OpenML
Supervised Classification on diabetes

Supervised Classification on diabetes

Task 37 Supervised Classification diabetes 131682 runs submitted
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  • at2 basic mythbusting mythbusting_1 OpenML-CC18 OpenML100 study_1 study_107 study_123 study_14 study_15 study_20 study_29 study_30 study_41 study_7 study_70 study_73 study_98 study_99 under100k under1m
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8315, f_measure: 0.7645, kappa: 0.4754, kb_relative_information_score: 236.8374, mean_absolute_error: 0.3208, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7636, predictive_accuracy: 0.7682, prior_entropy: 0.9335, recall: 0.7682, relative_absolute_error: 0.7058, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3967, root_relative_squared_error: 0.8323, scimark_benchmark: 1857.5664, usercpu_time_millis: 3.139, usercpu_time_millis_testing: 0.37, usercpu_time_millis_training: 2.769,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.832, f_measure: 0.7624, kappa: 0.4714, kb_relative_information_score: 246.8153, mean_absolute_error: 0.3124, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7613, predictive_accuracy: 0.7656, prior_entropy: 0.9335, recall: 0.7656, relative_absolute_error: 0.6873, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3957, root_relative_squared_error: 0.8302, scimark_benchmark: 1861.7123, usercpu_time_millis: 1.738, usercpu_time_millis_testing: 0.136, usercpu_time_millis_training: 1.602,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8301, f_measure: 0.7581, kappa: 0.4634, kb_relative_information_score: 255.5739, mean_absolute_error: 0.3064, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7569, predictive_accuracy: 0.7604, prior_entropy: 0.9335, recall: 0.7604, relative_absolute_error: 0.6741, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3978, root_relative_squared_error: 0.8345, scimark_benchmark: 1860.6861, usercpu_time_millis: 2.248, usercpu_time_millis_testing: 0.199, usercpu_time_millis_training: 2.049,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8366, f_measure: 0.766, kappa: 0.4776, kb_relative_information_score: 246.5559, mean_absolute_error: 0.3144, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7657, predictive_accuracy: 0.7708, prior_entropy: 0.9335, recall: 0.7708, relative_absolute_error: 0.6918, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3937, root_relative_squared_error: 0.8259, scimark_benchmark: 1856.5802, usercpu_time_millis: 4.539, usercpu_time_millis_testing: 0.532, usercpu_time_millis_training: 4.007,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.828, f_measure: 0.7624, kappa: 0.4701, kb_relative_information_score: 198.5557, mean_absolute_error: 0.3448, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7618, predictive_accuracy: 0.7669, prior_entropy: 0.9335, recall: 0.7669, relative_absolute_error: 0.7586, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4022, root_relative_squared_error: 0.8439, scimark_benchmark: 1130.8659, usercpu_time_millis: 4.82, usercpu_time_millis_testing: 0.908, usercpu_time_millis_training: 3.912,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8371, f_measure: 0.7609, kappa: 0.468, kb_relative_information_score: 247.6696, mean_absolute_error: 0.3135, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7598, predictive_accuracy: 0.7643, prior_entropy: 0.9335, recall: 0.7643, relative_absolute_error: 0.6899, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3937, root_relative_squared_error: 0.826, scimark_benchmark: 1853.3841, usercpu_time_millis: 5.696, usercpu_time_millis_testing: 0.589, usercpu_time_millis_training: 5.107,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4978, f_measure: 0.5134, kb_relative_information_score: 0.4584, mean_absolute_error: 0.4542, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.4239, predictive_accuracy: 0.651, prior_entropy: 0.9335, recall: 0.651, relative_absolute_error: 0.9994, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4766, root_relative_squared_error: 1, scimark_benchmark: 1855.9428, usercpu_time_millis: 1.092, usercpu_time_millis_testing: 0.207, usercpu_time_millis_training: 0.885,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4993, f_measure: 0.5134, kb_relative_information_score: 0.1503, mean_absolute_error: 0.4544, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.4239, predictive_accuracy: 