OpenML
Supervised Classification on monks-problems-2

Supervised Classification on monks-problems-2

Task 146065 Supervised Classification monks-problems-2 261558 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.491, f_measure: 0.5213, kb_relative_information_score: 0.1232, mean_absolute_error: 0.4506, mean_prior_absolute_error: 0.4507, number_of_instances: 601, precision: 0.432, predictive_accuracy: 0.6572, prior_entropy: 0.9279, recall: 0.6572, relative_absolute_error: 0.9997, root_mean_prior_squared_error: 0.4746, root_mean_squared_error: 0.4746, root_relative_squared_error: 1, scimark_benchmark: 1353.2631, usercpu_time_millis: 0.092, usercpu_time_millis_testing: 0.033, usercpu_time_millis_training: 0.059,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.491, f_measure: 0.5213, kb_relative_information_score: 0.1232, mean_absolute_error: 0.4506, mean_prior_absolute_error: 0.4507, number_of_instances: 601, precision: 0.432, predictive_accuracy: 0.6572, prior_entropy: 0.9279, recall: 0.6572, relative_absolute_error: 0.9997, root_mean_prior_squared_error: 0.4746, root_mean_squared_error: 0.4746, root_relative_squared_error: 1, scimark_benchmark: 1327.9136, usercpu_time_millis: 0.083, usercpu_time_millis_testing: 0.031, usercpu_time_millis_training: 0.052,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.491, f_measure: 0.5213, kb_relative_information_score: 0.1232, mean_absolute_error: 0.4506, mean_prior_absolute_error: 0.4507, number_of_instances: 601, precision: 0.432, predictive_accuracy: 0.6572, prior_entropy: 0.9279, recall: 0.6572, relative_absolute_error: 0.9997, root_mean_prior_squared_error: 0.4746, root_mean_squared_error: 0.4746, root_relative_squared_error: 1, scimark_benchmark: 1342.3162, usercpu_time_millis: 0.219, usercpu_time_millis_testing: 0.031, usercpu_time_millis_training: 0.188,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.491, f_measure: 0.5213, kb_relative_information_score: 0.1232, mean_absolute_error: 0.4506, mean_prior_absolute_error: 0.4507, number_of_instances: 601, precision: 0.432, predictive_accuracy: 0.6572, prior_entropy: 0.9279, recall: 0.6572, relative_absolute_error: 0.9997, root_mean_prior_squared_error: 0.4746, root_mean_squared_error: 0.4746, root_relative_squared_error: 1, scimark_benchmark: 1340.2651, usercpu_time_millis: 0.099, usercpu_time_millis_testing: 0.038, usercpu_time_millis_training: 0.061,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.491, f_measure: 0.5213, kb_relative_information_score: 0.1232, mean_absolute_error: 0.4506, mean_prior_absolute_error: 0.4507, number_of_instances: 601, precision: 0.432, predictive_accuracy: 0.6572, prior_entropy: 0.9279, recall: 0.6572, relative_absolute_error: 0.9997, root_mean_prior_squared_error: 0.4746, root_mean_squared_error: 0.4746, root_relative_squared_error: 1, scimark_benchmark: 1328.6041, usercpu_time_millis: 0.112, usercpu_time_millis_testing: 0.038, usercpu_time_millis_training: 0.074,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.491, f_measure: 0.5213, kb_relative_information_score: 0.1232, mean_absolute_error: 0.4506, mean_prior_absolute_error: 0.4507, number_of_instances: 601, precision: 0.432, predictive_accuracy: 0.6572, prior_entropy: 0.9279, recall: 0.6572, relative_absolute_error: 0.9997, root_mean_prior_squared_error: 0.4746, root_mean_squared_error: 0.4746, root_relative_squared_error: 1, scimark_benchmark: 1324.2619, usercpu_time_millis: 0.086, usercpu_time_millis_testing: 0.033, usercpu_time_millis_training: 0.053,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.491, f_measure: 0.5213, kb_relative_information_score: 0.1232, mean_absolute_error: 0.4506, mean_prior_absolute_error: 0.4507, number_of_instances: 601, precision: 0.432, predictive_accuracy: 0.6572, prior_entropy: 0.9279, recall: 0.6572, relative_absolute_error: 0.9997, root_mean_prior_squared_error: 0.4746, root_mean_squared_error: 0.4746, root_relative_squared_error: 1, scimark_benchmark: 