3   7   8   0  67   0   3]
- [  7   0   4   1   3  33  20]
- [  9   1  12   8  11   4  80]]
-Node Classification on random seed  8979 -> 0.586
-Confusion Matrix:
- [[ 59   6  13   1   5  13   5]
- [  2 148   7   4   5   4   0]
- [ 16  18 133  70  33  17  35]
- [ 23   1  14  88   6   8  23]
- [  6   6   7   1  40   0   4]
- [  6   2   2   1   2  51   3]
- [ 10   1   7   1   9  17  67]]
-Node Classification on random seed  8980 -> 0.61
-Confusion Matrix:
- [[ 82   3   3   1   8  13  12]
- [  9 130  13   1  11   3   1]
- [ 20  29 127  42  32  17  43]
- [ 10   7   6  92   8   9  16]
- [  5   2   0   0  62   3   4]
- [  4   1   2   0   0  48   0]
- [ 25   1   6   8   5   7  69]]
-Node Classification on random seed  8981 -> 0.635
-Confusion Matrix:
- [[ 71   1   1   3   1  14   5]
- [  3 130   3   5   1   4   7]
- [ 24  31 138  42  21  23  37]
- [ 11   5   8 107   3  17  12]
- [  1   7   4   0  68   1   5]
- [  7   0   2   4   2  40   3]
- [  8   5   5  14   1  14  81]]
-Node Classification on random seed  8982 -> 0.571
-Confusion Matrix:
- [[ 68   2   1   8   3  12   7]
- [  5 124   8   0   6   1   6]
- [ 31  33  96  43  29  16  66]
- [  7   5  23  96  11   6  18]
- [  3   2   5   3  66   2   2]
- [  3   0   2   2   0  53   9]
- [  5   3   6  12   7  16  68]]
-Node Classification on random seed  8983 -> 0.619
-Confusion Matrix:
- [[ 71   2   7   6   4  10   4]
- [  5 134   1   9   4   1   2]
- [ 22  19 148  27  13  28  55]
- [ 18   4  19 102   6   2  21]
- [  3   7   5   3  52   4   1]
- [  5   2   3   1   0  46   8]
- [ 20   3   4   5   3  15  66]]
-Node Classification on random seed  8984 -> 0.608
-Confusion Matrix:
- [[ 67   2   7   5   3   8  20]
- [  4 125   6   4   8   1   1]
- [ 29  22 145  26  15  30  51]
- [ 14   2  14 100   7   6  28]
- [  0   8   5   0  49   0   5]
- [  5   2   2   0   1  42   5]
- [  8   6   7   5   8  12  80]]
-Node Classification on random seed  8985 -> 0.629
-Confusion Matrix:
- [[ 71   2   1   4   3  11   5]
- [  7 135   7   4   7   4   2]
- [ 16  24 135  40  25  31  40]
- [ 16   3   6  99   5   5  14]
- [  2  11   1   3  56   0   5]
- [ 15   1   2   0   0  43   4]
- [ 14   5   5   2   7  12  90]]
-Node Classification on random seed  8986 -> 0.619
-Confusion Matrix:
- [[ 69   2   5  11   7  16   3]
- [  1 120   8   1  11   2   3]
- [ 27  32 152  47  19  17  18]
- [  8   3  17 103   4   7   5]
- [  1   5   3   3  60   0   0]
- [  3   3   5   3   2  45   4]
- [ 10   3   8  13   4  37  70]]
-Node Classification on random seed  8987 -> 0.638
-Confusion Matrix:
- [[ 58   2   1  12   1  12  12]
- [  4 129   4   1   3   5   5]
- [ 36  21 128  28  20  30  34]
- [ 11   4  14 119   4   5   9]
- [  1  12   4   2  61   2   2]
- [  9   0   0   1   2  49   6]
- [ 16   8   5   1   6   7  94]]
-Node Classification on random seed  8988 -> 0.645
-Confusion Matrix:
- [[ 61   6   5   3   3   1  21]
- [  4 133   7   3   7   2   3]
- [ 23  13 165  19  30  18  43]
- [  5   4  19 105  15   5  10]
- [  1   3   7   0  60   1   1]
- [ 15   5   1   0   1  45   8]
- [  9   7   9   7   6   5  76]]
-Node Classification on random seed  8989 -> 0.57
-Confusion Matrix:
- [[ 68   1   2  12   6  15  14]
- [  5 121   3   5  10   3   2]
- [ 23  19 116  52  33  27  46]
- [ 12   0  28  95   9  10  11]
- [  0   2   3   1  54   1   3]
- [  5   1   3   1   2  53   3]
- [ 11  10  10   2   4  20  63]]
-Node Classification on random seed  8990 -> 0.648
-Confusion Matrix:
- [[ 79   6   0   7   2   5   6]
- [  5 132   4   1   9   0   3]
- [ 13  23 138  36  28  13  41]
- [ 12   8  16 114   6   4   7]
- [  2  14   5   1  73   1   1]
- [  8   1   1   1   0  42   6]
- [ 12   7  10   5  10  12  70]]
-Node Classification on random seed  8991 -> 0.616
-Confusion Matrix:
- [[ 56   3  15   3   7   8  16]
- [  5 115   8   5   4   1   9]
- [ 27  13 122  33  29  30  44]
- [ 11   5  10 110   6   8   6]
- [  0   7   3   0  63   1   2]
- [ 11   3   1   4   0  54   3]
- [ 10   8   8   6   7   4  96]]
-Node Classification on random seed  8992 -> 0.619
-Confusion Matrix:
- [[ 68   4  11  10   4  13   4]
- [  2 132   4   1  15   2   1]
- [ 28  12 150  27  26  20  44]
- [ 10   7  10 112   5  11  13]
- [  0   5   1   1  50   2   0]
- [  4   1  10   3   7  45   3]
- [ 12   3  10   7  17  11  62]]
-Node Classification on random seed  8993 -> 0.592
-Confusion Matrix:
- [[ 47   5   4  10   4  19  18]
- [  4 128   9   1  12   2   6]
- [ 21   8 133  30  33  25  53]
- [ 14   4  17  99   1  10  19]
- [  2   4   3   1  61   0   3]
- [  6   5   0   1   1  40   2]
- [ 13   6   6   2   5  19  84]]
-Node Classification on random seed  8994 -> 0.619
-Confusion Matrix:
- [[ 54   1  14   9   5  10  18]
- [  1 130   9   4   9   3   5]
- [ 16   9 146  34  18  33  31]
- [ 13   1  22 118   5   8  15]
- [  6   0   4   3  57   1   3]
- [  4   0   1   4   3  41   7]
- [  8   5   5   5   5  24  73]]
-Node Classification on random seed  8995 -> 0.619
-Confusion Matrix:
- [[ 59   6   6   4   3  22   6]
- [  3 138   1   4   8   4   2]
- [ 24  19 157  29  28  35  37]
- [ 16   7   6  97  17   8  14]
- [  0   1   6   2  56   2   1]
- [  3   1   0   0   2  43   6]
- [ 13   7   7   0   8  13  69]]
-Node Classification on random seed  8996 -> 0.616
-Confusion Matrix:
- [[ 80   8   2   8   2  12  13]
- [  5 126   5   2   8   7   3]
- [ 23  23 111  26  37  33  47]
- [  5   2  21 109   1   5  13]
- [  2   4   4   1  71   1   1]
- [  3   1   0   6   1  40   7]
- [  9   5   4   3   8  13  79]]
-Node Classification on random seed  8997 -> 0.597
-Confusion Matrix:
- [[ 73   2   4   5   4   9   5]
- [  3 129   2   8   2   5   1]
- [ 24  23 118  56  40  20  28]
- [  7   3  18  99   5  13  10]
- [  5   8   1   0  67   1   5]
- [  2   3   4   3   1  48   5]
- [ 21   6   8   4  11  18  63]]
-Node Classification on random seed  8998 -> 0.608
-Confusion Matrix:
- [[ 68   0   2   6   3  16  13]
- [  1 124   8   8   3   6   6]
- [ 25  14 130  51  27  21  40]
- [ 21   4  15 101   7   5   9]
- [  0   4   4   5  55   2   3]
- [  4   1   1   0   0  49   1]
- [ 15   5  11   5   4  16  81]]
-Node Classification on random seed  8999 -> 0.638
-Confusion Matrix:
- [[ 73   4   2   3   5   5   9]
- [  5 112   7   6  29   3   1]
- [ 13  11 168  19  30  20  45]
- [  6   4  17 105   8   2  11]
- [  1   2   4   3  72   1   5]
- [  4   1   2   0   5  42   4]
- [  4   6  11   8  11  25  66]]
-Node Classification on random seed  9000 -> 0.631
-Confusion Matrix:
- [[ 73   2   3   3   9  10   3]
- [  2 113   4   0  19   2   2]
- [ 20  29 180  22  21  19  27]
- [ 18   1  29  99   5   7   4]
- [  1   3   6   1  64   2   4]
- [  9   1   2   1   1  44   3]
- [ 15   7  10   6  19  17  58]]
-Node Classification on random seed  9001 -> 0.596
-Confusion Matrix:
- [[ 84   2   3   2   2  10   8]
- [  2 133   5   1   1   6   2]
- [ 26  15 101  43  38  27  50]
- [ 21   5  12  91   5   6  11]
- [  2   7   1   1  64   2   4]
- [  5   0   3   3   0  57   7]
- [ 14   4  18   7   7  16  66]]
-Node Classification on random seed  9002 -> 0.642
-Confusion Matrix:
- [[ 77   1  10   1   3  16   6]
- [  5 131   4   1  16   2   5]
- [ 18  18 147  35  25  10  52]
- [ 13   6  13  96   2   9  12]
- [  0   4   4   1  55   2   1]
- [  5   0   5   1   0  51   7]
- [  6   2   8   5  11  13  85]]
-Node Classification on random seed  9003 -> 0.582
-Confusion Matrix:
- [[ 74   5   4   7   4   9  11]
- [  7 128   6   2   9   1   3]
- [ 17  30 117  50  42  24  26]
- [ 35   5   5  91   8   5  11]
- [  0   7   0   1  64   1   7]
- [  4   0   0   3   2  45   7]
- [ 14   2  19   8  11   6  63]]
-Node Classification on random seed  9004 -> 0.623
-Confusion Matrix:
- [[ 89   1   2   3   1  15  10]
- [  8 103   8   3   7   5   9]
- [ 33  16 143  32  14  39  33]
- [ 14   4  11 110   3   6   8]
- [  3   4   6   3  58   3   0]
- [ 12   1   1   0   0  45   4]
- [ 19   5  12   3   6  10  75]]
-Node Classification on random seed  9005 -> 0.652
-Confusion Matrix:
- [[ 71   1   1   6   3  16   3]
- [  5 142   2   0   9   3   2]
- [ 21  28 156  22  27  30  41]
- [ 10   5   8  99   3   9   7]
- [  1   1   5   4  63   1   4]
- [  0   0   3   3   4  50   5]
- [ 11   2  11  10  11  10  71]]
-Node Classification on random seed  9006 -> 0.607
-Confusion Matrix:
- [[ 78   4   1   2   2   9  10]
- [  2 134   5   4   9   4   2]
- [ 27  36 114  26  45  13  37]
- [ 12   4  12 108   2   8  24]
- [  1   5   2   1  58   2   3]
- [  4   3   3   3   2  39   5]
- [ 17   8   7   6   9  12  76]]
-Node Classification on random seed  9007 -> 0.589
-Confusion Matrix:
- [[ 67   2  10   3   6  16   9]
- [  8 117   2   4  23   0   9]
- [ 16  11 130  27  56  17  40]
- [  6  11  20 104   6   5  12]
- [  2   5   3   1  60   1   2]
- [  3   0   8   2   0  41   2]
- [  2   5  17   7  11  21  70]]
-Node Classification on random seed  9008 -> 0.62
-Confusion Matrix:
- [[ 82   6   3   0   6   7   7]
- [ 11 113   2   0  12   3   2]
- [ 32  27 146  14  43  13  45]
- [ 19   3  22  98  10   3   4]
- [  0   7   1   0  65   0   4]
- [  2   4   1   0   2  54   2]
- [  6   9   9  15   5  19  62]]
-Node Classification on random seed  9009 -> 0.616
-Confusion Matrix:
- [[ 67   4   7   9   9   2  13]
- [  3 114  10   3  11   1   2]
- [ 21  35 136  28  40  20  34]
- [  2   4  19 117   5   8  21]
- [  0   5   4   1  55   3   0]
- [  1   2   3   2   0  45   2]
- [ 12   2  10   2   3  21  82]]
-Node Classification on random seed  9010 -> 0.636
-Confusion Matrix:
- [[ 80   3   4   1   5   6   6]
- [  6 115   3   2  11   6   5]
- [ 29  13 142  30  24  24  48]
- [  8   4  22  94  11  11  10]
- [  3   1   3   1  72   2   2]
- [  3   2   1   1   0  46   3]
- [  8   3   7   6  15  11  87]]
-Node Classification on random seed  9011 -> 0.617
-Confusion Matrix:
- [[ 89   1   3   1   3  16   7]
- [  2 125   6   2   8   2   6]
- [ 23  36 118  41  36  30  30]
- [ 13   4   9 105   9   7   7]
- [  0   8   1   3  75   0   0]
- [  1   3   2   1   1  41   1]
- [  6   5  11  10   8  20  64]]
-Node Classification on random seed  9012 -> 0.599
-Confusion Matrix:
- [[ 58   2   4   5   4  10  22]
- [  8 108   6   6   6   6   8]
- [ 15  14 136  40  29  23  42]
- [  7   5  15  91  11   5  28]
- [  0   7   4   3  74   2   6]
- [  6   0   3   2   1  47   4]
- [  7   2  10   2  10  11  85]]
-Node Classification on random seed  9013 -> 0.587
-Confusion Matrix:
- [[ 72   2   8   7   2  11   6]
- [  2 117   5   1  13   2   2]
- [ 23  24 119  49  41  27  36]
- [  6   4  31  94   4  10   6]
- [  2   7   1   4  56   1   0]
- [  7   1   0   0   2  56   5]
- [ 12   2  22   5   8  12  73]]
-Node Classification on random seed  9014 -> 0.613
-Confusion Matrix:
- [[ 68   4   5  13   2   5   9]
- [  2 113   3   5  14   1   3]
- [ 20  27 141  21  44  12  41]
- [  9   8  15 105   1   4  14]
- [  2  13   5   4  70   0   4]
- [  6   5   1   2   5  39   6]
- [ 11   3  17   5   8   8  77]]
-Node Classification on random seed  9015 -> 0.62
-Confusion Matrix:
- [[ 77   1   5   3   3   5  13]
- [  2 120   6   2  14   2   7]
- [ 28  27 127  27  27  24  48]
- [ 19   5  12 107   6   2  12]
- [  2   3   2   1  64   1   4]
- [  7   2   4   1   2  36   7]
- [ 11   1   7  11   3  11  89]]
-Node Classification on random seed  9016 -> 0.653
-Confusion Matrix:
- [[ 77   9   2   3   3  11  13]
- [  2 136   9   3   3   0   4]
- [ 15  17 171  41  21  19  28]
- [  8   1  19  88   8   6  19]
- [  1   7   0   0  69   1   1]
- [  7   1   3   0   2  42   6]
- [ 10   8  12   8  10   6  70]]
-Node Classification on random seed  9017 -> 0.535
-Confusion Matrix:
- [[ 50   4   8   6   0   5  24]
- [  7  97   5  10   9   1   8]
- [ 24  36 114  35  48  15  54]
- [ 21   7  18  86  10   4  15]
- [  5   8   1   1  60   0   1]
- [  8   1   0   0   1  48  12]
- [ 16   2  17   6   4   8  80]]
-Node Classification on random seed  9018 -> 0.584
-Confusion Matrix:
- [[ 78   3   0   2   5   7   6]
- [  6 120   4   3  19   0   0]
- [ 32  27 118  34  53  25  25]
- [  5   3   9 107  10   4  19]
- [  0   7   4   0  60   0   2]
- [  8   3   1   4   4  41   5]
- [ 11   4  13   5  27  17  60]]
-Node Classification on random seed  9019 -> 0.575
-Confusion Matrix:
- [[ 59   6  11   7   5   7   6]
- [  6 127   6   5  17   0   5]
- [ 31  34 124  44  14  19  58]
- [ 12   8  11 113  10   3   4]
- [  1   2   3   1  58   0   2]
- [  2   2   7   6   1  45   0]
- [  8   2  21  17   6  15  49]]
-Node Classification on random seed  9020 -> 0.649
-Confusion Matrix:
- [[ 65   4   4   3   0   7  12]
- [  1 130   7   1   1   3   6]
- [ 18  26 136  37  27  19  38]
- [  8   5  11 109   4   6  24]
- [  3   8   7   2  62   1   1]
- [  2   2   9   2   0  57   4]
- [  6   1   8   4   8  11  90]]
-Node Classification on random seed  9021 -> 0.589
-Confusion Matrix:
- [[ 78   1  10  12   7   9   2]
- [  2 123  13   8   2   5   1]
- [ 20  14 118  61  34  18  27]
- [ 22   2  22  96   8   3  13]
- [  1   6   6   3  68   0   0]
- [ 10   0   2   5   0  40   1]
- [ 12   2   7  15   2  23  66]]
-Node Classification on random seed  9022 -> 0.599
-Confusion Matrix:
- [[ 79   3   2   2   3  13   9]
- [  3 127   1   0   8   5   9]
- [ 24  40 136  19  22  25  43]
- [ 14   5  16  88   5   3  20]
- [  3   6   2   4  65   4   5]
- [  3   6   2   1   0  38   7]
- [  8   6  15   1  13  21  66]]
-Node Classification on random seed  9023 -> 0.648
-Confusion Matrix:
- [[ 89   1   4   1   2  11  17]
- [  1 117  11   1   1   1  12]
- [ 22  22 150  28  13  23  45]
- [  6   3  16 118   6   9  12]
- [  1   6   5   2  50   1   4]
- [  8   0   4   0   0  47   7]
- [  8   1  11   8   4  14  77]]
-Node Classification on random seed  9024 -> 0.591
-Confusion Matrix:
- [[ 75   4  12   6   3   7   9]
- [  3 129   3   4   3   3   5]
- [ 31  28 126  39  28  20  28]
- [  9   0  14 108  14   2  23]
- [  1   9   1   1  55   2   0]
- [  6   4   4   4   5  34   9]
- [  7   2  18  13   7  18  64]]
-Node Classification on random seed  9025 -> 0.604
-Confusion Matrix:
- [[ 60   1  10   4   5  12  13]
- [  2 119   5   4  16   3   3]
- [ 44  15 128  35  27  19  41]
- [ 13   5  10 120   7   2  19]
- [  3   8   1   6  61   0   2]
- [  5   1   1   0   1  43   5]
- [ 10   5   5  10   8  10  73]]
-Node Classification on random seed  9026 -> 0.62
-Confusion Matrix:
- [[ 74   6   2   5   3   8  10]
- [  5 124   5   1   8   2   4]
- [ 16  26 156  27  40  27  31]
- [ 19   6  11  92   5  11   9]
- [  1   6   2   1  66   3   1]
- [  4   1   2   0   0  42   7]
- [  6   5  15   4  17  18  66]]
-Node Classification on random seed  9027 -> 0.605
-Confusion Matrix:
- [[ 67   1   3  10   3  11  10]
- [  9 118   3   3  14   5   1]
- [ 24  19 141  36  45  13  32]
- [ 11   3  27  94   4   4  20]
- [  1   8   4   0  53   0   1]
- [ 13   1   1   0   2  42   5]
- [ 10   7   1   8   7  15  90]]
-Node Classification on random seed  9028 -> 0.625
-Confusion Matrix:
- [[ 82   0   3   6   1  15  10]
- [  6 124   8   2   5   6   8]
- [ 19  16 134  50  27  18  32]
- [ 11   1  12 102   4   4  17]
- [  2   3  15   1  54   1   2]
- [  3   1   1   4   4  47   6]
- [  6   2  11   6  10  16  82]]
-Node Classification on random seed  9029 -> 0.596
-Confusion Matrix:
- [[ 55   0   1   8   7  12  23]
- [ 10 135   4   1   9   0   6]
- [ 21  17 140  23  33  23  38]
- [ 21   3  26  91   6   2  10]
- [  2   7   2   2  59   0   3]
- [  6   1   3   4   1  43  10]
- [ 12   4   7   7   9  20  73]]
-Node Classification on random seed  9030 -> 0.605
-Confusion Matrix:
- [[ 70   0   1   4   5  11  20]
- [  3 138   4   3   2   4  11]
- [ 37  21 122  43  22  22  33]
- [ 18   7   9 108   3   3  12]
- [  0  13   5   2  51   0   1]
- [ 10   0   4   0   0  39   5]
- [ 13   2  12   6   6  18  77]]
-Node Classification on random seed  9031 -> 0.653
-Confusion Matrix:
- [[ 80   4   1   5   3   9   3]
- [  5 136   3   2   7   2   1]
- [ 27  18 145  52  18  24  27]
- [ 15   2  13 111   5   2  23]
- [  1   5   1   2  61   2   4]
- [  4   4   2   0   0  48   6]
- [ 11   3  14   5   5   7  72]]
-Node Classification on random seed  9032 -> 0.58
-Confusion Matrix:
- [[ 61   9   4   3   2  10   4]
- [  7 111  10   7  12   8   7]
- [ 33  30 127  27  28  39  13]
- [ 20   3  14  96  10  10   8]
- [  1   0   8   0  67   0   4]
- [ 10   1   2   0   1  47   5]
- [ 17   9  15   3   4  22  71]]
-Node Classification on random seed  9033 -> 0.591
-Confusion Matrix:
- [[ 68   4   2   4   4   4  20]
- [  4 122   7   1  18   1   3]
- [ 26  22 120  24  31  12  60]
- [ 26   6  17  99  11   3  14]
- [  1   7   5   2  67   0   0]
- [  8   3   0   2   0  38   8]
- [ 16   4   5   9   8   7  77]]
-Node Classification on random seed  9034 -> 0.6
-Confusion Matrix:
- [[ 69   3   8   3   3   9   5]
- [  1 116   5   5  16   2   6]
- [ 21  14 135  49  27  25  52]
- [ 18   6  10 101   8  16  13]
- [  4   4   5   1  58   0   1]
- [  3   1   4   5   1  48   2]
- [ 14   2   5   3   5  15  73]]
-Node Classification on random seed  9035 -> 0.599
-Confusion Matrix:
- [[ 64   5   4   6   7   6   9]
- [  3 123  15   6   5   2   7]
- [ 19  29 134  31  29  26  45]
- [ 10   7  15  95   2   8  10]
- [  2   2   9   1  58   0   3]
- [  6   1   3   5   0  34   9]
- [ 21   3  14   3   8   5  91]]
-Node Classification on random seed  9036 -> 0.657
-Confusion Matrix:
- [[ 69   3   1   7   3   7   6]
- [  1 143   2   2   7   5   3]
- [ 14  15 161  57  14   6  47]
- [ 12   7  27 101   5   6  12]
- [  1   4   5   1  56   0   1]
- [  5   2   0   0   0  57   6]
- [ 11   3   5   9   5  16  70]]
-Node Classification on random seed  9037 -> 0.598
-Confusion Matrix:
- [[ 64   4   9   3   1   9  15]
- [  5 114   5   8  22   2   5]
- [ 28  21 135  39  37  17  38]
- [  9   1  23 112   5   4  15]
- [  0   3   3   0  71   0   2]
- [  4   0   4   0   2  42   7]
- [  9   1  13   6   9  14  60]]
-Node Classification on random seed  9038 -> 0.638
-Confusion Matrix:
- [[ 83   4   1   3   3   9  16]
- [  4 126   4   1   5   5   9]
- [ 28  25 149  18  22  19  35]
- [ 16   6  22  91  11   4  17]
- [  0   4   3   2  57   2   2]
- [  5   4   1   2   0  51   6]
- [  5   6   4   4   5  20  81]]
-Node Classification on random seed  9039 -> 0.624
-Confusion Matrix:
- [[ 76   2   4   1   3  15   6]
- [  4 128   6   0  11   1   2]
- [ 34  24 134  36  19  29  44]
- [  8   2  15 120   7   6   8]
- [  3   8   2   0  59   3   5]
- [  6   2   4   4   2  46   3]
- [ 11   3   5   8   7  13  61]]
-Node Classification on random seed  9040 -> 0.632
-Confusion Matrix:
- [[ 78   4   1   4   7  10  10]
- [  2 121   5   4  10   2   5]
- [ 14  30 154  37  26  22  29]
- [  7   5  19 106  18   6  13]
- [  0   2   6   2  52   0   3]
- [  7   0   1   3   1  43   2]
- [  6   5   6  15   5  14  78]]
-Node Classification on random seed  9041 -> 0.582
-Confusion Matrix:
- [[ 62   4   8   6   7  12   6]
- [  6 130   2   0  14   1   5]
- [ 30  27 128  27  12  36  40]
- [ 10   3   9 100  13   9  20]
- [  1   4   3   0  49   5   7]
- [ 15   2   1   0   0  39  11]
- [ 18   1  18   2   4  19  74]]
-Node Classification on random seed  9042 -> 0.591
-Confusion Matrix:
- [[ 56   9   9   8   4   3  10]
- [  4 103   9   4   4   0   3]
- [ 28  46 141  50  27  24  27]
- [  3   3   8 122   4   9  12]
- [  1   8   2   3  53   1   1]
- [  8   1   2   6   1  40  10]
- [  8  10  10  12  10   7  76]]
-Node Classification on random seed  9043 -> 0.62
-Confusion Matrix:
- [[ 77   1   5   6   7   4   6]
- [  7 114  10   4   6   5   1]
- [ 29  13 162  43  31  19  21]
- [  9   2  32 103   6   7   9]
- [  3   6   4   0  64   1   2]
- [  8   2   3   7   0  36   7]
- [ 20   4   8   4  10   8  64]]
-Node Classification on random seed  9044 -> 0.588
-Confusion Matrix:
- [[ 65   2   3  10   4   8  13]
- [  4 134   4   0   1   3   4]
- [ 30  16 116  46  23  16  67]
- [  5   8  11 105   3   3  14]
- [  1  12   7   1  59   1   1]
- [  8   2   0   2   5  44   1]
- [ 15   3   7  21  12  15  65]]
-Node Classification on random seed  9045 -> 0.625
-Confusion Matrix:
- [[ 67   2   6   5   4  16   9]
- [  0 140   2   4  11   2   4]
- [ 24  21 134  26  27  31  49]
- [ 12   1  13  98  11   7   9]
- [  2   3   4   0  60   1   1]
- [  8   4   1   0   0  35   3]
- [ 11   8   6   5  12  10  91]]
-Node Classification on random seed  9046 -> 0.614
-Confusion Matrix:
- [[ 76   3   2   1   4  15  12]
- [  2 136   5   3   2   1   6]
- [ 16  23 127  47  17  23  46]
- [ 12  11  17  94   3   7  17]
- [  1  10   8   1  52   0   3]
- [  3   3   2   2   1  47   9]
- [  5   1   6  10  10  16  82]]
-Node Classification on random seed  9047 -> 0.599
-Confusion Matrix:
- [[ 76   2   1  12   0   5  20]
- [  7 115   8   5  21   4   2]
- [ 24  16 159  24  30  17  32]
- [  9   2  22  98   3   8  16]
- [  3   5   5   3  49   0   3]
- [ 10   3   2   0   3  47   6]
- [ 15   6   5  12  13  17  55]]
-Node Classification on random seed  9048 -> 0.57
-Confusion Matrix:
- [[ 59   1   5   7   3   7  15]
- [ 13 130   3   1   9   6   2]
- [ 32  11 103  49  39  33  43]
- [  5   4  16  85   6   4  20]
- [  0  11   5   4  69   3   1]
- [ 17   0   3   0   0  39   5]
- [ 12   2   7   4   5  17  85]]
-Node Classification on random seed  9049 -> 0.642
-Confusion Matrix:
- [[ 54   3  12   5   6  11   8]
- [  7 127   8   4   8   4   7]
- [ 18  25 160  46  14   9  31]
- [ 15   3  13 101   3   6  12]
- [  3   8   1   1  69   0   2]
- [  4   0   7   1   2  45   3]
- [ 13   4   5   6   1  19  86]]
-Node Classification on random seed  9050 -> 0.632
-Confusion Matrix:
- [[ 80   2   7   7   3   2   7]
- [  4 115  10   8  15   1   3]
- [ 23  16 160  38  20  14  42]
- [ 12   2  11 107   9  10  15]
- [  0   8   3   1  55   3   1]
- [  7   1   1   2   2  42   3]
- [ 13   4   5  21   4   8  73]]
-Node Classification on random seed  9051 -> 0.603
-Confusion Matrix:
- [[ 57   1   1   4   5  10  12]
- [  3 130   2   4  11   3   8]
- [ 15  30 141  29  40  25  46]
- [ 26   6   6  92   2   2  12]
- [  0   8   3   0  67   0   4]
- [  5   1   2   3   0  40  12]
- [ 15   5   7  15   7   7  76]]
-Node Classification on random seed  9052 -> 0.589
-Confusion Matrix:
- [[ 66   1   3   7   3  17  13]
- [ 11 116   5   5   6   3   1]
- [ 31  23 132  30  31  22  38]
- [ 11   9   9 104   5   4  19]
- [  0  14   5   5  54   1   0]
- [  8   3   4   4   0  44   6]
- [  9   2   6   4  23  10  73]]
-Node Classification on random seed  9053 -> 0.573
-Confusion Matrix:
- [[ 76   1   5   2   2  18   8]
- [  6 116   9   6  11   4   1]
- [ 18  35 148  53  18  21  25]
- [ 17   4  11  86  20  34   6]
- [  1   3  10   0  54   0   2]
- [  3   3   3   1   0  41   4]
- [  8   5  14  10  12  13  52]]
-Node Classification on random seed  9054 -> 0.635
-Confusion Matrix:
- [[ 79   2   5   2   4  11   9]
- [  5 131   3   4   7   2   3]
- [ 28  13 141  24  26  23  50]
- [ 13   7  15 108   5  12   9]
- [  1   6   2   1  52   0   1]
- [  3   1   0   0   0  56   5]
- [ 11  13   3  10   3  23  68]]
-Node Classification on random seed  9055 -> 0.58
-Confusion Matrix:
- [[ 74   1   0   4   4   8  14]
- [  9 111   6   0  19   0   7]
- [ 51  22 128  32  31  27  40]
- [ 18   6   4 109   5   4  20]
- [  0   3   5   2  44   3   2]
- [ 16   1   1   0   2  36   6]
- [ 13   2   8   7   7  10  78]]
-Node Classification on random seed  9056 -> 0.631
-Confusion Matrix:
- [[ 44   4   6   4   3  25  14]
- [  5 124   7   3   9   5   3]
- [ 23  22 160  18  18  31  35]
- [  3   7  12  95   3   9  15]
- [  0  10   6   1  64   1   3]
- [  0   3   1   1   1  48  11]
- [  8   7   6   5   5  16  96]]
-Node Classification on random seed  9057 -> 0.608
-Confusion Matrix:
- [[ 74   6   6   8   2   6   8]
- [ 11 109   6   7   9   1   6]
- [ 30  14 142  26  35  28  35]
- [ 11   4  18  97  11   8  18]
- [  2   6   3   2  54   1   6]
- [  5   1   1   3   0  53   1]
- [ 10   2  13   8   4  10  79]]
-Node Classification on random seed  9058 -> 0.514
-Confusion Matrix:
- [[ 47   9  18   1   3  10  14]
- [  5 133   7   5   4   6   4]
- [ 15  26 102  49  37  36  55]
- [ 13   9  14  80   6   7  25]
- [  2   7   1   2  57   0   4]
- [  7   0   1   2   0  51   2]
- [  7   5  11   8  29  20  44]]
-Node Classification on random seed  9059 -> 0.595
-Confusion Matrix:
- [[ 69   0   3   6   7  24  10]
- [ 10 138   1   3   3   3   3]
- [ 27  19 126  60  29  22  27]
- [  6   3  14  91  15   5  15]
- [  1   6   3   2  55   0   3]
- [  8   1   6   1   2  41   3]
- [ 13   8   6   5   6  16  75]]
-Node Classification on random seed  9060 -> 0.625
-Confusion Matrix:
- [[ 72   2   5   3   3   7  11]
- [  9 110  14   3  13   5   6]
- [ 24  33 159  20  25  20  33]
- [ 10   5  20 111   3   7  10]
- [  0   8   3   4  66   0   2]
- [  5   1   2   0   0  44   1]
- [ 14   2  13   2  13  14  63]]
-Node Classification on random seed  9061 -> 0.637
-Confusion Matrix:
- [[ 57   1   6   4   7  11  14]
- [  4 134   4   2   4   3   6]
- [ 29  15 155  35  23  11  62]
- [ 10   2  18 103   7   6   4]
- [  3   5   4   0  53   0   5]
- [  2   1   3   4   0  53   5]
- [  4   4  10  11   3  11  82]]
-Node Classification on random seed  9062 -> 0.636
-Confusion Matrix:
- [[ 67  10   4   5   2  11   7]
- [  3 121   5   1   8   0  10]
- [ 24  20 168  22  26  19  24]
- [ 10   5  13 110  14  16   4]
- [  3   6   6   2  54   2   3]
- [  3   0   4   4   2  43   4]
- [  7   3   3  14   8  27  73]]
-Node Classification on random seed  9063 -> 0.647
-Confusion Matrix:
- [[ 77   7   2   1   6  11  10]
- [  5 154   2   2   1   5   5]
- [ 22  23 153  26  10  24  39]
- [ 20   4  15  90  15   5   5]
- [  3   8   6   0  61   3   0]
- [  6   2   3   2   0  37   4]
- [ 17   4   7   1   3  19  75]]
-Node Classification on random seed  9064 -> 0.641
-Confusion Matrix:
- [[ 71   2   5   2   1  11  10]
- [  0 137   3   0   3   2   7]
- [ 13  24 140  38  23  21  46]
- [ 10   9  18  93  10   5  24]
- [  0   7   2   2  65   2   2]
- [  2   4   4   0   0  55   5]
- [  7   4  10   1   4  16  80]]
-Node Classification on random seed  9065 -> 0.58
-Confusion Matrix:
- [[ 62   2   4  12   9   8  24]
- [  4 120   1   1  13   2   6]
- [ 17  21 117  42  35  23  50]
- [  7   4  26  89   4  14  17]
- [  1   3   1   1  62   0   8]
- [  3   1   3   0   1  43   6]
- [ 10   4   4  14   4  10  87]]
-Node Classification on random seed  9066 -> 0.633
-Confusion Matrix:
- [[ 75   1   1   8   2  14  11]
- [  3 128   5   2   6   3   7]
- [ 23  10 150  20  52  10  29]
- [  7   5  19  99   5  11  15]
- [  2   4   1   0  66   2   2]
- [  6   0   2   2   0  47   8]
- [ 27   9   5   6   8  14  68]]
-Node Classification on random seed  9067 -> 0.627
-Confusion Matrix:
- [[ 59   5   4   3   8  16   8]
- [  2 135   8   1  10   3   9]
- [ 20  27 177  22  22  20  21]
- [ 14  11  23  92   9   4  15]
- [  3   7   5   0  55   0   6]
- [  7   1   1   1   0  34   7]
- [ 16   3   8   5   5  13  75]]
-Node Classification on random seed  9068 -> 0.61
-Confusion Matrix:
- [[ 76   5   1   6   1  11   7]
- [  6 114   5   6  10   2  10]
- [ 20  23 137  30  45  11  47]
- [ 14   6  16 115   5   6  17]
- [  0   4   3   0  54   1   7]
- [  5   3   7   3   0  36   4]
- [ 10   5   6   7   5  10  78]]
-Node Classification on random seed  9069 -> 0.576
-Confusion Matrix:
- [[ 64   1   5   6   9   8  14]
- [  4 124   6   0  11   2   2]
- [ 26  19 134  44  30  34  36]
- [ 20   7  13  94  17  11   6]
- [  3   8   7   0  53   0   2]
- [  6   1   3   2   0  33   7]
- [  6   3  17  16   3   9  74]]
-Node Classification on random seed  9070 -> 0.63
-Confusion Matrix:
- [[ 81   6   9   7   4   6   8]
- [  6 123   3   2   8   1   5]
- [ 18  22 142  21  30  15  51]
- [  9   8  17 103   3  12  12]
- [  2   6   1   0  59   1   7]
- [  7   0   3   3   0  46   4]
- [  8   2  10   9   8  16  76]]
-Node Classification on random seed  9071 -> 0.615
-Confusion Matrix:
- [[ 59   4   4   5   4  15   9]
- [  7 144   2   2   4   5   5]
- [ 28  29 121  26  39  27  35]
- [ 29   3   9  89   6   3  16]
- [  2   7   2   0  73   0   1]
- [  3   0   2   0   1  50   9]
- [ 10   4   3   9  11   5  79]]
-Node Classification on random seed  9072 -> 0.62
-Confusion Matrix:
- [[ 82   0   2   7   2   6  11]
- [  3 122   6   3   2  11   9]
- [ 30  39 111  22  19  30  33]
- [ 21   6  17  99   5   7   9]
- [  1   7   5   1  76   0   1]
- [  7   4   1   2   0  42   8]
- [  9   4   4   8   7  11  88]]
-Node Classification on random seed  9073 -> 0.596
-Confusion Matrix:
- [[ 68   4   7  14   4  17  18]
- [  4 125   1   3   4   3   0]
- [ 14  17 137  35  28  26  42]
- [ 14   5  17  88  10   7   9]
- [  1  12   4   1  54   1   7]
- [  4   5   0   5   2  41   4]
- [ 11   2   6  16   6  14  83]]
-Node Classification on random seed  9074 -> 0.636
-Confusion Matrix:
- [[ 77   2   3   4   2   9   7]
- [  5 129  14   6   6   0   5]
- [ 23  17 146  34  11  23  55]
- [  6   1  24 106   2   9  15]
- [  1   4   5   4  58   1   6]
- [  4   3   1   2   0  45   6]
- [ 11   2   3   9   9  10  75]]
-Node Classification on random seed  9075 -> 0.622
-Confusion Matrix:
- [[ 58   6   4   4  11   7   9]
- [  2 135   2   1  16   2   6]
- [ 26  29 150  33  22  14  47]
- [  4   2  14 107   9   2   9]
- [  1   5   8   0  60   0   2]
- [  3   2   2   4   2  49   5]
- [ 12   1  19   4   5  22  63]]
-Node Classification on random seed  9076 -> 0.634
-Confusion Matrix:
- [[ 76   2   1   3   8  16   0]
- [  5 129   8   6  13   3   2]
- [ 22  19 154  44  21  23  18]
- [ 15   2   6 103  13   3  14]
- [  0   4   6   0  57   0   1]
- [  9   1   4   3   0  52   2]
- [ 17   2  13  13   9  15  63]]
-Node Classification on random seed  9077 -> 0.611
-Confusion Matrix:
- [[ 72   3   6   1  11  13   6]
- [ 10 130   1   1   8   2   3]
- [ 28  37 134  16  23  30  42]
- [ 11   9  16 102   1   8  16]
- [  2   9   2   2  58   4   0]
- [  6   1   3   1   1  40   4]
- [ 11   3   8   1  12  17  75]]
-Node Classification on random seed  9078 -> 0.551
-Confusion Matrix:
- [[ 76   2   6   3  10  12   6]
- [  6  90  20   3  18  11   3]
- [ 18   8 139  28  31  40  50]
- [ 14   1  21  78   2  12  27]
- [  2   7   5   3  57   2   1]
- [  9   2   0   4   2  39   3]
- [ 13   4   5  10   4  21  72]]
-Node Classification on random seed  9079 -> 0.634
-Confusion Matrix:
- [[ 72   3   9  12   4   3   9]
- [  7 139   2   3   6   3   3]
- [ 17  19 148  32  22  28  38]
- [  5   8  19  99   6   8  11]
- [  4   5   3   0  55   0   4]
- [  4   1   0   8   0  43   9]
- [ 18   4   5   6   4  14  78]]
-Node Classification on random seed  9080 -> 0.604
-Confusion Matrix:
- [[ 63   3   4   2   6  12  17]
- [  4 130   5  10   3   4   3]
- [ 17  19 141  48  24  30  38]
- [ 23   3   7  97   5   8  10]
- [  0  10   2   2  51   0   5]
- [  8   1   5   0   3  44   8]
- [ 11   8   8   5   3  12  78]]
-Node Classification on random seed  9081 -> 0.64
-Confusion Matrix:
- [[ 78   5   1   5   2  11   5]
- [  6 133   4   5   4   6   2]
- [ 19  19 151  37  20  31  31]
- [ 12   4  21  85   9   7  12]
- [  0  11   4   1  53   2   3]
- [  4   0   2   2   2  48   4]
- [  9   4   8   2   4  20  92]]
-Node Classification on random seed  9082 -> 0.582
-Confusion Matrix:
- [[ 66   6   7   4   8  14  12]
- [  2 108  19   4  13   1   5]
- [ 23  35 134  17  23  19  58]
- [ 13   4  24  92   8   8  13]
- [  0   5   4   2  56   3   2]
- [ 12   2   2   1   1  51   7]
- [  8   2   7   5   3  12  75]]
-Node Classification on random seed  9083 -> 0.61
-Confusion Matrix:
- [[ 70   4   2   3   2  12   6]
- [  2 115   7   5  12   8   1]
- [ 36  22 155  32  24  20  25]
- [ 23   2  30  98   2   3  10]
- [  1   5   3   2  57   1   3]
- [  8   2   1   1   4  47   1]
- [ 19   3   9   3   4  27  68]]
-Node Classification on random seed  9084 -> 0.615
-Confusion Matrix:
- [[ 87   2   6   3   3   9   7]
- [  7 142   2   8  10   2   0]
- [ 28  23 128  53  46  10  14]
- [ 22  10  14  84   6   1   9]
- [  1   5   3   5  56   0   2]
- [  8   1   1   3   2  48   9]
- [ 12   4  14   9   5   6  70]]
-Node Classification on random seed  9085 -> 0.61
-Confusion Matrix:
- [[ 77   4   1   9  10   5  12]
- [ 11 117  11   1  11   3   5]
- [ 32  28 146  37  18  21  29]
- [  4   1  19 106   5   4  13]
- [  6   5   6   5  63   3   1]
- [  8   0   0   6   1  37   4]
- [ 22   3   4   2  12   8  64]]
-Node Classification on random seed  9086 -> 0.62
-Confusion Matrix:
- [[ 83   1   3   2   6   4  12]
- [  2 129   4   5   4   5   2]
- [ 21  22 136  54  30  15  51]
- [ 12   7  13  98  10   7   8]
- [  0  12   6   2  57   0   1]
- [  4   1   1   2   1  44   3]
- [  9   5   5   6  10  12  73]]
-Node Classification on random seed  9087 -> 0.624
-Confusion Matrix:
- [[ 66   7   5   5   3  15  11]
- [  9 132   6   2   4   1   8]
- [ 41  17 172  22  21  13  50]
- [ 13   5  16  93   5   4  22]
- [  2   2   3   0  48   1   3]
- [  2   2   0   1   0  47   5]
- [ 12   3   5   4  11  15  66]]
-Node Classification on random seed  9088 -> 0.563
-Confusion Matrix:
- [[ 65   6  10   4   5   5  15]
- [  5 136   5   1   5   3   2]
- [ 36  28 105  38  37  20  55]
- [ 20   2  12  89   7   6  18]
- [  2   9   5   3  61   2   3]
- [  8   1   1   1   0  49   2]
- [ 14   4  16   3  11   7  58]]
-Node Classification on random seed  9089 -> 0.618
-Confusion Matrix:
- [[ 72   0   8  16   2   9   4]
- [  2 140  17   1   5   2   0]
- [ 29  27 128  41  22  15  29]
- [  6  13  22 102   2   4   7]
- [  1   3   7   2  62   1   1]
- [  4   4   8   3   0  47   1]
- [ 21   8  11   4   6  14  67]]
-Node Classification on random seed  9090 -> 0.63
-Confusion Matrix:
- [[ 70   3   2  11   2  11   3]
- [  5 119   3   4   8   4   2]
- [ 11  33 147  46  20  27  35]
- [  8   2   5 119   7   9  10]
- [  2   4   3   8  65   1   3]
- [  9   0   3   2   0  48   2]
- [ 24   5   7   7   2  17  62]]
-Node Classification on random seed  9091 -> 0.604
-Confusion Matrix:
- [[ 74   2   7   5   2  18   7]
- [  5 127  14   1   2   0   2]
- [ 18  24 132  41  20  37  38]
- [ 21   4   6  97   4   8  17]
- [  0   9   5   1  45   0   3]
- [  5   1   0   0   1  45   4]
- [  7   8  21  10   5  13  84]]
-Node Classification on random seed  9092 -> 0.609
-Confusion Matrix:
- [[ 65   2  10   4   8  11   9]
- [  5 121   4  11  15   2   2]
- [ 30   9 137  20  42  21  35]
- [ 12   6  16 100  12  10   4]
- [  0   6   3   3  59   0   1]
- [  7   2   1   0   1  60   4]
- [ 11   3   8   9   9  23  67]]
-Node Classification on random seed  9093 -> 0.587
-Confusion Matrix:
- [[ 71   5   2   7   6   8  14]
- [  6 115   5   6  15   3   4]
- [ 22  20 111  38  33  23  50]
- [  8   4  16 104  11   8  11]
- [  3   2   2   1  61   0   2]
- [ 12   2   5   0   0  49   1]
- [ 14   5  15   5   9  10  76]]
-Node Classification on random seed  9094 -> 0.575
-Confusion Matrix:
- [[ 58   2   5   5   5  14  13]
- [  2 124  10   1   5   1   3]
- [ 18  33 129  30  37  11  60]
- [  9   1  21  86   8   3  14]
- [  1   6   5   2  71   0   5]
- [  5   0   4   3   0  41  11]
- [ 17   2  10   3  33   7  66]]
-Node Classification on random seed  9095 -> 0.602
-Confusion Matrix:
- [[ 67   5   4   3   9  13  10]
- [  2 139   7   1  10   0   5]
- [ 25  19 136  40  40  21  33]
- [  8   3  24  88   6   6   9]
- [  0   7   6   4  56   2   2]
- [  3   2   0   0   0  43   9]
- [  7   5  11  15   7  15  73]]
-Node Classification on random seed  9096 -> 0.618
-Confusion Matrix:
- [[ 78   2   2   3   3   4   6]
- [  5 139   0   2   9   3   5]
- [ 19  28 123  65  39  10  25]
- [ 13  11  14  93   0  12  18]
- [  1   4   7   0  62   0   1]
- [  8   2   1   2   0  47   2]
- [ 13   3   8   4  12  16  76]]
-Node Classification on random seed  9097 -> 0.608
-Confusion Matrix:
- [[ 54   7   8   4   6  19   8]
- [  3 135   8   4   8   1   1]
- [ 32  23 131  42  25  14  53]
- [  5   5  15 100   4   8  16]
- [  2   6   6   1  53   2   1]
- [  5   2   5   2   0  48   3]
- [  5   3   7   7   4  12  87]]
-Node Classification on random seed  9098 -> 0.598
-Confusion Matrix:
- [[ 60   1   4  10   2  14  16]
- [ 12 114   2   2   7   4   2]
- [ 25  24 131  13  44  20  51]
- [  9   5  11 111   9   7  12]
- [  2   7   4   0  66   0   3]
- [  4   0   0   1   3  40   8]
- [ 13   7   2  11  14  17  76]]
-Node Classification on random seed  9099 -> 0.65
-Confusion Matrix:
- [[ 77   2   1   6   4   2   4]
- [  4 133   1   0   4   3   6]
- [ 23  33 160  20  41  17  33]
- [ 16   5  18 106   4   8  10]
- [  2   6   3   0  62   4   0]
- [  6   2   3   3   1  35   7]
- [ 19   3   5   2   9  10  77]]
-Node Classification on random seed  9100 -> 0.628
-Confusion Matrix:
- [[ 63   2   3   5   5  11  12]
- [ 19 139   0   1  11   3   1]
- [ 18  23 129  51  30  33  34]
- [  9   1   7 104   7   6  16]
- [  2   6   0   1  52   0   2]
- [  2   3   1   1   1  53   5]
- [  3   5   9   2   6  15  88]]
-Node Classification on random seed  9101 -> 0.625
-Confusion Matrix:
- [[ 66   4   5   6   8   6  14]
- [  5 132   4   1   3   7  11]
- [ 34  22 143  28  17  22  29]
- [ 14  10  10 109   6   3  14]
- [  1   5   8   3  57   1   2]
- [ 10   2   2   2   1  47   9]
- [ 11   7   6  11   1  10  71]]
-Node Classification on random seed  9102 -> 0.633
-Confusion Matrix:
- [[ 72   2   2   2   3  17  12]
- [  8 124   4   0   6   7  15]
- [ 19  17 142  26  25  27  40]
- [ 11   4   9 100   6   9  16]
- [  2   6   2   2  66   0   3]
- [  1   3   4   0   1  56   2]
- [  9   3   5  10  10  17  73]]
-Node Classification on random seed  9103 -> 0.582
-Confusion Matrix:
- [[ 83   1   8  14   7   3   8]
- [  5 114   9   3  12   4   6]
- [ 36  22 139  37  36  34  28]
- [  6   5  11  86   8  15  11]
- [  1   8  12   2  48   2   2]
- [  9   1   7   2   0  40   3]
- [ 12   1   4   9   9   5  72]]
-Node Classification on random seed  9104 -> 0.634
-Confusion Matrix:
- [[ 72   2   5   6   1  14  13]
- [  6 142   4   2   6   3   1]
- [ 10  38 132  42  29  12  44]
- [  3   3  28  90   0   6   7]
- [  0   6   2   3  73   0   2]
- [  6   3   0   1   1  45   3]
- [  9   6   9  12   9   9  80]]
-Node Classification on random seed  9105 -> 0.583
-Confusion Matrix:
- [[ 63   2   9   4   5   9  16]
- [  2 120   4   2  11   1   3]
- [ 17  23 154  19  29  23  56]
- [ 19   5  18  89   2   4  27]
- [  1   4   8   2  44   5   4]
- [  8   0   4   6   0  42   2]
- [ 15   3  11   7   7  20  71]]
-Node Classification on random seed  9106 -> 0.611
-Confusion Matrix:
- [[ 70   3   4   6   2  12   7]
- [  4 116   5   1   8   0   3]
- [ 26  21 147  48  20  42  31]
- [  6   3  27  86   6  12  16]
- [  1   4   3   0  53   4   3]
- [  9   1   1   0   1  54   0]
- [ 11   3   6   7   9  13  85]]
-Node Classification on random seed  9107 -> 0.63
-Confusion Matrix:
- [[ 80   1   3   6   6  12  10]
- [  3 111   8   4  21   5   5]
- [ 28   8 182  26  14  12  39]
- [ 13   1  23  94  10   8  16]
- [  5   2   4   3  53   3   3]
- [  7   2   2   1   4  44   3]
- [ 11   4   9   9   5  11  66]]
-Node Classification on random seed  9108 -> 0.576
-Confusion Matrix:
- [[ 48   5  15   5   2   6   9]
- [  5 128   4   0  10   1   4]
- [ 30  27 118  37  45  24  34]
- [ 19   8   9 104   5   5  22]
- [  0  10   4   0  62   2   0]
- [ 11   0   1   1   1  37   7]
- [ 19   3  20   1   8   5  79]]
-Node Classification on random seed  9109 -> 0.627
-Confusion Matrix:
- [[ 63   1  10   2   2   8   9]
- [  6 138   2   5   7   3   3]
- [ 30  16 153  41  39  20  25]
- [ 10   6  11 101   9   6  16]
