OpenML
Supervised Classification on heart-statlog

Supervised Classification on heart-statlog

Task 282 Supervised Classification heart-statlog 1419 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.3522, kb_relative_information_score: 0.1503, mean_absolute_error: 0.4975, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.2671, predictive_accuracy: 0.5169, prior_entropy: 0.9912, recall: 0.5169, relative_absolute_error: 0.9987, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.503, root_relative_squared_error: 1.0037, scimark_benchmark: 1686.4029, usercpu_time_millis: 0.03, usercpu_time_millis_testing: 0.01, usercpu_time_millis_training: 0.02,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.3522, kb_relative_information_score: 0.1503, mean_absolute_error: 0.4975, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.2671, predictive_accuracy: 0.5169, prior_entropy: 0.9912, recall: 0.5169, relative_absolute_error: 0.9987, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.503, root_relative_squared_error: 1.0037, scimark_benchmark: 1558.0519,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.3522, kb_relative_information_score: 0.1503, mean_absolute_error: 0.4975, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.2671, predictive_accuracy: 0.5169, prior_entropy: 0.9912, recall: 0.5169, relative_absolute_error: 0.9987, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.503, root_relative_squared_error: 1.0037, scimark_benchmark: 1534.3349, usercpu_time_millis: 0.01, usercpu_time_millis_training: 0.01,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8792, f_measure: 0.5627, kappa: 0.2385, kb_relative_information_score: 9.0756, mean_absolute_error: 0.4599, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.7841, predictive_accuracy: 0.6292, prior_entropy: 0.9912, recall: 0.6292, relative_absolute_error: 0.9232, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.4679, root_relative_squared_error: 0.9336, scimark_benchmark: 1514.2701,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.3522, kb_relative_information_score: 0.1503, mean_absolute_error: 0.4975, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.2671, predictive_accuracy: 0.5169, prior_entropy: 0.9912, recall: 0.5169, relative_absolute_error: 0.9987, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.503, root_relative_squared_error: 1.0037, scimark_benchmark: 1648.9029, usercpu_time_millis: 0.01, usercpu_time_millis_testing: 0.01,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9201, f_measure: 0.8196, kappa: 0.6389, kb_relative_information_score: 51.1472, mean_absolute_error: 0.2249, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.8223, predictive_accuracy: 0.8202, prior_entropy: 0.9912, recall: 0.8202, relative_absolute_error: 0.4514, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.3514, root_relative_squared_error: 0.7011, scimark_benchmark: 1675.3131, usercpu_time_millis: 0.02, usercpu_time_millis_testing: 0.02,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9201, f_measure: 0.8196, kappa: 0.6389, kb_relative_information_score: 51.092, mean_absolute_error: 0.2252, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.8223, predictive_accuracy: 0.8202, prior_entropy: 0.9912, recall: 0.8202, relative_absolute_error: 0.4521, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.3514, root_relative_squared_error: 0.7012, scimark_benchmark: 1672.6858,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9196, f_measure: 0.8196, kappa: 0.6389, kb_relative_information_score: 51.4855, mean_absolute_error: 0.2226, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.8223, predictive_accuracy: 0.8202, prior_entropy: 0.9912, recall: 0.8202, relative_absolute_error: 0.4469, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.3517, root_relative_squared_error: 0.7017, scimark_benchmark: 1671.2329,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.3522, kb_relative_information_score: 0.1503, mean_absolute_error: 0.4975, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.2671, predictive_accuracy: 0.5169, prior_entropy: 0.9912, recall: 0.5169, relative_absolute_error: 0.9987, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.503, root_relative_squared_error: 1.0037, scimark_benchmark: 1641.3622, usercpu_time_millis: 0.03, usercpu_time_millis_testing: 0.02, usercpu_time_millis_training: 0.01,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.3522, kb_relative_information_score: 0.1503, mean_absolute_error: 0.4975, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.2671, predictive_accuracy: 