OpenML
Supervised Classification on diabetes

Supervised Classification on diabetes

Task 37 Supervised Classification diabetes 131650 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: 0.497, f_measure: 0.5134, kb_relative_information_score: -0.1099, mean_absolute_error: 0.4545, 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: 1, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4766, root_relative_squared_error: 1, scimark_benchmark: 1858.4861, usercpu_time_millis: 1.069, usercpu_time_millis_testing: 0.16, usercpu_time_millis_training: 0.909,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8365, f_measure: 0.7565, kappa: 0.4563, kb_relative_information_score: 236.5986, mean_absolute_error: 0.3215, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7561, predictive_accuracy: 0.7617, prior_entropy: 0.9335, recall: 0.7617, relative_absolute_error: 0.7074, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3939, root_relative_squared_error: 0.8265, scimark_benchmark: 1858.6076, usercpu_time_millis: 1.778, usercpu_time_millis_testing: 0.197, usercpu_time_millis_training: 1.581,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8345, f_measure: 0.7608, kappa: 0.4693, kb_relative_information_score: 254.7444, mean_absolute_error: 0.3073, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7596, predictive_accuracy: 0.763, prior_entropy: 0.9335, recall: 0.763, relative_absolute_error: 0.6761, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3952, root_relative_squared_error: 0.8292, scimark_benchmark: 1869.2422, usercpu_time_millis: 3.155, usercpu_time_millis_testing: 0.27, usercpu_time_millis_training: 2.885,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8325, f_measure: 0.7619, kappa: 0.4682, kb_relative_information_score: 230.6473, mean_absolute_error: 0.3253, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7616, predictive_accuracy: 0.7669, prior_entropy: 0.9335, recall: 0.7669, relative_absolute_error: 0.7157, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3963, root_relative_squared_error: 0.8315, scimark_benchmark: 1872.0299, usercpu_time_millis: 4.252, usercpu_time_millis_testing: 0.502, usercpu_time_millis_training: 3.75,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8159, f_measure: 0.7481, kappa: 0.4359, kb_relative_information_score: 195.6001, mean_absolute_error: 0.3463, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7486, predictive_accuracy: 0.7552, prior_entropy: 0.9335, recall: 0.7552, relative_absolute_error: 0.762, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.407, root_relative_squared_error: 0.8538, scimark_benchmark: 1843.9726, usercpu_time_millis: 3.088, usercpu_time_millis_testing: 0.354, usercpu_time_millis_training: 2.734,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8306, f_measure: 0.7684, kappa: 0.4859, kb_relative_information_score: 245.669, mean_absolute_error: 0.3138, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7673, predictive_accuracy: 0.7708, prior_entropy: 0.9335, recall: 0.7708, relative_absolute_error: 0.6905, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3974, root_relative_squared_error: 0.8337, scimark_benchmark: 1813.0559, usercpu_time_millis: 9.052, usercpu_time_millis_testing: 0.955, usercpu_time_millis_training: 8.097,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8233, f_measure: 0.734, kappa: 0.4005, kb_relative_information_score: 147.5221, mean_absolute_error: 0.3766, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7505, predictive_accuracy: 0.7526, prior_entropy: 0.9335, recall: 0.7526, relative_absolute_error: 0.8287, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4152, root_relative_squared_error: 0.8712, scimark_benchmark: 1872.0299, usercpu_time_millis: 1.905, usercpu_time_millis_testing: 0.269, usercpu_time_millis_training: 1.636,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8274, f_measure: 0.7517, kappa: 0.4406, kb_relative_information_score: 165.1105, mean_absolute_error: 0.366, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7628, predictive_accuracy: 0.7656, prior_entropy: 0.9335, recall: 0.7656, relative_absolute_error: 0.8053, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4099, root_relative_squared_error: 0.86, scimark_benchmark: 1869.6309, usercpu_time_millis: 0.17, usercpu_time_millis_testing: 0.027, usercpu_time_millis_training: 0.143,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8245, f_measure: 0.7591, kappa: 0.4672, kb_relative_information_score: 254.7181, mean_absolute_error: 0.3054, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7582, predictive_accuracy: 0.7604, prior_entropy: 0.9335, recall: 0.7604, relative_absolute_error: 0.672, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4023, root_relative_squared_error: 0.8441, scimark_benchmark: 1874.0573, usercpu_time_millis: 5.014, usercpu_time_millis_testing: 0.491, usercpu_time_millis_training: 