Task
Supervised Classification on AP_Uterus_Kidney

Supervised Classification on AP_Uterus_Kidney

Task 3963 Supervised Classification AP_Uterus_Kidney 76 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9874, f_measure: 0.9611, kappa: 0.9112, kb_relative_information_score: 338.3569, mean_absolute_error: 0.0505, mean_prior_absolute_error: 0.4376, number_of_instances: 384, precision: 0.9613, predictive_accuracy: 0.9609, prior_entropy: 0.9085, recall: 0.9609, relative_absolute_error: 0.1154, root_mean_prior_squared_error: 0.4676, root_mean_squared_error: 0.1771, root_relative_squared_error: 0.3787,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9678, f_measure: 0.9584, kappa: 0.9051, kb_relative_information_score: 343.2171, mean_absolute_error: 0.0446, mean_prior_absolute_error: 0.4376, number_of_instances: 384, precision: 0.9586, predictive_accuracy: 0.9583, prior_entropy: 0.9085, recall: 0.9583, relative_absolute_error: 0.102, root_mean_prior_squared_error: 0.4676, root_mean_squared_error: 0.1959, root_relative_squared_error: 0.4189,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9623, f_measure: 0.9588, kappa: 0.9071, kb_relative_information_score: 328.6794, mean_absolute_error: 0.0672, mean_prior_absolute_error: 0.4376, number_of_instances: 384, precision: 0.9613, predictive_accuracy: 0.9583, prior_entropy: 0.9085, recall: 0.9583, relative_absolute_error: 0.1535, root_mean_prior_squared_error: 0.4676, root_mean_squared_error: 0.1951, root_relative_squared_error: 0.4173,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9982, f_measure: 0.9764, kappa: 0.9456, kb_relative_information_score: 348.2965, mean_absolute_error: 0.044, mean_prior_absolute_error: 0.4376, number_of_instances: 384, precision: 0.977, predictive_accuracy: 0.9766, prior_entropy: 0.9085, recall: 0.9766, relative_absolute_error: 0.1006, root_mean_prior_squared_error: 0.4676, root_mean_squared_error: 0.1357, root_relative_squared_error: 0.2902,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9783, f_measure: 0.9792, kappa: 0.9526, kb_relative_information_score: 364.2928, mean_absolute_error: 0.0208, mean_prior_absolute_error: 0.4376, number_of_instances: 384, precision: 0.9793, predictive_accuracy: 0.9792, prior_entropy: 0.9085, recall: 0.9792, relative_absolute_error: 0.0476, root_mean_prior_squared_error: 0.4676, root_mean_squared_error: 0.1443, root_relative_squared_error: 0.3087,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9882, f_measure: 0.9793, kappa: 0.9528, kb_relative_information_score: 354.238, mean_absolute_error: 0.0363, mean_prior_absolute_error: 0.4376, number_of_instances: 384, precision: 0.9796, predictive_accuracy: 0.9792, prior_entropy: 0.9085, recall: 0.9792, relative_absolute_error: 0.083, root_mean_prior_squared_error: 0.4676, root_mean_squared_error: 0.1414, root_relative_squared_error: 0.3025,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9674, f_measure: 0.9713, kappa: 0.9344, kb_relative_information_score: 354.1854, mean_absolute_error: 0.0328, mean_prior_absolute_error: 0.4376, number_of_instances: 384, precision: 0.9713, predictive_accuracy: 0.9714, prior_entropy: 0.9085, recall: 0.9714, relative_absolute_error: 0.0749, root_mean_prior_squared_error: 0.4676, root_mean_squared_error: 0.1703, root_relative_squared_error: 0.3643,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9685, f_measure: 0.9689, kappa: 0.9291, kb_relative_information_score: 354.6452, mean_absolute_error: 0.0313, mean_prior_absolute_error: 0.4376, number_of_instances: 384, precision: 0.9692, predictive_accuracy: 0.9688, prior_entropy: 0.9085, recall: 0.9688, relative_absolute_error: 0.0714, root_mean_prior_squared_error: 0.4676, root_mean_squared_error: 0.1768, root_relative_squared_error: 0.3781,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4903, f_measure: 0.5467, kb_relative_information_score: 