OpenML
Supervised Classification on musk

Supervised Classification on musk

Task 146082 Supervised Classification musk 13306 runs submitted
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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: 1278.1804, usercpu_time_millis: 2.811, usercpu_time_millis_testing: 0.185, usercpu_time_millis_training: 2.626,
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: 1282.9605, usercpu_time_millis: 2.901, usercpu_time_millis_testing: 0.184, usercpu_time_millis_training: 2.717,
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: 1291.4872, usercpu_time_millis: 2.959, usercpu_time_millis_testing: 0.189, 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: 1283.8023, usercpu_time_millis: 4.347, usercpu_time_millis_testing: 0.183, usercpu_time_millis_training: 4.164,
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: 1288.6801, usercpu_time_millis: 3.05, usercpu_time_millis_testing: -1.126, usercpu_time_millis_training: 4.176,
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: 1261.4487, usercpu_time_millis: 3.024, usercpu_time_millis_testing: 0.184, 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: 1287.5077, usercpu_time_millis: 3.215, usercpu_time_millis_testing: 1.509, usercpu_time_millis_training: 1.706,
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: 1267.6864, usercpu_time_millis: 3.639, usercpu_time_millis_testing: 0.234, usercpu_time_millis_training: 3.405,
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: 1266.0011, usercpu_time_millis: 3.305, usercpu_time_millis_testing: 0.196, usercpu_time_millis_training: 3.109,
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: 1288.0242, usercpu_time_millis: 3.225, usercpu_time_millis_testing: 0.18, usercpu_time_millis_training: 3.045,
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: 1257.4288, usercpu_time_millis: 3.475, usercpu_time_millis_testing: 0.255, usercpu_time_millis_training: 3.22,
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: 1275.2301, usercpu_time_millis: 2.69, usercpu_time_millis_testing: 0.178, usercpu_time_millis_training: 2.512,
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: 1295.7284, usercpu_time_millis: 2.776, usercpu_time_millis_testing: -1.162, usercpu_time_millis_training: 3.938,
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: 1298.7837, usercpu_time_millis: 2.778, usercpu_time_millis_testing: 0.181, 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: 1273.9498, usercpu_time_millis: 2.812, usercpu_time_millis_testing: 0.186, usercpu_time_millis_training: 2.626,
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: 1290.2701, usercpu_time_millis: 2.816, usercpu_time_millis_testing: 0.181, usercpu_time_millis_training: 2.635,
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: 1276.2428, usercpu_time_millis: 2.803, usercpu_time_millis_testing: 0.176, usercpu_time_millis_training: 2.627,
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: 1289.9281, usercpu_time_millis: 2.887, usercpu_time_millis_testing: 0.195, usercpu_time_millis_training: 2.692,
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: 1279.6131, usercpu_time_millis: 2.883, usercpu_time_millis_testing: 0.194, usercpu_time_millis_training: 2.689,
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: 1289.861, usercpu_time_millis: 3.15, usercpu_time_millis_testing: 0.19, 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: 1277.4483, usercpu_time_millis: 2.944, usercpu_time_millis_testing: 0.185, usercpu_time_millis_training: 2.759,
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: 1298.8181, usercpu_time_millis: 2.976, usercpu_time_millis_testing: 0.176, usercpu_time_millis_training: 2.8,
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: 1268.9613, usercpu_time_millis: 3.137, usercpu_time_millis_testing: 0.182, usercpu_time_millis_training: 2.955,
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: 1294.8287, usercpu_time_millis: 3.092, usercpu_time_millis_testing: 0.177, usercpu_time_millis_training: 2.915,
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: 1293.7117, usercpu_time_millis: 3.079, usercpu_time_millis_testing: 0.181, usercpu_time_millis_training: 2.898,
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: 1258.1077, usercpu_time_millis: 3.184, usercpu_time_millis_testing: 0.184, usercpu_time_millis_training: 3,
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: 1271.2794, usercpu_time_millis: 3.206, usercpu_time_millis_testing: 0.182, usercpu_time_millis_training: 3.024,
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: 1276.2882, usercpu_time_millis: 2.902, usercpu_time_millis_testing: 0.19, 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: 1293.304, usercpu_time_millis: 2.913, usercpu_time_millis_testing: 0.183, usercpu_time_millis_training: 2.73,
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: 1269.7821, usercpu_time_millis: 2.876, usercpu_time_millis_testing: 0.19, usercpu_time_millis_training: 2.686,
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: 1288.1222, usercpu_time_millis: 2.884, usercpu_time_millis_testing: 0.187, usercpu_time_millis_training: 2.697,
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: 1275.7787, usercpu_time_millis: 1.622, usercpu_time_millis_testing: 0.194, usercpu_time_millis_training: 1.428,
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: 1294.9713, usercpu_time_millis: 3.004, usercpu_time_millis_testing: 0.19, usercpu_time_millis_training: 2.814,
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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