Task
Supervised Classification on diggle_table_a1

Supervised Classification on diggle_table_a1

Task 4387 Supervised Classification diggle_table_a1 226 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.712, f_measure: 0.6626, kappa: 0.3241, kb_relative_information_score: 0.2414, mean_absolute_error: 0.3863, mean_prior_absolute_error: 0.4992, weighted_recall: 0.6625, number_of_instances: 480, precision: 0.6626, predictive_accuracy: 0.6625, prior_entropy: 0.9987, relative_absolute_error: 0.774, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.479, root_relative_squared_error: 0.9588, scimark_benchmark: 931.1106, unweighted_recall: 0.6621,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.751, f_measure: 0.7542, kappa: 0.5078, kb_relative_information_score: 0.2923, mean_absolute_error: 0.3716, mean_prior_absolute_error: 0.4992, weighted_recall: 0.7542, number_of_instances: 480, precision: 0.7544, predictive_accuracy: 0.7542, prior_entropy: 0.9987, relative_absolute_error: 0.7445, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.4545, root_relative_squared_error: 0.9098, scimark_benchmark: 979.7764, unweighted_recall: 0.7541,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4259, f_measure: 0.4368, kappa: -0.0132, kb_relative_information_score: -6.2723, mean_absolute_error: 0.5044, mean_prior_absolute_error: 0.4992, number_of_instances: 480, precision: 0.4884, predictive_accuracy: 0.5083, prior_entropy: 0.9988, recall: 0.5083, relative_absolute_error: 1.0105, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.5172, root_relative_squared_error: 1.0352, scimark_benchmark: 906.0979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5819, f_measure: 0.5829, kappa: 0.1641, kb_relative_information_score: 79.0289, mean_absolute_error: 0.4167, mean_prior_absolute_error: 0.4992, number_of_instances: 480, precision: 0.5828, predictive_accuracy: 0.5833, prior_entropy: 0.9988, recall: 0.5833, relative_absolute_error: 0.8347, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.6455, root_relative_squared_error: 1.2921,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7078, f_measure: 0.6647, kappa: 0.33, kb_relative_information_score: 115.0146, mean_absolute_error: 0.3876, mean_prior_absolute_error: 0.4992, number_of_instances: 480, precision: 0.6664, predictive_accuracy: 0.6646, prior_entropy: 0.9988, recall: 0.6646, relative_absolute_error: 0.7765, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.4871, root_relative_squared_error: 0.975, scimark_benchmark: 972.587,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6888, f_measure: 0.6373, kappa: 0.2732, kb_relative_information_score: 125.6308, mean_absolute_error: 0.3718, mean_prior_absolute_error: 0.4992, number_of_instances: 480, precision: 0.6373, predictive_accuracy: 0.6375, prior_entropy: 0.9988, recall: 0.6375, relative_absolute_error: 0.7448, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.5296, root_relative_squared_error: 1.06, scimark_benchmark: 934.3687,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5819, f_measure: 0.5829, kappa: 0.1641, kb_relative_information_score: 79.0289, mean_absolute_error: 0.4167, mean_prior_absolute_error: 0.4992, number_of_instances: 480, precision: 0.5828, predictive_accuracy: 0.5833, prior_entropy: 0.9988, recall: 0.5833, relative_absolute_error: 0.8347, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.6455, root_relative_squared_error: 1.2921,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5819, f_measure: 0.5829, kappa: 0.1641, kb_relative_information_score: 79.0289, mean_absolute_error: 0.4167, mean_prior_absolute_error: 0.4992, number_of_instances: 480, precision: 0.5828, predictive_accuracy: 0.5833, prior_entropy: 0.9988, recall: 0.5833, relative_absolute_error: 0.8347, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.6455, root_relative_squared_error: 1.2921,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7606, f_measure: 0.7605, kappa: 0.5206, kb_relative_information_score: 249.4219, mean_absolute_error: 0.2396, mean_prior_absolute_error: 0.4992, number_of_instances: 480, precision: 0.7609, predictive_accuracy: 0.7604, prior_entropy: 0.9988, recall: 0.7604, relative_absolute_error: 0.48, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.4895, root_relative_squared_error: 0.9798,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.573, f_measure: 0.5728, kappa: 0.1469, kb_relative_information_score: 73.015, mean_absolute_error: 0.4229, mean_prior_absolute_error: 0.4992, number_of_instances: 480, precision: 0.5762, predictive_accuracy: 0.5771, prior_entropy: 0.9988, recall: 0.5771, relative_absolute_error: 