OpenML
Supervised Classification on musk

Supervised Classification on musk

Task 3950 Supervised Classification musk 66544 runs submitted
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  • mythbusting_1 study_1 study_15 study_20 under100k
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.999, f_measure: 0.9997, kappa: 0.9988, kb_relative_information_score: 6585.79, mean_absolute_error: 0.0003, mean_prior_absolute_error: 0.2608, number_of_instances: 6598, precision: 0.9997, predictive_accuracy: 0.9997, prior_entropy: 0.6204, recall: 0.9997, relative_absolute_error: 0.0012, root_mean_prior_squared_error: 0.3611, root_mean_squared_error: 0.0174, root_relative_squared_error: 0.0482, scimark_benchmark: 1284.8417, usercpu_time_millis: 2.787, usercpu_time_millis_testing: 0.19, usercpu_time_millis_training: 2.597,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.999, f_measure: 0.9997, kappa: 0.9988, kb_relative_information_score: 6585.79, mean_absolute_error: 0.0003, mean_prior_absolute_error: 0.2608, number_of_instances: 6598, precision: 0.9997, predictive_accuracy: 0.9997, prior_entropy: 0.6204, recall: 0.9997, relative_absolute_error: 0.0012, root_mean_prior_squared_error: 0.3611, root_mean_squared_error: 0.0174, root_relative_squared_error: 0.0482, scimark_benchmark: 1251.49, usercpu_time_millis: 2.908, usercpu_time_millis_testing: 0.192, usercpu_time_millis_training: 2.716,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.999, f_measure: 0.9997, kappa: 0.9988, kb_relative_information_score: 6585.79, mean_absolute_error: 0.0003, mean_prior_absolute_error: 0.2608, number_of_instances: 6598, precision: 0.9997, predictive_accuracy: 0.9997, prior_entropy: 0.6204, recall: 0.9997, relative_absolute_error: 0.0012, root_mean_prior_squared_error: 0.3611, root_mean_squared_error: 0.0174, root_relative_squared_error: 0.0482, scimark_benchmark: 1238.886, usercpu_time_millis: 2.991, usercpu_time_millis_testing: 0.188, usercpu_time_millis_training: 2.803,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.999, f_measure: 0.9997, kappa: 0.9988, kb_relative_information_score: 6585.79, mean_absolute_error: 0.0003, mean_prior_absolute_error: 0.2608, number_of_instances: 6598, precision: 0.9997, predictive_accuracy: 0.9997, prior_entropy: 0.6204, recall: 0.9997, relative_absolute_error: 0.0012, root_mean_prior_squared_error: 0.3611, root_mean_squared_error: 0.0174, root_relative_squared_error: 0.0482, scimark_benchmark: 1235.0661, usercpu_time_millis: 2.928, usercpu_time_millis_testing: 0.183, usercpu_time_millis_training: 2.745,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.999, f_measure: 0.9997, kappa: 0.9988, kb_relative_information_score: 6585.79, mean_absolute_error: 0.0003, mean_prior_absolute_error: 0.2608, number_of_instances: 6598, precision: 0.9997, predictive_accuracy: 0.9997, prior_entropy: 0.6204, recall: 0.9997, relative_absolute_error: 0.0012, root_mean_prior_squared_error: 0.3611, root_mean_squared_error: 0.0174, root_relative_squared_error: 0.0482, scimark_benchmark: 1240.6689, usercpu_time_millis: 3.036, usercpu_time_millis_testing: 0.196, usercpu_time_millis_training: 2.84,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.999, f_measure: 0.9997, kappa: 0.9988, kb_relative_information_score: 6585.79, mean_absolute_error: 0.0003, mean_prior_absolute_error: 0.2608, number_of_instances: 6598, precision: 0.9997, predictive_accuracy: 0.9997, prior_entropy: 0.6204, recall: 0.9997, relative_absolute_error: 0.0012, root_mean_prior_squared_error: 0.3611, root_mean_squared_error: 0.0174, root_relative_squared_error: 0.0482, scimark_benchmark: 1271.6542, usercpu_time_millis: 2.585, usercpu_time_millis_testing: 0.174, usercpu_time_millis_training: 2.411,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.999, f_measure: 0.9997, kappa: 0.9988, kb_relative_information_score: 6585.79, mean_absolute_error: 0.0003, mean_prior_absolute_error: 0.2608, number_of_instances: 