Task
Supervised Classification on AP_Prostate_Kidney

Supervised Classification on AP_Prostate_Kidney

Task 3978 Supervised Classification AP_Prostate_Kidney 76 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9842, f_measure: 0.9878, kappa: 0.9629, kb_relative_information_score: 302.5656, mean_absolute_error: 0.0219, mean_prior_absolute_error: 0.3325, number_of_instances: 329, precision: 0.9878, predictive_accuracy: 0.9878, prior_entropy: 0.7443, recall: 0.9878, relative_absolute_error: 0.0658, root_mean_prior_squared_error: 0.4071, root_mean_squared_error: 0.1135, root_relative_squared_error: 0.2788,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9817, f_measure: 0.9878, kappa: 0.9633, kb_relative_information_score: 313.6402, mean_absolute_error: 0.0122, mean_prior_absolute_error: 0.3325, number_of_instances: 329, precision: 0.9878, predictive_accuracy: 0.9878, prior_entropy: 0.7443, recall: 0.9878, relative_absolute_error: 0.0366, root_mean_prior_squared_error: 0.4071, root_mean_squared_error: 0.1103, root_relative_squared_error: 0.2708,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9532, f_measure: 0.9847, kappa: 0.9534, kb_relative_information_score: 306.365, mean_absolute_error: 0.0211, mean_prior_absolute_error: 0.3325, number_of_instances: 329, precision: 0.9848, predictive_accuracy: 0.9848, prior_entropy: 0.7443, recall: 0.9848, relative_absolute_error: 0.0636, root_mean_prior_squared_error: 0.4071, root_mean_squared_error: 0.123, root_relative_squared_error: 0.302,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9991, f_measure: 0.9846, kappa: 0.9529, kb_relative_information_score: 305.6901, mean_absolute_error: 0.0246, mean_prior_absolute_error: 0.3325, number_of_instances: 329, precision: 0.9851, predictive_accuracy: 0.9848, prior_entropy: 0.7443, recall: 0.9848, relative_absolute_error: 0.074, root_mean_prior_squared_error: 0.4071, root_mean_squared_error: 0.1043, root_relative_squared_error: 0.2562,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9908, f_measure: 0.9939, kappa: 0.9817, kb_relative_information_score: 320.5841, mean_absolute_error: 0.0061, mean_prior_absolute_error: 0.3325, number_of_instances: 329, precision: 0.9939, predictive_accuracy: 0.9939, prior_entropy: 0.7443, recall: 0.9939, relative_absolute_error: 0.0183, root_mean_prior_squared_error: 0.4071, root_mean_squared_error: 0.078, root_relative_squared_error: 0.1915,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.995, f_measure: 0.9909, kappa: 0.9726, kb_relative_information_score: 242.4644, mean_absolute_error: 0.0892, mean_prior_absolute_error: 0.3325, number_of_instances: 329, precision: 0.991, predictive_accuracy: 0.9909, prior_entropy: 0.7443, recall: 0.9909, relative_absolute_error: 0.2681, root_mean_prior_squared_error: 0.4071, root_mean_squared_error: 0.1547, root_relative_squared_error: 0.3799,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9919, f_measure: 0.9939, kappa: 0.9815, kb_relative_information_score: 320.5841, mean_absolute_error: 0.0061, mean_prior_absolute_error: 0.3325, number_of_instances: 329, precision: 0.994, predictive_accuracy: 0.9939, prior_entropy: 0.7443, recall: 0.9939, relative_absolute_error: 0.0183, root_mean_prior_squared_error: 0.4071, root_mean_squared_error: 0.078, root_relative_squared_error: 0.1915,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9822, f_measure: 0.9819, kappa: 0.9456, kb_relative_information_score: 306.2913, mean_absolute_error: 0.0189, mean_prior_absolute_error: 0.3325, number_of_instances: 329, precision: 0.9821, predictive_accuracy: 0.9818, prior_entropy: 0.7443, recall: 0.9818, relative_absolute_error: 0.0568, root_mean_prior_squared_error: 0.4071, root_mean_squared_error: 0.135, root_relative_squared_error: 0.3315, scimark_benchmark: 1150.4212, usercpu_time_millis: 1480, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 