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: 1292.5662, usercpu_time_millis: 3.046, usercpu_time_millis_testing: 0.191, usercpu_time_millis_training: 2.855,
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: 1287.9552, usercpu_time_millis: 2.816, usercpu_time_millis_testing: 0.173, usercpu_time_millis_training: 2.643,
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: 1288.4199, usercpu_time_millis: 2.98, usercpu_time_millis_testing: 0.19, usercpu_time_millis_training: 2.79,
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: 1287.7208, usercpu_time_millis: 2.812, usercpu_time_millis_testing: 0.178, usercpu_time_millis_training: 2.634,
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: 1281.9469, usercpu_time_millis: 2.884, usercpu_time_millis_testing: 0.191, usercpu_time_millis_training: 2.693,
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: 1262.257, usercpu_time_millis: 3.003, usercpu_time_millis_testing: 0.183, usercpu_time_millis_training: 2.82,
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: 1283.5029, usercpu_time_millis: 2.791, usercpu_time_millis_testing: 0.186, usercpu_time_millis_training: 2.605,
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: 1269.0489, usercpu_time_millis: 3.473, usercpu_time_millis_testing: 0.265, usercpu_time_millis_training: 3.208,
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: 1290.5585, usercpu_time_millis: 3.205, usercpu_time_millis_testing: 0.18, usercpu_time_millis_training: 3.025,
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: 1288.3033, usercpu_time_millis: 3.142, usercpu_time_millis_testing: 0.174, usercpu_time_millis_training: 2.968,
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: 1310.9551, usercpu_time_millis: 2.708, usercpu_time_millis_testing: 0.172, usercpu_time_millis_training: 2.536,
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: 1273.5423, usercpu_time_millis: 2.798, usercpu_time_millis_testing: 0.176, usercpu_time_millis_training: 2.622,
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: 1302.034, usercpu_time_millis: 2.834, usercpu_time_millis_testing: 0.183, usercpu_time_millis_training: 2.651,
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: 1270.8118, usercpu_time_millis: 2.805, usercpu_time_millis_testing: 0.178, 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: 1271.6315, usercpu_time_millis: 3.024, usercpu_time_millis_testing: 0.191, 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: 1282.107, usercpu_time_millis: 2.793, usercpu_time_millis_testing: 0.18, usercpu_time_millis_training: 2.613,
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: 1289.2999, usercpu_time_millis: 2.781, usercpu_time_millis_testing: 0.186, usercpu_time_millis_training: 2.595,
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: 1284.3579, usercpu_time_millis: 2.7, usercpu_time_millis_testing: 0.177, usercpu_time_millis_training: 2.523,
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: 1285.0324, usercpu_time_millis: 2.839, usercpu_time_millis_testing: 0.193, usercpu_time_millis_training: 2.646,
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: 1287.1739, 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: 1285.1305, usercpu_time_millis: 3.061, usercpu_time_millis_testing: 0.197, 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: 1287.9134, usercpu_time_millis: 2.932, usercpu_time_millis_testing: 0.193, usercpu_time_millis_training: 2.739,
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: 1291.3181, usercpu_time_millis: 3.639, usercpu_time_millis_testing: 0.201, usercpu_time_millis_training: 3.438,
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: 1248.4804, usercpu_time_millis: 3.736, usercpu_time_millis_testing: 0.186, usercpu_time_millis_training: 3.55,
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: 1285.1668, usercpu_time_millis: 4.671, usercpu_time_millis_testing: 0.241, usercpu_time_millis_training: 4.43,
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: 1270.6887, usercpu_time_millis: 3.616, usercpu_time_millis_testing: 0.186, usercpu_time_millis_training: 3.43,
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: 1266.7465, usercpu_time_millis: 4.127, usercpu_time_millis_testing: 0.219, usercpu_time_millis_training: 3.908,
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: 1265.2975, usercpu_time_millis: 5.281, usercpu_time_millis_testing: 0.302, usercpu_time_millis_training: 4.979,
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: 1284.7193, usercpu_time_millis: 2.93, usercpu_time_millis_testing: 0.185, 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: 1275.2704, usercpu_time_millis: 2.97, usercpu_time_millis_testing: 0.183, 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: 1280.5383, usercpu_time_millis: 2.865, usercpu_time_millis_testing: 0.18, usercpu_time_millis_training: 2.685,
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: 1291.2717, usercpu_time_millis: 2.993, usercpu_time_millis_testing: 0.187, usercpu_time_millis_training: 2.806,
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: 1286.5881, usercpu_time_millis: 3.021, usercpu_time_millis_testing: 0.196, usercpu_time_millis_training: 2.825,
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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