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OpenML
Task
Supervised Classification on hungarian

Supervised Classification on hungarian

Task 3722 Supervised Classification hungarian 495 runs submitted
0 likes downloaded by 0 people , 0 total downloads 0 issues
Visibility: Public
  • mythbusting_1 study_1 study_107 study_123 study_15 study_20 study_41 under100k under1m
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495 Runs

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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8657, f_measure: 0.821, kappa: 0.6084, kb_relative_information_score: 162.0175, mean_absolute_error: 0.2048, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.821, predictive_accuracy: 0.8231, prior_entropy: 0.9439, recall: 0.8231, relative_absolute_error: 0.444, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.3666, root_relative_squared_error: 0.7635, scimark_benchmark: 942.9518, usercpu_time_millis: 40, usercpu_time_millis_testing: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8406, f_measure: 0.8449, kappa: 0.6675, kb_relative_information_score: 190.6782, mean_absolute_error: 0.1565, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.8483, predictive_accuracy: 0.8435, prior_entropy: 0.9439, recall: 0.8435, relative_absolute_error: 0.3391, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.3956, root_relative_squared_error: 0.8238, scimark_benchmark: 1304.9611, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7985, f_measure: 0.8238, kappa: 0.6135, kb_relative_information_score: 179.4738, mean_absolute_error: 0.1735, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.8245, predictive_accuracy: 0.8265, prior_entropy: 0.9439, recall: 0.8265, relative_absolute_error: 0.376, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.4165, root_relative_squared_error: 0.8674, scimark_benchmark: 916.6405, usercpu_time_millis: 60, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8153, f_measure: 0.838, kappa: 0.6453, kb_relative_information_score: 188.4374, mean_absolute_error: 0.1599, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.8385, predictive_accuracy: 0.8401, prior_entropy: 0.9439, recall: 0.8401, relative_absolute_error: 0.3465, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.3998, root_relative_squared_error: 0.8327, scimark_benchmark: 1297.6599, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9061, f_measure: 0.8497, kappa: 0.6727, kb_relative_information_score: 163.5012, mean_absolute_error: 0.2095, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.8494, predictive_accuracy: 0.8503, prior_entropy: 0.9439, recall: 0.8503, relative_absolute_error: 0.4541, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.3394, root_relative_squared_error: 0.7068, scimark_benchmark: 1304.9611, usercpu_time_millis: 70, usercpu_time_millis_training: 70,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7041, f_measure: 0.6827, kappa: 0.3681, kb_relative_information_score: 80.8747, mean_absolute_error: 0.3231, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.7327, predictive_accuracy: 0.6769, prior_entropy: 0.9439, recall: 0.6769, relative_absolute_error: 0.7004, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.5684, root_relative_squared_error: 1.1839, scimark_benchmark: 916.5955, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9069, f_measure: 0.832, kappa: 0.6333, kb_relative_information_score: 161.6632, mean_absolute_error: 0.2099, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.8317, predictive_accuracy: 0.8333, prior_entropy: 0.9439, recall: 0.8333, relative_absolute_error: 0.455, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.3436, root_relative_squared_error: 0.7156, scimark_benchmark: 934.6432, usercpu_time_millis: 4050, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 4010,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9124, f_measure: 0.8486, kappa: 0.6686, kb_relative_information_score: 181.8758, mean_absolute_error: 0.1766, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.849, predictive_accuracy: 0.8503, prior_entropy: 0.9439, recall: 0.8503, relative_absolute_error: 0.3829, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.3481, root_relative_squared_error: 0.725, scimark_benchmark: 1290.1085,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9163, f_measure: 0.8453, kappa: 0.6618, kb_relative_information_score: 172.9232, mean_absolute_error: 0.1947, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.8455, predictive_accuracy: 0.8469, prior_entropy: 0.9439, recall: 0.8469, relative_absolute_error: 0.4219, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.3336, root_relative_squared_error: 0.6947, scimark_benchmark: 1368.9272, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.899, f_measure: 0.8316, kappa: 0.6317, kb_relative_information_score: 165.8808, mean_absolute_error: 0.2007, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.8315, predictive_accuracy: 0.8333, prior_entropy: 0.9439, recall: 0.8333, relative_absolute_error: 0.4349, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.3618, root_relative_squared_error: 0.7535, scimark_benchmark: 1350.9691, usercpu_time_millis: 270, usercpu_time_millis_training: 270,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8862, f_measure: 0.8137, kappa: 0.5916, kb_relative_information_score: 140.7007, mean_absolute_error: 0.2453, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.8139, predictive_accuracy: 0.8163, prior_entropy: 0.9439, recall: 0.8163, relative_absolute_error: 0.5318, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.3589, root_relative_squared_error: 0.7474, scimark_benchmark: 1280.6952, usercpu_time_millis: 60, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7118, f_measure: 0.7185, kappa: 0.3915, kb_relative_information_score: 111.4734, mean_absolute_error: 0.2766, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.7195, predictive_accuracy: 0.7177, prior_entropy: 0.9439, recall: 0.7177, relative_absolute_error: 