Task
Supervised Classification on tae

Supervised Classification on tae

Task 47 Supervised Classification tae 940 runs submitted
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  • basic study_1 study_107 study_123 study_41 study_50 study_7 study_73 under100k under1m
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6274, f_measure: 0.5031, kappa: 0.2546, kb_relative_information_score: 48.2563, mean_absolute_error: 0.3311, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.5032, predictive_accuracy: 0.5033, prior_entropy: 1.5845, recall: 0.5033, relative_absolute_error: 0.7453, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.5754, root_relative_squared_error: 1.2209, scimark_benchmark: 931.9984,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7418, f_measure: 0.5784, kappa: 0.374, kb_relative_information_score: 36.047, mean_absolute_error: 0.3743, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.5768, predictive_accuracy: 0.5828, prior_entropy: 1.5845, recall: 0.5828, relative_absolute_error: 0.8425, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.4316, root_relative_squared_error: 0.9158, scimark_benchmark: 912.8659,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7443, f_measure: 0.5924, kappa: 0.3939, kb_relative_information_score: 37.3424, mean_absolute_error: 0.3714, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.5919, predictive_accuracy: 0.596, prior_entropy: 1.5845, recall: 0.596, relative_absolute_error: 0.8359, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.4306, root_relative_squared_error: 0.9136, scimark_benchmark: 910.121,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6053, f_measure: 0.4065, kappa: 0.1265, kb_relative_information_score: 24.8536, mean_absolute_error: 0.4068, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.4053, predictive_accuracy: 0.4172, prior_entropy: 1.5845, recall: 0.4172, relative_absolute_error: 0.9157, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.4738, root_relative_squared_error: 1.0052, scimark_benchmark: 916.4357,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6355, f_measure: 0.4893, kappa: 0.2465, kb_relative_information_score: 26.7914, mean_absolute_error: 0.3985, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.4967, predictive_accuracy: 0.4967, prior_entropy: 1.5845, recall: 0.4967, relative_absolute_error: 0.8969, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.4703, root_relative_squared_error: 0.9977,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7279, f_measure: 0.5899, kappa: 0.3844, kb_relative_information_score: 48.0684, mean_absolute_error: 0.3444, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.5914, predictive_accuracy: 0.5894, prior_entropy: 1.5845, recall: 0.5894, relative_absolute_error: 0.7751, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.4408, root_relative_squared_error: 0.9351, scimark_benchmark: 919.7601,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6989, f_measure: 0.4736, kappa: 0.2155, kb_relative_information_score: 42.7508, mean_absolute_error: 0.3523, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.4737, predictive_accuracy: 0.4768, prior_entropy: 1.5845, recall: 0.4768, relative_absolute_error: 0.7929, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.4649, root_relative_squared_error: 0.9864, scimark_benchmark: 914.5451,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7068, f_measure: 0.5604, kappa: 0.3449, kb_relative_information_score: 46.0748, mean_absolute_error: 0.3503, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.5615, predictive_accuracy: 0.5629, prior_entropy: 1.5845, recall: 0.5629, relative_absolute_error: 0.7883, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.4496, root_relative_squared_error: 0.9538, scimark_benchmark: 947.9517,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5349, f_measure: 0.3671, kappa: 0.0668, kb_relative_information_score: 15.359, mean_absolute_error: 0.4269, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.3635, predictive_accuracy: 0.3775, prior_entropy: 1.5845, recall: 0.3775, relative_absolute_error: 0.9608, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.4668, root_relative_squared_error: 0.9903, scimark_benchmark: 909.6601,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6418, f_measure: 0.496, kappa: 0.2559, kb_relative_information_score: 36.7041, mean_absolute_error: 0.3782, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.4967, predictive_accuracy: 0.5033, prior_entropy: 1.5845, recall: 0.5033, relative_absolute_error: 0.8513, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.4791, root_relative_squared_error: 1.0166, scimark_benchmark: 947.9334,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7751, f_measure: 0.623, kappa: 0.4338, kb_relative_information_score: 62.1358, mean_absolute_error: 0.2931, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.6243, predictive_accuracy: 0.6225, prior_entropy: 1.5845, recall: 0.6225, relative_absolute_error: 0.6598, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.4315, root_relative_squared_error: 0.9155, scimark_benchmark: 947.7758,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7162, f_measure: 0.5964, kappa: 0.394, kb_relative_information_score: 47.6931, mean_absolute_error: 0.3488, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.5971, predictive_accuracy: 0.596, prior_entropy: 1.5845, recall: 0.596, relative_absolute_error: 0.785, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.4474, root_relative_squared_error: 0.9492, scimark_benchmark: 926.2701,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5256, f_measure: 0.2575, kappa: 0.0335, kb_relative_information_score: 16.8378, mean_absolute_error: 0.4327, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.2449, predictive_accuracy: 0.3642, prior_entropy: 1.5845, recall: 0.3642, relative_absolute_error: 0.9738, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.5334, root_relative_squared_error: 1.1317, scimark_benchmark: 918.7337,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6678, f_measure: 0.51, kappa: 0.2763, kb_relative_information_score: 40.5502, mean_absolute_error: 0.365, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.5174, predictive_accuracy: 0.5166, prior_entropy: 1.5845, recall: 