6598, precision: 0.9997, predictive_accuracy: 0.9997, prior_entropy: 0.6204, recall: 0.9997, relative_absolute_error: 0.0012, root_mean_prior_squared_error: 0.3611, root_mean_squared_error: 0.0174, root_relative_squared_error: 0.0482, scimark_benchmark: 1235.3716, usercpu_time_millis: 2.93, usercpu_time_millis_testing: 0.194, usercpu_time_millis_training: 2.736,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.999, f_measure: 0.9997, kappa: 0.9988, kb_relative_information_score: 6585.79, mean_absolute_error: 0.0003, mean_prior_absolute_error: 0.2608, number_of_instances: 6598, precision: 0.9997, predictive_accuracy: 0.9997, prior_entropy: 0.6204, recall: 0.9997, relative_absolute_error: 0.0012, root_mean_prior_squared_error: 0.3611, root_mean_squared_error: 0.0174, root_relative_squared_error: 0.0482, scimark_benchmark: 1232.7939, usercpu_time_millis: 2.996, usercpu_time_millis_testing: 0.191, usercpu_time_millis_training: 2.805,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.999, f_measure: 0.9997, kappa: 0.9988, kb_relative_information_score: 6585.79, mean_absolute_error: 0.0003, mean_prior_absolute_error: 0.2608, number_of_instances: 6598, precision: 0.9997, predictive_accuracy: 0.9997, prior_entropy: 0.6204, recall: 0.9997, relative_absolute_error: 0.0012, root_mean_prior_squared_error: 0.3611, root_mean_squared_error: 0.0174, root_relative_squared_error: 0.0482, scimark_benchmark: 1273.217, usercpu_time_millis: 2.994, usercpu_time_millis_testing: 0.183, usercpu_time_millis_training: 2.811,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.999, f_measure: 0.9997, kappa: 0.9988, kb_relative_information_score: 6585.79, mean_absolute_error: 0.0003, mean_prior_absolute_error: 0.2608, number_of_instances: 6598, precision: 0.9997, predictive_accuracy: 0.9997, prior_entropy: 0.6204, recall: 0.9997, relative_absolute_error: 0.0012, root_mean_prior_squared_error: 0.3611, root_mean_squared_error: 0.0174, root_relative_squared_error: 0.0482, scimark_benchmark: 1273.2871, usercpu_time_millis: 3.01, usercpu_time_millis_testing: 0.111, usercpu_time_millis_training: 2.899,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.999, f_measure: 0.9997, kappa: 0.9988, kb_relative_information_score: 6585.79, mean_absolute_error: 0.0003, mean_prior_absolute_error: 0.2608, number_of_instances: 6598, precision: 0.9997, predictive_accuracy: 0.9997, prior_entropy: 0.6204, recall: 0.9997, relative_absolute_error: 0.0012, root_mean_prior_squared_error: 0.3611, root_mean_squared_error: 0.0174, root_relative_squared_error: 0.0482, scimark_benchmark: 1245.5543, usercpu_time_millis: 3.055, usercpu_time_millis_testing: 0.191, usercpu_time_millis_training: 2.864,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.999, f_measure: 0.9997, kappa: 0.9988, kb_relative_information_score: 6585.79, mean_absolute_error: 0.0003, mean_prior_absolute_error: 0.2608, number_of_instances: 6598, precision: 0.9997, predictive_accuracy: 0.9997, prior_entropy: 0.6204, recall: 0.9997, relative_absolute_error: 0.0012, root_mean_prior_squared_error: 0.3611, root_mean_squared_error: 0.0174, root_relative_squared_error: 0.0482, scimark_benchmark: 1277.3731, usercpu_time_millis: 3.515, usercpu_time_millis_testing: 0.197, usercpu_time_millis_training: 3.318,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.999, f_measure: 0.9997, kappa: 0.9988, kb_relative_information_score: 6585.79, mean_absolute_error: 0.0003, mean_prior_absolute_error: 0.2608, number_of_instances: 6598, precision: 0.9997, predictive_accuracy: 0.9997, prior_entropy: 0.6204, recall: 0.9997, relative_absolute_error: 0.0012, root_mean_prior_squared_error: 0.3611, root_mean_squared_error: 0.0174, root_relative_squared_error: 0.0482, scimark_benchmark: 1263.1441, usercpu_time_millis: 3.408, usercpu_time_millis_testing: 0.295, usercpu_time_millis_training: 3.113,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.999, f_measure: 