- [  1   4   3   2  60   0   3]
- [  3   1   5   1   3  43   2]
- [  6   3   9   6   8  26  69]]
-Node Classification on random seed  9110 -> 0.638
-Confusion Matrix:
- [[ 72   3   3   1   0   7  14]
- [  4 121  12   1   6   1   6]
- [ 19  49 142  27  29  26  22]
- [ 11   4  10 116   3   7   9]
- [  3  10   2   3  61   0   2]
- [  5   1   1   2   1  48   4]
- [ 10   7  11   9   1  16  78]]
-Node Classification on random seed  9111 -> 0.595
-Confusion Matrix:
- [[ 78   1   5   6   2   7  11]
- [  5 134   7   1  12   4   4]
- [ 34  33 136  22  20  24  48]
- [  9   1   8  76  12   4  27]
- [  3   8   2   1  51   0   9]
- [  8   1   1   5   1  31  14]
- [ 21   3   5   1   4  11  89]]
-Node Classification on random seed  9112 -> 0.586
-Confusion Matrix:
- [[ 71   2   6   2   7  16  19]
- [  3 131   1   2   6   1   2]
- [ 15  30 117  48  36  11  50]
- [ 24   4  31  81   3   7   9]
- [  1   9   1   1  62   3   3]
- [  4   3   4   0   1  49   3]
- [ 16   8   7   1   7   7  75]]
-Node Classification on random seed  9113 -> 0.662
-Confusion Matrix:
- [[ 61   0   1   9  10   6   4]
- [ 11 131   6   4  11   1   0]
- [ 37  15 165  22  21   9  30]
- [ 14   3  11 125   6   4  12]
- [  2   4   3   3  67   1   7]
- [  9   2   3   0   0  36   7]
- [ 15   2  11   7   4  11  77]]
-Node Classification on random seed  9114 -> 0.608
-Confusion Matrix:
- [[ 64   1   3   8   3  12   6]
- [  5 129   5   0  21   1   1]
- [ 17  24 136  37  23  28  34]
- [  8   2  34  81   4  10  15]
- [  2   3   6   2  59   1   1]
- [  2   2   2   2   0  57   8]
- [ 13   1  10   3  13  19  82]]
-Node Classification on random seed  9115 -> 0.623
-Confusion Matrix:
- [[ 85   2   7   6   6   7  13]
- [  2 113   8  14  12   0   3]
- [ 23  12 153  50  28  16  26]
- [ 24   0  17  93  11   3   8]
- [  2   2   6   5  61   2   1]
- [  5   0   3   0   1  51   2]
- [ 13   0  13   7  10   7  67]]
-Node Classification on random seed  9116 -> 0.612
-Confusion Matrix:
- [[ 86   1   1   9   3  10   7]
- [ 12 116   2   5   4   2   5]
- [ 14  37 142  29  31  24  36]
- [  9  10  13  94   4   9  16]
- [  2   6   1   3  76   0   2]
- [  8   7   1   4   1  33   5]
- [ 16   1   6   6   9  17  65]]
-Node Classification on random seed  9117 -> 0.651
-Confusion Matrix:
- [[ 74   2   2   1   3  12  12]
- [  1 140   3   5   8   5   2]
- [ 12  21 173  30  22  30  35]
- [ 10   7  17  86   7   7  18]
- [  0   9   5   1  54   0   2]
- [  6   2   2   0   3  40   3]
- [  6   6   4   8   7  13  84]]
-Node Classification on random seed  9118 -> 0.625
-Confusion Matrix:
- [[ 76   3   2   2  14  13   6]
- [  0 135   6   1   9   2   2]
- [ 45  19 138  30  28  35  21]
- [ 21   2   8 115   5   5   6]
- [  0   5   7   0  62   1   0]
- [ 14   1   1   0   3  34   5]
- [ 16   4  10   3   6  14  65]]
-Node Classification on random seed  9119 -> 0.606
-Confusion Matrix:
- [[ 66   0  10   7   3   6   7]
- [  3 124   2   1   3   4   2]
- [ 20  23 150  43  18  26  40]
- [ 13   3  19 106  10   3  21]
- [  4   6   3   3  48   1   3]
- [  7   1   2   3   1  41   9]
- [ 17   3   7   7  12  18  71]]
-Node Classification on random seed  9120 -> 0.611
-Confusion Matrix:
- [[ 70   3   4   3   5  10  12]
- [  4 141   3   2   9   1   3]
- [ 18  40 115  37  21  18  51]
- [ 10   7  15 105   5  10   6]
- [  3   6   3   0  62   0   4]
- [  5   2   6   1   1  43   6]
- [ 14   5   7   8   4  17  75]]
-Node Classification on random seed  9121 -> 0.58
-Confusion Matrix:
- [[ 54   3   6   8   3  14  15]
- [ 12 119   1   5  14  10   1]
- [ 19  21 123  51  22  32  37]
- [  3   0  24 114   3   4  10]
- [  3   3   1   4  49   0   3]
- [  2   2   8   0   0  37   4]
- [ 10   6  13   5  20  18  84]]
-Node Classification on random seed  9122 -> 0.631
-Confusion Matrix:
- [[ 61   3   4   4   3   5  22]
- [  4 129   4   1   5   4   9]
- [ 26  16 177  25  24  19  34]
- [ 18   5  17  99   4   5  16]
- [  1   5   7   3  57   1   1]
- [ 13   2   4   0   1  44   2]
- [ 22   3   6   5   9   7  64]]
-Node Classification on random seed  9123 -> 0.607
-Confusion Matrix:
- [[ 70   2   2   0   0  18   8]
- [  3 135   1   4   6   1   3]
- [ 23  27 135  47   9  27  32]
- [ 22   9  10  98   1  13  16]
- [  2   9   4   5  57   4   2]
- [  8   1   1   1   1  33  11]
- [ 15   4  14   5   0  22  79]]
-Node Classification on random seed  9124 -> 0.638
-Confusion Matrix:
- [[ 71   1   6   1   6  12  11]
- [  4 135   5   1   3   3   7]
- [ 20  26 160  22  23  23  55]
- [ 12   2  18  84   3   6  11]
- [  1   8   1   2  60   1   2]
- [  4   1   2   1   1  38  14]
- [ 15   3   6   3   4  12  90]]
-Node Classification on random seed  9125 -> 0.603
-Confusion Matrix:
- [[ 53   2  13  10   4  10   8]
- [  6 124   7   1   8   3   5]
- [ 47  19 141  27  21  17  45]
- [ 13   5  16 102   2   7  10]
- [  0   7   7   2  58   0   0]
- [  5   3   0   2   2  47   2]
- [ 13   5  10   7   8  18  78]]
-Node Classification on random seed  9126 -> 0.614
-Confusion Matrix:
- [[ 65   2   2   7   6   8  12]
- [  6 116   9   2  11   1   5]
- [ 31  15 164  28  23  19  49]
- [  6   3  36 113   6   8  10]
- [  1   5   2   2  49   1   3]
- [  6   2   1   3   1  33   2]
- [ 19   2   4   4   5  18  74]]
-Node Classification on random seed  9127 -> 0.59
-Confusion Matrix:
- [[ 59   4   6  14  10   9   3]
- [  4 133   3   1   3   0   3]
- [ 30  42 121  25  36  15  46]
- [  5   7  13 108  12   8  15]
- [  1  11   3   1  44   1   1]
- [  6   3   5   2   3  53   1]
- [ 12   3  14   9   9  11  72]]
-Node Classification on random seed  9128 -> 0.64
-Confusion Matrix:
- [[ 72   0   3   1   4   6  12]
- [  7 116   2   5  10   7  13]
- [ 22  12 150  39  26  19  41]
- [ 11   0  12 108   2   8  15]
- [  0   2   6   2  53   1   8]
- [  3   1   0   0   2  50   6]
- [ 14   2   7  16   6   7  91]]
-Node Classification on random seed  9129 -> 0.617
-Confusion Matrix:
- [[ 63   1   5   4   1   9  14]
- [  3 118   8   5  26   2   4]
- [ 13  24 128  35  32  10  52]
- [  8   6  20 111  12   0   9]
- [  1  12   5   0  57   2   3]
- [  5   2   2   1   0  45   8]
- [  7   3  10   4   6   9  95]]
-Node Classification on random seed  9130 -> 0.584
-Confusion Matrix:
- [[ 72   2   2   4   5  15   8]
- [  3 109   9   1   8   6   5]
- [ 33  22 136  35  29  28  27]
- [ 15   4  16  96  14   6   7]
- [  0  15   2   1  55   3   2]
- [ 16   1   3   1   1  35   4]
- [ 11   2   9  14   6  21  81]]
-Node Classification on random seed  9131 -> 0.62
-Confusion Matrix:
- [[ 79   3   9   4   3   8   9]
- [  4 133   2   4  10   3  11]
- [ 29  19 151  26  30  40  28]
- [ 12   9  17  91   2   5  15]
- [  2   4   2   1  47   3   1]
- [  7   1   4   0   0  44   5]
- [ 11   3   5   6   7  16  75]]
-Node Classification on random seed  9132 -> 0.578
-Confusion Matrix:
- [[ 55   0   4   3   9  16  16]
- [  7 137   2   3   5   4   3]
- [ 36  36 117  59  19  18  27]
- [ 14  10  22  90   5   2  15]
- [  3   6   1   1  63   1   2]
- [  7   1  10   1   0  32   7]
- [  5   6  10  10   7   9  84]]
-Node Classification on random seed  9133 -> 0.625
-Confusion Matrix:
- [[ 75   6   6   3   2  13   1]
- [  9 121   2   3   8   2   4]
- [ 21  19 140  46  32  22  29]
- [  6   4  15 119   3   1  11]
- [  0  13   4   2  57   0   3]
- [ 12   1   3   0   1  39   3]
- [ 20  12   9   6   5  13  74]]
-Node Classification on random seed  9134 -> 0.625
-Confusion Matrix:
- [[ 81   3   4   3   4  11  11]
- [  3 124   4   3   9   2   2]
- [ 24  28 151  38  22  28  29]
- [  6   4  12  94  10   6  13]
- [  0  12   5   1  58   1   3]
- [  6   2   1   3   0  54   4]
- [ 12   6   3  19   6  12  63]]
-Node Classification on random seed  9135 -> 0.651
-Confusion Matrix:
- [[ 85   4   2   4   1  25   5]
- [  3 126   5   2   2   1   3]
- [ 18  34 145  23  31  23  28]
- [ 11   5   9 107   8   9  13]
- [  4   7   3   1  56   1   1]
- [  2   3   4   2   0  47   8]
- [  6   3  11   3   6  15  85]]
-Node Classification on random seed  9136 -> 0.639
-Confusion Matrix:
- [[ 68   3   6   0   8   8  19]
- [  3 133   0   5   2   3   4]
- [ 22  11 155  16  39  17  36]
- [  5  13  22 104   5   4  13]
- [  3   8   5   3  51   0   0]
- [  8   2   5   0   2  48  12]
- [  8   3   7   5   7  19  80]]
-Node Classification on random seed  9137 -> 0.621
-Confusion Matrix:
- [[ 53   3   9   4  10  15   7]
- [  8 127   4   1   5   2   3]
- [ 23  16 170  36  28  30  37]
- [  7   8  16 104   7   7   8]
- [  1   5   0   2  61   0   3]
- [  6   1   8   1   1  30   7]
- [ 16   2   9   3   6  14  76]]
-Node Classification on random seed  9138 -> 0.609
-Confusion Matrix:
- [[ 87   2   8  11   3  11  10]
- [  1 125  13   6   5   1   3]
- [ 20  25 134  23  35  10  39]
- [ 20   6  23  79   9   5  18]
- [  0   7   4   2  63   0   2]
- [  5   1   1   1   0  45   3]
- [ 13   5  11  10  10   9  76]]
-Node Classification on random seed  9139 -> 0.599
-Confusion Matrix:
- [[ 65   2   2   7   3  21   5]
- [  9 121  12  12   5   1   6]
- [ 26   9 130  61  33  22  24]
- [ 12   0  14 102   5   8  11]
- [  3   8   5   1  67   0   4]
- [  2   0   3   0   1  46   5]
- [ 11   1  15  13   3  16  68]]
-Node Classification on random seed  9140 -> 0.61
-Confusion Matrix:
- [[ 57   3   8   8   3   4  15]
- [  8 122   5   6   8   0   7]
- [ 23  15 140  44  30  18  43]
- [  8   2  17 111   3  14  13]
- [  2  10   2   3  57   1   1]
- [  7   0   2   0   1  40   3]
- [ 20   6   4   6  11   6  83]]
-Node Classification on random seed  9141 -> 0.647
-Confusion Matrix:
- [[ 70   4   9   4   4   7   8]
- [  1 113   6   2  15   2   4]
- [ 23  16 167  31  29  24  16]
- [ 16   8  11 106   5   5   3]
- [  1   7   0   2  62   1   1]
- [  9   3   1   3   1  54   4]
- [ 15   3  13  12   5  19  75]]
-Node Classification on random seed  9142 -> 0.618
-Confusion Matrix:
- [[ 61   2   5   1   7  17   7]
- [  4 123   4   5  13   5   1]
- [ 21  21 155  29  33  30  29]
- [  7   9  15 107   6   7  19]
- [  1   4   3   1  58   0   1]
- [  6   1   1   0   4  46   1]
- [  9  11   4   5  12  21  68]]
-Node Classification on random seed  9143 -> 0.636
-Confusion Matrix:
- [[ 62   0   4   7   5  13  18]
- [  2 135   1   5   3   6   5]
- [ 13  25 147  28  26  22  49]
- [  7   3   8 110   7   6  13]
- [  0   8   3   1  59   2   0]
- [  2   1   1   2   2  43   6]
- [  9   4  14   4   8  21  80]]
-Node Classification on random seed  9144 -> 0.626
-Confusion Matrix:
- [[ 72   1   4   9   2   7   6]
- [  4 148   4   2   8   1   5]
- [ 17  20 134  55  20  17  50]
- [  8   3  13  96   9  11   8]
- [  5  10   4   1  52   3   1]
- [  8   1   0   1   1  52   4]
- [ 14   5   6  11   6   9  72]]
-Node Classification on random seed  9145 -> 0.594
-Confusion Matrix:
- [[ 76   3   9   2   3   5   6]
- [  5 139   4   4   3   2   8]
- [ 30  17 131  38  30  17  54]
- [ 18   6  12  85  10  11  11]
- [  1   6   2   2  55   2   6]
- [  9   0   1   2   1  40   5]
- [ 27   2   8   5   2  17  68]]
-Node Classification on random seed  9146 -> 0.614
-Confusion Matrix:
- [[ 59  10   2   3   4  10   8]
- [  5 126   5   5  13   2   1]
- [ 21  20 159  47  21  24  24]
- [ 10   3  26 105   6   8  12]
- [  1   2   5   1  62   0   3]
- [  5   0   4   1   2  47   5]
- [ 11   7  11   6  11  21  56]]
-Node Classification on random seed  9147 -> 0.593
-Confusion Matrix:
- [[ 64   0   8   6   4  21   5]
- [  5 123   3   1   7   2   2]
- [ 24  44 123  42  27  26  22]
- [ 17   5  12 107   1  12   5]
- [  1  10   4   2  62   2   1]
- [  7   4   3   1   5  38   3]
- [  7   3   8  20  11  14  76]]
-Node Classification on random seed  9148 -> 0.649
-Confusion Matrix:
- [[ 73   6  12   1   2  10   6]
- [  1 135   7   1   7   0   6]
- [ 18  24 138  34  32  10  52]
- [ 13   6  10 102   6   2  13]
- [  0   6   4   0  68   0   2]
- [  1   2   1   2   0  56   6]
- [ 10   6   3  12   5  12  77]]
-Node Classification on random seed  9149 -> 0.639
-Confusion Matrix:
- [[ 78   2   3   6   3  10   7]
- [  5 124   2   2   5   2   4]
- [ 27  23 163  40  21  17  37]
- [ 17   7  10  88   4   8  10]
- [  0   3   3   1  68   1   2]
- [  9   3   2   5   0  41   8]
- [ 17   4  15   5   2   9  77]]
-Node Classification on random seed  9150 -> 0.606
-Confusion Matrix:
- [[ 59   3   2   7   6  13  18]
- [  4 131   5   2   5   3   6]
- [ 13  27 140  41  30  31  43]
- [  3   4   8  99   8  10  12]
- [  0  14   2   0  58   2   4]
- [  3   1   7   1   1  41   6]
- [  4   4   7  10   8  16  78]]
-Node Classification on random seed  9151 -> 0.613
-Confusion Matrix:
- [[ 70   5   0   4  12  12  12]
- [  4 128   4   1  15   2   3]
- [ 31  18 131  29  27  17  30]
- [ 12   4  12 112   7   3  15]
- [  2   5   3   2  63   1   2]
- [  3   2   6   0   3  50   7]
- [ 10   3  11   8  24  16  59]]
-Node Classification on random seed  9152 -> 0.624
-Confusion Matrix:
- [[ 76   2   2   2   3  16   9]
- [  5 135   5   4   1   1   3]
- [ 24  24 123  42  25  27  31]
- [ 13   0  20 101   9   5  12]
- [  2   9   2   0  56   1   3]
- [  4   3   2   2   1  58   2]
- [ 16   5  15   7   2  15  75]]
-Node Classification on random seed  9153 -> 0.652
-Confusion Matrix:
- [[ 84   1   3   4   0   5  10]
- [  6 133   8   1   7   0   4]
- [ 32  15 145  21  36  13  33]
- [  8   7  18  99   8   7  13]
- [  2   7   2   0  60   0   2]
- [  3   0   2   5   1  50   5]
- [ 16   5   7  13   7  11  81]]
-Node Classification on random seed  9154 -> 0.619
-Confusion Matrix:
- [[ 62   3   7  12   5  14   8]
- [  2 128   7   1  12   1   1]
- [ 21  17 149  43  24  14  40]
- [ 11   1  24 109   6   6   6]
- [  2   7   5   3  50   6   4]
- [  1   1   3   1   1  51   5]
- [  6   4  13  11   9  13  70]]
-Node Classification on random seed  9155 -> 0.612
-Confusion Matrix:
- [[ 76   3   5   3   2  13   5]
- [  4 127   6   5   5   0   5]
- [ 34  17 130  24  39  36  31]
- [ 18   6  18 108   4   5   6]
- [  1   7   6   1  58   0   3]
- [  4   0   1   3   2  49   1]
- [ 23   5   7   6   7  17  64]]
-Node Classification on random seed  9156 -> 0.608
-Confusion Matrix:
- [[ 42   1   8   8   4  24   8]
- [  4 152   6   1   8   1   3]
- [ 10  25 144  40  20  19  48]
- [  9   5  19 106   7   9  19]
- [  0   2   6   0  55   1   1]
- [  1   2   1   1   1  47   7]
- [  9   6   7   4   5  32  62]]
-Node Classification on random seed  9157 -> 0.601
-Confusion Matrix:
- [[ 54   2   8  12   5  13  20]
- [  6 123   8   7   8   2   5]
- [ 28  15 147  31  18  17  37]
- [ 18   2  22 103   2   4  13]
- [  7   5   1   2  61   0   4]
- [ 10   2   1   4   1  40  11]
- [  5   4  11   3   8  17  73]]
-Node Classification on random seed  9158 -> 0.601
-Confusion Matrix:
- [[ 66   4   8   5   3  13  10]
- [  6 115   5   7  11   3   0]
- [ 25  24 156  34  26  10  38]
- [  1   4  39  86   9   5  15]
- [  1   7   4   1  55   1   2]
- [  8   2   1   0   1  55   2]
- [ 12   5  10  10  13  14  68]]
-Node Classification on random seed  9159 -> 0.632
-Confusion Matrix:
- [[ 63   1  13   5   5   8  11]
- [ 10 125   7   1  10   5   1]
- [ 15  24 154  24  26  19  52]
- [  9   2  18  98   3   6  17]
- [  3   3   4   3  61   0   1]
- [  0   2   2   0   1  49   5]
- [ 10   4   7   2   8  21  82]]
-Node Classification on random seed  9160 -> 0.637
-Confusion Matrix:
- [[ 79   3   4   4   3   4   9]
- [  1 142   6   3   4   1   4]
- [ 17  34 122  33  35  17  33]
- [ 14   5  17 101   5  13   9]
- [  0  10   4   1  56   1   2]
- [  4   3   1   3   1  43   7]
- [  7   5  13   8   8   7  94]]
-Node Classification on random seed  9161 -> 0.61
-Confusion Matrix:
- [[ 79   4   8   1   6  10   7]
- [  4 121   8   1   7   2  13]
- [ 25  21 132  49  24  34  35]
- [  2   7  12 110   3   4   7]
- [  1   9   1   1  50   1   3]
- [  6   3   3   5   2  42   3]
- [ 18   2  14   6   4  14  76]]
-Node Classification on random seed  9162 -> 0.645
-Confusion Matrix:
- [[ 67   0   8   8   6  11  10]
- [  2 153   6   1  10   2   2]
- [ 17   9 169  29  24  23  30]
- [ 13   5  25  91   7   3  16]
- [  1   7   5   1  49   1   1]
- [ 10   1   2   2   2  43   2]
- [ 12   6   7  11   3  14  73]]
-Node Classification on random seed  9163 -> 0.639
-Confusion Matrix:
- [[ 89   1   0   5   4  10   0]
- [  4 128   4   3  11   5   5]
- [ 28  23 131  42  29  28  32]
- [  8   2   6 113   4   2  10]
- [  2   5   6   1  70   0   2]
- [  7   4   2   5   0  45   1]
- [ 21   3   1  11  10  14  63]]
-Node Classification on random seed  9164 -> 0.591
-Confusion Matrix:
- [[ 60   0   8   8   4   8  15]
- [  0 131   1   3   8   2   4]
- [ 16   7 130  53  33  25  43]
- [ 13   1  19  95  12   6  16]
- [  0   5   8   1  63   2   5]
- [  4   2   3   6   2  47   0]
- [  8   7  15   9   2  25  65]]
-Node Classification on random seed  9165 -> 0.635
-Confusion Matrix:
- [[ 78   1   6   7   7   4   5]
- [  6 142   1   1   0   3   9]
- [ 17  22 133  46  34  14  32]
- [ 12   5  14 122   8   4   8]
- [  2   8   2   1  56   0   5]
- [ 11   0   6   2   1  35   8]
- [ 23   2   7   5   7   9  69]]
-Node Classification on random seed  9166 -> 0.626
-Confusion Matrix:
- [[ 67   1   8  13   3  12   4]
- [  8 122  11   2   8   2   4]
- [ 27  13 141  32  16  15  47]
- [ 11   5  12 116   6   7   9]
- [  1   4   7   2  59   3   4]
- [  7   2   2   3   0  39   7]
- [ 16   4  10  12   4  10  82]]
-Node Classification on random seed  9167 -> 0.65
-Confusion Matrix:
- [[ 90   4   4   3   4  11   5]
- [  8 129   5   5   5   2   1]
- [ 26  38 140  28  11  21  34]
- [ 10   7  11 110   7   2  19]
- [  1  10   3   0  63   3   3]
- [  4   3   1   2   2  42   2]
- [ 12   5   4   4   3  17  76]]
-Node Classification on random seed  9168 -> 0.619
-Confusion Matrix:
- [[ 83   1   6   3   8  20   7]
- [ 13 127   6   0   4   2   7]
- [ 20  27 143  26  14  20  43]
- [  8   5  13  91   6   8  20]
- [  1  12   6   2  57   0   3]
- [  5   0   3   3   1  42   8]
- [ 10   2   9   5   4  20  76]]
-Node Classification on random seed  9169 -> 0.643
-Confusion Matrix:
- [[ 73   7   5   7   2   8  12]
- [  6 121   5   0   2   6   4]
- [ 22  33 148  22  31  23  33]
- [  8   7  10 115   3   2  19]
- [  0   7   2   1  64   1   2]
- [  5   1   1   3   0  38   8]
- [ 15   4   6   8   7   9  84]]
-Node Classification on random seed  9170 -> 0.597
-Confusion Matrix:
- [[ 73   1   2   8   3  14  18]
- [  4 117   5   2  10   4   2]
- [ 12  18 163  60  16  28  17]
- [ 14   1  19  87   2  31  16]
- [  0  11   3   0  56   0   2]
- [ 12   0   2   0   2  38   4]
- [  6   4  15   6   4  25  63]]
-Node Classification on random seed  9171 -> 0.613
-Confusion Matrix:
- [[ 66   2   4   7   6  17  17]
- [  9 126   5   5   8   2  13]
- [ 17  12 163  30  30  28  26]
- [  5   0  12  99   4  14   7]
- [  0   9   9   1  49   1   9]
- [ 13   0   4   0   0  44   4]
- [ 12   0   6  10   6  23  66]]
-Node Classification on random seed  9172 -> 0.608
-Confusion Matrix:
- [[ 83   2   2   3   3  21   4]
- [  4 130   5   4   5   2   4]
- [ 21  24 121  68  27  21  32]
- [ 12   6  20  96   9   9   3]
- [  0   5   4   0  62   0   2]
- [  8   1   2   0   1  49   4]
- [ 16   2   7  12   5  12  67]]
-Node Classification on random seed  9173 -> 0.623
-Confusion Matrix:
- [[ 76   1   2   3   3  14   1]
- [  3 132   2   0   4   7   5]
- [ 26  30 145  22  47  17  30]
- [  7   4  20  94   8   8  21]
- [  0   7   8   2  58   1   1]
- [  3   2   3   2   2  43   9]
- [ 15   4   7   7   5  14  75]]
-Node Classification on random seed  9174 -> 0.608
-Confusion Matrix:
- [[ 62   0   2   3   2  12  27]
- [  3 127   8   2   3   4   1]
- [ 26  20 132  46  18  32  45]
- [  6   2  15 104   4   1  19]
- [  0  15   2   2  57   0   1]
- [  9   0   5   3   1  39   3]
- [ 14   2   4   7   7  16  87]]
-Node Classification on random seed  9175 -> 0.633
-Confusion Matrix:
- [[ 63   1   4   0   2  20   7]
- [  5 122   8   2  21   5   3]
- [  9  40 154  22  20  30  32]
- [  8   4  12 103   2  17  12]
- [  0   7   3   2  62   0   2]
- [  2   1   0   0   0  47   8]
- [  5  12  11   1   4  23  82]]
-Node Classification on random seed  9176 -> 0.6
-Confusion Matrix:
- [[ 56   5   6   7   3  11  11]
- [  5 116   3   4  11   2   6]
- [ 20  24 136  42  28  16  38]
- [ 13   4  17 101   3   4  15]
- [  2  13   3   5  59   3   3]
- [  9   2   2   2   3  50   3]
- [ 10   2   9  11   7  13  82]]
-Node Classification on random seed  9177 -> 0.591
-Confusion Matrix:
- [[ 84   4   5   3   2  20   7]
- [  2 115   5   2  14   1   1]
- [ 33  24 118  28  54  21  39]
- [  8   5  15 118   6   7   6]
- [  0   3   2   4  58   0   1]
- [  9   4   4   0   3  43   7]
- [  8   7   8   6  11  20  55]]
-Node Classification on random seed  9178 -> 0.604
-Confusion Matrix:
- [[ 47   1   5   5   5  15  19]
- [  5 136   2   0  12   0   8]
- [ 15  20 146  40  25  22  59]
- [ 13   3  13  98  17   8  10]
- [  2   4   0   0  64   0   3]
- [  3   3   1   1   1  41   6]
- [ 10   2   9  10   9  10  72]]
-Node Classification on random seed  9179 -> 0.64
-Confusion Matrix:
- [[ 82   2  10   7   2   9   3]
- [  6 146   6   2   2   1   2]
- [ 26  31 139  29  22  33  21]
- [  8   8   7  97   3   6   6]
- [  2   4   5   2  68   0   0]
- [  9   8   1   2   0  43   4]
- [ 21   4  10  13   7  16  65]]
-Node Classification on random seed  9180 -> 0.618
-Confusion Matrix:
- [[ 61   2   3   1   7   9  10]
- [  6 138   7   3  13   0   5]
- [ 37  23 144  30  26  13  37]
- [ 21   6   7  95  11   8  10]
- [  2   9   4   0  59   0   0]
- [  8   1   6   1   0  43   3]
- [ 14   3   9   6  12   9  78]]
-Node Classification on random seed  9181 -> 0.589
-Confusion Matrix:
- [[ 61  10   4   9   5   9  13]
- [  5 126  11   2   4   7   7]
- [ 18  37 120  42  27  17  42]
- [  5   2  13 105   3  10  19]
- [  0   3   6   3  60   1   4]
- [  3   2   1   5   0  36  14]
- [ 11   2   7   3   8  17  81]]
-Node Classification on random seed  9182 -> 0.636
-Confusion Matrix:
- [[ 67   0   0   2   4  14   3]
- [  3 128   4   2   2   7   1]
- [ 23  14 142  38  30  17  53]
- [ 11   4  11 117   3   6  21]
- [  3   4   3   1  58   6   3]
- [ 13   2   1   1   0  37   4]
- [ 15   4   3   3   9  16  87]]
-Node Classification on random seed  9183 -> 0.66
-Confusion Matrix:
- [[ 80   5  16   3   5   5  18]
- [  4 113   5   0   6   1   4]
- [ 14  18 143  17  28  20  42]
- [ 13   9  11 126   9   3  15]
- [  0   4   6   0  59   1   1]
- [  2   1   1   4   0  43   5]
- [  5   5  11   9   7   7  96]]
-Node Classification on random seed  9184 -> 0.605
-Confusion Matrix:
- [[ 69   3   7   6   4  11   3]
- [  6 130   3   1   3   3   5]
- [ 38  29 132  38  33  16  32]
- [ 13   7  22  87   2   3  18]
- [  1   9   3   4  59   3   6]
- [  5   1   3   0   0  49   2]
- [ 17   6   8   7   2  12  79]]
-Node Classification on random seed  9185 -> 0.622
-Confusion Matrix:
- [[ 71   4   2   2   4   6   3]
- [  3 125   9   4  10   0   0]
- [ 29  29 164  39  13  17  31]
- [ 10   6   8 108   0   7  19]
- [  2  12   6   3  52   1   1]
- [ 17   1   3   0   1  44   2]
- [ 24   5   6   8   6  25  58]]
-Node Classification on random seed  9186 -> 0.623
-Confusion Matrix:
- [[ 76   1   2   6   2   5  15]
- [  2 123   5  10   2   1   2]
- [ 26  26 154  28  23  22  37]
- [  6   4  14 104   6   9  19]
- [  3   9   4   4  55   0   1]
- [  0   2   9   0   1  40   3]
- [ 13   4  10  11   7  23  71]]
-Node Classification on random seed  9187 -> 0.63
-Confusion Matrix:
- [[ 62   7   7   5   5  17   5]
- [  0 126   4   5   6   4   7]
- [ 16  27 167  23  25  22  29]
- [ 13   5  14  96   5  11  12]
- [  1   5   4   0  66   1   1]
- [  2   4   4   0   2  47   3]
- [ 15   5  10  11   5  23  66]]
-Node Classification on random seed  9188 -> 0.621
-Confusion Matrix:
- [[ 68   2   3   3   4  29  13]
- [  2 149   3   3   2   7   1]
- [ 15  28 116  38  16  17  49]
- [ 22   8   5  97   5  14   9]
- [  2   5   2   1  61   4   4]
- [  3   1   1   8   0  33   2]
- [  3   4  10   8   7  16  97]]
-Node Classification on random seed  9189 -> 0.613
-Confusion Matrix:
- [[ 70   2   3   3  12  13   9]
- [  2 143   6   2  10   0   1]
- [ 25  19 128  26  54  16  27]
- [ 12   3  18 103  13   2  15]
- [  0   3   2   0  67   0   2]
- [  2   0   4   3   1  39   6]
- [  9   6   7  10  22  17  63]]
-Node Classification on random seed  9190 -> 0.607
-Confusion Matrix:
- [[ 65   2   9   4   4  21   6]
- [  9 127   7   2   9   2   3]
- [ 30  36 154  30  16  22  33]
- [ 10   1  21  83   7   9  10]
- [  2   7   5   6  65   1   2]
- [  9   2   4   1   0  38   1]
- [ 13   3   9   7   5  13  75]]
-Node Classification on random seed  9191 -> 0.563
-Confusion Matrix:
- [[ 69  11  12   3   2  11  17]
- [  4 129   3   2   9  14   5]
- [ 15  15 126  29  29  30  49]
- [  5   3  22  77  12   3  14]
- [  3   6   9   2  54   3   2]
- [  2   1   0   2   0  37  27]
- [  7   4  14   7  18  11  71]]
-Node Classification on random seed  9192 -> 0.595
-Confusion Matrix:
- [[ 70   1  10   3   2   9   6]
- [  3 129   4   1   5   3   3]
- [ 24  29 118  44  30  33  37]
- [ 11   5  16  93   6   8   9]
- [  2   5   3   1  58   0   3]
- [  4   1   4   3   2  56   7]
- [  9   5   9  15   7  23  71]]
-Node Classification on random seed  9193 -> 0.603
-Confusion Matrix:
- [[ 52   4  10   5   7   8  12]
- [  5 129   3   0   6  10   3]
- [  7  20 163  40  38  31  27]
- [  8   0  18  89   7   6  19]
- [  1   8   3   0  55   6   3]
- [ 11   1   5   4   0  42   6]
- [ 21   1  10   8   8   7  73]]
-Node Classification on random seed  9194 -> 0.598
-Confusion Matrix:
- [[ 59   5  10   3   2  14   9]
- [  2 129   7   2   5   3   4]
- [ 29  27 131  41  25  37  35]
- [ 12   3  10  94   5   6  11]
- [  2   8   4   1  58   1   1]
- [  4   2   2   4   0  60   6]
- [ 14   5  11   5   7  18  67]]
-Node Classification on random seed  9195 -> 0.603
-Confusion Matrix:
- [[ 58   2  10   2  13  12   6]
- [  3 122   4   1   9   4   4]
- [ 20  42 131  40  33  18  34]
- [ 11   1  13 106  10   6  12]
- [  1  13   2   0  65   0   7]
- [  1   1   0   5   0  39   7]
- [ 12   2   3   9  12  12  82]]
-Node Classification on random seed  9196 -> 0.584
-Confusion Matrix:
- [[ 69   5   4  12   3  10  10]
- [  6 100   9   1  11   2   2]
- [ 40  38 122  25  30  18  40]
- [ 15   4  15  96   0   4  14]
- [  2   4   4   1  77   3   1]
- [  6   3   3   4   4  48   5]
- [ 13   2  13   1   9  20  72]]
-Node Classification on random seed  9197 -> 0.608
-Confusion Matrix:
- [[ 68   2   5   4   2   7  21]
- [  4 129   2   1  11   3   7]
- [ 27  24 134  60  20  28  26]
- [  8   2  17 113   3   2  13]
- [  0  12   5   1  53   0   2]
- [  1   0   2   3   0  43   4]
- [ 10   1  19   8   4  21  68]]
-Node Classification on random seed  9198 -> 0.618
-Confusion Matrix:
- [[ 62   2   3   4   2  11  15]
- [ 13 103   5   0  22   4   1]
- [ 20  18 170  40  18  20  26]
- [  9   1   9  87  14   8  12]
- [  2   8   5   1  62   0   6]
- [  8   4   1   3   2  43   3]
- [ 18   5   8   2  18  11  91]]
-Node Classification on random seed  9199 -> 0.585
-Confusion Matrix:
- [[ 77   1   3  10   4  18   6]
- [  1 107   5   3  20   3   1]
- [ 30  22 126  30  19  27  50]
- [ 27  11   8 106   3  11  14]
- [  4   3   3   0  64   1   0]
- [  9   2   1   1   1  46   6]
- [ 17   1   8   6   7  18  59]]
-Node Classification on random seed  9200 -> 0.572
-Confusion Matrix:
- [[ 72   3  12   4   5   8  11]
- [  7 118   8   1   7   1   5]
- [ 20  25 112  44  20  38  42]
- [ 19   3   8 103  13   7  12]
- [  1  10   2   5  60   0   5]
- [  4   1   7   1   2  45   3]
- [  8   2  19  11   7  17  62]]
-Node Classification on random seed  9201 -> 0.632
-Confusion Matrix:
- [[ 68   6   3   1   5  15  15]
- [  5 124   3   0   7   2   8]
- [ 18  28 151  37  24  16  38]
- [ 14   6  13 102   4   9   5]
- [  3   5   2   3  51   1   4]
- [  9   1   5   1   0  50   4]
- [ 20   3   7   7   6   5  86]]
-Node Classification on random seed  9202 -> 0.624
-Confusion Matrix:
- [[ 69   6   2   5   3   6   8]
- [  4 132   8   3  13   1   7]
- [ 14  14 155  37  24  26  33]
- [ 16  10  14  93   5   5  24]
- [  2   1   3   1  63   0   3]
- [  2   2   2   1   3  37   6]
- [ 19   5  11  11   8   8  75]]
-Node Classification on random seed  9203 -> 0.605
-Confusion Matrix:
- [[ 65   5  12   4   2   8  13]
- [  3 116  12   3  16   5   1]
- [ 22  17 159  34  41  21  34]
- [ 27   6   6  97   4   4  11]
- [  0   5   4   1  63   1   2]
- [  4   0   1   1   1  54   2]
- [ 22   3   5   9   9  14  51]]
-Node Classification on random seed  9204 -> 0.633
-Confusion Matrix:
- [[ 75   5   2   3   9   6  12]
- [  0 114   4   7   9   0   5]
- [ 14  16 162  24  19  14  48]
- [  6   4  19 123   4   8  19]
- [  0   2   5   1  67   1   7]
- [ 11   1   3   1   4  31   8]
- [ 11   1   7   9  29   9  61]]
-Node Classification on random seed  9205 -> 0.672
-Confusion Matrix:
- [[ 77   9   1   4   2   7   7]
- [  3 130   2   2  11   2   4]
- [ 28  10 170  31  18  18  32]
- [ 11   4   5 111   7   9   9]
- [  1   2   4   1  62   1   4]
- [  8   2   4   0   0  39   9]
- [ 20   2   3   9   7  15  83]]
-Node Classification on random seed  9206 -> 0.576
-Confusion Matrix:
- [[ 71   4   3   1   5   7  21]
- [  3 117   6   2   4   1   4]
- [ 39  25 129  44  30  18  36]
- [ 27   4  16  77   5   2  14]
- [  2   7   3   1  64   1   1]
- [  6   2   3   6   2  37   5]
- [ 21   1  13   8   6  15  81]]
-Node Classification on random seed  9207 -> 0.595
-Confusion Matrix:
- [[ 70   2   1  11   6   5  11]
- [ 10 127   5   2   8   3   4]
- [ 20  23 135  30  32  15  47]
- [ 25   2  20  88   3   7  14]
- [  2   8   2   0  60   0   4]
- [ 15   2   2   0   0  44   3]
- [ 13   5  15   9  12   7  71]]
-Node Classification on random seed  9208 -> 0.667
-Confusion Matrix:
- [[ 95   3   4   1   2  13   6]
- [  6 140   6   2   7   0   4]
- [ 26  20 150  35  13  21  28]
- [ 15   1  10  98   8   4  15]
- [  1   2   1   5  59   2   3]
- [  3   2   4   0   0  51   6]
- [ 15   6   5   4   9  15  74]]
-Node Classification on random seed  9209 -> 0.598
-Confusion Matrix:
- [[ 80   3   7   7   3  13  10]
- [  2 129   9   2   7   3   5]
- [ 27  11 104  35  44  26  44]
- [ 10   7   7 117   8   8  12]
- [  2   8   4   1  54   3   1]
- [  2   2   4   1   1  52   6]
- [  9   3  18   7   3  17  62]]
-Node Classification on random seed  9210 -> 0.626
-Confusion Matrix:
- [[ 91   2   0   8   4   7  16]
- [  9 131   5   1   6   4   4]
- [ 21  23 157  28  28  31  31]
- [ 19   0  12 103   5   3   9]
- [  1   6   4   2  46   5   4]
- [  9   1   0   5   1  43  10]
- [  8   4   8   9   5  16  55]]
-Node Classification on random seed  9211 -> 0.628
-Confusion Matrix:
- [[ 85   5   3   7   1   3   8]
- [  3 137  10   1  10   0   3]
- [ 26  42 124  34  24  13  47]
- [  6   3  13 101  12   2  14]
- [  2   5   6   1  56   0   2]
- [  8   5   4   0   1  39   2]
- [ 13   5  12   5   4   7  86]]
-Node Classification on random seed  9212 -> 0.593
-Confusion Matrix:
- [[ 65   2   1   6   6  16   5]
- [  4 125   7   5   8   4   0]
- [ 24  36 136  29  18  25  39]
- [ 14   1  18  87   6   8  21]
- [  1  12   2   3  59   2   4]
- [  6   3   1   5   0  45   9]
- [ 10   6  11   4   5  20  76]]
-Node Classification on random seed  9213 -> 0.63
-Confusion Matrix:
- [[ 58   4   8  10   4  12  11]
- [  8 113   9   7  12   2   2]
- [ 19   6 168  46  36  11  34]
- [  3   3   8 107  12   9  11]
- [  4   5   2   5  62   1   0]
- [  1   1   4   0   1  42   3]
- [ 14   2  19   9   5   7  80]]
-Node Classification on random seed  9214 -> 0.651
-Confusion Matrix:
- [[ 75   4   0  10   1   9  20]
- [  9 116   8   1   7   4   2]
- [ 21  20 161  32  33  16  20]
- [  4   3  12 114  13   3  11]
- [  3   7   4   4  63   1   3]
- [  7   2   4   2   0  44   5]
- [ 14   2   4   6  11   7  78]]
-Node Classification on random seed  9215 -> 0.63
-Confusion Matrix:
- [[ 67   3   6   4   5  16  14]
- [  6 128   4   0  10   7   3]
- [ 19  24 157  35  24  22  38]
- [  8   3  16  89   5   6  14]
- [  0   4   3   0  53   1   4]
- [  9   0   5   1   0  48   1]
- [  9   1  10   7  11  12  88]]
-Node Classification on random seed  9216 -> 0.582
-Confusion Matrix:
- [[ 73   3   1   5   6  15  10]
- [  3  98  14   3  14   1   4]
- [ 30  25 144  29  19  19  59]
- [ 11   8  17 100   6   7  14]
- [  0   5   4   1  68   1   2]
- [  3   1   0   2   0  34  12]
- [  7   2   5  10  10  30  65]]
-Node Classification on random seed  9217 -> 0.603
-Confusion Matrix:
- [[ 64   1   1   4   4  12  17]
- [  4 140   3   2   6   3   2]
- [ 37  30 118  24  50  15  42]
- [ 10   8   6 107   3   5  27]
- [  0   4   0   2  56   1   4]
- [  6   2   0   0   0  41   6]
- [ 15  10   8   6   7  10  77]]
-Node Classification on random seed  9218 -> 0.61
-Confusion Matrix:
- [[ 63   0   2   3   5  11  15]
- [  1 138   4   4   6   4   6]
- [ 14  26 137  55  24  23  36]
- [ 16   4  19  97   6   7  17]
- [  1  10   5   2  58   1   1]
- [  4   0   4   1   0  40   5]
- [  5   2   9   7   4  21  77]]
-Node Classification on random seed  9219 -> 0.599
-Confusion Matrix:
- [[ 62   0   9  14   4   8   8]
- [  9 109   8   2   4   1  11]
- [ 51  12 155  33  18  22  32]
- [ 16   7  19  98   5   9   5]
- [  1   6   3   3  53   2   1]
- [  6   0   5   3   0  37  16]
- [ 11   6   9   9   5   8  85]]
-Node Classification on random seed  9220 -> 0.644
-Confusion Matrix:
- [[ 74   3   8   3   4  10  13]
- [  3 125   1   2   7   2   4]
- [ 20  34 150  17  20  36  36]
- [  9  10  13 110   4  14   6]
- [  0   7   3   4  60   2   1]
- [  7   0   0   2   1  48   5]
- [  8   2  10  11   5   9  77]]
-Node Classification on random seed  9221 -> 0.625
-Confusion Matrix:
- [[ 73   5   6  13   1   5  12]
- [  8 126   3   1   8   4   4]
- [ 17  15 148  39  34  14  44]
- [ 11   7   4  99   7   9  20]
- [  2   8   4   0  64   1   3]
- [  8   2   2   0   0  39   2]
- [  5   9  14  14   5   5  76]]
-Node Classification on random seed  9222 -> 0.659
-Confusion Matrix:
- [[ 74   2  12   0   7   2  13]
- [ 10 123   5   0  17   1   0]
- [ 20  24 178  29  25  12  39]
- [  6   7  15 105   1   5  15]
- [  5   2   3   0  56   0   1]
- [  5   3   1   2   1  39   7]
- [  7   3   6   8   5  15  84]]
-Node Classification on random seed  9223 -> 0.676
-Confusion Matrix:
- [[ 96   0   2   0   3   9  11]
- [  3 119  10   3   6   1   5]
- [ 19  17 157  20  35  20  28]
- [  6   8  19 103   7   7   9]
- [  1   6   1   2  63   1   5]
- [  8   1   3   1   1  51   1]
- [  5   6   7   2   3  22  87]]
-Node Classification on random seed  9224 -> 0.616
-Confusion Matrix:
- [[ 70   3   6  15   3  13   7]
- [  9 125   6   4   1   6   1]
- [ 19  22 157  38  20  16  28]
- [ 13   5  16 102   7   4   7]
- [  0   5   8   3  62   1   3]
- [  4   3   3   6   0  29  11]
- [ 10  12  12  11   4  19  71]]
-Node Classification on random seed  9225 -> 0.598
-Confusion Matrix:
- [[ 57   1   7   1   4  10  21]
- [  7 104   9   5  11   6   7]
- [ 38  14 151  43  21  15  44]
- [ 11   2  12 107   4  11  10]
- [  3   4   7   2  57   1   1]
- [  4   0   3   1   0  45   7]
- [ 14   3   8   3   9  18  77]]
-Node Classification on random seed  9226 -> 0.568
-Confusion Matrix:
- [[ 64   4   6   9   9  11  10]
- [  3 128   9   1  15   3   4]
- [ 37  28 120  28  20  27  42]
- [ 16   2  18 100   8   3   6]
- [  6   7   4   0  57   2   3]
- [  3   1   3   5   3  46   7]
- [  9   2  10  20   7  21  53]]
-Node Classification on random seed  9227 -> 0.617
-Confusion Matrix:
- [[ 63   0   6   3   4  18   7]
- [  3 131   4   5   8   2   3]
- [ 31  18 139  38  25  26  39]
- [ 16   2   6 101   4   8  13]
- [  0   5   4   4  63   1   3]
- [  2   1   2   5   2  48   7]
- [  9   8   8   7   6  20  72]]
-Node Classification on random seed  9228 -> 0.626
-Confusion Matrix:
- [[ 80   5   6   3   4  11   6]
- [  6 120   5   3   3   4   2]
- [ 15  32 131  40  44  17  34]
- [  2   8  21 112   5   9  14]
- [  0   4   2   1  61   1   1]
- [  4   0   2   0   1  39   3]
- [  9   6  14   4   6  17  83]]
-Node Classification on random seed  9229 -> 0.663
-Confusion Matrix:
- [[ 69   0   5   4   2  16   3]
- [  2 130   1   2   7   8   6]
- [ 22   8 146  32  25  34  31]
- [ 13   0  16 114   4   5  13]
- [  2   8   2   0  64   2   2]
- [  3   1   2   3   2  34  11]
- [  6   1  14   3   5  11 106]]
-Node Classification on random seed  9230 -> 0.632
-Confusion Matrix:
- [[ 76   5   2   9   6   8  12]
- [  6 135   6   2   7   1   7]
- [ 22  20 145  20  10  29  43]
- [ 11   2  13 111   2   5  15]
- [  0   6   2   3  59   0   4]
- [  8   4   2   3   1  42   5]
- [ 19   4  10  12   6  16  64]]
-Node Classification on random seed  9231 -> 0.63
-Confusion Matrix:
- [[ 78   3   2   2   6   9   3]
- [  6 156   6   0   1   0   0]
- [ 21  33 120  33  25  22  47]
- [ 17   6  14  91   3  12  11]
- [  0  11   3   2  69   3   2]
- [  4   1   2   2   0  44   2]
- [  9  10  16   4   2  15  72]]
-Node Classification on random seed  9232 -> 0.626
-Confusion Matrix:
- [[ 63   5   2   3   2  14  12]
- [ 10 129   9   5   4   2   6]
- [ 19  21 159  40  12  19  41]
- [ 15   4  20 102   3   3  16]
- [  6   7   2   1  56   1   8]
- [  4   1   2   2   0  47   2]
- [  6   8  11   5   3  18  70]]
-Node Classification on random seed  9233 -> 0.621
-Confusion Matrix:
- [[ 74   4   6  14   1  12   4]
- [  3 114  10  10   5   1   5]
- [ 30  33 142  33  24  23  28]
- [ 10   3   8 124   4   4  13]
- [  1   2   6   4  64   0   0]
- [  4   2  20   0   0  32   3]
- [ 11   0   9  10   4  15  71]]
-Node Classification on random seed  9234 -> 0.601
-Confusion Matrix:
- [[ 55   7   3   5   5  20  11]
- [  4 118   3   2  10   3   5]
- [ 21  20 139  45  13  29  42]
- [ 13   4  18 105   8  10   9]
- [  0   5   4   3  71   1   2]
- [  3   1   4   2   1  55   3]
- [ 14   2   8   6   3  27  58]]
-Node Classification on random seed  9235 -> 0.614
-Confusion Matrix:
- [[ 68   0   1   7   2  14  11]
- [  1 121  11   3   6   6   4]
- [ 22  31 148  35  23  24  32]
- [ 14   3  13 107   2   9  15]
- [  1   9   2   3  51   4   1]
- [  8   0   2   1   0  42   3]
- [  7   6  14   7   5  24  77]]
-Node Classification on random seed  9236 -> 0.652
-Confusion Matrix:
- [[ 69   6   0   6   2  10  15]
- [  2 134   7   3   4   4   4]
- [ 13  25 153  36  14  16  63]
- [  7  12  10  91   6   5  17]
- [  2   4   2   0  68   3   2]
- [  2   4   4   1   0  33  11]
- [  5   3   2   5   3   8 104]]
-Node Classification on random seed  9237 -> 0.62
-Confusion Matrix:
- [[ 65  12   1   8   3  15   7]
- [  7 126  10   1   6   3   4]
- [ 24  16 139  36  28  24  36]
- [  9   3  12  98   5   6  21]
- [  1  11   4   3  70   1   0]
- [  6   5   1   2   0  51   9]
- [  7   5   3   4   8  13  71]]
-Node Classification on random seed  9238 -> 0.654
-Confusion Matrix:
- [[ 66   1   3   0   6  11   3]
- [  2 135   1   3   8   1   8]
- [ 17  24 144  33  28  24  44]
- [ 10   3  11 120   5   6  12]
- [  3   5   2   2  70   1   3]
- [  2   3   3   3   1  39   2]
- [  9   1   2  14  10  16  80]]
-Node Classification on random seed  9239 -> 0.624
-Confusion Matrix:
- [[ 72   7   2   4   6   7  10]
- [  2 143   5   0   8   1   2]
- [ 10  28 133  39  28  26  30]
- [ 20   6  19  97   2   7  10]
- [  0  13   4   0  59   0   1]
- [  8   1   4   1   0  51   2]
- [ 24   6  12   4   5  12  69]]
-Node Classification on random seed  9240 -> 0.595
-Confusion Matrix:
- [[ 57   6   4   1   2  14  15]
- [  5 107   8  11   9   0   5]
- [ 26  13 135  49  15  19  38]
- [ 13   4  12  98   3   5  15]
