OpenML
Supervised Classification on electricity

Supervised Classification on electricity

Task 146012 Supervised Classification electricity 25374 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, f_measure: 0.4204, kb_relative_information_score: 0.0359, mean_absolute_error: 0.4886, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.3311, predictive_accuracy: 0.5755, prior_entropy: 0.9835, recall: 0.5755, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4943, root_relative_squared_error: 1, scimark_benchmark: 1290.4116, usercpu_time_millis: 2.236, usercpu_time_millis_testing: 0.039, usercpu_time_millis_training: 2.197,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, f_measure: 0.4204, kb_relative_information_score: 0.0359, mean_absolute_error: 0.4886, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.3311, predictive_accuracy: 0.5755, prior_entropy: 0.9835, recall: 0.5755, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4943, root_relative_squared_error: 1, scimark_benchmark: 1305.0757, usercpu_time_millis: 1.326, usercpu_time_millis_testing: 0.038, usercpu_time_millis_training: 1.288,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7283, f_measure: 0.7486, kappa: 0.484, kb_relative_information_score: 13195.7191, mean_absolute_error: 0.3659, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.7651, predictive_accuracy: 0.7574, prior_entropy: 0.9835, recall: 0.7574, relative_absolute_error: 0.7488, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4277, root_relative_squared_error: 0.8653, scimark_benchmark: 1300.9642, usercpu_time_millis: 1.786, usercpu_time_millis_testing: 0.052, usercpu_time_millis_training: 1.734,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, f_measure: 0.4204, kb_relative_information_score: 0.0359, mean_absolute_error: 0.4886, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.3311, predictive_accuracy: 0.5755, prior_entropy: 0.9835, recall: 0.5755, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4943, root_relative_squared_error: 1, scimark_benchmark: 1288.083, usercpu_time_millis: 1.499, usercpu_time_millis_testing: 0.039, usercpu_time_millis_training: 1.46,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7283, f_measure: 0.7486, kappa: 0.484, kb_relative_information_score: 13195.7191, mean_absolute_error: 0.3659, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.7651, predictive_accuracy: 0.7574, prior_entropy: 0.9835, recall: 0.7574, relative_absolute_error: 0.7488, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4277, root_relative_squared_error: 0.8653, scimark_benchmark: 1272.4654, usercpu_time_millis: 1.866, usercpu_time_millis_testing: 0.05, usercpu_time_millis_training: 1.816,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, f_measure: 0.4204, kb_relative_information_score: 0.0359, mean_absolute_error: 0.4886, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.3311, predictive_accuracy: 0.5755, prior_entropy: 0.9835, recall: 0.5755, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4943, root_relative_squared_error: 1, scimark_benchmark: 1299.2371, usercpu_time_millis: 1.527, usercpu_time_millis_testing: 0.039, usercpu_time_millis_training: 1.488,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7283, f_measure: 0.7486, kappa: 0.484, kb_relative_information_score: 13195.7191, mean_absolute_error: 0.3659, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.7651, predictive_accuracy: 0.7574, prior_entropy: 0.9835, recall: 0.7574, relative_absolute_error: 0.7488, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4277, root_relative_squared_error: 0.8653, scimark_benchmark: 1299.5171, usercpu_time_millis: 2.168, usercpu_time_millis_testing: 0.047, usercpu_time_millis_training: 2.121,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7283, f_measure: 0.7486, kappa: 0.484, kb_relative_information_score: 13195.7191, mean_absolute_error: 0.3659, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.7651, predictive_accuracy: 0.7574, prior_entropy: 0.9835, recall: 0.7574, relative_absolute_error: 0.7488, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4277, root_relative_squared_error: 0.8653, scimark_benchmark: 1301.1061, usercpu_time_millis: 1.668, usercpu_time_millis_testing: 0.052, usercpu_time_millis_training: 1.616,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7283, f_measure: 0.7486, kappa: 0.484, kb_relative_information_score: 13195.7191, mean_absolute_error: 0.3659, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.7651, predictive_accuracy: 0.7574, prior_entropy: 0.9835, recall: 0.7574, relative_absolute_error: 0.7488, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4277, root_relative_squared_error: 0.8653, scimark_benchmark: 1305.5585, usercpu_time_millis: 1.579, usercpu_time_millis_testing: 0.056, usercpu_time_millis_training: 1.523,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, f_measure: 0.4204, kb_relative_information_score: 