OpenML
Supervised Classification on heart-statlog

Supervised Classification on heart-statlog

Task 52 Supervised Classification heart-statlog 887 runs submitted
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  • basic mythbusting mythbusting_1 study_1 study_107 study_123 study_15 study_20 study_29 study_30 study_41 study_50 study_7 under100k under1m
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.864, f_measure: 0.7989, kappa: 0.5916, kb_relative_information_score: 131.0292, mean_absolute_error: 0.2652, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.8, predictive_accuracy: 0.8, prior_entropy: 0.9912, recall: 0.8, relative_absolute_error: 0.5369, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.3809, root_relative_squared_error: 0.7666, scimark_benchmark: 944.3741,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.3968, kb_relative_information_score: 25.6977, mean_absolute_error: 0.4444, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.3086, predictive_accuracy: 0.5556, prior_entropy: 0.9912, recall: 0.5556, relative_absolute_error: 0.8999, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.6667, root_relative_squared_error: 1.3416, scimark_benchmark: 948.1653,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7892, f_measure: 0.7812, kappa: 0.5561, kb_relative_information_score: 131.1587, mean_absolute_error: 0.2644, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.7904, predictive_accuracy: 0.7852, prior_entropy: 0.9912, recall: 0.7852, relative_absolute_error: 0.5353, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.4243, root_relative_squared_error: 0.8538, scimark_benchmark: 948.1267,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8983, f_measure: 0.8291, kappa: 0.6533, kb_relative_information_score: 152.0919, mean_absolute_error: 0.2265, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.8294, predictive_accuracy: 0.8296, prior_entropy: 0.9912, recall: 0.8296, relative_absolute_error: 0.4586, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.3548, root_relative_squared_error: 0.7141, scimark_benchmark: 933.2544,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8626, f_measure: 0.8022, kappa: 0.5981, kb_relative_information_score: 133.3225, mean_absolute_error: 0.2586, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.8045, predictive_accuracy: 0.8037, prior_entropy: 0.9912, recall: 0.8037, relative_absolute_error: 0.5236, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.3849, root_relative_squared_error: 0.7745, scimark_benchmark: 920.5212,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8304, f_measure: 0.8329, kappa: 0.6611, kb_relative_information_score: 137.4394, mean_absolute_error: 0.2613, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.8331, predictive_accuracy: 0.8333, prior_entropy: 0.9912, recall: 0.8333, relative_absolute_error: 0.5291, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.3754, root_relative_squared_error: 0.7555, scimark_benchmark: 920.9515,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7992, f_measure: 0.8057, kappa: 0.6054, kb_relative_information_score: 164.1155, mean_absolute_error: 0.1926, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.8085, predictive_accuracy: 0.8074, prior_entropy: 0.9912, recall: 0.8074, relative_absolute_error: 0.39, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.4389, root_relative_squared_error: 0.8832, scimark_benchmark: 919.7154,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.848, f_measure: 0.7848, kappa: 0.5635, kb_relative_information_score: 134.0948, mean_absolute_error: 0.2537, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.7847, predictive_accuracy: 0.7852, prior_entropy: 0.9912, recall: 0.7852, relative_absolute_error: 0.5138, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.3995, root_relative_squared_error: 0.804,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7961, f_measure: 0.7505, kappa: 0.497, kb_relative_information_score: 125.9746, mean_absolute_error: 0.2621, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.7735, predictive_accuracy: 0.7593, prior_entropy: 0.9912, recall: 0.7593, relative_absolute_error: 0.5307, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.4414, root_relative_squared_error: 0.8883, scimark_benchmark: 946.5242,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7583, f_measure: 0.7553, kappa: 0.5042, kb_relative_information_score: 133.9175, mean_absolute_error: 0.2495, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.7552, predictive_accuracy: 0.7556, prior_entropy: 0.9912, recall: 0.7556, relative_absolute_error: 0.5052, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.4702, root_relative_squared_error: 0.9463, scimark_benchmark: 943.4476,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7939, f_measure: 0.8002, kappa: 0.5957, kb_relative_information_score: 126.7878, mean_absolute_error: 0.2779, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.8004, predictive_accuracy: 