0.6103, mean_absolute_error: 0.4369, mean_prior_absolute_error: 0.4376, number_of_instances: 384, precision: 0.4584, predictive_accuracy: 0.6771, prior_entropy: 0.9085, recall: 0.6771, relative_absolute_error: 0.9985, root_mean_prior_squared_error: 0.4676, root_mean_squared_error: 0.4676, root_relative_squared_error: 1,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9938, f_measure: 0.9716, kappa: 0.9354, kb_relative_information_score: 320.3665, mean_absolute_error: 0.0818, mean_prior_absolute_error: 0.4376, number_of_instances: 384, precision: 0.9725, predictive_accuracy: 0.9714, prior_entropy: 0.9085, recall: 0.9714, relative_absolute_error: 0.1869, root_mean_prior_squared_error: 0.4676, root_mean_squared_error: 0.1691, root_relative_squared_error: 0.3616,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9502, f_measure: 0.9582, kappa: 0.9043, kb_relative_information_score: 344.9976, mean_absolute_error: 0.0417, mean_prior_absolute_error: 0.4376, number_of_instances: 384, precision: 0.9582, predictive_accuracy: 0.9583, prior_entropy: 0.9085, recall: 0.9583, relative_absolute_error: 0.0952, root_mean_prior_squared_error: 0.4676, root_mean_squared_error: 0.2041, root_relative_squared_error: 0.4365,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5097, f_measure: 0.5722, kappa: 0.0147, kb_relative_information_score: -17.5986, mean_absolute_error: 0.4354, mean_prior_absolute_error: 0.4376, number_of_instances: 384, precision: 0.5692, predictive_accuracy: 0.5755, prior_entropy: 0.9085, recall: 0.5755, relative_absolute_error: 0.995, root_mean_prior_squared_error: 0.4676, root_mean_squared_error: 0.6428, root_relative_squared_error: 1.3747,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9723, f_measure: 0.974, kappa: 0.9407, kb_relative_information_score: 359.469, mean_absolute_error: 0.026, mean_prior_absolute_error: 0.4376, number_of_instances: 384, precision: 0.9741, predictive_accuracy: 0.974, prior_entropy: 0.9085, recall: 0.974, relative_absolute_error: 0.0595, root_mean_prior_squared_error: 0.4676, root_mean_squared_error: 0.1614, root_relative_squared_error: 0.3451, scimark_benchmark: 1922.3298, usercpu_time_millis: 12046.875, usercpu_time_millis_testing: 5640.625, usercpu_time_millis_training: 6406.25,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9764, f_measure: 0.9766, kappa: 0.9467, kb_relative_information_score: 361.8809, mean_absolute_error: 0.0234, mean_prior_absolute_error: 0.4376, number_of_instances: 384, precision: 0.9768, predictive_accuracy: 0.9766, prior_entropy: 0.9085, recall: 0.9766, relative_absolute_error: 0.0536, root_mean_prior_squared_error: 0.4676, root_mean_squared_error: 0.1531, root_relative_squared_error: 0.3274, scimark_benchmark: 1922.3298, usercpu_time_millis: 11125, usercpu_time_millis_testing: 5546.875, usercpu_time_millis_training: 5578.125,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.5467, kb_relative_information_score: 84.5115, mean_absolute_error: 0.3229, mean_prior_absolute_error: 0.4376, number_of_instances: 384, precision: 0.4584, predictive_accuracy: 0.6771, prior_entropy: 0.9085, recall: 0.6771, relative_absolute_error: 0.7379, root_mean_prior_squared_error: 0.4676, root_mean_squared_error: 0.5683, root_relative_squared_error: 1.2153, scimark_benchmark: 1922.3298, usercpu_time_millis: 37125, usercpu_time_millis_testing: 15109.375, usercpu_time_millis_training: 22015.625,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.5467, kb_relative_information_score: 84.5115, mean_absolute_error: 0.3229, mean_prior_absolute_error: 0.4376, number_of_instances: 384, precision: 0.4584, predictive_accuracy: 0.6771, prior_entropy: 0.9085, recall: 0.6771, relative_absolute_error: 0.7379, root_mean_prior_squared_error: 0.4676, root_mean_squared_error: 0.5683, root_relative_squared_error: 1.2153, scimark_benchmark: 1280.301, usercpu_time_millis: 28625, usercpu_time_millis_testing: 