0.5996, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.5181, root_relative_squared_error: 1.0791, scimark_benchmark: 1301.9956,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8259, f_measure: 0.7999, kappa: 0.5613, kb_relative_information_score: 126.5002, mean_absolute_error: 0.2712, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.7999, predictive_accuracy: 0.8027, prior_entropy: 0.9439, recall: 0.8027, relative_absolute_error: 0.5878, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.3934, root_relative_squared_error: 0.8194, scimark_benchmark: 1306.6379, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.816, f_measure: 0.8167, kappa: 0.6033, kb_relative_information_score: 139.0569, mean_absolute_error: 0.2531, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.8171, predictive_accuracy: 0.8163, prior_entropy: 0.9439, recall: 0.8163, relative_absolute_error: 0.5485, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.3821, root_relative_squared_error: 0.7957, scimark_benchmark: 1354.2491, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7787, f_measure: 0.7959, kappa: 0.5574, kb_relative_information_score: 159.3058, mean_absolute_error: 0.2041, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.7959, predictive_accuracy: 0.7959, prior_entropy: 0.9439, recall: 0.7959, relative_absolute_error: 0.4423, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.4518, root_relative_squared_error: 0.9408, scimark_benchmark: 1291.6995, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6069, f_measure: 0.655, kappa: 0.2457, kb_relative_information_score: 94.32, mean_absolute_error: 0.3027, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.6974, predictive_accuracy: 0.6973, prior_entropy: 0.9439, recall: 0.6973, relative_absolute_error: 0.6561, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.5502, root_relative_squared_error: 1.1459, scimark_benchmark: 1287.514, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8656, f_measure: 0.8078, kappa: 0.58, kb_relative_information_score: 137.5103, mean_absolute_error: 0.2502, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.8073, predictive_accuracy: 0.8095, prior_entropy: 0.9439, recall: 0.8095, relative_absolute_error: 0.5424, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.3737, root_relative_squared_error: 0.7782, scimark_benchmark: 1392.1129,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7676, f_measure: 0.7981, kappa: 0.5557, kb_relative_information_score: 163.7876, mean_absolute_error: 0.1973, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.8001, predictive_accuracy: 0.8027, prior_entropy: 0.9439, recall: 0.8027, relative_absolute_error: 0.4276, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.4442, root_relative_squared_error: 0.925, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7393, f_measure: 0.7749, kappa: 0.5034, kb_relative_information_score: 150.3423, mean_absolute_error: 0.2177, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.7793, predictive_accuracy: 0.7823, prior_entropy: 0.9439, recall: 0.7823, relative_absolute_error: 0.4718, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.4666, root_relative_squared_error: 0.9717, scimark_benchmark: 1353.5686,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4843, f_measure: 0.4988, kb_relative_information_score: -0.1652, mean_absolute_error: 0.4614, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.4089, predictive_accuracy: 0.6395, prior_entropy: 0.9439, recall: 0.6395, relative_absolute_error: 1.0001, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.4802, root_relative_squared_error: 1.0001, scimark_benchmark: 1358.4955,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7675, f_measure: 0.7993, kappa: 0.5595, kb_relative_information_score: 117.5243, mean_absolute_error: 0.2905, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.7998, predictive_accuracy: 0.8027, prior_entropy: 0.9439, recall: 0.8027, relative_absolute_error: 0.6297, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.4034, root_relative_squared_error: 0.8401, scimark_benchmark: 1466.6185,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8892, f_measure: 0.8461, kappa: 0.6646, kb_relative_information_score: 192.0464, mean_absolute_error: 0.1546, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.8458, predictive_accuracy: 0.8469, prior_entropy: 0.9439, recall: 0.8469, relative_absolute_error: 0.3352, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.3784, root_relative_squared_error: 0.788, scimark_benchmark: 931.2336, usercpu_time_millis: 40, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.877, f_measure: 0.8464, kappa: 0.666, kb_relative_information_score: 172.5101, mean_absolute_error: 0.1936, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.8461, predictive_accuracy: 0.8469, prior_entropy: 0.9439, recall: 0.8469, relative_absolute_error: 0.4196, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.356, root_relative_squared_error: 0.7415, scimark_benchmark: 941.7954, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.877, f_measure: 0.8464, kappa: 0.666, kb_relative_information_score: 172.5101, mean_absolute_error: 0.1936, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.8461, predictive_accuracy: 0.8469, prior_entropy: 0.9439, recall: 0.8469, relative_absolute_error: 0.4196, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.356, root_relative_squared_error: 0.7415, scimark_benchmark: 923.7642, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.877, f_measure: 0.8464, kappa: 0.666, kb_relative_information_score: 172.5101, mean_absolute_error: 0.1936, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.8461, predictive_accuracy: 0.8469, prior_entropy: 0.9439, recall: 0.8469, relative_absolute_error: 0.4196, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.356, root_relative_squared_error: 0.7415, scimark_benchmark: 894.7455, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8951, f_measure: 0.8302, kappa: 0.627, kb_relative_information_score: 177.7633, mean_absolute_error: 