0.9997, kappa: 0.9988, kb_relative_information_score: 6585.79, mean_absolute_error: 0.0003, mean_prior_absolute_error: 0.2608, number_of_instances: 6598, precision: 0.9997, predictive_accuracy: 0.9997, prior_entropy: 0.6204, recall: 0.9997, relative_absolute_error: 0.0012, root_mean_prior_squared_error: 0.3611, root_mean_squared_error: 0.0174, root_relative_squared_error: 0.0482, scimark_benchmark: 1250.9132, usercpu_time_millis: 2.98, usercpu_time_millis_testing: 0.188, usercpu_time_millis_training: 2.792,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.999, f_measure: 0.9997, kappa: 0.9988, kb_relative_information_score: 6585.79, mean_absolute_error: 0.0003, mean_prior_absolute_error: 0.2608, number_of_instances: 6598, precision: 0.9997, predictive_accuracy: 0.9997, prior_entropy: 0.6204, recall: 0.9997, relative_absolute_error: 0.0012, root_mean_prior_squared_error: 0.3611, root_mean_squared_error: 0.0174, root_relative_squared_error: 0.0482, scimark_benchmark: 1245.9758, usercpu_time_millis: 2.858, usercpu_time_millis_testing: 0.202, usercpu_time_millis_training: 2.656,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.999, f_measure: 0.9997, kappa: 0.9988, kb_relative_information_score: 6585.79, mean_absolute_error: 0.0003, mean_prior_absolute_error: 0.2608, number_of_instances: 6598, precision: 0.9997, predictive_accuracy: 0.9997, prior_entropy: 0.6204, recall: 0.9997, relative_absolute_error: 0.0012, root_mean_prior_squared_error: 0.3611, root_mean_squared_error: 0.0174, root_relative_squared_error: 0.0482, scimark_benchmark: 1276.4897, usercpu_time_millis: 2.864, usercpu_time_millis_testing: 0.182, usercpu_time_millis_training: 2.682,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.999, f_measure: 0.9997, kappa: 0.9988, kb_relative_information_score: 6585.79, mean_absolute_error: 0.0003, mean_prior_absolute_error: 0.2608, number_of_instances: 6598, precision: 0.9997, predictive_accuracy: 0.9997, prior_entropy: 0.6204, recall: 0.9997, relative_absolute_error: 0.0012, root_mean_prior_squared_error: 0.3611, root_mean_squared_error: 0.0174, root_relative_squared_error: 0.0482, scimark_benchmark: 1250.1406, usercpu_time_millis: 3.032, usercpu_time_millis_testing: 0.194, usercpu_time_millis_training: 2.838,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.999, f_measure: 0.9997, kappa: 0.9988, kb_relative_information_score: 6585.79, mean_absolute_error: 0.0003, mean_prior_absolute_error: 0.2608, number_of_instances: 6598, precision: 0.9997, predictive_accuracy: 0.9997, prior_entropy: 0.6204, recall: 0.9997, relative_absolute_error: 0.0012, root_mean_prior_squared_error: 0.3611, root_mean_squared_error: 0.0174, root_relative_squared_error: 0.0482, scimark_benchmark: 1234.015, usercpu_time_millis: 2.938, usercpu_time_millis_testing: 0.189, usercpu_time_millis_training: 2.749,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.999, f_measure: 0.9997, kappa: 0.9988, kb_relative_information_score: 6585.79, mean_absolute_error: 0.0003, mean_prior_absolute_error: 0.2608, number_of_instances: 6598, precision: 0.9997, predictive_accuracy: 0.9997, prior_entropy: 0.6204, recall: 0.9997, relative_absolute_error: 0.0012, root_mean_prior_squared_error: 0.3611, root_mean_squared_error: 0.0174, root_relative_squared_error: 0.0482, scimark_benchmark: 1277.8976, usercpu_time_millis: 2.731, usercpu_time_millis_testing: 0.178, usercpu_time_millis_training: 2.553,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.999, f_measure: 0.9997, kappa: 0.9988, kb_relative_information_score: 6585.79, mean_absolute_error: 0.0003, mean_prior_absolute_error: 0.2608, number_of_instances: 6598, precision: 0.9997, predictive_accuracy: 0.9997, prior_entropy: 0.6204, recall: 0.9997, relative_absolute_error: 0.0012, root_mean_prior_squared_error: 0.3611, root_mean_squared_error: 0.0174, root_relative_squared_error: 0.0482, scimark_benchmark: 1270.8354, usercpu_time_millis: 