Task
Supervised Classification on rabe_131

Supervised Classification on rabe_131

Task 4443 Supervised Classification rabe_131 231 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9862, f_measure: 0.984, kappa: 0.9673, kb_relative_information_score: 482.7393, mean_absolute_error: 0.016, mean_prior_absolute_error: 0.4877, number_of_instances: 500, precision: 0.9846, predictive_accuracy: 0.984, prior_entropy: 0.9829, recall: 0.984, relative_absolute_error: 0.0328, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.1265, root_relative_squared_error: 0.2563,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9862, f_measure: 0.984, kappa: 0.9673, kb_relative_information_score: 482.7393, mean_absolute_error: 0.016, mean_prior_absolute_error: 0.4877, number_of_instances: 500, precision: 0.9846, predictive_accuracy: 0.984, prior_entropy: 0.9829, recall: 0.984, relative_absolute_error: 0.0328, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.1265, root_relative_squared_error: 0.2563, scimark_benchmark: 906.0979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.981, f_measure: 0.984, kappa: 0.967, kb_relative_information_score: 482.7393, mean_absolute_error: 0.016, mean_prior_absolute_error: 0.4877, number_of_instances: 500, precision: 0.9844, predictive_accuracy: 0.984, prior_entropy: 0.9829, recall: 0.984, relative_absolute_error: 0.0328, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.1265, root_relative_squared_error: 0.2563,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9751, f_measure: 0.984, kappa: 0.967, kb_relative_information_score: 474.8938, mean_absolute_error: 0.0266, mean_prior_absolute_error: 0.4877, number_of_instances: 500, precision: 0.9844, predictive_accuracy: 0.984, prior_entropy: 0.9829, recall: 0.984, relative_absolute_error: 0.0546, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.1258, root_relative_squared_error: 0.2549, scimark_benchmark: 972.587,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.981, f_measure: 0.984, kappa: 0.967, kb_relative_information_score: 482.7293, mean_absolute_error: 0.016, mean_prior_absolute_error: 0.4877, number_of_instances: 500, precision: 0.9844, predictive_accuracy: 0.984, prior_entropy: 0.9829, recall: 0.984, relative_absolute_error: 0.0328, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.1265, root_relative_squared_error: 0.2563, scimark_benchmark: 934.3687,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.981, f_measure: 0.984, kappa: 0.967, kb_relative_information_score: 482.7393, mean_absolute_error: 0.016, mean_prior_absolute_error: 0.4877, number_of_instances: 500, precision: 0.9844, predictive_accuracy: 0.984, prior_entropy: 0.9829, recall: 0.984, relative_absolute_error: 0.0328, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.1265, root_relative_squared_error: 0.2563,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9631, f_measure: 0.9582, kappa: 0.9149, kb_relative_information_score: 455.8287, mean_absolute_error: 0.042, mean_prior_absolute_error: 0.4877, number_of_instances: 500, precision: 0.9612, predictive_accuracy: 0.958, prior_entropy: 0.9829, recall: 0.958, relative_absolute_error: 0.0861, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.2049, root_relative_squared_error: 0.4152,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.4258, kb_relative_information_score: 64.5911, mean_absolute_error: 0.42, mean_prior_absolute_error: 0.4877, number_of_instances: 500, precision: 0.3364, predictive_accuracy: 0.58, prior_entropy: 0.9829, recall: 0.58, relative_absolute_error: 0.8612, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.6481, root_relative_squared_error: 1.313, scimark_benchmark: 931.771,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.4258, kb_relative_information_score: 64.5911, mean_absolute_error: 0.42, mean_prior_absolute_error: 0.4877, number_of_instances: 500, precision: 0.3364, predictive_accuracy: 0.58, prior_entropy: 0.9829, recall: 0.58, relative_absolute_error: 0.8612, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.6481, root_relative_squared_error: 1.313, scimark_benchmark: 944.1067,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9833, f_measure: 0.984, kappa: 0.9673, kb_relative_information_score: 460.8016, mean_absolute_error: 0.0445, mean_prior_absolute_error: 0.4877, number_of_instances: 500, precision: 0.9846, predictive_accuracy: 0.984, prior_entropy: 0.9829, recall: 0.984, relative_absolute_error: 0.0913, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.1325, root_relative_squared_error: 0.2684, scimark_benchmark: 941.6675,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9833, f_measure: 0.984, kappa: 0.9673, kb_relative_information_score: 460.8282, mean_absolute_error: 0.044, mean_prior_absolute_error: 0.4877, number_of_instances: 500, precision: 0.9846, predictive_accuracy: 