11781.25, usercpu_time_millis_training: 16843.75,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5097, f_measure: 0.5467, kb_relative_information_score: 22.9636, mean_absolute_error: 0.4107, mean_prior_absolute_error: 0.4376, number_of_instances: 384, precision: 0.4584, predictive_accuracy: 0.6771, prior_entropy: 0.9085, recall: 0.6771, relative_absolute_error: 0.9384, root_mean_prior_squared_error: 0.4676, root_mean_squared_error: 0.4735, root_relative_squared_error: 1.0126, scimark_benchmark: 1380.6673, usercpu_time_millis: 1192700, usercpu_time_millis_testing: 55270, usercpu_time_millis_training: 1137430,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.5467, kb_relative_information_score: 84.5115, mean_absolute_error: 0.3229, mean_prior_absolute_error: 0.4376, number_of_instances: 384, precision: 0.4584, predictive_accuracy: 0.6771, prior_entropy: 0.9085, recall: 0.6771, relative_absolute_error: 0.7379, root_mean_prior_squared_error: 0.4676, root_mean_squared_error: 0.5683, root_relative_squared_error: 1.2153, scimark_benchmark: 1542.6339, usercpu_time_millis: 22390, usercpu_time_millis_testing: 11990, usercpu_time_millis_training: 10400,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.5467, kb_relative_information_score: 84.5115, mean_absolute_error: 0.3229, mean_prior_absolute_error: 0.4376, number_of_instances: 384, precision: 0.4584, predictive_accuracy: 0.6771, prior_entropy: 0.9085, recall: 0.6771, relative_absolute_error: 0.7379, root_mean_prior_squared_error: 0.4676, root_mean_squared_error: 0.5683, root_relative_squared_error: 1.2153, scimark_benchmark: 1381.5926, usercpu_time_millis: 38670, usercpu_time_millis_testing: 19250, usercpu_time_millis_training: 19420,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9723, f_measure: 0.974, kappa: 0.9407, kb_relative_information_score: 359.469, mean_absolute_error: 0.026, mean_prior_absolute_error: 0.4376, number_of_instances: 384, precision: 0.9741, predictive_accuracy: 0.974, prior_entropy: 0.9085, recall: 0.974, relative_absolute_error: 0.0595, root_mean_prior_squared_error: 0.4676, root_mean_squared_error: 0.1614, root_relative_squared_error: 0.3451, scimark_benchmark: 1389.039, usercpu_time_millis: 13160, usercpu_time_millis_testing: 6660, usercpu_time_millis_training: 6500,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9764, f_measure: 0.9766, kappa: 0.9467, kb_relative_information_score: 361.8809, mean_absolute_error: 0.0234, mean_prior_absolute_error: 0.4376, number_of_instances: 384, precision: 0.9768, predictive_accuracy: 0.9766, prior_entropy: 0.9085, recall: 0.9766, relative_absolute_error: 0.0536, root_mean_prior_squared_error: 0.4676, root_mean_squared_error: 0.1531, root_relative_squared_error: 0.3274, scimark_benchmark: 1389.2572, usercpu_time_millis: 14630, usercpu_time_millis_testing: 7340, usercpu_time_millis_training: 7290,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5089, f_measure: 0.5711, kappa: 0.0105, kb_relative_information_score: -17.5986, mean_absolute_error: 0.4354, mean_prior_absolute_error: 0.4376, number_of_instances: 384, precision: 0.5673, predictive_accuracy: 0.5755, prior_entropy: 0.9085, recall: 0.5755, relative_absolute_error: 0.995, root_mean_prior_squared_error: 0.4676, root_mean_squared_error: 0.6419, root_relative_squared_error: 1.3728, scimark_benchmark: 1665.974, usercpu_time_millis: 289781.25, usercpu_time_millis_testing: 77750, usercpu_time_millis_training: 212031.25,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9844, f_measure: 0.9819, kappa: 0.9587, kb_relative_information_score: 366.7047, mean_absolute_error: 0.0182, mean_prior_absolute_error: 0.4376, number_of_instances: 384, precision: 0.9823, predictive_accuracy: 0.9818, prior_entropy: 0.9085, recall: 0.9818, relative_absolute_error: 0.0417, root_mean_prior_squared_error: 0.4676, root_mean_squared_error: 