0.5166, relative_absolute_error: 0.8214, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.4656, root_relative_squared_error: 0.9879, scimark_benchmark: 927.9795,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6337, f_measure: 0.5293, kappa: 0.2948, kb_relative_information_score: 32.2901, mean_absolute_error: 0.3881, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.5294, predictive_accuracy: 0.5298, prior_entropy: 1.5845, recall: 0.5298, relative_absolute_error: 0.8734, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.4586, root_relative_squared_error: 0.973, scimark_benchmark: 915.9416,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7279, f_measure: 0.5611, kappa: 0.3443, kb_relative_information_score: 55.374, mean_absolute_error: 0.3122, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.5626, predictive_accuracy: 0.5629, prior_entropy: 1.5845, recall: 0.5629, relative_absolute_error: 0.7027, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.4769, root_relative_squared_error: 1.0118, scimark_benchmark: 909.8808,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6689, f_measure: 0.5528, kappa: 0.3336, kb_relative_information_score: 59.5388, mean_absolute_error: 0.2962, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.5524, predictive_accuracy: 0.5563, prior_entropy: 1.5845, recall: 0.5563, relative_absolute_error: 0.6666, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.5369, root_relative_squared_error: 1.1392, scimark_benchmark: 882.4126,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7469, f_measure: 0.5741, kappa: 0.3639, kb_relative_information_score: 59.3467, mean_absolute_error: 0.2993, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.5769, predictive_accuracy: 0.5762, prior_entropy: 1.5845, recall: 0.5762, relative_absolute_error: 0.6737, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.4686, root_relative_squared_error: 0.9942, scimark_benchmark: 911.1409,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6642, f_measure: 0.5142, kappa: 0.3144, kb_relative_information_score: 30.9492, mean_absolute_error: 0.3883, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.5349, predictive_accuracy: 0.543, prior_entropy: 1.5845, recall: 0.543, relative_absolute_error: 0.874, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.4538, root_relative_squared_error: 0.9628, scimark_benchmark: 923.1651,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5741, f_measure: 0.396, kappa: 0.1691, kb_relative_information_score: 17.9167, mean_absolute_error: 0.4184, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.427, predictive_accuracy: 0.4437, prior_entropy: 1.5845, recall: 0.4437, relative_absolute_error: 0.9417, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.4631, root_relative_squared_error: 0.9826, scimark_benchmark: 946.8465,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6869, f_measure: 0.4968, kappa: 0.2544, kb_relative_information_score: 37.4168, mean_absolute_error: 0.3693, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.4974, predictive_accuracy: 0.5033, prior_entropy: 1.5845, recall: 0.5033, relative_absolute_error: 0.8311, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.4586, root_relative_squared_error: 0.9731, scimark_benchmark: 946.8453,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.627, f_measure: 0.4949, kappa: 0.2544, kb_relative_information_score: 48.2788, mean_absolute_error: 0.3311, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.5214, predictive_accuracy: 0.5033, prior_entropy: 1.5845, recall: 0.5033, relative_absolute_error: 0.7453, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.5754, root_relative_squared_error: 1.2209, scimark_benchmark: 926.0215,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7295, f_measure: 0.5807, kappa: 0.3742, kb_relative_information_score: 35.8655, mean_absolute_error: 0.3752, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.5813, predictive_accuracy: 0.5828, prior_entropy: 1.5845, recall: 0.5828, relative_absolute_error: 0.8444, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.4356, root_relative_squared_error: 0.9241, scimark_benchmark: 888.9056,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7042, f_measure: 0.4726, kappa: 0.2152, kb_relative_information_score: 46.8507, mean_absolute_error: 0.3319, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.4747, predictive_accuracy: 0.4768, prior_entropy: 1.5845, recall: 0.4768, relative_absolute_error: 0.7469, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.4648, root_relative_squared_error: 0.9862, scimark_benchmark: 915.1591,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.699, f_measure: 0.5483, kappa: 0.3246, kb_relative_information_score: 48.2661, mean_absolute_error: 0.3377, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.548, predictive_accuracy: 0.5497, prior_entropy: 1.5845, recall: 0.5497, relative_absolute_error: 0.76, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.4757, root_relative_squared_error: 1.0093, scimark_benchmark: 914.0995,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8414, f_measure: 0.6883, kappa: 0.5328, kb_relative_information_score: 84.9261, mean_absolute_error: 0.2134, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.6882, predictive_accuracy: 0.6887, prior_entropy: 1.5845, recall: 0.6887, relative_absolute_error: 0.4803, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.404, root_relative_squared_error: 0.8572, scimark_benchmark: 947.2958,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6131, f_measure: 0.4497, kappa: 0.1874, kb_relative_information_score: 23.8582, mean_absolute_error: 0.4088, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.4595, predictive_accuracy: 0.457, prior_entropy: 1.5845, recall: 0.457, relative_absolute_error: 0.92, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.4683, root_relative_squared_error: 0.9936, scimark_benchmark: 945.4691,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5625, f_measure: 0.4153, kappa: 0.1249, kb_relative_information_score: 30.4307, mean_absolute_error: 0.3885, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.4156, predictive_accuracy: 0.4172, prior_entropy: 1.5845, recall: 0.4172, relative_absolute_error: 0.8744, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.6233, root_relative_squared_error: 