OpenML
Supervised Classification on diabetes

Supervised Classification on diabetes

Task 37 Supervised Classification diabetes 131653 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: 0.8031, build_cpu_time: 0.0541, build_memory: 875941257.8333, f_measure: 0.761, kappa: 0.4666, kb_relative_information_score: 270.7828, mean_absolute_error: 0.2969, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7604, predictive_accuracy: 0.7656, prior_entropy: 0.9335, recall: 0.7656, relative_absolute_error: 0.6532, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4162, root_relative_squared_error: 0.8732, scimark_benchmark: 908.8705,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6957, build_cpu_time: 0.0159, build_memory: 608816325.9792, f_measure: 0.6665, kappa: 0.2556, kb_relative_information_score: 155.391, mean_absolute_error: 0.3538, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.6633, predictive_accuracy: 0.6732, prior_entropy: 0.9335, recall: 0.6732, relative_absolute_error: 0.7784, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4953, root_relative_squared_error: 1.0391, scimark_benchmark: 929.5397,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7452, build_cpu_time: 0.19, build_memory: 215704356.6667, f_measure: 0.6841, kappa: 0.3029, kb_relative_information_score: 215.5944, mean_absolute_error: 0.3133, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.6833, predictive_accuracy: 0.6849, prior_entropy: 0.9335, recall: 0.6849, relative_absolute_error: 0.6894, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.5275, root_relative_squared_error: 1.1067, scimark_benchmark: 916.8903,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8279, build_cpu_time: 0.2841, build_memory: 1393185671.6563, f_measure: 0.7647, kappa: 0.4763, kb_relative_information_score: 257.6479, mean_absolute_error: 0.3057, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7637, predictive_accuracy: 0.7682, prior_entropy: 0.9335, recall: 0.7682, relative_absolute_error: 0.6726, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3989, root_relative_squared_error: 0.837, scimark_benchmark: 937.5757,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7093, build_cpu_time: 0.0332, build_memory: 768952559.6042, f_measure: 0.6605, kappa: 0.2463, kb_relative_information_score: 170.6991, mean_absolute_error: 0.3421, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.658, predictive_accuracy: 0.6641, prior_entropy: 0.9335, recall: 0.6641, relative_absolute_error: 0.7526, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.5074, root_relative_squared_error: 1.0645, scimark_benchmark: 929.5397,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7413, f_measure: 0.7412, kappa: 0.426, kb_relative_information_score: 315.3666, mean_absolute_error: 0.2575, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7398, predictive_accuracy: 0.7435, prior_entropy: 0.9335, recall: 0.7435, relative_absolute_error: 0.5665, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.504, root_relative_squared_error: 1.0574, scimark_benchmark: 876.8277, usercpu_time_millis: 1520, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 1480,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.808, f_measure: 0.7378, kappa: 0.4122, kb_relative_information_score: 129.2411, mean_absolute_error: 0.3828, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7386, predictive_accuracy: 0.7461, prior_entropy: 0.9335, recall: 0.7461, relative_absolute_error: 0.8422, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4202, root_relative_squared_error: 0.8816, scimark_benchmark: 929.566, usercpu_time_millis: 1110, usercpu_time_millis_training: 1110,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7443, f_measure: 0.7379, kappa: 0.4147, kb_relative_information_score: 241.2932, mean_absolute_error: 0.3145, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7369, predictive_accuracy: 0.7435, prior_entropy: 0.9335, recall: 0.7435, relative_absolute_error: 0.692, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4462, root_relative_squared_error: 0.9362, scimark_benchmark: 918.4924, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.5134, kb_relative_information_score: 154.1008, mean_absolute_error: 0.349, 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: 0.7678, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.5907, root_relative_squared_error: 1.2394, scimark_benchmark: 929.0255,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7896, build_cpu_time: 0.0695, build_memory: 876226893.2396, f_measure: 0.7577, kappa: 0.455, kb_relative_information_score: 254.7996, mean_absolute_error: 0.3129, 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: 0.6885, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4167, root_relative_squared_error: 0.8743, scimark_benchmark: 940.159,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7302, f_measure: 0.7642, kappa: 0.4744, kb_relative_information_score: 360.1638, mean_absolute_error: 0.2318, 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: 0.51, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4814, root_relative_squared_error: 1.01, scimark_benchmark: 942.2963, usercpu_time_millis: 50, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8172, f_measure: 0.7653, kappa: 0.4782, kb_relative_information_score: 262.1315, mean_absolute_error: 0.3009, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7642, predictive_accuracy: 0.7682, prior_entropy: 0.9335, recall: 0.7682, relative_absolute_error: 0.6621, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4075, root_relative_squared_error: 0.8549, scimark_benchmark: 915.2795,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7729, f_measure: 0.7087, kappa: 0.3571, kb_relative_information_score: 264.1062, mean_absolute_error: 0.286, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7079, predictive_accuracy: 0.7096, prior_entropy: 0.9335, recall: 0.7096, relative_absolute_error: 0.6292, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4925, root_relative_squared_error: 1.0332, scimark_benchmark: 