0.8, prior_entropy: 0.9912, recall: 0.8, relative_absolute_error: 0.5627, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.4051, root_relative_squared_error: 0.8153, scimark_benchmark: 949.9775,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8891, f_measure: 0.815, kappa: 0.6256, kb_relative_information_score: 151.1045, mean_absolute_error: 0.2253, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.8152, predictive_accuracy: 0.8148, prior_entropy: 0.9912, recall: 0.8148, relative_absolute_error: 0.4561, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.3682, root_relative_squared_error: 0.741, scimark_benchmark: 947.9738,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7751, f_measure: 0.7475, kappa: 0.4877, kb_relative_information_score: 96.8526, mean_absolute_error: 0.3322, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.7547, predictive_accuracy: 0.7519, prior_entropy: 0.9912, recall: 0.7519, relative_absolute_error: 0.6726, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.4314, root_relative_squared_error: 0.8682, scimark_benchmark: 948.556,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5167, f_measure: 0.4293, kappa: 0.0369, kb_relative_information_score: 33.8399, mean_absolute_error: 0.4296, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.7577, predictive_accuracy: 0.5704, prior_entropy: 0.9912, recall: 0.5704, relative_absolute_error: 0.8699, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.6555, root_relative_squared_error: 1.3191, scimark_benchmark: 916.2133,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8051, f_measure: 0.7854, kappa: 0.5657, kb_relative_information_score: 133.0096, mean_absolute_error: 0.2607, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.7856, predictive_accuracy: 0.7852, prior_entropy: 0.9912, recall: 0.7852, relative_absolute_error: 0.5278, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.416, root_relative_squared_error: 0.8371, scimark_benchmark: 948.1877,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8243, f_measure: 0.7755, kappa: 0.5439, kb_relative_information_score: 130.4597, mean_absolute_error: 0.2607, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.7788, predictive_accuracy: 0.7778, prior_entropy: 0.9912, recall: 0.7778, relative_absolute_error: 0.5278, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.4156, root_relative_squared_error: 0.8364, scimark_benchmark: 922.6369,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7383, f_measure: 0.7455, kappa: 0.4831, kb_relative_information_score: 131.5466, mean_absolute_error: 0.2519, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.7483, predictive_accuracy: 0.7481, prior_entropy: 0.9912, recall: 0.7481, relative_absolute_error: 0.51, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.5018, root_relative_squared_error: 1.01, scimark_benchmark: 944.4615,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7583, f_measure: 0.7553, kappa: 0.5042, kb_relative_information_score: 133.9175, mean_absolute_error: 0.2495, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.7552, predictive_accuracy: 0.7556, prior_entropy: 0.9912, recall: 0.7556, relative_absolute_error: 0.5052, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.4702, root_relative_squared_error: 0.9463, scimark_benchmark: 946.7656,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.66, f_measure: 0.6656, kappa: 0.3342, kb_relative_information_score: 96.9422, mean_absolute_error: 0.3148, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.7026, predictive_accuracy: 0.6852, prior_entropy: 0.9912, recall: 0.6852, relative_absolute_error: 0.6374, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.5611, root_relative_squared_error: 1.1292, scimark_benchmark: 928.1692,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.3968, kb_relative_information_score: 25.6977, mean_absolute_error: 0.4444, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.3086, predictive_accuracy: 0.5556, prior_entropy: 0.9912, recall: 0.5556, relative_absolute_error: 0.8999, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.6667, root_relative_squared_error: 1.3416,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7583, f_measure: 0.7553, kappa: 0.5042, kb_relative_information_score: 133.9175, mean_absolute_error: 0.2495, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.7552, predictive_accuracy: 0.7556, prior_entropy: 0.9912, recall: 0.7556, relative_absolute_error: 0.5052, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.4702, root_relative_squared_error: 0.9463, scimark_benchmark: 910.1692,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.66, f_measure: 0.6656, kappa: 0.3342, kb_relative_information_score: 96.9422, mean_absolute_error: 0.3148, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.7026, predictive_accuracy: 0.6852, prior_entropy: 0.9912, recall: 0.6852, relative_absolute_error: 