OpenML
Supervised Classification on heart-statlog

Supervised Classification on heart-statlog

Task 282 Supervised Classification heart-statlog 1420 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9201, f_measure: 0.8196, kappa: 0.6389, kb_relative_information_score: 50.3208, mean_absolute_error: 0.2301, 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: 0.4619, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.3523, root_relative_squared_error: 0.7029, scimark_benchmark: 1712.0472, 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: 1677.8599,
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: 1637.4588,
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: 1759.5409,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9201, f_measure: 0.8196, kappa: 0.6389, kb_relative_information_score: 51.0979, 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: 0.452, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.3516, root_relative_squared_error: 0.7016, scimark_benchmark: 1753.2197, usercpu_time_millis: 0.02, usercpu_time_millis_testing: 0.02,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7578, f_measure: 0.3522, kb_relative_information_score: 1.7647, mean_absolute_error: 0.4904, 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: 0.9844, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.496, root_relative_squared_error: 0.9897, scimark_benchmark: 1756.9575,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9034, f_measure: 0.8073, kappa: 0.6155, kb_relative_information_score: 41.5986, mean_absolute_error: 0.2875, 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: 0.5771, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.364, root_relative_squared_error: 0.7263, scimark_benchmark: 1743.858, usercpu_time_millis: 0.02, usercpu_time_millis_training: 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: 51.076, 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: 0.3522, root_relative_squared_error: 0.7028, scimark_benchmark: 1735.4309,
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: 1744.3433, 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: 1744.5539, usercpu_time_millis: 0.01, usercpu_time_millis_testing: 0.01,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8969, f_measure: 0.8073, kappa: 0.6155, kb_relative_information_score: 37.2686, mean_absolute_error: 0.3139, 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: 0.6301, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.374, root_relative_squared_error: 0.7462, scimark_benchmark: 1742.3991, 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: 1723.0196,
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: 1724.0796, 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: 1731.4039,
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: 1759.842,
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: 1749.3018, 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: 1748.4037,
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: 1749.6595, 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: 1745.6513, 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: 1743.513,
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: 1744.6197, usercpu_time_millis: 0.02, usercpu_time_millis_training: 0.02,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.868, f_measure: 0.3522, kb_relative_information_score: 6.1983, mean_absolute_error: 0.4722, 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: 0.948, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.4793, root_relative_squared_error: 0.9564, scimark_benchmark: 1726.1864, 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: 1753.7627,
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: 1755.5648,
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: 1751.1207,
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: 1750.3377,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9181, f_measure: 0.808, kappa: 0.6161, kb_relative_information_score: 49.1055, mean_absolute_error: 0.2375, 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: 0.4768, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.3545, root_relative_squared_error: 0.7074, scimark_benchmark: 1745.6401, usercpu_time_millis: 0.01, usercpu_time_millis_training: 0.01,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9196, f_measure: 0.8196, kappa: 0.6389, kb_relative_information_score: 50.9872, mean_absolute_error: 0.2258, 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: 0.4533, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.3521, root_relative_squared_error: 0.7026, scimark_benchmark: 1746.1051, 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: 1750.8295, 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: 1755.6917, usercpu_time_millis: 0.02, usercpu_time_millis_testing: 0.02,
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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: 1788.3115,
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: 1671.155, 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: 1661.6478, 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: 1658.7692, 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: 1754.9078, 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: 1748.7587,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.861, f_measure: 0.775, kappa: 0.5494, kb_relative_information_score: 46.7147, mean_absolute_error: 0.2468, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.7755, predictive_accuracy: 0.7753, prior_entropy: 0.9912, recall: 0.7753, relative_absolute_error: 0.4955, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.3929, root_relative_squared_error: 0.7839, scimark_benchmark: 936.2574, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.3522, kb_relative_information_score: 2.5698, mean_absolute_error: 0.4831, 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: 0.9699, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.6951, root_relative_squared_error: 1.3869, scimark_benchmark: 927.2882, usercpu_time_millis: 40, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8777, f_measure: 0.8052, kappa: 0.6143, kb_relative_information_score: 49.4802, mean_absolute_error: 0.2305, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.8278, predictive_accuracy: 0.809, prior_entropy: 0.9912, recall: 0.809, relative_absolute_error: 0.4628, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.3966, root_relative_squared_error: 0.7912, scimark_benchmark: 938.1282, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8777, f_measure: 0.8052, kappa: 0.6143, kb_relative_information_score: 49.4802, mean_absolute_error: 0.2305, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.8278, predictive_accuracy: 