0.651, prior_entropy: 0.9335, recall: 0.651, relative_absolute_error: 0.9997, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4766, root_relative_squared_error: 1, scimark_benchmark: 1869.7037, usercpu_time_millis: 1.351, usercpu_time_millis_testing: 0.22, usercpu_time_millis_training: 1.131,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8338, f_measure: 0.7676, kappa: 0.4831, kb_relative_information_score: 232.8374, mean_absolute_error: 0.3233, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7666, predictive_accuracy: 0.7708, prior_entropy: 0.9335, recall: 0.7708, relative_absolute_error: 0.7114, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3961, root_relative_squared_error: 0.831, scimark_benchmark: 1872.4216, usercpu_time_millis: 10.286, usercpu_time_millis_testing: 1.351, usercpu_time_millis_training: 8.935,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8305, f_measure: 0.7562, kappa: 0.4581, kb_relative_information_score: 251.1075, mean_absolute_error: 0.3097, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7549, predictive_accuracy: 0.7591, prior_entropy: 0.9335, recall: 0.7591, relative_absolute_error: 0.6815, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3976, root_relative_squared_error: 0.8341, scimark_benchmark: 1870.742, usercpu_time_millis: 7.59, usercpu_time_millis_testing: 0.598, usercpu_time_millis_training: 6.992,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8362, f_measure: 0.7627, kappa: 0.4684, kb_relative_information_score: 222.3199, mean_absolute_error: 0.3308, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.764, predictive_accuracy: 0.7695, prior_entropy: 0.9335, recall: 0.7695, relative_absolute_error: 0.7278, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3959, root_relative_squared_error: 0.8306, scimark_benchmark: 1871.2001, usercpu_time_millis: 3.631, usercpu_time_millis_testing: 0.45, usercpu_time_millis_training: 3.181,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8277, f_measure: 0.7555, kappa: 0.4576, kb_relative_information_score: 245.8679, mean_absolute_error: 0.3128, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7543, predictive_accuracy: 0.7578, prior_entropy: 0.9335, recall: 0.7578, relative_absolute_error: 0.6882, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3997, root_relative_squared_error: 0.8385, scimark_benchmark: 1868.7112, usercpu_time_millis: 0.529, usercpu_time_millis_testing: 0.166, usercpu_time_millis_training: 0.363,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.829, f_measure: 0.7633, kappa: 0.4703, kb_relative_information_score: 218.8357, mean_absolute_error: 0.3329, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.764, predictive_accuracy: 0.7695, prior_entropy: 0.9335, recall: 0.7695, relative_absolute_error: 0.7326, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3985, root_relative_squared_error: 0.8361, scimark_benchmark: 1870.1619, usercpu_time_millis: 3.094, usercpu_time_millis_testing: 0.401, usercpu_time_millis_training: 2.693,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8303, f_measure: 0.7598, kappa: 0.4677, kb_relative_information_score: 246.5755, mean_absolute_error: 0.3134, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7587, predictive_accuracy: 0.7617, prior_entropy: 0.9335, recall: 0.7617, relative_absolute_error: 0.6895, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3975, root_relative_squared_error: 0.8339, scimark_benchmark: 1861.8971, usercpu_time_millis: 1.5, usercpu_time_millis_testing: 0.146, usercpu_time_millis_training: 1.354,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8046, f_measure: 0.7222, kappa: 0.3743, kb_relative_information_score: 125.78, mean_absolute_error: 0.39, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7408, predictive_accuracy: 0.7435, prior_entropy: 0.9335, recall: 0.7435, relative_absolute_error: 0.8581, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4247, root_relative_squared_error: 0.8911, scimark_benchmark: 1867.6156, usercpu_time_millis: 0.395, usercpu_time_millis_testing: 0.066, usercpu_time_millis_training: 0.329,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.815, f_measure: 0.6968, kappa: 0.3203, kb_relative_information_score: 124.2872, mean_absolute_error: 0.391, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7354, predictive_accuracy: 0.7305, prior_entropy: 0.9335, recall: 0.7305, relative_absolute_error: 