0.984, prior_entropy: 0.9829, recall: 0.984, relative_absolute_error: 0.0901, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.1354, root_relative_squared_error: 0.2743, scimark_benchmark: 941.6675,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9995, f_measure: 0.982, kappa: 0.9629, kb_relative_information_score: 472.086, mean_absolute_error: 0.0291, mean_prior_absolute_error: 0.4877, number_of_instances: 500, precision: 0.9823, predictive_accuracy: 0.982, prior_entropy: 0.9829, recall: 0.982, relative_absolute_error: 0.0598, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.1054, root_relative_squared_error: 0.2136, scimark_benchmark: 934.695,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9631, f_measure: 0.9582, kappa: 0.9149, kb_relative_information_score: 455.8287, mean_absolute_error: 0.042, mean_prior_absolute_error: 0.4877, number_of_instances: 500, precision: 0.9612, predictive_accuracy: 0.958, prior_entropy: 0.9829, recall: 0.958, relative_absolute_error: 0.0861, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.2049, root_relative_squared_error: 0.4152,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9631, f_measure: 0.9582, kappa: 0.9149, kb_relative_information_score: 455.8287, mean_absolute_error: 0.042, mean_prior_absolute_error: 0.4877, number_of_instances: 500, precision: 0.9612, predictive_accuracy: 0.958, prior_entropy: 0.9829, recall: 0.958, relative_absolute_error: 0.0861, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.2049, root_relative_squared_error: 0.4152,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9887, f_measure: 0.9442, kappa: 0.8861, kb_relative_information_score: 358.4104, mean_absolute_error: 0.1546, mean_prior_absolute_error: 0.4877, number_of_instances: 500, precision: 0.9459, predictive_accuracy: 0.944, prior_entropy: 0.9829, recall: 0.944, relative_absolute_error: 0.3169, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.2288, root_relative_squared_error: 0.4637, scimark_benchmark: 941.6675, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9631, f_measure: 0.9582, kappa: 0.9149, kb_relative_information_score: 455.8287, mean_absolute_error: 0.042, mean_prior_absolute_error: 0.4877, number_of_instances: 500, precision: 0.9612, predictive_accuracy: 0.958, prior_entropy: 0.9829, recall: 0.958, relative_absolute_error: 0.0861, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.2049, root_relative_squared_error: 0.4152,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9631, f_measure: 0.9582, kappa: 0.9149, kb_relative_information_score: 455.8287, mean_absolute_error: 0.042, mean_prior_absolute_error: 0.4877, number_of_instances: 500, precision: 0.9612, predictive_accuracy: 0.958, prior_entropy: 0.9829, recall: 0.958, relative_absolute_error: 0.0861, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.2049, root_relative_squared_error: 0.4152,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9833, f_measure: 0.984, kappa: 0.9673, kb_relative_information_score: 444.992, mean_absolute_error: 0.065, mean_prior_absolute_error: 0.4877, number_of_instances: 500, precision: 0.9846, predictive_accuracy: 0.984, prior_entropy: 0.9829, recall: 0.984, relative_absolute_error: 0.1333, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.1373, root_relative_squared_error: 0.2781, scimark_benchmark: 905.2959,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9631, f_measure: 0.9582, kappa: 0.9149, kb_relative_information_score: 455.8287, mean_absolute_error: 0.042, mean_prior_absolute_error: 0.4877, number_of_instances: 500, precision: 0.9612, predictive_accuracy: 0.958, prior_entropy: 0.9829, recall: 0.958, relative_absolute_error: 0.0861, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.2049, root_relative_squared_error: 0.4152,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.4258, kb_relative_information_score: 64.5911, mean_absolute_error: 0.42, mean_prior_absolute_error: 0.4877, number_of_instances: 500, precision: 0.3364, predictive_accuracy: 0.58, prior_entropy: 0.9829, recall: 0.58, relative_absolute_error: 0.8612, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.6481, root_relative_squared_error: 1.313, scimark_benchmark: 937.5117,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.4258, kb_relative_information_score: 64.5911, mean_absolute_error: 0.42, mean_prior_absolute_error: 0.4877, number_of_instances: 500, precision: 0.3364, predictive_accuracy: 0.58, prior_entropy: 0.9829, recall: 0.58, relative_absolute_error: 0.8612, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.6481, root_relative_squared_error: 1.313, scimark_benchmark: 974.2014, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9833, f_measure: 0.984, kappa: 0.9673, kb_relative_information_score: 460.8016, mean_absolute_error: 0.0445, mean_prior_absolute_error: 0.4877, number_of_instances: 