0.8472, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.6503, root_relative_squared_error: 1.3018, scimark_benchmark: 944.1067,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.573, f_measure: 0.5728, kappa: 0.1469, kb_relative_information_score: 73.015, mean_absolute_error: 0.4229, mean_prior_absolute_error: 0.4992, number_of_instances: 480, precision: 0.5762, predictive_accuracy: 0.5771, prior_entropy: 0.9988, recall: 0.5771, relative_absolute_error: 0.8472, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.6503, root_relative_squared_error: 1.3018, scimark_benchmark: 916.0735, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4249, f_measure: 0.4368, kappa: -0.0132, kb_relative_information_score: -7.5662, mean_absolute_error: 0.5058, mean_prior_absolute_error: 0.4992, number_of_instances: 480, precision: 0.4884, predictive_accuracy: 0.5083, prior_entropy: 0.9988, recall: 0.5083, relative_absolute_error: 1.0133, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.5173, root_relative_squared_error: 1.0356, scimark_benchmark: 941.6675,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4249, f_measure: 0.4368, kappa: -0.0132, kb_relative_information_score: -7.5735, mean_absolute_error: 0.5058, mean_prior_absolute_error: 0.4992, number_of_instances: 480, precision: 0.4884, predictive_accuracy: 0.5083, prior_entropy: 0.9988, recall: 0.5083, relative_absolute_error: 1.0133, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.5175, root_relative_squared_error: 1.036, scimark_benchmark: 941.6675,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4249, f_measure: 0.4368, kappa: -0.0132, kb_relative_information_score: -7.5735, mean_absolute_error: 0.5058, mean_prior_absolute_error: 0.4992, number_of_instances: 480, precision: 0.4884, predictive_accuracy: 0.5083, prior_entropy: 0.9988, recall: 0.5083, relative_absolute_error: 1.0133, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.5175, root_relative_squared_error: 1.036, scimark_benchmark: 941.6675,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6984, f_measure: 0.6521, kappa: 0.3028, kb_relative_information_score: 81.2465, mean_absolute_error: 0.4252, mean_prior_absolute_error: 0.4992, number_of_instances: 480, precision: 0.652, predictive_accuracy: 0.6521, prior_entropy: 0.9988, recall: 0.6521, relative_absolute_error: 0.8518, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.4717, root_relative_squared_error: 0.9441, scimark_benchmark: 938.191,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7451, f_measure: 0.7313, kappa: 0.4632, kb_relative_information_score: 118.0632, mean_absolute_error: 0.3948, mean_prior_absolute_error: 0.4992, number_of_instances: 480, precision: 0.7332, predictive_accuracy: 0.7313, prior_entropy: 0.9988, recall: 0.7313, relative_absolute_error: 0.7909, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.4576, root_relative_squared_error: 0.9159, scimark_benchmark: 938.191, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5858, f_measure: 0.5937, kappa: 0.1967, kb_relative_information_score: 51.406, mean_absolute_error: 0.4506, mean_prior_absolute_error: 0.4992, number_of_instances: 480, precision: 0.6027, predictive_accuracy: 0.5958, prior_entropy: 0.9988, recall: 0.5958, relative_absolute_error: 0.9026, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.5181, root_relative_squared_error: 1.0371, scimark_benchmark: 905.2959,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.573, f_measure: 0.5728, kappa: 0.1469, kb_relative_information_score: 73.015, mean_absolute_error: 0.4229, mean_prior_absolute_error: 0.4992, number_of_instances: 480, precision: 0.5762, predictive_accuracy: 0.5771, prior_entropy: 0.9988, recall: 0.5771, relative_absolute_error: 0.8472, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.6503, root_relative_squared_error: 1.3018, scimark_benchmark: 947.1781,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.573, f_measure: 0.5728, kappa: 0.1469, kb_relative_information_score: 73.015, mean_absolute_error: 0.4229, mean_prior_absolute_error: 0.4992, number_of_instances: 480, precision: 0.5762, predictive_accuracy: 0.5771, prior_entropy: 0.9988, recall: 0.5771, relative_absolute_error: 0.8472, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.6503, root_relative_squared_error: 1.3018, scimark_benchmark: 941.3847, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4249, f_measure: 0.4368, kappa: -0.0132, kb_relative_information_score: -7.5662, mean_absolute_error: 0.5058, mean_prior_absolute_error: 0.4992, number_of_instances: 480, precision: 0.4884, predictive_accuracy: 0.5083, prior_entropy: 0.9988, recall: 0.5083, relative_absolute_error: 