1329.6878, usercpu_time_millis: 0.083, usercpu_time_millis_testing: 0.031, usercpu_time_millis_training: 0.052,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.491, f_measure: 0.5213, kb_relative_information_score: 0.1232, mean_absolute_error: 0.4506, mean_prior_absolute_error: 0.4507, number_of_instances: 601, precision: 0.432, predictive_accuracy: 0.6572, prior_entropy: 0.9279, recall: 0.6572, relative_absolute_error: 0.9997, root_mean_prior_squared_error: 0.4746, root_mean_squared_error: 0.4746, root_relative_squared_error: 1, scimark_benchmark: 1372.9922, usercpu_time_millis: 0.085, usercpu_time_millis_testing: 0.033, usercpu_time_millis_training: 0.052,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.491, f_measure: 0.5213, kb_relative_information_score: 0.1232, mean_absolute_error: 0.4506, mean_prior_absolute_error: 0.4507, number_of_instances: 601, precision: 0.432, predictive_accuracy: 0.6572, prior_entropy: 0.9279, recall: 0.6572, relative_absolute_error: 0.9997, root_mean_prior_squared_error: 0.4746, root_mean_squared_error: 0.4746, root_relative_squared_error: 1, scimark_benchmark: 1339.3614, usercpu_time_millis: 0.087, usercpu_time_millis_testing: 0.033, usercpu_time_millis_training: 0.054,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.491, f_measure: 0.5213, kb_relative_information_score: 0.1232, mean_absolute_error: 0.4506, mean_prior_absolute_error: 0.4507, number_of_instances: 601, precision: 0.432, predictive_accuracy: 0.6572, prior_entropy: 0.9279, recall: 0.6572, relative_absolute_error: 0.9997, root_mean_prior_squared_error: 0.4746, root_mean_squared_error: 0.4746, root_relative_squared_error: 1, scimark_benchmark: 1337.9565, usercpu_time_millis: 0.235, usercpu_time_millis_testing: 0.086, usercpu_time_millis_training: 0.149,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.491, f_measure: 0.5213, kb_relative_information_score: 0.1232, mean_absolute_error: 0.4506, mean_prior_absolute_error: 0.4507, number_of_instances: 601, precision: 0.432, predictive_accuracy: 0.6572, prior_entropy: 0.9279, recall: 0.6572, relative_absolute_error: 0.9997, root_mean_prior_squared_error: 0.4746, root_mean_squared_error: 0.4746, root_relative_squared_error: 1, scimark_benchmark: 1328.5142, usercpu_time_millis: 0.082, usercpu_time_millis_testing: 0.032, usercpu_time_millis_training: 0.05,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.491, f_measure: 0.5213, kb_relative_information_score: 0.1232, mean_absolute_error: 0.4506, mean_prior_absolute_error: 0.4507, number_of_instances: 601, precision: 0.432, predictive_accuracy: 0.6572, prior_entropy: 0.9279, recall: 0.6572, relative_absolute_error: 0.9997, root_mean_prior_squared_error: 0.4746, root_mean_squared_error: 0.4746, root_relative_squared_error: 1, scimark_benchmark: 1328.1503, usercpu_time_millis: 0.086, usercpu_time_millis_testing: 0.032, usercpu_time_millis_training: 0.054,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.491, f_measure: 0.5213, kb_relative_information_score: 0.1232, mean_absolute_error: 0.4506, mean_prior_absolute_error: 0.4507, number_of_instances: 601, precision: 0.432, predictive_accuracy: 0.6572, prior_entropy: 0.9279, recall: 0.6572, relative_absolute_error: 0.9997, root_mean_prior_squared_error: 0.4746, root_mean_squared_error: 0.4746, root_relative_squared_error: 1, scimark_benchmark: 1340.8889, usercpu_time_millis: 0.084, usercpu_time_millis_testing: 0.03, usercpu_time_millis_training: 0.054,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.491, f_measure: 0.5213, kb_relative_information_score: 0.1232, mean_absolute_error: 0.4506, mean_prior_absolute_error: 0.4507, number_of_instances: 601, precision: 0.432, predictive_accuracy: 0.6572, prior_entropy: 0.9279, recall: 0.6572, relative_absolute_error: 0.9997, root_mean_prior_squared_error: 0.4746, root_mean_squared_error: 0.4746, root_relative_squared_error: 1, scimark_benchmark: 1321.4391, usercpu_time_millis: 