1460,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4935, f_measure: 0.6977, kb_relative_information_score: 2.2928, mean_absolute_error: 0.3296, mean_prior_absolute_error: 0.3325, number_of_instances: 329, precision: 0.6245, predictive_accuracy: 0.7903, prior_entropy: 0.7443, recall: 0.7903, relative_absolute_error: 0.9914, root_mean_prior_squared_error: 0.4071, root_mean_squared_error: 0.4072, root_relative_squared_error: 1.0001,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9912, f_measure: 0.9908, kappa: 0.972, kb_relative_information_score: 295.8746, mean_absolute_error: 0.0374, mean_prior_absolute_error: 0.3325, number_of_instances: 329, precision: 0.991, predictive_accuracy: 0.9909, prior_entropy: 0.7443, recall: 0.9909, relative_absolute_error: 0.1124, root_mean_prior_squared_error: 0.4071, root_mean_squared_error: 0.1093, root_relative_squared_error: 0.2685,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9706, f_measure: 0.9788, kappa: 0.9362, kb_relative_information_score: 303.2244, mean_absolute_error: 0.0213, mean_prior_absolute_error: 0.3325, number_of_instances: 329, precision: 0.9789, predictive_accuracy: 0.9787, prior_entropy: 0.7443, recall: 0.9787, relative_absolute_error: 0.064, root_mean_prior_squared_error: 0.4071, root_mean_squared_error: 0.1459, root_relative_squared_error: 0.3583,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5065, f_measure: 0.2129, kappa: 0.0059, kb_relative_information_score: -505.741, mean_absolute_error: 0.7295, mean_prior_absolute_error: 0.3325, number_of_instances: 329, precision: 0.6866, predictive_accuracy: 0.2705, prior_entropy: 0.7443, recall: 0.2705, relative_absolute_error: 2.1939, root_mean_prior_squared_error: 0.4071, root_mean_squared_error: 0.8541, root_relative_squared_error: 2.0979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5065, f_measure: 0.6977, kb_relative_information_score: -7.2223, mean_absolute_error: 0.333, mean_prior_absolute_error: 0.3325, number_of_instances: 329, precision: 0.6245, predictive_accuracy: 0.7903, prior_entropy: 0.7443, recall: 0.7903, relative_absolute_error: 1.0014, root_mean_prior_squared_error: 0.4071, root_mean_squared_error: 0.4071, root_relative_squared_error: 1,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9908, f_measure: 0.9939, kappa: 0.9817, kb_relative_information_score: 320.5841, mean_absolute_error: 0.0061, mean_prior_absolute_error: 0.3325, number_of_instances: 329, precision: 0.9939, predictive_accuracy: 0.9939, prior_entropy: 0.7443, recall: 0.9939, relative_absolute_error: 0.0183, root_mean_prior_squared_error: 0.4071, root_mean_squared_error: 0.078, root_relative_squared_error: 0.1915, scimark_benchmark: 1922.3298, usercpu_time_millis: 9390.625, usercpu_time_millis_testing: 4406.25, usercpu_time_millis_training: 4984.375,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9855, f_measure: 0.9939, kappa: 0.9815, kb_relative_information_score: 320.5841, mean_absolute_error: 0.0061, mean_prior_absolute_error: 0.3325, number_of_instances: 329, precision: 0.994, predictive_accuracy: 0.9939, prior_entropy: 0.7443, recall: 0.9939, relative_absolute_error: 0.0183, root_mean_prior_squared_error: 0.4071, root_mean_squared_error: 0.078, root_relative_squared_error: 0.1915, scimark_benchmark: 1922.3298, usercpu_time_millis: 9906.25, usercpu_time_millis_testing: 4671.875, usercpu_time_millis_training: 5234.375,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.6977, kb_relative_information_score: 87.9632, mean_absolute_error: 0.2097, mean_prior_absolute_error: 0.3325, number_of_instances: 329, precision: 0.6245, predictive_accuracy: 0.7903, prior_entropy: 0.7443, recall: 0.7903, relative_absolute_error: 0.6308, root_mean_prior_squared_error: 0.4071, root_mean_squared_error: 0.458, root_relative_squared_error: 1.1249, scimark_benchmark: 1922.3298, usercpu_time_millis: 