1.0133, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.5173, root_relative_squared_error: 1.0356, scimark_benchmark: 974.2014,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4249, f_measure: 0.4368, kappa: -0.0132, kb_relative_information_score: -7.5735, mean_absolute_error: 0.5058, mean_prior_absolute_error: 0.4992, number_of_instances: 480, precision: 0.4884, predictive_accuracy: 0.5083, prior_entropy: 0.9988, recall: 0.5083, relative_absolute_error: 1.0133, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.5175, root_relative_squared_error: 1.036, scimark_benchmark: 941.3847,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.712, f_measure: 0.6626, kappa: 0.3241, kb_relative_information_score: 115.8596, mean_absolute_error: 0.3863, mean_prior_absolute_error: 0.4992, number_of_instances: 480, precision: 0.6626, predictive_accuracy: 0.6625, prior_entropy: 0.9988, recall: 0.6625, relative_absolute_error: 0.774, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.479, root_relative_squared_error: 0.9588, scimark_benchmark: 937.5117, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4259, f_measure: 0.4368, kappa: -0.0132, kb_relative_information_score: -6.2723, mean_absolute_error: 0.5044, mean_prior_absolute_error: 0.4992, number_of_instances: 480, precision: 0.4884, predictive_accuracy: 0.5083, prior_entropy: 0.9988, recall: 0.5083, relative_absolute_error: 1.0105, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.5172, root_relative_squared_error: 1.0352, scimark_benchmark: 942.2392,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7078, f_measure: 0.6647, kappa: 0.33, kb_relative_information_score: 115.0146, mean_absolute_error: 0.3876, mean_prior_absolute_error: 0.4992, number_of_instances: 480, precision: 0.6664, predictive_accuracy: 0.6646, prior_entropy: 0.9988, recall: 0.6646, relative_absolute_error: 0.7765, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.4871, root_relative_squared_error: 0.975, scimark_benchmark: 908.9569,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6888, f_measure: 0.6373, kappa: 0.2732, kb_relative_information_score: 125.6308, mean_absolute_error: 0.3718, mean_prior_absolute_error: 0.4992, number_of_instances: 480, precision: 0.6373, predictive_accuracy: 0.6375, prior_entropy: 0.9988, recall: 0.6375, relative_absolute_error: 0.7448, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.5296, root_relative_squared_error: 1.06, scimark_benchmark: 940.1541, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.573, f_measure: 0.5728, kappa: 0.1469, kb_relative_information_score: 73.015, mean_absolute_error: 0.4229, mean_prior_absolute_error: 0.4992, number_of_instances: 480, precision: 0.5762, predictive_accuracy: 0.5771, prior_entropy: 0.9988, recall: 0.5771, relative_absolute_error: 0.8472, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.6503, root_relative_squared_error: 1.3018, scimark_benchmark: 934.7923,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4249, f_measure: 0.4368, kappa: -0.0132, kb_relative_information_score: -7.5735, mean_absolute_error: 0.5058, mean_prior_absolute_error: 0.4992, number_of_instances: 480, precision: 0.4884, predictive_accuracy: 0.5083, prior_entropy: 0.9988, recall: 0.5083, relative_absolute_error: 1.0133, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.5175, root_relative_squared_error: 1.036, scimark_benchmark: 930.404,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4249, f_measure: 0.4368, kappa: -0.0132, kb_relative_information_score: -7.5735, mean_absolute_error: 0.5058, mean_prior_absolute_error: 0.4992, number_of_instances: 480, precision: 0.4884, predictive_accuracy: 0.5083, prior_entropy: 0.9988, recall: 0.5083, relative_absolute_error: 1.0133, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.5175, root_relative_squared_error: 1.036, scimark_benchmark: 930.404,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4249, f_measure: 0.4368, kappa: -0.0132, kb_relative_information_score: -7.5735, mean_absolute_error: 0.5058, mean_prior_absolute_error: 0.4992, number_of_instances: 480, precision: 0.4884, predictive_accuracy: 0.5083, prior_entropy: 0.9988, recall: 0.5083, relative_absolute_error: 1.0133, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.5175, root_relative_squared_error: 1.036, scimark_benchmark: 930.404,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6984, f_measure: 0.6521, kappa: 0.3028, kb_relative_information_score: 81.2465, mean_absolute_error: 0.4252, mean_prior_absolute_error: 0.4992, number_of_instances: 480, precision: 0.652, predictive_accuracy: 0.6521, prior_entropy: 0.9988, recall: 0.6521, relative_absolute_error: 