1.3225, scimark_benchmark: 913.3439,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5053, f_measure: 0.1764, kb_relative_information_score: 14.4964, mean_absolute_error: 0.4386, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.1186, predictive_accuracy: 0.3444, prior_entropy: 1.5845, recall: 0.3444, relative_absolute_error: 0.9871, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.5389, root_relative_squared_error: 1.1433, scimark_benchmark: 948.9555,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6627, f_measure: 0.5118, kappa: 0.2754, kb_relative_information_score: 36.945, mean_absolute_error: 0.3662, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.5135, predictive_accuracy: 0.5166, prior_entropy: 1.5845, recall: 0.5166, relative_absolute_error: 0.8242, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.4714, root_relative_squared_error: 1.0001, scimark_benchmark: 950.0125,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.66, f_measure: 0.5097, kappa: 0.2763, kb_relative_information_score: 39.4275, mean_absolute_error: 0.3694, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.5182, predictive_accuracy: 0.5166, prior_entropy: 1.5845, recall: 0.5166, relative_absolute_error: 0.8314, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.4704, root_relative_squared_error: 0.9979, scimark_benchmark: 922.0428,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6837, f_measure: 0.5426, kappa: 0.3139, kb_relative_information_score: 42.2465, mean_absolute_error: 0.362, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.543, predictive_accuracy: 0.543, prior_entropy: 1.5845, recall: 0.543, relative_absolute_error: 0.8148, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.4625, root_relative_squared_error: 0.9812, scimark_benchmark: 927.3677,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6961, f_measure: 0.5351, kappa: 0.3047, kb_relative_information_score: 46.1361, mean_absolute_error: 0.3433, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.5356, predictive_accuracy: 0.5364, prior_entropy: 1.5845, recall: 0.5364, relative_absolute_error: 0.7726, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.473, root_relative_squared_error: 1.0036,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6992, f_measure: 0.5546, kappa: 0.3338, kb_relative_information_score: 44.6182, mean_absolute_error: 0.3547, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.5552, predictive_accuracy: 0.5563, prior_entropy: 1.5845, recall: 0.5563, relative_absolute_error: 0.7983, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.4545, root_relative_squared_error: 0.9642, scimark_benchmark: 911.6133,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7178, f_measure: 0.5687, kappa: 0.3546, kb_relative_information_score: 47.4036, mean_absolute_error: 0.3458, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.5699, predictive_accuracy: 0.5695, prior_entropy: 1.5845, recall: 0.5695, relative_absolute_error: 0.7784, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.4446, root_relative_squared_error: 0.9433, scimark_benchmark: 933.3083,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7417, f_measure: 0.5636, kappa: 0.3543, kb_relative_information_score: 36.2417, mean_absolute_error: 0.3738, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.5639, predictive_accuracy: 0.5695, prior_entropy: 1.5845, recall: 0.5695, relative_absolute_error: 0.8414, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.4317, root_relative_squared_error: 0.9159, scimark_benchmark: 882.2431,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5743, f_measure: 0.3952, kappa: 0.1687, kb_relative_information_score: 20.3206, mean_absolute_error: 0.4125, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.4249, predictive_accuracy: 0.4437, prior_entropy: 1.5845, recall: 0.4437, relative_absolute_error: 0.9284, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.467, root_relative_squared_error: 0.9908, scimark_benchmark: 945.2517,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5128, f_measure: 0.3431, kappa: 0.0261, kb_relative_information_score: 16.8123, mean_absolute_error: 0.4327, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.3399, predictive_accuracy: 0.351, prior_entropy: 1.5845, recall: 0.351, relative_absolute_error: 0.9738, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.6578, root_relative_squared_error: 1.3956, scimark_benchmark: 943.7442,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.817, f_measure: 0.6745, kappa: 0.5133, kb_relative_information_score: 66.1403, mean_absolute_error: 0.2871, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.6742, predictive_accuracy: 0.6755, prior_entropy: 1.5845, recall: 0.6755, relative_absolute_error: 0.6461, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.397, root_relative_squared_error: 0.8422, scimark_benchmark: 948.3306,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6753, f_measure: 0.5322, kappa: 0.3059, kb_relative_information_score: 41.6992, mean_absolute_error: 0.3635, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.5385, predictive_accuracy: 0.5364, prior_entropy: 1.5845, recall: 0.5364, relative_absolute_error: 0.8181, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.4641, root_relative_squared_error: 0.9846, scimark_benchmark: 948.5589,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6719, f_measure: 0.5101, kappa: 0.2646, kb_relative_information_score: 39.5189, mean_absolute_error: 0.3679, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.5106, predictive_accuracy: 0.5099, prior_entropy: 1.5845, recall: 0.5099, relative_absolute_error: 0.8281, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.4683, root_relative_squared_error: 0.9935, scimark_benchmark: 950.3485,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7106, f_measure: 0.5357, kappa: 0.3038, kb_relative_information_score: 27.6725, mean_absolute_error: 0.3953, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.5365, predictive_accuracy: 0.5364, prior_entropy: 1.5845, recall: 0.5364, relative_absolute_error: 0.8896, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.4413, root_relative_squared_error: 0.9363,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.653, f_measure: 0.5354, kappa: 