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: 1276.0294, usercpu_time_millis: 3.006, usercpu_time_millis_testing: 0.179, usercpu_time_millis_training: 2.827,
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: 1281.0895, usercpu_time_millis: 2.829, usercpu_time_millis_testing: 0.118, usercpu_time_millis_training: 2.711,
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: 1261.44, usercpu_time_millis: 2.852, usercpu_time_millis_testing: 0.177, usercpu_time_millis_training: 2.675,
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: 1237.5201, usercpu_time_millis: 3.022, usercpu_time_millis_testing: 0.189, usercpu_time_millis_training: 2.833,
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: 1249.4518, usercpu_time_millis: 3.182, usercpu_time_millis_testing: 0.2, usercpu_time_millis_training: 2.982,
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: 1233.737, usercpu_time_millis: 2.907, usercpu_time_millis_testing: 0.194, usercpu_time_millis_training: 2.713,
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: 1275.3183, usercpu_time_millis: 2.779, usercpu_time_millis_testing: 0.176, usercpu_time_millis_training: 2.603,
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: 1235.8696, usercpu_time_millis: 3.026, usercpu_time_millis_testing: 0.188, 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: 1278.6629, usercpu_time_millis: 2.821, usercpu_time_millis_testing: 0.179, usercpu_time_millis_training: 2.642,
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: 1273.2516, usercpu_time_millis: 2.804, usercpu_time_millis_testing: 0.192, usercpu_time_millis_training: 2.612,
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: 1244.4532, usercpu_time_millis: 2.887, usercpu_time_millis_testing: 0.191, usercpu_time_millis_training: 2.696,
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: 1267.3149, usercpu_time_millis: 2.847, usercpu_time_millis_testing: 0.182, usercpu_time_millis_training: 2.665,
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: 1230.6471, usercpu_time_millis: 3.056, usercpu_time_millis_testing: 0.185, usercpu_time_millis_training: 2.871,
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: 1230.0954, usercpu_time_millis: 3.289, usercpu_time_millis_testing: 0.205, usercpu_time_millis_training: 3.084,
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: 1228.4103, usercpu_time_millis: 3.882, usercpu_time_millis_testing: 0.188, usercpu_time_millis_training: 3.694,
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: 1278.2434, usercpu_time_millis: 3.304, usercpu_time_millis_testing: 0.232, usercpu_time_millis_training: 3.072,
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: 1276.1885, usercpu_time_millis: 4.042, usercpu_time_millis_testing: 0.218, usercpu_time_millis_training: 3.824,
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: 1237.118, usercpu_time_millis: 2.955, usercpu_time_millis_testing: 0.185, usercpu_time_millis_training: 2.77,
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: 1243.4422, usercpu_time_millis: 3.052, usercpu_time_millis_testing: 0.204, usercpu_time_millis_training: 2.848,
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: 1272.1437, usercpu_time_millis: 2.893, usercpu_time_millis_testing: 0.181, usercpu_time_millis_training: 2.712,
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: 1228.7344, usercpu_time_millis: 3.064, usercpu_time_millis_testing: 0.191, usercpu_time_millis_training: 2.873,
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: 1277.3572, usercpu_time_millis: 2.92, usercpu_time_millis_testing: 0.186, usercpu_time_millis_training: 2.734,
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: 1231.5138, usercpu_time_millis: 2.956, usercpu_time_millis_testing: 0.191, usercpu_time_millis_training: 2.765,
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: 1220.0187, usercpu_time_millis: 2.963, usercpu_time_millis_testing: 0.198, usercpu_time_millis_training: 2.765,
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: 1278.9976, usercpu_time_millis: 2.736, usercpu_time_millis_testing: 0.177, usercpu_time_millis_training: 2.559,
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: 1264.9223, usercpu_time_millis: 2.911, usercpu_time_millis_testing: 0.183, usercpu_time_millis_training: 2.728,
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: 1274.2685, usercpu_time_millis: 2.853, usercpu_time_millis_testing: 0.189, usercpu_time_millis_training: 2.664,
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: 1270.3704, usercpu_time_millis: 2.81, usercpu_time_millis_testing: 0.182, usercpu_time_millis_training: 2.628,
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: 1268.4737, usercpu_time_millis: 2.97, usercpu_time_millis_testing: 0.199, 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: 1276.4389, usercpu_time_millis: 3.159, usercpu_time_millis_testing: 0.19, usercpu_time_millis_training: 2.969,
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: 1221.6459, usercpu_time_millis: 3.221, usercpu_time_millis_testing: 0.198, usercpu_time_millis_training: 3.023,
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: 1236.4718, usercpu_time_millis: 3.144, usercpu_time_millis_testing: 0.184, usercpu_time_millis_training: 2.96,
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: 1246.9994, usercpu_time_millis: 3.14, usercpu_time_millis_testing: 0.189, usercpu_time_millis_training: 2.951,
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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