930.32, usercpu_time_millis: 640, usercpu_time_millis_training: 640,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7693, f_measure: 0.7151, kappa: 0.3668, kb_relative_information_score: 284.5913, mean_absolute_error: 0.2747, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7132, predictive_accuracy: 0.7188, prior_entropy: 0.9335, recall: 0.7188, relative_absolute_error: 0.6044, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.505, root_relative_squared_error: 1.0594, scimark_benchmark: 923.3111, usercpu_time_millis: 1230, usercpu_time_millis_training: 1230,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7332, f_measure: 0.7427, kappa: 0.4278, kb_relative_information_score: 319.6347, mean_absolute_error: 0.255, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7412, predictive_accuracy: 0.7461, prior_entropy: 0.9335, recall: 0.7461, relative_absolute_error: 0.5611, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.5015, root_relative_squared_error: 1.0522, scimark_benchmark: 1160.1034, usercpu_time_millis: 3790, usercpu_time_millis_testing: 130, usercpu_time_millis_training: 3660,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.497, f_measure: 0.5134, kb_relative_information_score: -0.1051, 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: 938.9865,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8084, f_measure: 0.7347, kappa: 0.4059, kb_relative_information_score: 252.6102, mean_absolute_error: 0.3051, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7346, predictive_accuracy: 0.7422, prior_entropy: 0.9335, recall: 0.7422, relative_absolute_error: 0.6712, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4201, root_relative_squared_error: 0.8813, scimark_benchmark: 934.5243, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.5134, kb_relative_information_score: 154.1008, mean_absolute_error: 0.349, 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: 0.7678, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.5907, root_relative_squared_error: 1.2394, scimark_benchmark: 915.2795, usercpu_time_millis: 680, usercpu_time_millis_testing: 60, usercpu_time_millis_training: 620,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8016, f_measure: 0.7442, kappa: 0.4313, kb_relative_information_score: 281.2266, mean_absolute_error: 0.2845, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7427, predictive_accuracy: 0.7474, prior_entropy: 0.9335, recall: 0.7474, relative_absolute_error: 0.626, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4294, root_relative_squared_error: 0.9008, scimark_benchmark: 923.9763, usercpu_time_millis: 320, usercpu_time_millis_training: 320,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4764, f_measure: 0.2263, kappa: -0.034, kb_relative_information_score: -381.6627, mean_absolute_error: 0.6536, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.4297, predictive_accuracy: 0.3464, prior_entropy: 0.9335, recall: 0.3464, relative_absolute_error: 1.4382, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.8085, root_relative_squared_error: 1.6962, scimark_benchmark: 889.9023, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7975, f_measure: 0.7282, kappa: 0.3897, kb_relative_information_score: 226.6015, mean_absolute_error: 0.3232, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7299, predictive_accuracy: 0.7383, prior_entropy: 0.9335, recall: 0.7383, relative_absolute_error: 0.711, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.419, root_relative_squared_error: 0.879, scimark_benchmark: 929.0255, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7828, f_measure: 0.7254, kappa: 0.3891, kb_relative_information_score: 236.827, mean_absolute_error: 0.3103, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7236, predictive_accuracy: 0.7292, prior_entropy: 0.9335, recall: 0.7292, relative_absolute_error: 0.6827, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4349, root_relative_squared_error: 0.9124, scimark_benchmark: 902.4773, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.742, f_measure: 0.7418, kappa: 0.4264, kb_relative_information_score: 320.5221, mean_absolute_error: 0.2544, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7403, predictive_accuracy: 0.7448, prior_entropy: 0.9335, recall: 0.7448, relative_absolute_error: 0.5597, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4977, root_relative_squared_error: 1.0442, scimark_benchmark: 940.2751, usercpu_time_millis: 740, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 720,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.825, build_cpu_time: 0.681, build_memory: 1476105315.5833, f_measure: 0.7534, kappa: 0.4537, kb_relative_information_score: 345.3729, mean_absolute_error: 0.2397, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7522, predictive_accuracy: 0.7552, prior_entropy: 0.9335, recall: 0.7552, relative_absolute_error: 0.5273, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4656, root_relative_squared_error: 0.9768, scimark_benchmark: 941.5665,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8166, build_cpu_time: 2.0639, build_memory: 272949030.5833, f_measure: 0.7615, kappa: 0.472, kb_relative_information_score: 345.9181, mean_absolute_error: 0.2403, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7605, predictive_accuracy: 0.763, prior_entropy: 0.9335, recall: 0.763, relative_absolute_error: 0.5287, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.47, root_relative_squared_error: 0.9861, scimark_benchmark: 938.0657,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7924, build_cpu_time: 4.6814, build_memory: 595546328.6979, f_measure: 0.7579, kappa: 0.4648, kb_relative_information_score: 340.3045, mean_absolute_error: 0.2437, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.757, predictive_accuracy: 0.7591, prior_entropy: 0.9335, recall: 0.7591, relative_absolute_error: 0.5361, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4781, root_relative_squared_error: 1.003, scimark_benchmark: 897.921,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8351, build_cpu_time: 11.7798, build_memory: 