0.093, usercpu_time_millis_testing: 0.041, usercpu_time_millis_training: 0.052,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.491, f_measure: 0.5213, kb_relative_information_score: 0.1232, mean_absolute_error: 0.4506, mean_prior_absolute_error: 0.4507, number_of_instances: 601, precision: 0.432, predictive_accuracy: 0.6572, prior_entropy: 0.9279, recall: 0.6572, relative_absolute_error: 0.9997, root_mean_prior_squared_error: 0.4746, root_mean_squared_error: 0.4746, root_relative_squared_error: 1, scimark_benchmark: 1323.1265, usercpu_time_millis: 0.085, usercpu_time_millis_testing: 0.032, usercpu_time_millis_training: 0.053,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.491, f_measure: 0.5213, kb_relative_information_score: 0.1232, mean_absolute_error: 0.4506, mean_prior_absolute_error: 0.4507, number_of_instances: 601, precision: 0.432, predictive_accuracy: 0.6572, prior_entropy: 0.9279, recall: 0.6572, relative_absolute_error: 0.9997, root_mean_prior_squared_error: 0.4746, root_mean_squared_error: 0.4746, root_relative_squared_error: 1, scimark_benchmark: 1335.7222, usercpu_time_millis: 0.087, usercpu_time_millis_testing: 0.033, usercpu_time_millis_training: 0.054,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.491, f_measure: 0.5213, kb_relative_information_score: 0.1232, mean_absolute_error: 0.4506, mean_prior_absolute_error: 0.4507, number_of_instances: 601, precision: 0.432, predictive_accuracy: 0.6572, prior_entropy: 0.9279, recall: 0.6572, relative_absolute_error: 0.9997, root_mean_prior_squared_error: 0.4746, root_mean_squared_error: 0.4746, root_relative_squared_error: 1, scimark_benchmark: 1336.8834, usercpu_time_millis: 0.085, usercpu_time_millis_testing: 0.031, usercpu_time_millis_training: 0.054,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.491, f_measure: 0.5213, kb_relative_information_score: 0.1232, mean_absolute_error: 0.4506, mean_prior_absolute_error: 0.4507, number_of_instances: 601, precision: 0.432, predictive_accuracy: 0.6572, prior_entropy: 0.9279, recall: 0.6572, relative_absolute_error: 0.9997, root_mean_prior_squared_error: 0.4746, root_mean_squared_error: 0.4746, root_relative_squared_error: 1, scimark_benchmark: 1353.8493, usercpu_time_millis: 0.085, usercpu_time_millis_testing: 0.032, usercpu_time_millis_training: 0.053,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.491, f_measure: 0.5213, kb_relative_information_score: 0.1232, mean_absolute_error: 0.4506, mean_prior_absolute_error: 0.4507, number_of_instances: 601, precision: 0.432, predictive_accuracy: 0.6572, prior_entropy: 0.9279, recall: 0.6572, relative_absolute_error: 0.9997, root_mean_prior_squared_error: 0.4746, root_mean_squared_error: 0.4746, root_relative_squared_error: 1, scimark_benchmark: 1352.4627, usercpu_time_millis: 0.084, usercpu_time_millis_testing: 0.032, usercpu_time_millis_training: 0.052,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.491, f_measure: 0.5213, kb_relative_information_score: 0.1232, mean_absolute_error: 0.4506, mean_prior_absolute_error: 0.4507, number_of_instances: 601, precision: 0.432, predictive_accuracy: 0.6572, prior_entropy: 0.9279, recall: 0.6572, relative_absolute_error: 0.9997, root_mean_prior_squared_error: 0.4746, root_mean_squared_error: 0.4746, root_relative_squared_error: 1, scimark_benchmark: 1344.9047, usercpu_time_millis: 0.084, usercpu_time_millis_testing: 0.033, usercpu_time_millis_training: 0.051,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.491, f_measure: 0.5213, kb_relative_information_score: 0.1232, mean_absolute_error: 0.4506, mean_prior_absolute_error: 0.4507, number_of_instances: 601, precision: 0.432, predictive_accuracy: 0.6572, prior_entropy: 0.9279, recall: 0.6572, relative_absolute_error: 0.9997, root_mean_prior_squared_error: 0.4746, root_mean_squared_error: 0.4746, root_relative_squared_error: 1, scimark_benchmark: 1324.38, usercpu_time_millis: 0.08, usercpu_time_millis_testing: 0.029, usercpu_time_millis_training: 