28500, usercpu_time_millis_testing: 12875, usercpu_time_millis_training: 15625,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.6977, kb_relative_information_score: 87.9632, mean_absolute_error: 0.2097, mean_prior_absolute_error: 0.3325, number_of_instances: 329, precision: 0.6245, predictive_accuracy: 0.7903, prior_entropy: 0.7443, recall: 0.7903, relative_absolute_error: 0.6308, root_mean_prior_squared_error: 0.4071, root_mean_squared_error: 0.458, root_relative_squared_error: 1.1249, scimark_benchmark: 1280.301, usercpu_time_millis: 20421.875, usercpu_time_millis_testing: 9828.125, usercpu_time_millis_training: 10593.75,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.6977, kb_relative_information_score: 87.9632, mean_absolute_error: 0.2097, mean_prior_absolute_error: 0.3325, number_of_instances: 329, precision: 0.6245, predictive_accuracy: 0.7903, prior_entropy: 0.7443, recall: 0.7903, relative_absolute_error: 0.6308, root_mean_prior_squared_error: 0.4071, root_mean_squared_error: 0.458, root_relative_squared_error: 1.1249, scimark_benchmark: 1382.2421, usercpu_time_millis: 21370, usercpu_time_millis_testing: 8630, usercpu_time_millis_training: 12740,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.6977, kb_relative_information_score: 87.9632, mean_absolute_error: 0.2097, mean_prior_absolute_error: 0.3325, number_of_instances: 329, precision: 0.6245, predictive_accuracy: 0.7903, prior_entropy: 0.7443, recall: 0.7903, relative_absolute_error: 0.6308, root_mean_prior_squared_error: 0.4071, root_mean_squared_error: 0.458, root_relative_squared_error: 1.1249, scimark_benchmark: 1562.8608, usercpu_time_millis: 23400, usercpu_time_millis_testing: 11940, usercpu_time_millis_training: 11460,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9908, f_measure: 0.9939, kappa: 0.9817, kb_relative_information_score: 320.5841, mean_absolute_error: 0.0061, mean_prior_absolute_error: 0.3325, number_of_instances: 329, precision: 0.9939, predictive_accuracy: 0.9939, prior_entropy: 0.7443, recall: 0.9939, relative_absolute_error: 0.0183, root_mean_prior_squared_error: 0.4071, root_mean_squared_error: 0.078, root_relative_squared_error: 0.1915, scimark_benchmark: 1651.7681, usercpu_time_millis: 10370, usercpu_time_millis_testing: 4900, usercpu_time_millis_training: 5470,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9855, f_measure: 0.9939, kappa: 0.9815, kb_relative_information_score: 320.5841, mean_absolute_error: 0.0061, mean_prior_absolute_error: 0.3325, number_of_instances: 329, precision: 0.994, predictive_accuracy: 0.9939, prior_entropy: 0.7443, recall: 0.9939, relative_absolute_error: 0.0183, root_mean_prior_squared_error: 0.4071, root_mean_squared_error: 0.078, root_relative_squared_error: 0.1915, scimark_benchmark: 1646.3919, usercpu_time_millis: 9470, usercpu_time_millis_testing: 4620, usercpu_time_millis_training: 4850,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5065, f_measure: 0.2129, kappa: 0.0059, kb_relative_information_score: -505.741, mean_absolute_error: 0.7295, mean_prior_absolute_error: 0.3325, number_of_instances: 329, precision: 0.6866, predictive_accuracy: 0.2705, prior_entropy: 0.7443, recall: 0.2705, relative_absolute_error: 2.1939, root_mean_prior_squared_error: 0.4071, root_mean_squared_error: 0.8541, root_relative_squared_error: 2.0979, scimark_benchmark: 1659.2869, usercpu_time_millis: 274310, usercpu_time_millis_testing: 71680, usercpu_time_millis_training: 202630,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5065, f_measure: 0.6977, kb_relative_information_score: -10.9202, mean_absolute_error: 0.3343, mean_prior_absolute_error: 0.3325, number_of_instances: 329, precision: 0.6245, predictive_accuracy: 0.7903, prior_entropy: 0.7443, recall: 0.7903, relative_absolute_error: 1.0054, root_mean_prior_squared_error: 0.4071, root_mean_squared_error: 0.4072, root_relative_squared_error: 