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OpenML
OpenML
Supervised Classification on disclosure_z

Supervised Classification on disclosure_z

Task 3794 Supervised Classification disclosure_z 585 runs submitted
0 likes downloaded by 0 people , 0 total downloads 0 issues
Visibility: Public
  • mythbusting_1 study_1 study_107 study_15 study_20 study_41 study_7 under100k under1m
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585 Runs

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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4832, f_measure: 0.4816, kappa: -0.0398, kb_relative_information_score: -13.1199, mean_absolute_error: 0.5065, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.4815, predictive_accuracy: 0.4819, prior_entropy: 0.9981, recall: 0.4819, relative_absolute_error: 1.0157, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.585, root_relative_squared_error: 1.1715, scimark_benchmark: 1363.454, usercpu_time_millis: 20, usercpu_time_millis_testing: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4993, f_measure: 0.3745, kappa: -0.0014, kb_relative_information_score: 29.6027, mean_absolute_error: 0.4758, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.4918, predictive_accuracy: 0.5242, prior_entropy: 0.9981, recall: 0.5242, relative_absolute_error: 0.9542, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.6898, root_relative_squared_error: 1.3814, scimark_benchmark: 1304.9611, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.3623, kb_relative_information_score: 31.6103, mean_absolute_error: 0.4743, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.2763, predictive_accuracy: 0.5257, prior_entropy: 0.9981, recall: 0.5257, relative_absolute_error: 0.9511, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.6887, root_relative_squared_error: 1.3792, scimark_benchmark: 1333.5799, usercpu_time_millis: 330, usercpu_time_millis_testing: 50, usercpu_time_millis_training: 280,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5409, f_measure: 0.5355, kappa: 0.0831, kb_relative_information_score: 63.7317, mean_absolute_error: 0.4502, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.5471, predictive_accuracy: 0.5498, prior_entropy: 0.9981, recall: 0.5498, relative_absolute_error: 0.9027, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.6709, root_relative_squared_error: 1.3436, scimark_benchmark: 1287.514, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5712, f_measure: 0.5554, kappa: 0.1109, kb_relative_information_score: 14.3473, mean_absolute_error: 0.4904, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.5582, predictive_accuracy: 0.5604, prior_entropy: 0.9981, recall: 0.5604, relative_absolute_error: 0.9833, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.4965, root_relative_squared_error: 0.9942, scimark_benchmark: 930.5999, usercpu_time_millis: 60, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5013, f_measure: 0.4692, kappa: 0.0027, kb_relative_information_score: 19.5648, mean_absolute_error: 0.4834, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.5033, predictive_accuracy: 0.5166, prior_entropy: 0.9981, recall: 0.5166, relative_absolute_error: 0.9693, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.6953, root_relative_squared_error: 1.3924, scimark_benchmark: 942.9708, usercpu_time_millis: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5571, f_measure: 0.5366, kappa: 0.0722, kb_relative_information_score: 13.2891, mean_absolute_error: 0.4907, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.5381, predictive_accuracy: 0.5408, prior_entropy: 0.9981, recall: 0.5408, relative_absolute_error: 0.984, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.4985, root_relative_squared_error: 0.9984, scimark_benchmark: 918.0213, usercpu_time_millis: 1550, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 1510,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4844, f_measure: 0.4801, kappa: -0.0316, kb_relative_information_score: -12.5566, mean_absolute_error: 0.5076, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.4844, predictive_accuracy: 0.4924, prior_entropy: 0.9981, recall: 0.4924, relative_absolute_error: 1.0178, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.7124, root_relative_squared_error: 1.4267, scimark_benchmark: 918.6491, usercpu_time_millis: 140, usercpu_time_millis_testing: 50, usercpu_time_millis_training: 90,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4939, f_measure: 0.3623, kb_relative_information_score: -0.015, mean_absolute_error: 0.4987, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.2763, predictive_accuracy: 0.5257, prior_entropy: 0.9981, recall: 0.5257, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.4993, root_relative_squared_error: 1, scimark_benchmark: 1073.494,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4939, f_measure: 0.3623, kb_relative_information_score: -0.015, mean_absolute_error: 0.4987, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.2763, predictive_accuracy: 0.5257, prior_entropy: 0.9981, recall: 0.5257, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.4993, root_relative_squared_error: 1, scimark_benchmark: 1331.6907,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4939, f_measure: 