0.3056, kb_relative_information_score: 55.216, mean_absolute_error: 0.3091, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.5415, predictive_accuracy: 0.5364, prior_entropy: 1.5845, recall: 0.5364, relative_absolute_error: 0.6956, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.5559, root_relative_squared_error: 1.1795,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5458, f_measure: 0.3776, kappa: 0.2091, kb_relative_information_score: 19.8324, mean_absolute_error: 0.4135, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.3484, predictive_accuracy: 0.4702, prior_entropy: 1.5845, recall: 0.4702, relative_absolute_error: 0.9306, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.4604, root_relative_squared_error: 0.9769,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4861, f_measure: 0.1764, kb_relative_information_score: 0.1105, mean_absolute_error: 0.4444, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.1186, predictive_accuracy: 0.3444, prior_entropy: 1.5845, recall: 0.3444, relative_absolute_error: 1.0002, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.4714, root_relative_squared_error: 1.0002,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6477, f_measure: 0.4824, kappa: 0.2371, kb_relative_information_score: 34.731, mean_absolute_error: 0.3853, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.4933, predictive_accuracy: 0.4901, prior_entropy: 1.5845, recall: 0.4901, relative_absolute_error: 0.8671, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.4684, root_relative_squared_error: 0.9938,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6857, f_measure: 0.491, kappa: 0.2347, kb_relative_information_score: 39.3241, mean_absolute_error: 0.3647, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.4926, predictive_accuracy: 0.4901, prior_entropy: 1.5845, recall: 0.4901, relative_absolute_error: 0.8207, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.4627, root_relative_squared_error: 0.9817,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8168, f_measure: 0.6749, kappa: 0.513, kb_relative_information_score: 65.1261, mean_absolute_error: 0.2909, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.6747, predictive_accuracy: 0.6755, prior_entropy: 1.5845, recall: 0.6755, relative_absolute_error: 0.6546, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.3949, root_relative_squared_error: 0.8378, scimark_benchmark: 943.1009, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6147, f_measure: 0.5375, kappa: 0.3058, kb_relative_information_score: 29.921, mean_absolute_error: 0.3933, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.5513, predictive_accuracy: 0.5364, prior_entropy: 1.5845, recall: 0.5364, relative_absolute_error: 0.8853, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.4624, root_relative_squared_error: 0.981, scimark_benchmark: 937.5117, usercpu_time_millis: 60, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8168, f_measure: 0.6749, kappa: 0.513, kb_relative_information_score: 65.1261, mean_absolute_error: 0.2909, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.6747, predictive_accuracy: 0.6755, prior_entropy: 1.5845, recall: 0.6755, relative_absolute_error: 0.6546, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.3949, root_relative_squared_error: 0.8378, scimark_benchmark: 931.771, usercpu_time_millis: 60, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6677, f_measure: 0.5146, kappa: 0.287, kb_relative_information_score: 19.6077, mean_absolute_error: 0.4139, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.5267, predictive_accuracy: 0.5232, prior_entropy: 1.5845, recall: 0.5232, relative_absolute_error: 0.9316, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.4529, root_relative_squared_error: 0.9609,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6677, f_measure: 0.5146, kappa: 0.287, kb_relative_information_score: 19.6077, mean_absolute_error: 0.4139, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.5267, predictive_accuracy: 0.5232, prior_entropy: 1.5845, recall: 0.5232, relative_absolute_error: 0.9316, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.4529, root_relative_squared_error: 0.9609,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6677, f_measure: 0.5146, kappa: 0.287, kb_relative_information_score: 19.6077, mean_absolute_error: 0.4139, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.5267, predictive_accuracy: 0.5232, prior_entropy: 1.5845, recall: 0.5232, relative_absolute_error: 0.9316, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.4529, root_relative_squared_error: 0.9609,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6677, f_measure: 0.5146, kappa: 0.287, kb_relative_information_score: 19.6077, mean_absolute_error: 0.4139, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.5267, predictive_accuracy: 0.5232, prior_entropy: 1.5845, recall: 0.5232, relative_absolute_error: 0.9316, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.4529, root_relative_squared_error: 0.9609,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6677, f_measure: 0.5146, kappa: 0.287, kb_relative_information_score: 19.6077, mean_absolute_error: 0.4139, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.5267, predictive_accuracy: 0.5232, prior_entropy: 1.5845, recall: 0.5232, relative_absolute_error: 0.9316, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.4529, root_relative_squared_error: 0.9609,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.721, f_measure: 0.5262, kappa: 0.2944, kb_relative_information_score: 40.5857, mean_absolute_error: 0.3622, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.526, predictive_accuracy: 0.5298, prior_entropy: 1.5845, recall: 0.5298, relative_absolute_error: 0.8151, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.4446, root_relative_squared_error: 0.9433,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.721, f_measure: 0.5262, kappa: 0.2944, kb_relative_information_score: 40.5857, mean_absolute_error: 0.3622, mean_prior_absolute_error: 0.4443, number_of_instances: 151, precision: 0.526, predictive_accuracy: 0.5298, prior_entropy: 1.5845, recall: 0.5298, relative_absolute_error: 0.8151, root_mean_prior_squared_error: 0.4713, root_mean_squared_error: 0.4446, root_relative_squared_error: 0.9433,