0.8603, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4238, root_relative_squared_error: 0.8891, scimark_benchmark: 1869.1727, usercpu_time_millis: 1.674, usercpu_time_millis_testing: 0.26, usercpu_time_millis_training: 1.414,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8316, f_measure: 0.7651, kappa: 0.4747, kb_relative_information_score: 194.9709, mean_absolute_error: 0.3477, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7655, predictive_accuracy: 0.7708, prior_entropy: 0.9335, recall: 0.7708, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4016, root_relative_squared_error: 0.8426, scimark_benchmark: 1874.4489, usercpu_time_millis: 4.898, usercpu_time_millis_testing: 0.756, usercpu_time_millis_training: 4.142,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8153, f_measure: 0.7382, kappa: 0.4125, kb_relative_information_score: 191.949, mean_absolute_error: 0.3491, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7399, predictive_accuracy: 0.7474, prior_entropy: 0.9335, recall: 0.7474, relative_absolute_error: 0.7682, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4075, root_relative_squared_error: 0.8549, scimark_benchmark: 1817.9594, usercpu_time_millis: 1.092, usercpu_time_millis_testing: 0.119, usercpu_time_millis_training: 0.973,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8313, f_measure: 0.7552, kappa: 0.4566, kb_relative_information_score: 259.2177, mean_absolute_error: 0.3029, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.754, predictive_accuracy: 0.7578, prior_entropy: 0.9335, recall: 0.7578, relative_absolute_error: 0.6665, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3974, root_relative_squared_error: 0.8338, scimark_benchmark: 1865.9581, usercpu_time_millis: 5.446, usercpu_time_millis_testing: 0.58, usercpu_time_millis_training: 4.866,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8328, f_measure: 0.7658, kappa: 0.48, kb_relative_information_score: 255.8091, mean_absolute_error: 0.3071, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7646, predictive_accuracy: 0.7682, prior_entropy: 0.9335, recall: 0.7682, relative_absolute_error: 0.6758, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3959, root_relative_squared_error: 0.8307, scimark_benchmark: 1822.8344, usercpu_time_millis: 0.998, usercpu_time_millis_testing: 0.093, usercpu_time_millis_training: 0.905,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8347, f_measure: 0.7645, kappa: 0.4754, kb_relative_information_score: 241.122, mean_absolute_error: 0.3182, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7636, predictive_accuracy: 0.7682, prior_entropy: 0.9335, recall: 0.7682, relative_absolute_error: 0.7001, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3951, root_relative_squared_error: 0.8288, scimark_benchmark: 1865.8853, usercpu_time_millis: 4.296, usercpu_time_millis_testing: 0.565, usercpu_time_millis_training: 3.731,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8341, f_measure: 0.7679, kappa: 0.484, kb_relative_information_score: 233.9284, mean_absolute_error: 0.3229, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7668, predictive_accuracy: 0.7708, prior_entropy: 0.9335, recall: 0.7708, relative_absolute_error: 0.7104, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3956, root_relative_squared_error: 0.83, scimark_benchmark: 1872.0299, usercpu_time_millis: 4.393, usercpu_time_millis_testing: 0.589, usercpu_time_millis_training: 3.804,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8295, f_measure: 0.7641, kappa: 0.4757, kb_relative_information_score: 244.5593, mean_absolute_error: 0.3151, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7629, predictive_accuracy: 0.7669, prior_entropy: 0.9335, recall: 0.7669, relative_absolute_error: 0.6933, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3977, root_relative_squared_error: 0.8343, scimark_benchmark: 1821.8602, usercpu_time_millis: 2.084, usercpu_time_millis_testing: 0.185, usercpu_time_millis_training: 1.899,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.837, f_measure: 0.7683, kappa: 0.4838, kb_relative_information_score: 232.1501, mean_absolute_error: 0.3247, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7675, predictive_accuracy: 0.7721, prior_entropy: 0.9335, recall: 0.7721, relative_absolute_error: 0.7144, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3944, root_relative_squared_error: 