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: 1765.9269, usercpu_time_millis: 0.02, usercpu_time_millis_testing: 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: 1765.6336,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9075, f_measure: 0.8073, kappa: 0.6155, kb_relative_information_score: 39.0019, mean_absolute_error: 0.3034, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.8159, predictive_accuracy: 0.809, prior_entropy: 0.9912, recall: 0.809, relative_absolute_error: 0.6091, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.3669, root_relative_squared_error: 0.732, scimark_benchmark: 1767.1401, usercpu_time_millis: 0.02, usercpu_time_millis_testing: 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: 1761.089, 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: 51.0827, mean_absolute_error: 0.2253, 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: 0.4523, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.3514, root_relative_squared_error: 0.7012, scimark_benchmark: 1747.7982, 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: 1745.6558,
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: 1745.3158,
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: 1758.1994, 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: 1758.4633, 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: 1754.4972, usercpu_time_millis: 0.01, usercpu_time_millis_training: 0.01,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7578, f_measure: 0.3522, kb_relative_information_score: 0.2333, mean_absolute_error: 0.4971, 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: 0.9979, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.5027, root_relative_squared_error: 1.003, scimark_benchmark: 1756.2194, usercpu_time_millis: 0.02, usercpu_time_millis_training: 0.02,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9176, f_measure: 0.808, kappa: 0.6161, kb_relative_information_score: 49.9605, mean_absolute_error: 0.2322, 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: 0.4661, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.3539, root_relative_squared_error: 0.7062, scimark_benchmark: 1756.9826, usercpu_time_millis: 0.02, usercpu_time_millis_testing: 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: 1761.7433, 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: 50.8135, mean_absolute_error: 0.227, 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: 0.4556, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.3521, root_relative_squared_error: 0.7026, scimark_benchmark: 1760.4923,
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: 1763.2281, usercpu_time_millis: 0.02, usercpu_time_millis_testing: 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: 1763.1678, 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: 50.3109, mean_absolute_error: 0.2302, 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: 0.4622, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.3518, root_relative_squared_error: 0.702, scimark_benchmark: 1754.3236,
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: 1761.9611,
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: 1758.1716,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8847, f_measure: 0.3522, kb_relative_information_score: 3.2339, mean_absolute_error: 0.4843, 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: 0.9721, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.4902, root_relative_squared_error: 0.9781, scimark_benchmark: 1760.0349,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9156, f_measure: 0.808, kappa: 0.6161, kb_relative_information_score: 48.5251, mean_absolute_error: 0.2412, 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: 0.4841, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.3567, root_relative_squared_error: 0.7117, scimark_benchmark: 1761.2028,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9196, f_measure: 0.8196, kappa: 0.6389, kb_relative_information_score: 50.5989, mean_absolute_error: 0.2283, 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: 0.4584, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.3522, root_relative_squared_error: 0.7027, scimark_benchmark: 1759.2472,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9156, f_measure: 0.7964, kappa: 0.5932, kb_relative_information_score: 48.4151, mean_absolute_error: 0.2419, 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: 0.4856, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.3566, root_relative_squared_error: 0.7115, scimark_benchmark: 1762.2568,
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: 1762.0809, usercpu_time_millis: 0.02, usercpu_time_millis_testing: 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: 1762.3167, usercpu_time_millis: 0.01, usercpu_time_millis_testing: 0.01,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7578, f_measure: 0.3522, kb_relative_information_score: 3.4186, mean_absolute_error: 0.4838, 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: 0.9712, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.4899, root_relative_squared_error: 0.9775, scimark_benchmark: 1760.0996, usercpu_time_millis: 0.01, usercpu_time_millis_testing: 0.01,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.907, f_measure: 0.7964, kappa: 0.5932, kb_relative_information_score: 40.2384, mean_absolute_error: 0.2957, 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: 0.5936, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.3646, root_relative_squared_error: 0.7274, scimark_benchmark: 1763.3516, usercpu_time_millis: 0.01, usercpu_time_millis_testing: 0.01,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9075, f_measure: 0.8073, kappa: 0.6155, kb_relative_information_score: 39.9402, mean_absolute_error: 0.2972, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.8159, predictive_accuracy: 0.809, prior_entropy: 0.9912, recall: 0.809, relative_absolute_error: 0.5966, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.3649, root_relative_squared_error: 0.728, scimark_benchmark: 1768.0949, 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: 1503.627, usercpu_time_millis: 0.04, usercpu_time_millis_testing: 0.04,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8953, f_measure: 0.3522, kb_relative_information_score: 1.9204, mean_absolute_error: 0.4897, 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: 0.983, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.4954, root_relative_squared_error: 0.9884, scimark_benchmark: 1504.0146, usercpu_time_millis: 0.03, usercpu_time_millis_testing: 0.03,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9146, f_measure: 0.7964, kappa: 0.5932, kb_relative_information_score: 46.8853, mean_absolute_error: 0.2522, 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: 0.5063, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.3559, root_relative_squared_error: 0.7101, scimark_benchmark: 1504.5004, 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: 0.7401, 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: 1765.0506,
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: 1739.3328,
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: 1756.0655,
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: 1761.0886,
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: 1759.7285,
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: 1761.1537,
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: 1764.8694, 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: 1774.3677,
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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