- [  0  11  10   3  53   0   1]
- [  7   1   4   4   0  57   4]
- [ 17   4   4  10   7  26  88]]
-Node Classification on random seed  9241 -> 0.618
-Confusion Matrix:
- [[ 94   1   4   8   6  16   1]
- [  8 121   2   1   4   3  15]
- [ 27  19 149  31  40   9  32]
- [ 20   9  16  82   8   7  11]
- [  0   8   1   1  72   0   0]
- [  7   1   2   1   4  41   2]
- [ 10   4   6   3   9  25  59]]
-Node Classification on random seed  9242 -> 0.599
-Confusion Matrix:
- [[ 62   0   2   8   4   8  16]
- [  2 134   4   0   6   3   6]
- [ 44  14 133  33  25  12  44]
- [ 19   6  21  96  11   3  12]
- [  1   7   1   3  55   0   2]
- [ 11   0   3   0   1  51   5]
- [ 12   3  17  11  13   8  68]]
-Node Classification on random seed  9243 -> 0.613
-Confusion Matrix:
- [[ 60   3   7   7   2   9   7]
- [  0 149  11   3   5   2   5]
- [ 23  35 130  32  32  29  29]
- [ 10   2   8 112   8   9  13]
- [  1   7   8   3  51   0   1]
- [  3   4   2   2   3  38   8]
- [  5   3  16   8   1  21  73]]
-Node Classification on random seed  9244 -> 0.654
-Confusion Matrix:
- [[ 84   4   3   4   3   9  13]
- [  5 134   5   1   8   2   2]
- [ 17  29 158  26   9  18  40]
- [ 11   6  14  96   5   8  11]
- [  0  11   6   1  71   2   1]
- [  2   2   1   3   0  46   8]
- [  9   5   8  18   8   8  65]]
-Node Classification on random seed  9245 -> 0.622
-Confusion Matrix:
- [[ 50   1   0  12   1   5  13]
- [  5 132   7   1   8   3  10]
- [ 21  20 177  33  12  17  51]
- [  6   0  19  91  14   6  18]
- [  4   5   8   1  57   1   0]
- [  9   0   0   4   1  49   5]
- [  6   1  11  19   6  14  66]]
-Node Classification on random seed  9246 -> 0.577
-Confusion Matrix:
- [[ 75   4   7   1   6   8   7]
- [  4 127   7   5   7   4   1]
- [ 15  16 126  57  20  30  41]
- [ 41   6  10  87   8   7  10]
- [  2   6   4   3  53   0   2]
- [  3   2  12   1   1  45   1]
- [ 17   4   7   9   6  21  64]]
-Node Classification on random seed  9247 -> 0.627
-Confusion Matrix:
- [[ 73  10   8   1   5   6   9]
- [  2 125   8   1   4   6   1]
- [ 28  20 128  22  16  28  43]
- [  8   6  24 105   6   8  14]
- [  1   1   7   0  60   1   3]
- [  7   2   1   2   0  49   7]
- [ 18   5  10   4   9  11  87]]
-Node Classification on random seed  9248 -> 0.615
-Confusion Matrix:
- [[ 78   2  10   3   7  10   6]
- [  4 118   1   4  18   4  13]
- [ 21  25 132  20  12  34  44]
- [  9   1  18 111   7   6  13]
- [  3   8   3   0  61   1   2]
- [  4   0   4   4   1  43   5]
- [ 14   5   7  10   6  16  72]]
-Node Classification on random seed  9249 -> 0.625
-Confusion Matrix:
- [[ 73   4   2   3   2  14  12]
- [  5 134   2   7   4   4   4]
- [ 17  10 132  37  31  32  46]
- [ 12   3  16 104   7   5  18]
- [  1   3   1   0  61   0   6]
- [  9   0   0   1   0  49   1]
- [ 16   0  16   4   9  11  72]]
-Node Classification on random seed  9250 -> 0.637
-Confusion Matrix:
- [[ 84   2   2   7   2  11   4]
- [  1 135   2   3  14   3   4]
- [ 22  31 136  51  17  21  25]
- [  6   3   6 113   5   5  18]
- [  1   2   4   5  74   1   4]
- [  6   1   2   3   3  41   3]
- [  7   4   6  22   5  19  54]]
-Node Classification on random seed  9251 -> 0.664
-Confusion Matrix:
- [[ 63   2   7   4   5   8  13]
- [  4 153   7   4  14   1   2]
- [ 17  13 142  20  21  24  46]
- [  5   8   8 109  15   4  10]
- [  0   2   3   1  61   0   1]
- [  2   0   3   3   1  41   6]
- [  7   5   9  13   7  11  95]]
-Node Classification on random seed  9252 -> 0.631
-Confusion Matrix:
- [[ 80   4   2   4   1   7   4]
- [  0 164   0   7   9   3   1]
- [ 27  31 143  39  20   7  41]
- [ 15   7  31  84   9   1  11]
- [  1   4   4   1  54   0   2]
- [  7   4   2   3   3  40   2]
- [  8   4  13  12   7  11  66]]
-Node Classification on random seed  9253 -> 0.585
-Confusion Matrix:
- [[ 79   1   0   3   5   7  10]
- [  4 113  13   6  11   3  10]
- [ 24  31 116  25  27  29  52]
- [  8   4   8 100  10   5  20]
- [  2   5   3   1  70   0   4]
- [  9   0   4   0   3  37  10]
- [ 14   4   9   6   6  19  70]]
-Node Classification on random seed  9254 -> 0.666
-Confusion Matrix:
- [[ 71   6   4   8   3  10   5]
- [  2 139   2   6   7   6   2]
- [ 16  10 189  31  27  23  34]
- [ 10   2  16  89   8   4  12]
- [  1   4   4   1  72   0   3]
- [  5   3   2   5   3  36  13]
- [ 12   2   4   6   6   6  70]]
-Node Classification on random seed  9255 -> 0.645
-Confusion Matrix:
- [[ 75   4   3   4   5  13   8]
- [  4 120   7   0  13  10   1]
- [ 18  18 156  40  18  20  31]
- [  7   4  17 109   8   5  11]
- [  1   8   3   1  67   1   2]
- [  5   0   1   3   2  57   4]
- [  8   2  10  10   3  22  61]]
-Node Classification on random seed  9256 -> 0.635
-Confusion Matrix:
- [[ 84   3   4   4   2  11   9]
- [  5 115   1   3   4   3   2]
- [ 17  30 142  24  29  18  38]
- [ 15   8  18  98   6  11  18]
- [  1   7   6   3  56   2   1]
- [  3   2   6   1   4  55   2]
- [  8   3   3   7   7  16  85]]
-Node Classification on random seed  9257 -> 0.631
-Confusion Matrix:
- [[ 85   2  10   3   0  11   5]
- [  4 126   3   4   3   1   6]
- [ 19  30 152  44  26  15  29]
- [ 29   3  13  96   8   6   9]
- [  0  12   2   0  64   1   2]
- [  7   1   2   7   0  36   3]
- [  7   8   9   4   4  17  72]]
-Node Classification on random seed  9258 -> 0.593
-Confusion Matrix:
- [[ 48   1   3   6   1  14  21]
- [  3 135   5   2   9   2  10]
- [ 34   8 129  45  30  24  55]
- [  9   2   9 119   5   7  11]
- [  0   5   2   0  65   0   3]
- [  6   0   3   2   0  40   6]
- [  9   5   5  23   9  13  57]]
-Node Classification on random seed  9259 -> 0.555
-Confusion Matrix:
- [[ 59   1   2   3   6  15  18]
- [  5 111   7   5   7   4   5]
- [ 37  12 112  48  39  33  50]
- [ 33   0   6 102   9   4   7]
- [  0   4   2   2  62   0   4]
- [  8   2   2   1   0  39   6]
- [  6   4  11  13   4  20  70]]
-Node Classification on random seed  9260 -> 0.593
-Confusion Matrix:
- [[ 80   5   1   7   1   6  10]
- [ 15 108   8   3  19   0   2]
- [ 19  16 133  68  36  19  31]
- [ 12   4  12  92  13   2  19]
- [  3   7   3   0  54   1   1]
- [  5   2   0   0   4  47   7]
- [ 16   4  10   7   2   7  79]]
-Node Classification on random seed  9261 -> 0.615
-Confusion Matrix:
- [[ 51   2   7  13   1  15  11]
- [  2 132   7   1   3   5   8]
- [ 14  20 133  62  23  20  45]
- [ 11   6  12 101  10   4  17]
- [  1   1   8   0  60   1   5]
- [  2   0   1   1   2  49   8]
- [  8   6   9   0   3  10  89]]
-Node Classification on random seed  9262 -> 0.625
-Confusion Matrix:
- [[ 67   2   2   4   4   8  17]
- [ 10 121   4   6   3   1   3]
- [ 33  16 143  27  21  16  58]
- [ 12   5   7 109   5  13  17]
- [  3   9   4   1  53   0   1]
- [  9   1   0   3   2  44   5]
- [ 14   1   4  10   5   9  88]]
-Node Classification on random seed  9263 -> 0.655
-Confusion Matrix:
- [[ 81   3   2   3   5  14   5]
- [  2 123   6   1   7   5   3]
- [ 30  21 148  49  28  15  22]
- [ 13   1  16 115   1   2  16]
- [  0   9   4   5  55   1   1]
- [  4   0   2   1   0  44   5]
- [  9   4   8   3   4  15  89]]
-Node Classification on random seed  9264 -> 0.603
-Confusion Matrix:
- [[ 61   3   8   1   2  15  11]
- [  2 148   6   2   6   2   0]
- [ 12  28 122  47  32  26  37]
- [  6   3  25  91   3   5  17]
- [  3   6   4   0  67   2   2]
- [  2   1   3   4   7  35   9]
- [ 12   4   9   7   5  18  79]]
-Node Classification on random seed  9265 -> 0.563
-Confusion Matrix:
- [[ 64   5  13   5   2  14   4]
- [  4 126   3   3  12   1   2]
- [ 26  24 115  39  63  17  44]
- [  7  10  19 103   7   7  14]
- [  2   6   1   0  68   0   3]
- [  4   1   1   5   8  27   2]
- [  5   3  20   4   9  18  60]]
-Node Classification on random seed  9266 -> 0.62
-Confusion Matrix:
- [[ 57   5   4   3   4  15   6]
- [  5 136   5   3   9   1   5]
- [ 14  26 158  31  32  33  36]
- [ 11   3  14  90   4   5  20]
- [  3   6   3   3  60   0   1]
- [  2   1   4   4   2  39   3]
- [ 11   1   8  13   8  13  80]]
-Node Classification on random seed  9267 -> 0.609
-Confusion Matrix:
- [[ 70   2   3  12   2   7   6]
- [ 10 123   3  10   4   5   6]
- [ 22  23 128  24  50  25  29]
- [  6   3  32 101   2   6  12]
- [  5   6   3   0  73   0   0]
- [  2   0   1   1   0  48   8]
- [ 10   3  18  14   3  13  66]]
-Node Classification on random seed  9268 -> 0.628
-Confusion Matrix:
- [[ 79   2   2   5   6   9   8]
- [  2 147   6   2   1   2   1]
- [ 25  28 138  27  28  30  24]
- [ 18   6  15  85   8  11   8]
- [  1   6   3   6  61   1   3]
- [  5   3   2   0   4  46   7]
- [  4   2  10  20   3  18  72]]
-Node Classification on random seed  9269 -> 0.63
-Confusion Matrix:
- [[ 73   4   5   5   7  16  10]
- [  2 155   1   2   7   1   0]
- [ 32  34 134  29  30  11  39]
- [  8   7  12  90   2   6  15]
- [  3   8   6   3  54   0   2]
- [  0   4   1   1   4  46   3]
- [ 10   5   4  10   6  15  78]]
-Node Classification on random seed  9270 -> 0.618
-Confusion Matrix:
- [[ 68   3  12   9   6   9   4]
- [  4 141   5   4   5   0   4]
- [ 15  27 129  42  20  21  48]
- [ 15   2   8  96   4   5  16]
- [  0   7   2   0  62   3   0]
- [  3   3   0   5   4  48   6]
- [ 13   4   7   8   6  23  74]]
-Node Classification on random seed  9271 -> 0.576
-Confusion Matrix:
- [[ 76   3   3   4   4   5  12]
- [  4 106  14   0   8  12   5]
- [ 32  12 123  43  41  23  42]
- [ 11   4  16 100   9   8  13]
- [  3   4   6   4  59   0   1]
- [  7   0   2   0   0  40   9]
- [ 26   1   4   3   6  20  72]]
-Node Classification on random seed  9272 -> 0.551
-Confusion Matrix:
- [[ 55   4   8   1   5  15  15]
- [  6 123   5   3   9   2  11]
- [ 30  19 119  44  35  29  33]
- [ 16   3  23  90   5   6  10]
- [  1   8   4   0  71   2   3]
- [  9   2   1   0   3  37   6]
- [  8   5  11  22   9  18  56]]
-Node Classification on random seed  9273 -> 0.61
-Confusion Matrix:
- [[ 70  12  12   2   2  11   7]
- [  6 121   8   0   8   5   3]
- [ 24  20 164  32  18  29  35]
- [  3   3  16 101   2   6  18]
- [  1   7   6   4  50   1   3]
- [  6   3   9   0   0  33   3]
- [  6   4  13   8  13  21  71]]
-Node Classification on random seed  9274 -> 0.621
-Confusion Matrix:
- [[ 61   8   5  11   7   8  10]
- [  7 142   6   8   2   0   3]
- [  8  26 148  49  23  17  33]
- [ 16   5  24 104   5   0  10]
- [  3   5   1   1  56   0   2]
- [  9   1   0   5   0  43   7]
- [ 18   0  11   7   6  12  67]]
-Node Classification on random seed  9275 -> 0.598
-Confusion Matrix:
- [[ 63   1   6   1   7  14  10]
- [  3 131   5   4   6   4   6]
- [ 29  44 131  48  18  16  24]
- [ 14   9  13 109   3   1  12]
- [  1  19   1   0  62   0   2]
- [  3   4   4   2   0  42   4]
- [  6   6  12   7   3  30  60]]
-Node Classification on random seed  9276 -> 0.642
-Confusion Matrix:
- [[ 79   0  13   6   5   7   6]
- [  6 127   0   5  10   0   2]
- [ 23  14 129  34  31  24  39]
- [  2   4  20 116   5   3  11]
- [  1   5   2   1  60   0   3]
- [  3   2   1   0   0  44   2]
- [ 10   4  13   4  20  17  87]]
-Node Classification on random seed  9277 -> 0.596
-Confusion Matrix:
- [[ 86   6   2   1   4   4  17]
- [  2 143   4   0  12   2   2]
- [ 28  23 120  65  12  32  32]
- [ 25   9  11  77   3   7  12]
- [  1   8   1   4  52   1   2]
- [  3   3   1   1   0  41   7]
- [ 21   7   3   5   5  16  77]]
-Node Classification on random seed  9278 -> 0.63
-Confusion Matrix:
- [[ 65   6   0   1   3  11   8]
- [  2 133   7   1   8   2   2]
- [ 34  31 159  23  19  17  39]
- [ 24   1  13 108   6  11  15]
- [  3   6  10   0  57   0   2]
- [  2   1   4   1   0  49   5]
- [ 17   3  10   7   4  11  59]]
-Node Classification on random seed  9279 -> 0.633
-Confusion Matrix:
- [[ 64   5   1   5   1  20   8]
- [  3 129   2   2   6   2   2]
- [ 16  24 154  27  18  34  42]
- [ 11   3  18 102   6  10   5]
- [  0   9   3   0  65   2   2]
- [  0   4   0   3   1  44   6]
- [  6  10   3  13   9  25  75]]
-Node Classification on random seed  9280 -> 0.636
-Confusion Matrix:
- [[ 73   2   7   3   4   8   9]
- [  3 145   6   4   7   1   8]
- [ 26  32 122  31  27  30  38]
- [ 10   1  14 103   5   5   8]
- [  1   4   1   1  68   1   2]
- [  1   0   3   3   4  34  10]
- [  7   3   5  17   1  11  91]]
-Node Classification on random seed  9281 -> 0.637
-Confusion Matrix:
- [[ 76   3   2   7   4   7   3]
- [  6 120   9   4   4   4   1]
- [ 34  20 158  44  26  18  20]
- [  7   6   8 123   5   5  10]
- [  1  12   5   6  49   0   1]
- [  7   0   3   0   1  42  11]
- [ 11   2  14  13   7  12  69]]
-Node Classification on random seed  9282 -> 0.603
-Confusion Matrix:
- [[ 78   2  16   1   5   7  11]
- [  3 128   2   5   3   5   5]
- [ 36  18 144  29  20  16  35]
- [ 27   3  16  88   6   9  18]
- [  0   4  11   2  58   0   0]
- [ 11   1   2   1   1  35   2]
- [ 18   4  22   4   6  10  72]]
-Node Classification on random seed  9283 -> 0.612
-Confusion Matrix:
- [[ 64   3   0  11   8  11  13]
- [  5 122   6   6   7   1   4]
- [ 28  21 137  22  23  22  47]
- [  8   7  23 115   7   5  10]
- [  5   7   6   4  55   1   3]
- [  6   1   2   1   0  43   6]
- [  9   5   6   7  11  10  76]]
-Node Classification on random seed  9284 -> 0.608
-Confusion Matrix:
- [[ 76   3   3   2   3  13  14]
- [  8 120   8   1  19   5   3]
- [ 37  23 145  18  36  17  28]
- [ 15   5  16  96   6   7  13]
- [  3  10   1   2  57   2   4]
- [  5   0   1   2   0  53   2]
- [  9   4   6  17   7  14  61]]
-Node Classification on random seed  9285 -> 0.642
-Confusion Matrix:
- [[ 57   3   2   9   6   8  15]
- [  2 127   4   3   7   7   1]
- [ 23  25 144  26  16  28  43]
- [ 12   6  13 119   6  11   5]
- [  0   5   2   0  59   0   2]
- [  6   2   3   3   1  48   2]
- [  7   6   9   3   5  21  88]]
-Node Classification on random seed  9286 -> 0.678
-Confusion Matrix:
- [[ 78   5   2   5   2  13   3]
- [ 11 127   3   0   9   4  12]
- [ 29  15 181  12  15  15  42]
- [ 11   2  11 107   4  10  10]
- [  3   4   2   0  67   0   3]
- [  3   0   0   0   0  50   3]
- [  8   6   6  11   6  22  68]]
-Node Classification on random seed  9287 -> 0.639
-Confusion Matrix:
- [[ 70   5   1   6   8  11   9]
- [  5 149   3   2   5   6   2]
- [ 20  16 134  43  32  23  37]
- [  1   6  12 110   8  10  12]
- [  1   5   0   1  66   1   1]
- [  4   2   6   1   0  42   9]
- [ 11   4   6   7   7  12  68]]
-Node Classification on random seed  9288 -> 0.547
-Confusion Matrix:
- [[ 75   1  15   1   4   8  10]
- [  5 118   5   8   8   3   6]
- [ 22  32  95  86  23  20  29]
- [  8   2  43  97   2   6  15]
- [  0   7   4   2  55   0   2]
- [  1   1   4   6   2  43   3]
- [ 13   5  12   8   5  16  64]]
-Node Classification on random seed  9289 -> 0.665
-Confusion Matrix:
- [[ 72   1   2   5   4  12   8]
- [  3 139   5   1   6   3   3]
- [ 15  20 157  27  20  26  34]
- [  7   6  16 104   6   9   6]
- [  2   8   8   2  66   0   1]
- [  3   2   2   2   0  44  11]
- [ 11   2  11   7  10   8  83]]
-Node Classification on random seed  9290 -> 0.605
-Confusion Matrix:
- [[ 79   3   6   3   3   8   3]
- [  3 141   4   4   1   1   3]
- [ 28  32 112  35  34  21  29]
- [ 15   7   8 110   5  12   5]
- [  2   6   4   2  54   2   2]
- [ 22   4   4   3   1  26   3]
- [ 26   2  18   7   6   8  83]]
-Node Classification on random seed  9291 -> 0.628
-Confusion Matrix:
- [[ 69   2  10   6   7  13   8]
- [  6 126  12  10   5   5   8]
- [ 26  18 152  28  21  17  43]
- [ 10   4  11 101   4  10   5]
- [  0   8   4   6  52   2   5]
- [ 10   0   0   2   1  42   5]
- [  7   5   1   8   7  12  86]]
-Node Classification on random seed  9292 -> 0.615
-Confusion Matrix:
- [[ 72   4   4   5   7   6   6]
- [  5 125   3   1   0   0   6]
- [ 26  30 130  29  25  38  39]
- [ 13   4  11 112   6   8   8]
- [  1   8   6   2  58   1   5]
- [  9   2   2   0   0  42   3]
- [ 12   8   5  18   5  14  76]]
-Node Classification on random seed  9293 -> 0.643
-Confusion Matrix:
- [[ 70   3   6   2   7  11  15]
- [  3 123   3   0   5   7   3]
- [ 18  26 166  25  24  16  36]
- [ 17   4  12 108   2   9  12]
- [  1   3   3   0  61   1   3]
- [  3   2   6   8   1  34   4]
- [  4   4  15   8   6  19  81]]
-Node Classification on random seed  9294 -> 0.586
-Confusion Matrix:
- [[ 58   2   4   5   2  18   5]
- [  3 138   1   0   4   3   3]
- [ 29  30 109  27  40  36  35]
- [ 11   7  16 107  12  10   6]
- [  0  12   6   6  59   0   3]
- [  7   0   1   2   0  43   4]
- [  7   8  11  11   7  20  72]]
-Node Classification on random seed  9295 -> 0.6
-Confusion Matrix:
- [[ 87   2   6   6   7  15   1]
- [  4 105   8   4   2   1   6]
- [ 47  12 131  35  35  27  30]
- [ 25   0  15  91   1  11  16]
- [  1   4   1   1  55   2   4]
- [  9   1   0   2   2  52   5]
- [ 19   3   4   6   5  15  79]]
-Node Classification on random seed  9296 -> 0.611
-Confusion Matrix:
- [[ 61   5   7   8   4   9  20]
- [  6 135   1   0  12   2   3]
- [ 13  27 143  15  52  26  39]
- [ 20   3  19 107   1  10  14]
- [  0   5   0   1  56   2   1]
- [  0   2   2   1   0  46   4]
- [ 13   0   6  13   8  15  63]]
-Node Classification on random seed  9297 -> 0.633
-Confusion Matrix:
- [[ 64   7   6   7   2  10   7]
- [  3 118  13   0   3   8   2]
- [ 20  23 166  19  15  20  44]
- [  7   7  22  91   6   7  14]
- [  2   5   6   5  61   0   5]
- [ 11   0   5   2   0  52   3]
- [  8   5  13   5   2  18  81]]
-Node Classification on random seed  9298 -> 0.609
-Confusion Matrix:
- [[ 68   3   5   3   5   9  16]
- [  7 142   2   4   8   0   3]
- [ 26  14 107  44  39  33  28]
- [  9   6   9 107   4   8  13]
- [  2   4   4   1  65   0   2]
- [ 10   1   3   2   2  37  12]
- [ 14   6  10   5   9   6  83]]
-Node Classification on random seed  9299 -> 0.594
-Confusion Matrix:
- [[ 56   4   6   2   6  18   5]
- [  1 132   8   2  10   1   8]
- [ 10  15 124  41  19  45  50]
- [ 11   2  18  94  18   7  13]
- [  0   7   3   2  68   2   3]
- [  2   2   2   1   0  54   6]
- [  6   3  11  11   3  22  66]]
-Node Classification on random seed  9300 -> 0.609
-Confusion Matrix:
- [[ 64   1   3  13   6  15  12]
- [  4 138   4   5   8   5  10]
- [ 45  26 127  31  16  16  41]
- [  8   1  24 105   3   5  16]
- [  1   1   2   5  54   1   0]
- [  4   0   1   4   2  34   7]
- [ 10   4  10   9   5   7  87]]
-Node Classification on random seed  9301 -> 0.603
-Confusion Matrix:
- [[ 53   2   6   7   5  10  16]
- [  6 127   6   1   6   6   4]
- [ 25  16 161  33  28  26  35]
- [ 16  12  20 105   2   3   7]
- [  0   8   3   2  46   2   2]
- [  8   3   0   4   3  43   1]
- [ 12   5  11  11   8  16  68]]
-Node Classification on random seed  9302 -> 0.65
-Confusion Matrix:
- [[ 74   4   0   5   5  13  14]
- [  4 128   4   0  10   1   6]
- [ 29  16 143  25  29  14  47]
- [ 12  10  13 106   0   3   9]
- [  1   6   1   1  69   1   2]
- [  6   2   1   1   1  42   9]
- [  9   2   4  10   1  19  88]]
-Node Classification on random seed  9303 -> 0.636
-Confusion Matrix:
- [[ 67   1   6  13   3   7   7]
- [  4 134   8   1  16   0   2]
- [ 38  21 145  33  25  27  24]
- [ 11   1  10 110   6   0  11]
- [  0   5   4   2  58   2   4]
- [  5   2   5   0   1  44   1]
- [ 12   1  13   8   7  17  78]]
-Node Classification on random seed  9304 -> 0.598
-Confusion Matrix:
- [[ 76   5   2   2   2  15   8]
- [  3 119   9   2   5   6   7]
- [ 20  18 129  43  52  18  40]
- [  8   9  10  84  19   6   8]
- [  0   8   2   1  55   1   2]
- [  8   0   5   5   1  50   5]
- [ 11   4  11   4  10   7  85]]
-Node Classification on random seed  9305 -> 0.614
-Confusion Matrix:
- [[ 70   3  11   2   3   5  11]
- [  3 108  12   3   7   0   3]
- [ 23  13 158  35  37  20  38]
- [  9   4  14 103  11   4   7]
- [  3  13   5   1  59   3   1]
- [  1   2   2   4   6  38  11]
- [ 14   3  12   7   9  11  78]]
-Node Classification on random seed  9306 -> 0.592
-Confusion Matrix:
- [[ 69   2   6   1   3  18   5]
- [  9 139   4  11   5   1   6]
- [ 41  21 130  40  22  21  42]
- [ 24   3  16  84   2   5  15]
- [  1   6   1   6  58   0   7]
- [  4   1   5   0   0  38   4]
- [ 14   3   6   8   4  15  74]]
-Node Classification on random seed  9307 -> 0.608
-Confusion Matrix:
- [[ 58  11   4  14   8   5   8]
- [ 10 124   4   2  13   0   1]
- [ 39  15 166  14  31  18  27]
- [ 10   5  18  99   4   5  19]
- [  0   7   4   1  56   1   2]
- [ 11   2   3   3   0  47   4]
- [ 17   1  19  13   5  14  58]]
-Node Classification on random seed  9308 -> 0.595
-Confusion Matrix:
- [[ 68   2   8   5   4   2  22]
- [ 11 130   9   1   0   0   9]
- [ 42  23 135  58   8  13  34]
- [ 17   1  12  97   3   3  14]
- [  4   8   6   0  51   0   0]
- [  8   3   3   2   0  34  13]
- [ 27   6   6   5   9   4  80]]
-Node Classification on random seed  9309 -> 0.609
-Confusion Matrix:
- [[ 69   3   1   2   5   9   9]
- [  3 136   3   2  15   2   2]
- [ 22  22 112  38  32  17  42]
- [ 22   4  21  84  11   7  25]
- [  0   3   3   0  68   0   4]
- [  1   2   6   1   1  45   9]
- [ 12   3   3   9   4  11  95]]
-Node Classification on random seed  9310 -> 0.63
-Confusion Matrix:
- [[ 85   0   4   4   6  14   8]
- [  1 128   6   2  12   3   6]
- [ 26  35 151  18  28  23  44]
- [  7   5  16  94   3   7  20]
- [  0   5   5   1  62   3   2]
- [  3   2   2   4   0  43   5]
- [ 11   5   6   4   6   8  67]]
-Node Classification on random seed  9311 -> 0.605
-Confusion Matrix:
- [[ 73   2   6   8   5   8   6]
- [  2 125   6   2  18   2   4]
- [ 26  21 147  34  26  25  38]
- [ 10   5  23  90   7   9   6]
- [  0   1   5   2  54   1   3]
- [  9   1   3   0   1  45   2]
- [ 14   3  10  10   9  22  71]]
-Node Classification on random seed  9312 -> 0.63
-Confusion Matrix:
- [[ 76   2   2   2   3  15   8]
- [  1 130   4   3   8   4   0]
- [ 27  25 126  56  16  25  35]
- [ 10   4   7 123   4  12   5]
- [  0   4   4   3  60   2   3]
- [  7   1   6   0   2  45   5]
- [ 10   3  10   9   6  17  70]]
-Node Classification on random seed  9313 -> 0.604
-Confusion Matrix:
- [[ 82   1   7   7   2   9   8]
- [  2 116   4   4  13   3   2]
- [ 29  33 143  27  33  23  37]
- [ 16   2  26  83   4   4  24]
- [  1   6   2   2  56   0   3]
- [  3   0   6   0   2  45   3]
- [ 10   2   8   9  10   9  79]]
-Node Classification on random seed  9314 -> 0.602
-Confusion Matrix:
- [[ 69   1   6   8   0  18   9]
- [  1 124   5   1   9   4   2]
- [ 18  30 136  31  46  33  30]
- [ 11   2  19 106   6  12   8]
- [  0   4   7   0  58   0   2]
- [  5   2   2   2   2  42  10]
- [  4   4   8  17   6  13  67]]
-Node Classification on random seed  9315 -> 0.617
-Confusion Matrix:
- [[ 73   7   1   3   3  14   8]
- [ 10 125   9   0   1   2  10]
- [ 19  27 152  22  12  35  35]
- [  4   7  19 100   4   8  15]
- [  7   7   9   0  50   1   1]
- [ 13   1   0   0   0  46   5]
- [ 19   9   9   3   4  20  71]]
-Node Classification on random seed  9316 -> 0.63
-Confusion Matrix:
- [[ 63   5   6   8   5  19  10]
- [  2 121   7   0   8   2   5]
- [ 12  27 138  39  37  33  41]
- [ 12   3   8 114   0   0  15]
- [  3   7   3   1  59   0   2]
- [  6   0   3   0   0  45   1]
- [  8   3  11   5   4   9  90]]
-Node Classification on random seed  9317 -> 0.64
-Confusion Matrix:
- [[ 83   2   4   7   9   7   7]
- [  4 130  10   7  16   0   1]
- [ 22  21 137  41  28   7  41]
- [ 24   3  11  90   3   5   8]
- [  0   5   4   1  64   1   2]
- [  5   2   1   1   2  52   9]
- [ 11   0  14   9   2   3  84]]
-Node Classification on random seed  9318 -> 0.674
-Confusion Matrix:
- [[ 79   4   3   2   5   8   8]
- [  1 127   7   0   8   1   5]
- [ 17  24 189  15  12  22  40]
- [ 20  10  22  84   2   3  19]
- [  1   3   1   0  57   1   3]
- [  8   2   0   0   0  52   5]
- [ 12   3   8   4   5  12  86]]
-Node Classification on random seed  9319 -> 0.601
-Confusion Matrix:
- [[ 63   2   9  12   3  10   5]
- [  4 122   5   7  21   6   3]
- [ 13  14 131  44  38  19  38]
- [  9   6  19  99   2   4  20]
- [  4   2   5   1  64   6   3]
- [  5   0   5   4   1  46   3]
- [ 10   5   5   6  10  11  76]]
-Node Classification on random seed  9320 -> 0.641
-Confusion Matrix:
- [[ 76   0   9   7   5  12   1]
- [  6 129   9   0   4   2   3]
- [ 23  15 157  28  20  21  43]
- [ 16   6  13 118   1   3  17]
- [  1   7  12   4  55   1   1]
- [  9   1   1   4   2  40   3]
- [  9   3  11  10   4  12  66]]
-Node Classification on random seed  9321 -> 0.584
-Confusion Matrix:
- [[ 65   6   8   7   8   8   8]
- [  5 121  10   2   2   0  11]
- [ 37  29 144  28  12  25  27]
- [ 17   1  16 106   1  10  19]
- [  0   5   3   1  57   1   4]
- [ 15   0   4   0   3  35   5]
- [ 13   5  15   9   5  31  56]]
-Node Classification on random seed  9322 -> 0.593
-Confusion Matrix:
- [[ 86   9   3   0   3   6  10]
- [  1 113   3   2   5   1   9]
- [ 25  21 126  47  26  33  37]
- [ 13   5  11  94   3  11  28]
- [  1   3   6   5  56   1   5]
- [  2   2   2   1   0  34  13]
- [ 13   1   9  12   5  14  84]]
-Node Classification on random seed  9323 -> 0.649
-Confusion Matrix:
- [[ 79   1   0   8   1  17   4]
- [  3 135   3   3   8   1   3]
- [ 32  20 158  22  30  18  35]
- [  5   5  34  93   8   8   7]
- [  8   4   3   3  63   2   2]
- [  5   2   1   1   0  41   3]
- [ 12   7   5   1   6  10  80]]
-Node Classification on random seed  9324 -> 0.578
-Confusion Matrix:
- [[ 51   3   9   5   4  21  17]
- [  7 135   4   1   3   3  10]
- [ 27  20 116  28  39  35  42]
- [  4   9  12 111   4   3  21]
- [  0  13   5   2  41   1   4]
- [  4   1   1   1   1  48   4]
- [  7   5   8   8   8  18  76]]
-Node Classification on random seed  9325 -> 0.623
-Confusion Matrix:
- [[ 71   3   4   4   1  10   8]
- [  2 117   9   3   5   5   1]
- [ 34  12 170  24  16  27  50]
- [  6   2  14  98   2  13  17]
- [  4   5   5   1  59   0   1]
- [  6   1   2   1   1  45  12]
- [ 17   6   9  13   5  16  63]]
-Node Classification on random seed  9326 -> 0.6
-Confusion Matrix:
- [[ 58   3   9   8   6  16   5]
- [  4 139   8   8   2   3   5]
- [ 23  26 132  41  27  25  37]
- [ 12   2  13 113   5   9   9]
- [  1   9   3   1  54   1   4]
- [  5   2   2   5   1  37   1]
- [  9   3  15  14   7  11  67]]
-Node Classification on random seed  9327 -> 0.591
-Confusion Matrix:
- [[ 63   2  13   2   4   6   6]
- [  1 115  13   7   9   1   2]
- [ 18  33 137  33  23  22  64]
- [  9   6  12 100   3   6  25]
- [  0   6   6   4  59   2   0]
- [  1   0   3   2   0  43   7]
- [  5   4  17   6  10  16  74]]
-Node Classification on random seed  9328 -> 0.611
-Confusion Matrix:
- [[ 67   2   4   8   3  16   6]
- [  9 130   5   6   9   0   5]
- [ 17  18 148  28  39  30  24]
- [  9   3  20 102   2   8  12]
- [  2   8   4   0  55   0   3]
- [  3   1   3   5   2  39   6]
- [ 15   4  11   9   9  21  70]]
-Node Classification on random seed  9329 -> 0.652
-Confusion Matrix:
- [[ 91   3   2   4   3  14   2]
- [  3 106   7   4   9   0   4]
- [ 24  18 153  34  27  27  24]
- [  9   7  14 112   9   7  10]
- [  2   3   5   0  70   1   5]
- [  2   2   1   4   0  55   1]
- [  6   9   6   9   8  19  65]]
-Node Classification on random seed  9330 -> 0.626
-Confusion Matrix:
- [[ 66   0  11   7   4   7  18]
- [ 12 129   4   1  10   4   3]
- [ 25  25 136  13  25  25  41]
- [  9   1  17 110   5   3  11]
- [  4   4   7   0  64   1   2]
- [ 12   1   2   1   3  49   3]
- [ 22   2   6   2   9  12  72]]
-Node Classification on random seed  9331 -> 0.624
-Confusion Matrix:
- [[ 78   2   7   8   5   9   8]
- [  6 117   5   2  23   1   0]
- [ 21  14 157  26  28  19  37]
- [ 10   9  10  96   5   5  12]
- [  1   3   3   1  71   3   2]
- [ 10   0   1   1   2  45   5]
- [ 11   1  10  26   5  19  60]]
-Node Classification on random seed  9332 -> 0.595
-Confusion Matrix:
- [[ 73   1   2   7   4  13   4]
- [  3 119   2   0  15   0   3]
- [ 30  17 138  27  26  34  46]
- [ 22   4  19  99   7   4  10]
- [  2   2   9   1  62   1   4]
- [  6   1   2   0   0  43   5]
- [ 30   0  15  10   6  11  61]]
-Node Classification on random seed  9333 -> 0.59
-Confusion Matrix:
- [[ 57   1   2   3   7   7  18]
- [  3 124   7   4  10   0   5]
- [ 25  17 147  26  28  44  45]
- [ 22   1  19 107   6   7   7]
- [  1   5   5   0  56   0   2]
- [  6   1   9   2   1  37   6]
- [ 10   2   6   5  15  20  62]]
-Node Classification on random seed  9334 -> 0.594
-Confusion Matrix:
- [[ 68   2   7   5   3  18   3]
- [  4 117   3   2  11   6   8]
- [ 30  18 146  48  10  25  27]
- [ 12   7  22  97   5   9  11]
- [  0  11   3   4  56   1   4]
- [  8   1   5   1   2  45   2]
- [ 17   3  15  10   1  22  65]]
-Node Classification on random seed  9335 -> 0.655
-Confusion Matrix:
- [[ 54   5   6   2   6  16  14]
- [  1 117  14   2  10   2   6]
- [  9  14 191  24  16  26  43]
- [ 12   5  11 105   4   9  18]
- [  2   4   5   1  69   1   3]
- [  8   3   5   0   2  34   4]
- [ 14   4   4   0   4   6  85]]
-Node Classification on random seed  9336 -> 0.616
-Confusion Matrix:
- [[ 75   2   5   7   2   7   7]
- [  3 125  13   0   8   3   2]
- [ 32  15 119  29  40  32  45]
- [ 10   3   7 130   7   1  10]
- [  1   5   4   1  57   1   3]
- [  6   2   4   1   5  41   3]
- [ 11   0  10  13   5  19  69]]
-Node Classification on random seed  9337 -> 0.641
-Confusion Matrix:
- [[ 82   1   5   4   3  11   3]
- [  2 124   6   3   6   2   0]
- [ 22  30 157  30  28  16  42]
- [ 16   3  21 104   7   4  13]
- [  1   5   3   3  53   3   2]
- [  4   1   2   2   3  49   4]
- [ 16   1  12   0   5  14  72]]
-Node Classification on random seed  9338 -> 0.594
-Confusion Matrix:
- [[ 69   2   1   6   2  10  23]
- [  1 120   5   3  15   2   7]
- [ 28  53 128  27  16  22  30]
- [ 14  11  15 101   7   5   8]
- [  3   6   9   1  47   0   0]
- [  4   6   4   2   0  44   6]
- [  3   4  15   5   8  17  85]]
-Node Classification on random seed  9339 -> 0.656
-Confusion Matrix:
- [[ 89   2   4   1   4   7   2]
- [  5 130   1   7   4   1   6]
- [ 25  25 154  39  17  17  39]
- [ 13   3  11  99  12   6   5]
- [  2   9   3   0  54   0   5]
- [  5   5   0   6   0  47   2]
- [ 13   7   8   9   2  12  83]]
-Node Classification on random seed  9340 -> 0.606
-Confusion Matrix:
- [[ 65   3   1   3   9  10  12]
- [  3 123  10   0  11   3   5]
- [ 25  22 144  28  21  35  54]
- [ 17   5  16  98   3  12   8]
- [  1   3   7   0  70   0   2]
- [  5   6   1   0   2  29   6]
- [  8   5   8   3   8  13  77]]
-Node Classification on random seed  9341 -> 0.622
-Confusion Matrix:
- [[ 55   0   2  10   2  19  15]
- [  1 137   6   2   5   4   3]
- [ 28  29 122  33  27  25  43]
- [  9   2  11 129   0   7   8]
- [  0  10   5   2  52   2   1]
- [  2   1   6   1   0  46   4]
- [ 13   5  14   7   4  10  81]]
-Node Classification on random seed  9342 -> 0.621
-Confusion Matrix:
- [[ 69   2   3   9   5  12  11]
- [  9 140   6   3   2   2   1]
- [ 32  21 132  40  20  18  44]
- [ 12   2  18  91   0   1  14]
- [  0   8   6   2  53   3   2]
- [  8   3   1   0   1  59   1]
- [ 15   3   5  10   4  20  77]]
-Node Classification on random seed  9343 -> 0.651
-Confusion Matrix:
- [[ 81   2   7   5   2  15   1]
- [  3 140   2   2   7   2   5]
- [ 24  16 167  36  16  30  33]
- [ 10   3  20  97   5   9  12]
- [  0   4   4   5  47   1   2]
- [  4   2   4   6   1  45   3]
- [ 13   3   6   2   6  16  74]]
-Node Classification on random seed  9344 -> 0.612
-Confusion Matrix:
- [[ 67   1   8   7   5   9   5]
- [  9 111  10   2  10   1   7]
- [ 47  22 143  22  33  21  30]
- [ 14   2   9 107   7   7  13]
- [  1   6   3   0  63   1   4]
- [  4   2   2   1   4  48   1]
- [ 16   6  11   5   7  13  73]]
-Node Classification on random seed  9345 -> 0.61
-Confusion Matrix:
- [[ 63   1   6   5   3  19  14]
- [  1 119   7   2   7   3   7]
- [ 22  20 153  31  30  26  33]
- [ 17   1  19 103   4   7  14]
- [  1   5   3   2  53   0   3]
- [  7   2  14   1   0  41   0]
- [  9   3  15   3   7  16  78]]
-Node Classification on random seed  9346 -> 0.612
-Confusion Matrix:
- [[ 79  11   1   2   8   4   9]
- [  2 134   7   2   5   0   3]
- [ 32  23 114  66  25  19  38]
- [  8   6  16 104   2   6  11]
- [  2   4   2   0  66   0   1]
- [  2   1   4   4   3  42   9]
- [ 19   5  10   3   5   8  73]]
-Node Classification on random seed  9347 -> 0.597
-Confusion Matrix:
- [[ 63   3   4   4   6   8  10]
- [  6 136   4   1  20   0   7]
- [ 37  21 122  18  35  15  53]
- [  8   1  25  95   5   3   9]
- [  3   6   9   3  68   1   3]
- [ 11   2   3   2   2  35   4]
- [  9   3  16   5   9   9  78]]
-Node Classification on random seed  9348 -> 0.606
-Confusion Matrix:
- [[ 61   5   5   9   3   9  14]
- [  6 117   6   0   8   3   5]
- [ 18  32 147  29  21  23  47]
- [ 13   3   9 112   2  10   7]
- [  4   9   3   1  52   1   6]
- [  5   3   6   1   0  44   9]
- [ 13   5   5  10  12  14  73]]
-Node Classification on random seed  9349 -> 0.632
-Confusion Matrix:
- [[ 68   1   3   3   5  18   7]
- [  5 118   6   3   3   3   4]
- [ 14  18 177  29  21  22  52]
- [ 10   4  16  93   8   6  23]
- [  3   5   3   2  50   2   4]
- [  9   0   1   0   1  44   4]
- [  9   0   6   6   7  22  82]]
-Node Classification on random seed  9350 -> 0.657
-Confusion Matrix:
- [[ 80   0   1   7   6   6   9]
- [  2 130   7   5   5   3   4]
- [ 17  24 171  29  24  14  35]
- [ 17   5  25  96   4   0  10]
- [  1   8   3   1  64   0   4]
- [  2   3   3   4   2  41   7]
- [  9   4   4  10   8  11  75]]
-Node Classification on random seed  9351 -> 0.549
-Confusion Matrix:
- [[ 70   2   8  10   2  10  12]
- [  4 128   2   3   9   2   0]
- [ 35  21 106  36  32  24  55]
- [ 18   3  36  64  15  10  16]
- [  2   5   0   1  69   1   3]
- [ 11   0   2   1   4  44   0]
- [ 13   2  14   6  10  11  68]]
-Node Classification on random seed  9352 -> 0.555
-Confusion Matrix:
- [[ 67   3  10   7   3  10   8]
- [ 15 131   5   0   2   3   8]
- [ 38  19 109  33  54  22  48]
- [  6   1  16  99   3   7  19]
- [  2   4   3   1  59   0   4]
- [  2   1   1   3   1  43   8]
- [  5   2  18   6  36   8  47]]
-Node Classification on random seed  9353 -> 0.633
-Confusion Matrix:
- [[ 66   2   6   7   6  12  10]
- [  7 118  13   2   3   5   3]
- [ 21  19 152  21  27  16  51]
- [  3   5  23 118   6   6   8]
- [  0   5   4   2  53   3   1]
- [ 11   0   5   2   1  44   4]
- [ 11   3   9   9   5  10  82]]
-Node Classification on random seed  9354 -> 0.632
-Confusion Matrix:
- [[ 81   0   0  12   0   6  12]
- [ 11 121   3   6   8   2   5]
- [ 20  10 154  33  28  13  45]
- [  2   2  20 114   6   5  26]
- [  1  10   2   1  51   2   1]
- [  3   0   0   1   4  39   5]
- [ 12   5  12   6   6  22  72]]
-Node Classification on random seed  9355 -> 0.615
-Confusion Matrix:
- [[ 73   5   6   5   4  12  12]
- [  2 120  11   2   7   2  10]
- [ 24  20 147  34  13  23  47]
- [  9   2  14 106   8   3  12]
- [  0   6   7   1  62   0   2]
- [  2   2   5   1   1  46  15]
- [ 23   0  12   7   2  12  61]]
-Node Classification on random seed  9356 -> 0.627
-Confusion Matrix:
- [[ 79   5   6  10   3   4  15]
- [  2 122   8   5   6   1   3]
- [ 38  20 135  34  17  16  41]
- [ 23   2  24  97   2   4  18]
- [  0   3   4   1  52   0   0]
- [  2   3   2   5   1  52   5]
- [  7   4  12   5   3   9  90]]
-Node Classification on random seed  9357 -> 0.624
-Confusion Matrix:
- [[ 73   1   2   3   8  10   6]
- [  5 121   5   1  17   3   0]
- [ 30  13 137  50  14  28  25]
- [  7   2  29 104  11   1  10]
- [  2   9   4   2  66   0   1]
- [  5   1   4   8   0  46   2]
- [ 14   5  12   7   7  12  77]]
-Node Classification on random seed  9358 -> 0.598
-Confusion Matrix:
- [[ 53   2   2   5   3  24  16]
- [  7 126   9   6   9   0   5]
- [ 16  17 117  50  27  25  35]
- [  5   1  15 109  10   2  27]
- [  0   6   6   0  58   1   4]
- [  4   1   3   1   1  52   3]
- [ 12   3  16   5   5  13  83]]
-Node Classification on random seed  9359 -> 0.633
-Confusion Matrix:
- [[ 75   4   3   6   2  11  16]
- [  4 120   7   4   6   5   2]
- [ 14  23 142  46  30  16  46]
- [ 15   0  11 128   2   4   5]
- [  0   6   2   7  55   1   5]
- [  9   1   2   2   2  40  10]
- [  6   4   4   5   9  10  73]]
-Node Classification on random seed  9360 -> 0.624
-Confusion Matrix:
- [[ 62   2   6   5   4   9  22]
- [  0 129   1   2  11   2   6]
- [ 21  23 141  49  21  26  34]
- [  5   7  14 108   4   5  14]
- [  0   4   6   0  60   7   3]
- [  4   0   1   3   6  49   6]
- [  8   2  10   6   5  12  75]]
-Node Classification on random seed  9361 -> 0.625
-Confusion Matrix:
- [[ 59   1   3   5   3  12   6]
- [  6 132   9   4  12   1   1]
- [ 23  17 139  35  27  19  30]
- [ 10  10  19 114   7   6  13]
- [  2   5   7   1  58   2   2]
- [  7   3   1   0   0  46   5]
- [ 15   5  11   6   9  15  77]]
-Node Classification on random seed  9362 -> 0.596
-Confusion Matrix:
- [[ 71   7   5   5   5  15   6]
- [ 12 121   7   1   3   5   7]
- [ 23  18 127  25  39  28  49]
- [ 15   3  21  85   1   6  10]
- [  2   2   3   0  68   0   3]
- [  7   2   6   6   2  42   7]
- [ 19   2   9   4   6   8  82]]
-Node Classification on random seed  9363 -> 0.63
-Confusion Matrix:
- [[ 72   1   0   2   4  15   2]
- [  1 129   2   2   4   2   2]
- [ 17  23 154  40  30  28  29]
- [ 14   4  19  99   1   4  19]
- [  0   9   4   4  61   1   2]
- [  4   1   1   5   0  40   5]
- [ 14   6   9   9   6  25  75]]
-Node Classification on random seed  9364 -> 0.638
-Confusion Matrix:
- [[ 77   4   7   4   1   8  15]
- [  6 132   9   0   6   3   3]
- [ 20  18 149  31  33  17  29]
- [  7   3  19 102   9   7   9]
- [  2   2   5   1  58   3   4]
- [ 13   0   4   0   0  43   5]
- [ 19   6  11  10   0   9  77]]
-Node Classification on random seed  9365 -> 0.621
-Confusion Matrix:
- [[ 68   9   2   4   6  21   3]
- [  5 135   3   2   7   7   2]
- [ 24  12 120  39  41  26  36]
- [  4   5  15 102   5   5  17]
- [  0   3   4   0  74   1   2]
- [  4   2   5   1   1  42  11]
- [  7   1   7   4   6  20  80]]
-Node Classification on random seed  9366 -> 0.577
-Confusion Matrix:
- [[ 62   5   3   3   3  15  12]
- [  7 111   4   4  14   8   2]
- [ 29  15 127  31  38  16  47]
- [ 18   7  11  97   9   2   5]
- [  3  14   3   1  70   2   5]
- [  8   2   1   4   1  39   5]
- [ 21   3   6  19   4  13  71]]
-Node Classification on random seed  9367 -> 0.61
-Confusion Matrix:
- [[ 70   1   7   5   2  16  15]
- [  9 115   7   0   5   2   6]
- [ 28  21 155  26  24  24  34]
- [ 13   1  13  89   7  15  21]
- [  0   6   6   1  52   2   6]
- [  3   3   7   0   1  48   9]
- [  5   4   9   8   5  13  81]]
-Node Classification on random seed  9368 -> 0.634
-Confusion Matrix:
- [[ 59   5   2  13   1  12  16]
- [  0 127  14   0   9   4   5]
- [ 26  28 146  28  14  13  47]
- [ 13   4  11 113   1   2  13]
- [  1   2   3   2  66   0   5]
- [  4   3   3   1   0  47   1]
- [ 15   5   5   5   9  21  76]]
-Node Classification on random seed  9369 -> 0.63
-Confusion Matrix:
- [[ 69   1   4   2   6  16  14]
- [  6 117   4   1  14   4   5]
- [ 24  13 151  42  22  23  33]
- [ 18   3  11 108   2   7  14]
- [  1   5   1   4  64   2   5]
- [  4   1   0   0   1  41   8]
- [ 10   0   7   2   8  22  80]]
-Node Classification on random seed  9370 -> 0.645
-Confusion Matrix:
- [[ 80   3   4   3   5   6  12]
- [  3 142   4   4   3   0   2]
- [ 26  21 141  28  23  18  31]
- [ 20   3  15  99   8   7  11]
- [  2   6   8   3  50   3   4]
- [  7   0   1   1   2  50   7]
- [ 18   4   6   9   6   8  83]]
-Node Classification on random seed  9371 -> 0.644
-Confusion Matrix:
- [[ 64   4   2   2   5   6  17]
- [  4 123   0   6   3   2  11]
- [ 21  16 159  22  22  28  56]
- [ 14   2  14 100   2   2  24]