0.8275, scimark_benchmark: 1869.8473, usercpu_time_millis: 3.339, usercpu_time_millis_testing: 0.454, usercpu_time_millis_training: 2.885,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8343, f_measure: 0.7638, kappa: 0.4748, kb_relative_information_score: 245.8249, mean_absolute_error: 0.3143, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7627, predictive_accuracy: 0.7669, prior_entropy: 0.9335, recall: 0.7669, relative_absolute_error: 0.6916, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3952, root_relative_squared_error: 0.8291, scimark_benchmark: 1873.5991, usercpu_time_millis: 7.451, usercpu_time_millis_testing: 0.774, usercpu_time_millis_training: 6.677,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8374, f_measure: 0.7621, kappa: 0.4704, kb_relative_information_score: 246.8206, mean_absolute_error: 0.3143, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7611, predictive_accuracy: 0.7656, prior_entropy: 0.9335, recall: 0.7656, relative_absolute_error: 0.6915, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3935, root_relative_squared_error: 0.8256, scimark_benchmark: 1841.0391, usercpu_time_millis: 5.564, usercpu_time_millis_testing: 0.607, usercpu_time_millis_training: 4.957,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8346, f_measure: 0.7689, kappa: 0.4877, kb_relative_information_score: 252.6356, mean_absolute_error: 0.3097, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7678, predictive_accuracy: 0.7708, prior_entropy: 0.9335, recall: 0.7708, relative_absolute_error: 0.6814, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3952, root_relative_squared_error: 0.8291, scimark_benchmark: 1865.8853, usercpu_time_millis: 0.577, usercpu_time_millis_testing: 0.051, usercpu_time_millis_training: 0.526,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8312, f_measure: 0.759, kappa: 0.4594, kb_relative_information_score: 202.8352, mean_absolute_error: 0.3436, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7612, predictive_accuracy: 0.7669, prior_entropy: 0.9335, recall: 0.7669, relative_absolute_error: 0.7561, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4, root_relative_squared_error: 0.8392, scimark_benchmark: 1867.725, usercpu_time_millis: 1.855, usercpu_time_millis_testing: 0.274, usercpu_time_millis_training: 1.581,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.825, f_measure: 0.771, kappa: 0.4937, kb_relative_information_score: 256.3102, mean_absolute_error: 0.3051, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7702, predictive_accuracy: 0.7721, prior_entropy: 0.9335, recall: 0.7721, relative_absolute_error: 0.6713, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4022, root_relative_squared_error: 0.8438, scimark_benchmark: 1869.6309, usercpu_time_millis: 2.018, usercpu_time_millis_testing: 0.175, usercpu_time_millis_training: 1.843,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8223, f_measure: 0.6913, kappa: 0.3107, kb_relative_information_score: 119.1607, mean_absolute_error: 0.3938, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7438, predictive_accuracy: 0.7305, prior_entropy: 0.9335, recall: 0.7305, relative_absolute_error: 0.8664, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4247, root_relative_squared_error: 0.8911, scimark_benchmark: 1873.5991, usercpu_time_millis: 2.291, usercpu_time_millis_testing: 0.37, usercpu_time_millis_training: 1.921,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.832, f_measure: 0.758, kappa: 0.4583, kb_relative_information_score: 184.0827, mean_absolute_error: 0.3544, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7585, predictive_accuracy: 0.7643, prior_entropy: 0.9335, recall: 0.7643, relative_absolute_error: 0.7797, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4035, root_relative_squared_error: 0.8465, scimark_benchmark: 1872.0299, usercpu_time_millis: 3.562, usercpu_time_millis_testing: 0.577, usercpu_time_millis_training: 2.985,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8059, f_measure: 0.7296, kappa: 0.4032, kb_relative_information_score: 252.116, mean_absolute_error: 0.3022, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7289, predictive_accuracy: 0.7305, prior_entropy: 0.9335, recall: 0.7305, relative_absolute_error: 0.6649, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4182, root_relative_squared_error: 0.8773, scimark_benchmark: 1874.977, usercpu_time_millis: 9.044, usercpu_time_millis_testing: 