Metric:

Timeline

Plotting contribution timeline

Leaderboard

Rank Name Top Score Entries Highest rank

Note: The leaderboard ignores resubmissions of previous solutions, as well as parameter variations that do not improve performance.

Challenge

In supervised classification, you are given an input dataset in which instances are labeled with a certain class. The goal is to build a model that predicts the class for future unlabeled instances. The model is evaluated using a train-test procedure, e.g. cross-validation.

To make results by different users comparable, you are given the exact train-test folds to be used, and you need to return at least the predictions generated by your model for each of the test instances. OpenML will use these predictions to calculate a range of evaluation measures on the server.

You can also upload your own evaluation measures, provided that the code for doing so is available from the implementation used. For extremely large datasets, it may be infeasible to upload all predictions. In those cases, you need to compute and provide the evaluations yourself.

Optionally, you can upload the model trained on all the input data. There is no restriction on the file format, but please use a well-known format or PMML.

Given inputs

Expected outputs

evaluations A list of user-defined evaluations of the task as key-value pairs. KeyValue (optional)
model A file containing the model built on all the input data. File (optional)
predictions The desired output format Predictions (optional)

How to submit runs

Using your favorite machine learning environment

Download this task directly in your environment and automatically upload your results

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From your own software

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

OpenML APIs