4.523,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8237, f_measure: 0.7633, kappa: 0.4703, kb_relative_information_score: 215.0221, mean_absolute_error: 0.3348, 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: 0.7365, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.401, root_relative_squared_error: 0.8414, scimark_benchmark: 1869.1727, usercpu_time_millis: 2.696, usercpu_time_millis_testing: 0.319, usercpu_time_millis_training: 2.377,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8319, f_measure: 0.7538, kappa: 0.4463, kb_relative_information_score: 179.9553, mean_absolute_error: 0.3573, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7591, predictive_accuracy: 0.7643, prior_entropy: 0.9335, recall: 0.7643, relative_absolute_error: 0.7861, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4047, root_relative_squared_error: 0.849, scimark_benchmark: 1869.8382, usercpu_time_millis: 2.178, usercpu_time_millis_testing: 0.326, usercpu_time_millis_training: 1.852,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8272, f_measure: 0.7631, kappa: 0.4763, kb_relative_information_score: 257.6248, mean_absolute_error: 0.3039, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7623, predictive_accuracy: 0.7643, prior_entropy: 0.9335, recall: 0.7643, relative_absolute_error: 0.6686, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4005, root_relative_squared_error: 0.8402, scimark_benchmark: 1868.2531, usercpu_time_millis: 10.925, usercpu_time_millis_testing: 1.139, usercpu_time_millis_training: 9.786,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8349, f_measure: 0.7621, kappa: 0.4704, kb_relative_information_score: 246.1693, mean_absolute_error: 0.3144, 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: 0.6917, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3947, root_relative_squared_error: 0.8281, scimark_benchmark: 1870.8114, usercpu_time_millis: 6.339, usercpu_time_millis_testing: 0.647, usercpu_time_millis_training: 5.692,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8299, f_measure: 0.7621, kappa: 0.4678, kb_relative_information_score: 193.7566, mean_absolute_error: 0.3482, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7627, predictive_accuracy: 0.7682, prior_entropy: 0.9335, recall: 0.7682, relative_absolute_error: 0.7661, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4025, root_relative_squared_error: 0.8444, scimark_benchmark: 1869.8223, usercpu_time_millis: 3.001, usercpu_time_millis_testing: 0.411, usercpu_time_millis_training: 2.59,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8332, f_measure: 0.7691, kappa: 0.4865, kb_relative_information_score: 228.5064, mean_absolute_error: 0.3259, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7681, predictive_accuracy: 0.7721, prior_entropy: 0.9335, recall: 0.7721, relative_absolute_error: 0.717, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3965, root_relative_squared_error: 0.8319, scimark_benchmark: 1858.6076, usercpu_time_millis: 7.981, usercpu_time_millis_testing: 1.146, usercpu_time_millis_training: 6.835,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8354, f_measure: 0.766, kappa: 0.4776, kb_relative_information_score: 244.097, mean_absolute_error: 0.3161, 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: 0.6954, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3942, root_relative_squared_error: 0.8271, scimark_benchmark: 1872.9496, usercpu_time_millis: 2.018, usercpu_time_millis_testing: 0.183, usercpu_time_millis_training: 1.835,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8354, f_measure: 0.763, kappa: 0.472, kb_relative_information_score: 234.6943, mean_absolute_error: 0.3224, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7621, predictive_accuracy: 0.7669, prior_entropy: 0.9335, recall: 0.7669, relative_absolute_error: 0.7094, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3951, root_relative_squared_error: 0.8288, scimark_benchmark: 1870.2804, usercpu_time_millis: 1.225, usercpu_time_millis_testing: 0.116, usercpu_time_millis_training: 1.109,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8326, f_measure: 0.7607, kappa: 0.4657, kb_relative_information_score: 234.21, mean_absolute_error: 0.3226, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7602, predictive_accuracy: 0.7656, prior_entropy: 0.9335, recall: 0.7656, relative_absolute_error: 0.7099, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3964, root_relative_squared_error: 0.8317, scimark_benchmark: 1872.0299, usercpu_time_millis: 3.156, usercpu_time_millis_testing: 0.311, usercpu_time_millis_training: 2.845,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8328, f_measure: 0.7573, kappa: 0.4606, kb_relative_information_score: 237.0925, mean_absolute_error: 0.3201, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7561, predictive_accuracy: 0.7604, prior_entropy: 0.9335, recall: 0.7604, relative_absolute_error: 