0.135, root_relative_squared_error: 0.2887, scimark_benchmark: 1124.9151, usercpu_time_millis: 6810, usercpu_time_millis_testing: 250, usercpu_time_millis_training: 6560,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9725, f_measure: 0.9715, kappa: 0.9352, kb_relative_information_score: 357.0571, mean_absolute_error: 0.0286, mean_prior_absolute_error: 0.4376, number_of_instances: 384, precision: 0.972, predictive_accuracy: 0.9714, prior_entropy: 0.9085, recall: 0.9714, relative_absolute_error: 0.0655, root_mean_prior_squared_error: 0.4676, root_mean_squared_error: 0.1693, root_relative_squared_error: 0.362, scimark_benchmark: 1345.0631, usercpu_time_millis: 4780, usercpu_time_millis_testing: 2660, usercpu_time_millis_training: 2120,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9783, f_measure: 0.9792, kappa: 0.9526, kb_relative_information_score: 364.2928, mean_absolute_error: 0.0208, mean_prior_absolute_error: 0.4376, number_of_instances: 384, precision: 0.9793, predictive_accuracy: 0.9792, prior_entropy: 0.9085, recall: 0.9792, relative_absolute_error: 0.0476, root_mean_prior_squared_error: 0.4676, root_mean_squared_error: 0.1443, root_relative_squared_error: 0.3087, scimark_benchmark: 1425.2056, usercpu_time_millis: 1950, usercpu_time_millis_testing: 130, usercpu_time_millis_training: 1820,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9844, f_measure: 0.9819, kappa: 0.9587, kb_relative_information_score: 366.7047, mean_absolute_error: 0.0182, mean_prior_absolute_error: 0.4376, number_of_instances: 384, precision: 0.9823, predictive_accuracy: 0.9818, prior_entropy: 0.9085, recall: 0.9818, relative_absolute_error: 0.0417, root_mean_prior_squared_error: 0.4676, root_mean_squared_error: 0.135, root_relative_squared_error: 0.2887, scimark_benchmark: 1310.272, usercpu_time_millis: 7710, usercpu_time_millis_testing: 100, usercpu_time_millis_training: 7610,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5093, f_measure: 0.5467, kb_relative_information_score: 22.9636, mean_absolute_error: 0.4107, mean_prior_absolute_error: 0.4376, number_of_instances: 384, precision: 0.4584, predictive_accuracy: 0.6771, prior_entropy: 0.9085, recall: 0.6771, relative_absolute_error: 0.9384, root_mean_prior_squared_error: 0.4676, root_mean_squared_error: 0.4735, root_relative_squared_error: 1.0126, scimark_benchmark: 1178.7956, usercpu_time_millis: 707360, usercpu_time_millis_testing: 161910, usercpu_time_millis_training: 545450,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.98, f_measure: 0.9689, kappa: 0.9294, kb_relative_information_score: 355.0722, mean_absolute_error: 0.0308, mean_prior_absolute_error: 0.4376, number_of_instances: 384, precision: 0.9696, predictive_accuracy: 0.9688, prior_entropy: 0.9085, recall: 0.9688, relative_absolute_error: 0.0704, root_mean_prior_squared_error: 0.4676, root_mean_squared_error: 0.1673, root_relative_squared_error: 0.3577, scimark_benchmark: 1277.8327, usercpu_time_millis: 765470, usercpu_time_millis_testing: 90, usercpu_time_millis_training: 765380,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9594, f_measure: 0.9611, kappa: 0.9112, kb_relative_information_score: 345.7897, mean_absolute_error: 0.0417, mean_prior_absolute_error: 0.4376, number_of_instances: 384, precision: 0.9613, predictive_accuracy: 0.9609, prior_entropy: 0.9085, recall: 0.9609, relative_absolute_error: 0.0953, root_mean_prior_squared_error: 0.4676, root_mean_squared_error: 0.1971, root_relative_squared_error: 0.4215, scimark_benchmark: 1404.0128, usercpu_time_millis: 8010, usercpu_time_millis_testing: 6740, usercpu_time_millis_training: 1270,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9842, f_measure: 0.9819, kappa: 0.9587, kb_relative_information_score: 366.2346, mean_absolute_error: 0.0189, mean_prior_absolute_error: 0.4376, number_of_instances: 384, precision: 0.9823, predictive_accuracy: 