0.0359, mean_absolute_error: 0.4886, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.3311, predictive_accuracy: 0.5755, prior_entropy: 0.9835, recall: 0.5755, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4943, root_relative_squared_error: 1, scimark_benchmark: 1306.4426, usercpu_time_millis: 1.129, usercpu_time_millis_testing: 0.039, usercpu_time_millis_training: 1.09,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7283, f_measure: 0.7486, kappa: 0.484, kb_relative_information_score: 13195.7191, mean_absolute_error: 0.3659, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.7651, predictive_accuracy: 0.7574, prior_entropy: 0.9835, recall: 0.7574, relative_absolute_error: 0.7488, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4277, root_relative_squared_error: 0.8653, scimark_benchmark: 1296.4217, usercpu_time_millis: 1.491, usercpu_time_millis_testing: 0.054, usercpu_time_millis_training: 1.437,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, f_measure: 0.4204, kb_relative_information_score: 0.0359, mean_absolute_error: 0.4886, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.3311, predictive_accuracy: 0.5755, prior_entropy: 0.9835, recall: 0.5755, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4943, root_relative_squared_error: 1, scimark_benchmark: 1283.7114, usercpu_time_millis: 1.049, usercpu_time_millis_testing: 0.035, usercpu_time_millis_training: 1.014,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, f_measure: 0.4204, kb_relative_information_score: 0.0359, mean_absolute_error: 0.4886, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.3311, predictive_accuracy: 0.5755, prior_entropy: 0.9835, recall: 0.5755, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4943, root_relative_squared_error: 1, scimark_benchmark: 1304.3367, usercpu_time_millis: 1.057, usercpu_time_millis_testing: 0.034, usercpu_time_millis_training: 1.023,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7283, f_measure: 0.7486, kappa: 0.484, kb_relative_information_score: 13195.7191, mean_absolute_error: 0.3659, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.7651, predictive_accuracy: 0.7574, prior_entropy: 0.9835, recall: 0.7574, relative_absolute_error: 0.7488, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4277, root_relative_squared_error: 0.8653, scimark_benchmark: 1302.4571, usercpu_time_millis: 2.027, usercpu_time_millis_testing: 0.064, usercpu_time_millis_training: 1.963,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, f_measure: 0.4204, kb_relative_information_score: 0.0359, mean_absolute_error: 0.4886, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.3311, predictive_accuracy: 0.5755, prior_entropy: 0.9835, recall: 0.5755, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4943, root_relative_squared_error: 1, scimark_benchmark: 1302.9611, usercpu_time_millis: 1.242, usercpu_time_millis_testing: 0.039, usercpu_time_millis_training: 1.203,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, f_measure: 0.4204, kb_relative_information_score: 0.0359, mean_absolute_error: 0.4886, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.3311, predictive_accuracy: 0.5755, prior_entropy: 0.9835, recall: 0.5755, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4943, root_relative_squared_error: 1, scimark_benchmark: 1299.3948, usercpu_time_millis: 1.187, usercpu_time_millis_testing: 0.05, usercpu_time_millis_training: 1.137,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7283, f_measure: 0.7486, kappa: 0.484, kb_relative_information_score: 13195.7191, mean_absolute_error: 0.3659, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.7651, predictive_accuracy: 0.7574, prior_entropy: 0.9835, recall: 0.7574, relative_absolute_error: 0.7488, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4277, root_relative_squared_error: 0.8653, scimark_benchmark: 1299.3447, usercpu_time_millis: 1.482, usercpu_time_millis_testing: 0.047, usercpu_time_millis_training: 1.435,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, f_measure: 0.4204, kb_relative_information_score: 0.0359, mean_absolute_error: 0.4886, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.3311, predictive_accuracy: 0.5755, prior_entropy: 0.9835, recall: 0.5755, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4943, root_relative_squared_error: 1, scimark_benchmark: 1291.058, usercpu_time_millis: 1.622, usercpu_time_millis_testing: 0.038, usercpu_time_millis_training: 1.584,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7283, f_measure: 0.7486, kappa: 0.484, kb_relative_information_score: 13195.7191, mean_absolute_error: 0.3659, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.7651, predictive_accuracy: 0.7574, prior_entropy: 0.9835, recall: 0.7574, relative_absolute_error: 0.7488, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4277, root_relative_squared_error: 0.8653, scimark_benchmark: 1286.668, usercpu_time_millis: 