- [  0   4   3   0  71   1   5]
- [  6   1   2   8   0  47   5]
- [  4   5   9   7   3   8  80]]
-Node Classification on random seed  9372 -> 0.595
-Confusion Matrix:
- [[ 51   3  18   4   6  18  14]
- [ 14 124   5   6   6   5   1]
- [ 15  22 127  42  44  25  27]
- [ 12   5  10 121   4  11  11]
- [  1   5   1   2  53   1   4]
- [  6   0   1   0   0  52   9]
- [  5   6   8   9   8  11  67]]
-Node Classification on random seed  9373 -> 0.612
-Confusion Matrix:
- [[ 46   6   4   3   2  10  18]
- [  3 137  10   6   3   1   1]
- [ 19  33 141  42  30  25  37]
- [  5   3  25 105   1   8  15]
- [  1   9   0   4  58   1   2]
- [  2   1   4   2   0  47   9]
- [  2   5   3   6  12  15  78]]
-Node Classification on random seed  9374 -> 0.613
-Confusion Matrix:
- [[ 71   1   1   6   3  19  13]
- [  4 142   6   1   7   1   6]
- [ 21  35 118  28  39  32  32]
- [  6   5  14 110   5   5  10]
- [  3   4   2   2  59   0   1]
- [  5   0   4   4   0  41   6]
- [  9   4   7  13   6  17  72]]
-Node Classification on random seed  9375 -> 0.634
-Confusion Matrix:
- [[ 60   2   3   4   3  33  13]
- [  1 138  11   2   4   8   2]
- [ 21  17 145  27  25  29  34]
- [  6   4  16 102   6  14  10]
- [  1   6   2   1  59   3   0]
- [  5   0   0   3   1  46   4]
- [  8   4   4   8   5  16  84]]
-Node Classification on random seed  9376 -> 0.613
-Confusion Matrix:
- [[ 64   2   5   4   6  17   7]
- [  6 139   5   2  15   0   4]
- [ 17  26 145  36  18  14  46]
- [ 10   3  11 125   1   6  16]
- [  0   8   6   2  49   1   1]
- [  3   0   5   7   2  28   5]
- [ 14   3  17   9  23   4  63]]
-Node Classification on random seed  9377 -> 0.583
-Confusion Matrix:
- [[ 60   1   9   7   8   8  15]
- [  5 110   7   6  17   2   5]
- [ 17  20 128  47  23  16  47]
- [  9   6  19 102   8   1  23]
- [  1   4   3   2  66   0   1]
- [  9   0   0   0   1  36   9]
- [ 14   3  10  12   2  20  81]]
-Node Classification on random seed  9378 -> 0.593
-Confusion Matrix:
- [[ 75   3  10  16   9   6   2]
- [  1 120  16   0  14   4   4]
- [ 30  23 137  24  22  22  49]
- [ 13   6   8  91  10   6  17]
- [  1   6   9   0  63   0   0]
- [  8   0   2   7   0  43   2]
- [ 17   2  11   3   9  15  64]]
-Node Classification on random seed  9379 -> 0.585
-Confusion Matrix:
- [[ 61   6   8   7   4   8   5]
- [  9 132   5   3   3   6   4]
- [  7  39 105  52  20  24  40]
- [ 12   8  24  91  11  13  19]
- [  1   5   1   0  73   4   2]
- [  1   0   3   4   0  51   4]
- [ 19   1   4  12   5  12  72]]
-Node Classification on random seed  9380 -> 0.682
-Confusion Matrix:
- [[ 65   9   2   7   3   5  15]
- [  6 152   6   1   3   3   0]
- [ 16  16 162  23  19  19  37]
- [ 19   4  10  97   4   0  18]
- [  0  10   6   0  64   1   1]
- [  6   3   2   3   0  55   8]
- [  6   2   6   6   7   6  87]]
-Node Classification on random seed  9381 -> 0.639
-Confusion Matrix:
- [[ 56   2   2   7   6  16  16]
- [  3 133   2   0  12   2   5]
- [ 15  21 184  18  26  26  30]
- [ 11   7  18  95   8   6  10]
- [  0   2   2   4  56   2   4]
- [  7   0   4   1   0  44   7]
- [ 15   2   7   5  16  14  71]]
-Node Classification on random seed  9382 -> 0.609
-Confusion Matrix:
- [[ 66   1   2   9   6  21   9]
- [  3 123   6   3   5   1   9]
- [ 17  23 157  43  21  37  25]
- [  8   3  15  85  11   8  10]
- [  0   4   5   2  67   5   3]
- [  4   2   2   1   0  47   8]
- [  9   3  12   8   6  21  64]]
-Node Classification on random seed  9383 -> 0.604
-Confusion Matrix:
- [[ 79   0   5   3   2  24   4]
- [  7 119   4   3  14   2   3]
- [ 34  23 140  38  13  23  35]
- [  9   4  18  94   4   8  18]
- [  0   5   4   0  59   0   1]
- [  2   1   5   6   0  30  18]
- [ 13   5   4   4  13  17  83]]
-Node Classification on random seed  9384 -> 0.571
-Confusion Matrix:
- [[ 66   4   4   2   1  14  12]
- [  8 134   2   6  11   2   0]
- [ 15  23 134  42  38  29  40]
- [  7   3  18  92  17  12  16]
- [  3  11   6   1  48   1   2]
- [  6   0   1   0   2  46   2]
- [  7   2   9  18   8  24  51]]
-Node Classification on random seed  9385 -> 0.608
-Confusion Matrix:
- [[ 79   4   3   5   4   7  15]
- [  3 123   8   3   2   3   1]
- [ 17  11 121  50  39  22  44]
- [ 11   3   7 103   5  10  12]
- [  0   2   2   9  56   0   3]
- [  8   1   5   4   0  43   7]
- [ 12   7  17  11   7   8  83]]
-Node Classification on random seed  9386 -> 0.572
-Confusion Matrix:
- [[ 52   0  18   7   5  20   8]
- [  6 117   9   3   7   5   7]
- [ 23  16 127  20  60  36  27]
- [  5   6  15  84  12  14  11]
- [  2   2   4   2  64   1   1]
- [  6   1   2   3   1  49   6]
- [  9   1   4   6  12  25  79]]
-Node Classification on random seed  9387 -> 0.641
-Confusion Matrix:
- [[ 75   3  15   8   1  14   1]
- [  6 122   9   1  10  10   4]
- [ 26  16 159  29  28  23  28]
- [ 10   1  16 106   2   6  12]
- [  1   4   3   0  61   1   3]
- [  2   0   3   2   0  46   3]
- [  6   3  19   7   5  18  72]]
-Node Classification on random seed  9388 -> 0.635
-Confusion Matrix:
- [[ 84   4   2   4   2   9   4]
- [  6 141   3   8   2   3   2]
- [ 26  17 146  47  25  20  28]
- [  6   6  17  91  14   6  20]
- [  3   5   0   1  61   3   1]
- [ 11   2   3   2   0  53   5]
- [  8   4  10   4   5  17  59]]
-Node Classification on random seed  9389 -> 0.632
-Confusion Matrix:
- [[ 67   0  12   4   4  11   4]
- [  4 139  12   0   6   6   4]
- [ 15  17 158  35  30  19  37]
- [ 22   4  13  98   4   8   7]
- [  1   7   2   4  56   2   2]
- [  9   1   1   0   2  43   3]
- [  6   5  12   9   7  17  71]]
-Node Classification on random seed  9390 -> 0.626
-Confusion Matrix:
- [[ 56   6   6   2   5  19   9]
- [  3 147   6   0   1   1   1]
- [ 21  17 155  31  18  29  59]
- [  6   6  25  92   0  12   5]
- [  2   4   9   2  49   0   3]
- [  8   2   2   2   1  45   6]
- [  9   4   8   2   7  15  82]]
-Node Classification on random seed  9391 -> 0.555
-Confusion Matrix:
- [[ 48   2   5   6   7  14  18]
- [  5 121  16   6   8   4  10]
- [ 21  15 142  16  38  43  48]
- [ 23   5  18  82   5  17   6]
- [  0   1   2   3  57   2   1]
- [  5   0   3   1   3  35   5]
- [ 14   4   8   2   9  26  70]]
-Node Classification on random seed  9392 -> 0.578
-Confusion Matrix:
- [[ 72   0   8   3  10  12   7]
- [  6 114   3   4   6   6   4]
- [ 39  12 128  39  45  18  59]
- [ 19   9   9  91   4   4  15]
- [  1   4   5   0  64   1   5]
- [  4   1   0   5   0  40   6]
- [ 12   5   7   9  13   3  69]]
-Node Classification on random seed  9393 -> 0.609
-Confusion Matrix:
- [[ 68   0   5  10   6  14  14]
- [  4 109  13   7  14   1   6]
- [ 19  13 149  35  40  18  43]
- [  9   5  15  81   9   7   7]
- [  1   2   2   0  72   0   4]
- [  1   2   2   1   3  46  11]
- [  6   1  10   7   9  15  84]]
-Node Classification on random seed  9394 -> 0.587
-Confusion Matrix:
- [[ 69   3   4  12   4  14  11]
- [  4 150   5   2   6   0   6]
- [ 28  26 126  42  14  20  35]
- [  6   5  20  89  17  12  15]
- [  3  13   5   0  47   4   1]
- [  6   4   4   0   2  40   2]
- [ 23   6   2   1   9  17  66]]
-Node Classification on random seed  9395 -> 0.581
-Confusion Matrix:
- [[ 68   2   2   4   2   6  21]
- [ 10 117   6   6  11   2   3]
- [ 40  11 120  59  27  20  42]
- [  8   5  14 106   4   6  11]
- [  0   1   4   2  59   0   3]
- [  8   1   3   1   2  31   7]
- [ 14   1   5  16  11  18  80]]
-Node Classification on random seed  9396 -> 0.649
-Confusion Matrix:
- [[ 66   2   4  10   7  11  14]
- [ 12 124  10   8   9   2   4]
- [ 19  26 143  30  33  15  22]
- [  5   1  14 128  13   2  12]
- [  2  10   1   1  64   2   2]
- [  5   0   2   1   1  46   3]
- [  9   2   4   7   4  10  78]]
-Node Classification on random seed  9397 -> 0.624
-Confusion Matrix:
- [[ 77   1  10   6   2   9   8]
- [  2 131   1   5   4   2   3]
- [ 35  26 129  40  20  26  39]
- [ 19   5  13  96   1   6  17]
- [  1   8   4   1  62   2   1]
- [  5   4   0   3   0  50   6]
- [ 10   2   4   3   4  18  79]]
-Node Classification on random seed  9398 -> 0.613
-Confusion Matrix:
- [[ 61   1   9   4   3  15  14]
- [  5 113   7   4  10   4   3]
- [ 26  29 145  23  15  28  44]
- [  7   4  16 109   5   7  11]
- [  1   7   5   0  63   0   1]
- [  0   1   5   2   0  52   3]
- [  7   4  15   7  19  16  70]]
-Node Classification on random seed  9399 -> 0.601
-Confusion Matrix:
- [[ 68  12   1   6   2  14   8]
- [  0 126   4   6  10   5   3]
- [ 24  18 137  39  31  33  40]
- [ 12   5   9 101   6   5  22]
- [  3   7   2   0  57   0   2]
- [  3   1   2   0   2  39   8]
- [  9   3  14   5   6  17  73]]
-Node Classification on random seed  9400 -> 0.545
-Confusion Matrix:
- [[ 68   1   2   8   4   4  10]
- [  6 125   2   3   7   0   6]
- [ 31  20  83  22  37  35  75]
- [ 19   7  13  89  10   7  25]
- [  2   8   2   2  56   2   4]
- [  9   1   3   6   1  36   6]
- [ 14   6   8  11   4  12  88]]
-Node Classification on random seed  9401 -> 0.633
-Confusion Matrix:
- [[ 80   2   3   7   4   9  13]
- [  2 119   6   3  15   3   0]
- [ 19  21 155  53  20  29  31]
- [ 10   4   2 104  11   7   8]
- [  0   7   7   1  59   2   0]
- [  3   3   1   1   0  49   7]
- [ 15   4  11  11   2  10  67]]
-Node Classification on random seed  9402 -> 0.622
-Confusion Matrix:
- [[ 69   0   2   5   2  19   8]
- [  1 147   5   2  12   2   4]
- [ 21  16 125  21  29  33  47]
- [  8   3  17  97   7  13   7]
- [  3   4   9   2  59   0   2]
- [  5   0   1   2   1  49   2]
- [  9   5  12   2   9  26  76]]
-Node Classification on random seed  9403 -> 0.63
-Confusion Matrix:
- [[ 59   4   8  15  10  15   6]
- [  7 130   3   1   3   4   5]
- [ 29  14 174  32  26  12  21]
- [  7   5  21  92  11   3  18]
- [  0   7   5   2  72   0   1]
- [ 10   0   2   2   1  35   9]
- [ 11   3  12  10   7   8  68]]
-Node Classification on random seed  9404 -> 0.62
-Confusion Matrix:
- [[ 64   1  10   1   3  10  19]
- [  2 129  11   4   7   1   5]
- [ 18  24 134  29  44  11  39]
- [  8   2  18 102   5   5  10]
- [  2   5   3   3  59   1   3]
- [  7   1   6   3   0  39  11]
- [  5   1  13   9   9  11  93]]
-Node Classification on random seed  9405 -> 0.56
-Confusion Matrix:
- [[ 58   2   6   0   1  23  17]
- [  3 125   6   3  13   2   7]
- [ 31  18 149  49  22  22  30]
- [ 25   4  19  70   7   9  20]
- [  2   6   5   1  55   1   0]
- [  4   2   3   6   1  48   4]
- [  9   2  10  11  15  19  55]]
-Node Classification on random seed  9406 -> 0.605
-Confusion Matrix:
- [[ 49   4   9   3   3  25  18]
- [  0 122   4   2   2   7   0]
- [ 11  35 147  34  34  30  32]
- [  9   5  26 101   4   3  13]
- [  2  10   2   3  59   1   1]
- [  3   2   3   1   1  48   3]
- [ 14   3  14   3   5  11  79]]
-Node Classification on random seed  9407 -> 0.569
-Confusion Matrix:
- [[ 72   4   8   7   4  20   4]
- [  6 111  12   3   9   1   3]
- [ 18  45 120  38  22  35  33]
- [  8   6  18  97   9   5  17]
- [  0   3   5   3  50   2   2]
- [  5   0   6   6   1  46   5]
- [ 11   4  16   4  12  11  73]]
-Node Classification on random seed  9408 -> 0.623
-Confusion Matrix:
- [[ 63   0   5   3   4  15  20]
- [  9 142   4   3   7   3   0]
- [ 27  21 141  20  27  11  53]
- [ 16   9  17 115   6   5   9]
- [  1   7   3   0  57   0   2]
- [  6   6   0   0   0  35   9]
- [ 14   1   8   7  10   9  70]]
-Node Classification on random seed  9409 -> 0.61
-Confusion Matrix:
- [[ 79   3   9   2   3   9  10]
- [  5 119   3   2   5   1   4]
- [ 40  27 123  51  19  17  34]
- [  8   0   8 104   9   5  14]
- [  2  11   4   1  57   0   4]
- [  3   2   9   1   3  43   3]
- [  4   2  25   6   4  18  85]]
-Node Classification on random seed  9410 -> 0.604
-Confusion Matrix:
- [[ 69   2   3   5   6  11  14]
- [  3 120   7   3  11   8   6]
- [ 33  14 122  24  31  29  46]
- [ 18   3  19 111   7   3   8]
- [  1   4   5   1  61   1   6]
- [  8   3   0   1   0  47   5]
- [ 12   3  14   3   2  13  74]]
-Node Classification on random seed  9411 -> 0.644
-Confusion Matrix:
- [[ 78   5   2   6   4  12   6]
- [  3 102  12   3  19   3   4]
- [ 15   4 183  33  22  28  29]
- [ 12   0  16 107   1   6  10]
- [  0   6   4   1  67   1   6]
- [  9   2   3   4   0  40   6]
- [ 13   5  12  10   5  14  67]]
-Node Classification on random seed  9412 -> 0.632
-Confusion Matrix:
- [[ 77   3   6   9   6   9   8]
- [  2 141   2   3   5   3   4]
- [ 18  23 132  31  21  26  38]
- [ 24   7   9 111   8   3   6]
- [  2  10   3   3  61   0   2]
- [  4   1   6   1   3  35   5]
- [ 18   7   5  10   3  11  75]]
-Node Classification on random seed  9413 -> 0.634
-Confusion Matrix:
- [[ 72   0   4   2   3  14   6]
- [  6 125   6   1  11   4   8]
- [ 28  22 162  35  23  28  24]
- [  5   2  11  96  16   7  15]
- [  3   9   4   1  55   0   2]
- [  4   0   0   1   2  43   8]
- [ 10   1   6  17   5  12  81]]
-Node Classification on random seed  9414 -> 0.609
-Confusion Matrix:
- [[ 69   5   7  19   1   9   8]
- [  3 124   3   4   5   2   4]
- [ 28  26 150  45  20   8  35]
- [ 19   2  23  91   4   1  24]
- [  2   9   1   3  58   1   1]
- [  3   2   2   6   1  35   8]
- [ 12   4   5   5   8  13  82]]
-Node Classification on random seed  9415 -> 0.555
-Confusion Matrix:
- [[ 66   1   4  17   7   8  13]
- [  4 123   3   3   9  14   6]
- [ 41  11 125  23  23  36  46]
- [ 18   1  14  82   8   5  23]
- [  0   7   6   0  56   0   3]
- [  4   2   6   3   0  48   7]
- [ 12   3  14   7  17  16  55]]
-Node Classification on random seed  9416 -> 0.586
-Confusion Matrix:
- [[ 71   0   4   1   3   6  11]
- [  3 118   2   5  21   2  10]
- [ 23  18 120  47  39  19  52]
- [ 20   4  25  81   8   1  17]
- [  1   7   2   2  65   0   3]
- [  5   0   4   0   1  48   2]
- [  8   2   4  14  10   8  83]]
-Node Classification on random seed  9417 -> 0.609
-Confusion Matrix:
- [[ 86   7   8   2   6  12   2]
- [  3 125   9   4   7   3   3]
- [ 22  36 118  41  29  30  31]
- [ 16   2  11 100   3   3  11]
- [  1   9   2   0  66   2   3]
- [  8   0   0   2   1  48   2]
- [ 10   4  11   9   6  20  66]]
-Node Classification on random seed  9418 -> 0.637
-Confusion Matrix:
- [[ 72   0   0   6   5  11  16]
- [  5 131   1   2  10   1   6]
- [ 27  23 151  39  33  16  38]
- [  9   1  12  92   7   9  19]
- [  1   4   2   1  67   1   4]
- [  2   0   3   2   0  39   8]
- [  3   2   1   5  11  17  85]]
-Node Classification on random seed  9419 -> 0.623
-Confusion Matrix:
- [[ 71   1   2  18   3   8   8]
- [  6 122  11   5   8   6   3]
- [ 13  38 153  39  15  17  25]
- [  8   3  23  90   2   2  11]
- [  2   4   5   2  61   0   1]
- [ 10   1   1   6   1  51   3]
- [ 18  10  11  12   5  10  75]]
-Node Classification on random seed  9420 -> 0.575
-Confusion Matrix:
- [[ 69   3   3   5   5  14  10]
- [  4 118   5   3  14   1   4]
- [ 20  23 122  38  28  19  49]
- [ 20   5  21  96   7   3  20]
- [  0   7   2   3  60   4   2]
- [  8   4   2   5   0  44   6]
- [ 16   8  12   9   3  10  66]]
-Node Classification on random seed  9421 -> 0.586
-Confusion Matrix:
- [[ 61   9   2  10   3   6  19]
- [  6 131   5   5   5   2   3]
- [ 35  34 140  21  16  29  53]
- [ 18   4  10  90   7  13  16]
- [  3   5   9   0  47   0   3]
- [  5   1   1   1   0  33   6]
- [ 10   3   6   8   8  14  84]]
-Node Classification on random seed  9422 -> 0.622
-Confusion Matrix:
- [[ 51   5   7   5   1  13  14]
- [ 10 144   3   5   5   3   0]
- [ 18   9 145  35  21  18  41]
- [ 20   3  15  93   2  13  21]
- [  1   9   4   2  60   0   4]
- [  5   3   2   0   2  51   4]
- [  9   3  15   6   9  13  78]]
-Node Classification on random seed  9423 -> 0.58
-Confusion Matrix:
- [[ 63   1   2   5   4  18  20]
- [  4 121   3   2   9   7   4]
- [ 12  35 130  23  39  30  45]
- [ 18   9  12  82   5  17  16]
- [  1   8   5   1  57   0   0]
- [  8   1   1   0   1  45   3]
- [ 11   9   7   4   8  12  82]]
-Node Classification on random seed  9424 -> 0.632
-Confusion Matrix:
- [[ 84   2   1   5   7   6   6]
- [  8 127   6   3   7   1   4]
- [ 27  19 136  36  21  27  43]
- [ 11   1  16  89   5  18  11]
- [  0   6   1   0  70   0   1]
- [  4   1   3   3   4  46   3]
- [ 14   2   9   6   6  14  80]]
-Node Classification on random seed  9425 -> 0.629
-Confusion Matrix:
- [[ 63   3   1   6   2  15   3]
- [  1 138   5   7  11   3   4]
- [ 18  23 147  35  28  27  35]
- [  3   4  18 112   3   7   7]
- [  2   3   2   2  65   3   0]
- [  6   2   2   0   0  36   8]
- [  8   2  15  18   8  21  68]]
-Node Classification on random seed  9426 -> 0.635
-Confusion Matrix:
- [[ 69   2   7   5   3   9  10]
- [  6 120   4   1  12   9   5]
- [ 22  23 163  27  10  43  31]
- [ 11   6  15  93   3  11   6]
- [  1   5   2   2  62   0   4]
- [  2   0   3   4   3  53   8]
- [ 10   4   6   5   6  19  75]]
-Node Classification on random seed  9427 -> 0.6
-Confusion Matrix:
- [[ 75   4   1   8   3  14   8]
- [  6 122   8   5   3   1   2]
- [ 36  34 124  29  16  20  46]
- [ 11   6  13 110  12   6  13]
- [  2  11   8   1  57   0   1]
- [  9   2   3   3   0  35   3]
- [ 14   4  14  10   2   8  77]]
-Node Classification on random seed  9428 -> 0.641
-Confusion Matrix:
- [[ 69  10   6   1   3   6  16]
- [  2 138   7   1   3   1   4]
- [ 23  29 168  24  12  20  38]
- [  9  12  21 102   2   6  14]
- [  1   8   2   2  59   0   4]
- [  8   2   4   0   0  32  10]
- [  4   7  12   9   6  10  73]]
-Node Classification on random seed  9429 -> 0.606
-Confusion Matrix:
- [[ 64   8   9   8   1  14  13]
- [ 13 108   9   6   2   2   4]
- [ 18  20 152  26  25  22  41]
- [  4   6   9  95   7   9  22]
- [  2   4   6   3  56   3   4]
- [  4   3   1   1   0  52   6]
- [ 10   3  11  11   5  19  79]]
-Node Classification on random seed  9430 -> 0.621
-Confusion Matrix:
- [[ 80   7  10   7   4   8   5]
- [  6 135   3   6  10   3   1]
- [ 30  28 139  34  29  17  32]
- [  7   4  14 100   5   7  10]
- [  1  10   3   1  56   2   2]
- [  5   3   1   3   3  40   3]
- [ 22   5   9   5   4  10  71]]
-Node Classification on random seed  9431 -> 0.636
-Confusion Matrix:
- [[ 74   1   2   3   3  12   4]
- [  2 132   3   3   7   7   8]
- [ 30  12 133  30  41  20  46]
- [ 10   4  14 103   5   5  19]
- [  3   3   7   1  65   0   1]
- [  6   1   0   1   0  50  11]
- [ 13   3   3   7   5   8  79]]
-Node Classification on random seed  9432 -> 0.618
-Confusion Matrix:
- [[ 83   0   1   3   7  10   7]
- [  3 118   7   1   4   3   6]
- [ 29  23 146  33  17  20  42]
- [ 19   4  12  97  10   2  13]
- [  2   6   2   3  61   1   4]
- [  3   1   2   1   7  45   7]
- [ 12   4  11  18  10  12  68]]
-Node Classification on random seed  9433 -> 0.635
-Confusion Matrix:
- [[ 82   1   0   6   4  10   5]
- [  4 123   4   4   5   1   0]
- [ 20  25 146  39  23  24  33]
- [ 11   6  10  98   4   7  17]
- [  1  10   5   1  56   3   2]
- [  8   0   1   2   3  41   3]
- [ 11   8  11  10   5  18  89]]
-Node Classification on random seed  9434 -> 0.586
-Confusion Matrix:
- [[ 79  10   5   5   2   3   7]
- [  5 111   1   5  10   2   9]
- [ 26  24 132  47  54  21  27]
- [  7   3  13  93   5   5  22]
- [  3   4   2   7  60   3   3]
- [  5   0   2   5   0  39   5]
- [ 11   3  16   9   6  12  72]]
-Node Classification on random seed  9435 -> 0.662
-Confusion Matrix:
- [[ 64   2   0   9   6  12  17]
- [  5 139   3   2   1   1   5]
- [ 22  25 150  48  10  13  33]
- [  4   9  13 115   5   5   7]
- [  0   9   6   1  59   2   3]
- [  1   0   1   3   0  51   5]
- [  6   2   4   7   4  27  84]]
-Node Classification on random seed  9436 -> 0.593
-Confusion Matrix:
- [[ 52   2   7   6   1   9  16]
- [  5 131   7   6   3   3  11]
- [ 28  27 143  38  13  27  35]
- [ 15   0  24  95   3   7   8]
- [  2   7   6   6  57   0   2]
- [  2   0   2   7   0  41   7]
- [  8   3  14  16   5  19  74]]
-Node Classification on random seed  9437 -> 0.653
-Confusion Matrix:
- [[ 80   2   3   3   1  12  12]
- [  2 124   7   2   9   3   5]
- [ 20  18 149  22  39  21  39]
- [  9   2  11 105   3  12  11]
- [  2  10   1   1  63   1   1]
- [ 10   2   2   0   1  58   4]
- [ 18   3   3   1   6  13  74]]
-Node Classification on random seed  9438 -> 0.608
-Confusion Matrix:
- [[ 50   3   7  10   3  16  10]
- [  7 117  10   2  10   1   4]
- [ 16  13 171  29  19  26  50]
- [  5   1  37  90   1   5  14]
- [  2   4   5   1  59   0   3]
- [  3   2   2   2   1  39  12]
- [ 11   4  15   2   6  18  82]]
-Node Classification on random seed  9439 -> 0.606
-Confusion Matrix:
- [[ 61   1   9   4   3   8  10]
- [  2 114   8   8   9   4   3]
- [ 19  10 140  46  17  31  39]
- [ 22   2  26  94  10   9  12]
- [  0   3   5   3  65   1   1]
- [ 10   0   0   1   2  51   4]
- [ 17   1   9   6   6  13  81]]
-Node Classification on random seed  9440 -> 0.61
-Confusion Matrix:
- [[ 82   2   1   6   6   6  20]
- [  3 112   0   0  12   5   4]
- [ 27  16 138  34  30  25  41]
- [ 14   5  20  84  19   5   6]
- [  3   4   4   1  70   1   3]
- [  2   4   5   2   0  43   6]
- [ 10   3   8   7  12   8  81]]
-Node Classification on random seed  9441 -> 0.574
-Confusion Matrix:
- [[ 78   1   2  12   7   3   5]
- [  4  99   5   3  22   1   6]
- [ 31  38 124  60  22  26  30]
- [  6   6  22  96   7   4  11]
- [  2   3   6   4  67   1   2]
- [  5   3   3   1   1  41   4]
- [ 23   4   9   7   8   6  69]]
-Node Classification on random seed  9442 -> 0.6
-Confusion Matrix:
- [[ 66   1   2  12   2  14   5]
- [  3 137   6   1   2   5   1]
- [ 12  19 148  48   7  33  46]
- [ 20   0  10  77  19  16  14]
- [  1   8   7   2  54   1   4]
- [  8   0   3   2   1  44   7]
- [  7   8  10  12   5  16  74]]
-Node Classification on random seed  9443 -> 0.633
-Confusion Matrix:
- [[ 73   3   1  10   7  11   3]
- [  4 134   7   3   7  11   1]
- [ 31   9 142  25  14  14  47]
- [ 17   9  15  97   3   8  15]
- [  1   6  10   2  67   1   2]
- [  4   0   3   1   1  42   7]
- [ 17   4   8  12   3  10  78]]
-Node Classification on random seed  9444 -> 0.595
-Confusion Matrix:
- [[ 70   5   9   4  10   8   8]
- [  6 125   4   3   8   2   7]
- [ 39  23 139  44  27  16  24]
- [ 17   4  12 111   2   2   5]
- [  0   6   6   2  57   0   1]
- [ 10   1   1   2   0  34   6]
- [ 17   4  13  18  12  17  59]]
-Node Classification on random seed  9445 -> 0.628
-Confusion Matrix:
- [[ 64   4   9   3   3  14   9]
- [ 10 116   5   3  11   1   3]
- [ 21  30 152  43  25  22  27]
- [ 13   2  22 107   1   3  14]
- [  1   2   3   3  65   3   2]
- [  4   1   3   0   2  43   2]
- [ 12   2   5   6   7  16  81]]
-Node Classification on random seed  9446 -> 0.591
-Confusion Matrix:
- [[ 71   0   4   6   1  12  17]
- [  8 117   5   0   7   6   1]
- [ 26  29 121  22  20  46  38]
- [ 16   1  17 104   4  16  19]
- [  2   7   4   2  58   1   5]
- [  6   1   1   1   2  51   7]
- [  9  11   4   5   4  16  69]]
-Node Classification on random seed  9447 -> 0.602
-Confusion Matrix:
- [[ 69   3   2  11   2   7  21]
- [  5 116   8   7  10   5   5]
- [ 20  18 130  41  35  19  36]
- [  6   7  21  91  12   8   4]
- [  0   8   2   1  58   1   3]
- [  4   0   0   2   0  43   7]
- [ 16   4   6   7   9  15  95]]
-Node Classification on random seed  9448 -> 0.629
-Confusion Matrix:
- [[ 74   2   1   3   3   6  13]
- [  3 119   3   5   7   1   9]
- [ 29  12 151  26  29  39  38]
- [  5   3  14 101   4   8  11]
- [  1   7   4   1  61   2   1]
- [  2   3   1   0   2  41  13]
- [  5   5  12  16   9  13  82]]
-Node Classification on random seed  9449 -> 0.624
-Confusion Matrix:
- [[ 59   4   2   4   2  16  17]
- [  8 127  12   6  11   2   2]
- [ 13  15 141  45  30  24  27]
- [ 10   4  11 105  14   4   7]
- [  2   2   3   1  61   0   1]
- [  4   0   3   3   2  43   4]
- [  9   2  11  10   5  24  88]]
-Node Classification on random seed  9450 -> 0.626
-Confusion Matrix:
- [[ 62   1   1  10   5   6  16]
- [  4 141   6   4   1   3   2]
- [ 24  18 135  40  26  31  33]
- [ 11   3  16 101   6   3   9]
- [  1   9   2   3  52   0   3]
- [ 11   1   2   4   1  47   7]
- [  7   2   4   5   8  25  88]]
-Node Classification on random seed  9451 -> 0.584
-Confusion Matrix:
- [[ 75   5   5   2   4  19   8]
- [  4 125   4   4   4   2   3]
- [ 27  16 114  49  26  25  46]
- [ 14   3  15 120   6   4  18]
- [  5   7   2   0  50   1   2]
- [ 14   0   1   0   2  31  11]
- [ 20   4   6  13   6   9  69]]
-Node Classification on random seed  9452 -> 0.577
-Confusion Matrix:
- [[ 57   6   3   9   3   6  19]
- [  3 117  12   5   6   2   5]
- [ 37  19 119  58  17  24  31]
- [  9   3  15 119   6   4  11]
- [  2   5   3   3  52   0   6]
- [  5   0   3   5   1  35  11]
- [ 13   6  14  12   5  16  78]]
-Node Classification on random seed  9453 -> 0.612
-Confusion Matrix:
- [[ 71   0   0   6   8  13   5]
- [  7 120   7   4  12   3   4]
- [ 31  24 159  44  22  19  21]
- [  9   6  16  99   5   4   7]
- [  0  10   4   1  37   2   1]
- [  0   1   3   2   2  56   6]
- [ 12   6  16   5  16  24  70]]
-Node Classification on random seed  9454 -> 0.607
-Confusion Matrix:
- [[ 68   2   4   2   0   9  12]
- [  6 132   4   1   0   5  11]
- [ 39  21 148  29  33  24  29]
- [ 17   2  20  94   4   9  19]
- [  3   4   9   1  63   0   4]
- [  4   0   5   0   1  43   8]
- [ 11   4  10   0   5  22  59]]
-Node Classification on random seed  9455 -> 0.625
-Confusion Matrix:
- [[ 91   2   2   4   8   6   7]
- [  3 154   3   5   3   2   2]
- [ 28  34 122  53  32  10  45]
- [  7   9  23  96   2   3  13]
- [  0   9   2   0  57   0   0]
- [  3   0   3   0   1  38   2]
- [ 13   0  10  14   2  10  67]]
-Node Classification on random seed  9456 -> 0.638
-Confusion Matrix:
- [[ 72   2   3   5   0  15  12]
- [  2 141   8   5   3   1   6]
- [ 11  12 154  38  17  32  46]
- [  7   4  10  97   2   5  26]
- [  2   8   3   4  53   3   2]
- [  1   1   3   4   0  45  13]
- [  9   4   7   8   3  15  76]]
-Node Classification on random seed  9457 -> 0.596
-Confusion Matrix:
- [[ 77   1   2   4   2   7  13]
- [  2 128  10   7  10   3   3]
- [ 24  32 118  43  28  23  44]
- [ 16   4  18 109   4   6   6]
- [  2   6   4   4  59   1   1]
- [  7   3   0   4   0  37   3]
- [ 16   3   8   6   2  22  68]]
-Node Classification on random seed  9458 -> 0.656
-Confusion Matrix:
- [[ 69   1   6   2   4  16  18]
- [  8 143   6   4   2   2   6]
- [ 17  19 158  16  22  23  43]
- [ 11   2  17 104   2   6  22]
- [  2   5   4   2  57   0   1]
- [  6   1   1   2   0  47   4]
- [ 10   2   9   4   3  13  78]]
-Node Classification on random seed  9459 -> 0.595
-Confusion Matrix:
- [[ 58   1   1   2   4  12  22]
- [  6 120   8   2  12   1   5]
- [ 19  14 148  37  24  36  31]
- [ 14   2  13 108   5  11   5]
- [  2   2   3   5  54   0   2]
- [  9   2   1   1   1  46   4]
- [  9   7   7  20  11  32  61]]
-Node Classification on random seed  9460 -> 0.656
-Confusion Matrix:
- [[ 69   2   1   4   3   6  11]
- [  3 141   5   3   3   4   2]
- [ 23  23 137  36  31  13  42]
- [  8   2   8 126   4   2  11]
- [  3   7   4   4  63   0   1]
- [  3   2   0   1   2  42  12]
- [ 10   8   8  10   6  13  78]]
-Node Classification on random seed  9461 -> 0.61
-Confusion Matrix:
- [[ 70   2  10   2   6   7   8]
- [  4 110   6   3  18   3  12]
- [ 21  10 153  53  37  11  35]
- [ 17   1  18  99   8   2  12]
- [  0   3   3   1  58   0   2]
- [  2   0   7   2   4  45   2]
- [ 14   8  11  10   6   9  75]]
-Node Classification on random seed  9462 -> 0.591
-Confusion Matrix:
- [[ 60   8   1   5   1  11  11]
- [  2 132   6   4   4   2   7]
- [ 27  32 119  53  35  19  28]
- [ 14   4  20  92   5   5  19]
- [  3   5   3   2  64   1   4]
- [  5   1   7   0   0  43   4]
- [ 14   5  12   3   6  11  81]]
-Node Classification on random seed  9463 -> 0.639
-Confusion Matrix:
- [[ 68   5   2   7   4  12   6]
- [  7 140   6   9   1   2   3]
- [  8  27 162  40  16  24  34]
- [ 21   1  13  97   3   4  19]
- [  4   7   2   4  46   1   3]
- [  7   1   3   1   2  42   1]
- [ 10   1   9   8   6  17  84]]
-Node Classification on random seed  9464 -> 0.598
-Confusion Matrix:
- [[ 59   4   5   3   4  13  17]
- [  1 125   9   1   4   4   4]
- [ 28  22 129  44  31  23  43]
- [ 11   7  10 101   7   5  13]
- [  6   7   1   1  56   1   4]
- [  6   3   2   3   1  49   1]
- [ 10   4   7   6   8  18  79]]
-Node Classification on random seed  9465 -> 0.615
-Confusion Matrix:
- [[ 83   1   8   4   3   6  13]
- [  5 125   6   6  10   2   4]
- [ 18  21 135  26  21  30  39]
- [ 13   2  16 114   7  13  17]
- [  2   2   3   5  55   6   1]
- [ 13   1   3   1   0  42   7]
- [  8   2  10   6   7  17  61]]
-Node Classification on random seed  9466 -> 0.65
-Confusion Matrix:
- [[ 80   3   2   6   3   6   3]
- [  3 144  10   1   1   2   6]
- [ 18  28 148  61  17  10  22]
- [  8   4  12 111   4   6  21]
- [  1   8   4   1  59   3   4]
- [ 13   2   1   3   2  44   5]
- [ 11   2  15   4   3  11  64]]
-Node Classification on random seed  9467 -> 0.609
-Confusion Matrix:
- [[ 61   2  10   3   7  15  12]
- [  2 130   1   3   5   7  13]
- [ 18  28 130  25  20  32  61]
- [  5   1  16 116   9   9  13]
- [  1   2   4   0  50   0   3]
- [  9   1   4   1   0  44   3]
- [  8   1  14   5   6  12  78]]
-Node Classification on random seed  9468 -> 0.665
-Confusion Matrix:
- [[ 76   2   0   6   4   8   4]
- [  5 135   6   0   2   0   4]
- [ 34  25 153  25  20  24  46]
- [ 11   3  10  98   9   7   3]
- [  1   7   5   0  63   1   4]
- [  6   0   2   1   0  50   4]
- [  8   3   9   9   2  15  90]]
-Node Classification on random seed  9469 -> 0.601
-Confusion Matrix:
- [[ 65   2  11   9   6  11   2]
- [  5 125   6   1  10   5   6]
- [ 46  22 121  28  13  19  58]
- [  7   4   9 115   4   4  22]
- [  4   3   7   0  55   1   2]
- [  3   1   4   5   1  50   9]
- [ 13   3   4   8   7  14  70]]
-Node Classification on random seed  9470 -> 0.605
-Confusion Matrix:
- [[ 71   2   4   5   2  10  11]
- [  2 120   6   1  22   2   3]
- [ 21  30 154  45  23  20  32]
- [  8   8  14  93   6  17  12]
- [  1   5   5   1  58   0   3]
- [  5   1   2   0   4  45   5]
- [ 10   1   9   4  15  18  64]]
-Node Classification on random seed  9471 -> 0.601
-Confusion Matrix:
- [[ 68   4   4   8   8   7  12]
- [  3 132   6   3  10   0   2]
- [ 21  18 123  48  15  35  51]
- [  7   1  19 117   6   5   8]
- [  0   4   6   3  49   1   3]
- [  4   0   9   2   2  49   4]
- [  3   2  10  11   7  27  63]]
-Node Classification on random seed  9472 -> 0.57
-Confusion Matrix:
- [[ 55   5  10   6   4   7  17]
- [ 12 121   3   6   6   6   6]
- [ 23  19 124  40  28  29  43]
- [ 17   3  10 102   3   9  19]
- [  1   4   4   3  58   0   0]
- [ 10   0   2   0   0  40   6]
- [ 24   0  10  11  11  13  70]]
-Node Classification on random seed  9473 -> 0.642
-Confusion Matrix:
- [[ 87   2   1   1   3  10   4]
- [ 10 134   2   1  12   2   2]
- [ 24  25 149  18  35  18  31]
- [ 10   7  20 106   5   7  10]
- [  0  10   6   0  55   1   4]
- [  8   3   0   5   3  46   4]
- [ 13   2   5   9  12  13  65]]
-Node Classification on random seed  9474 -> 0.592
-Confusion Matrix:
- [[ 69   1   3  17   8  12   5]
- [  5 113   2   8   6   3   6]
- [ 37  29 117  41  20  37  31]
- [ 13   4  11 103   4   6  15]
- [  0   6   7   0  64   0   1]
- [  2   1   3   5   0  49   6]
- [ 12   2  10   7   8  14  77]]
-Node Classification on random seed  9475 -> 0.629
-Confusion Matrix:
- [[ 62   0   5   6   5  13   9]
- [  5 120   9   4   4   3   4]
- [ 19  16 134  49  18  16  57]
- [ 14   8  13 124   4   5  12]
- [  1   6   4   0  61   0   3]
- [  1   4   5   1   0  44   4]
- [ 11   3   7   4   5  14  84]]
-Node Classification on random seed  9476 -> 0.571
-Confusion Matrix:
- [[ 60   1  12   2   4  16  13]
- [ 12 109   6   4   6   6   6]
- [ 21  20 131  60  23  28  26]
- [ 18   6  20  98   3  16   3]
- [  2   6   4   2  55   0   2]
- [  4   3   1   4   2  42  10]
- [ 13   2   7   9   6  20  76]]
-Node Classification on random seed  9477 -> 0.627
-Confusion Matrix:
- [[ 62   4   3  11   3  10  10]
- [  5 135   8   0  15   7   2]
- [ 24  30 153  30  18  23  36]
- [  8   5  12  98   7   9  13]
- [  2   3   4   2  60   0   1]
- [  7   1   4   0   0  57   5]
- [ 17   2   5   3   6  18  62]]
-Node Classification on random seed  9478 -> 0.565
-Confusion Matrix:
- [[ 62   3  10   4   5   9   7]
- [  1 121   5   3   7   7  16]
- [ 30  29 102  56  35  27  41]
- [ 11   7   4 101   7   3  18]
- [  0   5   3   0  61   0   6]
- [ 14   0   2   0   1  34   8]
- [ 14   1   7   3  12  14  84]]
-Node Classification on random seed  9479 -> 0.611
-Confusion Matrix:
- [[ 79   2   5   6   8   7   5]
- [  5 128   9   4  10   8   3]
- [ 21  18 130  45  22  28  42]
- [ 17   4  10 103   3   3  21]
- [  1   5   4   2  55   0   7]
- [  6   9   1   1   1  47   4]
- [ 16   4   7   2   5   8  69]]
-Node Classification on random seed  9480 -> 0.611
-Confusion Matrix:
- [[ 66   6   0   3   0  11  17]
- [  7 121  11   3   7   6  10]
- [ 33  19 142  32  16  18  33]
- [ 19   2  18  97   5   2  10]
- [  1   4   6   0  73   0   1]
- [  7   0   3   2   0  44  10]
- [ 17   2   7  20   8  13  68]]
-Node Classification on random seed  9481 -> 0.59
-Confusion Matrix:
- [[ 81   7   1   9   2   6   6]
- [  4 126   3   4   6   4   3]
- [ 19  31 133  31  43  24  45]
- [ 12   9   7  84   5   5  19]
- [  5   8   2   0  50   1   2]
- [ 11   1   3   6   1  40   2]
- [ 22   4   8   4   9  16  76]]
-Node Classification on random seed  9482 -> 0.606
-Confusion Matrix:
- [[ 91   1   8   3   4   7   6]
- [  7 100   7   0   8   1   3]
- [ 34  26 144  30  38  38  28]
- [ 10   2  29  87   4   1  23]
- [  1   2   9   2  59   0   0]
- [  6   0   1   0   1  54   4]
- [ 11   3   9   9   7  11  71]]
-Node Classification on random seed  9483 -> 0.624
-Confusion Matrix:
- [[ 72   1   5   9   7   2   7]
- [  1 132   7   1   6   0   4]
- [ 28  31 126  28  59   9  25]
- [ 16   6  22 114   8   1  10]
- [  0   7   3   1  63   0   3]
- [  6   2   2   0   1  43   5]
- [ 12   5  13   4   3  16  74]]
-Node Classification on random seed  9484 -> 0.602
-Confusion Matrix:
- [[ 68   2   8   5   2  11  19]
- [  5 112   4   0   9   5   0]
- [ 26  18 128  33  26  46  38]
- [ 12   3  20 106   4   4  11]
- [  3   5   2   4  61   0   1]
- [ 10   4   3   0   0  45   6]
- [  7   3   8   5  11  15  82]]
-Node Classification on random seed  9485 -> 0.632
-Confusion Matrix:
- [[ 62   1   9   7   6  11   7]
- [  1 125   4   9   3   0   6]
- [ 23  36 158  32  17  19  39]
- [ 15   4  10  96   9   5  14]
- [  1   5   4   1  56   1   1]
- [  7   3   5   3   1  47   1]
- [  9   5   5   4   7  18  88]]
-Node Classification on random seed  9486 -> 0.628
-Confusion Matrix:
- [[ 85   1   6   3   2   6   4]
- [  5 120   3   3   8   8   4]
- [ 25  13 139  51  40   8  42]
- [ 11   6   7 109   9   6  10]
- [  2   5   4   0  63   0   2]
- [  5   1   5   3   1  39   9]
- [ 12   4  12   9   9   8  73]]
-Node Classification on random seed  9487 -> 0.619
-Confusion Matrix:
- [[ 75   2   3  15   5  12   9]
- [  9 109   3   0   7   0  13]
- [ 29  20 132  27  19  34  44]
- [  4   3  15 119   2   7  11]
- [  3   5   4   0  65   2   3]
- [  2   0   3   1   0  46  11]
- [ 14   4  15   7   1  13  73]]
-Node Classification on random seed  9488 -> 0.618
-Confusion Matrix:
- [[ 75   2   8  13   2   8   7]
- [  6 118   3   5   6   1   6]
- [ 25  19 133  64  24  10  29]
- [  9   3  11 115   4   4  19]
- [  4   2   7   3  66   0   6]
- [  2   0   4   3   1  28  12]
- [ 16   1  11  13   4   5  83]]
-Node Classification on random seed  9489 -> 0.602
-Confusion Matrix:
- [[ 70   4   5   2   7  15   6]
- [  5 137   2   0   3   4   7]
- [ 31  26 119  35  29  26  35]
- [ 17   4  20  89   9   9  14]
- [  2   8   6   1  49   0   1]
- [  5   4   8   2   4  52   1]
- [ 12   2   4   3   3  17  86]]
-Node Classification on random seed  9490 -> 0.614
-Confusion Matrix:
- [[ 82   1   4  11   5  17   7]
- [  6 120   2   1   9   0   3]
- [ 26  18 111  28  34  32  50]
- [  6   1   7 117   7  10  11]
- [  1   8   5   0  58   1   2]
- [  4   1   5   2   0  44   7]
- [ 12   3   8  13  11   7  82]]
-Node Classification on random seed  9491 -> 0.623
-Confusion Matrix:
- [[ 84   0   7   7   5  15   5]
- [  4 118   5   6   6   7   6]
- [ 20  20 143  23  22  23  44]
- [ 11   8  19 102   5   4  17]
- [  0  10   4   1  59   1   4]
- [  3   3   2   1   3  43   0]
- [ 11   2   8   8  17  10  74]]
-Node Classification on random seed  9492 -> 0.661
-Confusion Matrix:
- [[ 70   1   4   3   3   7  10]
- [  7 115   9   3   5   4   8]
- [ 15  14 196  20  22  14  41]
- [ 13   8  16  98   4  10  11]
- [  0   9   5   2  62   0   5]
- [ 15   0   3   1   0  36   7]
- [ 11   2   4   5   5  13  84]]
-Node Classification on random seed  9493 -> 0.626
-Confusion Matrix:
- [[ 55   2   5   4   2  17  14]
- [  5 122   3   3  10   3   2]
- [ 31  32 140  19  26  18  33]
- [ 13   5  11 117   6   9   7]
- [  4   9   3   2  67   1   4]
- [  6   3   1   2   0  45   8]
- [  8   1  11   7   8  16  80]]
-Node Classification on random seed  9494 -> 0.66
-Confusion Matrix:
- [[ 74   2   8   7   1   9  10]
- [  5 139   7   1   9   1   4]
- [ 13  29 159  24  22  26  35]
- [  3   2  15  92  11   4  17]
- [  1   6   4   1  61   1   3]
- [  8   2   2   0   0  44   6]
- [  4   1  14   4  10   8  91]]
-Node Classification on random seed  9495 -> 0.634
-Confusion Matrix:
- [[ 73   2   4   3   1  14  16]
- [  3 128   2   6   4   8   7]
- [ 20  18 161  32  34  15  35]
- [ 15   7  13 105   1   2  16]
- [  2  12   3   1  51   0   2]
- [  2   2   2   0   1  45   5]
- [ 14   4  13   1   7  17  71]]
-Node Classification on random seed  9496 -> 0.603
-Confusion Matrix:
- [[ 68   2   5   3   2  20  10]
- [  3 120   4   5  10   1   4]
- [ 44  14 145  25  18  25  40]
- [ 14   1   7  97   6   7  17]
- [  0   9   4   2  60   2   3]
- [  4   1   3   6   0  48   7]
- [  8   4   7   5  21  24  65]]
-Node Classification on random seed  9497 -> 0.648
-Confusion Matrix:
- [[ 66   4  10   0   5  13   3]
- [  7 122   1   1  13   0   6]
- [ 22  25 173  20  27  29  21]
- [  6  10  21 101   3   4  12]
- [  0   6   4   2  65   1   3]
- [  4   5   3   4   0  54   0]
- [ 13   4   0   9   7  24  67]]
-Node Classification on random seed  9498 -> 0.592
-Confusion Matrix:
- [[ 53   3   4   7   2  12  21]
- [  2 110   6   2  11   1   6]
- [ 19  22 140  28  30  43  41]
- [ 14   9  15 105   3   7  17]
- [  3   8   1   1  61   3   1]
- [  9   0   1   0   1  59   3]
- [ 16   2  10   3   1  20  64]]
-Node Classification on random seed  9499 -> 0.571
-Confusion Matrix:
- [[ 63   1   8   6   8   9  23]
- [ 13 126   7   1   8   1   3]
- [ 31  37 106  49  18  28  34]
- [ 11   7  12 107   6   4  14]
- [  2   6   8   0  49   0   3]
- [  4   0   1   0   1  58   3]
- [ 15   7   5   2  13  20  62]]
-Node Classification on random seed  9500 -> 0.614
-Confusion Matrix:
- [[ 55   4   6   0   5  10  10]
- [  9 128   6   0   4   1   3]
- [ 32  29 134  22  37  13  46]
- [ 12   7  25  88  11   4  18]
- [  4   6   3   2  65   1   2]
- [  5   0   4   0   0  56   4]
- [  7   2  11   2  10   9  88]]
-Node Classification on random seed  9501 -> 0.65
-Confusion Matrix:
- [[ 84   3   2   4   2  12   2]
- [  6 140   4   2   1   3   9]
- [ 30  18 146  26  35  13  40]
- [  7   1  15 114   4   4   8]
- [  2   6   3   4  58   0   2]
- [  8   1   9   1   5  33   3]
- [ 13   1  10   8   6  17  75]]
-Node Classification on random seed  9502 -> 0.633
-Confusion Matrix:
- [[ 78   1   4   7   5  14  12]
- [  5 135   4   1   6   2   4]
- [ 26  24 146  30  22  21  40]
- [ 14   3  18  77   9   2  14]
