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: 1290.1311, usercpu_time_millis: 4.664, usercpu_time_millis_testing: 0.207, usercpu_time_millis_training: 4.457,
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: 1272.3901, usercpu_time_millis: 5.827, usercpu_time_millis_testing: 0.304, usercpu_time_millis_training: 5.523,
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: 1267.9351, usercpu_time_millis: 4.723, usercpu_time_millis_testing: 0.237, usercpu_time_millis_training: 4.486,
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: 1270.2893, usercpu_time_millis: 4.365, usercpu_time_millis_testing: 0.207, usercpu_time_millis_training: 4.158,
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: 1291.2938, usercpu_time_millis: 5.96, usercpu_time_millis_testing: 0.321, usercpu_time_millis_training: 5.639,
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: 1273.5221, usercpu_time_millis: 6.23, usercpu_time_millis_testing: 0.307, usercpu_time_millis_training: 5.923,
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: 1237.1918, usercpu_time_millis: 7.592, usercpu_time_millis_testing: 1.757, usercpu_time_millis_training: 5.835,
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: 1273.2004, usercpu_time_millis: 5.671, usercpu_time_millis_testing: 0.279, usercpu_time_millis_training: 5.392,
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: 1268.9062, usercpu_time_millis: 5.785, usercpu_time_millis_testing: 0.309, usercpu_time_millis_training: 5.476,
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: 1275.0183, usercpu_time_millis: 2.751, usercpu_time_millis_testing: 0.179, usercpu_time_millis_training: 2.572,
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: 1273.0962, usercpu_time_millis: 2.807, usercpu_time_millis_testing: 0.177, usercpu_time_millis_training: 2.63,
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: 1303.0754, usercpu_time_millis: 2.722, usercpu_time_millis_testing: 1.564, usercpu_time_millis_training: 1.158,
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: 1274.382, usercpu_time_millis: 2.895, usercpu_time_millis_testing: 0.2, usercpu_time_millis_training: 2.695,
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: 1269.2402, usercpu_time_millis: 3.024, usercpu_time_millis_testing: 0.189, usercpu_time_millis_training: 2.835,
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: 1282.4104, usercpu_time_millis: 2.799, usercpu_time_millis_testing: 0.181, usercpu_time_millis_training: 2.618,
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: 1296.4441, usercpu_time_millis: 2.932, usercpu_time_millis_testing: 0.184, usercpu_time_millis_training: 2.748,
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: 1299.1518, usercpu_time_millis: 2.95, usercpu_time_millis_testing: 0.177, usercpu_time_millis_training: 2.773,
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: 1279.5261, usercpu_time_millis: 2.929, usercpu_time_millis_testing: 0.184, 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: 1287.8593, usercpu_time_millis: 3.04, usercpu_time_millis_testing: 0.184, usercpu_time_millis_training: 2.856,
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: 1268.6573, usercpu_time_millis: 3.095, usercpu_time_millis_testing: 0.191, usercpu_time_millis_training: 2.904,
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: 1287.2065, usercpu_time_millis: 3.286, usercpu_time_millis_testing: 0.19, usercpu_time_millis_training: 3.096,
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: 1268.6578, usercpu_time_millis: 3.112, usercpu_time_millis_testing: 0.192, usercpu_time_millis_training: 2.92,
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: 1294.1535, usercpu_time_millis: 3.104, usercpu_time_millis_testing: 0.18, usercpu_time_millis_training: 2.924,
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: 1290.6039, usercpu_time_millis: 3.481, usercpu_time_millis_testing: 0.176, usercpu_time_millis_training: 3.305,
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: 1274.0807, usercpu_time_millis: 3.411, usercpu_time_millis_testing: 0.212, usercpu_time_millis_training: 3.199,
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: 1293.4491, usercpu_time_millis: 2.725, usercpu_time_millis_testing: 0.179, usercpu_time_millis_training: 2.546,
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: 1279.9946, usercpu_time_millis: 2.681, usercpu_time_millis_testing: 0.173, usercpu_time_millis_training: 2.508,
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: 1298.9291, usercpu_time_millis: 2.761, usercpu_time_millis_testing: 0.176, usercpu_time_millis_training: 2.585,
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: 1300.0363, usercpu_time_millis: 3.051, usercpu_time_millis_testing: 0.194, usercpu_time_millis_training: 2.857,
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: 1275.3464, usercpu_time_millis: 2.861, usercpu_time_millis_testing: 0.176, 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: 1301.3849, usercpu_time_millis: 2.763, usercpu_time_millis_testing: 0.173, usercpu_time_millis_training: 2.59,
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: 1280.3009, usercpu_time_millis: 3.065, usercpu_time_millis_testing: 0.192, 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: 1285.5152, usercpu_time_millis: 2.887, usercpu_time_millis_testing: 0.185, usercpu_time_millis_training: 2.702,
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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