0.6374, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.5611, root_relative_squared_error: 1.1292, scimark_benchmark: 948.4896,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.725, f_measure: 0.733, kappa: 0.458, kb_relative_information_score: 125.44, mean_absolute_error: 0.263, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.7383, predictive_accuracy: 0.737, prior_entropy: 0.9912, recall: 0.737, relative_absolute_error: 0.5325, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.5128, root_relative_squared_error: 1.032, scimark_benchmark: 920.007,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.765, f_measure: 0.7697, kappa: 0.5327, kb_relative_information_score: 143.76, mean_absolute_error: 0.2296, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.7698, predictive_accuracy: 0.7704, prior_entropy: 0.9912, recall: 0.7704, relative_absolute_error: 0.465, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.4792, root_relative_squared_error: 0.9644, scimark_benchmark: 945.7693,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.885, f_measure: 0.8248, kappa: 0.6442, kb_relative_information_score: 124.2775, mean_absolute_error: 0.2837, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.8265, predictive_accuracy: 0.8259, prior_entropy: 0.9912, recall: 0.8259, relative_absolute_error: 0.5744, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.3655, root_relative_squared_error: 0.7356, scimark_benchmark: 913.1395,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8903, f_measure: 0.8107, kappa: 0.6159, kb_relative_information_score: 124.1124, mean_absolute_error: 0.2841, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.8108, predictive_accuracy: 0.8111, prior_entropy: 0.9912, recall: 0.8111, relative_absolute_error: 0.5753, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.3636, root_relative_squared_error: 0.7317, scimark_benchmark: 929.791,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6925, f_measure: 0.7221, kappa: 0.437, kb_relative_information_score: 70.8179, mean_absolute_error: 0.3814, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.722, predictive_accuracy: 0.7222, prior_entropy: 0.9912, recall: 0.7222, relative_absolute_error: 0.7723, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.4501, root_relative_squared_error: 0.9059, scimark_benchmark: 918.0314,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8831, f_measure: 0.7998, kappa: 0.5943, kb_relative_information_score: 151.1689, mean_absolute_error: 0.2226, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.7997, predictive_accuracy: 0.8, prior_entropy: 0.9912, recall: 0.8, relative_absolute_error: 0.4508, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.3828, root_relative_squared_error: 0.7704,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5083, f_measure: 0.4133, kappa: 0.0185, kb_relative_information_score: 29.7688, mean_absolute_error: 0.437, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.7554, predictive_accuracy: 0.563, prior_entropy: 0.9912, recall: 0.563, relative_absolute_error: 0.8849, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.6611, root_relative_squared_error: 1.3304, scimark_benchmark: 913.3902,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8144, f_measure: 0.7807, kappa: 0.5549, kb_relative_information_score: 130.1217, mean_absolute_error: 0.2599, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.781, predictive_accuracy: 0.7815, prior_entropy: 0.9912, recall: 0.7815, relative_absolute_error: 0.5263, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.4252, root_relative_squared_error: 0.8557, scimark_benchmark: 948.5183,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8053, f_measure: 0.8032, kappa: 0.6008, kb_relative_information_score: 126.9672, mean_absolute_error: 0.2785, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.8033, predictive_accuracy: 0.8037, prior_entropy: 0.9912, recall: 0.8037, relative_absolute_error: 0.564, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.401, root_relative_squared_error: 0.8069, scimark_benchmark: 944.9221,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7992, f_measure: 0.8032, kappa: 0.6008, kb_relative_information_score: 162.08, mean_absolute_error: 0.1963, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.8033, predictive_accuracy: 0.8037, prior_entropy: 0.9912, recall: 0.8037, relative_absolute_error: 0.3975, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.4431, root_relative_squared_error: 0.8916, scimark_benchmark: 932.0296,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7183, f_measure: 0.7221, kappa: 0.437, kb_relative_information_score: 117.2977, mean_absolute_error: 0.2778, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.722, predictive_accuracy: 0.7222, prior_entropy: 0.9912, recall: 0.7222, relative_absolute_error: 0.5624, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.527, root_relative_squared_error: 1.0607, scimark_benchmark: 