0.767, usercpu_time_millis_training: 8.277,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8317, f_measure: 0.7705, kappa: 0.4899, kb_relative_information_score: 235.3087, mean_absolute_error: 0.3213, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7695, predictive_accuracy: 0.7734, prior_entropy: 0.9335, recall: 0.7734, relative_absolute_error: 0.707, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3971, root_relative_squared_error: 0.8331, scimark_benchmark: 1873.4805, usercpu_time_millis: 8.906, usercpu_time_millis_testing: 1.288, usercpu_time_millis_training: 7.618,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8109, f_measure: 0.5758, kappa: 0.0977, kb_relative_information_score: 84.5128, mean_absolute_error: 0.4124, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.715, predictive_accuracy: 0.6745, prior_entropy: 0.9335, recall: 0.6745, relative_absolute_error: 0.9074, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4386, root_relative_squared_error: 0.9201, scimark_benchmark: 1835.621, usercpu_time_millis: 0.233, usercpu_time_millis_testing: 0.038, usercpu_time_millis_training: 0.195,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4978, f_measure: 0.5134, kb_relative_information_score: 0.194, mean_absolute_error: 0.4544, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.4239, predictive_accuracy: 0.651, prior_entropy: 0.9335, recall: 0.651, relative_absolute_error: 0.9997, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4766, root_relative_squared_error: 1, scimark_benchmark: 1838.5681, usercpu_time_millis: 1.074, usercpu_time_millis_testing: 0.186, usercpu_time_millis_training: 0.888,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8313, f_measure: 0.7678, kappa: 0.4819, kb_relative_information_score: 234.6081, mean_absolute_error: 0.3224, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7673, predictive_accuracy: 0.7721, prior_entropy: 0.9335, recall: 0.7721, relative_absolute_error: 0.7095, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.397, root_relative_squared_error: 0.8329, scimark_benchmark: 1869.8223, usercpu_time_millis: 5.454, usercpu_time_millis_testing: 0.609, usercpu_time_millis_training: 4.845,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4996, f_measure: 0.5134, kb_relative_information_score: -0.1107, mean_absolute_error: 0.4544, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.4239, predictive_accuracy: 0.651, prior_entropy: 0.9335, recall: 0.651, relative_absolute_error: 0.9998, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4766, root_relative_squared_error: 1, scimark_benchmark: 1846.6923, usercpu_time_millis: 0.171, usercpu_time_millis_testing: 0.033, usercpu_time_millis_training: 0.138,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8089, f_measure: 0.7365, kappa: 0.4191, kb_relative_information_score: 252.7134, mean_absolute_error: 0.3025, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7361, predictive_accuracy: 0.737, prior_entropy: 0.9335, recall: 0.737, relative_absolute_error: 0.6657, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4158, root_relative_squared_error: 0.8724, scimark_benchmark: 1834.1671, usercpu_time_millis: 1.221, usercpu_time_millis_testing: 0.076, usercpu_time_millis_training: 1.145,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8349, f_measure: 0.7597, kappa: 0.4655, kb_relative_information_score: 257.5324, mean_absolute_error: 0.3056, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7586, predictive_accuracy: 0.763, prior_entropy: 0.9335, recall: 0.763, relative_absolute_error: 0.6723, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3946, root_relative_squared_error: 0.828, scimark_benchmark: 1836.0792, usercpu_time_millis: 2.246, usercpu_time_millis_testing: 0.171, usercpu_time_millis_training: 2.075,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.833, f_measure: 0.7468, kappa: 0.4305, kb_relative_information_score: 186.7201, mean_absolute_error: 0.3531, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7518, predictive_accuracy: 0.7578, prior_entropy: 0.9335, recall: 0.7578, relative_absolute_error: 0.777, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4034, root_relative_squared_error: 0.8463, scimark_benchmark: 1834.0485, usercpu_time_millis: 2.336, usercpu_time_millis_testing: 0.309, usercpu_time_millis_training: 2.027,

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