2.081, usercpu_time_millis_testing: 0.072, usercpu_time_millis_training: 2.009,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, f_measure: 0.4204, kb_relative_information_score: 0.0359, mean_absolute_error: 0.4886, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.3311, predictive_accuracy: 0.5755, prior_entropy: 0.9835, recall: 0.5755, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4943, root_relative_squared_error: 1, scimark_benchmark: 1298.6036, usercpu_time_millis: 1.593, usercpu_time_millis_testing: 0.039, usercpu_time_millis_training: 1.554,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, f_measure: 0.4204, kb_relative_information_score: 0.0359, mean_absolute_error: 0.4886, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.3311, predictive_accuracy: 0.5755, prior_entropy: 0.9835, recall: 0.5755, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4943, root_relative_squared_error: 1, scimark_benchmark: 1282.3991, usercpu_time_millis: 1.348, usercpu_time_millis_testing: 0.036, usercpu_time_millis_training: 1.312,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7283, f_measure: 0.7486, kappa: 0.484, kb_relative_information_score: 13195.7191, mean_absolute_error: 0.3659, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.7651, predictive_accuracy: 0.7574, prior_entropy: 0.9835, recall: 0.7574, relative_absolute_error: 0.7488, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4277, root_relative_squared_error: 0.8653, scimark_benchmark: 1286.6912, usercpu_time_millis: 3.764, usercpu_time_millis_testing: 0.092, usercpu_time_millis_training: 3.672,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, f_measure: 0.4204, kb_relative_information_score: 0.0359, mean_absolute_error: 0.4886, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.3311, predictive_accuracy: 0.5755, prior_entropy: 0.9835, recall: 0.5755, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4943, root_relative_squared_error: 1, scimark_benchmark: 1286.3545, usercpu_time_millis: 1.487, usercpu_time_millis_testing: 0.038, usercpu_time_millis_training: 1.449,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, f_measure: 0.4204, kb_relative_information_score: 0.0359, mean_absolute_error: 0.4886, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.3311, predictive_accuracy: 0.5755, prior_entropy: 0.9835, recall: 0.5755, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4943, root_relative_squared_error: 1, scimark_benchmark: 1285.5813, usercpu_time_millis: 2.004, usercpu_time_millis_testing: 0.076, usercpu_time_millis_training: 1.928,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7283, f_measure: 0.7486, kappa: 0.484, kb_relative_information_score: 13195.7191, mean_absolute_error: 0.3659, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.7651, predictive_accuracy: 0.7574, prior_entropy: 0.9835, recall: 0.7574, relative_absolute_error: 0.7488, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4277, root_relative_squared_error: 0.8653, scimark_benchmark: 1275.775, usercpu_time_millis: 3.437, usercpu_time_millis_testing: 0.077, usercpu_time_millis_training: 3.36,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7283, f_measure: 0.7486, kappa: 0.484, kb_relative_information_score: 13195.7191, mean_absolute_error: 0.3659, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.7651, predictive_accuracy: 0.7574, prior_entropy: 0.9835, recall: 0.7574, relative_absolute_error: 0.7488, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4277, root_relative_squared_error: 0.8653, scimark_benchmark: 1284.9331, usercpu_time_millis: 2.334, usercpu_time_millis_testing: 0.062, usercpu_time_millis_training: 2.272,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, f_measure: 0.4204, kb_relative_information_score: 0.0359, mean_absolute_error: 0.4886, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.3311, predictive_accuracy: 0.5755, prior_entropy: 0.9835, recall: 0.5755, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4943, root_relative_squared_error: 1, scimark_benchmark: 1277.9268, usercpu_time_millis: 1.536, usercpu_time_millis_testing: 0.046, usercpu_time_millis_training: 1.49,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, f_measure: 0.4204, kb_relative_information_score: 0.0359, mean_absolute_error: 0.4886, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.3311, predictive_accuracy: 0.5755, prior_entropy: 0.9835, recall: 0.5755, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4943, root_relative_squared_error: 1, scimark_benchmark: 1287.9227, usercpu_time_millis: 0.983, usercpu_time_millis_testing: 0.034, usercpu_time_millis_training: 0.949,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7283, f_measure: 0.7486, kappa: 0.484, kb_relative_information_score: 13195.7191, mean_absolute_error: 0.3659, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.7651, predictive_accuracy: 0.7574, prior_entropy: 0.9835, recall: 