500, precision: 0.9846, predictive_accuracy: 0.984, prior_entropy: 0.9829, recall: 0.984, relative_absolute_error: 0.0913, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.1325, root_relative_squared_error: 0.2684, scimark_benchmark: 932.438, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9833, f_measure: 0.984, kappa: 0.9673, kb_relative_information_score: 460.8282, mean_absolute_error: 0.044, mean_prior_absolute_error: 0.4877, number_of_instances: 500, precision: 0.9846, predictive_accuracy: 0.984, prior_entropy: 0.9829, recall: 0.984, relative_absolute_error: 0.0901, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.1354, root_relative_squared_error: 0.2743, scimark_benchmark: 941.3847,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9833, f_measure: 0.984, kappa: 0.9673, kb_relative_information_score: 460.8282, mean_absolute_error: 0.044, mean_prior_absolute_error: 0.4877, number_of_instances: 500, precision: 0.9846, predictive_accuracy: 0.984, prior_entropy: 0.9829, recall: 0.984, relative_absolute_error: 0.0901, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.1354, root_relative_squared_error: 0.2743, scimark_benchmark: 974.2014,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9994, f_measure: 0.984, kappa: 0.967, kb_relative_information_score: 446.1291, mean_absolute_error: 0.0624, mean_prior_absolute_error: 0.4877, number_of_instances: 500, precision: 0.9844, predictive_accuracy: 0.984, prior_entropy: 0.9829, recall: 0.984, relative_absolute_error: 0.128, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.1233, root_relative_squared_error: 0.2499, scimark_benchmark: 974.2014, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9862, f_measure: 0.984, kappa: 0.9673, kb_relative_information_score: 482.7393, mean_absolute_error: 0.016, mean_prior_absolute_error: 0.4877, number_of_instances: 500, precision: 0.9846, predictive_accuracy: 0.984, prior_entropy: 0.9829, recall: 0.984, relative_absolute_error: 0.0328, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.1265, root_relative_squared_error: 0.2563, scimark_benchmark: 942.2392,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9631, f_measure: 0.9582, kappa: 0.9149, kb_relative_information_score: 455.8287, mean_absolute_error: 0.042, mean_prior_absolute_error: 0.4877, number_of_instances: 500, precision: 0.9612, predictive_accuracy: 0.958, prior_entropy: 0.9829, recall: 0.958, relative_absolute_error: 0.0861, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.2049, root_relative_squared_error: 0.4152,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9751, f_measure: 0.984, kappa: 0.967, kb_relative_information_score: 474.8938, mean_absolute_error: 0.0266, mean_prior_absolute_error: 0.4877, number_of_instances: 500, precision: 0.9844, predictive_accuracy: 0.984, prior_entropy: 0.9829, recall: 0.984, relative_absolute_error: 0.0546, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.1258, root_relative_squared_error: 0.2549, scimark_benchmark: 908.9569,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.981, f_measure: 0.984, kappa: 0.967, kb_relative_information_score: 482.7293, mean_absolute_error: 0.016, mean_prior_absolute_error: 0.4877, number_of_instances: 500, precision: 0.9844, predictive_accuracy: 0.984, prior_entropy: 0.9829, recall: 0.984, relative_absolute_error: 0.0328, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.1265, root_relative_squared_error: 0.2563, scimark_benchmark: 938.1282,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.4258, kb_relative_information_score: 64.5911, mean_absolute_error: 0.42, mean_prior_absolute_error: 0.4877, number_of_instances: 500, precision: 0.3364, predictive_accuracy: 0.58, prior_entropy: 0.9829, recall: 0.58, relative_absolute_error: 0.8612, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.6481, root_relative_squared_error: 1.313, scimark_benchmark: 926.5462, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9833, f_measure: 0.984, kappa: 0.9673, kb_relative_information_score: 460.8282, mean_absolute_error: 0.044, mean_prior_absolute_error: 0.4877, number_of_instances: 500, precision: 0.9846, predictive_accuracy: 0.984, prior_entropy: 0.9829, recall: 0.984, relative_absolute_error: 0.0901, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.1354, root_relative_squared_error: 0.2743, scimark_benchmark: 903.2737,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9833, f_measure: 0.984, kappa: 0.9673, kb_relative_information_score: 460.8282, mean_absolute_error: 0.044, mean_prior_absolute_error: 0.4877, number_of_instances: 500, precision: 0.9846, predictive_accuracy: 0.984, prior_entropy: 0.9829, recall: 0.984, relative_absolute_error: 0.0901, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.1354, root_relative_squared_error: 0.2743, scimark_benchmark: 