0.1775, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.8318, predictive_accuracy: 0.8333, prior_entropy: 0.9439, recall: 0.8333, relative_absolute_error: 0.3847, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.3952, root_relative_squared_error: 0.8231, scimark_benchmark: 894.7455, usercpu_time_millis: 90, usercpu_time_millis_training: 90,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9014, f_measure: 0.8201, kappa: 0.605, kb_relative_information_score: 176.4946, mean_absolute_error: 0.1784, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.8211, predictive_accuracy: 0.8231, prior_entropy: 0.9439, recall: 0.8231, relative_absolute_error: 0.3867, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.3968, root_relative_squared_error: 0.8263, scimark_benchmark: 936.7115, usercpu_time_millis: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8967, f_measure: 0.8184, kappa: 0.6, kb_relative_information_score: 172.8509, mean_absolute_error: 0.1846, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.8222, predictive_accuracy: 0.8231, prior_entropy: 0.9439, recall: 0.8231, relative_absolute_error: 0.4002, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.4015, root_relative_squared_error: 0.8361, scimark_benchmark: 911.3823, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8945, f_measure: 0.8184, kappa: 0.6, kb_relative_information_score: 174.6889, mean_absolute_error: 0.1822, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.8222, predictive_accuracy: 0.8231, prior_entropy: 0.9439, recall: 0.8231, relative_absolute_error: 0.3948, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.4042, root_relative_squared_error: 0.8417, scimark_benchmark: 934.5243, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8873, f_measure: 0.8076, kappa: 0.576, kb_relative_information_score: 166.2012, mean_absolute_error: 0.1949, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.8116, predictive_accuracy: 0.8129, prior_entropy: 0.9439, recall: 0.8129, relative_absolute_error: 0.4225, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.4196, root_relative_squared_error: 0.8739, scimark_benchmark: 938.4285, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8406, f_measure: 0.7709, kappa: 0.5006, kb_relative_information_score: 141.2063, mean_absolute_error: 0.2343, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.7701, predictive_accuracy: 0.7721, prior_entropy: 0.9439, recall: 0.7721, relative_absolute_error: 0.5079, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.4113, root_relative_squared_error: 0.8565, scimark_benchmark: 933.8635, usercpu_time_millis: 100, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 90,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8623, f_measure: 0.784, kappa: 0.5285, kb_relative_information_score: 150.2159, mean_absolute_error: 0.224, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.7833, predictive_accuracy: 0.7857, prior_entropy: 0.9439, recall: 0.7857, relative_absolute_error: 0.4855, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.3839, root_relative_squared_error: 0.7994, scimark_benchmark: 924.6116, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8742, f_measure: 0.8105, kappa: 0.5849, kb_relative_information_score: 151.661, mean_absolute_error: 0.2245, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.8105, predictive_accuracy: 0.8129, prior_entropy: 0.9439, recall: 0.8129, relative_absolute_error: 0.4867, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.3769, root_relative_squared_error: 0.7849, scimark_benchmark: 924.6116, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7888, build_cpu_time: 0.0349, build_memory: 1086352631.8367, f_measure: 0.7522, kappa: 0.4577, kb_relative_information_score: 126.9461, mean_absolute_error: 0.2572, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.7512, predictive_accuracy: 0.7551, prior_entropy: 0.9439, recall: 0.7551, relative_absolute_error: 0.5576, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.4511, root_relative_squared_error: 0.9395, scimark_benchmark: 916.8903,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8934, build_cpu_time: 2.6189, build_memory: 36819546.6122, f_measure: 0.7911, kappa: 0.5404, kb_relative_information_score: 160.9635, mean_absolute_error: 0.2044, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.7929, predictive_accuracy: 0.7959, prior_entropy: 0.9439, recall: 0.7959, relative_absolute_error: 0.443, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.3776, root_relative_squared_error: 0.7864, scimark_benchmark: 899.4388,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8793, build_cpu_time: 4.9066, build_memory: 727284226.6667, f_measure: 0.7967, kappa: 0.5547, kb_relative_information_score: 159.1983, mean_absolute_error: 0.2049, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.7964, predictive_accuracy: 0.7993, prior_entropy: 0.9439, recall: 0.7993, relative_absolute_error: 0.444, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.3994, root_relative_squared_error: 0.8317, scimark_benchmark: 946.4503,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8529, build_cpu_time: 10.5845, build_memory: 32745343.8367, f_measure: 0.794, kappa: 0.55, kb_relative_information_score: 157.6842, mean_absolute_error: 0.2075, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.7934, predictive_accuracy: 0.7959, prior_entropy: 0.9439, recall: 0.7959, relative_absolute_error: 0.4497, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.4244, root_relative_squared_error: 0.8838, scimark_benchmark: 939.521,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8416, build_cpu_time: 20.7626, build_memory: 649855242.9932, f_measure: 0.7809, kappa: 0.522, kb_relative_information_score: 153.9807, mean_absolute_error: 0.2117, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.7801, predictive_accuracy: 0.7823, prior_entropy: 0.9439, recall: 0.7823, relative_absolute_error: 0.4589, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.4422, root_relative_squared_error: 0.9209, scimark_benchmark: 