- [  0   5   3   0  51   4   0]
- [  2   2   3   5   0  62   9]
- [  8   0   6   3  16  13  84]]
-Node Classification on random seed  9503 -> 0.597
-Confusion Matrix:
- [[ 77   2  10   1   6   7   9]
- [  7 119  13   6   3   1   3]
- [ 25  26  98  40  45  30  51]
- [  9   1   8 110   7   5   6]
- [  0   8   0   5  64   1   2]
- [  4   1   3   2   2  58   5]
- [ 10   8  12   4   4  11  71]]
-Node Classification on random seed  9504 -> 0.644
-Confusion Matrix:
- [[ 85   5   5   6   2  12   2]
- [  2 134   4   3   3   2   2]
- [ 18  24 160  27  22  24  42]
- [ 12   1   9 107   5   6  16]
- [  3   6   3   0  45   2   5]
- [  1   3   3   5   0  51   6]
- [  7   5  10   8  11  24  62]]
-Node Classification on random seed  9505 -> 0.591
-Confusion Matrix:
- [[ 71   2   7   3   5  12  11]
- [  4 131   3   3  11   2   0]
- [ 23  25 142  46  20  14  51]
- [ 22  11  13  84   2   9  26]
- [  1   8   6   1  56   0   5]
- [  1   4   2   1   0  46   5]
- [ 13   6   7   2   8  14  61]]
-Node Classification on random seed  9506 -> 0.611
-Confusion Matrix:
- [[ 65   3   2   3   8  23  12]
- [  2 117   7   4  18   2   1]
- [ 17   5 151  21  37  26  43]
- [ 16   1  13  94   9   9  22]
- [  1   5   2   1  60   2   3]
- [  6   2   4   0   7  48   3]
- [ 13   3   7   2   8  16  76]]
-Node Classification on random seed  9507 -> 0.599
-Confusion Matrix:
- [[ 65   2   1   3   4   8  18]
- [  4 107   6   4  10   5   6]
- [ 24  17 147  33  29  31  40]
- [ 14   2  16 107   5   7  13]
- [  0   4   2   4  59   1   1]
- [  5   3   3   5   0  40   9]
- [  5   2  18   5  14  18  74]]
-Node Classification on random seed  9508 -> 0.621
-Confusion Matrix:
- [[ 88   4   1   5   3  11  10]
- [  4 149   6   4  10   3   1]
- [ 23  12 118  40  54  14  30]
- [ 11   2  17  88   4  11  10]
- [  0   9   3   0  58   1   2]
- [  6   0   1   3   2  38   6]
- [  9   3  16   9   8  11  82]]
-Node Classification on random seed  9509 -> 0.624
-Confusion Matrix:
- [[ 78   2   5   3   5  12  10]
- [  4 137   6   3   5   6   4]
- [ 24  11 127  19  34  36  34]
- [ 11   3  24 104   4   6  15]
- [  2   4   2   2  65   3   5]
- [  7   0   1   1   1  43   5]
- [ 13   4   5  11   8  16  70]]
-Node Classification on random seed  9510 -> 0.603
-Confusion Matrix:
- [[ 85   1   3   3   4  12  14]
- [  8 129   4   5   2   5   2]
- [ 14  21 116  48  58  22  38]
- [  7   2  16  98   4   6  19]
- [  1   5   2   2  67   1   1]
- [  9   0   1   2   2  43   8]
- [  7   3   9   7   5  14  65]]
-Node Classification on random seed  9511 -> 0.614
-Confusion Matrix:
- [[ 75   2   8   4   2   0  18]
- [  3 126   6   5  11   1  10]
- [ 27  26 142  28  20  26  31]
- [ 12   8  18  93  10   5  12]
- [  2   5   5   0  51   4   1]
- [  5   1   5   1   0  51   8]
- [  9  10  15   5   7  10  76]]
-Node Classification on random seed  9512 -> 0.647
-Confusion Matrix:
- [[ 72   5   7   3   1  13  15]
- [  0 129   3   6   2   8   0]
- [ 15  16 162  34  28  23  48]
- [ 15   1   9 102   7   7  20]
- [  1   5   4   3  49   2   3]
- [  6   0   0   2   0  47   5]
- [  3   4   8   8   3  10  86]]
-Node Classification on random seed  9513 -> 0.633
-Confusion Matrix:
- [[ 68   2   8  12   1   8   8]
- [  3 134   1   1   7   0   2]
- [ 19  10 156  31  50  21  25]
- [ 15  10  17  97   5   6  18]
- [  6   4   7   1  59   0   3]
- [  1   5   2   2   1  40   7]
- [ 14   3  11   7   3  10  79]]
-Node Classification on random seed  9514 -> 0.59
-Confusion Matrix:
- [[ 68   2   6   5   1   9  16]
- [  4 128   8   3  11   5   6]
- [ 24  20 123  47  30  24  41]
- [  7   2  15  98   2   2  24]
- [  1   4  11   3  52   0   2]
- [  9   0   0   1   1  47  10]
- [  9   3  10   6   5  21  74]]
-Node Classification on random seed  9515 -> 0.629
-Confusion Matrix:
- [[ 85   3   2   8   5   5   8]
- [  2 130   2   6   9   5   7]
- [ 32  12 149  37  16  11  35]
- [ 13   3  17 104   4   3  14]
- [  2   2   9   3  50   2   2]
- [ 16   1   2   2   1  43   4]
- [ 13   1  11  10  12  19  68]]
-Node Classification on random seed  9516 -> 0.588
-Confusion Matrix:
- [[ 78   2   7  10   5  17   7]
- [  4 100   9   0   6   2   0]
- [ 26  25 104  40  64  17  37]
- [  8   4   9 126   4  10   6]
- [  0  10   4   3  56   1   1]
- [  3   2   4   2   0  52   1]
- [ 16   2   7  11   5  21  72]]
-Node Classification on random seed  9517 -> 0.636
-Confusion Matrix:
- [[ 87   3  14   0   1   8  12]
- [  4 125   5   3  13   0   1]
- [ 16  19 164  34  20  24  30]
- [  8   1  17  99   6   7  21]
- [  1   5   3   5  53   3   4]
- [  4   1   0   2   1  42   4]
- [  9   7  10   3  22  13  66]]
-Node Classification on random seed  9518 -> 0.623
-Confusion Matrix:
- [[ 70   5   3   3   2   7  13]
- [  7 122   3   2  12   2   5]
- [ 26  19 133  22  37  43  29]
- [ 10   6  14  93  13  10   7]
- [  1   7   7   0  58   1   6]
- [  2   2   2   1   0  50   4]
- [ 17   3   5   8   1  10  97]]
-Node Classification on random seed  9519 -> 0.614
-Confusion Matrix:
- [[ 60   0   8   6   9  18   8]
- [  3 125   4   2   6   1   5]
- [ 27  23 142  20  40  13  39]
- [ 17   2  18 118   2   9  11]
- [  2   5   1   9  55   2   0]
- [  5   2   6   1   1  42   4]
- [  6   5  13   5   7  21  72]]
-Node Classification on random seed  9520 -> 0.638
-Confusion Matrix:
- [[ 74   5   1   2   3  10   7]
- [  9 137   6   2  13   7   2]
- [ 16  24 144  23  40  29  38]
- [  5   3  11  85  15  11  11]
- [  1   4   0   1  59   0   4]
- [  3   2   0   2   1  54   2]
- [ 16   2   5   6   6  14  85]]
-Node Classification on random seed  9521 -> 0.622
-Confusion Matrix:
- [[ 69   3   7   8   3   9  13]
- [  4 137   4   2   3   0   2]
- [ 29  23 144  42  25  14  34]
- [ 17   4  21 104   4   4  10]
- [  3  12   4   1  56   1   0]
- [  6   1   0   0   1  47  13]
- [  9   6  11   4   7  14  65]]
-Node Classification on random seed  9522 -> 0.618
-Confusion Matrix:
- [[ 80   3   1   6   8   9   6]
- [  3 130   7   6   4   6   3]
- [ 29  21 119  44  24  21  46]
- [ 14   0  11 115   3  11   9]
- [  0  10   5   8  56   1   5]
- [  6   2   2   2   3  42   0]
- [  9   2   6   5   2  19  76]]
-Node Classification on random seed  9523 -> 0.611
-Confusion Matrix:
- [[ 66   5  11   4   8   3  13]
- [  2 124   5   6   5   2   6]
- [ 17  22 147  40  34  16  35]
- [ 11   8  24  98  10   4  17]
- [  1  11   1   1  63   1   0]
- [  7   4   2   1   2  39   5]
- [ 11   2   9   6   9   8  74]]
-Node Classification on random seed  9524 -> 0.614
-Confusion Matrix:
- [[ 87   3   1   2   6  14   3]
- [  6 132   4   2   5   2   5]
- [ 30  16 126  36  33  22  46]
- [ 17   1   9  96   5   8  14]
- [  1   5   2   3  67   3   1]
- [  7   4   2   0   0  43   6]
- [ 17   4   1  12  11  17  63]]
-Node Classification on random seed  9525 -> 0.614
-Confusion Matrix:
- [[ 67   4   4   4   8  13  12]
- [ 11 115  12   4  10   1   3]
- [ 35  22 153  26  18  21  44]
- [ 11   6  12 102   7   5   9]
- [  1   5   4   1  65   2   1]
- [ 11   3   1   1   0  43   7]
- [  4   1   6   1   5  30  69]]
-Node Classification on random seed  9526 -> 0.575
-Confusion Matrix:
- [[ 59   1  10   7   4  11   7]
- [  9 114   8   6   4   5   9]
- [ 28  20 128  50  32  19  28]
- [ 16   6  19 106   3   2   7]
- [  3  11   4   3  57   1   7]
- [  9   3   2   2   0  41   0]
- [ 17   2   8   9  11  22  70]]
-Node Classification on random seed  9527 -> 0.622
-Confusion Matrix:
- [[ 70   2   6   9   2  11   7]
- [  4 138   3   1   7   7   4]
- [ 27  18 138  29  28  31  32]
- [ 10   7  13  96   5   5  17]
- [  0   7   0   1  68   1   2]
- [  6   0   2   3   0  46   3]
- [ 15   3   7  11   9  23  66]]
-Node Classification on random seed  9528 -> 0.613
-Confusion Matrix:
- [[ 74   3   7   3   0  12   0]
- [  9 142   4   2   6   4   3]
- [ 14   7 117  52  30  42  45]
- [ 21   6   9  96   1  13   8]
- [  1   8   0   2  60   1   4]
- [ 11   1   2   2   0  49   0]
- [  9   4   9   7  10  15  75]]
-Node Classification on random seed  9529 -> 0.597
-Confusion Matrix:
- [[ 63   3   1   5   8  13   7]
- [  1 136   1   4   4  12   3]
- [ 15  43 134  31  22  27  45]
- [ 17  10   9  97   4   7  12]
- [  0   9   3   4  53   2   2]
- [  6   2   3   2   2  40   6]
- [  6  11   8   3  10  20  74]]
-Node Classification on random seed  9530 -> 0.586
-Confusion Matrix:
- [[ 73   1   2   3   2  11  11]
- [  7 113  10   3   8   6   1]
- [ 12  19 139  47  36  28  45]
- [ 30   4   6  85   6  18  18]
- [  0   4   3   1  58   0   3]
- [  6   0   4   1   0  41   2]
- [ 12   4   9  10   5  16  77]]
-Node Classification on random seed  9531 -> 0.645
-Confusion Matrix:
- [[ 64   4   9  10   2   2  20]
- [  1 142   8   2   2   0   2]
- [ 24  29 175  31  24   8  26]
- [ 19   5  12  85   3   4  25]
- [  0   9   5   2  61   3   4]
- [  2   1   6   0   1  42   5]
- [ 10   0  13   6   6  10  76]]
-Node Classification on random seed  9532 -> 0.636
-Confusion Matrix:
- [[ 72   1   3   6   4  15   5]
- [  4 130   1   4   8   1   4]
- [ 24  33 140  39  15  15  24]
- [  5  10  24 105   2   9  15]
- [  1   1   3   3  65   1   3]
- [  7   1   3   2   0  48   9]
- [ 17   3  13   7  12   7  76]]
-Node Classification on random seed  9533 -> 0.637
-Confusion Matrix:
- [[ 70   2   4   1   3  19   7]
- [  3 135   3   6   1   4   1]
- [ 21  39 145  39  15  21  40]
- [ 21   4   8  96   7   7   7]
- [  0   5   1   2  51   2   3]
- [  4   0   0   4   0  61   4]
- [ 18   4   5  12   5  11  79]]
-Node Classification on random seed  9534 -> 0.632
-Confusion Matrix:
- [[ 69   0   1   1   4  10  16]
- [  1 139   4   4  14   4   0]
- [ 20  27 157  37  25  19  31]
- [ 13   3  14  96   5   2  24]
- [  0   9   1   3  54   1   3]
- [  8   0   2   2   4  34  11]
- [ 11   2   9   6   4  13  83]]
-Node Classification on random seed  9535 -> 0.612
-Confusion Matrix:
- [[ 68   4   1   4   6   2  18]
- [  7 130   9   2   3   3   5]
- [ 23  27 136  32  18  25  44]
- [ 10   2  25  86   8  10   3]
- [  3   3   7   1  62   0   3]
- [  7   2   2   0   1  45   8]
- [ 10   4  10  15   9  12  85]]
-Node Classification on random seed  9536 -> 0.6
-Confusion Matrix:
- [[ 52   1   3   8   3  12  10]
- [  2 141   6   2   3   7   5]
- [ 22  25 132  25  25  28  52]
- [ 15   2  16  90   2   7  27]
- [  1   8   1   3  55   3   3]
- [  5   0   7   0   0  48   1]
- [ 16   6   9   3   5  21  82]]
-Node Classification on random seed  9537 -> 0.641
-Confusion Matrix:
- [[ 78   2   4   3   5  12   9]
- [  3 137   8   6   4   1   3]
- [ 22  14 158  33  34  32  12]
- [ 17   1  17  99   7   7   9]
- [  1   6   6   5  58   0   4]
- [  2   4   1   1   2  39   8]
- [  9   6   5  15   3  16  72]]
-Node Classification on random seed  9538 -> 0.607
-Confusion Matrix:
- [[ 66   6   8   9   6   5  11]
- [  9 129   9   4  11   0   4]
- [ 21  22 151  32  23  36  14]
- [ 24   2  18  87   7  12  16]
- [  1   4   4   0  61   2   5]
- [  7   0   3   1   0  44   3]
- [ 18   7  10   4   2  13  69]]
-Node Classification on random seed  9539 -> 0.63
-Confusion Matrix:
- [[ 65   2   3   4   5   8  22]
- [  4 117   4   3   9   4   3]
- [ 18  21 145  47  21  16  46]
- [  2   4  13 119   3   2  14]
- [  2   9   4   2  58   1   5]
- [  2   1   0   0   1  50  10]
- [ 14   3  10   7   8  13  76]]
-Node Classification on random seed  9540 -> 0.606
-Confusion Matrix:
- [[ 83   2   1   3   5   7   9]
- [  6 124   4   4  15   4   1]
- [ 22  18 129  40  39  30  39]
- [  4   1  15 101   9   6  15]
- [  1   6   9   3  51   0   4]
- [  3   1   3   0   0  39   6]
- [ 21   1   5   8   9  15  79]]
-Node Classification on random seed  9541 -> 0.673
-Confusion Matrix:
- [[ 76   3   6   2   4  10   7]
- [  2 140   2   3   4   0   5]
- [ 15  10 156  30  26  27  30]
- [  8   3   7 112   5  15  11]
- [  0  10   2   0  67   5   3]
- [  2   1   1   0   0  57   5]
- [ 10   3  11   8   6  25  65]]
-Node Classification on random seed  9542 -> 0.564
-Confusion Matrix:
- [[ 71   3   4  12   4   4  22]
- [  8 140   4   2   3   5   7]
- [ 31  16 114  25  56  11  49]
- [  7   4  12  83   5   6  23]
- [  1   5   2   0  59   2   3]
- [  5   3   3   2   0  41  11]
- [ 23   2  10   8  21  12  56]]
-Node Classification on random seed  9543 -> 0.606
-Confusion Matrix:
- [[ 72   1   3   9   0  16   8]
- [  9 114   5   0  10  11   5]
- [ 30  15 145  33  18  33  34]
- [ 12   5  18 105   8  10  15]
- [  2   4   8   1  56   0   1]
- [  9   0   3   2   0  52   4]
- [  8   3   9   5   5  22  62]]
-Node Classification on random seed  9544 -> 0.653
-Confusion Matrix:
- [[ 87   3   5   5   5  13   3]
- [  1 128  10   2  10   1   5]
- [ 41  16 158  26  11  26  30]
- [ 13   1  20 107   2   6  13]
- [  1   3   3   1  55   0   3]
- [  4   2   3   2   1  47   7]
- [ 13   4   3   4   5  20  71]]
-Node Classification on random seed  9545 -> 0.654
-Confusion Matrix:
- [[ 81   1   9   5   5   5   6]
- [  6 123   7   2   8   0   9]
- [ 28  27 172  32  17  12  25]
- [ 20   5  17  96   6   2  11]
- [  2   4   7   0  60   0   3]
- [  5   4   4   0   0  45   3]
- [ 10   3  17   7   3   9  77]]
-Node Classification on random seed  9546 -> 0.612
-Confusion Matrix:
- [[ 69   0   4   8   0  21   9]
- [  8 121   7   3   7   4   3]
- [ 23  14 162  29  10  27  35]
- [ 15   1  22  77   1  20  15]
- [  3   3   5   1  71   0   5]
- [  4   3   9   1   1  50   3]
- [  9   3   5  13   8  26  62]]
-Node Classification on random seed  9547 -> 0.613
-Confusion Matrix:
- [[ 75   5   1   9   4  18   6]
- [  7 117   8   2   5   4   2]
- [ 26  23 146  28  15  39  39]
- [  8   5  21 105   9  11   5]
- [  3   4   2   2  50   1   3]
- [  6   0   0   1   2  45   3]
- [ 20   2   8   5   4  21  75]]
-Node Classification on random seed  9548 -> 0.608
-Confusion Matrix:
- [[ 55   2  10   5   2  10   4]
- [  8 118   5   2  14   1   8]
- [ 34  30 159  17  20  18  45]
- [ 26   1  16  91   2   9  12]
- [  0   2   5   2  64   0   5]
- [  9   0   3   1   0  45   6]
- [ 24   4   7   8   7   8  76]]
-Node Classification on random seed  9549 -> 0.619
-Confusion Matrix:
- [[ 75   3   0   3   4  15   7]
- [  5 124   5   5   5   4   2]
- [ 18  14 149  39  26  27  43]
- [  9   2   9  90   9  19  10]
- [  1   8   4   1  56   0   5]
- [  6   3   3   4   1  49   3]
- [ 10   1  11  10   5  22  76]]
-Node Classification on random seed  9550 -> 0.605
-Confusion Matrix:
- [[ 61   3   5   7   3  18  14]
- [  4 131   6   0   9   2   2]
- [ 20  20 138  39  34  26  33]
- [ 12   1  18  99   8   4  23]
- [  0   4   3   2  68   3   5]
- [  5   1   6   0   4  36   4]
- [  8   4   7   2   5  21  72]]
-Node Classification on random seed  9551 -> 0.574
-Confusion Matrix:
- [[ 70   4   4   1   1   5  10]
- [  8 139   9   0  10   4   4]
- [ 38  23 116  50  46  26  27]
- [ 21   9  15  74   4  11   7]
- [  3   8   2   1  54   1   2]
- [  2   2   2   0   1  45   2]
- [  9   4  15   6   8  21  76]]
-Node Classification on random seed  9552 -> 0.631
-Confusion Matrix:
- [[ 76   0   3   2   3  15  14]
- [  3 123   4   5  14   5   1]
- [ 21  22 161  30  29  29  41]
- [  7   0  19  89   3   5  19]
- [  0   3   1   1  62   1   4]
- [  4   0   1   0   4  37   2]
- [ 13   2  11   5   3  20  83]]
-Node Classification on random seed  9553 -> 0.598
-Confusion Matrix:
- [[ 86   0   9   3   5  14   7]
- [  5 133   5   0   4   2   2]
- [ 23  33 117  38  26  13  46]
- [ 10   8  16  96   7   9  23]
- [  2   9   1   4  53   0   1]
- [  6   5   5   3   2  38   3]
- [ 16   5   7   3   9  13  75]]
-Node Classification on random seed  9554 -> 0.626
-Confusion Matrix:
- [[ 70   1   3   5   4   8   5]
- [  8 150   6   7   4   0   2]
- [ 27  18 123  39  28  26  28]
- [  8   5  21  92   4  15   7]
- [  5   6   2   2  53   2   1]
- [  7   2   1   0   1  45   4]
- [ 17   6   6   7   5  21  93]]
-Node Classification on random seed  9555 -> 0.619
-Confusion Matrix:
- [[ 68   4   2  18   7   5  13]
- [  2 124   4   3   3   6   6]
- [ 30  27 146  25  17  14  39]
- [ 12   5  17 107   7   4  20]
- [  1   4   9   2  59   0   1]
- [  5   3   2   2   0  42   8]
- [  4   6   6  18   7  13  73]]
-Node Classification on random seed  9556 -> 0.64
-Confusion Matrix:
- [[ 76   1   7   4   5   4   6]
- [  2 139   6   2   9   1   4]
- [ 35  12 146  24  34  20  42]
- [ 11   2  15  92   8   3  12]
- [  1   8   1   1  69   2   2]
- [ 13   1   0   7   0  39   4]
- [  9   3  16   6   6  11  79]]
-Node Classification on random seed  9557 -> 0.613
-Confusion Matrix:
- [[ 74   4   9   9   6   8   2]
- [  5 110   4   6   7   4   1]
- [ 25  30 160  24  28  25  27]
- [ 12   3  20  85   9   5  16]
- [  1   4   6   0  61   1   4]
- [  4   0   7   4   1  39   8]
- [ 13   4  10   5   8  18  84]]
-Node Classification on random seed  9558 -> 0.583
-Confusion Matrix:
- [[ 87   2   5   2   6  14   5]
- [  4 117   6   4  14   9   0]
- [ 28  28 123  57  28  25  30]
- [ 11   8  13  86  16   6  16]
- [  1   8   4   3  45   0   0]
- [  3   2   3   0   2  43   7]
- [ 14   3   9   3   5  13  82]]
-Node Classification on random seed  9559 -> 0.602
-Confusion Matrix:
- [[ 63   6   7   8   5  13  13]
- [  4 126   6   2   8   2   4]
- [ 28  23 136  36  29  26  47]
- [  7   2   8 109   3   1  13]
- [  1   6   4   3  60   2   2]
- [  4   1   3   6   0  41   5]
- [ 18   2   8  15   3  14  67]]
-Node Classification on random seed  9560 -> 0.596
-Confusion Matrix:
- [[ 67   1   5   4   3  13   6]
- [  4 129   7   5   2   1   3]
- [ 27  16 129  58  32  15  47]
- [  8   5  29  90  10   6  10]
- [  2   5   5   0  62   2   2]
- [  7   1   3   2   0  41   1]
- [ 16   5   7   4  10  15  78]]
-Node Classification on random seed  9561 -> 0.621
-Confusion Matrix:
- [[ 70   5   7   1   2  16  14]
- [  5 115   5   3  10   4   2]
- [ 19  26 137  41  31  15  39]
- [  5   2  10 121  10   7  13]
- [  2  10   1   1  62   0   2]
- [  5   0   6   1   0  45   7]
- [  5   1  13   3   8  22  71]]
-Node Classification on random seed  9562 -> 0.613
-Confusion Matrix:
- [[ 76   0   0   3   4  17  11]
- [ 10 124  11   1   8   1  12]
- [ 33  13 153  18  31  19  48]
- [ 17   5  10  96   7   7  17]
- [  0   6   3   2  66   1   4]
- [ 11   2   2   0   1  39   4]
- [ 12   1   8   8   7  12  59]]
-Node Classification on random seed  9563 -> 0.612
-Confusion Matrix:
- [[ 75   2   8   4   7  12   6]
- [  8 116   4   4   7   3   3]
- [ 35  19 146  46  23  22  24]
- [ 19   0  12 115   4   1  17]
- [  1   6   6   2  48   0   2]
- [ 11   0   2   5   2  33   2]
- [ 16   4  18   8   7   6  79]]
-Node Classification on random seed  9564 -> 0.63
-Confusion Matrix:
- [[ 59   0   3   8   5  21   9]
- [  1 118   3   0  11   3   3]
- [ 18  28 169  36  25  33  31]
- [  3   4   8 111   3   7  10]
- [  1   4   7   0  63   0   2]
- [ 14   0   1   3   2  45   2]
- [ 11   2  14   9  11  14  65]]
-Node Classification on random seed  9565 -> 0.619
-Confusion Matrix:
- [[ 76   4   5   3   3  11   9]
- [  2 114   6   3   8   4  11]
- [ 18  22 151  28  24  29  41]
- [  8   6  19  89   9   8  16]
- [  0   6   1   3  63   4   7]
- [  5   1   0   0   0  41   6]
- [ 15   6   4   6   7  13  85]]
-Node Classification on random seed  9566 -> 0.63
-Confusion Matrix:
- [[ 71   4   1   5   2  14  15]
- [  5 135   9   0   8   7   3]
- [ 40  15 136  31  11  31  32]
- [ 15   3  11 101   4   7  13]
- [  1  15   4   1  61   1   0]
- [  9   1   4   0   8  37   5]
- [ 10   3   2   2  12   6  89]]
-Node Classification on random seed  9567 -> 0.571
-Confusion Matrix:
- [[ 76   3  10  11   9   9   5]
- [  2 112   4   2   9   1   5]
- [ 23  31 133  43  31  28  32]
- [  9   6  30  95   4   5  19]
- [  0   6   1   4  59   0   1]
- [  7   1   1   2   1  40   4]
- [ 25   6   9   4  18   8  56]]
-Node Classification on random seed  9568 -> 0.583
-Confusion Matrix:
- [[ 58   4   4   3   6  20   4]
- [  4 139   3   3   6   4   4]
- [ 27  24 113  38  31  30  52]
- [ 10  16  14 103   8   5  10]
- [  1   2   0   3  51   0   5]
- [  7   2   0   2   0  60   5]
- [ 17   1   4  11   9  18  59]]
-Node Classification on random seed  9569 -> 0.606
-Confusion Matrix:
- [[ 57   2   4   6   7  20  18]
- [  3 113   8   0  13   2   4]
- [ 19  24 146  35  25  27  36]
- [ 11   5  22 100   6   2  12]
- [  0   2   2   1  68   0   1]
- [  4   2   1   3   2  47   8]
- [ 10   2  10  13   6  16  75]]
-Node Classification on random seed  9570 -> 0.603
-Confusion Matrix:
- [[ 86   1   0   9   4   7   2]
- [  3 123   1   2   8   2   6]
- [ 39  29 123  48  32  15  17]
- [ 19   8  30  98   3   6  14]
- [  1   6   3   0  68   1   2]
- [ 10   1   2   1   0  47   4]
- [ 17   5   7  10   8  14  58]]
-Node Classification on random seed  9571 -> 0.635
-Confusion Matrix:
- [[ 71   4   2   4   4  15   3]
- [  0 122   6   4   1   6   1]
- [ 25  24 162  35  26  21  31]
- [ 18   8  10 103   9   8  11]
- [  1   7   2   1  65   0   0]
- [  3   0   4   2   0  41   8]
- [  7  12   5   2   7  28  71]]
-Node Classification on random seed  9572 -> 0.646
-Confusion Matrix:
- [[ 71   7   3   8   6   3   5]
- [  3 124   3   2   8   2   2]
- [ 24  23 164  33  32  17  20]
- [ 20   2  21  93   4   8   8]
- [  2   4   6   5  72   0   5]
- [  2   0   7   2   2  33   2]
- [ 14   2   9  14   3  11  89]]
-Node Classification on random seed  9573 -> 0.647
-Confusion Matrix:
- [[ 55   9   6   4   6  12  11]
- [  7 139   5   1   5   3   0]
- [ 15  21 165  27  26  19  30]
- [ 14   7  11 109   1   7  19]
- [  4   8   6   1  51   1   3]
- [  4   5   3   0   0  48   3]
- [  6   6   8   7   4  18  80]]
-Node Classification on random seed  9574 -> 0.609
-Confusion Matrix:
- [[ 71   4   6  13   5   8   7]
- [ 13 123   3   4   8   6   1]
- [ 19  30 137  19  30  26  44]
- [ 13   7  24  97  11   3   8]
- [  2   9   5   0  57   2   1]
- [  4   2   0   2   0  53   3]
- [ 12   3   8   2   7  17  71]]
-Node Classification on random seed  9575 -> 0.609
-Confusion Matrix:
- [[ 82   2   3   3   5   8   4]
- [  3 118   2   4  14   0   6]
- [ 38  23 124  27  36  32  35]
- [ 11   0  12 104  15   6   4]
- [  3   4   1   2  59   2   3]
- [  4   5   5   2   0  50   1]
- [ 12   3  14  13   5  19  72]]
-Node Classification on random seed  9576 -> 0.575
-Confusion Matrix:
- [[ 84   4   6   6   2  12   9]
- [  0 139   6   6  13   4   5]
- [ 35   7 109  38  47  31  41]
- [ 13   6   7  75   8  16  18]
- [  1   4   3   1  58   0   3]
- [  2   1   2   1   1  47   8]
- [  8   7   8  15  10  10  63]]
-Node Classification on random seed  9577 -> 0.618
-Confusion Matrix:
- [[ 77   3   7   3   4  12  10]
- [  4 120  10   7  14   1   2]
- [ 21  18 130  40  17  13  51]
- [ 14   1  20  94   5   3   9]
- [  2   5   2   3  72   0   1]
- [  4   3   3   0   3  48   7]
- [ 16  13   8   5   3  15  77]]
-Node Classification on random seed  9578 -> 0.645
-Confusion Matrix:
- [[ 75   3   6   3   5  19   2]
- [  5 124   6   9   6   0   1]
- [ 14  17 157  35  25  43  30]
- [ 13   4  12 115   5   3  13]
- [  0   4   4   6  55   0   1]
- [  9   1   1   0   0  44   2]
- [ 16   1  10   2   3  16  75]]
-Node Classification on random seed  9579 -> 0.654
-Confusion Matrix:
- [[ 63   3   5   2   5   3  18]
- [  2 135  10   2   6   4   9]
- [ 29  23 154  24  25  18  37]
- [  3   5   6 117  12   4  16]
- [  0   6   4   1  56   1   0]
- [  4   2   3   2   0  51   2]
- [  8   9   6   2   8  17  78]]
-Node Classification on random seed  9580 -> 0.627
-Confusion Matrix:
- [[ 81   2   4   1   2  10   8]
- [  4 117   3   3   4   2  10]
- [ 16  17 150  39  44  19  35]
- [ 13   4  19 101  11   3  12]
- [  1   7   4   3  69   2   3]
- [  5   1   3   6   1  41   4]
- [ 11   2  14   9   1  11  68]]
-Node Classification on random seed  9581 -> 0.604
-Confusion Matrix:
- [[ 70   6   1   7   3  12   6]
- [  6 128   4   0  11   3   4]
- [ 28  18 133  30  41  44  33]
- [ 10   3  12 106   4   9  18]
- [  1   9   1   1  50   2   4]
- [  8   3   1   0   1  39   6]
- [ 19   1   8   5   8   5  78]]
-Node Classification on random seed  9582 -> 0.615
-Confusion Matrix:
- [[ 66   2   7   3   8   5   4]
- [ 12 135   3   5   8   9   2]
- [ 30  28 141  28  26  29  24]
- [ 24   3  18  84   9   4  18]
- [  0   6   7   0  60   1   2]
- [  5   3   0   0   0  53   3]
- [  7   3   3  17   8  11  76]]
-Node Classification on random seed  9583 -> 0.597
-Confusion Matrix:
- [[ 55   3   2   7   5   5  15]
- [  6 141   2   5   6   5   4]
- [ 31  15 151  29  36  21  48]
- [  7   3  14 105   2  16  15]
- [  2   8   6   2  48   0   3]
- [  6   1   2   1   3  43   3]
- [ 21   6   4   4  13  16  54]]
-Node Classification on random seed  9584 -> 0.637
-Confusion Matrix:
- [[ 69   0   7  11   7  14   4]
- [  1 134   4   5  12   3   2]
- [ 37  21 150  28  37   5  36]
- [  4   4  17  99   6   2   8]
- [  2   6   0   6  70   0   4]
- [  6   0   0   4   1  44  12]
- [  6   1  13  15   7   5  71]]
-Node Classification on random seed  9585 -> 0.625
-Confusion Matrix:
- [[ 67   3   5   5   1  19  11]
- [  5 124   7   2   6   3   1]
- [ 21  22 153  37  24  14  52]
- [  6   4  17 110   3   4  13]
- [  1   1   3   3  54   1   3]
- [ 13   0   0   1   1  35  11]
- [ 22   7   8   5   8   2  82]]
-Node Classification on random seed  9586 -> 0.617
-Confusion Matrix:
- [[ 82   1   3   1   5   6  18]
- [ 16 122  13   1   6   5   2]
- [ 28  15 122  61  25  15  34]
- [  9   2  11  95   4   6   5]
- [  3   6   2   2  61   0   1]
- [ 15   1   1   1   2  42   1]
- [ 10   4  10   4  10  18  93]]
-Node Classification on random seed  9587 -> 0.606
-Confusion Matrix:
- [[ 55   2   5   4   3  14   3]
- [  7 143   6   4   4   0   4]
- [ 19  23 153  45  36  14  22]
- [  2   6  31  91   2   9  23]
- [  3   6   2   1  57   1   4]
- [ 17   5   3   3   0  27   5]
- [ 13  12   9   8   5   9  80]]
-Node Classification on random seed  9588 -> 0.61
-Confusion Matrix:
- [[ 55   6   4   2   2  17   8]
- [  2 134   6   5   7   0   9]
- [ 20  34 145  38  17  30  31]
- [  2  14  22  98   3   8  13]
- [  1  12   1   3  58   0   5]
- [  2   4   1   1   3  50   3]
- [  2   9   7   6   9  21  70]]
-Node Classification on random seed  9589 -> 0.64
-Confusion Matrix:
- [[ 68   1   1   2   6  17  15]
- [ 10 124   3   4   6   1   9]
- [ 32   9 157  33  14  12  47]
- [ 17   6  11 101   8   6   8]
- [  0   7   6   2  62   0   5]
- [  7   2   1   0   1  52   4]
- [  7   5   0  15   7  13  76]]
-Node Classification on random seed  9590 -> 0.584
-Confusion Matrix:
- [[ 56   9   6   2   3  11  16]
- [  5 143  10   3   0   2   4]
- [ 35  30 130  36  24  22  30]
- [ 29   5  21  78  13   8   2]
- [  0   8   8   2  56   1   1]
- [  7   2   2   5   0  41   4]
- [ 12   1   7  13  10   7  80]]
-Node Classification on random seed  9591 -> 0.6
-Confusion Matrix:
- [[ 55   2   7   1   3  22  16]
- [  6 118   8   2  16  12   2]
- [ 24  23 143  28  25  32  33]
- [  9   2  16 112   4   5   6]
- [  0   6   2   4  52   1   6]
- [  7   5   3   7   1  39   6]
- [  4   3   6   7   9  19  81]]
-Node Classification on random seed  9592 -> 0.594
-Confusion Matrix:
- [[ 57   6   5   3   9  10  16]
- [  6 134   9   1   1   3   5]
- [ 22  26 133  53  18  19  50]
- [ 13   2  20 102   2   3  10]
- [  1   9   4   0  57   0   4]
- [ 13   0   1   1   0  39   4]
- [ 11   3  18   3   7  15  72]]
-Node Classification on random seed  9593 -> 0.613
-Confusion Matrix:
- [[ 65   3   4   4   3  12  11]
- [  0 121   7   2  10   4   4]
- [ 27  28 123  41  23  21  35]
- [ 23   4   9 113  11   6   5]
- [  3   5   6   4  64   1   0]
- [  6   0   1   1   6  40   6]
- [  6   4   1  24   7   9  87]]
-Node Classification on random seed  9594 -> 0.598
-Confusion Matrix:
- [[ 70   1   4   6   3   3  11]
- [ 11 139   5   0   6   2   1]
- [ 43  19 129  44  36  21  31]
- [  8   6  18  90   2   8  18]
- [  3   3   3   2  67   3   0]
- [ 12   0   3   0   0  38  13]
- [ 13   4   9  10  10   7  65]]
-Node Classification on random seed  9595 -> 0.593
-Confusion Matrix:
- [[ 60   6   0   3  13  19   8]
- [  3 141   4   1  11   3   2]
- [ 18  30 120  52  26  24  29]
- [ 18   5  10 107   8  15   8]
- [  1   6   5   1  65   5   3]
- [  2   1   3   0   0  31   5]
- [  8   4  11  14   8  14  69]]
-Node Classification on random seed  9596 -> 0.611
-Confusion Matrix:
- [[ 84   3   1   3   3  14   7]
- [  5 139   4   1   9   1   2]
- [ 30  29 117  35  55  18  26]
- [ 18   2  27 101   6   4   5]
- [  0   8   2   2  55   2   2]
- [  4   0   4   0   1  41   5]
- [ 17   2  14   7   4   7  74]]
-Node Classification on random seed  9597 -> 0.63
-Confusion Matrix:
- [[ 64   4   5  10   3  17  10]
- [  7 154   6   2   5   1   6]
- [ 26  19 148  33  25  15  23]
- [ 15   4  19 102   4   9  10]
- [  1   6   1   0  60   1   1]
- [ 14   4   0   4   4  28   6]
- [ 12   4   8   8   6  12  74]]
-Node Classification on random seed  9598 -> 0.602
-Confusion Matrix:
- [[ 75   0   5   4   6   4  10]
- [  6 111  11   5  18   3   8]
- [ 18  19 147  42  49  19  33]
- [ 17   2   7  99  13   5  12]
- [  0   1   1   1  59   0   4]
- [  6   0   6   1   3  43   5]
- [ 12   0  22   8   5   7  68]]
-Node Classification on random seed  9599 -> 0.613
-Confusion Matrix:
- [[ 66   1   1   2   8  17  13]
- [  5 128   3   3   6   4  10]
- [ 16  20 141  46  19  32  34]
- [  8   2  20  90   8   3  14]
- [  0  16   3   2  63   1   4]
- [  1   2   0   5   0  53   7]
- [  5   7  12   4   3  20  72]]
-Node Classification on random seed  9600 -> 0.615
-Confusion Matrix:
- [[ 59   1   0  10   0  14  19]
- [  9 127   2   5   7   4   0]
- [ 18  16 148  31  47  19  47]
- [  7   2  25  84   8   5  12]
- [  1   6   5   7  53   0   2]
- [  7   3   1   3   0  56   7]
- [  5   4   4   7  10   5  88]]
-Node Classification on random seed  9601 -> 0.641
-Confusion Matrix:
- [[ 83   2   3   2   2   9  13]
- [  3 119  14   2  12   5   1]
- [ 27  19 159  24  31  15  41]
- [  5   3  12 102   3   3  26]
- [  1   3   2   0  58   2   4]
- [  1   1   6   1   1  46   4]
- [ 17   3   5   7  14  10  74]]
-Node Classification on random seed  9602 -> 0.59
-Confusion Matrix:
- [[ 69   2   4   7   2  14  12]
- [  2 130   3   8  14   2   5]
- [ 27  18 150  23  25  28  24]
- [ 13   7  23  94  13   3  19]
- [  3   9   3   7  55   2   1]
- [ 10   2   0   5   0  40   4]
- [ 28   4  10   9   4  11  52]]
-Node Classification on random seed  9603 -> 0.663
-Confusion Matrix:
- [[ 79   3   5   2   4  12  13]
- [  4 146   2   1   5   0   9]
- [ 19  16 155  15  20  35  40]
- [  6   4  18  92   6   7   7]
- [  3   8   7   3  60   3   3]
- [  6   1   1   0   0  48   5]
- [ 11   3   6   4   6  14  83]]
-Node Classification on random seed  9604 -> 0.588
-Confusion Matrix:
- [[ 63   2   2   5   4  11  11]
- [  5 117   5   4   8   3   7]
- [ 41  15 128  31  42  31  51]
- [  5   2   7  90   6  16  21]
- [  3   4   2   1  58   0   3]
- [  8   0   2   3   0  35   7]
- [  7   2  12   8   8   7  97]]
-Node Classification on random seed  9605 -> 0.565
-Confusion Matrix:
- [[ 65   2  10   7  10  11  13]
- [  9 130  12   2   6   1   5]
- [ 22  12 127  39  30  24  48]
- [ 17   0  20  89   7   3  15]
- [  0   6   0   2  54   0   3]
- [  6   2   3   8   7  43   5]
- [ 14   3  14   7   6  24  57]]
-Node Classification on random seed  9606 -> 0.597
-Confusion Matrix:
- [[ 70   5   4   6  10  14   3]
- [  3 130   8   1   8   3  11]
- [ 30   9 133  48  23  25  38]
- [ 10   4  13  83  13   8  18]
- [  1   5   7   0  58   1   4]
- [  4   2   6   1   3  33   4]
- [ 15   2  11   3   8  11  90]]
-Node Classification on random seed  9607 -> 0.589
-Confusion Matrix:
- [[ 70   4   5   4   3  10  12]
- [  5 139   1   0  10   2   7]
- [ 24  33 130  56  23  15  44]
- [ 14   6  26  94   1   6   6]
- [  1   7   3   0  60   1   3]
- [  0   3   1   2   0  43  10]
- [ 11   7   9  18   7  11  53]]
-Node Classification on random seed  9608 -> 0.582
-Confusion Matrix:
- [[ 85   4   7   1   1  15   4]
- [  3 130   4   3   3   1  13]
- [ 19  32 124  40  13  37  39]
- [ 18   4  29  69   4   7   7]
- [  0   9   6   0  61   1   4]
- [  7   8   5   0   2  45   3]
- [ 14   7   7   1   4  32  68]]
-Node Classification on random seed  9609 -> 0.583
-Confusion Matrix:
- [[ 71   2  14   5   2   3  10]
- [  4 114  16   7   5   6   5]
- [ 10   8 155  40  19  25  58]
- [  9   2  15  83  17  14  17]
- [  0   6   5   0  54   3   7]
- [ 12   2   4   2   0  32   2]
- [ 14   3  22   5   6  11  74]]
-Node Classification on random seed  9610 -> 0.59
-Confusion Matrix:
- [[ 74   6  13   2   1  13   6]
- [  5 126   6   0   7   4   3]
- [ 47  21 124  40  17  42  27]
- [ 16   3  11 102   2  11  13]
- [  2   2   3   2  59   3   6]
- [  7   4   3   1   0  37   1]
- [ 11   7  10  14   1  17  68]]
-Node Classification on random seed  9611 -> 0.641
-Confusion Matrix:
- [[ 80   2   2   2   4  10   6]
- [  5 132   1   2   6   2   3]
- [ 28  28 144  24  54  11  41]
- [ 17   4  10  98   3   5   5]
- [  1   7   1   1  70   1   0]
- [ 10   2   3   1   0  45   4]
- [ 17   1  13   4   4  14  72]]
-Node Classification on random seed  9612 -> 0.64
-Confusion Matrix:
- [[ 70   2   6   4   4  11  18]
- [  5 112   3   1  15   3   8]
- [ 26  14 151  38  24  25  36]
- [  7   3  14 128   1   5  16]
- [  0   4   5   0  59   1   4]
- [  3   2   1   0   0  47   4]
- [  5   1  10   6   4  21  73]]
-Node Classification on random seed  9613 -> 0.654
-Confusion Matrix:
- [[ 70   2   4   5   7  16   3]
- [  3 126  12   5   8   2   4]
- [ 12  15 185  30  14  16  40]
- [  7   4  24  77   9   1  25]
- [  0   7   7   5  57   0   4]
- [  3   2   3   1   1  47   3]
- [ 18   7   2   2   7   6  92]]
-Node Classification on random seed  9614 -> 0.608
-Confusion Matrix:
- [[ 77   1   5   6   4   9   9]
- [  3 148   5   7   4   2   3]
- [ 18  31 144  31  21  28  24]
- [ 14   8  13  77  17   5  13]
- [  1   9   8   2  58   0   3]
- [  3   1   4   8   1  36   5]
- [ 14   8   5  11   4  24  68]]
-Node Classification on random seed  9615 -> 0.638
-Confusion Matrix:
- [[ 63   4   5   8   3   7   1]
- [  5 132   4   0   6   4   6]
- [ 36  15 152  28  28  26  37]
- [ 17   2  16 100   3   2  21]
- [  0   4   2   0  67   1   3]
- [  5   1   0   3   1  55   2]
- [ 17   3  13   8   2  13  69]]
-Node Classification on random seed  9616 -> 0.658
-Confusion Matrix:
- [[ 69   2   3   1   4  13   9]
- [  3 113   9   0  12   1  11]
- [  9  28 173  23  38  22  28]
- [ 13   4   9 106   4   3  10]
- [  2   3   2   3  68   1   1]
- [  1   2   8   1   0  42   5]
- [  7   3  21   4   7  12  87]]
-Node Classification on random seed  9617 -> 0.59
-Confusion Matrix:
- [[ 56   2   5  12   2  10  14]
- [  9 140   5   4   2   0   5]
- [ 31   6 135  43  30  25  42]
- [ 17   8  10 107   7   5  15]
- [  3   9   3   3  50   0   5]
- [  3   1   5   5   1  42   4]
- [ 20   3   7  10   7  12  60]]
-Node Classification on random seed  9618 -> 0.597
-Confusion Matrix:
- [[ 64   1  14   2   3  14   8]
- [  3 136   5   3   5   3   7]
- [ 21  23 120  36  24  19  59]
- [ 21   2  23 103   4   6  12]
- [  1   6   2   1  54   2   6]
- [  2   4   5   0   3  38   8]
- [ 11   5  14   2   9   4  82]]
-Node Classification on random seed  9619 -> 0.627
-Confusion Matrix:
- [[ 68   5   5   7   6   8   7]
- [  6 134   6   2   6   4   3]
- [ 17  33 161  42  10  23  31]
- [  6   7  16  97   8   6  16]
- [  1   8   5   4  60   0   0]
- [ 10   2   3   1   0  46   0]
- [ 17   5   3   7  11  16  61]]
-Node Classification on random seed  9620 -> 0.616
-Confusion Matrix:
- [[ 73   2   2   1   5  13   7]
- [  5 125  10   0   5   4   5]
- [ 19  34 135  38  31  23  37]
- [  8   5  14 101   3  10   5]
- [  1   2   7   3  62   0   1]
- [ 12   2   1   4   2  38   8]
- [ 10   2   5  23   7   8  82]]
-Node Classification on random seed  9621 -> 0.646
-Confusion Matrix:
- [[ 68   2   2   6   4   9  11]
- [  2 120   5   1   1   3   5]
- [ 40  22 159  34  14  11  37]
- [ 14   1  10 121   5   4  17]
- [  2   4   6   2  56   0   2]
- [  6   2   2   1   4  44   8]
- [ 20   6   7   5   7  10  78]]
-Node Classification on random seed  9622 -> 0.621
-Confusion Matrix:
- [[ 60  11   1   1   2  11  18]
- [  9 145   5   6  13   2   5]
- [ 31   9 127  25  36  23  42]
- [ 11   4  22 105   5   4   5]
- [  4   7   2   2  58   1   5]
- [  5   6   2   0   0  51   6]
- [ 18   1   3   5   2   9  75]]
-Node Classification on random seed  9623 -> 0.617
-Confusion Matrix:
- [[ 67   2   6   2   0  14   9]
- [  8 142   4   2   3   1   5]
- [ 14  22 129  38  34  31  44]
- [ 10   2  12  97   6   5  17]
- [  0  12   4   2  56   0   2]
- [  5   0   5   0   0  46   7]
- [  7   7   6   7  10  18  80]]
-Node Classification on random seed  9624 -> 0.602
-Confusion Matrix:
- [[ 83   3   3   6   5  14   9]
- [  1 133   6   5   6   4   4]
- [ 27  23 138  42  26  17  43]
- [ 22   5  18  83   4  11  10]
- [  1   5   2   0  54   2   0]
- [ 10   0   1   2   0  34   7]
- [ 17   5   9   3   6  14  77]]
-Node Classification on random seed  9625 -> 0.586
-Confusion Matrix:
- [[ 88   2   1   5   2  22   4]
- [  6 125   3   2  16   0   2]
- [ 25  17 126  41  58  26  17]
- [ 15   1  11  85  12   7  19]
- [  7   6   2   2  65   0   0]
- [ 10   3   0   4   3  42   0]
- [ 19   5   4   7   6  22  55]]
-Node Classification on random seed  9626 -> 0.521
-Confusion Matrix:
- [[ 71   2   7   6   3  17   5]
- [  4 113   5   3   7   7   3]
- [ 34  23  93  34  39  26  58]
- [ 25   7  10  85  12   9  10]
- [  2   4   3   4  47   0   7]
- [ 11   1   7   4   1  40   5]
- [ 17   3   7   8  14  25  72]]
-Node Classification on random seed  9627 -> 0.586
-Confusion Matrix:
- [[ 53   8   2  10   5   8  12]
- [  5 110   9   2   2   2   8]
- [ 36  21 149  53  30  11  29]
- [ 18   6  24  97   5   3  17]
- [  3   4   3   1  57   0   1]
- [  8   4   0   0   7  39   4]
- [ 12   1  11   4   6  19  81]]
-Node Classification on random seed  9628 -> 0.586
-Confusion Matrix:
- [[ 75   0   2   6   2   9  18]
- [ 10 135   7   5  10   0   5]
- [ 32  16 134  23  21  21  58]
- [ 13   3  17  83   7  10  21]
- [  6   7   7   0  48   2   3]
- [ 10   1   3   2   0  45   5]
- [ 19   3   6  11   7   6  66]]
-Node Classification on random seed  9629 -> 0.634
-Confusion Matrix:
- [[ 88   1   7   2   2  14   2]
- [  6 131   7   2   8   3   1]
- [ 18  17 138  25  34  24  33]
- [ 32   3  14  92   9   7  14]
- [  1   5   2   3  55   0   0]
- [  0   0   2   3   2  54   8]
- [ 11   1  10   4   7  22  76]]
-Node Classification on random seed  9630 -> 0.618
-Confusion Matrix:
- [[ 63   2   1   7   8  11  16]
- [  2 131   7   4   6   2   2]
- [ 28  22 154  24  30  19  38]
- [ 17   1  13  91   1   3  25]
- [  0  10   2   0  68   1   2]
- [  9   3   3   3   4  43   4]
- [  3   7   6   8   7  21  68]]
-Node Classification on random seed  9631 -> 0.628
-Confusion Matrix:
- [[ 57   1   0  16   1  13  17]
- [  4 114   4   2   7   7   8]
- [ 22  20 154  31  37  31  30]
- [  9   2  14 112   7   4  13]
- [  0   5   1   2  62   0   3]
- [  4   3   0   1   1  49   5]
- [  9   6   8   5   4  15  80]]
-Node Classification on random seed  9632 -> 0.59
-Confusion Matrix:
- [[ 69   4   6   9   4   9   8]
- [  6 137   4   1   8   6   5]
- [ 21  13 136  34  32  19  45]
- [ 18   4  28  70  13   4  15]
- [  5   4   5   1  58   2   3]
- [  7   0   0   3   2  47   4]
- [ 19   1  13  10   2  13  73]]
-Node Classification on random seed  9633 -> 0.652
-Confusion Matrix:
- [[ 63   3   5   8   4  11  12]
- [  2 145   3   3   8   5   2]
- [ 14  21 145  29  20  22  55]