2.884, usercpu_time_millis_testing: 0.174, usercpu_time_millis_training: 2.71,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.999, f_measure: 0.9997, kappa: 0.9988, kb_relative_information_score: 6585.79, mean_absolute_error: 0.0003, mean_prior_absolute_error: 0.2608, number_of_instances: 6598, precision: 0.9997, predictive_accuracy: 0.9997, prior_entropy: 0.6204, recall: 0.9997, relative_absolute_error: 0.0012, root_mean_prior_squared_error: 0.3611, root_mean_squared_error: 0.0174, root_relative_squared_error: 0.0482, scimark_benchmark: 1242.6319, usercpu_time_millis: 2.957, usercpu_time_millis_testing: 0.186, usercpu_time_millis_training: 2.771,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.999, f_measure: 0.9997, kappa: 0.9988, kb_relative_information_score: 6585.79, mean_absolute_error: 0.0003, mean_prior_absolute_error: 0.2608, number_of_instances: 6598, precision: 0.9997, predictive_accuracy: 0.9997, prior_entropy: 0.6204, recall: 0.9997, relative_absolute_error: 0.0012, root_mean_prior_squared_error: 0.3611, root_mean_squared_error: 0.0174, root_relative_squared_error: 0.0482, scimark_benchmark: 1269.6376, usercpu_time_millis: 2.865, usercpu_time_millis_testing: 0.184, usercpu_time_millis_training: 2.681,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.999, f_measure: 0.9997, kappa: 0.9988, kb_relative_information_score: 6585.79, mean_absolute_error: 0.0003, mean_prior_absolute_error: 0.2608, number_of_instances: 6598, precision: 0.9997, predictive_accuracy: 0.9997, prior_entropy: 0.6204, recall: 0.9997, relative_absolute_error: 0.0012, root_mean_prior_squared_error: 0.3611, root_mean_squared_error: 0.0174, root_relative_squared_error: 0.0482, scimark_benchmark: 1226.3373, usercpu_time_millis: 2.952, usercpu_time_millis_testing: 0.186, usercpu_time_millis_training: 2.766,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.999, f_measure: 0.9997, kappa: 0.9988, kb_relative_information_score: 6585.79, mean_absolute_error: 0.0003, mean_prior_absolute_error: 0.2608, number_of_instances: 6598, precision: 0.9997, predictive_accuracy: 0.9997, prior_entropy: 0.6204, recall: 0.9997, relative_absolute_error: 0.0012, root_mean_prior_squared_error: 0.3611, root_mean_squared_error: 0.0174, root_relative_squared_error: 0.0482, scimark_benchmark: 1234.2246, usercpu_time_millis: 2.927, usercpu_time_millis_testing: 0.19, usercpu_time_millis_training: 2.737,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.999, f_measure: 0.9997, kappa: 0.9988, kb_relative_information_score: 6585.79, mean_absolute_error: 0.0003, mean_prior_absolute_error: 0.2608, number_of_instances: 6598, precision: 0.9997, predictive_accuracy: 0.9997, prior_entropy: 0.6204, recall: 0.9997, relative_absolute_error: 0.0012, root_mean_prior_squared_error: 0.3611, root_mean_squared_error: 0.0174, root_relative_squared_error: 0.0482, scimark_benchmark: 1277.2432, usercpu_time_millis: 2.977, usercpu_time_millis_testing: 0.18, usercpu_time_millis_training: 2.797,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.999, f_measure: 0.9997, kappa: 0.9988, kb_relative_information_score: 6585.79, mean_absolute_error: 0.0003, mean_prior_absolute_error: 0.2608, number_of_instances: 6598, precision: 0.9997, predictive_accuracy: 0.9997, prior_entropy: 0.6204, recall: 0.9997, relative_absolute_error: 0.0012, root_mean_prior_squared_error: 0.3611, root_mean_squared_error: 0.0174, root_relative_squared_error: 0.0482, scimark_benchmark: 1225.8418, usercpu_time_millis: 3.04, usercpu_time_millis_testing: 0.188, usercpu_time_millis_training: 2.852,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.999, f_measure: 0.9997, kappa: 0.9988, kb_relative_information_score: 6585.79, mean_absolute_error: 0.0003, mean_prior_absolute_error: 0.2608, number_of_instances: 6598, precision: 0.9997, predictive_accuracy: 0.9997, prior_entropy: 0.6204, recall: 0.9997, relative_absolute_error: 0.0012, root_mean_prior_squared_error: 