0.5169, prior_entropy: 0.9912, recall: 0.5169, relative_absolute_error: 0.9987, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.503, root_relative_squared_error: 1.0037, scimark_benchmark: 1637.2365, usercpu_time_millis: 0.03, usercpu_time_millis_testing: 0.01, usercpu_time_millis_training: 0.02,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.3522, kb_relative_information_score: 0.1503, mean_absolute_error: 0.4975, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.2671, predictive_accuracy: 0.5169, prior_entropy: 0.9912, recall: 0.5169, relative_absolute_error: 0.9987, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.503, root_relative_squared_error: 1.0037, scimark_benchmark: 1672.7672, usercpu_time_millis: 0.03, usercpu_time_millis_testing: 0.01, usercpu_time_millis_training: 0.02,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.3522, kb_relative_information_score: 0.1503, mean_absolute_error: 0.4975, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.2671, predictive_accuracy: 0.5169, prior_entropy: 0.9912, recall: 0.5169, relative_absolute_error: 0.9987, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.503, root_relative_squared_error: 1.0037, scimark_benchmark: 1668.1274, usercpu_time_millis: 0.02, usercpu_time_millis_training: 0.02,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8994, f_measure: 0.6959, kappa: 0.4276, kb_relative_information_score: 13.7212, mean_absolute_error: 0.4394, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.7961, predictive_accuracy: 0.7191, prior_entropy: 0.9912, recall: 0.7191, relative_absolute_error: 0.8822, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.4496, root_relative_squared_error: 0.8971, scimark_benchmark: 1684.7395,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.3522, kb_relative_information_score: 0.1503, mean_absolute_error: 0.4975, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.2671, predictive_accuracy: 0.5169, prior_entropy: 0.9912, recall: 0.5169, relative_absolute_error: 0.9987, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.503, root_relative_squared_error: 1.0037, scimark_benchmark: 1685.0577, usercpu_time_millis: 0.02, usercpu_time_millis_training: 0.02,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8236, f_measure: 0.6716, kappa: 0.3818, kb_relative_information_score: 8.89, mean_absolute_error: 0.461, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.7644, predictive_accuracy: 0.6966, prior_entropy: 0.9912, recall: 0.6966, relative_absolute_error: 0.9254, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.4703, root_relative_squared_error: 0.9383, scimark_benchmark: 1659.0773, usercpu_time_millis: 0.01, usercpu_time_millis_testing: 0.01,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9206, f_measure: 0.808, kappa: 0.6161, kb_relative_information_score: 50.1624, mean_absolute_error: 0.2312, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.8122, predictive_accuracy: 0.809, prior_entropy: 0.9912, recall: 0.809, relative_absolute_error: 0.4642, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.3517, root_relative_squared_error: 0.7017, scimark_benchmark: 1681.7833,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8817, f_measure: 0.7429, kappa: 0.499, kb_relative_information_score: 19.0948, mean_absolute_error: 0.413, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.7879, predictive_accuracy: 0.7528, prior_entropy: 0.9912, recall: 0.7528, relative_absolute_error: 0.829, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.4305, root_relative_squared_error: 0.859, scimark_benchmark: 1667.0295, usercpu_time_millis: 0.02, usercpu_time_millis_testing: 0.02,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9146, f_measure: 0.7964, kappa: 0.5932, kb_relative_information_score: 46.2335, mean_absolute_error: 0.2566, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.8024, predictive_accuracy: 0.7978, prior_entropy: 0.9912, recall: 0.7978, relative_absolute_error: 0.5151, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.356, root_relative_squared_error: 0.7103, scimark_benchmark: 1661.635, usercpu_time_millis: 0.02, usercpu_time_millis_testing: 0.02,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9161, f_measure: 0.7964, kappa: 0.5932, kb_relative_information_score: 46.2053, mean_absolute_error: 0.2569, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.8024, predictive_accuracy: 0.7978, prior_entropy: 0.9912, recall: 0.7978, relative_absolute_error: 0.5156, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.3552, root_relative_squared_error: 