- [  9   3  11 111   9   4   9]
- [  1   3   6   0  63   1   3]
- [  4   0   0   0   1  46   8]
- [ 14   3   7   3  10  12  79]]
-Node Classification on random seed  9634 -> 0.63
-Confusion Matrix:
- [[ 87   4   5   7   3  10   2]
- [  3 124   3   1   4   5   6]
- [ 25  35 143  24  22  14  44]
- [  9   5  16 107   2   5  15]
- [  3  10   4   2  55   3   2]
- [  4   1   3   3   1  45   2]
- [ 20   3   6  10   8  16  69]]
-Node Classification on random seed  9635 -> 0.616
-Confusion Matrix:
- [[ 69   1   1   5   2  16   8]
- [  4 138   2   4   4   2   3]
- [ 28  24 119  46  51  14  33]
- [ 21   8   9 103   6   3   5]
- [  6   4   1   4  64   0   2]
- [  3   0   1   1   4  50   6]
- [  4   4  12   8   5  19  73]]
-Node Classification on random seed  9636 -> 0.647
-Confusion Matrix:
- [[ 85   2   7   5   5  12   9]
- [  4 127   6   6  19   0  11]
- [ 13  17 161  31  27  14  42]
- [  7   1  12  91   9   2  10]
- [  1   5   3   2  57   2   1]
- [  8   1   4   3   0  37   5]
- [ 16   5   6   5   7   8  89]]
-Node Classification on random seed  9637 -> 0.615
-Confusion Matrix:
- [[ 72   2   2   7   4  15  10]
- [ 12 118   3   5  11   7   3]
- [ 35  27 149  26  15  13  39]
- [  8  10  26 100  10   6   8]
- [  1   3   3   1  60   0   5]
- [  3   1   1   0   0  51   3]
- [ 12   4   8   7   8  21  65]]
-Node Classification on random seed  9638 -> 0.618
-Confusion Matrix:
- [[ 80   1   1   1   3   9   7]
- [ 13 111   3   1   9   8   5]
- [ 21  22 132  63  21  18  37]
- [  8   6  10 112   4   8  13]
- [  0   6   4   2  59   2   0]
- [ 11   2   1   1   0  49   5]
- [ 12   2   7   9   8  18  75]]
-Node Classification on random seed  9639 -> 0.599
-Confusion Matrix:
- [[ 61   2   5   3   5  22   2]
- [  2 124   2  11  16   1  10]
- [ 21  17 132  25  39  26  51]
- [  8   2  15  94   6   4  23]
- [  1   2   5   1  62   4   4]
- [  9   2   1   0   0  49   3]
- [ 11   3   5   2   6  24  77]]
-Node Classification on random seed  9640 -> 0.604
-Confusion Matrix:
- [[ 67   0   2   6   7  23  10]
- [  8 123  14   4   5   3   2]
- [ 14  24 134  27  28  28  45]
- [  5   6  14 100   8   5  10]
- [  1   5   7   1  57   1   3]
- [  1   0   2   3   0  54   3]
- [  7   8   9  18   7  22  69]]
-Node Classification on random seed  9641 -> 0.595
-Confusion Matrix:
- [[ 77   3   1   7   3   5   9]
- [  4 128  15   1   5   2   1]
- [ 36  28 129  26  19  15  47]
- [ 15   6  19  90   8   3  15]
- [  2  15   6   5  54   2   1]
- [  9   1   5   0   2  46   6]
- [ 19   9   7   4   7  12  71]]
-Node Classification on random seed  9642 -> 0.603
-Confusion Matrix:
- [[ 89   1   3   3   2   6  19]
- [  1 114  10   3   5   6   4]
- [ 31  25 104  64  23  20  47]
- [ 22   5  10 110   3   2  10]
- [  0   6   4   1  62   0   1]
- [  7   2   2   1   0  51   5]
- [  8   4   6   5   4  16  73]]
-Node Classification on random seed  9643 -> 0.583
-Confusion Matrix:
- [[ 68   1  11   3   5   2  18]
- [  4 119   7   4   8   0   6]
- [ 15  19 127  40  74  13  50]
- [  6   4  17  84   6   8  21]
- [  0   7   1   5  50   1   4]
- [  8   1   1   1   0  37   3]
- [  9   4  12   3   8   7  98]]
-Node Classification on random seed  9644 -> 0.612
-Confusion Matrix:
- [[ 70   1   4   3   1   9  17]
- [  4 144  13   6   3   0   3]
- [ 22  23 122  51  22  13  58]
- [  6   7  19 110   2   5   7]
- [  0   6   4   7  47   0   2]
- [  6   2   0   4   1  33   5]
- [  6  11   8  12   8   7  86]]
-Node Classification on random seed  9645 -> 0.607
-Confusion Matrix:
- [[ 67   0   4   3  10  12   9]
- [  7 114   0   6  15   0   1]
- [ 14  29 131  37  40  11  44]
- [ 11   4  19  98   3   8   5]
- [  3   9   5   2  66   0   1]
- [  5   2   2   1   2  46   9]
- [  9   5   8  19   7  12  85]]
-Node Classification on random seed  9646 -> 0.574
-Confusion Matrix:
- [[ 64   2   8   2   2  14  11]
- [  8 111   9   8  10   0   4]
- [ 19  23 136  74  29  20  42]
- [ 18   1   4  90  10   6  18]
- [  1   8   1   1  55   0   1]
- [  3   1   1   3   1  50   3]
- [  8   3   9  13  10  17  68]]
-Node Classification on random seed  9647 -> 0.618
-Confusion Matrix:
- [[ 73   3   8   4   2  11   2]
- [  6 123   3   4   6   3   5]
- [ 25   7 144  39  31  17  45]
- [ 16   2  20  84  10   4  13]
- [  2   3   2   1  66   1   5]
- [  6   2   2   0   0  56   4]
- [ 22   2   5  11   9  19  72]]
-Node Classification on random seed  9648 -> 0.616
-Confusion Matrix:
- [[ 70   0   5  12   7   6   8]
- [  1 136   3   4   9   5   8]
- [ 19  24 143  38  26  12  28]
- [ 36   3  18  90   4   6  10]
- [  1   4   6   3  68   1   3]
- [  5   3   3   4   0  41   7]
- [ 11   4  12  10   4  11  68]]
-Node Classification on random seed  9649 -> 0.6
-Confusion Matrix:
- [[ 58   7   2   5   1  15  17]
- [  6 124   4   5   7   4   3]
- [ 24  21 144  43  23  22  42]
- [  3  10  17 106   2  13   9]
- [  1   8   8   0  59   1   3]
- [  5   6   2   0   1  41   9]
- [ 13   3   9   2   9  15  68]]
-Node Classification on random seed  9650 -> 0.596
-Confusion Matrix:
- [[ 73   3   7   4   5  18   5]
- [  3 116   5   6   9   1   2]
- [ 28  30 144  27  28  26  34]
- [ 10   6  21  88  10   3  16]
- [  1   5   6   1  59   2   0]
- [  5   2   1   3   0  46   1]
- [ 12   5   5   9   8  31  70]]
-Node Classification on random seed  9651 -> 0.609
-Confusion Matrix:
- [[ 73   3  13   9   7   9   7]
- [  4 128   9  19   8   1   3]
- [ 27  12 159  26  36  27  37]
- [  6   8   9 103   8   5   9]
- [  1   5   0   2  60   1   2]
- [  4   2   2   1   2  36   1]
- [ 12   3  13   4  13  21  50]]
-Node Classification on random seed  9652 -> 0.626
-Confusion Matrix:
- [[ 76   2   9   3   5   8  10]
- [  4 140   5   2  14   3   1]
- [ 27  14 138  26  35  23  40]
- [ 15   3  19  85   4   5  23]
- [  2   6   2   0  52   3   1]
- [  6   0   1   1   0  39   5]
- [  6   3   9   7  11  11  96]]
-Node Classification on random seed  9653 -> 0.602
-Confusion Matrix:
- [[ 60   2   2  10   5   7   9]
- [  0 121   3   1  11   5   5]
- [ 22  25 128  42  52  23  26]
- [  8   2  22 111   7   6   8]
- [  1   6   1   2  69   0   4]
- [  6   1   4   2   0  47   7]
- [ 16   2  10  11   7  15  66]]
-Node Classification on random seed  9654 -> 0.626
-Confusion Matrix:
- [[ 74   1   5   2   4  18  12]
- [  7 120   5   2  14   5   1]
- [ 16   9 153  41  22  24  42]
- [ 10   3  14  90   9   5  19]
- [  0   6   6   2  62   0   0]
- [  2   0   3   2   2  51   6]
- [ 12   5   8   1  12  17  76]]
-Node Classification on random seed  9655 -> 0.626
-Confusion Matrix:
- [[ 47   2   2  19   4   9  16]
- [  4 131  10   3   6   0   3]
- [ 24  23 149  23  29  22  34]
- [ 10   1  16  94  10   6  21]
- [  7   4   4   0  61   1   1]
- [  4   1   4   6   1  49   4]
- [  8   2   6   8   6  10  95]]
-Node Classification on random seed  9656 -> 0.618
-Confusion Matrix:
- [[ 84   1   5   4   4  11  12]
- [  3 123   5   9  13   1   7]
- [ 22  33 144  19  24  23  41]
- [  6   5  23  96   7   7  13]
- [  1   7   3   1  60   1   4]
- [  3   5   4   1   1  44   4]
- [  7   4  15   6   6  11  67]]
-Node Classification on random seed  9657 -> 0.607
-Confusion Matrix:
- [[ 60   5  19   2   3   9   7]
- [  4 118  11   2   7   0   3]
- [ 33   9 140  71  22  13  29]
- [  9   4   9 113   2   5  16]
- [  6   1   6   3  63   0   2]
- [  4   1   5   1   4  39   5]
- [ 12   1  14  13   4  17  74]]
-Node Classification on random seed  9658 -> 0.58
-Confusion Matrix:
- [[ 75   1   4   4   3   7  21]
- [ 13 117   9   3  15   3   5]
- [ 38  34 122  43  24  30  20]
- [ 11   1  11  89   6  11  17]
- [  5   1   7   1  56   0   4]
- [  6   2   2   0   0  46   4]
- [ 12   3   9   4   6  20  75]]
-Node Classification on random seed  9659 -> 0.606
-Confusion Matrix:
- [[ 80   2   6  16   6  10   2]
- [ 10 128   4   1  13   0   9]
- [ 19  31 151  35  12  17  41]
- [ 10   5  13 100   1   7  25]
- [  0   5   7   0  52   4   3]
- [  4   1   2   2   1  38   4]
- [ 19   2   5   6  11  23  57]]
-Node Classification on random seed  9660 -> 0.627
-Confusion Matrix:
- [[ 85   4   1   3   1   7  10]
- [  2 137   2   6   2   1   2]
- [ 28  22 129  27  19  30  50]
- [ 16   5  13  94   6   6  14]
- [  3   5   7   0  66   2   2]
- [  9   2   3   2   0  49   7]
- [ 15   6   7   4  10  12  67]]
-Node Classification on random seed  9661 -> 0.617
-Confusion Matrix:
- [[ 59   2   1   2  12  17  18]
- [  1 149   1   5  10   3   2]
- [ 14  30 136  27  14  33  52]
- [ 17   5   8  93  11   5  18]
- [  1   9   1   3  63   2   1]
- [  3   1   1   1   0  46   5]
- [  7   4   4   4   8  20  71]]
-Node Classification on random seed  9662 -> 0.607
-Confusion Matrix:
- [[ 56   4   9   6   0  16   9]
- [  8 124   7   0   2   2   6]
- [ 39  32 160  24  14  20  32]
- [ 13   5  17  88   4   4  15]
- [  4  10   8   0  49   2   4]
- [  9   0   7   3   0  42   6]
- [ 16   2  13   9   3   9  88]]
-Node Classification on random seed  9663 -> 0.667
-Confusion Matrix:
- [[ 91   1   6   2   1   2  11]
- [  4 128   7   4   4   2   8]
- [ 15  21 151  49  22  16  36]
- [  4   4   6 122   3   3  24]
- [  2   3   3   1  55   5   5]
- [  3   0   6   0   0  44   7]
- [ 12   1  14   5   3   8  76]]
-Node Classification on random seed  9664 -> 0.635
-Confusion Matrix:
- [[ 67   1   3   7   8   5   8]
- [  4 122   4   3  16   2   3]
- [ 20  20 162  37  27  16  42]
- [  7   2  32  94  17   2  16]
- [  0   2   3   1  66   1   2]
- [  5   2   2   2   3  52   4]
- [  7   2   2   7   6  12  72]]
-Node Classification on random seed  9665 -> 0.632
-Confusion Matrix:
- [[ 68   2  19   3   2   3  11]
- [  2 129   7   7   7   7   3]
- [ 14  35 129  36  18  28  40]
- [  6   5  18 126   2   4   7]
- [  3   9   2   0  67   3   4]
- [  3   1   3   2   1  35   3]
- [ 13   4  16   4   2   9  78]]
-Node Classification on random seed  9666 -> 0.605
-Confusion Matrix:
- [[ 63   1   6   3   3   7  19]
- [  5 131   3   6   6   3   5]
- [ 36  21 110  37  24  14  59]
- [ 11   3  10 126   2   3   9]
- [  2   7   9   4  54   1   3]
- [  3   0   3   1   0  44   7]
- [ 12   6   9   3   8  21  77]]
-Node Classification on random seed  9667 -> 0.644
-Confusion Matrix:
- [[ 68   4   2   0   0  23   6]
- [  7 117   1   4   9   5   5]
- [ 22  20 165  42  19  32  24]
- [ 14   4   6 127   7  10   2]
- [  3   6   2   0  60   2   1]
- [  3   0   2   4   0  56   2]
- [  8   5   7   8   7  28  51]]
-Node Classification on random seed  9668 -> 0.586
-Confusion Matrix:
- [[ 69   2   2  10  11   6  11]
- [ 10 110   3   4   4   3  10]
- [ 25  25 141  41  29  24  41]
- [ 22   4   9  95   5   6  19]
- [  2   4   3   0  51   2   6]
- [  2   0   2   6   1  45   6]
- [ 21   5  12   4   5   7  75]]
-Node Classification on random seed  9669 -> 0.631
-Confusion Matrix:
- [[ 80   2   0   4   3  13  16]
- [  6 148   2   1   3   4   3]
- [ 23  18 142  18  15  25  54]
- [ 26   6   9  99   6   7  12]
- [  2  11   2   4  59   2   6]
- [  3   4   3   0   1  27   6]
- [  6   2  11   7   8  15  76]]
-Node Classification on random seed  9670 -> 0.609
-Confusion Matrix:
- [[ 73   2   6   1   8  12   7]
- [  7 127   0   0  11   6   4]
- [ 18  12 131  31  26  35  53]
- [ 23   5   8  81   8  10  20]
- [  1   5   1   2  68   0   1]
- [  9   2   3   0   1  48   7]
- [ 11   3   6   4   5  17  81]]
-Node Classification on random seed  9671 -> 0.615
-Confusion Matrix:
- [[ 72   6   5   8   6   7   5]
- [  5 121   7   0   8   4   2]
- [ 19  34 143  19  60  20  39]
- [ 10   3  16  98   8   4  10]
- [  1   4   1   4  75   1   0]
- [  8   2   0   1   2  40   7]
- [ 12   6   4   8   3  16  66]]
-Node Classification on random seed  9672 -> 0.631
-Confusion Matrix:
- [[ 68   1  13   3   2  10  10]
- [  4 142   2   4   5   4   2]
- [ 23  29 135  35  29  17  37]
- [ 18   3   6 104   2   6  19]
- [  0   8   4   4  60   0   1]
- [  8   1   0   4   4  45   3]
- [ 11   2  10   3   7  15  77]]
-Node Classification on random seed  9673 -> 0.606
-Confusion Matrix:
- [[ 64   3   0   6   4  16  10]
- [  5 124   9   0  11   3   4]
- [ 33  12 123  43  19  16  51]
- [  8   3   9 117  11  12  11]
- [  0   3   7   0  66   3   2]
- [  5   0   5   0   0  37  15]
- [ 15   9   8   5   6  12  75]]
-Node Classification on random seed  9674 -> 0.606
-Confusion Matrix:
- [[ 66   9   5   7   5   7  13]
- [  4 118   4   0   8   4  10]
- [ 35  18 125  30  21  36  40]
- [ 13   5  16 109  10   5   5]
- [  3   8   0   1  68   2   0]
- [ 13   0   4   1   1  47   4]
- [ 14   2   5   2   5  19  73]]
-Node Classification on random seed  9675 -> 0.593
-Confusion Matrix:
- [[ 68   4   3   4   5  21  10]
- [  2 134   5   7   6   5   3]
- [ 20  20 116  59  27  26  41]
- [  7   1  12 120   5  13   9]
- [  1   6   7   0  49   1   2]
- [  4   0   1   1   2  45   6]
- [ 14   0  14  12   4  17  61]]
-Node Classification on random seed  9676 -> 0.648
-Confusion Matrix:
- [[ 82   2   4   5   0   6   6]
- [  4 133   8   1   8   3   1]
- [ 17  19 143  36  31  28  38]
- [ 16   2   9 105   3   7  12]
- [  2   3  10   4  67   0   2]
- [  8   0   5   1   0  44   8]
- [ 10   2  11   4   4  12  74]]
-Node Classification on random seed  9677 -> 0.598
-Confusion Matrix:
- [[ 73   1  10   5   1  10  10]
- [  4 124  10   1   4   3   4]
- [ 23  23 122  25  59  21  39]
- [  7   3  22 102   5   7  11]
- [  3   5   3   1  70   0   1]
- [  8   0   1   2   2  46   6]
- [ 17   1   9  16   9  10  61]]
-Node Classification on random seed  9678 -> 0.626
-Confusion Matrix:
- [[ 77   2   2   5   6   7   5]
- [  6 123   5   7  14   1   9]
- [ 29  11 151  43  29  25  29]
- [ 11   4  13 106   4   2   9]
- [  1   2   7   1  55   0   2]
- [ 16   0   1   0   0  47   5]
- [ 23   3   7   6   9  13  67]]
-Node Classification on random seed  9679 -> 0.641
-Confusion Matrix:
- [[ 82   3   5   4   4   6   8]
- [  1 148   5   4   5   1   5]
- [ 25  17 144  27  27  25  44]
- [ 15   7  18  91   3   4  10]
- [  1   5   1   1  68   2   0]
- [  7   1   1   8   0  43   2]
- [ 15   1  16   5   4  16  65]]
-Node Classification on random seed  9680 -> 0.605
-Confusion Matrix:
- [[ 75   2   6   2   4   6  15]
- [  8 106   8   2   4   3   3]
- [ 13  30 150  26  30  46  30]
- [ 15   8  16  95   4   7  25]
- [  0   5   6   2  48   1   0]
- [  9   2   1   0   2  39  10]
- [  5   4   9   5   6  15  92]]
-Node Classification on random seed  9681 -> 0.597
-Confusion Matrix:
- [[ 63   1   5   7   3  24  17]
- [  3 123   9   3   4   1   6]
- [ 16  17 135  29  25  25  54]
- [ 16   4  16  95   4   5  22]
- [  0   3   2   1  62   2   4]
- [  8   1   2   0   1  37   4]
- [  5   0  18   6   9  21  82]]
-Node Classification on random seed  9682 -> 0.636
-Confusion Matrix:
- [[ 73   0   5   6   4  26   3]
- [  3 124   9   0  11   3   1]
- [ 20  22 161  33  17  19  30]
- [ 23   3  16 107   6   7   9]
- [  2   7   3   3  56   0   1]
- [  4   3   4   3   0  40   4]
- [  7   5  10   4  11  17  75]]
-Node Classification on random seed  9683 -> 0.596
-Confusion Matrix:
- [[ 70   2   0   7   4  10  13]
- [  2 129  10   1  11   8   9]
- [ 20  19 144  48  33  17  28]
- [ 10   1  10  91   3   6  27]
- [  1   8   5   4  51   3   0]
- [  6   4   1   3   1  46   4]
- [ 15   6   7   3  17  17  65]]
-Node Classification on random seed  9684 -> 0.605
-Confusion Matrix:
- [[ 71   1   4   3   3  12   8]
- [  5 123  17   6   8   3   2]
- [ 15  24 121  48  24  31  36]
- [ 16   3  14  92   8   7   9]
- [  2   7   6   3  58   0   4]
- [  4   3   2   0   0  50   4]
- [  7   5   5   7   9  20  90]]
-Node Classification on random seed  9685 -> 0.61
-Confusion Matrix:
- [[ 60   6  14   3   2  17   4]
- [  8 125  15   1   6   1   3]
- [ 20  19 137  32  43  31  29]
- [  8   5  11 113   5   7  16]
- [  1   4   4   1  56   1   2]
- [  9   0   1   0   3  47   8]
- [ 13   1  13   5   5  13  72]]
-Node Classification on random seed  9686 -> 0.655
-Confusion Matrix:
- [[ 63   5   0   8   6  11  15]
- [  2 133   6   5   8   1   3]
- [  9  13 168  51  10  21  43]
- [  7   4  15 114   6   7  12]
- [  0   5   3   5  52   0   5]
- [  1   0   2   2   4  37   5]
- [  7   4   5  11   2  16  88]]
-Node Classification on random seed  9687 -> 0.59
-Confusion Matrix:
- [[ 73   2   6   8   4   8   7]
- [  0 113  15   2  12   6   3]
- [ 21  22 166  40  31  10  37]
- [ 22   5  24  86   5   2   9]
- [  1   6  11   1  53   1   1]
- [  8   3   3   5   0  34   3]
- [ 16   8  18  11   7   6  65]]
-Node Classification on random seed  9688 -> 0.574
-Confusion Matrix:
- [[ 56   2  17   3   6   7   8]
- [  3 139   7   2   7   1   2]
- [ 27  16 115  37  38  37  38]
- [ 11   5  22  87   3  10  23]
- [  4  10   1   0  60   0   6]
- [  7   2   4   0   0  37   6]
- [  8   5  17   1   9  14  80]]
-Node Classification on random seed  9689 -> 0.626
-Confusion Matrix:
- [[ 73   1   6   4   3   7  11]
- [  2 119   3   4  14   4   4]
- [ 25  34 142  34  33  39  22]
- [ 11   1  18 110   5   2   7]
- [  0   0   1   1  62   0   2]
- [  2   0   0   0   3  57   7]
- [ 10   1  18   4  12  19  63]]
-Node Classification on random seed  9690 -> 0.641
-Confusion Matrix:
- [[ 70  12   1  10   6   6  12]
- [  1 130   7   4   9   0   6]
- [ 24  17 165  24  17  18  43]
- [  9   1  23  95  11   4  16]
- [  0   3   8   3  55   1   5]
- [  3   1   3   3   0  49   5]
- [ 10   0   9   4   4  16  77]]
-Node Classification on random seed  9691 -> 0.644
-Confusion Matrix:
- [[ 82   5   8   3   3  12   3]
- [  3 127   9   3   5   4   4]
- [ 36  11 152  38  23  13  44]
- [ 15   2   5 109   4   9   6]
- [  3   4   3   2  67   3   2]
- [  3   2   3   0   0  34   8]
- [ 18   4   7   6   9  11  73]]
-Node Classification on random seed  9692 -> 0.574
-Confusion Matrix:
- [[ 58   1   0   2   5  19  19]
- [  2 113   6   2   5   8   1]
- [ 48  32 137  21  15  33  32]
- [ 13   5  32  85   4  11  16]
- [  4   5   6   0  62   2   2]
- [ 12   2   0   2   0  37   7]
- [ 14   4  10   3   7  14  82]]
-Node Classification on random seed  9693 -> 0.632
-Confusion Matrix:
- [[ 85   3   6   4   2   9   9]
- [  8 122   1   2  12   1   2]
- [ 27  11 151  32  42  15  30]
- [  8   5  14 102   3   5  15]
- [  0   2   7   3  58   1   4]
- [  5   1   0   0   1  45   9]
- [ 22   5  18   3  10  11  69]]
-Node Classification on random seed  9694 -> 0.593
-Confusion Matrix:
- [[ 83   4   5   5   2  10   5]
- [  2 113   3   3  12   2   5]
- [ 24  25 135  63  27  28  24]
- [ 21   3  13  98   9   8   9]
- [  0   5   3   3  60   3   2]
- [  5   0   3   3   1  45   2]
- [ 18   1  12  11   6  17  59]]
-Node Classification on random seed  9695 -> 0.556
-Confusion Matrix:
- [[ 67   0   4   5   5  12   7]
- [ 14 110  13   2  22   2   4]
- [ 33  16 111  56  27  30  39]
- [  8   1  11 101  10  10  21]
- [  3   2   7   3  64   2   2]
- [  6   1   0   1   2  39   2]
- [ 22   3  10  10   4  12  64]]
-Node Classification on random seed  9696 -> 0.625
-Confusion Matrix:
- [[ 74   3   1   4   1  17   5]
- [  3 134   2   1  18   3   3]
- [ 33  17 123  40  20  32  43]
- [  8   3  10 106   2  10   8]
- [  0   3   1   3  58   1   8]
- [  3   2   2   0   0  54   4]
- [ 15   0   8  11   7  20  76]]
-Node Classification on random seed  9697 -> 0.638
-Confusion Matrix:
- [[ 72   5   3   3   2  12   7]
- [  2 127   8   2   7   4   2]
- [ 24  25 151  48  17  17  36]
- [ 19   2   7 111   9   4  11]
- [  1   6   4   3  59   3   2]
- [  9   5   2   1   1  45   2]
- [ 16   6   1   4   7  13  73]]
-Node Classification on random seed  9698 -> 0.63
-Confusion Matrix:
- [[ 57   3   4   6   3  20   5]
- [  4 138   6   5   6   6   3]
- [ 20  17 146  32  24  35  45]
- [ 20   4   7 102   3  12  14]
- [  0   6   5   1  60   0   3]
- [  5   0   1   1   0  41   5]
- [  7   4   7   2   2  17  86]]
-Node Classification on random seed  9699 -> 0.582
-Confusion Matrix:
- [[ 61   4   3   7  10   8   8]
- [  8 122   4   1  12   3   6]
- [ 30  33 120  32  34  33  42]
- [ 17   2  11 101   7   2  16]
- [  1   5   3   3  57   1   2]
- [  3   1   1   5   2  39   7]
- [ 19   3   5   6  13   5  82]]
-Node Classification on random seed  9700 -> 0.654
-Confusion Matrix:
- [[ 68   4   1   9   1  14  13]
- [  5 124   5   1   3   2   5]
- [ 32  16 176  11  17  24  35]
- [ 19   8  21  84   2   2  13]
- [  4   7   7   1  51   0   1]
- [  7   3   0   0   2  60   1]
- [ 14   6   6   7   4  13  91]]
-Node Classification on random seed  9701 -> 0.616
-Confusion Matrix:
- [[ 78   2   1   7   3   8   6]
- [  3 114  10   4  16   2   9]
- [ 30  19 141  28  38  15  42]
- [ 13   2  11 105   3   3  15]
- [  2   2   4   1  67   0   1]
- [  3   0   0   6   0  50   5]
- [ 21   4   4  17   8  16  61]]
-Node Classification on random seed  9702 -> 0.597
-Confusion Matrix:
- [[ 65   1   2   6   4  21  10]
- [  2 116   2   7  11   1   1]
- [ 23  26 139  26  17  31  51]
- [  3   2  20 109   0  10  16]
- [  1   6   3   5  52   5   0]
- [ 14   1   3   6   1  44   0]
- [  8   1  19  11   7  19  72]]
-Node Classification on random seed  9703 -> 0.578
-Confusion Matrix:
- [[ 60   4  11   5  10   3  16]
- [  1 131   4   1  10   4   5]
- [ 22  26 100  48  62  16  32]
- [  6   0  18  91  12   7  11]
- [  2   4   5   0  70   0   3]
- [  6   3   7   0   3  45   4]
- [ 14   4  12   1   6  14  81]]
-Node Classification on random seed  9704 -> 0.612
-Confusion Matrix:
- [[ 62   1   3   2   4  18  13]
- [  8 121   3   6   8   2   1]
- [ 11  23 156  30  16  23  55]
- [  7   6  19  96  10  11  18]
- [  0  11   3   1  56   1   3]
- [  3   2   2   5   0  44  10]
- [ 13   2   5   6   7  16  77]]
-Node Classification on random seed  9705 -> 0.618
-Confusion Matrix:
- [[ 58   1  13   9   4   9  19]
- [  4 124   3   2   5   2   5]
- [ 26  31 139  28  23  19  45]
- [ 13   3  20 116   5   5   3]
- [  0   5   2   3  58   2   1]
- [ 12   1   0   0   0  46   5]
- [ 24   3   3   4   6  14  77]]
-Node Classification on random seed  9706 -> 0.638
-Confusion Matrix:
- [[ 69   1   5  11   1  17   5]
- [  4 132   3   4  10   4  12]
- [  9  13 159  32  27  32  34]
- [  3   1  36  98   8   4   6]
- [  4   6   4   2  55   2   3]
- [  2   1   7   2   0  45   5]
- [  4   2   7   6   6  17  80]]
-Node Classification on random seed  9707 -> 0.632
-Confusion Matrix:
- [[ 50   2   7   6   6  15  10]
- [  1 125   6   2  15   3   2]
- [ 25  15 157  44  26  16  27]
- [ 15   2  19 104   5   5  16]
- [  1   1   9   5  60   1   1]
- [ 10   0   1   2   0  46   3]
- [  5   4  11   5   8  11  90]]
-Node Classification on random seed  9708 -> 0.581
-Confusion Matrix:
- [[ 83   3   7   5  10   7   7]
- [  3 131   2   4   7   4   4]
- [ 23  27  84  62  63  20  43]
- [  6   2  19 108   5   5  17]
- [  2   5   1   1  51   0   1]
- [  4   0   2   2   0  45   5]
- [  8   4   9   4   8   8  79]]
-Node Classification on random seed  9709 -> 0.621
-Confusion Matrix:
- [[ 59   0   4   8   2   5  26]
- [  2 120   7   5  12   1   4]
- [ 15  14 149  49  26  22  26]
- [ 15   4  22 100   6   2   8]
- [  3   3   4   3  59   1   2]
- [  5   1   1   7   2  42  10]
- [ 14   3   3   6  12  14  92]]
-Node Classification on random seed  9710 -> 0.618
-Confusion Matrix:
- [[ 62   0  10   2   4  16  12]
- [ 16 120   3   2   7   0   3]
- [ 23  15 143  29  40  22  38]
- [  9   4  13  88   4   7  16]
- [  0   3   1   4  74   1   6]
- [  9   0   0   0   0  45   5]
- [ 13   5  11   6   5  18  86]]
-Node Classification on random seed  9711 -> 0.614
-Confusion Matrix:
- [[ 63   9  17   3   1  14   2]
- [  8 112  10   2  10   1   0]
- [ 28  22 155  25  23  33  27]
- [ 12   4  15 112   1   6  13]
- [  1   9   5   3  56   2   1]
- [  7   5   1   2   0  43   3]
- [ 18   5   8   4   5  21  73]]
-Node Classification on random seed  9712 -> 0.652
-Confusion Matrix:
- [[ 82   1   2   3   1  13   8]
- [  3 130  10   3   2   7   4]
- [ 28   9 157  34  14  25  44]
- [  5   1  23 122   3   5   8]
- [  4   6   3   1  59   1   0]
- [ 11   3   0   2   0  40   4]
- [  5   4  11  13   1  23  62]]
-Node Classification on random seed  9713 -> 0.594
-Confusion Matrix:
- [[ 55   5   5   8   2  15  10]
- [  6 119   8   3   8   1   3]
- [ 29  25 128  36  41  19  32]
- [ 11   5  17 102   5   7  13]
- [  0   7   6   0  58   1   4]
- [  3   1   4   0   2  46   7]
- [  7   6  11  12   7  14  86]]
-Node Classification on random seed  9714 -> 0.61
-Confusion Matrix:
- [[ 60   2   3   4   4  15  15]
- [  3 124   0   4  10   6   7]
- [ 15  38 131  25  18  20  53]
- [  5   4  12 105   6  10  24]
- [  1   4   2   0  70   1   4]
- [  0   1   1   0   0  50   6]
- [  3  10  11   3  23  17  70]]
-Node Classification on random seed  9715 -> 0.605
-Confusion Matrix:
- [[ 57   1   6   6   6  12   6]
- [  3 123   4   5  17   3   5]
- [ 15  13 142  39  30  28  39]
- [  6   4  30 107   4   3  20]
- [  1   1   2   2  56   1   6]
- [  9   3   4   3   2  43   4]
- [  6   2  16   6   7  15  77]]
-Node Classification on random seed  9716 -> 0.605
-Confusion Matrix:
- [[ 84   5   6   8   3   8   3]
- [  2 113   3   3  19   2   3]
- [ 20  17 149  55  25   9  45]
- [  9   5  21  93   8   6   7]
- [  2   5   7   0  61   0   2]
- [  4   3   2   6   3  39   6]
- [  7   3  10  12   6  25  66]]
-Node Classification on random seed  9717 -> 0.641
-Confusion Matrix:
- [[ 67   1   4   4   6   5  14]
- [  2 123  14   6  14   0   1]
- [ 11  26 156  43  28  14  37]
- [  7   5  20 113   1   5  12]
- [  1   2   7   3  53   3   1]
- [ 10   2   2   3   0  47   4]
- [  7   3   7   5   9  10  82]]
-Node Classification on random seed  9718 -> 0.585
-Confusion Matrix:
- [[ 62   4   7   2   5  10  15]
- [  3 123   7   1   3   3   0]
- [ 24  26 137  44  37  16  28]
- [ 29   5  14  91   6   7   7]
- [  2   7   2   4  48   1   3]
- [  9   2   1   7   3  45   4]
- [ 26   2  10   5  15   9  79]]
-Node Classification on random seed  9719 -> 0.63
-Confusion Matrix:
- [[ 64   3   6   7   7   8  17]
- [  2 130   2   2  16   2   1]
- [ 16  16 137  42  25  25  47]
- [  6  10  17  96  11   5   9]
- [  0   1   4   0  70   1   1]
- [  2   2   2   1   0  47   4]
- [ 14   5   9   4   5  13  86]]
-Node Classification on random seed  9720 -> 0.632
-Confusion Matrix:
- [[ 87   0   3   0   1   5   8]
- [  2 110   1   4  12   4   4]
- [ 34  23 135  45  32  14  39]
- [  7   3  19 111   4   1  13]
- [  1   7   2   2  65   0   2]
- [  2   2   5   7   0  43   5]
- [ 13   2  17   6   2  15  81]]
-Node Classification on random seed  9721 -> 0.59
-Confusion Matrix:
- [[ 74   0   5   4   6  11   6]
- [  9 125   7   2   3   2   2]
- [ 49  14 139  37  26  20  28]
- [ 15   4  11  99   3   3  31]
- [  0   1   3   3  59   0   2]
- [  3   1   4   0   0  51   6]
- [ 19   2  14   2  29  23  43]]
-Node Classification on random seed  9722 -> 0.598
-Confusion Matrix:
- [[ 62   1  10   8   1  14   8]
- [  4 137   8   1   4   3   7]
- [ 15  20 131  36  39  24  46]
- [  8   5  13  99  13  12   5]
- [  2  11   4   0  63   1   2]
- [  7   3   0   3   0  46   5]
- [ 20   4   7  11   4  13  60]]
-Node Classification on random seed  9723 -> 0.625
-Confusion Matrix:
- [[ 70   1   1   3   8   7  23]
- [  1 126  13   3   8   1   4]
- [ 14  22 148  40  27  24  30]
- [ 11   2  17 105  10  10  13]
- [  2   3   6   0  65   0   0]
- [  9   0   1   3   0  44   4]
- [ 11   7  11   4   4  17  67]]
-Node Classification on random seed  9724 -> 0.588
-Confusion Matrix:
- [[ 74   5   4   4   3  12  14]
- [  7 117   5   4   9   3   6]
- [ 16  12 116  31  64  39  29]
- [ 14   0  33  87   8  10  12]
- [  3   2   4   0  55   1   2]
- [  4   1   3   1   3  50   5]
- [  9   1   7   3   8  11  89]]
-Node Classification on random seed  9725 -> 0.608
-Confusion Matrix:
- [[ 93   3   4   5   2   9  10]
- [  7 136   3   4   6   2   5]
- [ 14  28 142  30  20  28  39]
- [  9   8  10 100   8  15  12]
- [  1   8   6   1  51   1   3]
- [  5   3   5   5   0  31  11]
- [ 11   2   8  12   6  23  55]]
-Node Classification on random seed  9726 -> 0.667
-Confusion Matrix:
- [[ 72   3   3   7   2  11   8]
- [  4 126   0   7   3   2   1]
- [ 14  29 151  37  22  17  32]
- [  9   7   9 117   9   3  20]
- [  0   5   1   1  63   3   0]
- [  1   1   4   1   0  51  12]
- [  3   1  10  11   2  18  87]]
-Node Classification on random seed  9727 -> 0.638
-Confusion Matrix:
- [[ 93   2   1   5   3   5   9]
- [  4 130  10   1   5   3   6]
- [ 21  12 154  27  35  24  44]
- [ 12   7  24  98   5   5  14]
- [  1   3   6   2  54   1   2]
- [  7   0   1   3   1  37   4]
- [  7   2  11   3   4  20  72]]
-Node Classification on random seed  9728 -> 0.612
-Confusion Matrix:
- [[ 72   3   4   1   2  10  20]
- [  4 130   7   0   2   3   1]
- [ 21  25 128  40  22  26  57]
- [  6   4  10 110   6   9  19]
- [  1   4   4   3  57   1   3]
- [  4   3   1   1   2  43   7]
- [ 10   3   4  13   9  13  72]]
-Node Classification on random seed  9729 -> 0.621
-Confusion Matrix:
- [[ 64   3  13   7   0   7  10]
- [  3 147   2   4   3   4   4]
- [ 24  25 124  31  48  16  30]
- [  4   5  13 125   2   5  10]
- [  3   6   1   2  60   1   3]
- [  6   0   3   1   0  38   4]
- [  9   3  12  11   9  32  63]]
-Node Classification on random seed  9730 -> 0.63
-Confusion Matrix:
- [[ 75   2   6   1   0   8   6]
- [  2 128   8   3   2   2   1]
- [ 15  15 157  28  12  21  60]
- [ 19   1  29  82   7   3  24]
- [  0   9   3   0  55   2   5]
- [  8   3   1   1   1  56   5]
- [  9   6   6   6   8  22  77]]
-Node Classification on random seed  9731 -> 0.595
-Confusion Matrix:
- [[ 47   5   3  10   3  18   9]
- [  7 125   6   1   7   3   4]
- [ 14  28 130  52  33  27  34]
- [  2  10  20  99   1   7  17]
- [  0   3   8   2  45   7   2]
- [  6   2   0   1   0  53   5]
- [  6   0  13   8   6  15  96]]
-Node Classification on random seed  9732 -> 0.608
-Confusion Matrix:
- [[ 67   5   9   3   3  27   4]
- [  3 115   5   1  20   5   2]
- [ 15  23 135  56  23  29  42]
- [  8   1  12 106   6   9  13]
- [  0   5   3   2  53   4   1]
- [  1   0   4   0   2  54   5]
- [  4   2   6   2   7  20  78]]
-Node Classification on random seed  9733 -> 0.64
-Confusion Matrix:
- [[ 65   0   1   4   6   3  12]
- [  9 124   3   4   7   2  10]
- [ 22  14 166  36  23  14  53]
- [ 10   3  24  99   8   4   9]
- [  2   6   5   0  60   0   4]
- [  3   1   0   5   1  51   6]
- [ 11   3  12   4   6  10  75]]
-Node Classification on random seed  9734 -> 0.632
-Confusion Matrix:
- [[ 67   2   0   8   7  10   7]
- [  4 122   1   0   4   1   5]
- [ 32  23 159  34  19  25  35]
- [  8   5  21 114   1   8  21]
- [  1   8   4   1  64   1   0]
- [  4   4   4   1   1  52   4]
- [ 11   3   8   2   9  21  54]]
-Node Classification on random seed  9735 -> 0.573
-Confusion Matrix:
- [[ 72   4   5   5   6   6  12]
- [  9 115  10   2   6   1   5]
- [ 31  18 116  68  26  20  47]
- [ 16   5  15  98   7   4   5]
- [  3   8   3   2  53   1   0]
- [  4   2   1   1   2  41   8]
- [ 21   4  11   6   8   9  78]]
-Node Classification on random seed  9736 -> 0.63
-Confusion Matrix:
- [[ 76   1  13   2   3  11   2]
- [  6 118   4   0  10   1   2]
- [ 20  36 157  28  22  21  33]
- [ 13   0  26  96   4   8  13]
- [  1   5   3   0  64   0   0]
- [  6   1   7   0   2  47   1]
- [  9   2  21   4   8  21  72]]
-Node Classification on random seed  9737 -> 0.599
-Confusion Matrix:
- [[ 72   2  12   4   4  16   5]
- [  3 114   2   2  14   2   1]
- [ 39  15 153  31  23  20  29]
- [ 24  11  18  84   9   4  14]
- [  2   3   1   1  60   1   1]
- [  2   2   0   2   4  42   8]
- [ 27   9  12  12   4   6  74]]
-Node Classification on random seed  9738 -> 0.617
-Confusion Matrix:
- [[ 65   3   7   1   6  11   7]
- [  4 134  12   2  12   2   1]
- [ 20  28 137  44  22  29  46]
- [ 13   1  10 103   9   1  15]
- [  0   4   1   1  61   0   2]
- [  6   1   3   1   0  42   4]
- [ 11   7   8   3   8  17  75]]
-Node Classification on random seed  9739 -> 0.582
-Confusion Matrix:
- [[ 68   1   2   3   3  12   6]
- [  9 134   6   3  10   1   3]
- [ 21  13 119  55  52  25  24]
- [ 20   3  18  89   4  11   6]
- [  1   9   4   0  55   0   2]
- [  6   0   5   6   2  43   8]
- [ 13   5  11   8   9  18  74]]
-Node Classification on random seed  9740 -> 0.59
-Confusion Matrix:
- [[ 61   3   5   4   1  12  20]
- [  4 106   2   2  32   0   2]
- [ 32  29 120  39  45  30  22]
- [ 15   4  10 115   3   9   7]
- [  0   1   2   3  71   0   2]
- [  7   0   2   1   0  53   3]
- [  7   4  23   4  10   9  64]]
-Node Classification on random seed  9741 -> 0.653
-Confusion Matrix:
- [[102   4   0   2   3   8   4]
- [  7 129   2   0   4   3   2]
- [ 27  21 138  40  30  10  41]
- [ 16  11   7  96   8   8  11]
- [  3   5   5   0  57   0   5]
- [ 15   1   4   0   0  36   2]
- [  6   1   5   6  10  10  95]]
-Node Classification on random seed  9742 -> 0.634
-Confusion Matrix:
- [[ 77   3   4   6   3  14  10]
- [  3 124   8   1   3   6   2]
- [ 20  18 160  23  41  13  34]
- [  8   1  18  96   7   4  15]
- [  3   9   5   0  70   0   4]
- [  5   1   1   4   1  41   3]
- [  9   1  10  13   4  28  66]]
-Node Classification on random seed  9743 -> 0.604
-Confusion Matrix:
- [[ 68   3   4   5   1  14  13]
- [  3 116   9   1   7   4  12]
- [ 13  12 134  29  32  39  65]
- [  5   3   7 108   4  13  16]
- [  1  10   0   1  64   3   1]
- [  3   0   4   1   0  45   2]
- [  9   3   4   8   7  25  69]]
-Node Classification on random seed  9744 -> 0.65
-Confusion Matrix:
- [[ 70   4   0   2   5  13   7]
- [  9 119   9   4   9   1   3]
- [ 13  20 163  38  22  21  42]
- [ 11   5  12 112   7   2   9]
- [  1   5   3   0  65   0   2]
- [  4   0   4   0   3  45   8]
- [  5   7  10   4   8  18  76]]
-Node Classification on random seed  9745 -> 0.621
-Confusion Matrix:
- [[ 89   5   1   7   4   6  12]
- [  6 119   6   2  28   5   2]
- [ 21  23 142  34  31  23  32]
- [ 10   1  15  92  12   5  15]
- [  1   3   3   2  69   0   1]
- [  4   1   0   1   1  40   7]
- [ 20   5  12   4   5   3  70]]
-Node Classification on random seed  9746 -> 0.604
-Confusion Matrix:
- [[ 64   2   6   7   1  20   3]
- [  5 127   6   2  11   2   3]
- [ 40  22 142  42  20  20  35]
- [ 12   2  15  92   2   6  10]
- [  0   8   2   2  60   1   2]
- [  8   3   5   1   3  47   2]
- [ 18   3  11   9   4  20  72]]
-Node Classification on random seed  9747 -> 0.66
-Confusion Matrix:
- [[ 60   2   3   2   2  12  18]
- [  1 148   4   6   5   2   2]
- [ 17  26 165  30  23  16  35]
- [  3   5  17 120   7   6   7]
- [  0   3   5   3  60   0   3]
- [  3   5   1   5   2  29   8]
- [  8   6   5  12   5  15  78]]
-Node Classification on random seed  9748 -> 0.613
-Confusion Matrix:
- [[ 60   0   3   7  12   9  12]
- [  6 124   5   4   6   1  13]
- [ 29  23 158  21  22  29  32]
- [ 12   2  18 106   9   6  11]
- [  1   9   4   1  46   1   7]
- [  5   2   3   0   1  45   3]
- [ 18   3   9   2   8  18  74]]
-Node Classification on random seed  9749 -> 0.646
-Confusion Matrix:
- [[ 54   1   2   8   6   9  22]
- [ 12 130   4   5   7   3   5]
- [ 17  13 157  39  19  25  29]
- [  9   3  12 114   6   5  11]
- [  4   2   4   2  56   0   3]
- [  8   0   1   0   1  51  15]
- [  6   1  11   5  10   9  84]]
-Node Classification on random seed  9750 -> 0.632
-Confusion Matrix:
- [[ 65   4   5  11   4  14  15]
- [  2 140   6   4   3   1   6]
- [ 19  17 139  32  37  17  43]
- [ 14   1  13 111   7   7   8]
- [  0   5   4   1  58   1   1]
- [  8   1   0   2   2  37   5]
- [  5   4   6  11   4  18  82]]
-Node Classification on random seed  9751 -> 0.612
-Confusion Matrix:
- [[ 58   4   8  11   1  13  10]
- [  5 147   4   3   2   2   2]
- [ 18  25 131  66  14  26  29]
- [ 12   1  24  94   6   4   9]
- [  2   8   6   1  49   5   3]
- [  2   1   2   2   2  46   8]
- [ 10   3   7  10   0  17  87]]
-Node Classification on random seed  9752 -> 0.617
-Confusion Matrix:
- [[ 61   3   4   5   8   7   6]
- [  2 147  10   2  11   6   4]
- [ 26  34 161  21  29  13  42]
- [  9   3  15  96   6   7   7]
- [  2   6   1   2  54   3   5]
- [ 13   2   0   0   7  31   6]
- [ 14   5  13   7   5  12  67]]
-Node Classification on random seed  9753 -> 0.618
-Confusion Matrix:
- [[ 59   0  13   1   5  15   5]
- [  8 140   1   2   7   2   5]
- [ 25  24 139  30  35  11  43]
- [  4   1  11  94   4  10  31]
- [  0  10   1   1  54   1   3]
- [  4   0   8   1   2  46   8]
- [ 21   1  11   3  11   3  86]]
-Node Classification on random seed  9754 -> 0.628
-Confusion Matrix:
- [[ 81   2   4   5   3  13   9]
- [  7 120   3   2   7   2   5]
- [ 18  21 156  25  29  17  55]
- [ 12   2  15 108   1   4  17]
- [  1   3   5   1  53   1   4]
- [  7   1   2   2   5  40   7]
- [  4   2   7  14   9  19  70]]
-Node Classification on random seed  9755 -> 0.643
-Confusion Matrix:
- [[ 75   9   5   7   4   4   1]
- [  7 130   5   0   9   5   2]
- [ 21  28 170  33  23  22  24]
- [  8  11  17  96  13   6   5]
- [  3   9   1   0  55   0   5]
- [  8   2   2   2   3  47   4]
- [ 16   5  12   5   3   8  70]]
-Node Classification on random seed  9756 -> 0.577
-Confusion Matrix:
- [[ 63   4   8   2   3  12   9]
- [  2  94   9   2  21   2   1]
- [ 26  22 121  53  65  20  31]
- [ 12   0  10 115  12   3  12]
- [  1   2   5   1  68   3   0]
- [  4   1   0   0   1  39   8]
- [ 22   5   9   3  12   5  77]]
-Node Classification on random seed  9757 -> 0.6
-Confusion Matrix:
- [[ 54   1   3  19   6  15  17]
- [  8 120   4   4  16   0   8]
- [ 17  24 136  37  16  28  30]
- [ 14   7  14 129   3   2   9]
- [  2   1   8   1  60   1   7]
- [  8   2   5   4   0  40   3]
- [ 16   1   6   8   5  20  61]]
-Node Classification on random seed  9758 -> 0.577
-Confusion Matrix:
- [[ 58   1   8   4   4  17  14]
- [  8 127   8   0   6   2   4]
- [ 41  19 127  37  21  28  48]
- [  9   7   9  92   7   3  18]
- [  3   8   4   0  52   0   0]
- [  2   0   1   1   0  49  13]
- [ 10   6   3   9  18  22  72]]
-Node Classification on random seed  9759 -> 0.615
-Confusion Matrix:
- [[ 80   1   3   1   3   9   6]
- [  4 133   4   4  15   1   2]
- [ 23  21 143  32  30  12  43]
- [ 20   7  20  90   4   6  15]
- [  3   2   4   0  66   3   5]
- [  7   7   5   0   0  32  16]
- [  5   3   5   8   8  18  71]]
-Node Classification on random seed  9760 -> 0.613
-Confusion Matrix:
- [[ 78   3   4   1   1  10  18]
- [  3 122   3   3   5   9  10]
- [ 22  27 137  43  27  22  19]
- [ 11   8  12 102  14   7  13]
- [  2   3   0   3  58   2   5]
- [ 11   4   0   5   0  37   4]
- [ 13   3   5   7  15  10  79]]
-Node Classification on random seed  9761 -> 0.627
-Confusion Matrix:
- [[ 77   7   2   5   6  18   1]
- [  4 120   5   2  11   1   8]
- [ 34  26 165  22  18  20  43]
- [ 12   3  16 102   8   6   7]
- [  1   4   3   0  55   0   4]
- [  3   3   2   2   2  42   9]
- [ 15   6   6  10   6  12  66]]
-Node Classification on random seed  9762 -> 0.595
-Confusion Matrix:
- [[ 68   3  11   8   2  13   6]
- [  9 120   5   2   9   5   6]
- [ 39  14 138  36  36  16  21]
- [ 16   3  19 101   4   6   9]
- [  2   7   8   6  51   0   5]
- [  9   2   2   4   0  45   3]
- [ 18   7   8   1   5  20  72]]
-Node Classification on random seed  9763 -> 0.602
-Confusion Matrix:
- [[ 75   2   3   0   3  12  10]
- [  3 127  11   3   5   2   2]
- [ 15  30 146  45  31  26  37]
- [ 17   7  22  93   2   2  16]
- [  0  10   5   0  56   1   2]
- [  4   1   3   0   1  43   6]
- [ 11   4  20   8   4  12  62]]
-Node Classification on random seed  9764 -> 0.646
-Confusion Matrix:
- [[ 69   1   3   5   1  16  11]
- [  9 137   5   5   5   4   3]
- [ 19  19 169  17  21  10  55]