949.147,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8744, f_measure: 0.8183, kappa: 0.6316, kb_relative_information_score: 140.4074, mean_absolute_error: 0.248, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.8182, predictive_accuracy: 0.8185, prior_entropy: 0.9912, recall: 0.8185, relative_absolute_error: 0.5022, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.3765, root_relative_squared_error: 0.7578, scimark_benchmark: 918.9251,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8358, f_measure: 0.8402, kappa: 0.6756, kb_relative_information_score: 182.4355, mean_absolute_error: 0.1593, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.8407, predictive_accuracy: 0.8407, prior_entropy: 0.9912, recall: 0.8407, relative_absolute_error: 0.3225, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.3991, root_relative_squared_error: 0.8031, scimark_benchmark: 948.7476,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8325, f_measure: 0.8365, kappa: 0.6683, kb_relative_information_score: 180.4, mean_absolute_error: 0.163, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.8369, predictive_accuracy: 0.837, prior_entropy: 0.9912, recall: 0.837, relative_absolute_error: 0.33, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.4037, root_relative_squared_error: 0.8124, scimark_benchmark: 923.5426,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5875, f_measure: 0.5613, kappa: 0.1892, kb_relative_information_score: 66.4088, mean_absolute_error: 0.3704, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.706, predictive_accuracy: 0.6296, prior_entropy: 0.9912, recall: 0.6296, relative_absolute_error: 0.7499, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.6086, root_relative_squared_error: 1.2247, scimark_benchmark: 948.8715,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8807, f_measure: 0.7994, kappa: 0.593, kb_relative_information_score: 129.7431, mean_absolute_error: 0.2699, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.7996, predictive_accuracy: 0.8, prior_entropy: 0.9912, recall: 0.8, relative_absolute_error: 0.5465, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.3681, root_relative_squared_error: 0.7408, scimark_benchmark: 912.1487,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8242, f_measure: 0.8315, kappa: 0.6577, kb_relative_information_score: 178.3644, mean_absolute_error: 0.1667, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.8365, predictive_accuracy: 0.8333, prior_entropy: 0.9912, recall: 0.8333, relative_absolute_error: 0.3375, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.4082, root_relative_squared_error: 0.8216, scimark_benchmark: 947.5579,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7767, f_measure: 0.7809, kappa: 0.5556, kb_relative_information_score: 149.8666, mean_absolute_error: 0.2185, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.781, predictive_accuracy: 0.7815, prior_entropy: 0.9912, recall: 0.7815, relative_absolute_error: 0.4425, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.4675, root_relative_squared_error: 0.9407, scimark_benchmark: 946.2933,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8053, f_measure: 0.8032, kappa: 0.6008, kb_relative_information_score: 126.9672, mean_absolute_error: 0.2785, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.8033, predictive_accuracy: 0.8037, prior_entropy: 0.9912, recall: 0.8037, relative_absolute_error: 0.564, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.401, root_relative_squared_error: 0.8069, scimark_benchmark: 882.8637,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7861, f_measure: 0.7843, kappa: 0.5621, kb_relative_information_score: 140.5144, mean_absolute_error: 0.2433, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.7848, predictive_accuracy: 0.7852, prior_entropy: 0.9912, recall: 0.7852, relative_absolute_error: 0.4927, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.4297, root_relative_squared_error: 0.8648, scimark_benchmark: 2010.0595,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8793, f_measure: 0.7801, kappa: 0.5534, kb_relative_information_score: 123.3802, mean_absolute_error: 0.2837, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.7814, predictive_accuracy: 0.7815, prior_entropy: 0.9912, recall: 0.7815, relative_absolute_error: 0.5745, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.3697, root_relative_squared_error: 0.744, scimark_benchmark: 2020.264,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8193, f_measure: 0.7486, kappa: 0.4894, kb_relative_information_score: 110.3302, mean_absolute_error: 0.303, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.753, predictive_accuracy: 0.7519, prior_entropy: 0.9912, recall: 0.7519, relative_absolute_error: 0.6134, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.4184, root_relative_squared_error: 0.842, scimark_benchmark: 1982.2698,

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