0.051,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.491, f_measure: 0.5213, kb_relative_information_score: 0.1232, mean_absolute_error: 0.4506, mean_prior_absolute_error: 0.4507, number_of_instances: 601, precision: 0.432, predictive_accuracy: 0.6572, prior_entropy: 0.9279, recall: 0.6572, relative_absolute_error: 0.9997, root_mean_prior_squared_error: 0.4746, root_mean_squared_error: 0.4746, root_relative_squared_error: 1, scimark_benchmark: 1311.9742, usercpu_time_millis: 0.087, usercpu_time_millis_testing: 0.031, usercpu_time_millis_training: 0.056,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.491, f_measure: 0.5213, kb_relative_information_score: 0.1232, mean_absolute_error: 0.4506, mean_prior_absolute_error: 0.4507, number_of_instances: 601, precision: 0.432, predictive_accuracy: 0.6572, prior_entropy: 0.9279, recall: 0.6572, relative_absolute_error: 0.9997, root_mean_prior_squared_error: 0.4746, root_mean_squared_error: 0.4746, root_relative_squared_error: 1, scimark_benchmark: 1313.2813, usercpu_time_millis: 0.09, usercpu_time_millis_testing: 0.035, usercpu_time_millis_training: 0.055,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.491, f_measure: 0.5213, kb_relative_information_score: 0.1232, mean_absolute_error: 0.4506, mean_prior_absolute_error: 0.4507, number_of_instances: 601, precision: 0.432, predictive_accuracy: 0.6572, prior_entropy: 0.9279, recall: 0.6572, relative_absolute_error: 0.9997, root_mean_prior_squared_error: 0.4746, root_mean_squared_error: 0.4746, root_relative_squared_error: 1, scimark_benchmark: 1342.0227, usercpu_time_millis: 0.086, usercpu_time_millis_testing: 0.031, usercpu_time_millis_training: 0.055,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.491, f_measure: 0.5213, kb_relative_information_score: 0.1232, mean_absolute_error: 0.4506, mean_prior_absolute_error: 0.4507, number_of_instances: 601, precision: 0.432, predictive_accuracy: 0.6572, prior_entropy: 0.9279, recall: 0.6572, relative_absolute_error: 0.9997, root_mean_prior_squared_error: 0.4746, root_mean_squared_error: 0.4746, root_relative_squared_error: 1, scimark_benchmark: 1352.0104, usercpu_time_millis: 0.09, usercpu_time_millis_testing: 0.035, usercpu_time_millis_training: 0.055,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.491, f_measure: 0.5213, kb_relative_information_score: 0.1232, mean_absolute_error: 0.4506, mean_prior_absolute_error: 0.4507, number_of_instances: 601, precision: 0.432, predictive_accuracy: 0.6572, prior_entropy: 0.9279, recall: 0.6572, relative_absolute_error: 0.9997, root_mean_prior_squared_error: 0.4746, root_mean_squared_error: 0.4746, root_relative_squared_error: 1, scimark_benchmark: 1317.0421, usercpu_time_millis: 0.096, usercpu_time_millis_testing: 0.036, usercpu_time_millis_training: 0.06,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.491, f_measure: 0.5213, kb_relative_information_score: 0.1232, mean_absolute_error: 0.4506, mean_prior_absolute_error: 0.4507, number_of_instances: 601, precision: 0.432, predictive_accuracy: 0.6572, prior_entropy: 0.9279, recall: 0.6572, relative_absolute_error: 0.9997, root_mean_prior_squared_error: 0.4746, root_mean_squared_error: 0.4746, root_relative_squared_error: 1, scimark_benchmark: 1322.0564, usercpu_time_millis: 0.091, usercpu_time_millis_testing: 0.035, usercpu_time_millis_training: 0.056,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.491, f_measure: 0.5213, kb_relative_information_score: 0.1232, mean_absolute_error: 0.4506, mean_prior_absolute_error: 0.4507, number_of_instances: 601, precision: 0.432, predictive_accuracy: 0.6572, prior_entropy: 0.9279, recall: 0.6572, relative_absolute_error: 0.9997, root_mean_prior_squared_error: 0.4746, root_mean_squared_error: 0.4746, root_relative_squared_error: 1, scimark_benchmark: 1344.9757, usercpu_time_millis: 0.095, usercpu_time_millis_testing: 0.035, usercpu_time_millis_training: 