0.7042, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3965, root_relative_squared_error: 0.8318, scimark_benchmark: 1866.8908, usercpu_time_millis: 2.536, usercpu_time_millis_testing: 0.273, usercpu_time_millis_training: 2.263,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8349, f_measure: 0.7672, kappa: 0.4801, kb_relative_information_score: 234.0048, mean_absolute_error: 0.3232, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.767, predictive_accuracy: 0.7721, prior_entropy: 0.9335, recall: 0.7721, relative_absolute_error: 0.711, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3951, root_relative_squared_error: 0.829, scimark_benchmark: 1870.742, usercpu_time_millis: 0.674, usercpu_time_millis_testing: 0.209, usercpu_time_millis_training: 0.465,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8309, f_measure: 0.766, kappa: 0.4776, kb_relative_information_score: 199.3662, mean_absolute_error: 0.3446, 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: 0.7582, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4011, root_relative_squared_error: 0.8414, scimark_benchmark: 1870.2804, usercpu_time_millis: 8.595, usercpu_time_millis_testing: 1.386, usercpu_time_millis_training: 7.209,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7864, f_measure: 0.5247, kappa: 0.0167, kb_relative_information_score: 57.2927, mean_absolute_error: 0.4268, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7049, predictive_accuracy: 0.6549, prior_entropy: 0.9335, recall: 0.6549, relative_absolute_error: 0.9391, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4509, root_relative_squared_error: 0.946, scimark_benchmark: 1872.4956, usercpu_time_millis: 0.156, usercpu_time_millis_testing: 0.032, usercpu_time_millis_training: 0.124,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8299, f_measure: 0.7586, kappa: 0.4653, kb_relative_information_score: 245.1407, mean_absolute_error: 0.3138, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7575, predictive_accuracy: 0.7604, prior_entropy: 0.9335, recall: 0.7604, relative_absolute_error: 0.6905, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3979, root_relative_squared_error: 0.8347, scimark_benchmark: 1869.7037, usercpu_time_millis: 1.728, usercpu_time_millis_testing: 0.157, usercpu_time_millis_training: 1.571,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8367, f_measure: 0.7645, kappa: 0.4728, kb_relative_information_score: 222.8417, mean_absolute_error: 0.3308, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7654, predictive_accuracy: 0.7708, prior_entropy: 0.9335, recall: 0.7708, relative_absolute_error: 0.7278, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3956, root_relative_squared_error: 0.83, scimark_benchmark: 1865.4271, usercpu_time_millis: 1.889, usercpu_time_millis_testing: 0.209, usercpu_time_millis_training: 1.68,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4985, f_measure: 0.5134, kb_relative_information_score: 0.0575, 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: 1869.1727, usercpu_time_millis: 1.441, usercpu_time_millis_testing: 0.321, usercpu_time_millis_training: 1.12,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4978, f_measure: 0.5134, kb_relative_information_score: -0.0718, mean_absolute_error: 0.4545, 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: 0.9999, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4766, root_relative_squared_error: 1, scimark_benchmark: 1749.2121, usercpu_time_millis: 1.384, usercpu_time_millis_testing: 0.22, usercpu_time_millis_training: 1.164,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8253, f_measure: 0.76, kappa: 0.4687, kb_relative_information_score: 248.1522, mean_absolute_error: 0.3108, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.759, predictive_accuracy: 0.7617, prior_entropy: 0.9335, recall: 0.7617, relative_absolute_error: 0.6839, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4007, root_relative_squared_error: 0.8407, scimark_benchmark: 1873.4078, usercpu_time_millis: 14.377, usercpu_time_millis_testing: 1.207, usercpu_time_millis_training: 13.17,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4985, f_measure: 0.5134, kb_relative_information_score: 0.0579, 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: 1854.7475, usercpu_time_millis: 1.618, usercpu_time_millis_testing: 0.236, usercpu_time_millis_training: 1.382,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7881, f_measure: 0.7173, kappa: 0.3776, kb_relative_information_score: 241.7842, mean_absolute_error: 0.304, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7172, predictive_accuracy: 0.7174, prior_entropy: 0.9335, recall: 0.7174, relative_absolute_error: 0.6689, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4374, root_relative_squared_error: 0.9176, scimark_benchmark: 1145.9487, usercpu_time_millis: 34.145, usercpu_time_millis_testing: 2.843, usercpu_time_millis_training: 