0.9818, prior_entropy: 0.9085, recall: 0.9818, relative_absolute_error: 0.0432, root_mean_prior_squared_error: 0.4676, root_mean_squared_error: 0.1356, root_relative_squared_error: 0.2901, scimark_benchmark: 1377.7429, usercpu_time_millis: 149370, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 149350,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9311, f_measure: 0.9376, kappa: 0.8577, kb_relative_information_score: 319.131, mean_absolute_error: 0.0729, mean_prior_absolute_error: 0.4376, number_of_instances: 384, precision: 0.9378, predictive_accuracy: 0.9375, prior_entropy: 0.9085, recall: 0.9375, relative_absolute_error: 0.1666, root_mean_prior_squared_error: 0.4676, root_mean_squared_error: 0.2462, root_relative_squared_error: 0.5265, scimark_benchmark: 872.4536, usercpu_time_millis: 8460, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 8420,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9685, f_measure: 0.969, kappa: 0.93, kb_relative_information_score: 337.2984, mean_absolute_error: 0.0585, mean_prior_absolute_error: 0.4376, number_of_instances: 384, precision: 0.9708, predictive_accuracy: 0.9688, prior_entropy: 0.9085, recall: 0.9688, relative_absolute_error: 0.1336, root_mean_prior_squared_error: 0.4676, root_mean_squared_error: 0.1708, root_relative_squared_error: 0.3652, scimark_benchmark: 739.3244, usercpu_time_millis: 3360, usercpu_time_millis_testing: 60, usercpu_time_millis_training: 3300,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9958, f_measure: 0.9637, kappa: 0.9173, kb_relative_information_score: 312.9151, mean_absolute_error: 0.0943, mean_prior_absolute_error: 0.4376, number_of_instances: 384, precision: 0.9641, predictive_accuracy: 0.9635, prior_entropy: 0.9085, recall: 0.9635, relative_absolute_error: 0.2155, root_mean_prior_squared_error: 0.4676, root_mean_squared_error: 0.1641, root_relative_squared_error: 0.351, scimark_benchmark: 1034.3134, usercpu_time_millis: 3910, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 3870,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9744, f_measure: 0.9741, kappa: 0.9409, kb_relative_information_score: 359.469, mean_absolute_error: 0.026, mean_prior_absolute_error: 0.4376, number_of_instances: 384, precision: 0.9744, predictive_accuracy: 0.974, prior_entropy: 0.9085, recall: 0.974, relative_absolute_error: 0.0595, root_mean_prior_squared_error: 0.4676, root_mean_squared_error: 0.1614, root_relative_squared_error: 0.3451, scimark_benchmark: 1196.8175, usercpu_time_millis: 8590, usercpu_time_millis_testing: 2220, usercpu_time_millis_training: 6370,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9714, f_measure: 0.9688, kappa: 0.9288, kb_relative_information_score: 354.0867, mean_absolute_error: 0.0321, mean_prior_absolute_error: 0.4376, number_of_instances: 384, precision: 0.9689, predictive_accuracy: 0.9688, prior_entropy: 0.9085, recall: 0.9688, relative_absolute_error: 0.0734, root_mean_prior_squared_error: 0.4676, root_mean_squared_error: 0.1737, root_relative_squared_error: 0.3714, scimark_benchmark: 1171.4728, usercpu_time_millis: 2930, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 2910,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9744, f_measure: 0.9741, kappa: 0.9409, kb_relative_information_score: 359.469, mean_absolute_error: 0.026, mean_prior_absolute_error: 0.4376, number_of_instances: 384, precision: 0.9744, predictive_accuracy: 0.974, prior_entropy: 0.9085, recall: 0.974, relative_absolute_error: 0.0595, root_mean_prior_squared_error: 0.4676, root_mean_squared_error: 0.1614, root_relative_squared_error: 0.3451, scimark_benchmark: 1319.0128, usercpu_time_millis: 4950, usercpu_time_millis_testing: 2780, usercpu_time_millis_training: 2170,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5048, f_measure: 0.5467, kb_relative_information_score: 22.3247, mean_absolute_error: 