930.404,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9995, f_measure: 0.982, kappa: 0.9629, kb_relative_information_score: 472.086, mean_absolute_error: 0.0291, mean_prior_absolute_error: 0.4877, number_of_instances: 500, precision: 0.9823, predictive_accuracy: 0.982, prior_entropy: 0.9829, recall: 0.982, relative_absolute_error: 0.0598, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.1054, root_relative_squared_error: 0.2136, scimark_benchmark: 903.2737,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9887, f_measure: 0.9442, kappa: 0.8861, kb_relative_information_score: 358.4104, mean_absolute_error: 0.1546, mean_prior_absolute_error: 0.4877, number_of_instances: 500, precision: 0.9459, predictive_accuracy: 0.944, prior_entropy: 0.9829, recall: 0.944, relative_absolute_error: 0.3169, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.2288, root_relative_squared_error: 0.4637, scimark_benchmark: 938.4601, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9833, f_measure: 0.984, kappa: 0.9673, kb_relative_information_score: 460.8282, mean_absolute_error: 0.044, mean_prior_absolute_error: 0.4877, number_of_instances: 500, precision: 0.9846, predictive_accuracy: 0.984, prior_entropy: 0.9829, recall: 0.984, relative_absolute_error: 0.0901, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.1354, root_relative_squared_error: 0.2743, scimark_benchmark: 932.438,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9833, f_measure: 0.984, kappa: 0.9673, kb_relative_information_score: 444.992, mean_absolute_error: 0.065, mean_prior_absolute_error: 0.4877, number_of_instances: 500, precision: 0.9846, predictive_accuracy: 0.984, prior_entropy: 0.9829, recall: 0.984, relative_absolute_error: 0.1333, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.1373, root_relative_squared_error: 0.2781, scimark_benchmark: 932.438,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9994, f_measure: 0.984, kappa: 0.967, kb_relative_information_score: 446.1291, mean_absolute_error: 0.0624, mean_prior_absolute_error: 0.4877, number_of_instances: 500, precision: 0.9844, predictive_accuracy: 0.984, prior_entropy: 0.9829, recall: 0.984, relative_absolute_error: 0.128, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.1233, root_relative_squared_error: 0.2499, scimark_benchmark: 936.9595,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.998, f_measure: 0.976, kappa: 0.9507, kb_relative_information_score: 411.1929, mean_absolute_error: 0.0979, mean_prior_absolute_error: 0.4877, number_of_instances: 500, precision: 0.976, predictive_accuracy: 0.976, prior_entropy: 0.9829, recall: 0.976, relative_absolute_error: 0.2008, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.173, root_relative_squared_error: 0.3506, scimark_benchmark: 908.9569, usercpu_time_millis: 280, usercpu_time_millis_testing: 150, usercpu_time_millis_training: 130,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9985, f_measure: 0.978, kappa: 0.9549, kb_relative_information_score: 411.7512, mean_absolute_error: 0.0977, mean_prior_absolute_error: 0.4877, number_of_instances: 500, precision: 0.978, predictive_accuracy: 0.978, prior_entropy: 0.9829, recall: 0.978, relative_absolute_error: 0.2003, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.1719, root_relative_squared_error: 0.3484, scimark_benchmark: 906.5979, usercpu_time_millis: 80, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9966, f_measure: 0.964, kappa: 0.9259, kb_relative_information_score: 409.9908, mean_absolute_error: 0.0984, mean_prior_absolute_error: 0.4877, number_of_instances: 500, precision: 0.964, predictive_accuracy: 0.964, prior_entropy: 0.9829, recall: 0.964, relative_absolute_error: 0.2017, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.1781, root_relative_squared_error: 0.3607, scimark_benchmark: 921.466, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9957, f_measure: 0.962, kappa: 0.922, kb_relative_information_score: 408.8632, mean_absolute_error: 0.0993, mean_prior_absolute_error: 0.4877, number_of_instances: 500, precision: 0.962, predictive_accuracy: 0.962, prior_entropy: 0.9829, recall: 0.962, relative_absolute_error: 0.2037, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.1812, root_relative_squared_error: 0.367, scimark_benchmark: 945.0448, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9887, f_measure: 0.9442, kappa: 0.8861, kb_relative_information_score: 358.4104, mean_absolute_error: 0.1546, mean_prior_absolute_error: 0.4877, number_of_instances: 500, precision: 0.9459, predictive_accuracy: 0.944, prior_entropy: 0.9829, recall: 0.944, relative_absolute_error: 0.3169, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.2288, root_relative_squared_error: 0.4637, scimark_benchmark: 1313.9976, usercpu_time_millis: 10, usercpu_time_millis_training: 10,

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