0.7088, scimark_benchmark: 1590.3441, usercpu_time_millis: 0.04, usercpu_time_millis_testing: 0.03, usercpu_time_millis_training: 0.01,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9156, f_measure: 0.808, kappa: 0.6161, kb_relative_information_score: 48.475, mean_absolute_error: 0.2415, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.8122, predictive_accuracy: 0.809, prior_entropy: 0.9912, recall: 0.809, relative_absolute_error: 0.4848, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.3566, root_relative_squared_error: 0.7116, scimark_benchmark: 1594.0073, usercpu_time_millis: 0.05, usercpu_time_millis_testing: 0.03, usercpu_time_millis_training: 0.02,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.3522, kb_relative_information_score: 0.1503, mean_absolute_error: 0.4975, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.2671, predictive_accuracy: 0.5169, prior_entropy: 0.9912, recall: 0.5169, relative_absolute_error: 0.9987, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.503, root_relative_squared_error: 1.0037, scimark_benchmark: 1588.3493, usercpu_time_millis: 0.05, usercpu_time_millis_testing: 0.03, usercpu_time_millis_training: 0.02,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.3522, kb_relative_information_score: 0.1503, mean_absolute_error: 0.4975, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.2671, predictive_accuracy: 0.5169, prior_entropy: 0.9912, recall: 0.5169, relative_absolute_error: 0.9987, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.503, root_relative_squared_error: 1.0037, scimark_benchmark: 1742.9367,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.3522, kb_relative_information_score: 0.1503, mean_absolute_error: 0.4975, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.2671, predictive_accuracy: 0.5169, prior_entropy: 0.9912, recall: 0.5169, relative_absolute_error: 0.9987, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.503, root_relative_squared_error: 1.0037, scimark_benchmark: 1717.1804, usercpu_time_millis: 0.01, usercpu_time_millis_testing: 0.01,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.3522, kb_relative_information_score: 0.1503, mean_absolute_error: 0.4975, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.2671, predictive_accuracy: 0.5169, prior_entropy: 0.9912, recall: 0.5169, relative_absolute_error: 0.9987, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.503, root_relative_squared_error: 1.0037, scimark_benchmark: 1714.4318, usercpu_time_millis: 0.02, usercpu_time_millis_testing: 0.02,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7401, f_measure: 0.6906, kappa: 0.3875, kb_relative_information_score: 28.3838, mean_absolute_error: 0.3536, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.7069, predictive_accuracy: 0.6966, prior_entropy: 0.9912, recall: 0.6966, relative_absolute_error: 0.7097, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.4636, root_relative_squared_error: 0.9249, scimark_benchmark: 1703.8632, usercpu_time_millis: 0.02, usercpu_time_millis_training: 0.02,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.3522, kb_relative_information_score: 0.1503, mean_absolute_error: 0.4975, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.2671, predictive_accuracy: 0.5169, prior_entropy: 0.9912, recall: 0.5169, relative_absolute_error: 0.9987, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.503, root_relative_squared_error: 1.0037, scimark_benchmark: 1709.5074,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.3522, kb_relative_information_score: 0.1503, mean_absolute_error: 0.4975, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.2671, predictive_accuracy: 0.5169, prior_entropy: 0.9912, recall: 0.5169, relative_absolute_error: 0.9987, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.503, root_relative_squared_error: 1.0037, scimark_benchmark: 1712.4889,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7401, f_measure: 0.741, kappa: 0.4814, kb_relative_information_score: 26.9232, mean_absolute_error: 0.3691, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.7421, predictive_accuracy: 0.7416, prior_entropy: 0.9912, recall: 0.7416, relative_absolute_error: 0.741, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.4411, root_relative_squared_error: 0.88, scimark_benchmark: 1708.2535, usercpu_time_millis: 0.01, usercpu_time_millis_training: 0.01,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.3522, kb_relative_information_score: 0.1503, mean_absolute_error: 0.4975, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.2671, predictive_accuracy: 