0.4114, mean_prior_absolute_error: 0.4376, number_of_instances: 384, precision: 0.4584, predictive_accuracy: 0.6771, prior_entropy: 0.9085, recall: 0.6771, relative_absolute_error: 0.9402, root_mean_prior_squared_error: 0.4676, root_mean_squared_error: 0.4732, root_relative_squared_error: 1.012, scimark_benchmark: 983.6718, usercpu_time_millis: 478090, usercpu_time_millis_testing: 101930, usercpu_time_millis_training: 376160,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9526, f_measure: 0.9531, kappa: 0.8928, kb_relative_information_score: 333.2102, mean_absolute_error: 0.058, mean_prior_absolute_error: 0.4376, number_of_instances: 384, precision: 0.9531, predictive_accuracy: 0.9531, prior_entropy: 0.9085, recall: 0.9531, relative_absolute_error: 0.1325, root_mean_prior_squared_error: 0.4676, root_mean_squared_error: 0.2144, root_relative_squared_error: 0.4584, scimark_benchmark: 895.4679, usercpu_time_millis: 7630, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 7600,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9725, f_measure: 0.9715, kappa: 0.9352, kb_relative_information_score: 357.0571, mean_absolute_error: 0.0286, mean_prior_absolute_error: 0.4376, number_of_instances: 384, precision: 0.972, predictive_accuracy: 0.9714, prior_entropy: 0.9085, recall: 0.9714, relative_absolute_error: 0.0655, root_mean_prior_squared_error: 0.4676, root_mean_squared_error: 0.1693, root_relative_squared_error: 0.362, scimark_benchmark: 798.5179, usercpu_time_millis: 8830, usercpu_time_millis_testing: 2530, usercpu_time_millis_training: 6300,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9963, f_measure: 0.9663, kappa: 0.9234, kb_relative_information_score: 308.1722, mean_absolute_error: 0.1004, mean_prior_absolute_error: 0.4376, number_of_instances: 384, precision: 0.9669, predictive_accuracy: 0.9661, prior_entropy: 0.9085, recall: 0.9661, relative_absolute_error: 0.2294, root_mean_prior_squared_error: 0.4676, root_mean_squared_error: 0.1694, root_relative_squared_error: 0.3623, scimark_benchmark: 1048.9315, usercpu_time_millis: 1820, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 1790,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9627, f_measure: 0.9587, kappa: 0.9063, kb_relative_information_score: 330.7245, mean_absolute_error: 0.0642, mean_prior_absolute_error: 0.4376, number_of_instances: 384, precision: 0.9599, predictive_accuracy: 0.9583, prior_entropy: 0.9085, recall: 0.9583, relative_absolute_error: 0.1466, root_mean_prior_squared_error: 0.4676, root_mean_squared_error: 0.1935, root_relative_squared_error: 0.4139, scimark_benchmark: 1076.0659, usercpu_time_millis: 850, usercpu_time_millis_testing: 80, usercpu_time_millis_training: 770,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9594, f_measure: 0.9611, kappa: 0.9112, kb_relative_information_score: 345.7897, mean_absolute_error: 0.0417, mean_prior_absolute_error: 0.4376, number_of_instances: 384, precision: 0.9613, predictive_accuracy: 0.9609, prior_entropy: 0.9085, recall: 0.9609, relative_absolute_error: 0.0953, root_mean_prior_squared_error: 0.4676, root_mean_squared_error: 0.1971, root_relative_squared_error: 0.4215, scimark_benchmark: 1145.9754, usercpu_time_millis: 11180, usercpu_time_millis_testing: 11170, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9697, f_measure: 0.9688, kappa: 0.9285, kb_relative_information_score: 354.1012, mean_absolute_error: 0.0321, mean_prior_absolute_error: 0.4376, number_of_instances: 384, precision: 0.9688, predictive_accuracy: 0.9688, prior_entropy: 0.9085, recall: 0.9688, relative_absolute_error: 0.0734, root_mean_prior_squared_error: 0.4676, root_mean_squared_error: 0.1737, root_relative_squared_error: 0.3714, scimark_benchmark: 1180.1836, usercpu_time_millis: 1090, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 1070,

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