0.3623, kb_relative_information_score: -0.0193, mean_absolute_error: 0.4987, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.2763, predictive_accuracy: 0.5257, prior_entropy: 0.9981, recall: 0.5257, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.4993, root_relative_squared_error: 1, scimark_benchmark: 915.963, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5193, f_measure: 0.5106, kappa: 0.0181, kb_relative_information_score: 8.2602, mean_absolute_error: 0.4931, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.5104, predictive_accuracy: 0.5121, prior_entropy: 0.9981, recall: 0.5121, relative_absolute_error: 0.9887, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.5262, root_relative_squared_error: 1.0539, scimark_benchmark: 1361.1055, usercpu_time_millis: 260, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 220,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.504, f_measure: 0.5056, kappa: 0.0081, kb_relative_information_score: 5.5117, mean_absolute_error: 0.494, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.5054, predictive_accuracy: 0.506, prior_entropy: 0.9981, recall: 0.506, relative_absolute_error: 0.9905, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.7028, root_relative_squared_error: 1.4075, scimark_benchmark: 1361.1055,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5278, f_measure: 0.5374, kappa: 0.0719, kb_relative_information_score: 14.2186, mean_absolute_error: 0.4897, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.5372, predictive_accuracy: 0.5378, prior_entropy: 0.9981, recall: 0.5378, relative_absolute_error: 0.982, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.5345, root_relative_squared_error: 1.0705, scimark_benchmark: 1318.5526, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5129, f_measure: 0.5177, kappa: 0.0325, kb_relative_information_score: 3.1679, mean_absolute_error: 0.4971, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.5177, predictive_accuracy: 0.5196, prior_entropy: 0.9981, recall: 0.5196, relative_absolute_error: 0.9969, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.5285, root_relative_squared_error: 1.0585, scimark_benchmark: 1318.1432, usercpu_time_millis: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.483, f_measure: 0.4837, kappa: -0.034, kb_relative_information_score: -24.6021, mean_absolute_error: 0.5166, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.4843, predictive_accuracy: 0.4834, prior_entropy: 0.9981, recall: 0.4834, relative_absolute_error: 1.036, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.7188, root_relative_squared_error: 1.4394, scimark_benchmark: 1341.5768, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4992, f_measure: 0.372, kappa: -0.0017, kb_relative_information_score: 29.6027, mean_absolute_error: 0.4758, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.4869, predictive_accuracy: 0.5242, prior_entropy: 0.9981, recall: 0.5242, relative_absolute_error: 0.9542, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.6898, root_relative_squared_error: 1.3814, scimark_benchmark: 1287.514,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4939, f_measure: 0.3623, kb_relative_information_score: -0.0107, mean_absolute_error: 0.4987, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.2763, predictive_accuracy: 0.5257, prior_entropy: 0.9981, recall: 0.5257, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.4993, root_relative_squared_error: 1, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5435, f_measure: 0.5441, kappa: 0.0869, kb_relative_information_score: 55.7014, mean_absolute_error: 0.4562, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.5447, predictive_accuracy: 0.5438, prior_entropy: 0.9981, recall: 0.5438, relative_absolute_error: 0.9148, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.6754, root_relative_squared_error: 1.3526, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5047, f_measure: 0.5058, kappa: 0.0095, kb_relative_information_score: 9.5269, mean_absolute_error: 0.4909, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.5061, predictive_accuracy: 0.5091, prior_entropy: 0.9981, recall: 0.5091, relative_absolute_error: 0.9845, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.7007, root_relative_squared_error: 1.4032, scimark_benchmark: 1353.5686, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4939, f_measure: 0.3623, kb_relative_information_score: -0.0193, mean_absolute_error: 0.4987, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.2763, predictive_accuracy: 0.5257, prior_entropy: 0.9981, recall: 0.5257, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.4993, root_relative_squared_error: 1, scimark_benchmark: 1503.3362,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4939, f_measure: 0.3623, kb_relative_information_score: -0.0107, mean_absolute_error: 0.4987, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.2763, predictive_accuracy: 0.5257, prior_entropy: 0.9981, recall: 0.5257, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.4993, root_relative_squared_error: 1, scimark_benchmark: 1605.6303,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5647, f_measure: 0.5553, kappa: 0.1078, kb_relative_information_score: 24.6846, mean_absolute_error: 