1.0003, scimark_benchmark: 1162.7293, usercpu_time_millis: 261900, usercpu_time_millis_testing: 57740, usercpu_time_millis_training: 204160,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9851, f_measure: 0.9849, kappa: 0.9549, kb_relative_information_score: 310.1683, mean_absolute_error: 0.0152, mean_prior_absolute_error: 0.3325, number_of_instances: 329, precision: 0.9853, predictive_accuracy: 0.9848, prior_entropy: 0.7443, recall: 0.9848, relative_absolute_error: 0.0457, root_mean_prior_squared_error: 0.4071, root_mean_squared_error: 0.1233, root_relative_squared_error: 0.3028, scimark_benchmark: 1367.678, usercpu_time_millis: 4300, usercpu_time_millis_testing: 2290, usercpu_time_millis_training: 2010,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9908, f_measure: 0.9939, kappa: 0.9817, kb_relative_information_score: 320.5841, mean_absolute_error: 0.0061, mean_prior_absolute_error: 0.3325, number_of_instances: 329, precision: 0.9939, predictive_accuracy: 0.9939, prior_entropy: 0.7443, recall: 0.9939, relative_absolute_error: 0.0183, root_mean_prior_squared_error: 0.4071, root_mean_squared_error: 0.078, root_relative_squared_error: 0.1915, scimark_benchmark: 1198.8645, usercpu_time_millis: 2080, usercpu_time_millis_testing: 150, usercpu_time_millis_training: 1930,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9889, f_measure: 0.9909, kappa: 0.9726, kb_relative_information_score: 317.1122, mean_absolute_error: 0.0091, mean_prior_absolute_error: 0.3325, number_of_instances: 329, precision: 0.991, predictive_accuracy: 0.9909, prior_entropy: 0.7443, recall: 0.9909, relative_absolute_error: 0.0274, root_mean_prior_squared_error: 0.4071, root_mean_squared_error: 0.0955, root_relative_squared_error: 0.2346, scimark_benchmark: 1243.7717, usercpu_time_millis: 5020, usercpu_time_millis_testing: 80, usercpu_time_millis_training: 4940,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5065, f_measure: 0.6977, kb_relative_information_score: -10.9202, mean_absolute_error: 0.3343, mean_prior_absolute_error: 0.3325, number_of_instances: 329, precision: 0.6245, predictive_accuracy: 0.7903, prior_entropy: 0.7443, recall: 0.7903, relative_absolute_error: 1.0054, root_mean_prior_squared_error: 0.4071, root_mean_squared_error: 0.4072, root_relative_squared_error: 1.0003, scimark_benchmark: 1321.2193, usercpu_time_millis: 356160, usercpu_time_millis_testing: 68180, usercpu_time_millis_training: 287980,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9899, f_measure: 0.9878, kappa: 0.9633, kb_relative_information_score: 312.3433, mean_absolute_error: 0.0135, mean_prior_absolute_error: 0.3325, number_of_instances: 329, precision: 0.9878, predictive_accuracy: 0.9878, prior_entropy: 0.7443, recall: 0.9878, relative_absolute_error: 0.0407, root_mean_prior_squared_error: 0.4071, root_mean_squared_error: 0.1115, root_relative_squared_error: 0.2739, scimark_benchmark: 1348.5647, usercpu_time_millis: 653550, usercpu_time_millis_testing: 70, usercpu_time_millis_training: 653480,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9817, f_measure: 0.9848, kappa: 0.9544, kb_relative_information_score: 308.0904, mean_absolute_error: 0.0185, mean_prior_absolute_error: 0.3325, number_of_instances: 329, precision: 0.9849, predictive_accuracy: 0.9848, prior_entropy: 0.7443, recall: 0.9848, relative_absolute_error: 0.0555, root_mean_prior_squared_error: 0.4071, root_mean_squared_error: 0.1229, root_relative_squared_error: 0.3019, scimark_benchmark: 1347.22, usercpu_time_millis: 7760, usercpu_time_millis_testing: 6630, usercpu_time_millis_training: 1130,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9836, f_measure: 0.9909, kappa: 0.9723, kb_relative_information_score: 317.1122, mean_absolute_error: 0.0091, mean_prior_absolute_error: 0.3325, number_of_instances: 329, precision: 0.9909, predictive_accuracy: 