0.7574, relative_absolute_error: 0.7488, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4277, root_relative_squared_error: 0.8653, scimark_benchmark: 1291.5031, usercpu_time_millis: 1.598, usercpu_time_millis_testing: 0.055, usercpu_time_millis_training: 1.543,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, f_measure: 0.4204, kb_relative_information_score: 0.0359, mean_absolute_error: 0.4886, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.3311, predictive_accuracy: 0.5755, prior_entropy: 0.9835, recall: 0.5755, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4943, root_relative_squared_error: 1, scimark_benchmark: 1287.3475, usercpu_time_millis: 0.969, usercpu_time_millis_testing: 0.036, usercpu_time_millis_training: 0.933,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, f_measure: 0.4204, kb_relative_information_score: 0.0359, mean_absolute_error: 0.4886, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.3311, predictive_accuracy: 0.5755, prior_entropy: 0.9835, recall: 0.5755, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4943, root_relative_squared_error: 1, scimark_benchmark: 1299.4822, usercpu_time_millis: 1.087, usercpu_time_millis_testing: 0.037, usercpu_time_millis_training: 1.05,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7283, f_measure: 0.7486, kappa: 0.484, kb_relative_information_score: 13195.7191, mean_absolute_error: 0.3659, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.7651, predictive_accuracy: 0.7574, prior_entropy: 0.9835, recall: 0.7574, relative_absolute_error: 0.7488, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4277, root_relative_squared_error: 0.8653, scimark_benchmark: 1297.7688, usercpu_time_millis: 2.035, usercpu_time_millis_testing: 0.064, usercpu_time_millis_training: 1.971,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7283, f_measure: 0.7486, kappa: 0.484, kb_relative_information_score: 13195.7191, mean_absolute_error: 0.3659, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.7651, predictive_accuracy: 0.7574, prior_entropy: 0.9835, recall: 0.7574, relative_absolute_error: 0.7488, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4277, root_relative_squared_error: 0.8653, scimark_benchmark: 1284.2614, usercpu_time_millis: 1.535, usercpu_time_millis_testing: 0.055, usercpu_time_millis_training: 1.48,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, f_measure: 0.4204, kb_relative_information_score: 0.0359, mean_absolute_error: 0.4886, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.3311, predictive_accuracy: 0.5755, prior_entropy: 0.9835, recall: 0.5755, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4943, root_relative_squared_error: 1, scimark_benchmark: 1292.6369, usercpu_time_millis: 1.229, usercpu_time_millis_testing: 0.042, usercpu_time_millis_training: 1.187,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7283, f_measure: 0.7486, kappa: 0.484, kb_relative_information_score: 13195.7191, mean_absolute_error: 0.3659, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.7651, predictive_accuracy: 0.7574, prior_entropy: 0.9835, recall: 0.7574, relative_absolute_error: 0.7488, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4277, root_relative_squared_error: 0.8653, scimark_benchmark: 1297.2592, usercpu_time_millis: 1.727, usercpu_time_millis_testing: 0.06, usercpu_time_millis_training: 1.667,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, f_measure: 0.4204, kb_relative_information_score: 0.0359, mean_absolute_error: 0.4886, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.3311, predictive_accuracy: 0.5755, prior_entropy: 0.9835, recall: 0.5755, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4943, root_relative_squared_error: 1, scimark_benchmark: 1311.5854, usercpu_time_millis: 1.028, usercpu_time_millis_testing: 0.038, usercpu_time_millis_training: 0.99,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, f_measure: 0.4204, kb_relative_information_score: 0.0359, mean_absolute_error: 0.4886, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.3311, predictive_accuracy: 0.5755, prior_entropy: 0.9835, recall: 0.5755, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4943, root_relative_squared_error: 1, scimark_benchmark: 1264.7298, usercpu_time_millis: 3.545, usercpu_time_millis_testing: 0.133, usercpu_time_millis_training: 3.412,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, f_measure: 0.4204, kb_relative_information_score: 0.0359, mean_absolute_error: 0.4886, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.3311, predictive_accuracy: 0.5755, prior_entropy: 0.9835, recall: 0.5755, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4943, root_relative_squared_error: 1, scimark_benchmark: 1273.3582, usercpu_time_millis: 1.4, usercpu_time_millis_testing: 0.035, usercpu_time_millis_training: 1.365,
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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