0.4837, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.5551, predictive_accuracy: 0.5559, prior_entropy: 0.9981, recall: 0.5559, relative_absolute_error: 0.9699, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.5047, root_relative_squared_error: 1.0108, scimark_benchmark: 927.0753, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5566, f_measure: 0.5571, kappa: 0.1115, kb_relative_information_score: 16.2852, mean_absolute_error: 0.4894, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.5569, predictive_accuracy: 0.5574, prior_entropy: 0.9981, recall: 0.5574, relative_absolute_error: 0.9813, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.4974, root_relative_squared_error: 0.9962, scimark_benchmark: 945.6434, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5566, f_measure: 0.5571, kappa: 0.1115, kb_relative_information_score: 16.2852, mean_absolute_error: 0.4894, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.5569, predictive_accuracy: 0.5574, prior_entropy: 0.9981, recall: 0.5574, relative_absolute_error: 0.9813, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.4974, root_relative_squared_error: 0.9962, scimark_benchmark: 876.8277, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5566, f_measure: 0.5571, kappa: 0.1115, kb_relative_information_score: 16.2852, mean_absolute_error: 0.4894, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.5569, predictive_accuracy: 0.5574, prior_entropy: 0.9981, recall: 0.5574, relative_absolute_error: 0.9813, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.4974, root_relative_squared_error: 0.9962, scimark_benchmark: 923.7642, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5566, f_measure: 0.5571, kappa: 0.1115, kb_relative_information_score: 16.2852, mean_absolute_error: 0.4894, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.5569, predictive_accuracy: 0.5574, prior_entropy: 0.9981, recall: 0.5574, relative_absolute_error: 0.9813, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.4974, root_relative_squared_error: 0.9962, scimark_benchmark: 894.7455, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5208, f_measure: 0.5136, kappa: 0.0242, kb_relative_information_score: 13.9332, mean_absolute_error: 0.4889, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.5134, predictive_accuracy: 0.5151, prior_entropy: 0.9981, recall: 0.5151, relative_absolute_error: 0.9804, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.5504, root_relative_squared_error: 1.1022, scimark_benchmark: 940.2922, usercpu_time_millis: 220, usercpu_time_millis_training: 220,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5239, f_measure: 0.5294, kappa: 0.0574, kb_relative_information_score: 16.4226, mean_absolute_error: 0.4882, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.5305, predictive_accuracy: 0.5332, prior_entropy: 0.9981, recall: 0.5332, relative_absolute_error: 0.979, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.5474, root_relative_squared_error: 1.0962, scimark_benchmark: 938.2848, usercpu_time_millis: 90, usercpu_time_millis_training: 90,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5127, f_measure: 0.515, kappa: 0.0278, kb_relative_information_score: 8.7557, mean_absolute_error: 0.4927, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.5154, predictive_accuracy: 0.5181, prior_entropy: 0.9981, recall: 0.5181, relative_absolute_error: 0.988, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.5435, root_relative_squared_error: 1.0885, scimark_benchmark: 911.3823, usercpu_time_millis: 60, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5067, f_measure: 0.5143, kappa: 0.0286, kb_relative_information_score: 5.5573, mean_absolute_error: 0.4951, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.516, predictive_accuracy: 0.5196, prior_entropy: 0.9981, recall: 0.5196, relative_absolute_error: 0.9929, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.5412, root_relative_squared_error: 1.0838, scimark_benchmark: 922.9039, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5004, f_measure: 0.5221, kappa: 0.044, kb_relative_information_score: 2.641, mean_absolute_error: 0.4976, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.5239, predictive_accuracy: 0.5272, prior_entropy: 0.9981, recall: 0.5272, relative_absolute_error: 0.9978, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.5376, root_relative_squared_error: 1.0765, scimark_benchmark: 938.4285, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5223, f_measure: 0.5396, kappa: 0.0763, kb_relative_information_score: 11.3505, mean_absolute_error: 0.4908, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.5395, predictive_accuracy: 0.5408, prior_entropy: 0.9981, recall: 0.5408, relative_absolute_error: 0.9842, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.5276, root_relative_squared_error: 1.0565, scimark_benchmark: 936.6206, usercpu_time_millis: 100, usercpu_time_millis_training: 100,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5241, f_measure: 0.5077, kappa: 0.013, kb_relative_information_score: 10.8185, mean_absolute_error: 0.4912, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.5079, predictive_accuracy: 0.5106, prior_entropy: 0.9981, recall: 0.5106, relative_absolute_error: 0.9849, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.5167, root_relative_squared_error: 