- [  6   7  11  94   5  14  21]
- [  0   6   5   3  60   3   1]
- [  6   2   4   2   1  34   4]
- [ 13   4   8   5   5   9  83]]
-Node Classification on random seed  9765 -> 0.644
-Confusion Matrix:
- [[ 82   2   3   2   8   7   9]
- [  4 124   5   1   6   2   4]
- [ 14  19 127  33  45  21  43]
- [ 16   3  10 118   5   4   7]
- [  1   8   2   0  75   1   4]
- [  6   1   2   5   7  43   8]
- [  4   2   8   4   9  11  75]]
-Node Classification on random seed  9766 -> 0.571
-Confusion Matrix:
- [[ 74   1   2   7   9   5  15]
- [  4 131   7   5   2   7   4]
- [ 33  22 122  30  19  22  52]
- [  7  15   8  87  17   9  21]
- [  0   6   4   0  64   2   3]
- [ 12   1   7   2   1  36   6]
- [ 22   5   5   9   9  12  57]]
-Node Classification on random seed  9767 -> 0.668
-Confusion Matrix:
- [[ 63   2   4   8   3  19   2]
- [  5 135   3   5  16   2   3]
- [ 25   9 137  39  30  19  28]
- [  2   3  10 122   5   7  10]
- [  2   2   3   2  60   3   1]
- [  3   4   2   0   1  59   2]
- [ 18   2   9   5   4  10  92]]
-Node Classification on random seed  9768 -> 0.638
-Confusion Matrix:
- [[ 63   2   4   2   3  12   6]
- [  8 133   5   5   5   5   5]
- [ 17  21 140  36  38  28  41]
- [  5   9  13 110   2   6  14]
- [  4   5   1   5  71   0   3]
- [  4   0   2   1   0  53   5]
- [  7   4   2   6   2  19  68]]
-Node Classification on random seed  9769 -> 0.653
-Confusion Matrix:
- [[ 59   4   3   2   2  21  10]
- [  4 128   6   1   8   3   8]
- [ 14  24 155  33  25  19  46]
- [  6   1   6 124  10   2   8]
- [  0   7   6   0  61   0   6]
- [  1   2   2   2   0  44   1]
- [ 12   5  13   3  11  10  82]]
-Node Classification on random seed  9770 -> 0.609
-Confusion Matrix:
- [[ 68   2   3   8   5  12  12]
- [  4 123   3   3  16   7   7]
- [ 21  16 144  38  32  20  48]
- [  6   6  15 104   5   7  15]
- [  2   4   2   3  70   1   1]
- [  3   3   2   1   0  37   3]
- [ 15   2   7  12   7  12  63]]
-Node Classification on random seed  9771 -> 0.646
-Confusion Matrix:
- [[ 71   1   6   4   5   2  11]
- [  3 134   5   1  10   1   4]
- [ 19  15 153  18  40  34  22]
- [ 13   2   8 115   2  10  10]
- [  1  10   5   0  71   0   2]
- [ 16   2   0   0   3  40   5]
- [ 15   5   8   9  15  12  62]]
-Node Classification on random seed  9772 -> 0.628
-Confusion Matrix:
- [[ 67   4  12   3   3  17  10]
- [  7 121   6   3   4   0   4]
- [ 14  20 166  28  13  27  42]
- [ 11   7  16  91  10   8  13]
- [  3   4   7   2  62   1   2]
- [  6   1   3   1   2  42   9]
- [  4   2   9  13   8  13  79]]
-Node Classification on random seed  9773 -> 0.594
-Confusion Matrix:
- [[ 87   3   4   5   2  10   5]
- [  2 129   3   2   4   3   0]
- [ 21  23 118  51  56  28  26]
- [ 15   9   7  96   8   1  22]
- [  1   8   5   7  53   1   1]
- [  7   1   1   1   0  37   9]
- [ 10   3  16   9   6  10  74]]
-Node Classification on random seed  9774 -> 0.661
-Confusion Matrix:
- [[ 74   2   3   5   4  11   8]
- [  2 131   5   0   4   4   9]
- [  9  32 170  25  15  21  35]
- [  6   4  24 104   2   8   3]
- [  2  10   4   1  65   1   4]
- [  5   2   1   5   0  50   1]
- [  5   6   8  18   5  20  67]]
-Node Classification on random seed  9775 -> 0.587
-Confusion Matrix:
- [[ 49   2   4   4   4  16  16]
- [  5 127   8   3  14   1   1]
- [ 35  17 128  36  17  43  41]
- [ 24   2  10  81   6  17  10]
- [  1   9   4   1  66   1   1]
- [  5   2   3   1   0  53   3]
- [  6   2   5   3   8  22  83]]
-Node Classification on random seed  9776 -> 0.554
-Confusion Matrix:
- [[ 59   2  11   0  10  11  11]
- [  3 130   1   3  14   6   6]
- [ 17  39 106  54  20  37  48]
- [ 17   6  20  88   7   9  11]
- [  0   5   2   5  46   0   6]
- [  4   2   5   0   1  50   7]
- [  4   4  10  11   6  11  75]]
-Node Classification on random seed  9777 -> 0.617
-Confusion Matrix:
- [[ 83   4   7   2   3   6   8]
- [  1 115   3   5  16   3   4]
- [ 29  32 143  27  30  16  40]
- [ 13   6  14 100   1   5  12]
- [  0   3   5   0  61   1   1]
- [  9   0   4   0   1  35   5]
- [ 14   4  23   8   9   9  80]]
-Node Classification on random seed  9778 -> 0.615
-Confusion Matrix:
- [[ 72   2   0   7   2   9  13]
- [  3 127  14   2   2   1   6]
- [ 16  14 152  41  34  13  42]
- [  9   6  16 109   9   3  11]
- [  0   2   5   4  61   1   2]
- [  9   3   2   2   3  37   6]
- [  9   5  11  14  22  10  57]]
-Node Classification on random seed  9779 -> 0.649
-Confusion Matrix:
- [[ 75   6   9   4   2  13  20]
- [  1 116   7   0   2   1   8]
- [ 16  24 160  29  13  18  45]
- [  4   3  17  96   2   2  13]
- [  1  12   3   2  70   1   8]
- [  1   2   4   0   1  51   7]
- [  8   4   4   6   3  25  81]]
-Node Classification on random seed  9780 -> 0.592
-Confusion Matrix:
- [[ 78   7   7   4   1  13  11]
- [  4 117   7   3  22   1   4]
- [ 20  27 124  54  41  25  34]
- [ 11   4  12  99   3  16  11]
- [  3   6   3   1  61   0   5]
- [  5   0   2   1   1  39   5]
- [  5   6   7   4   3   9  74]]
-Node Classification on random seed  9781 -> 0.609
-Confusion Matrix:
- [[ 80   1   1   5   4  10  12]
- [ 10 125   9   0   0   1   6]
- [ 25  27 141  26  36  32  29]
- [  7   4  26  85   4   3  21]
- [  3   7   7   1  48   1   2]
- [ 10   4   0   0   1  51  13]
- [ 14   6   5   4   7   7  79]]
-Node Classification on random seed  9782 -> 0.609
-Confusion Matrix:
- [[ 85   2   1   4   5  14   4]
- [  3 141  10   2   2   4   2]
- [ 26  14 150  54  25  32  24]
- [ 14   4  18  70  22   2  14]
- [  0   4   5   2  58   1   3]
- [  5   3   3   0   0  45   3]
- [ 15   7  16   6   5  11  60]]
-Node Classification on random seed  9783 -> 0.603
-Confusion Matrix:
- [[ 55   3   2   8   6  19   5]
- [  5 123   2   5  13   7   6]
- [ 22  12 154  27  39  16  50]
- [ 10   6  13  97   6   6  26]
- [  2   6   2   3  55   1   1]
- [  6   3   0   1   0  45  10]
- [  5   4   5   7  10  17  74]]
-Node Classification on random seed  9784 -> 0.615
-Confusion Matrix:
- [[ 62   4   2  12   5  12   8]
- [  3 137   5   4   3   2   5]
- [ 16  31 120  51  24  25  41]
- [ 15   4  10 109   1   8  19]
- [  1   6   6   0  63   4   0]
- [  6   1   3   6   0  39   9]
- [ 10   6   4   5   1   7  85]]
-Node Classification on random seed  9785 -> 0.6
-Confusion Matrix:
- [[ 66   3   1  11   8  14  11]
- [  3 125   1   2  14   3   2]
- [ 22  21 147  43  31  28  33]
- [  8   2  20  91   8   9  14]
- [  0   7   4   1  60   0   4]
- [  7   1   1   1   1  50   0]
- [  6   7  13  13   4  18  61]]
-Node Classification on random seed  9786 -> 0.615
-Confusion Matrix:
- [[ 77   9   0   6   4   7  16]
- [ 13 124   3   3   4  10   7]
- [ 22  30 145  29  18  25  38]
- [ 14   5  12  98   5   4  13]
- [  1   9   6   0  56   0   1]
- [  8   2   0   0   1  34  11]
- [ 12   3  13   7   8   6  81]]
-Node Classification on random seed  9787 -> 0.576
-Confusion Matrix:
- [[ 59   0   7   6   7  11  17]
- [  4 128   1  12   4   2   5]
- [ 35  23 112  43  39  23  51]
- [ 14   3  17  99   3   5  10]
- [  3   9   2   3  56   1   1]
- [  0   3   4   0   0  45   9]
- [  9   3   5   6  10  14  77]]
-Node Classification on random seed  9788 -> 0.628
-Confusion Matrix:
- [[ 67   3   7   0   6  20   3]
- [  4 119   6   1  11   3   1]
- [ 38  20 162  31  14  16  31]
- [ 15   8  13 108   8   3   6]
- [  0   5   7   6  42   1   4]
- [ 12   3   6   5   0  39   3]
- [ 19   4   6   6   6  11  91]]
-Node Classification on random seed  9789 -> 0.645
-Confusion Matrix:
- [[ 55   4   1   6   3  17  18]
- [  4 124   1   2  10   7   1]
- [ 24  22 129  25  27  24  32]
- [ 14   4  12 126   2   6  11]
- [  1   4   3   0  70   2   2]
- [  1   4   4   0   1  54   6]
- [  7   9   7   1   9  17  87]]
-Node Classification on random seed  9790 -> 0.598
-Confusion Matrix:
- [[ 63   1   5  17   8   8   7]
- [  1 134   1  11   6   3   4]
- [ 28  21 134  57  40  10  22]
- [  4   6  26  97   9  11  10]
- [  2   5   1   1  56   1   1]
- [  3   0   2   3   0  43   6]
- [ 16   7   3  12   7  16  71]]
-Node Classification on random seed  9791 -> 0.619
-Confusion Matrix:
- [[ 63   4   5   6   5   5   8]
- [  2 136   6   1   5   0   5]
- [ 16  35 149  35  21  23  35]
- [ 15   5  25  92  19   5   9]
- [  2   7   1   0  67   0   5]
- [  9   0   1   3   0  41   3]
- [ 17   3  11   2   8  14  71]]
-Node Classification on random seed  9792 -> 0.622
-Confusion Matrix:
- [[ 76   0   8   2   8   4   9]
- [  9 131   2   1   8   2   0]
- [ 30  23 153  33  27  14  35]
- [ 20   7  18  81  11  14  16]
- [  2   4   2   1  65   0   0]
- [  6   0   4   1   4  33   9]
- [ 20   0  10   1   4   9  83]]
-Node Classification on random seed  9793 -> 0.665
-Confusion Matrix:
- [[ 70   3   1   4   1  14   2]
- [  6 134   6   2   3   2   1]
- [ 37  19 171  24  16  18  38]
- [  5   4  23  96   8   5  15]
- [  2   5   1   0  64   2   3]
- [  4   0   0   0   0  49   5]
- [ 20   3   8   7   6  12  81]]
-Node Classification on random seed  9794 -> 0.64
-Confusion Matrix:
- [[ 82   0   2   1   3  12  17]
- [  3 143   4   2   5   6   1]
- [ 39  22 151  36  28  11  23]
- [ 19   3  13  88  12   3   5]
- [  1   5   2   0  59   0   1]
- [ 11   0   2   4   3  37   8]
- [  4   7   3   9   8  22  80]]
-Node Classification on random seed  9795 -> 0.63
-Confusion Matrix:
- [[ 76   1   4   9   3   6  10]
- [  0 149   4   4   7   7   1]
- [ 22  19 139  25  22  40  54]
- [  5   4  12 101  10   5   6]
- [  1   8   2   1  59   1   2]
- [  3   3   1   3   0  44   3]
- [  7   7  10   7   6  25  62]]
-Node Classification on random seed  9796 -> 0.619
-Confusion Matrix:
- [[ 75   4   0   4  10  20   5]
- [  2 118   3   3   8   5   8]
- [ 30  25 127  26  32  23  39]
- [ 10   2  15 107   5   8  16]
- [  1   8   3   0  61   3   3]
- [  5   1   0   2   1  51   2]
- [  9   3  14   2   2  19  80]]
-Node Classification on random seed  9797 -> 0.644
-Confusion Matrix:
- [[ 71   3   2   6   4  12  10]
- [  9 133   2   4   6   3   3]
- [ 21  18 164  19  33  26  44]
- [  8   1  23 110   4   3  15]
- [  1   9   5   1  55   0   2]
- [  7   2   0   3   1  41   3]
- [  5   5   7   8   3  15  70]]
-Node Classification on random seed  9798 -> 0.626
-Confusion Matrix:
- [[ 69   3  17   9   1   8   7]
- [  6 126   4   1   3   3   4]
- [ 20  10 166  36  28  22  33]
- [  5   2  32  90  13   6  16]
- [  2  10   2   2  60   0   2]
- [  2   0   2   3   0  40   5]
- [ 14   8   2   7  13  11  75]]
-Node Classification on random seed  9799 -> 0.545
-Confusion Matrix:
- [[ 62   1   7   8   5  15   8]
- [  6  99  10   4   9   6   2]
- [ 18  29 110  43  25  38  42]
- [ 18   6  13  94   8   8  21]
- [  1   5   8   2  53   0   4]
- [  6   0   3   4   0  39   3]
- [ 16   8   5   7   5  28  88]]
-Node Classification on random seed  9800 -> 0.582
-Confusion Matrix:
- [[ 49   6   4   5   4  27   9]
- [  1 130   4   2  12   1   3]
- [ 23  51 144  14  41  21  29]
- [ 11   4  12  94  13   7  10]
- [  0   5   4   1  59   2   4]
- [  7   3   1   2   3  49   4]
- [  5   9   4   9  15  26  57]]
-Node Classification on random seed  9801 -> 0.589
-Confusion Matrix:
- [[ 67   4   6   6   6   9   6]
- [  2 119  13   2  13   1   5]
- [ 36  13 125  26  49  27  34]
- [  6   6  25 111   3   6  11]
- [  3   4   9   2  51   1   4]
- [  4   2   1   1   2  47   6]
- [ 16   7  18   4   7   5  69]]
-Node Classification on random seed  9802 -> 0.607
-Confusion Matrix:
- [[ 56   0   7   6  13   9  11]
- [  6 123   2   4   5   5   7]
- [ 28  25 135  37  22   9  43]
- [ 15   2  17 107   7   4  11]
- [  1   8   3   2  66   0   1]
- [ 11   4   5   1   4  39   4]
- [ 10   4  13   5   1  21  81]]
-Node Classification on random seed  9803 -> 0.591
-Confusion Matrix:
- [[ 62   6  10   5   5   8  13]
- [  6  99  15   0  11   3   8]
- [ 23  22 128  47  25  24  41]
- [  5   1   6 117   5  12  20]
- [  0   4   2   3  60   0   1]
- [  6   2   0   1   2  46   1]
- [ 10   3  11  17   6  19  79]]
-Node Classification on random seed  9804 -> 0.598
-Confusion Matrix:
- [[ 84   3   5   4   2  11   8]
- [  5 123   7   5   5   3   3]
- [ 34  26 124  64  13  22  31]
- [ 13   4  14  97   3   1  14]
- [  2   8   8   4  46   5   2]
- [  3   0   3   2   2  52   8]
- [ 12   5   7   8   7  16  72]]
-Node Classification on random seed  9805 -> 0.624
-Confusion Matrix:
- [[ 76   3   6   5   5  11   7]
- [  8 115   8   2   7   3   8]
- [ 10  29 145  36  37  23  43]
- [  4   3   8 115   4   4  13]
- [  0   3   0   0  49   2   9]
- [  4   0   1   3   1  47   4]
- [  9   5   4  15   9  20  77]]
-Node Classification on random seed  9806 -> 0.603
-Confusion Matrix:
- [[ 72   1   2   1   8   8  15]
- [  3 121   6   5  10   2   3]
- [ 24  30 128  45  30  18  34]
- [ 26   3   5  81   8   9  13]
- [  0   5   4   2  66   0   3]
- [  1   0   3   1   2  47  12]
- [ 10   5   8   9  13  10  88]]
-Node Classification on random seed  9807 -> 0.613
-Confusion Matrix:
- [[ 56   5   2   7   5  13   8]
- [  6 125   5   3  10   0   1]
- [ 19  15 149  37  22  29  42]
- [  6   5  21  99   2   3   9]
- [  3   6   4   3  61   4   4]
- [  6   3   4   2   0  47  10]
- [ 17   3  11  13   8  11  76]]
-Node Classification on random seed  9808 -> 0.616
-Confusion Matrix:
- [[ 80   3   3   2   2   9  10]
- [  1 137   6   2   4   4   5]
- [ 34  37 131  25  26  13  38]
- [ 12   4   5  94  20  10  18]
- [  1   7   4   0  57   3   7]
- [  5   1   2   3   0  43   6]
- [ 10   6  12   3   7  14  74]]
-Node Classification on random seed  9809 -> 0.637
-Confusion Matrix:
- [[ 58   0   4   7   2  14  18]
- [  0 132   7   4  10   2   3]
- [ 18  21 167  27  18  25  40]
- [ 10   1  12 103   8   6  17]
- [  2   7   4   0  55   0   3]
- [  9   0   3   1   1  48   6]
- [  9   6   8   7   6  17  74]]
-Node Classification on random seed  9810 -> 0.619
-Confusion Matrix:
- [[ 69   8   2   4   2  14  14]
- [  7 133   6   4   8   4   2]
- [ 13  41 138  31  28   8  40]
- [ 10  10  18  85   6   8  17]
- [  1   4   7   2  63   1   3]
- [  3   1   3   2   0  58   3]
- [ 13   7   6   9   2   9  73]]
-Node Classification on random seed  9811 -> 0.586
-Confusion Matrix:
- [[ 72   7   4   8   0  12  10]
- [  0 131   4   9   7   5   0]
- [ 26  17 111  49  41  30  42]
- [  7   4  14  92   8   1  15]
- [  3   6   4   1  68   1   4]
- [  8   2   5   6   2  37   3]
- [ 12   2  12   3   9  11  75]]
-Node Classification on random seed  9812 -> 0.637
-Confusion Matrix:
- [[ 67   3   7   3   4   5  15]
- [ 11 126  12   3   2   5   4]
- [ 16  22 171  33  21  12  31]
- [ 14   6  14 107   5   4  19]
- [  0   6   3   1  52   1   8]
- [  9   4   1   0   0  44   2]
- [ 15   3  15   6  10   8  70]]
-Node Classification on random seed  9813 -> 0.562
-Confusion Matrix:
- [[ 64   1   9   2   9   9   8]
- [  8 109  10   4  17   3   6]
- [ 36  21 134  50  22  27  46]
- [  7   3  17  98   7  18   7]
- [  1   2   3   1  64   1   3]
- [  5   4   4   4   4  33   4]
- [ 12   5  12   7   7  12  60]]
-Node Classification on random seed  9814 -> 0.606
-Confusion Matrix:
- [[ 70   3   5   5   2  15   4]
- [  6 113   7   3  14   3   7]
- [ 18  24 134  34  20  16  71]
- [ 16   1   6 103   6   7  19]
- [  0   5   2   1  55   4   4]
- [  6   0   1   0   2  56   4]
- [  9   6   3   8  10  17  75]]
-Node Classification on random seed  9815 -> 0.649
-Confusion Matrix:
- [[ 72   5   2   2   5  10   6]
- [  6 121   5   1   9   1   4]
- [ 23  20 163  37  18  18  32]
- [ 20   5  14 104   1   4   7]
- [  0   9   3   0  61   0   5]
- [  6   3   3   1   2  54   5]
- [ 20   2  15   2   7  13  74]]
-Node Classification on random seed  9816 -> 0.635
-Confusion Matrix:
- [[ 71   3  11  11   7   6   2]
- [  4 140   6   1   8   1   3]
- [ 20  20 151  36  19  23  38]
- [  6   4  11  94   3   5  31]
- [  1   4   4   1  60   2   5]
- [  9   1   0   1   1  42   5]
- [  8   0   7  11   4  22  77]]
-Node Classification on random seed  9817 -> 0.63
-Confusion Matrix:
- [[ 71   6  10   3   4  12  12]
- [  2 124   2   1   3   3   5]
- [ 20  30 144  26  13  24  48]
- [ 12   7  13 114   5   8  14]
- [  4   3   4   1  67   2   4]
- [  4   1   4   6   1  48   6]
- [  9   2  12   7   5  12  62]]
-Node Classification on random seed  9818 -> 0.652
-Confusion Matrix:
- [[ 83   8   2   8   2  16   8]
- [  0 128   3   3   4   2   8]
- [ 10  19 157  39  14  16  45]
- [  6   6  14 112   6   9   9]
- [  0   5   3   0  67   2   5]
- [  1   0   2   7   0  42   6]
- [ 10   2  14   9   4  21  63]]
-Node Classification on random seed  9819 -> 0.567
-Confusion Matrix:
- [[ 46   1   7   5   3  11  27]
- [  6 123   1   2   5   0   5]
- [ 30  30 128  35  32  26  51]
- [  8   0  12  90  23   3  14]
- [  1  10   4   4  64   1   1]
- [  5   3   1   7   0  35  11]
- [  9   4   4   7   5  19  81]]
-Node Classification on random seed  9820 -> 0.635
-Confusion Matrix:
- [[ 80   4   3   5   4   7   5]
- [ 10 117   3   9  10   0   2]
- [ 21  14 170  47  17  14  33]
- [  7   3  15 101   9   8  21]
- [  4   1  12   1  65   0   1]
- [ 12   0   2   0   0  32  10]
- [ 12   2  11   7   7  12  70]]
-Node Classification on random seed  9821 -> 0.597
-Confusion Matrix:
- [[ 73   3   2   6   6  11  12]
- [  7 132   5   3  11   0   4]
- [ 19  32 132  39  22  24  53]
- [ 13   8  10  94   3   5   8]
- [  4   8   3   0  60   0   2]
- [  8   1   1   6   3  43   4]
- [ 18   4   7  12   4  12  63]]
-Node Classification on random seed  9822 -> 0.614
-Confusion Matrix:
- [[ 82   5   8   8   3   6   4]
- [  2 113   7   1  19   3   4]
- [ 27  21 138  26  41  28  36]
- [  4   9  14 105   4  10   8]
- [  0   3   4   3  59   1   1]
- [  7   1   1   4   0  45   4]
- [ 21   4   9   6  15   4  72]]
-Node Classification on random seed  9823 -> 0.603
-Confusion Matrix:
- [[ 64   5   6   3   1  12  14]
- [  8 127   1   4   6   2   9]
- [ 22  42 147  33   6  23  35]
- [ 20   1  10  88  15   7  10]
- [  4   9   5   2  52   1   4]
- [  5   0   5   5   0  51   7]
- [ 10   5  18   8   6   8  74]]
-Node Classification on random seed  9824 -> 0.554
-Confusion Matrix:
- [[ 65   7   1   7   3  11  18]
- [ 11 105   4   0  17   3   5]
- [ 38  19 121  34  62  12  46]
- [  5   4  29  86   3   5  10]
- [  1   3   3   3  53   0   1]
- [  7   0   1   0   1  52   9]
- [ 12   3  20   7  10  11  72]]
-Node Classification on random seed  9825 -> 0.563
-Confusion Matrix:
- [[ 72   3  16   5   1  10  11]
- [  5 117   6   2  11   1   5]
- [ 24  19  84  48  41  28  52]
- [  6   4   9 110  17   7  17]
- [  0   6   1   3  64   0   2]
- [  5   2   4   0   3  42   1]
- [ 22   1  11   6  11  11  74]]
-Node Classification on random seed  9826 -> 0.612
-Confusion Matrix:
- [[ 62   3   5  15   9  20   3]
- [  4 136   6   1   3   4   7]
- [ 17  21 141  35  14  33  52]
- [  6   0  14 114   3   4  14]
- [  2  10   4   3  61   0   0]
- [ 13   1   6   5   1  31   5]
- [  3   5  10   3   5  19  67]]
-Node Classification on random seed  9827 -> 0.644
-Confusion Matrix:
- [[ 68   0   5   4   2  15  11]
- [  2 140   8   3   4   3   7]
- [ 27  23 135  47  12  22  37]
- [ 13   1  14 105   1   9  10]
- [  6  14   0   0  66   1   1]
- [  4   2   2   0   1  44   4]
- [ 10   3   5   4   4  15  86]]
-Node Classification on random seed  9828 -> 0.656
-Confusion Matrix:
- [[ 74   5   7   5   2  12  10]
- [  1 145   2   3  10   0   6]
- [ 22  35 135  51  13   4  42]
- [  8   6   9 112   2   5   9]
- [  0   7   3   2  70   0   2]
- [  3   2   5   0   1  40   8]
- [  8   1   8   7   7  11  80]]
-Node Classification on random seed  9829 -> 0.623
-Confusion Matrix:
- [[ 62   8   4  17   8   3   6]
- [  1 137   1   1   4   2   4]
- [ 18  29 137  29  45  11  36]
- [ 12   7  19  94   8   5  10]
- [  2  12   2   0  62   0   2]
- [  9   1   7   0   0  38   8]
- [ 12   5   8   8   4   9  93]]
-Node Classification on random seed  9830 -> 0.622
-Confusion Matrix:
- [[ 74   0   5   3   9  10   5]
- [ 10 122   8   0   8   1   1]
- [ 19   8 135  44  22  51  38]
- [ 14   6   9  95   5   9   6]
- [  1   5   4   3  75   2   0]
- [  5   1   0   1   0  41   2]
- [  7   9  12   6   9  20  80]]
-Node Classification on random seed  9831 -> 0.587
-Confusion Matrix:
- [[ 63   5   5   7   1   8  10]
- [  4 118   5   5   4   4   2]
- [ 25  27 135  61  17  18  40]
- [ 12   1  14  98   4   7  11]
- [  3   6   3   3  52   2   8]
- [  5   2   0   6   8  48   1]
- [ 14   4   7  17   2  25  73]]
-Node Classification on random seed  9832 -> 0.61
-Confusion Matrix:
- [[ 69   2   7   1   4   8  15]
- [  6 134   4   2   2   0   7]
- [ 22  12 139  38  23  38  32]
- [ 16   1  15  95   6   7  13]
- [  1  12   5   2  55   3   0]
- [  8   1   1   1   1  59   3]
- [ 18   2  12  15   9  15  59]]
-Node Classification on random seed  9833 -> 0.658
-Confusion Matrix:
- [[ 70   0  12   5   2  17   1]
- [  9 145   6   2   4   3   4]
- [ 29  11 152  35  21  29  33]
- [ 11   3  12 113   5   7  10]
- [  0  10   7   2  57   2   1]
- [  4   0   4   3   0  52   0]
- [  9   1   4   6   5  13  69]]
-Node Classification on random seed  9834 -> 0.609
-Confusion Matrix:
- [[ 63   6   5  13   4  10  14]
- [  0 113   4   3   7   5   6]
- [ 25  33 133  48  14  21  49]
- [  8   2   8 113   3   9   8]
- [  2   6   3   1  59   3   2]
- [  5   4   0   5   0  43   5]
- [ 14   4   5   6   6  15  85]]
-Node Classification on random seed  9835 -> 0.637
-Confusion Matrix:
- [[ 70   1   6   2   2  11  16]
- [  8 131   6   3   6   3   1]
- [ 13  12 169  27  18  21  51]
- [ 21   7  12  84   3   6  17]
- [  5   7   2   0  63   0   1]
- [ 13   1   4   2   1  54   2]
- [ 16   3   7   1   6  19  66]]
-Node Classification on random seed  9836 -> 0.602
-Confusion Matrix:
- [[ 58   7  13   3   2  16   8]
- [  4 131   3   8   6   1   3]
- [ 23  21 153  26  19  28  46]
- [ 10   6  10  99   6  12  10]
- [  3   4   6   2  48   1   3]
- [  5   1   7   0   2  57   4]
- [  7  10   7  13   1  31  56]]
-Node Classification on random seed  9837 -> 0.605
-Confusion Matrix:
- [[ 78   2   2   6   7  14  10]
- [  8 141   4   1   4   3   2]
- [ 28  23 138  47  14  30  21]
- [ 28   3  15  79   4   5  17]
- [  2   3   5   0  63   0   1]
- [ 13   0   4   1   1  35   2]
- [ 29   2   6   4   4  20  71]]
-Node Classification on random seed  9838 -> 0.592
-Confusion Matrix:
- [[ 74   4   7   6   8   6  10]
- [  3 110  15   4   9   8   4]
- [ 30  21 136  24  47  11  46]
- [ 11   0   9 110   8  15  16]
- [  2   6   1   2  63   0   1]
- [  2   2   3   3   0  32  13]
- [ 20   4  12   4   8   3  67]]
-Node Classification on random seed  9839 -> 0.609
-Confusion Matrix:
- [[ 71   1   8   4   1   9  11]
- [  6 133   0   5   2   4  14]
- [ 35  12 132  28  35  27  22]
- [ 16   2  14  93   2  13  11]
- [  2   5   5   1  63   2   5]
- [  6   0   4   2   0  44   7]
- [ 21   2  10   5   5  27  73]]
-Node Classification on random seed  9840 -> 0.594
-Confusion Matrix:
- [[ 67   1   3   4   3  10  11]
- [  7 137   5   5   9   4   3]
- [ 15  23 121  59  16  19  59]
- [  9   4  20 103   4   6  13]
- [  1   4   3   5  48   0   2]
- [  2   2   0   2   0  59   4]
- [ 11   4  10  18   2  24  59]]
-Node Classification on random seed  9841 -> 0.608
-Confusion Matrix:
- [[ 66   4   4   6   4  19  12]
- [  3 126   9   5   8   5   5]
- [ 16  16 137  37  29  34  42]
- [  7   4  25 106   4   8   5]
- [  0   1   3   1  55   0   2]
- [  4   1   1   0   2  39   6]
- [ 16   2  11   9  12  10  79]]
-Node Classification on random seed  9842 -> 0.643
-Confusion Matrix:
- [[ 68   7   1   3   3  13   9]
- [  3 136   6   2   9   2   3]
- [ 15  17 144  38  38  19  36]
- [ 24   6  10 103   0   6   9]
- [  1  10   2   0  69   0   2]
- [ 10   0   1   1   0  47   2]
- [ 12   0  14   2   8  13  76]]
-Node Classification on random seed  9843 -> 0.614
-Confusion Matrix:
- [[ 77   2   5   4   1   1  11]
- [  5 129   6   6   7   3   4]
- [ 15  28 135  28  25  31  42]
- [ 13   6  18  97   9   5  15]
- [  0   7   6   0  60   0   1]
- [  7   2   5   7   1  39   6]
- [  9   2  22   5   9   7  77]]
-Node Classification on random seed  9844 -> 0.615
-Confusion Matrix:
- [[ 71   5   4   2   5  18   2]
- [  5 123  11   6  20   1   4]
- [ 19  27 148  34  25  19  29]
- [  9   2  15  98  13   5  12]
- [  1   1   3   5  56   0   1]
- [  2   1   5   1   1  33  15]
- [ 13   5   9  13   5  12  86]]
-Node Classification on random seed  9845 -> 0.584
-Confusion Matrix:
- [[ 41   1  14   4   5  29  18]
- [  4 114   5   3   5   6   3]
- [ 23  31 138  41  19  13  31]
- [ 17   5   8 111   9   6  15]
- [  1   7   6   0  64   3   6]
- [  8   0   5   5   1  48  11]
- [ 11   4  10   1   6  16  68]]
-Node Classification on random seed  9846 -> 0.598
-Confusion Matrix:
- [[ 73   2   7   3   2   6  13]
- [  3 128   3   5   6   8   3]
- [ 14  17 128  60  24  21  50]
- [ 15   6  19  79  11   7  16]
- [  1   6   5   4  61   1   3]
- [  3   0   2   4   0  46   5]
- [  8   4  11   3   7  14  83]]
-Node Classification on random seed  9847 -> 0.635
-Confusion Matrix:
- [[ 71   4   1   5   4  12   6]
- [ 12 122   3   2   9   0   7]
- [ 26  31 144  26  28  18  39]
- [  6   7   8 122   3   2  17]
- [  3   5   1   2  60   2   2]
- [  7   2   1   0   2  42   6]
- [ 14   1   6   5  10  20  74]]
-Node Classification on random seed  9848 -> 0.61
-Confusion Matrix:
- [[ 61   2  10   7   2  10  11]
- [  1 111  11   2  13   1  11]
- [ 20  11 164  32  27  52  31]
- [  7   2  20  89   3   5  19]
- [  2   2   2   0  64   4   0]
- [  5   0   6   0   0  41   6]
- [ 15   3  11   7   3  14  80]]
-Node Classification on random seed  9849 -> 0.63
-Confusion Matrix:
- [[ 70   3   1   9   9   3  14]
- [  4 111   5   0  20   1  10]
- [ 27  22 149  29  28  14  33]
- [ 13   6  15 107  10   6  12]
- [  2   6   7   0  57   0   2]
- [  2   1   3   3   0  49   5]
- [  7   1  12   7   5  13  87]]
-Node Classification on random seed  9850 -> 0.63
-Confusion Matrix:
- [[ 77   2   5   7   4   6   9]
- [  5 131   8   3   4   3   4]
- [ 19  36 146  35  20  21  47]
- [  8   8  12 108   4   3   7]
- [  0  11   3   0  61   0   1]
- [  8   1   4   0   1  33   5]
- [ 12   5   8  13   6  12  74]]
-Node Classification on random seed  9851 -> 0.596
-Confusion Matrix:
- [[ 66   1   5   9   2  23   3]
- [ 10 120   7   4   4   0   4]
- [ 25  25 154  44  25  37  20]
- [  4   3  24 103   2   4  12]
- [  4  10   4   2  58   6   2]
- [  3   1   3   2   2  40   0]
- [ 12   3  11  20   3  19  55]]
-Node Classification on random seed  9852 -> 0.632
-Confusion Matrix:
- [[ 79   2   6   2   3   9   8]
- [  6 130  13   1   8   2   1]
- [ 24  11 146  39  22  16  45]
- [  8   0   7 100   7  12  16]
- [  0   6   3   2  63   2   3]
- [ 11   2   5   0   0  35   5]
- [ 10   7  13  11  11   9  79]]
-Node Classification on random seed  9853 -> 0.659
-Confusion Matrix:
- [[ 81   3   4   9   1   8   5]
- [  7 124   8   1  14   2   1]
- [ 13  17 184  23  37  20  36]
- [  7   3  21  97   4   8  11]
- [  0   2   2   1  52   1   4]
- [  8   0   0   2   0  45   2]
- [ 19   2   9   9   8   9  76]]
-Node Classification on random seed  9854 -> 0.635
-Confusion Matrix:
- [[ 74   2   4   4  14  11   8]
- [  8 113   2   0  11   7   5]
- [ 14  17 158  30  20  36  31]
- [ 19   3  12 105   4   3  12]
- [  3   1   5   3  57   1   7]
- [  9   2   5   1   0  51   2]
- [ 17   2   3  10   5  12  77]]
-Node Classification on random seed  9855 -> 0.601
-Confusion Matrix:
- [[ 62   2  11   8   1  10  14]
- [  2 125   3   1   7   1   6]
- [ 37  28 128  24  34  24  31]
- [ 11   3  26  99   2   8  14]
- [  1   9   5   0  54   2   3]
- [  1   2   3   4   0  46   7]
- [ 10   3   5   7  16  13  87]]
-Node Classification on random seed  9856 -> 0.63
-Confusion Matrix:
- [[ 84   3   3   2   1  10   7]
- [  2 139   5   0   5   3   2]
- [ 37  35 131  36  16  24  32]
- [ 15   6  10  95   4   1  17]
- [  0   6   6   1  58   1   1]
- [  7   1   6   0   0  43   5]
- [ 17   2  12  11   4  14  80]]
-Node Classification on random seed  9857 -> 0.607
-Confusion Matrix:
- [[ 60   5   0   3   6  15  15]
- [ 10 110   7   5   5   4   4]
- [ 25  26 157  26  18  23  46]
- [ 19   4  23  86   5   8  12]
- [  2   6   7   1  65   1   3]
- [  3   1   2   1   0  49   4]
- [  8   5   7   1   6  21  80]]
-Node Classification on random seed  9858 -> 0.601
-Confusion Matrix:
- [[ 70   2   5   6   8  16  10]
- [ 10 128   5   0  12   1   4]
- [ 32  13 142  13  33  23  43]
- [ 17   8  10  90   6   9  17]
- [  1   3   7   2  56   1   2]
- [  6   2   0   3   4  46   5]
- [ 13   1   7  11  10  18  69]]
-Node Classification on random seed  9859 -> 0.617
-Confusion Matrix:
- [[ 74   1   6   5   2  15  12]
- [  8 118   6   0   8   2   1]
- [ 20  27 150  41  28  18  37]
- [ 16   2  20  95  12   8  14]
- [  3   7   1   2  57   1   3]
- [  3   0   3   3   1  47   1]
- [ 20   3   5   4   4  10  76]]
-Node Classification on random seed  9860 -> 0.613
-Confusion Matrix:
- [[ 79   5   1   5   4   9   6]
- [  2 130   8   2  10   3   4]
- [ 19  23 104  34  55  29  49]
- [  7   2  13 108   5   9  11]
- [  2   3   1   3  60   1   6]
- [  4   1   2   1   2  54   6]
- [  5   2  11   4   5  13  78]]
-Node Classification on random seed  9861 -> 0.644
-Confusion Matrix:
- [[ 74   2   2   2   4  12   6]
- [  0 118   6   3  10   2   2]
- [ 24  23 162  25  24  24  40]
- [ 11   9  26  85  12   7  11]
- [  2   4   4   3  70   4   4]
- [  5   2   3   2   0  44   3]
- [  5   4   4   4   6  10  91]]
-Node Classification on random seed  9862 -> 0.624
-Confusion Matrix:
- [[ 65   3   0   4   9  25  10]
- [  5 117  12   1   8  11   6]
- [ 28  19 149  27  23  28  28]
- [ 10   2   8  96   5  10   8]
- [  5   1   2   0  69   3   2]
- [  4   1   4   4   1  50   8]
- [ 18   1   9   2   9  12  78]]
-Node Classification on random seed  9863 -> 0.597
-Confusion Matrix:
- [[ 56   5  20   2   5   9   4]
- [  4 125   4   2   8   2   5]
- [ 32  31 121  41  25  20  36]
- [ 19   2  10 124   9   5  11]
- [  0   3   3   6  55   2   2]
- [  5   1   5   2   0  43   6]
- [ 14   3  10   5  12  13  73]]
-Node Classification on random seed  9864 -> 0.641
-Confusion Matrix:
- [[ 94   1   2   2   1   9   5]
- [ 13 125   2   1   4   6   7]
- [ 14  26 140  36  24  19  51]
- [ 13   3  14 102   2   9   7]
- [  4   8   7   3  64   1   3]
- [  4   1   2   0   0  47   7]
- [ 10   5   6   8   7  12  69]]
-Node Classification on random seed  9865 -> 0.634
-Confusion Matrix:
- [[ 82   3   5   5   2   8   5]
- [  3 136   3   2   9   3   1]
- [ 21  32 150  22  24  29  43]
- [  7   4  19 104  14   4  11]
- [  0   8   9   0  48   0   2]
- [ 10   4   1   2   3  43   3]
- [  6   5  11   7   4  12  71]]
-Node Classification on random seed  9866 -> 0.607
-Confusion Matrix:
- [[ 52   1   8   9   4  13  14]
- [  3 134   2   4   5   1   3]
- [ 26  32 146  20  36  15  51]
- [ 10   7  24 105   3   3  10]
- [  2   6   5   2  62   2   2]
- [  5   2   1   6   4  40   5]
- [  6   7   8   7   7  12  68]]
-Node Classification on random seed  9867 -> 0.632
-Confusion Matrix:
- [[ 79   1   6   7   6   8   9]
- [  2 107   6   1  14   3   5]
- [ 30  18 168  23  39  25  36]
- [  8   5  12 107   7   3   9]
- [  0   4   1   1  64   1   6]
- [  2   0   0   4   3  44   6]
- [  9   1   9   5  15  18  63]]
-Node Classification on random seed  9868 -> 0.633
-Confusion Matrix:
- [[ 66   3   4   8   4   3  12]
- [  3 113  12   1   6   1   4]
- [ 14  30 153  42  25  25  32]
- [ 10   9   9 117   5   7  14]
- [  1   7   2   0  49   1   4]
- [  3   2   0   1   0  45  12]
- [  9   6  15   6  12   3  90]]
-Node Classification on random seed  9869 -> 0.631
-Confusion Matrix:
- [[ 72   1   5   5   6  11   7]
- [  6 136   4   2  10   1   2]
- [ 33  21 163  18  31  10  37]
- [ 15   4  10  88   2   6  20]
- [  0   5   1   1  67   0   2]
- [  8   1   2   4   5  37  11]
- [ 19   5   7   7  13  11  68]]
-Node Classification on random seed  9870 -> 0.668
-Confusion Matrix:
- [[ 68   5   4   1   4  15   7]
- [  4 118   3   0   6   5   4]
- [ 23  25 187  35  23  11  20]
- [ 19   2  16 114  14   2   7]
- [  3   6   2   0  66   0   5]
- [  5   2   3   3   0  42   2]
- [ 17   3   8   5   9   4  73]]
-Node Classification on random seed  9871 -> 0.578
-Confusion Matrix:
- [[ 72   2   3   9   6  10  12]
- [  2 124   2   1  18   1   9]
- [ 25  17 133  38  36  20  31]
- [  6   3  15  86   9   8  36]
- [  0   4   3   0  66   1   1]
- [  7   1   1   1   3  33   9]
- [ 25   7   7  10  12  11  64]]
-Node Classification on random seed  9872 -> 0.553
-Confusion Matrix:
- [[ 58   1   4   8   6  12  15]
- [  1 126  12   3   7   0   3]
- [ 22  28 103  42  41  17  52]
- [  9   7  12  99  12   6  17]
- [  0   6   6   0  63   1   6]
- [  6   3   2   0   2  32   7]
- [ 17   3  12  14   6  19  72]]
-Node Classification on random seed  9873 -> 0.59
-Confusion Matrix:
- [[ 73   3   4   4   6   6   7]
- [  6 119   6   0  12   2   3]
- [ 40  14 120  52  49  16  40]
- [ 18   1  19  91   6   4   6]
- [  1   3   1   1  59   4   3]
- [  3   1   2   2   1  48   4]
- [ 21   0  10  14   5  10  80]]
-Node Classification on random seed  9874 -> 0.59
-Confusion Matrix:
- [[ 58   6   5   0   2  10  19]
- [  4 139   5   4  10   6   3]
- [ 22  19 117  72  14  15  43]
- [ 13   1   8 116   0   4   9]
- [  1   5   4   3  65   1   4]
- [  5   2   5   5   6  30  10]
- [ 14   5   6   5   7  28  65]]
-Node Classification on random seed  9875 -> 0.627
-Confusion Matrix:
- [[ 81   3   3   2   4  16   6]
- [  4 128   6   2   3   5   4]
- [ 21  35 135  43  28  19  29]
- [ 14   8  26 108   3   3  12]
- [  1   5   2   1  51   1   1]
- [  3   7   1   0   1  49   4]
- [  6   5  10   8   5  13  75]]
-Node Classification on random seed  9876 -> 0.585
-Confusion Matrix:
- [[ 47   4   8   2   8  11  13]
- [ 10 117   5   0  18   2   5]
- [ 22  36 151  32  27  18  44]
- [  9   1  17  96  15   7  13]
- [  3   2   2   2  55   0   4]
- [  6   1   3   2   0  41   3]
- [  4   1  14   6  16  19  78]]
-Node Classification on random seed  9877 -> 0.631
-Confusion Matrix:
- [[ 67   4   2   3   2   8  10]
- [  4 134   5   1   7   1   3]
- [ 20  11 132  50  26  16  52]
- [ 14   4  20 112   5  11   7]
- [  2   5   5   2  60   1   3]
- [  2   1   2   0   0  45  11]
- [  7   6  14   4   6  12  81]]
-Node Classification on random seed  9878 -> 0.644
-Confusion Matrix:
- [[ 74   5   5   9   1   3   1]
- [  1 129   3   4   9   1   6]
- [ 33  18 171  42  11  28  30]
- [ 18   6  11 101   4   5  15]
- [  1   5   6   1  62   1   1]
- [  7   0   3   2   0  35   9]
- [ 16   4  12   6   8   5  72]]
-Node Classification on random seed  9879 -> 0.615
-Confusion Matrix:
- [[ 59   3   2   5   3  18  11]
- [  8 131   7   2   7   8   2]
- [ 22  25 156  46  15  29  24]
- [ 12   4  10 104   4  11  10]
- [  3   9   6   1  54   3   3]
- [  3   2   3   0   2  45   3]
- [ 15   8  10   9   7  10  66]]
-Node Classification on random seed  9880 -> 0.608
-Confusion Matrix:
- [[ 67   1   4   6   2  13  14]
- [  9 110   8   6  10   3   2]
- [ 19  22 152  44  27  25  23]
- [ 10   4  15  97   4  12  22]
- [  1   9   3   3  58   2   3]
- [  5   1   1   4   0  46   7]
- [ 13   2   7   8   9   9  78]]
-Node Classification on random seed  9881 -> 0.6
-Confusion Matrix:
- [[ 57   0   6   4   4  12  19]
- [  2 124   6   9  11   3   1]
- [ 23  33 129  38  26  24  36]
- [ 12   1  13 100   0   9  16]
- [  1   3   5   1  76   0   2]
- [  7   1   2   1   1  46   8]
- [  7   6   9   3  17  18  68]]
-Node Classification on random seed  9882 -> 0.594
-Confusion Matrix:
- [[ 66   0   8   7   4  24   6]
- [  0 113   4   2   7   2   2]
- [ 36  21 154  31  16  25  33]
- [ 16   6  20 102   1  11  12]
- [  1   9  10   3  55   1   2]
- [  3   2   2   2   1  43  14]
- [  3   3  11   8  20  17  61]]
-Node Classification on random seed  9883 -> 0.59
-Confusion Matrix:
- [[ 69   2   6   5   2  10  15]
- [  6 125   6   3   1   0   5]
- [ 28  21 128  35  45  12  63]
- [ 16   2  11 114   6   4  19]
- [  1   2   3   2  59   1   1]
- [  2   2   4   1   4  38   7]
- [ 12   5   6   6  11  17  57]]
-Node Classification on random seed  9884 -> 0.649
-Confusion Matrix:
- [[ 76   4   3   7   1  15   4]
- [  0 141   3  10   5   1   0]
- [ 18  26 170  38  16  17  25]
- [  8   6  14 101  12   8   8]
- [  0  11   3   1  56   0   3]
- [  4   1   5   2   5  36  11]
- [ 14   2   6  12   7  15  69]]
-Node Classification on random seed  9885 -> 0.598
-Confusion Matrix:
- [[ 57   5   6   9   2  15  13]
- [  2 135   3   2   4   0   9]
- [ 20  23 152  23  23  12  42]
- [  4   6  35  73   8   6  32]
- [  2   9   4   3  54   2   5]
- [  7   1   0   1   0  56  10]
- [ 15   2  11   7   9  10  71]]
-Node Classification on random seed  9886 -> 0.622
-Confusion Matrix:
- [[ 64   6   2   7   6   7  22]
- [  2 114   8   5   9   2   4]
- [ 27  20 124  40  19  23  46]
- [ 10   6  18 101   5  14  12]
- [  1   8   3   0  65   2   1]
- [  1   2   0   4   0  44   4]
- [  6   4   6   4   7   5 110]]
-Node Classification on random seed  9887 -> 0.627
-Confusion Matrix:
- [[ 57   3   5   5   2  14  12]
- [  8 135   6   5  21   1   0]
- [ 22   9 142  28  44  26  34]
- [  9   2  18 112   4   8  15]
- [  3   3   3   1  61   0   2]
- [  3   3   0   1   5  45   4]
- [  7   5   4   1   5  22  75]]
-Node Classification on random seed  9888 -> 0.611
-Confusion Matrix:
- [[ 68   6   2   2   5  16   4]
- [  1 136   8   2  14   2   1]
- [ 14  27 159  18  32  30  39]
- [ 18   8  18  80   6  12  21]
- [  0   5   3   0  64   0   0]
- [  3   1   5   3   1  42   1]
- [  6   3  11  12   9  20  62]]
-Node Classification on random seed  9889 -> 0.625
-Confusion Matrix:
- [[ 58   5   6   5   7  13  17]
- [  4 125   3   1   7   1   8]
- [ 19  22 150  27  35  23  45]
- [ 11   4  14 107   4  11  11]
- [  1   4   5   1  54   2   1]
- [  2   2   1   2   3  48  10]
- [ 14   3   3   3   1  14  83]]
-Node Classification on random seed  9890 -> 0.603
-Confusion Matrix:
- [[ 70   2   8   3   4  17   6]
- [  4 138   1   3   7   3   2]
- [ 17  28 126  35  40  11  36]
- [ 17   4  15  83  18   3  18]
- [  0  11   1   0  57   0   4]
- [  4   1   4   6   0  30  20]
- [  5   4   9   7   9  10  99]]
-Node Classification on random seed  9891 -> 0.59
-Confusion Matrix:
- [[ 53   4   7   7   1  15  24]
- [  7 119   8   0  16   5   1]
- [ 46   9 130  39  19  21  39]
- [ 19   3   9 100   7   6  11]
- [  1   7   5   0  75   0   2]
- [  0   1   2   0   1  48  10]
- [  7   5   8  10   8  20  65]]
-Node Classification on random seed  9892 -> 0.627
-Confusion Matrix:
- [[ 88   2   0   1   1  16   9]
- [  6 131   6   0   8   3   9]
- [ 19  12 138  34  31  21  42]
- [ 10   9  20  94   4   6  15]
- [  1   7   3   5  59   1   2]
- [  5   3   0   0   3  41   7]
- [ 12   6  14   7   3  10  76]]
-Node Classification on random seed  9893 -> 0.551
-Confusion Matrix:
- [[ 70   2   5   8   5   9   5]
- [  2 121   6   7  14   2   4]
- [ 24  19 124  61  31  15  46]
- [ 35   6  12  75  14   6   9]
- [  2   6   5   3  61   0   4]
- [  5   1   1  10   1  37   6]
- [ 14   2   8  11  11  12  63]]
-Node Classification on random seed  9894 -> 0.631
-Confusion Matrix:
- [[ 54   2   4  15   2  16  16]
- [  4 138   4   4   3   2   3]
- [ 25  15 145  38  14  28  37]
- [  8   3  17 111  10   9  11]
- [  1   5   3   2  67   0   1]
- [  3   2   0   6   0  33  12]
- [  8   3  10   8   5  10  83]]
-Node Classification on random seed  9895 -> 0.615
-Confusion Matrix:
- [[ 80   1   3   6   3  18  11]
- [  7 115   4   0   6   4   2]
- [ 31  24 154  15  18  33  34]