943.8134,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.827, build_cpu_time: 41.5352, build_memory: 447121242.1769, f_measure: 0.7987, kappa: 0.5621, kb_relative_information_score: 157.9396, mean_absolute_error: 0.2062, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.7982, predictive_accuracy: 0.7993, prior_entropy: 0.9439, recall: 0.7993, relative_absolute_error: 0.4468, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.4415, root_relative_squared_error: 0.9196, scimark_benchmark: 937.5757,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7822, build_cpu_time: 34.0319, build_memory: 69363830.5034, f_measure: 0.7945, kappa: 0.5519, kb_relative_information_score: 159.2652, mean_absolute_error: 0.2042, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.7939, predictive_accuracy: 0.7959, prior_entropy: 0.9439, recall: 0.7959, relative_absolute_error: 0.4425, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.4517, root_relative_squared_error: 0.9408, scimark_benchmark: 925.7673,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7907, build_cpu_time: 8.5969, build_memory: 128322798.9932, f_measure: 0.7872, kappa: 0.535, kb_relative_information_score: 154.596, mean_absolute_error: 0.2114, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.7865, predictive_accuracy: 0.7891, prior_entropy: 0.9439, recall: 0.7891, relative_absolute_error: 0.4582, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.4568, root_relative_squared_error: 0.9514, scimark_benchmark: 942.0692,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8307, build_cpu_time: 4.5897, build_memory: 119776215.8367, f_measure: 0.7716, kappa: 0.4987, kb_relative_information_score: 146.183, mean_absolute_error: 0.2236, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.7715, predictive_accuracy: 0.7755, prior_entropy: 0.9439, recall: 0.7755, relative_absolute_error: 0.4846, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.4654, root_relative_squared_error: 0.9692, scimark_benchmark: 939.521,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8428, build_cpu_time: 2.5155, build_memory: 237320868.2993, f_measure: 0.7772, kappa: 0.5135, kb_relative_information_score: 150.2836, mean_absolute_error: 0.217, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.7763, predictive_accuracy: 0.7789, prior_entropy: 0.9439, recall: 0.7789, relative_absolute_error: 0.4703, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.4499, root_relative_squared_error: 0.937, scimark_benchmark: 923.9118,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8368, build_cpu_time: 0.2984, build_memory: 594850767.0476, f_measure: 0.7791, kappa: 0.5215, kb_relative_information_score: 143.1582, mean_absolute_error: 0.2299, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.7794, predictive_accuracy: 0.7789, prior_entropy: 0.9439, recall: 0.7789, relative_absolute_error: 0.4984, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.4322, root_relative_squared_error: 0.9001, scimark_benchmark: 937.6343,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8501, build_cpu_time: 1.2284, build_memory: 221045571.3742, f_measure: 0.8082, kappa: 0.5818, kb_relative_information_score: 166.7583, mean_absolute_error: 0.1936, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.8077, predictive_accuracy: 0.8095, prior_entropy: 0.9439, recall: 0.8095, relative_absolute_error: 0.4196, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.4193, root_relative_squared_error: 0.8732, scimark_benchmark: 902.712,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8441, build_cpu_time: 2.0996, build_memory: 921791775.3742, f_measure: 0.8146, kappa: 0.595, kb_relative_information_score: 169.8844, mean_absolute_error: 0.1888, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.8142, predictive_accuracy: 0.8163, prior_entropy: 0.9439, recall: 0.8163, relative_absolute_error: 0.4092, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.4255, root_relative_squared_error: 0.8862, scimark_benchmark: 939.521,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8186, build_cpu_time: 4.2947, build_memory: 111863863.4286, f_measure: 0.7914, kappa: 0.5454, kb_relative_information_score: 159.4793, mean_absolute_error: 0.2029, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.7907, predictive_accuracy: 0.7925, prior_entropy: 0.9439, recall: 0.7925, relative_absolute_error: 0.4398, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.4422, root_relative_squared_error: 0.9209, scimark_benchmark: 920.2874,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8665, build_cpu_time: 0.0875, build_memory: 453094316.6531, f_measure: 0.811, kappa: 0.5866, kb_relative_information_score: 161.3413, mean_absolute_error: 0.2049, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.8106, predictive_accuracy: 0.8129, prior_entropy: 0.9439, recall: 0.8129, relative_absolute_error: 0.4442, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.3919, root_relative_squared_error: 0.8163, scimark_benchmark: 920.7965,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8665, build_cpu_time: 0.0783, build_memory: 1400143848.5986, f_measure: 0.811, kappa: 0.5866, kb_relative_information_score: 161.3413, mean_absolute_error: 0.2049, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.8106, predictive_accuracy: 0.8129, prior_entropy: 0.9439, recall: 0.8129, relative_absolute_error: 0.4442, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.3919, root_relative_squared_error: 0.8163, scimark_benchmark: 943.4039,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8677, build_cpu_time: 0.0787, build_memory: 492422646.5578, f_measure: 0.811, kappa: 0.5866, kb_relative_information_score: 161.2414, mean_absolute_error: 0.2055, mean_prior_absolute_error: 0.4614, number_of_instances: 294, precision: 0.8106, predictive_accuracy: 0.8129, prior_entropy: 0.9439, recall: 0.8129, relative_absolute_error: 0.4454, root_mean_prior_squared_error: 0.4802, root_mean_squared_error: 0.3929, root_relative_squared_error: 0.8182, scimark_benchmark: 913.3372,