0.8518, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.4717, root_relative_squared_error: 0.9441, scimark_benchmark: 930.404,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7451, f_measure: 0.7313, kappa: 0.4632, kb_relative_information_score: 118.0632, mean_absolute_error: 0.3948, mean_prior_absolute_error: 0.4992, number_of_instances: 480, precision: 0.7332, predictive_accuracy: 0.7313, prior_entropy: 0.9988, recall: 0.7313, relative_absolute_error: 0.7909, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.4576, root_relative_squared_error: 0.9159, scimark_benchmark: 936.9595, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4249, f_measure: 0.4368, kappa: -0.0132, kb_relative_information_score: -7.5735, mean_absolute_error: 0.5058, mean_prior_absolute_error: 0.4992, number_of_instances: 480, precision: 0.4884, predictive_accuracy: 0.5083, prior_entropy: 0.9988, recall: 0.5083, relative_absolute_error: 1.0133, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.5175, root_relative_squared_error: 1.036, scimark_benchmark: 932.438,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5858, f_measure: 0.5937, kappa: 0.1967, kb_relative_information_score: 51.406, mean_absolute_error: 0.4506, mean_prior_absolute_error: 0.4992, number_of_instances: 480, precision: 0.6027, predictive_accuracy: 0.5958, prior_entropy: 0.9988, recall: 0.5958, relative_absolute_error: 0.9026, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.5181, root_relative_squared_error: 1.0371, scimark_benchmark: 730.6551, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.712, f_measure: 0.6626, kappa: 0.3241, kb_relative_information_score: 115.8596, mean_absolute_error: 0.3863, mean_prior_absolute_error: 0.4992, number_of_instances: 480, precision: 0.6626, predictive_accuracy: 0.6625, prior_entropy: 0.9988, recall: 0.6625, relative_absolute_error: 0.774, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.479, root_relative_squared_error: 0.9588, scimark_benchmark: 938.988, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7508, f_measure: 0.7126, kappa: 0.4254, kb_relative_information_score: 122.6433, mean_absolute_error: 0.3883, mean_prior_absolute_error: 0.4992, number_of_instances: 480, precision: 0.7139, predictive_accuracy: 0.7125, prior_entropy: 0.9988, recall: 0.7125, relative_absolute_error: 0.7779, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.45, root_relative_squared_error: 0.9008, scimark_benchmark: 1171.0303, usercpu_time_millis: 290, usercpu_time_millis_testing: 150, usercpu_time_millis_training: 140,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7475, f_measure: 0.7043, kappa: 0.4085, kb_relative_information_score: 122.8146, mean_absolute_error: 0.3877, mean_prior_absolute_error: 0.4992, number_of_instances: 480, precision: 0.7053, predictive_accuracy: 0.7042, prior_entropy: 0.9988, recall: 0.7042, relative_absolute_error: 0.7766, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.4506, root_relative_squared_error: 0.902, scimark_benchmark: 943.6618, usercpu_time_millis: 70, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7476, f_measure: 0.7085, kappa: 0.4167, kb_relative_information_score: 121.0119, mean_absolute_error: 0.3891, mean_prior_absolute_error: 0.4992, number_of_instances: 480, precision: 0.7092, predictive_accuracy: 0.7083, prior_entropy: 0.9988, recall: 0.7083, relative_absolute_error: 0.7796, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.4515, root_relative_squared_error: 0.9038, scimark_benchmark: 903.179, usercpu_time_millis: 40, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7424, f_measure: 0.698, kappa: 0.3959, kb_relative_information_score: 118.1047, mean_absolute_error: 0.3914, mean_prior_absolute_error: 0.4992, number_of_instances: 480, precision: 0.6989, predictive_accuracy: 0.6979, prior_entropy: 0.9988, recall: 0.6979, relative_absolute_error: 0.784, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.4549, root_relative_squared_error: 0.9105, scimark_benchmark: 901.5805, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7531, f_measure: 0.7105, kappa: 0.4207, kb_relative_information_score: 130.2011, mean_absolute_error: 0.3792, mean_prior_absolute_error: 0.4992, number_of_instances: 480, precision: 0.7112, predictive_accuracy: 0.7104, prior_entropy: 0.9988, recall: 0.7104, relative_absolute_error: 0.7596, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.4501, root_relative_squared_error: 0.9009, scimark_benchmark: 939.7883, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
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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