0.809, prior_entropy: 0.9912, recall: 0.809, relative_absolute_error: 0.4628, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.3966, root_relative_squared_error: 0.7912, scimark_benchmark: 933.3455, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.865, f_measure: 0.7846, kappa: 0.5703, kb_relative_information_score: 39.7012, mean_absolute_error: 0.2948, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.7927, predictive_accuracy: 0.7865, prior_entropy: 0.9912, recall: 0.7865, relative_absolute_error: 0.5918, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.3816, root_relative_squared_error: 0.7615, scimark_benchmark: 941.4991, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9226, f_measure: 0.819, kappa: 0.6384, kb_relative_information_score: 51.5606, mean_absolute_error: 0.2245, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.8254, predictive_accuracy: 0.8202, prior_entropy: 0.9912, recall: 0.8202, relative_absolute_error: 0.4507, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.3456, root_relative_squared_error: 0.6896, scimark_benchmark: 730.6551, usercpu_time_millis: 560, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 550,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8777, f_measure: 0.8052, kappa: 0.6143, kb_relative_information_score: 49.4802, mean_absolute_error: 0.2305, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.8278, predictive_accuracy: 0.809, prior_entropy: 0.9912, recall: 0.809, relative_absolute_error: 0.4628, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.3966, root_relative_squared_error: 0.7912, scimark_benchmark: 932.438,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8885, f_measure: 0.8063, kappa: 0.6149, kb_relative_information_score: 42.9694, mean_absolute_error: 0.2727, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.821, predictive_accuracy: 0.809, prior_entropy: 0.9912, recall: 0.809, relative_absolute_error: 0.5474, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.3753, root_relative_squared_error: 0.7488, scimark_benchmark: 901.4991, usercpu_time_millis: 100, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 90,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9029, f_measure: 0.8182, kappa: 0.6378, kb_relative_information_score: 45.0392, mean_absolute_error: 0.2622, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.8299, predictive_accuracy: 0.8202, prior_entropy: 0.9912, recall: 0.8202, relative_absolute_error: 0.5263, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.3636, root_relative_squared_error: 0.7255, scimark_benchmark: 763.3895, usercpu_time_millis: 3140, usercpu_time_millis_testing: 1610, usercpu_time_millis_training: 1530,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.91, f_measure: 0.8182, kappa: 0.6378, kb_relative_information_score: 45.9169, mean_absolute_error: 0.2572, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.8299, predictive_accuracy: 0.8202, prior_entropy: 0.9912, recall: 0.8202, relative_absolute_error: 0.5163, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.361, root_relative_squared_error: 0.7203, scimark_benchmark: 859.5223, usercpu_time_millis: 860, usercpu_time_millis_testing: 270, usercpu_time_millis_training: 590,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9055, f_measure: 0.8073, kappa: 0.6155, kb_relative_information_score: 44.9716, mean_absolute_error: 0.2628, 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: 0.5275, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.3646, root_relative_squared_error: 0.7275, scimark_benchmark: 935.0213, usercpu_time_millis: 370, usercpu_time_millis_testing: 90, usercpu_time_millis_training: 280,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.889, f_measure: 0.7727, kappa: 0.5473, kb_relative_information_score: 43.7377, mean_absolute_error: 0.2643, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.7832, predictive_accuracy: 0.7753, prior_entropy: 0.9912, recall: 0.7753, relative_absolute_error: 0.5306, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.3849, root_relative_squared_error: 0.7681, scimark_benchmark: 911.2316, usercpu_time_millis: 190, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 150,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9029, f_measure: 0.7955, kappa: 0.5926, kb_relative_information_score: 45.3655, mean_absolute_error: 0.2578, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.8066, predictive_accuracy: 0.7978, prior_entropy: 0.9912, recall: 0.7978, relative_absolute_error: 0.5176, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.3708, root_relative_squared_error: 0.7398, scimark_benchmark: 889.4922, usercpu_time_millis: 110, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 90,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9017, f_measure: 0.8182, kappa: 0.6378, kb_relative_information_score: 53.2895, mean_absolute_error: 0.2089, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.8299, predictive_accuracy: 0.8202, prior_entropy: 0.9912, recall: 0.8202, relative_absolute_error: 0.4194, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.3781, root_relative_squared_error: 0.7544, scimark_benchmark: 926.5859, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9017, f_measure: 0.8182, kappa: 0.6378, kb_relative_information_score: 53.2895, mean_absolute_error: 0.2089, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.8299, predictive_accuracy: 0.8202, prior_entropy: 0.9912, recall: 0.8202, relative_absolute_error: 0.4194, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.3781, root_relative_squared_error: 0.7544, scimark_benchmark: 926.5859, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9017, f_measure: 0.8182, kappa: 0.6378, kb_relative_information_score: 53.2895, mean_absolute_error: 0.2089, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.8299, predictive_accuracy: 0.8202, prior_entropy: 0.9912, recall: 0.8202, relative_absolute_error: 0.4194, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.3781, root_relative_squared_error: 0.7544, scimark_benchmark: 894.7131, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9017, f_measure: 0.8182, kappa: 0.6378, kb_relative_information_score: 53.2895, mean_absolute_error: 0.2089, mean_prior_absolute_error: 0.4981, number_of_instances: 89, precision: 0.8299, predictive_accuracy: 0.8202, prior_entropy: 0.9912, recall: 0.8202, relative_absolute_error: 0.4194, root_mean_prior_squared_error: 0.5012, root_mean_squared_error: 0.3781, root_relative_squared_error: 0.7544, scimark_benchmark: 929.0296, usercpu_time_millis: 10, usercpu_time_millis_training: 10,

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