1.0347, scimark_benchmark: 945.6434, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5566, build_cpu_time: 0.0079, build_memory: 866610861.1722, f_measure: 0.5571, kappa: 0.1115, kb_relative_information_score: 16.2852, mean_absolute_error: 0.4894, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.5569, predictive_accuracy: 0.5574, prior_entropy: 0.9981, recall: 0.5574, relative_absolute_error: 0.9813, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.4974, root_relative_squared_error: 0.9962, scimark_benchmark: 929.5397,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5165, build_cpu_time: 10.6476, build_memory: 31476566.9003, f_measure: 0.5069, kappa: 0.0107, kb_relative_information_score: 7.6762, mean_absolute_error: 0.4934, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.5066, predictive_accuracy: 0.5076, prior_entropy: 0.9981, recall: 0.5076, relative_absolute_error: 0.9895, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.5213, root_relative_squared_error: 1.0439, scimark_benchmark: 899.4388,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.525, build_cpu_time: 186.251, build_memory: 865507841.3414, f_measure: 0.5132, kappa: 0.0234, kb_relative_information_score: 21.8059, mean_absolute_error: 0.4823, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.513, predictive_accuracy: 0.5136, prior_entropy: 0.9981, recall: 0.5136, relative_absolute_error: 0.9672, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.5996, root_relative_squared_error: 1.2007, scimark_benchmark: 940.3132,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5342, build_cpu_time: 1.6758, build_memory: 1120864206.5982, f_measure: 0.5262, kappa: 0.0499, kb_relative_information_score: 11.306, mean_absolute_error: 0.4917, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.5265, predictive_accuracy: 0.5287, prior_entropy: 0.9981, recall: 0.5287, relative_absolute_error: 0.986, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.5105, root_relative_squared_error: 1.0224, scimark_benchmark: 931.9671,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.57, build_cpu_time: 86056.962, build_memory: 956521041.0634, f_measure: 0.5489, kappa: 0.102, kb_relative_information_score: 60.5321, mean_absolute_error: 0.4546, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.555, predictive_accuracy: 0.5574, prior_entropy: 0.9981, recall: 0.5574, relative_absolute_error: 0.9117, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.5594, root_relative_squared_error: 1.1202, scimark_benchmark: 888.7575,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5342, build_cpu_time: 1.7263, build_memory: 410309535.3233, f_measure: 0.5262, kappa: 0.0499, kb_relative_information_score: 11.306, mean_absolute_error: 0.4917, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.5265, predictive_accuracy: 0.5287, prior_entropy: 0.9981, recall: 0.5287, relative_absolute_error: 0.986, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.5105, root_relative_squared_error: 1.0224, scimark_benchmark: 945.0532,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.534, build_cpu_time: 1.4145, build_memory: 1359600727.8429, f_measure: 0.5266, kappa: 0.0505, kb_relative_information_score: 11.6073, mean_absolute_error: 0.4916, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.5267, predictive_accuracy: 0.5287, prior_entropy: 0.9981, recall: 0.5287, relative_absolute_error: 0.9857, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.5102, root_relative_squared_error: 1.0217, scimark_benchmark: 874.7324,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.551, build_cpu_time: 0.2042, build_memory: 187918977.7644, f_measure: 0.5409, kappa: 0.0797, kb_relative_information_score: 23.7963, mean_absolute_error: 0.4838, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.5411, predictive_accuracy: 0.5408, prior_entropy: 0.9981, recall: 0.5408, relative_absolute_error: 0.9702, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.5239, root_relative_squared_error: 1.0492, scimark_benchmark: 939.6298,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5264, build_cpu_time: 0.3975, build_memory: 968231803.5408, f_measure: 0.5352, kappa: 0.0673, kb_relative_information_score: 14.58, mean_absolute_error: 0.4895, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.535, predictive_accuracy: 0.5363, prior_entropy: 0.9981, recall: 0.5363, relative_absolute_error: 0.9815, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.5412, root_relative_squared_error: 1.0838, scimark_benchmark: 908.8705,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.511, build_cpu_time: 0.8655, build_memory: 203189643.1057, f_measure: 0.5097, kappa: 0.0161, kb_relative_information_score: 6.7927, mean_absolute_error: 0.4937, mean_prior_absolute_error: 0.4987, number_of_instances: 662, precision: 0.5094, predictive_accuracy: 0.5106, prior_entropy: 0.9981, recall: 0.5106, relative_absolute_error: 0.9901, root_mean_prior_squared_error: 0.4993, root_mean_squared_error: 0.5644, root_relative_squared_error: 1.1303, scimark_benchmark: 937.279,

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

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From your own software

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

OpenML APIs