31.302,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8096, f_measure: 0.7413, kappa: 0.4286, kb_relative_information_score: 254.5764, mean_absolute_error: 0.3018, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7405, predictive_accuracy: 0.7422, prior_entropy: 0.9335, recall: 0.7422, relative_absolute_error: 0.6641, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4143, root_relative_squared_error: 0.8693, scimark_benchmark: 1868.7112, usercpu_time_millis: 12.035, usercpu_time_millis_testing: 1.021, usercpu_time_millis_training: 11.014,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8287, f_measure: 0.7643, kappa: 0.4766, kb_relative_information_score: 246.4739, mean_absolute_error: 0.313, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7632, predictive_accuracy: 0.7669, prior_entropy: 0.9335, recall: 0.7669, relative_absolute_error: 0.6886, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3986, root_relative_squared_error: 0.8363, scimark_benchmark: 1869.1029, usercpu_time_millis: 5.151, usercpu_time_millis_testing: 0.554, usercpu_time_millis_training: 4.597,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8308, f_measure: 0.7568, kappa: 0.4558, kb_relative_information_score: 231.028, mean_absolute_error: 0.3244, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7571, predictive_accuracy: 0.763, prior_entropy: 0.9335, recall: 0.763, relative_absolute_error: 0.7137, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.397, root_relative_squared_error: 0.8329, scimark_benchmark: 1944.545, usercpu_time_millis: 1.91, usercpu_time_millis_testing: 0.162, usercpu_time_millis_training: 1.748,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.834, f_measure: 0.7614, kappa: 0.4698, kb_relative_information_score: 251.6435, mean_absolute_error: 0.3101, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7603, predictive_accuracy: 0.7643, prior_entropy: 0.9335, recall: 0.7643, relative_absolute_error: 0.6822, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3953, root_relative_squared_error: 0.8293, scimark_benchmark: 1874.5882, usercpu_time_millis: 6.945, usercpu_time_millis_testing: 0.624, usercpu_time_millis_training: 6.321,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.832, f_measure: 0.7624, kappa: 0.4701, kb_relative_information_score: 237.5376, mean_absolute_error: 0.3206, 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: 0.7054, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3964, root_relative_squared_error: 0.8317, scimark_benchmark: 1974.5001, usercpu_time_millis: 3.135, usercpu_time_millis_testing: 0.287, usercpu_time_millis_training: 2.848,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8357, f_measure: 0.7676, kappa: 0.4831, kb_relative_information_score: 236.0125, mean_absolute_error: 0.3218, 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: 0.708, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3947, root_relative_squared_error: 0.8281, scimark_benchmark: 1872.4881, usercpu_time_millis: 5.24, usercpu_time_millis_testing: 0.68, usercpu_time_millis_training: 4.56,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.497, f_measure: 0.5134, kb_relative_information_score: 0.0976, 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: 1747.3807, usercpu_time_millis: 0.558, usercpu_time_millis_testing: 0.137, usercpu_time_millis_training: 0.421,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8243, f_measure: 0.7255, kappa: 0.3826, kb_relative_information_score: 130.6912, mean_absolute_error: 0.388, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7575, predictive_accuracy: 0.7513, prior_entropy: 0.9335, recall: 0.7513, relative_absolute_error: 0.8538, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4207, root_relative_squared_error: 0.8827, scimark_benchmark: 1863.9794, usercpu_time_millis: 1.547, usercpu_time_millis_testing: 0.261, usercpu_time_millis_training: 1.286,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8307, f_measure: 0.7642, kappa: 0.4744, kb_relative_information_score: 236.6052, mean_absolute_error: 0.3208, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7634, 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: 0.3973, root_relative_squared_error: 0.8336, scimark_benchmark: 1867.1999, usercpu_time_millis: 4.364, usercpu_time_millis_testing: 0.519, usercpu_time_millis_training: 3.845,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8335, f_measure: 0.7686, kappa: 0.4847, kb_relative_information_score: 224.3954, mean_absolute_error: 0.3286, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7677, predictive_accuracy: 0.7721, prior_entropy: 0.9335, recall: 0.7721, relative_absolute_error: 0.723, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3969, root_relative_squared_error: 0.8327, scimark_benchmark: 1863.4543, usercpu_time_millis: 4.946, usercpu_time_millis_testing: 0.716, usercpu_time_millis_training: 4.23,

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