0.3611, root_mean_squared_error: 0.0174, root_relative_squared_error: 0.0482, scimark_benchmark: 1270.353, usercpu_time_millis: 3.148, usercpu_time_millis_testing: 0.178, usercpu_time_millis_training: 2.97,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.999, f_measure: 0.9997, kappa: 0.9988, kb_relative_information_score: 6585.79, mean_absolute_error: 0.0003, mean_prior_absolute_error: 0.2608, number_of_instances: 6598, precision: 0.9997, predictive_accuracy: 0.9997, prior_entropy: 0.6204, recall: 0.9997, relative_absolute_error: 0.0012, root_mean_prior_squared_error: 0.3611, root_mean_squared_error: 0.0174, root_relative_squared_error: 0.0482, scimark_benchmark: 1267.8484, usercpu_time_millis: 3.15, usercpu_time_millis_testing: 0.197, usercpu_time_millis_training: 2.953,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.999, f_measure: 0.9997, kappa: 0.9988, kb_relative_information_score: 6585.79, mean_absolute_error: 0.0003, mean_prior_absolute_error: 0.2608, number_of_instances: 6598, precision: 0.9997, predictive_accuracy: 0.9997, prior_entropy: 0.6204, recall: 0.9997, relative_absolute_error: 0.0012, root_mean_prior_squared_error: 0.3611, root_mean_squared_error: 0.0174, root_relative_squared_error: 0.0482, scimark_benchmark: 1274.2072, usercpu_time_millis: 3.397, usercpu_time_millis_testing: 0.18, usercpu_time_millis_training: 3.217,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.999, f_measure: 0.9997, kappa: 0.9988, kb_relative_information_score: 6585.79, mean_absolute_error: 0.0003, mean_prior_absolute_error: 0.2608, number_of_instances: 6598, precision: 0.9997, predictive_accuracy: 0.9997, prior_entropy: 0.6204, recall: 0.9997, relative_absolute_error: 0.0012, root_mean_prior_squared_error: 0.3611, root_mean_squared_error: 0.0174, root_relative_squared_error: 0.0482, scimark_benchmark: 1237.3782, usercpu_time_millis: 2.975, usercpu_time_millis_testing: 0.188, usercpu_time_millis_training: 2.787,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.999, f_measure: 0.9997, kappa: 0.9988, kb_relative_information_score: 6585.79, mean_absolute_error: 0.0003, mean_prior_absolute_error: 0.2608, number_of_instances: 6598, precision: 0.9997, predictive_accuracy: 0.9997, prior_entropy: 0.6204, recall: 0.9997, relative_absolute_error: 0.0012, root_mean_prior_squared_error: 0.3611, root_mean_squared_error: 0.0174, root_relative_squared_error: 0.0482, scimark_benchmark: 1241.0305, usercpu_time_millis: 3.251, usercpu_time_millis_testing: 0.201, usercpu_time_millis_training: 3.05,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.999, f_measure: 0.9997, kappa: 0.9988, kb_relative_information_score: 6585.79, mean_absolute_error: 0.0003, mean_prior_absolute_error: 0.2608, number_of_instances: 6598, precision: 0.9997, predictive_accuracy: 0.9997, prior_entropy: 0.6204, recall: 0.9997, relative_absolute_error: 0.0012, root_mean_prior_squared_error: 0.3611, root_mean_squared_error: 0.0174, root_relative_squared_error: 0.0482, scimark_benchmark: 1236.1089, usercpu_time_millis: 3.029, usercpu_time_millis_testing: 0.198, usercpu_time_millis_training: 2.831,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.999, f_measure: 0.9997, kappa: 0.9988, kb_relative_information_score: 6585.79, mean_absolute_error: 0.0003, mean_prior_absolute_error: 0.2608, number_of_instances: 6598, precision: 0.9997, predictive_accuracy: 0.9997, prior_entropy: 0.6204, recall: 0.9997, relative_absolute_error: 0.0012, root_mean_prior_squared_error: 0.3611, root_mean_squared_error: 0.0174, root_relative_squared_error: 0.0482, scimark_benchmark: 1285.762, usercpu_time_millis: 2.842, usercpu_time_millis_testing: 0.185, usercpu_time_millis_training: 2.657,
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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

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From your own software

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

OpenML APIs