0.06,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.491, f_measure: 0.5213, kb_relative_information_score: 0.1232, mean_absolute_error: 0.4506, mean_prior_absolute_error: 0.4507, number_of_instances: 601, precision: 0.432, predictive_accuracy: 0.6572, prior_entropy: 0.9279, recall: 0.6572, relative_absolute_error: 0.9997, root_mean_prior_squared_error: 0.4746, root_mean_squared_error: 0.4746, root_relative_squared_error: 1, scimark_benchmark: 1336.7794, usercpu_time_millis: 0.086, usercpu_time_millis_testing: 0.034, usercpu_time_millis_training: 0.052,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5563, f_measure: 0.5976, kappa: 0.0972, kb_relative_information_score: 15.8983, mean_absolute_error: 0.4355, mean_prior_absolute_error: 0.4507, number_of_instances: 601, precision: 0.6195, predictive_accuracy: 0.6589, prior_entropy: 0.9279, recall: 0.6589, relative_absolute_error: 0.9662, root_mean_prior_squared_error: 0.4746, root_mean_squared_error: 0.472, root_relative_squared_error: 0.9945, scimark_benchmark: 1329.4326, usercpu_time_millis: 0.155, usercpu_time_millis_testing: 0.046, usercpu_time_millis_training: 0.109,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.491, f_measure: 0.5213, kb_relative_information_score: 0.1232, mean_absolute_error: 0.4506, mean_prior_absolute_error: 0.4507, number_of_instances: 601, precision: 0.432, predictive_accuracy: 0.6572, prior_entropy: 0.9279, recall: 0.6572, relative_absolute_error: 0.9997, root_mean_prior_squared_error: 0.4746, root_mean_squared_error: 0.4746, root_relative_squared_error: 1, scimark_benchmark: 1336.3596, usercpu_time_millis: 0.093, usercpu_time_millis_testing: 0.035, usercpu_time_millis_training: 0.058,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.491, f_measure: 0.5213, kb_relative_information_score: 0.1232, mean_absolute_error: 0.4506, mean_prior_absolute_error: 0.4507, number_of_instances: 601, precision: 0.432, predictive_accuracy: 0.6572, prior_entropy: 0.9279, recall: 0.6572, relative_absolute_error: 0.9997, root_mean_prior_squared_error: 0.4746, root_mean_squared_error: 0.4746, root_relative_squared_error: 1, scimark_benchmark: 1339.839, usercpu_time_millis: 0.09, usercpu_time_millis_testing: 0.034, usercpu_time_millis_training: 0.056,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.491, f_measure: 0.5213, kb_relative_information_score: 0.1232, mean_absolute_error: 0.4506, mean_prior_absolute_error: 0.4507, number_of_instances: 601, precision: 0.432, predictive_accuracy: 0.6572, prior_entropy: 0.9279, recall: 0.6572, relative_absolute_error: 0.9997, root_mean_prior_squared_error: 0.4746, root_mean_squared_error: 0.4746, root_relative_squared_error: 1, scimark_benchmark: 1349.5838, usercpu_time_millis: 0.096, usercpu_time_millis_testing: 0.036, usercpu_time_millis_training: 0.06,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.491, f_measure: 0.5213, kb_relative_information_score: 0.1232, mean_absolute_error: 0.4506, mean_prior_absolute_error: 0.4507, number_of_instances: 601, precision: 0.432, predictive_accuracy: 0.6572, prior_entropy: 0.9279, recall: 0.6572, relative_absolute_error: 0.9997, root_mean_prior_squared_error: 0.4746, root_mean_squared_error: 0.4746, root_relative_squared_error: 1, scimark_benchmark: 1354.2029, usercpu_time_millis: 0.095, usercpu_time_millis_testing: 0.032, usercpu_time_millis_training: 0.063,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.491, f_measure: 0.5213, kb_relative_information_score: 0.1232, mean_absolute_error: 0.4506, mean_prior_absolute_error: 0.4507, number_of_instances: 601, precision: 0.432, predictive_accuracy: 0.6572, prior_entropy: 0.9279, recall: 0.6572, relative_absolute_error: 0.9997, root_mean_prior_squared_error: 0.4746, root_mean_squared_error: 0.4746, root_relative_squared_error: 1, scimark_benchmark: 1319.2091, usercpu_time_millis: 0.087, usercpu_time_millis_testing: 0.033, usercpu_time_millis_training: 0.054,

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