88531679.3542, f_measure: 0.7638, kappa: 0.4748, kb_relative_information_score: 270.6885, mean_absolute_error: 0.2971, 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: 0.6538, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3964, root_relative_squared_error: 0.8317, scimark_benchmark: 938.259,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8331, build_cpu_time: 21.4846, build_memory: 3408018626.7917, f_measure: 0.76, kappa: 0.4664, kb_relative_information_score: 268.1478, mean_absolute_error: 0.2987, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7588, predictive_accuracy: 0.763, prior_entropy: 0.9335, recall: 0.763, relative_absolute_error: 0.6573, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3969, root_relative_squared_error: 0.8327, scimark_benchmark: 945.8425,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8265, build_cpu_time: 0.4004, build_memory: 1578254280.4167, f_measure: 0.7553, kappa: 0.4552, kb_relative_information_score: 262.8495, mean_absolute_error: 0.3019, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7542, predictive_accuracy: 0.7591, prior_entropy: 0.9335, recall: 0.7591, relative_absolute_error: 0.6642, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4002, root_relative_squared_error: 0.8397, scimark_benchmark: 910.6427,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7443, build_cpu_time: 0.0076, build_memory: 94950925.6563, f_measure: 0.7379, kappa: 0.4147, kb_relative_information_score: 241.2932, mean_absolute_error: 0.3145, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7369, predictive_accuracy: 0.7435, prior_entropy: 0.9335, recall: 0.7435, relative_absolute_error: 0.692, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4462, root_relative_squared_error: 0.9362, scimark_benchmark: 938.5552,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7443, build_cpu_time: 0.0111, build_memory: 316845425.1563, f_measure: 0.7379, kappa: 0.4147, kb_relative_information_score: 241.2932, mean_absolute_error: 0.3145, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7369, predictive_accuracy: 0.7435, prior_entropy: 0.9335, recall: 0.7435, relative_absolute_error: 0.692, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4462, root_relative_squared_error: 0.9362, scimark_benchmark: 941.8538,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7443, build_cpu_time: 0.0234, build_memory: 28783375.7917, f_measure: 0.7379, kappa: 0.4147, kb_relative_information_score: 241.2932, mean_absolute_error: 0.3145, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7369, predictive_accuracy: 0.7435, prior_entropy: 0.9335, recall: 0.7435, relative_absolute_error: 0.692, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4462, root_relative_squared_error: 0.9362, scimark_benchmark: 943.1794,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.826, f_measure: 0.7548, kappa: 0.4533, kb_relative_information_score: 264.2527, mean_absolute_error: 0.3002, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7538, predictive_accuracy: 0.7591, prior_entropy: 0.9335, recall: 0.7591, relative_absolute_error: 0.6606, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4013, root_relative_squared_error: 0.8419,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.826, build_cpu_time: 0.1864, build_memory: 469541571.375, f_measure: 0.7548, kappa: 0.4533, kb_relative_information_score: 264.2527, mean_absolute_error: 0.3002, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7538, predictive_accuracy: 0.7591, prior_entropy: 0.9335, recall: 0.7591, relative_absolute_error: 0.6606, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4013, root_relative_squared_error: 0.8419, scimark_benchmark: 945.7863,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7576, f_measure: 0.7619, kappa: 0.4647, kb_relative_information_score: 356.7322, mean_absolute_error: 0.235, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7678, predictive_accuracy: 0.7721, prior_entropy: 0.9335, recall: 0.7721, relative_absolute_error: 0.517, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4546, root_relative_squared_error: 0.9538, scimark_benchmark: 944.7724,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8142, f_measure: 0.7556, kappa: 0.4562, kb_relative_information_score: 276.4553, mean_absolute_error: 0.2915, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7544, predictive_accuracy: 0.7591, prior_entropy: 0.9335, recall: 0.7591, relative_absolute_error: 0.6414, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4096, root_relative_squared_error: 0.8594, scimark_benchmark: 947.8538,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7503, f_measure: 0.7383, kappa: 0.4192, kb_relative_information_score: 313.7497, mean_absolute_error: 0.2583, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7368, predictive_accuracy: 0.7409, prior_entropy: 0.9335, recall: 0.7409, relative_absolute_error: 0.5682, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.5016, root_relative_squared_error: 1.0524, scimark_benchmark: 944.4584,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.83, build_cpu_time: 0.0093, build_memory: 654836833.3021, f_measure: 0.7692, kappa: 0.4829, kb_relative_information_score: 255.151, mean_absolute_error: 0.3101, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.771, predictive_accuracy: 0.776, prior_entropy: 0.9335, recall: 0.776, relative_absolute_error: 0.6823, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3963, root_relative_squared_error: 0.8315, scimark_benchmark: 945.7844,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7729, build_cpu_time: 0.6062, build_memory: 222703515.9271, f_measure: 0.7087, kappa: 0.3571, kb_relative_information_score: 264.1062, mean_absolute_error: 0.286, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7079, predictive_accuracy: 0.7096, prior_entropy: 0.9335, recall: 0.7096, relative_absolute_error: 0.6292, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4925, root_relative_squared_error: 1.0332, scimark_benchmark: 937.4026,

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