Metric:

Timeline

Plotting contribution timeline

Leaderboard

Rank Name Top Score Entries Highest rank

Note: The leaderboard ignores resubmissions of previous solutions, as well as parameter variations that do not improve performance.

Challenge

In supervised classification, you are given an input dataset in which instances are labeled with a certain class. The goal is to build a model that predicts the class for future unlabeled instances. The model is evaluated using a train-test procedure, e.g. cross-validation.

To make results by different users comparable, you are given the exact train-test folds to be used, and you need to return at least the predictions generated by your model for each of the test instances. OpenML will use these predictions to calculate a range of evaluation measures on the server.

You can also upload your own evaluation measures, provided that the code for doing so is available from the implementation used. For extremely large datasets, it may be infeasible to upload all predictions. In those cases, you need to compute and provide the evaluations yourself.

Optionally, you can upload the model trained on all the input data. There is no restriction on the file format, but please use a well-known format or PMML.

Given inputs

Expected outputs

evaluations A list of user-defined evaluations of the task as key-value pairs. KeyValue (optional)
model A file containing the model built on all the input data. File (optional)
predictions The desired output format Predictions (optional)

How to submit runs

Using your favorite machine learning environment

Download this task directly in your environment and automatically upload your results

OpenML bootcamp

From your own software

Use one of our APIs to download data from OpenML and upload your results

OpenML APIs