- [ 28   8  14 100   1   5   7]
- [  1   9   4   0  56   0   2]
- [  7   1   1   4   0  49   1]
- [ 14   8  10   8  10  22  61]]
-Node Classification on random seed  9896 -> 0.622
-Confusion Matrix:
- [[ 74   2   2   7   6  13   8]
- [  5 134   4   2  19   1   5]
- [ 33  33 134  24  25   9  40]
- [ 16   4  12 100   4   7  10]
- [  1   7   1   2  66   0   4]
- [  5   2   2   0   1  40   9]
- [  7   5   9   8  11  13  74]]
-Node Classification on random seed  9897 -> 0.623
-Confusion Matrix:
- [[ 63   0   2   3   7  13   4]
- [  1 126   9   4  15   4   5]
- [ 23  12 145  63  12  32  36]
- [  7   2  12  90   9  12   7]
- [  8   2   1   1  72   1   2]
- [  3   0   2   1   0  48   2]
- [ 12   2   8   7   9  22  79]]
-Node Classification on random seed  9898 -> 0.638
-Confusion Matrix:
- [[ 68   6   4   4   7  19   7]
- [  1 114  11   4   2   6   1]
- [ 23  15 163  30  18  23  44]
- [  3   2  22 114   3   7   6]
- [  0   4   9   2  60   2   1]
- [  2   0   4   1   1  43   9]
- [  8   9   7  14   4  17  76]]
-Node Classification on random seed  9899 -> 0.615
-Confusion Matrix:
- [[ 63   2   2   6   4  33  10]
- [  2 130  13   4  10   1   4]
- [ 26  12 138  33  37  26  29]
- [  6   1  29  99   2   7   6]
- [  0   4   5   1  71   1   3]
- [  4   1   1   1   1  45   5]
- [ 13   1  13  12   3  11  69]]
-Node Classification on random seed  9900 -> 0.57
-Confusion Matrix:
- [[ 68   4   2   9   6  10   2]
- [  3 139   6   8   8   2   5]
- [ 28  29  95  47  49  23  37]
- [ 16   5  20  94   8   2   7]
- [  2   9   2   2  66   0   3]
- [  8   2   6   3   1  39   5]
- [ 13   7   7   6   7  11  69]]
-Node Classification on random seed  9901 -> 0.63
-Confusion Matrix:
- [[ 69   1   3   5   2   8  14]
- [  4 139   2   0   7   2   9]
- [ 23  18 136  29  27  20  45]
- [ 12   7  18  93   2   9  13]
- [  1   5   4   0  63   1   7]
- [  6   1   0   1   0  54   6]
- [  8   1  12   7  11  19  76]]
-Node Classification on random seed  9902 -> 0.611
-Confusion Matrix:
- [[ 64   1   2   9   5  17  16]
- [  3 107   0   3  16   4   5]
- [ 16  18 153  41  36  17  43]
- [  8   1  15  95   5  11  20]
- [  1   6   3   1  62   0   5]
- [  5   0   5   0   1  46  11]
- [  8   2   6   7   8   8  84]]
-Node Classification on random seed  9903 -> 0.614
-Confusion Matrix:
- [[ 66   0   5  14   2   6  13]
- [  8 130  10   1   3   2   1]
- [ 30  18 131  48  11  21  34]
- [ 13   1  12  96  11  18   8]
- [  3   7   4   0  61   0   1]
- [  4   3   5   5   2  47   3]
- [ 18   2   6  14   3  16  83]]
-Node Classification on random seed  9904 -> 0.604
-Confusion Matrix:
- [[ 74   2   4   8   4  12   9]
- [ 11 117   8   3  13   2   5]
- [ 31  18 134  38  29  18  49]
- [ 14   0  12  92   7  10  14]
- [  1   1   3   0  66   0   5]
- [  7   0   2   1   1  40   1]
- [ 14   3   8   3  11  14  81]]
-Node Classification on random seed  9905 -> 0.609
-Confusion Matrix:
- [[ 70   8  16   4   4   8   9]
- [  4 134   5   0   4   4  11]
- [ 14  24 143  23  12  33  63]
- [ 13   8  10  96   6   5  21]
- [  3   9   5   2  43   0   3]
- [  7   1   7   0   1  50   3]
- [  6   2   6   6   4  17  73]]
-Node Classification on random seed  9906 -> 0.613
-Confusion Matrix:
- [[ 78   3   2   5   1  18  15]
- [  7 118   3   3   5   2   2]
- [ 17  30 127  33  33  18  49]
- [ 13   5  15 100   3   5  14]
- [  2   2   3   7  59   0   2]
- [  6   2   6   0   0  48   7]
- [  2   1  14   4   4  24  83]]
-Node Classification on random seed  9907 -> 0.607
-Confusion Matrix:
- [[ 70   2   1   1   7  15   8]
- [  4 110   4   4  18   1   6]
- [ 18   7 151  38  43  21  35]
- [  4   9  20 100  10   5  16]
- [  1   5   4   8  66   2   1]
- [  2   2   0   8   0  43   7]
- [  7   1  22   9   5  12  67]]
-Node Classification on random seed  9908 -> 0.593
-Confusion Matrix:
- [[ 56  10   1  18   6  12  16]
- [  4 114   8   9   5   1   0]
- [ 29  24 159  42  14  21  26]
- [ 19   4  23 103   2   2   5]
- [  1   9   7   4  50   1   6]
- [  3   4   1   4   1  40   4]
- [  5   6  10   9  13  18  71]]
-Node Classification on random seed  9909 -> 0.626
-Confusion Matrix:
- [[ 61   0   6   3   5  19  10]
- [  8 129   0   1  10   2   4]
- [ 17  21 141  43  14  25  38]
- [  4   2  14 100  12   7  16]
- [  0   8   5   1  61   0   4]
- [  7   3   3   4   2  56   8]
- [ 13   4  10   2   4  15  78]]
-Node Classification on random seed  9910 -> 0.612
-Confusion Matrix:
- [[ 72   3  14   6   3   5   3]
- [  7 132   6   4   1   2   7]
- [ 15  38 127  40  26  30  40]
- [  8   5   9 105   5   5  14]
- [  1  12   3   1  63   0   3]
- [ 15   1   3   2   2  40   3]
- [  8   4  18   5   1  10  73]]
-Node Classification on random seed  9911 -> 0.606
-Confusion Matrix:
- [[ 64   3   7   7   4  12  16]
- [  9 119   7   5  12   4   6]
- [ 20  14 153  18  27  26  47]
- [  6   2  11 102   7   9  25]
- [  2   5   7   3  53   0   1]
- [  3   2   3   4   0  41   7]
- [  9   5   8   5  12  14  74]]
-Node Classification on random seed  9912 -> 0.616
-Confusion Matrix:
- [[ 79   4   2   2   1  15  10]
- [  1 141   6   3   5   2   3]
- [ 26  29 121  68  18  15  26]
- [ 12   5  10 104   6   3  11]
- [  2   6   6   2  52   2   3]
- [  6   4   5   1   0  43   3]
- [  7   5  19   4   3  23  76]]
-Node Classification on random seed  9913 -> 0.641
-Confusion Matrix:
- [[ 66   2   6   9   1   8  12]
- [  9 150   5   2   4   2   2]
- [ 25  26 147  24  19  24  35]
- [ 10   6  16  80   5   7  22]
- [  2   3   8   0  66   0   3]
- [  3   1   0   4   0  50  13]
- [  8   3   8   9   4   9  82]]
-Node Classification on random seed  9914 -> 0.621
-Confusion Matrix:
- [[ 75   8   2   5   5  13   3]
- [  3 126   4   0   9   4   5]
- [ 42  23 147  23  26  23  41]
- [ 13   4   9  95   3   8  11]
- [  2   5   2   1  60   5   2]
- [  7   0   2   1   1  44   4]
- [ 16   1   8   7  14  14  74]]
-Node Classification on random seed  9915 -> 0.633
-Confusion Matrix:
- [[ 78   3   7   5   1  12  11]
- [  1 123   1   7   4   1   6]
- [ 19  30 136  35  32  30  34]
- [ 11   9   6 103   6   8  16]
- [  0   7   2   2  76   0   1]
- [  8   1   1   1   1  46   2]
- [ 10   5   5   3   9  14  71]]
-Node Classification on random seed  9916 -> 0.612
-Confusion Matrix:
- [[ 76   1   2   4   6  17   3]
- [  2 133   4   4   9   4   4]
- [ 23  25 144  32  15  30  50]
- [ 10   3  18  86   5   8  18]
- [  2   4   6   0  59   2   3]
- [  9   3   2   1   0  34  10]
- [  8   3   5  11   9  13  80]]
-Node Classification on random seed  9917 -> 0.582
-Confusion Matrix:
- [[ 75   1   1   1  13  13   4]
- [  6 142   1   4   2  12   0]
- [ 22  32 131  34  35  23  42]
- [ 20   2   9  87  15   6  16]
- [  1  11   4   2  48   1   1]
- [  9   1   1   3   1  37   2]
- [  8   3   7   5  10  34  62]]
-Node Classification on random seed  9918 -> 0.625
-Confusion Matrix:
- [[ 72   7   2   6   3  15   9]
- [  1 131   5   6   1   3   7]
- [ 22  28 154  34  22  16  35]
- [ 10   6  24  96   5  11  16]
- [  0   8   4   4  59   1   0]
- [  5   1   2   4   0  49   5]
- [ 11   1  13   7   4  11  64]]
-Node Classification on random seed  9919 -> 0.602
-Confusion Matrix:
- [[ 76   2   6  10   3  16   7]
- [  4 120   6   1   7   0   8]
- [ 17  34 136  24  17  35  61]
- [  6   9  11 105   1   6  18]
- [  1   6   2   3  47   2   1]
- [  6   0   3   5   3  38   4]
- [ 16   2  10  13   2  10  80]]
-Node Classification on random seed  9920 -> 0.575
-Confusion Matrix:
- [[ 68   1   9   7   2  13  11]
- [  0 130   9   3   7   0  12]
- [ 21  21 102  46  27  15  60]
- [ 15   2   9  90   8  28  11]
- [  0   5   3   1  63   2   7]
- [  2   3   7   5   1  43   6]
- [  6   4   3  10   8  15  79]]
-Node Classification on random seed  9921 -> 0.627
-Confusion Matrix:
- [[ 58   5   5   7   3  13   3]
- [  1 145   6   1   0   1   7]
- [ 27  29 149  27  15  23  43]
- [  7   6   9  89  11  15   9]
- [  0   9   2   3  73   0   3]
- [  9   5   2   3   3  42   2]
- [ 10   2   9   6   5  27  71]]
-Node Classification on random seed  9922 -> 0.633
-Confusion Matrix:
- [[ 66   2   8   4   1  14  13]
- [  5 138   4   4   7   2   4]
- [ 17  11 141  33  19  30  43]
- [ 14   3  17  98   8  12  16]
- [  7   6   3   0  57   2   5]
- [  2   0   0   2   1  56   5]
- [  6   2   7   5   7  16  77]]
-Node Classification on random seed  9923 -> 0.611
-Confusion Matrix:
- [[ 70   3   1   2   3  14  14]
- [  4 122   7   2  11   2   9]
- [ 18  15 149  48  25  28  32]
- [ 21   0  14 100   2   9   9]
- [  3   7   6   4  56   2   5]
- [  6   1   2   1   0  44   7]
- [  8   3  12  14   4  11  70]]
-Node Classification on random seed  9924 -> 0.652
-Confusion Matrix:
- [[ 72   4   6   0   3  11  14]
- [  1 125   4   5   9   0   2]
- [  8  15 166  28  22  35  30]
- [  5   8  27 110   7   5  11]
- [  2   9   2   5  57   0   2]
- [  6   0   6   2   0  42   4]
- [  4   3  13   6   8  16  80]]
-Node Classification on random seed  9925 -> 0.59
-Confusion Matrix:
- [[ 76   1   2   8   5  14   3]
- [  4 133   9   2  10   2   4]
- [ 29  21 111  59  32  25  38]
- [ 12   0   5 108   6   2  15]
- [  0   8   1   1  53   3   3]
- [  9   2   1   0   1  47   1]
- [ 35   0   2  10  12  13  62]]
-Node Classification on random seed  9926 -> 0.644
-Confusion Matrix:
- [[ 59   5   4   2   4   9  12]
- [  3 131   8   0   6   3   2]
- [ 25  24 156  37  24  20  28]
- [  7   1  27  93   5   3  16]
- [  0   1   3   2  58   1   5]
- [  3   2  11   0   1  57   4]
- [  7   2  11   4   5  19  90]]
-Node Classification on random seed  9927 -> 0.627
-Confusion Matrix:
- [[ 75   4   1   4   1  25   5]
- [  2 125   7   4   9   1   3]
- [ 13  16 123  33  32  28  52]
- [ 15   1  13  95   2   5  17]
- [  1   3   3   2  69   1   4]
- [  6   3   0   0   0  53   2]
- [  8   4   6  18   8  11  87]]
-Node Classification on random seed  9928 -> 0.586
-Confusion Matrix:
- [[ 64   1  14   5   5  13   8]
- [ 14 109   3   2  13  10   3]
- [ 30  19 152  34  31  22  31]
- [ 24   4  11  88   3   9  15]
- [  2   5   7   0  60   0   1]
- [ 10   0   2   2   1  31   8]
- [ 18   3  13   3   7   8  82]]
-Node Classification on random seed  9929 -> 0.617
-Confusion Matrix:
- [[ 71   1   1   9   4  12   6]
- [  7 120   9   6   9   2   3]
- [ 23  21 157  48  22  20  32]
- [ 23   1  13 100   7   9   8]
- [  0   6   5   1  55   0   5]
- [ 10   1   2   0   0  35  13]
- [ 14   4   9   3   1  13  79]]
-Node Classification on random seed  9930 -> 0.59
-Confusion Matrix:
- [[ 61   0   3   5   2  15   9]
- [  3 131   0  11   1   6   0]
- [ 18  23 117  76  32  24  32]
- [ 16   5  14  94   6   9   8]
- [  0   9   3   4  67   2   2]
- [  6   0   5   1   0  50   9]
- [ 16   1  12   5   3  14  70]]
-Node Classification on random seed  9931 -> 0.652
-Confusion Matrix:
- [[ 74  10   2   4   1  10   9]
- [  4 139   7   2   4   1   3]
- [ 29  18 151  33  34  19  26]
- [  4   2  24  97   8   3  11]
- [  1   4   1   5  63   1   6]
- [  4   2   1   4   0  55   3]
- [ 11   4  11   8   4  10  73]]
-Node Classification on random seed  9932 -> 0.591
-Confusion Matrix:
- [[ 80   3   3   4   4  18   7]
- [  0 116   6   1  15   5   4]
- [ 24  10 127  25  56  22  38]
- [  9   5  28  74  16  12   8]
- [  1   4   1   2  61   2   5]
- [  3   1   0   2   0  66   3]
- [  6   5   7   6   9  29  67]]
-Node Classification on random seed  9933 -> 0.665
-Confusion Matrix:
- [[ 85   3   3   2   1  12   4]
- [  6 142   3   6  10   5   0]
- [ 14  19 154  22  28  18  37]
- [  7   4  15 101  10   5  20]
- [  0  10   1   0  64   2   4]
- [  3   2   5   2   0  43   6]
- [ 12   3   9   3   6  13  76]]
-Node Classification on random seed  9934 -> 0.649
-Confusion Matrix:
- [[ 68   1   1   5   4  11  14]
- [  1 135   9   2   4   2   3]
- [ 26  22 163  19  30  20  44]
- [ 13   9  12  92   4   4  10]
- [  0   6   2   3  60   2   3]
- [  4   3   1   2   0  49   2]
- [  4   2  18  12   2  15  82]]
-Node Classification on random seed  9935 -> 0.6
-Confusion Matrix:
- [[ 72   4   3   5   3   9   9]
- [  3 113   5  10   2   1   4]
- [ 26  44 164  17  20  16  40]
- [ 17   5  18  87  12   7  16]
- [  2   5   8   3  59   1   1]
- [  6   3   1   2   0  38   9]
- [ 12   9   7  15   4  16  67]]
-Node Classification on random seed  9936 -> 0.631
-Confusion Matrix:
- [[ 57   6   0   5   2  10   9]
- [  3 141   4   1   5   6   1]
- [ 23  30 145  32  36  24  36]
- [ 10   1   8 111   2   3  13]
- [  0   5   6   0  69   3   2]
- [  9   0   5   1   2  38   4]
- [ 21   4   9   8   8  12  70]]
-Node Classification on random seed  9937 -> 0.631
-Confusion Matrix:
- [[ 74   2   2   6   4  19   4]
- [  3 135   5   1  15   2   6]
- [ 35  12 144  11  27  50  28]
- [ 12   5  18 105   4   3   8]
- [  2   4   5   1  68   2   2]
- [  8   2   2   4   1  36   1]
- [ 20   1   5  18   3   6  69]]
-Node Classification on random seed  9938 -> 0.614
-Confusion Matrix:
- [[ 77   1  16   4   7   9   6]
- [  5 145   3   3  10   0   1]
- [ 35  16 118  60  25   9  44]
- [ 10   0   9 116   3   6   5]
- [  2   9   3   0  57   0   3]
- [  9   2   9   1   0  31   6]
- [ 15   4   4  11   7  14  70]]
-Node Classification on random seed  9939 -> 0.639
-Confusion Matrix:
- [[ 92   6   3   1   2   1   4]
- [  7 123   6   3   5   0   3]
- [ 35  21 141  33  30  19  31]
- [ 11   5  12 107   6   4  10]
- [  2  12   4   0  55   1   0]
- [ 15   2   4   0   0  43   1]
- [ 23   7  12   5   5  10  78]]
-Node Classification on random seed  9940 -> 0.574
-Confusion Matrix:
- [[ 52   1   2  12   3  19  17]
- [  9 118   5   0  16   0   2]
- [ 37   8 137  45  37  11  55]
- [ 13   3  13  99   3   8  14]
- [  0   5   1   1  56   3   2]
- [ 10   0   1   0   0  45   7]
- [ 35   2   8   4   4  10  67]]
-Node Classification on random seed  9941 -> 0.583
-Confusion Matrix:
- [[ 67   2   5   1   2  14  12]
- [  9 113   9   3  16   3   1]
- [ 36  32 137  42  39  31  19]
- [  6   6  15  98   6   5  17]
- [  2   4   2   4  55   2   2]
- [  4   0   0   0   0  43   6]
- [ 16   3   2   7  14  18  70]]
-Node Classification on random seed  9942 -> 0.608
-Confusion Matrix:
- [[ 75   4   1   7   5   7  19]
- [  0 144   1   5   5   5   4]
- [ 16  17 132  42  24  21  51]
- [  9   3  15 108  10   5  13]
- [  1   3   5   4  45   0   4]
- [  7   2   1   3   1  47   7]
- [ 13   6  14   9   6  17  57]]
-Node Classification on random seed  9943 -> 0.591
-Confusion Matrix:
- [[ 79   6   2   4   2  11  11]
- [  4 142   5   3  13   0   5]
- [ 29  27 129  45  22  29  34]
- [ 12   3  12  99   5  12   4]
- [  1   6   9   1  54   1   2]
- [  8   3   5   6   3  35   5]
- [ 18   4   5   5   4  23  53]]
-Node Classification on random seed  9944 -> 0.59
-Confusion Matrix:
- [[ 54   3   5  11  10  20   3]
- [  0 146   3   0   8   4   2]
- [ 17  24 130  51  37  21  27]
- [ 16   5  14  97   8   3  17]
- [  1  10   6   1  48   0   0]
- [  2   2   2   7   2  38   5]
- [ 13   6  12   8   8  16  77]]
-Node Classification on random seed  9945 -> 0.625
-Confusion Matrix:
- [[ 80   4   5   6   4  14   4]
- [  2 120   5   4   6   4   5]
- [ 27  26 164  31  28  22  40]
- [  8   1  17  98   5   4  15]
- [  0   1   7   3  54   1   4]
- [  3   0   4   2   2  46   3]
- [ 10   4  16   9   6  13  63]]
-Node Classification on random seed  9946 -> 0.617
-Confusion Matrix:
- [[ 68   0  11  10   3   6  13]
- [  3 129   4   5   3   2   7]
- [ 16  18 139  48  29  12  31]
- [ 11   2  19 118   3   5   9]
- [  2  12   7   0  54   0   3]
- [ 11   1   2  10   0  37   7]
- [ 11   2  15  10   2  18  72]]
-Node Classification on random seed  9947 -> 0.594
-Confusion Matrix:
- [[ 80   4   4   5   3  17   9]
- [  3 121   7   0   7   7   0]
- [ 27  24 145  23  21  32  39]
- [ 14   7  21  90   4   7  19]
- [  2  10   2   0  63   3   1]
- [  2   4   1   2   1  39   6]
- [ 14   3   7   6  26  12  56]]
-Node Classification on random seed  9948 -> 0.635
-Confusion Matrix:
- [[ 66   3   2   2   2  27  12]
- [  3 124   3   6   8   4   6]
- [ 21  16 155  48  20  14  42]
- [ 13   2  12  99   4   7  15]
- [  1   5   7   0  53   0   2]
- [  3   0   1   0   0  49   2]
- [  3   4   8   7  15  15  89]]
-Node Classification on random seed  9949 -> 0.616
-Confusion Matrix:
- [[ 88   0   4   2   4   3  14]
- [  6 124  13   0   4   4   5]
- [ 30  10 135  34  48  26  33]
- [ 26   2  11  92   4   7   7]
- [  2   7   6   1  51   2   2]
- [  6   0   8   2   0  52   6]
- [ 10   3   8  13   7   4  74]]
-Node Classification on random seed  9950 -> 0.635
-Confusion Matrix:
- [[ 65   5  14  11   2  10  10]
- [  3 131   6   4  10   0   3]
- [ 34  20 149  23  21  15  38]
- [  8   5  13 103   4   4  17]
- [  2   8   4   2  60   0   3]
- [  2   2   3   3   0  42   8]
- [  8   6   6  13   7   8  85]]
-Node Classification on random seed  9951 -> 0.602
-Confusion Matrix:
- [[ 50   3   6   4   3  18  20]
- [  2 137   2   4   2   7   2]
- [ 31  28 129  28  26  20  46]
- [ 15   6  17 104   3   7  17]
- [  1   8   5   0  65   1   3]
- [  3   2   7   1   0  39   5]
- [  5   1  10   9   9  11  78]]
-Node Classification on random seed  9952 -> 0.582
-Confusion Matrix:
- [[ 58   6   4   6   2  16  10]
- [  0 130  13   5  14   5   8]
- [ 16  21 121  37  36  33  39]
- [  6   3  14  98   6  11  15]
- [  3   6   4   4  61   2   2]
- [  2   1   4   4   0  38  12]
- [ 14   7   6   4   6  11  76]]
-Node Classification on random seed  9953 -> 0.606
-Confusion Matrix:
- [[ 75   3   4   9   3  11  14]
- [  5 115   7  10  17   3   1]
- [ 30  12 145  24  36  22  30]
- [ 14   6  15 115   8   8   9]
- [  1   1   7   2  60   0   2]
- [  2   0   0   0   3  46   8]
- [ 10   4   9  12  15  17  50]]
-Node Classification on random seed  9954 -> 0.647
-Confusion Matrix:
- [[ 63  11   1   3   3  10   9]
- [  6 125   7   2   7   4   3]
- [ 17  31 163  35  16  13  32]
- [ 16   7  16  98   2   8  15]
- [  0   7   7   2  57   1   1]
- [  8   2   0   1   0  46   7]
- [ 12   5  10   3   3  10  95]]
-Node Classification on random seed  9955 -> 0.612
-Confusion Matrix:
- [[ 60   0   5   6   4  13   7]
- [ 10 119   4   3   6  10   2]
- [ 22  22 157  21  28  29  40]
- [  8   0  29  94  14   8   7]
- [  0   2   4   1  64   0   3]
- [ 17   1   2   0   1  35   5]
- [ 16   0   6   7  10  15  83]]
-Node Classification on random seed  9956 -> 0.631
-Confusion Matrix:
- [[ 74   5   3   9   0   9   7]
- [ 13 116   7   4   8   2   4]
- [ 16   8 156  31  38  35  37]
- [ 19   6  11  89   2   7   9]
- [  0   2   9   1  67   0   3]
- [  7   2   0   2   0  58   0]
- [  6   4   8   5   7  23  71]]
-Node Classification on random seed  9957 -> 0.62
-Confusion Matrix:
- [[ 61   2   8   8   1   8   8]
- [  9 121   7   2  13   2   6]
- [ 24  11 150  35  18  29  35]
- [ 17   5  13 101   3   8   7]
- [  0   5   8   2  59   1   4]
- [  3   1   1   3   2  52   3]
- [ 12   3  10  13  10  20  76]]
-Node Classification on random seed  9958 -> 0.608
-Confusion Matrix:
- [[ 69   1   5   7   8  11  12]
- [  7 141   5   2   9   6   8]
- [ 21  21 139  45  31  14  24]
- [ 12   2  29  81   8   2  10]
- [  1   4   7   1  58   1   4]
- [  9   1   2   3   0  51   5]
- [ 12   2  10  10   9  11  69]]
-Node Classification on random seed  9959 -> 0.642
-Confusion Matrix:
- [[ 79   1   7   4   6   7  12]
- [  5 136   9   3   5   4   2]
- [ 30  23 139  32  51  13  24]
- [ 12   3  20 100   0   3  13]
- [  0   6   3   3  63   0   2]
- [  5   0   2   2   0  43   1]
- [ 12   1   7   4  14   7  82]]
-Node Classification on random seed  9960 -> 0.612
-Confusion Matrix:
- [[ 48   0   3   7   6  15  18]
- [  8 119   6   4  15   2  10]
- [ 25  10 167  28  32  27  35]
- [ 10   8  21 107   3  12   5]
- [  3   2   4   3  54   1   2]
- [  6   0   2   1   0  53   6]
- [  9   3  12   9   5  10  64]]
-Node Classification on random seed  9961 -> 0.61
-Confusion Matrix:
- [[ 82   1   2   4   7  11   6]
- [  9 118   8   7  12   3   6]
- [ 16  30 145  54  15  18  28]
- [  8  12  16  81   9   9   8]
- [  1   3   5   0  55   0   2]
- [  4   2   2   2   1  47   8]
- [ 10   5   1  11  13  21  82]]
-Node Classification on random seed  9962 -> 0.635
-Confusion Matrix:
- [[ 68   5   3   4   7   8  16]
- [  1 128   4   1   8   5   2]
- [ 18  16 176  25  15  25  41]
- [  8   5  19 102   5   8  11]
- [  2   6   8   6  52   2   3]
- [  5   1   3   4   0  40   5]
- [ 15   3  13   7   4  18  69]]
-Node Classification on random seed  9963 -> 0.616
-Confusion Matrix:
- [[ 62   0   9   1   2  12  12]
- [  9 117   7   5   7   3   1]
- [ 24  20 133  40  19  18  44]
- [ 17   6  17 108   4   9   9]
- [  2   7   5   3  55   1   3]
- [  3   4   2   0   3  54   4]
- [ 11   2  15   8   6  10  87]]
-Node Classification on random seed  9964 -> 0.603
-Confusion Matrix:
- [[ 74   1   1   5   6   9   8]
- [  2 118   7   1  12   2   3]
- [ 26  36 136  29  27  26  38]
- [ 16   9  13  98   5  12   9]
- [  0   6   1   1  71   1   2]
- [  4   0   6   1   8  37   3]
- [ 19   5   5   5   3  24  69]]
-Node Classification on random seed  9965 -> 0.606
-Confusion Matrix:
- [[ 70   1   4   2   5   6  18]
- [  6 111   5   6  12   5   3]
- [ 29  21 159  37  17  24  44]
- [ 19   3  14 101   4   9  13]
- [  1   4   2   4  55   2   0]
- [  3   1   1   0   0  45   7]
- [ 20   3   7  10   4  18  65]]
-Node Classification on random seed  9966 -> 0.629
-Confusion Matrix:
- [[ 74   4   3   3   2  11   9]
- [  2 113   2   4   2   3   7]
- [ 18  30 155  24  28  17  42]
- [ 12   5  16  99   5   7  14]
- [  0   9   3   2  63   2   2]
- [  2   2   5   2   3  45   6]
- [ 12   9  11   5   9  17  80]]
-Node Classification on random seed  9967 -> 0.622
-Confusion Matrix:
- [[ 75   3   4   8   9   5  10]
- [  2 135   7   2   9   5   7]
- [ 29  21 119  56  23  12  36]
- [ 12   3  11 102   5   2  11]
- [  2   4   6   1  60   0   3]
- [  8   1   2   5   0  42   7]
- [ 12   8   3   6   8  10  89]]
-Node Classification on random seed  9968 -> 0.583
-Confusion Matrix:
- [[ 71   4   4   9   1  15   7]
- [  3 144   4   2   2   2   8]
- [ 21  35 113  42  37  28  39]
- [ 12   9  16  95   2   4  20]
- [  4   5   1   1  52   1   1]
- [  3   1   3   3   2  43   5]
- [ 17   4  22   4   6   8  65]]
-Node Classification on random seed  9969 -> 0.648
-Confusion Matrix:
- [[ 83   2   5   5   4  15   8]
- [  2 122   4   1  12   2   1]
- [ 28  10 182  30  31  19  27]
- [  9   5  20  93   3   9  12]
- [  2   8   4   2  63   0   0]
- [  5   2   1   2   0  43   4]
- [  0   4  13   6  12  23  62]]
-Node Classification on random seed  9970 -> 0.621
-Confusion Matrix:
- [[ 54   6   6   6   7   9  14]
- [ 11 120   8   4  10   3   6]
- [ 18  27 157  23  32  29  34]
- [  9   2  13  94   5  11  12]
- [  0   4   1   3  68   1   2]
- [  7   0   2   4   1  45   1]
- [  7   5   5  13   2  16  83]]
-Node Classification on random seed  9971 -> 0.593
-Confusion Matrix:
- [[ 73  12   2   5   4   7   6]
- [  4 128   7   0   0   7   2]
- [ 27  23 128  46  38  11  30]
- [ 13   8  10  97  11   8  19]
- [  0   6   1   1  56   3   3]
- [ 11   5   1   3   0  40   8]
- [ 15   6  10  11   8  15  71]]
-Node Classification on random seed  9972 -> 0.606
-Confusion Matrix:
- [[ 72   9   1   4   2   4  11]
- [  6 128   7   0   8   1   3]
- [ 23  16 108  41  73  25  32]
- [  5   8  11 103   4   4  12]
- [  1   6   4   2  65   1   1]
- [  5   0   4   0   1  39  10]
- [ 10   4   6   9   7  13  91]]
-Node Classification on random seed  9973 -> 0.601
-Confusion Matrix:
- [[ 78   1  11   6   9  14   5]
- [  5 114   6   6   1   9   1]
- [ 24  16 141  67  11  21  31]
- [ 17   5  19  88   2   6  11]
- [  0  10   4   1  64   1   3]
- [  4   1   5   2   0  52   1]
- [ 22   2   3  11   6  19  64]]
-Node Classification on random seed  9974 -> 0.592
-Confusion Matrix:
- [[ 70   0   5   3   2   5  11]
- [  2 106  11   1   4   4   7]
- [ 26  19 145  28  59  22  41]
- [ 23   5  11  98   8   8  15]
- [  0  13   3   1  51   0   2]
- [ 10   1   1   5   0  44   3]
- [  4   5  15   7   8  10  78]]
-Node Classification on random seed  9975 -> 0.606
-Confusion Matrix:
- [[ 64   5  10   2   6  12   9]
- [  7 138   3   2   4   2   4]
- [ 33  21 137  37  43  27  31]
- [ 18   9  10  91   2   8  17]
- [  0   7   2   2  58   4   2]
- [  6   0   4   1   0  49   4]
- [  4   2  14   8   4   8  69]]
-Node Classification on random seed  9976 -> 0.618
-Confusion Matrix:
- [[ 69   1   6   3   2  11  15]
- [  6 116   4   4  26   4   6]
- [ 27  16 144  32  32  22  49]
- [  7   6  12 106   3   4  15]
- [  1   3   0   2  62   0   2]
- [  7   1   3   4   2  45   5]
- [ 15   3   5   5   4   7  76]]
-Node Classification on random seed  9977 -> 0.586
-Confusion Matrix:
- [[ 53   1  10  12   4  12   3]
- [  3 128  16   0   6   4   3]
- [ 17  25 141  35  40  34  26]
- [  5   0  28  83  11  15  10]
- [  1   6   5   1  61   3   4]
- [  6   5   4   1   0  48   1]
- [ 15   2  14   6   7  13  72]]
-Node Classification on random seed  9978 -> 0.603
-Confusion Matrix:
- [[ 67   9   6   5   4   9  12]
- [  8 119  14   4   3   0   4]
- [ 21  35 140  48  17  18  22]
- [  6  12  17 109   5   6  13]
- [  2   4   7   4  59   1   1]
- [  1   4   6   0   0  46   3]
- [ 10   6  15   8  11  16  63]]
-Node Classification on random seed  9979 -> 0.657
-Confusion Matrix:
- [[ 68   3   1   3   2  20  12]
- [  6 124   4   1  10   1   4]
- [ 35  13 153  32  38  14  28]
- [ 10   1   8 120   4   5  14]
- [  0   5   0   5  65   0   1]
- [  3   0   2   2   2  42   4]
- [  9   4   6   8   4  19  85]]
-Node Classification on random seed  9980 -> 0.582
-Confusion Matrix:
- [[ 72   9   3   7   4  17   8]
- [  4 125   5   9   9   2   1]
- [ 36  31 132  30  17  20  36]
- [ 31   1  25  75   5   9  14]
- [  1   6   4   1  61   0   2]
- [  6   2   0   6   0  42   3]
- [ 18   2   9   8   5  12  75]]
-Node Classification on random seed  9981 -> 0.592
-Confusion Matrix:
- [[ 81   4   3   5   2  12  12]
- [  9 127   7   1  13   0   2]
- [ 25  25 127  24  35  25  41]
- [ 11   3  18  98  10   2  13]
- [  1   4   3   1  61   0   4]
- [  8   0   3   1   1  41   4]
- [ 34   4  10   7  14   7  57]]
-Node Classification on random seed  9982 -> 0.586
-Confusion Matrix:
- [[ 69   5   1   9  13   6   6]
- [  5 130   2   0  17   9   1]
- [ 19  42  95  53  31  24  38]
- [ 14   8  10 123   9   2   7]
- [  0   6   4   0  55   0   1]
- [ 11   1   2   3   1  50   2]
- [  9   3   6   9   8  17  64]]
-Node Classification on random seed  9983 -> 0.59
-Confusion Matrix:
- [[ 70   0   7   1   5  17   5]
- [  6 128   3   2   8   5   6]
- [ 32  21 103  50  52  22  31]
- [  5   2  12  91   9  11  19]
- [  1   7   5   0  63   1   3]
- [  7   0   2   4   1  44   0]
- [ 11   1   8   5   0  23  91]]
-Node Classification on random seed  9984 -> 0.611
-Confusion Matrix:
- [[ 75   7   6   2   6  17   3]
- [ 16 121   4   3   6   1   7]
- [ 28  18 129  32  35  15  41]
- [ 12   3   4  93   8   6  20]
- [  3   4   1   3  75   0   1]
- [  7   1   3   0   1  43   5]
- [ 29   3   7   6   7   8  75]]
-Node Classification on random seed  9985 -> 0.608
-Confusion Matrix:
- [[ 70   1   3   1   1   8  16]
- [  9 135   7   2   7   3   7]
- [ 23  17 120  25  44  31  45]
- [  3   4  16 107   9   9  20]
- [  1   5   3   0  65   2   5]
- [  4   0   2   1   0  44   6]
- [ 14   2   5   5   6  20  67]]
-Node Classification on random seed  9986 -> 0.636
-Confusion Matrix:
- [[ 76   2   3   5   2   9   7]
- [  4 114  16   3   3  12   5]
- [ 34  16 160  27  15  24  33]
- [ 13   3  16 101   4   5  13]
- [  1   6   9   1  65   4   4]
- [  8   1   3   1   1  49   2]
- [ 11   4   8   4   3  19  71]]
-Node Classification on random seed  9987 -> 0.64
-Confusion Matrix:
- [[ 75   0   3   3   5  14   8]
- [  5 127   6   6   5   3   2]
- [ 20  22 143  28  35  21  36]
- [ 15   3  17 101   7   5  14]
- [  2   7   2   0  55   0   1]
- [  7   1   5   0   0  51   4]
- [ 10   7   2  13   4  12  88]]
-Node Classification on random seed  9988 -> 0.655
-Confusion Matrix:
- [[ 81   4   4   6  10   9   5]
- [  0 133   7   0  10   4   4]
- [ 11  19 168  21  37  10  49]
- [  3   5  13 106  10   3  14]
- [  0   4   5   3  62   1   1]
- [  4   4   0   4   5  44   4]
- [  9   6   1  16   9  11  61]]
-Node Classification on random seed  9989 -> 0.64
-Confusion Matrix:
- [[ 69   7   1   3   2  14  10]
- [  6 119   8   1  10   8   4]
- [ 26   9 177  15  25  43  23]
- [ 12   0  24  96   5   9   8]
- [  0   5   6   2  69   3   2]
- [ 11   1   0   3   0  41   8]
- [  5   2   7   6   1  25  69]]
-Node Classification on random seed  9990 -> 0.644
-Confusion Matrix:
- [[ 79   1   3   5   1  10   9]
- [  2 120  10   3   8   2   7]
- [ 20  20 153  31  26  29  44]
- [  5   3   9 126   2   6   9]
- [  1   3   3   3  53   1   3]
- [  5   2   1   5   4  53   5]
- [ 13   3   7  12   3  17  60]]
-Node Classification on random seed  9991 -> 0.626
-Confusion Matrix:
- [[ 67   1   4   6   2   8  11]
- [  3 134   9   3   9   2   6]
- [ 16  18 148  46  41  12  41]
- [ 10   0  10  90   6   4  12]
- [  1   8   6   1  66   3   3]
- [  1   2   1   4   1  48   6]
- [  6   2  14  14   8  13  73]]
-Node Classification on random seed  9992 -> 0.625
-Confusion Matrix:
- [[ 69   5   1   6   3   3   3]
- [  3 134   5   2   9   4   7]
- [ 31  39 132  16  26  27  41]
- [  6  10  19 110   2   6   1]
- [  1  11   1   1  66   0   4]
- [  7   0   1   2   3  40   2]
- [ 22   3  11   4   4  23  74]]
-Node Classification on random seed  9993 -> 0.618
-Confusion Matrix:
- [[ 62   4   1  10   6  14  11]
- [  4 127   4   3   4   2   6]
- [  8  31 159  28  26  20  52]
- [  8   7  21  89   5   7  11]
- [  2   7   2   1  61   2   0]
- [  2   2   5   1   0  53   6]
- [ 11   3  10   8   7  20  67]]
-Node Classification on random seed  9994 -> 0.591
-Confusion Matrix:
- [[ 61   8   9   2   6   5  19]
- [  3 149   7   1   4   2   5]
- [ 46  38 123  34  17  34  31]
- [  8   6  17  93  11   3  13]
- [  3   8   5   0  50   0   3]
- [  4   1   1   3   1  43   4]
- [  6   5   8   5   8  15  72]]
-Node Classification on random seed  9995 -> 0.6
-Confusion Matrix:
- [[ 58   1   4   7   8  10  13]
- [  0 122  11   2  18   5   7]
- [ 14  20 147  42  43  23  30]
- [  6   2  23 101   4   1   9]
- [  0   4   3   2  63   3   9]
- [  1   0   2   3   4  37   7]
- [  9   2   4  14   3  27  72]]
-Node Classification on random seed  9996 -> 0.607
-Confusion Matrix:
- [[ 80   1   1   5   2  15   8]
- [  5 116  11   5   6   3   7]
- [ 32  21 131  38  39  21  33]
- [ 12   1  16  97   2   8  11]
- [  1   5   5   1  64   0   1]
- [ 14   2   5   0   1  54   3]
- [ 10   4   9   7   4  18  65]]
-Node Classification on random seed  9997 -> 0.553
-Confusion Matrix:
- [[ 65   3  12  11   7  18   9]
- [  5 118   1   2   7   5   9]
- [ 14  43 110  54  31  39  29]
- [  4   2  13  96   4   8  16]
- [  4   4   6   3  53   0   1]
- [  5   5   4   1   0  40   6]
- [ 11   2  16   9  14  10  71]]
-Node Classification on random seed  9998 -> 0.642
-Confusion Matrix:
- [[ 96   4   0   3   3   6   4]
- [  5 124   5  11   6   3   1]
- [ 40  25 155  28  21  14  33]
- [ 13   6   8  90   2   5  18]
- [  1  10   6   4  55   0   5]
- [  6   5   1   1   1  47   0]
- [ 21   6   2   3   9  13  75]]
-Node Classification on random seed  9999 -> 0.645
-Confusion Matrix:
- [[ 65   0   5   2   7   9  11]
- [  1 140   5   3  13   3   4]
- [ 39  21 167  19  20  33  32]
- [ 17   3  18  93   6   6   9]
- [  2   1   3   2  62   1   7]
- [  5   0   2   1   0  42  10]
- [ 10   1   6  10   3   5  76]]
-[0.561, 0.611, 0.586, 0.623, 0.613, 0.63, 0.604, 0.576, 0.573, 0.56, 0.615, 0.593, 0.583, 0.584, 0.586, 0.645, 0.617, 0.625, 0.605, 0.626, 0.629, 0.631, 0.626, 0.64, 0.589, 0.621, 0.576, 0.626, 0.603, 0.613, 0.603, 0.614, 0.627, 0.624, 0.652, 0.648, 0.643, 0.626, 0.602, 0.618, 0.624, 0.583, 0.633, 0.607, 0.613, 0.585, 0.587, 0.621, 0.604, 0.612, 0.632, 0.614, 0.61, 0.634, 0.623, 0.611, 0.623, 0.599, 0.586, 0.618, 0.627, 0.613, 0.627, 0.587, 0.626, 0.605, 0.607, 0.607, 0.65, 0.581, 0.593, 0.635, 0.574, 0.634, 0.591, 0.589, 0.604, 0.614, 0.605, 0.644, 0.653, 0.606, 0.603, 0.594, 0.603, 0.607, 0.606, 0.597, 0.622, 0.628, 0.62, 0.593, 0.634, 0.605, 0.597, 0.589, 0.628, 0.619, 0.615, 0.641, 0.601, 0.628, 0.627, 0.615, 0.621, 0.592, 0.609, 0.627, 0.55, 0.556, 0.67, 0.638, 0.624, 0.62, 0.589, 0.605, 0.651, 0.613, 0.633, 0.661, 0.575, 0.622, 0.636, 0.645, 0.632, 0.621, 0.639, 0.611, 0.603, 0.66, 0.652, 0.616, 0.576, 0.629, 0.66, 0.62, 0.613, 0.656, 0.626, 0.618, 0.584, 0.632, 0.626, 0.663, 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-[3875, 4067, 158, 2146, 8189, 1380, 7411, 9380, 5370, 6628]
-Maximum:  0.69 Seed:  3875
-Average:  0.614349100000002
-10 Higest Scores:
-1 : 0.69 on Seed 3875
-2 : 0.687 on Seed 4067
-3 : 0.686 on Seed 158
-4 : 0.685 on Seed 2146
-5 : 0.683 on Seed 8189
-6 : 0.682 on Seed 1380
-7 : 0.682 on Seed 7411
-8 : 0.682 on Seed 9380
-9 : 0.68 on Seed 5370
-10 : 0.68 on Seed 6628
diff --git a/EP/Cora_node_classification/node_classification.py b/EP/Cora_node_classification/node_classification.py
index ee430ae94089cf105cb1e07d9c84362ba34358b1..1ab131557a918ca1caecbe2a294c4ac6fffa1cb8 100644
--- a/EP/Cora_node_classification/node_classification.py
+++ b/EP/Cora_node_classification/node_classification.py
@@ -4,6 +4,7 @@
 @author: Utaemon Toyota
 @date: 31.1.2019
 @project: Software Projekt @ Heidelberg University, Institute for Computational Linguistics
+@requirements: cora.py and random_nodes_for_node_classification.py as well as the cora data
 @usage: python3 node_classification.py [-g] [-e] [-s] [-i] [-n]
         -g / --graph        Path to pickled networkX-graph
         -e / --embeddings   Path to pickled embeddings
diff --git a/EP/Cora_node_classification/random_nodes_for_node_classification.py b/EP/Cora_node_classification/random_nodes_for_node_classification.py
index 59212b91ca26a340dae12ecbf094292a58793645..b4ae51dd2f2eb182d662b9733add75291a55c8a2 100644
--- a/EP/Cora_node_classification/random_nodes_for_node_classification.py
+++ b/EP/Cora_node_classification/random_nodes_for_node_classification.py
@@ -1,3 +1,9 @@
+"""
+@requirements: cora.py
+@info: Will be imported from node_classification.
+"""
+
+
 import cora
 import pickle as pkl
 import random
@@ -21,7 +27,7 @@ def get_random_num_nodes(set_elm, num, seed):
     random.seed(seed)
     return set(random.sample(set_elm, num))
 
-def get_num_random_nodes_for_all_classes_read(path = "/home/utaemon/SP/graph.pkl", num = 20, seed = 1):
+def get_num_random_nodes_for_all_classes_read(path = "graph.pkl", num = 20, seed = 1):
     """get specific number of nodes per class, same number for all classes"""
     cora_dict = dict_of_node_classes_read(path)
     sampled_random_id_set = set()
@@ -29,17 +35,3 @@ def get_num_random_nodes_for_all_classes_read(path = "/home/utaemon/SP/graph.pkl
         for id in get_random_num_nodes(cora_dict[key], num, seed):
             sampled_random_id_set.add(id)
     return sampled_random_id_set
-
-
-#unused
-'''
-def get_num_of_random_nodes(path = "/home/utaemon/SP/graph.pkl", seed=0, num = 3):
-    """Get random nodes."""
-    random.seed(seed)
-    cora_nodes = set(read_graph(path).nodes)
-    return set(random.sample(cora_nodes, num))
-
-def pickle_output(method = get_num_random_nodes_for_all_classes_read(), output = "random_nodes.pkl"):
-    with open(output, "wb") as file:
-        pkl.dump(method, file)
-'''
\ No newline at end of file
diff --git a/EP/cora_embeddings_2.pkl b/EP/cora_embeddings_2.pkl
deleted file mode 100644
index adaa623ac5ff1f21584b7675263c197f34443b58..0000000000000000000000000000000000000000
Binary files a/EP/cora_embeddings_2.pkl and /dev/null differ
diff --git a/EP/cora_embeddings_norm.pkl b/EP/cora_embeddings_norm.pkl
deleted file mode 100644
index 41e8144fb8472ca1fffa492e1593e6d334b8e8c8..0000000000000000000000000000000000000000
Binary files a/EP/cora_embeddings_norm.pkl and /dev/null differ
diff --git a/EP/node_classification_1000.txt b/EP/node_classification_1000.txt
deleted file mode 100644
index 795ab1dd26085081773fd854d5795d71b89c95d2..0000000000000000000000000000000000000000
--- a/EP/node_classification_1000.txt
+++ /dev/null
@@ -1,145 +0,0 @@
-C=0.1
-
-max
-0.652
-avg
-0.5900960000000008
-
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-
-
-C Bestimmung
-/usr/bin/python3 /home/utaemon/PycharmProjects/Softwareprojekt/node_classification.py
-Iteration/Random Seed: 0
-C = 0.01
-0.558
-C = 0.1
-0.564
-C = 0.5
-0.564
-C = 1.0
-0.561
-C = 5.0
-0.542
-C = 10.0
-0.544
-Iteration/Random Seed: 1
-C = 0.01
-0.642
-C = 0.1
-0.635
-C = 0.5
-0.628
-C = 1.0
-0.619
-C = 5.0
-0.611
-C = 10.0
-0.61
-Iteration/Random Seed: 2
-C = 0.01
-0.549
-C = 0.1
-0.57
-C = 0.5
-0.553
-C = 1.0
-0.548
-C = 5.0
-0.539
-C = 10.0
-0.538
-Iteration/Random Seed: 3
-C = 0.01
-0.629
-C = 0.1
-0.624
-C = 0.5
-0.608
-C = 1.0
-0.603
-C = 5.0
-0.578
-C = 10.0
-0.575
-Iteration/Random Seed: 4
-C = 0.01
-0.62
-C = 0.1
-0.638
-C = 0.5
-0.632
-C = 1.0
-0.632
-C = 5.0
-0.629
-C = 10.0
-0.631
-Iteration/Random Seed: 5
-C = 0.01
-0.595
-C = 0.1
-0.615
-C = 0.5
-0.62
-C = 1.0
-0.622
-C = 5.0
-0.616
-C = 10.0
-0.61
-Iteration/Random Seed: 6
-C = 0.01
-0.607
-C = 0.1
-0.626
-C = 0.5
-0.618
-C = 1.0
-0.61
-C = 5.0
-0.598
-C = 10.0
-0.589
-Iteration/Random Seed: 7
-C = 0.01
-0.596
-C = 0.1
-0.603
-C = 0.5
-0.587
-C = 1.0
-0.581
-C = 5.0
-0.563
-C = 10.0
-0.561
-Iteration/Random Seed: 8
-C = 0.01
-0.602
-C = 0.1
-0.619
-C = 0.5
-0.617
-C = 1.0
-0.611
-C = 5.0
-0.608
-C = 10.0
-0.605
-Iteration/Random Seed: 9
-C = 0.01
-0.58
-C = 0.1
-0.595
-C = 0.5
-0.585
-C = 1.0
-0.577
-C = 5.0
-0.563
-C = 10.0
-0.56
-
-Process finished with exit code 0
-
diff --git a/Senseval_Prep/Senseval3/cl23.mrg b/Senseval_Prep/Senseval3/cl23.mrg
index 0762f6cd08a248beae0d1a336aa2323de5408b1b..4987e8b4f23fcbd1ca75dd92a779e837caa60f5c 100644
--- a/Senseval_Prep/Senseval3/cl23.mrg
+++ b/Senseval_Prep/Senseval3/cl23.mrg
@@ -1,3 +1,15 @@
+*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*
+*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*
+*x*                                                                     *x*
+*x*            Copyright (C) 1995 University of Pennsylvania            *x*
+*x*                                                                     *x*
+*x*    The data in this file are part of a preliminary version of the   *x*
+*x*    Penn Treebank Corpus and should not be redistributed.  Any       *x*
+*x*    research using this corpus or based on it should acknowledge     *x*
+*x*    that fact, as well as the preliminary nature of the corpus.      *x*
+*x*                                                                     *x*
+*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*
+*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*
 
 ( (S 
     (NP-SBJ (DT That) )
diff --git a/Senseval_Prep/senseval_preprocessing.py b/Senseval_Prep/senseval_preprocessing.py
index 4389e11e96c129eb54a22bcbbd0da5a2fc9992c6..c24bf891bb74b5f6ee22c25eef5f32c60a7fcce7 100644
--- a/Senseval_Prep/senseval_preprocessing.py
+++ b/Senseval_Prep/senseval_preprocessing.py
@@ -29,6 +29,9 @@ def get_stopword_list(stop_path):
         stopli = []
         for line in f:
             stopli.append(line[:-1])
+        stopli.append("n't")
+        stopli.append("'m")
+        stopli.append("whether")
         return stopli
 
 def get_infos(tree_path):