0.9909, prior_entropy: 0.7443, recall: 0.9909, relative_absolute_error: 0.0274, root_mean_prior_squared_error: 0.4071, root_mean_squared_error: 0.0955, root_relative_squared_error: 0.2346, scimark_benchmark: 1511.4999, usercpu_time_millis: 114780, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 114760,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.973, f_measure: 0.9758, kappa: 0.9274, kb_relative_information_score: 300.6961, mean_absolute_error: 0.0233, mean_prior_absolute_error: 0.3325, number_of_instances: 329, precision: 0.976, predictive_accuracy: 0.9757, prior_entropy: 0.7443, recall: 0.9757, relative_absolute_error: 0.07, root_mean_prior_squared_error: 0.4071, root_mean_squared_error: 0.1446, root_relative_squared_error: 0.3552, scimark_benchmark: 1307.0589, usercpu_time_millis: 5450, usercpu_time_millis_testing: 70, usercpu_time_millis_training: 5380,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9601, f_measure: 0.9818, kappa: 0.945, kb_relative_information_score: 302.6951, mean_absolute_error: 0.0245, mean_prior_absolute_error: 0.3325, number_of_instances: 329, precision: 0.9818, predictive_accuracy: 0.9818, prior_entropy: 0.7443, recall: 0.9818, relative_absolute_error: 0.0736, root_mean_prior_squared_error: 0.4071, root_mean_squared_error: 0.1347, root_relative_squared_error: 0.3307, scimark_benchmark: 900.8543, usercpu_time_millis: 3000, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 2970,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9983, f_measure: 0.9908, kappa: 0.972, kb_relative_information_score: 292.2997, mean_absolute_error: 0.0436, mean_prior_absolute_error: 0.3325, number_of_instances: 329, precision: 0.991, predictive_accuracy: 0.9909, prior_entropy: 0.7443, recall: 0.9909, relative_absolute_error: 0.1312, root_mean_prior_squared_error: 0.4071, root_mean_squared_error: 0.1046, root_relative_squared_error: 0.2568, scimark_benchmark: 1032.9125, usercpu_time_millis: 2240, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 2200,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9793, f_measure: 0.976, kappa: 0.9289, kb_relative_information_score: 299.7524, mean_absolute_error: 0.0243, mean_prior_absolute_error: 0.3325, number_of_instances: 329, precision: 0.9773, predictive_accuracy: 0.9757, prior_entropy: 0.7443, recall: 0.9757, relative_absolute_error: 0.0731, root_mean_prior_squared_error: 0.4071, root_mean_squared_error: 0.1559, root_relative_squared_error: 0.383, scimark_benchmark: 1156.1689, usercpu_time_millis: 9940, usercpu_time_millis_testing: 2420, usercpu_time_millis_training: 7520,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9822, f_measure: 0.9819, kappa: 0.9456, kb_relative_information_score: 306.2913, mean_absolute_error: 0.0189, mean_prior_absolute_error: 0.3325, number_of_instances: 329, precision: 0.9821, predictive_accuracy: 0.9818, prior_entropy: 0.7443, recall: 0.9818, relative_absolute_error: 0.0568, root_mean_prior_squared_error: 0.4071, root_mean_squared_error: 0.135, root_relative_squared_error: 0.3315, scimark_benchmark: 1269.0638, usercpu_time_millis: 2740, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 2730,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9831, f_measure: 0.9819, kappa: 0.9461, kb_relative_information_score: 306.6963, mean_absolute_error: 0.0182, mean_prior_absolute_error: 0.3325, number_of_instances: 329, precision: 0.9825, predictive_accuracy: 0.9818, prior_entropy: 0.7443, recall: 0.9818, relative_absolute_error: 0.0548, root_mean_prior_squared_error: 0.4071, root_mean_squared_error: 0.135, root_relative_squared_error: 0.3317, scimark_benchmark: 1362.753, usercpu_time_millis: 3890, usercpu_time_millis_testing: 2240, usercpu_time_millis_training: 1650,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9889, f_measure: 0.9909, kappa: 0.9726, kb_relative_information_score: 