0.5169, prior_entropy: 0.9912, recall: 0.5169, relative_absolute_error: 0.9987, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.503, root_relative_squared_error: 1.0037, scimark_benchmark: 1712.3919, usercpu_time_millis: 0.01, usercpu_time_millis_training: 0.01,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7401, f_measure: 0.741, kappa: 0.4814, kb_relative_information_score: 26.9232, mean_absolute_error: 0.3691, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.7421, predictive_accuracy: 0.7416, prior_entropy: 0.9912, recall: 0.7416, relative_absolute_error: 0.741, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.4411, root_relative_squared_error: 0.88, scimark_benchmark: 1717.0064, usercpu_time_millis: 0.02, usercpu_time_millis_training: 0.02,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.3522, kb_relative_information_score: 0.1503, mean_absolute_error: 0.4975, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.2671, predictive_accuracy: 0.5169, prior_entropy: 0.9912, recall: 0.5169, relative_absolute_error: 0.9987, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.503, root_relative_squared_error: 1.0037, scimark_benchmark: 1716.6931, usercpu_time_millis: 0.01, usercpu_time_millis_training: 0.01,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7401, f_measure: 0.741, kappa: 0.4814, kb_relative_information_score: 26.9232, mean_absolute_error: 0.3691, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.7421, predictive_accuracy: 0.7416, prior_entropy: 0.9912, recall: 0.7416, relative_absolute_error: 0.741, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.4411, root_relative_squared_error: 0.88, scimark_benchmark: 1770.0544,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.3522, kb_relative_information_score: 0.1503, mean_absolute_error: 0.4975, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.2671, predictive_accuracy: 0.5169, prior_entropy: 0.9912, recall: 0.5169, relative_absolute_error: 0.9987, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.503, root_relative_squared_error: 1.0037, scimark_benchmark: 1773.9607, usercpu_time_millis: 0.01, usercpu_time_millis_testing: 0.01,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7401, f_measure: 0.741, kappa: 0.4814, kb_relative_information_score: 26.9232, mean_absolute_error: 0.3691, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.7421, predictive_accuracy: 0.7416, prior_entropy: 0.9912, recall: 0.7416, relative_absolute_error: 0.741, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.4411, root_relative_squared_error: 0.88, scimark_benchmark: 1764.9741,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.3522, kb_relative_information_score: 0.1503, mean_absolute_error: 0.4975, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.2671, predictive_accuracy: 0.5169, prior_entropy: 0.9912, recall: 0.5169, relative_absolute_error: 0.9987, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.503, root_relative_squared_error: 1.0037, scimark_benchmark: 1761.4398,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7401, f_measure: 0.741, kappa: 0.4814, kb_relative_information_score: 26.9232, mean_absolute_error: 0.3691, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.7421, predictive_accuracy: 0.7416, prior_entropy: 0.9912, recall: 0.7416, relative_absolute_error: 0.741, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.4411, root_relative_squared_error: 0.88, scimark_benchmark: 1759.916, usercpu_time_millis: 0.02, usercpu_time_millis_training: 0.02,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7401, f_measure: 0.741, kappa: 0.4814, kb_relative_information_score: 26.9232, mean_absolute_error: 0.3691, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.7421, predictive_accuracy: 0.7416, prior_entropy: 0.9912, recall: 0.7416, relative_absolute_error: 0.741, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.4411, root_relative_squared_error: 0.88, scimark_benchmark: 1677.6806,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7401, f_measure: 0.741, kappa: 0.4814, kb_relative_information_score: 26.9232, mean_absolute_error: 0.3691, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.7421, predictive_accuracy: 0.7416, prior_entropy: 0.9912, recall: 0.7416, relative_absolute_error: 0.741, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.4411, root_relative_squared_error: 0.88, scimark_benchmark: 1656.0387, usercpu_time_millis: 0.01, usercpu_time_millis_training: 0.01,
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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