317.1122, mean_absolute_error: 0.0091, mean_prior_absolute_error: 0.3325, number_of_instances: 329, precision: 0.991, predictive_accuracy: 0.9909, prior_entropy: 0.7443, recall: 0.9909, relative_absolute_error: 0.0274, root_mean_prior_squared_error: 0.4071, root_mean_squared_error: 0.0955, root_relative_squared_error: 0.2346, scimark_benchmark: 1400.7629, usercpu_time_millis: 4240, usercpu_time_millis_testing: 60, usercpu_time_millis_training: 4180,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9628, f_measure: 0.9788, kappa: 0.9362, kb_relative_information_score: 300.6943, mean_absolute_error: 0.0252, mean_prior_absolute_error: 0.3325, number_of_instances: 329, precision: 0.9789, predictive_accuracy: 0.9787, prior_entropy: 0.7443, recall: 0.9787, relative_absolute_error: 0.0759, root_mean_prior_squared_error: 0.4071, root_mean_squared_error: 0.1456, root_relative_squared_error: 0.3576, scimark_benchmark: 954.1118, usercpu_time_millis: 4720, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 4710,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9783, f_measure: 0.9908, kappa: 0.972, kb_relative_information_score: 317.1122, mean_absolute_error: 0.0091, mean_prior_absolute_error: 0.3325, number_of_instances: 329, precision: 0.991, predictive_accuracy: 0.9909, prior_entropy: 0.7443, recall: 0.9909, relative_absolute_error: 0.0274, root_mean_prior_squared_error: 0.4071, root_mean_squared_error: 0.0955, root_relative_squared_error: 0.2346, scimark_benchmark: 888.6031, usercpu_time_millis: 7370, usercpu_time_millis_testing: 2590, usercpu_time_millis_training: 4780,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9985, f_measure: 0.9908, kappa: 0.972, kb_relative_information_score: 287.8024, mean_absolute_error: 0.0504, mean_prior_absolute_error: 0.3325, number_of_instances: 329, precision: 0.991, predictive_accuracy: 0.9909, prior_entropy: 0.7443, recall: 0.9909, relative_absolute_error: 0.1517, root_mean_prior_squared_error: 0.4071, root_mean_squared_error: 0.1078, root_relative_squared_error: 0.2648, scimark_benchmark: 1024.5299, usercpu_time_millis: 1180, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 1170,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9793, f_measure: 0.9878, kappa: 0.9633, kb_relative_information_score: 305.7783, mean_absolute_error: 0.0244, mean_prior_absolute_error: 0.3325, number_of_instances: 329, precision: 0.9878, predictive_accuracy: 0.9878, prior_entropy: 0.7443, recall: 0.9878, relative_absolute_error: 0.0733, root_mean_prior_squared_error: 0.4071, root_mean_squared_error: 0.11, root_relative_squared_error: 0.2701, scimark_benchmark: 983.0502, usercpu_time_millis: 830, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 820,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9817, f_measure: 0.9848, kappa: 0.9544, kb_relative_information_score: 308.0904, mean_absolute_error: 0.0185, mean_prior_absolute_error: 0.3325, number_of_instances: 329, precision: 0.9849, predictive_accuracy: 0.9848, prior_entropy: 0.7443, recall: 0.9848, relative_absolute_error: 0.0555, root_mean_prior_squared_error: 0.4071, root_mean_squared_error: 0.1229, root_relative_squared_error: 0.3019, scimark_benchmark: 1439.7699, usercpu_time_millis: 5210, usercpu_time_millis_testing: 5210,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9802, f_measure: 0.9789, kappa: 0.9368, kb_relative_information_score: 302.8194, mean_absolute_error: 0.0219, mean_prior_absolute_error: 0.3325, number_of_instances: 329, precision: 0.9793, predictive_accuracy: 0.9787, prior_entropy: 0.7443, recall: 0.9787, relative_absolute_error: 0.0659, root_mean_prior_squared_error: 0.4071, root_mean_squared_error: 0.1458, root_relative_squared_error: 0.3581, scimark_benchmark: 1346.1774, usercpu_time_millis: 1040, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 1030,

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