OpenML
Supervised Classification on primary-tumor

Supervised Classification on primary-tumor

Task 3866 Supervised Classification primary-tumor 554 runs submitted
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  • mythbusting_1 study_1 study_107 study_15 study_20 study_41 under100k under1m
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6708, f_measure: 0.797, kappa: 0.4184, kb_relative_information_score: 158.9395, mean_absolute_error: 0.177, mean_prior_absolute_error: 0.3735, number_of_instances: 339, precision: 0.8219, predictive_accuracy: 0.823, prior_entropy: 0.8101, recall: 0.823, relative_absolute_error: 0.4738, root_mean_prior_squared_error: 0.4317, root_mean_squared_error: 0.4207, root_relative_squared_error: 0.9745, scimark_benchmark: 917.407, usercpu_time_millis: 60, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8886, f_measure: 0.8553, kappa: 0.6044, kb_relative_information_score: 154.1816, mean_absolute_error: 0.1989, mean_prior_absolute_error: 0.3735, number_of_instances: 339, precision: 0.8541, predictive_accuracy: 0.8584, prior_entropy: 0.8101, recall: 0.8584, relative_absolute_error: 0.5325, root_mean_prior_squared_error: 0.4317, root_mean_squared_error: 0.33, root_relative_squared_error: 0.7644, scimark_benchmark: 945.0194, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8702, f_measure: 0.8365, kappa: 0.5462, kb_relative_information_score: 116.8055, mean_absolute_error: 0.2437, mean_prior_absolute_error: 0.3735, number_of_instances: 339, precision: 0.8364, predictive_accuracy: 0.8437, prior_entropy: 0.8101, recall: 0.8437, relative_absolute_error: 0.6526, root_mean_prior_squared_error: 0.4317, root_mean_squared_error: 0.3422, root_relative_squared_error: 0.7925, scimark_benchmark: 922.5036, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8805, f_measure: 0.8666, kappa: 0.6286, kb_relative_information_score: 154.4337, mean_absolute_error: 0.2, mean_prior_absolute_error: 0.3735, number_of_instances: 339, precision: 0.8695, predictive_accuracy: 0.8732, prior_entropy: 0.8101, recall: 0.8732, relative_absolute_error: 0.5355, root_mean_prior_squared_error: 0.4317, root_mean_squared_error: 0.3244, root_relative_squared_error: 0.7514, scimark_benchmark: 952.4682, usercpu_time_millis: 2850, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 2820,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8886, f_measure: 0.8553, kappa: 0.6044, kb_relative_information_score: 154.1816, mean_absolute_error: 0.1989, mean_prior_absolute_error: 0.3735, number_of_instances: 339, precision: 0.8541, predictive_accuracy: 0.8584, prior_entropy: 0.8101, recall: 0.8584, relative_absolute_error: 0.5325, root_mean_prior_squared_error: 0.4317, root_mean_squared_error: 0.33, root_relative_squared_error: 0.7644, scimark_benchmark: 942.3809,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8518, f_measure: 0.8312, kappa: 0.5331, kb_relative_information_score: 145.7212, mean_absolute_error: 0.2029, mean_prior_absolute_error: 0.3735, number_of_instances: 339, precision: 0.8302, predictive_accuracy: 0.8378, prior_entropy: 0.8101, recall: 0.8378, relative_absolute_error: 0.5433, root_mean_prior_squared_error: 0.4317, root_mean_squared_error: 0.3558, root_relative_squared_error: 0.8241, scimark_benchmark: 946.9304, usercpu_time_millis: 70, usercpu_time_millis_training: 70,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8741, f_measure: 0.8515, kappa: 0.5872, kb_relative_information_score: 133.659, mean_absolute_error: 0.2224, mean_prior_absolute_error: 0.3735, number_of_instances: 339, precision: 0.8528, predictive_accuracy: 0.8584, prior_entropy: 0.8101, recall: 0.8584, relative_absolute_error: 0.5955, root_mean_prior_squared_error: 0.4317, root_mean_squared_error: 0.3341, root_relative_squared_error: 0.7739, scimark_benchmark: 928.8135, usercpu_time_millis: 130, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 100,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7946, f_measure: 0.7822, kappa: 0.3928, kb_relative_information_score: 101.9096, mean_absolute_error: 0.2515, mean_prior_absolute_error: 0.3735, number_of_instances: 339, precision: 0.7792, predictive_accuracy: 0.7935, prior_entropy: 0.8101, recall: 0.7935, relative_absolute_error: 0.6733, root_mean_prior_squared_error: 0.4317, root_mean_squared_error: 0.3929, root_relative_squared_error: 0.9102, scimark_benchmark: 946.9304,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6708, f_measure: 0.797, kappa: 0.4184, kb_relative_information_score: 158.9395, mean_absolute_error: 0.177, mean_prior_absolute_error: 0.3735, number_of_instances: 339, precision: 0.8219, predictive_accuracy: 0.823, prior_entropy: 0.8101, recall: 0.823, relative_absolute_error: 0.4738, root_mean_prior_squared_error: 0.4317, root_mean_squared_error: 0.4207, root_relative_squared_error: 0.9745, scimark_benchmark: 917.9672, usercpu_time_millis: 50, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6708, f_measure: 0.797, kappa: 0.4184, kb_relative_information_score: 158.9395, mean_absolute_error: 0.177, mean_prior_absolute_error: 0.3735, number_of_instances: 339, precision: 0.8219, predictive_accuracy: 0.823, prior_entropy: 0.8101, recall: 0.823, relative_absolute_error: 0.4738, root_mean_prior_squared_error: 0.4317, root_mean_squared_error: 0.4207, root_relative_squared_error: 0.9745, scimark_benchmark: 1295.609, usercpu_time_millis: 60, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.856, f_measure: 0.8097, kappa: 0.4685, kb_relative_information_score: 117.2083, mean_absolute_error: 0.239, mean_prior_absolute_error: 0.3735, number_of_instances: 339, precision: 0.8092, predictive_accuracy: 0.8201, prior_entropy: 0.8101, recall: 0.8201, relative_absolute_error: 0.6398, root_mean_prior_squared_error: 0.4317, root_mean_squared_error: 0.3578, root_relative_squared_error: 0.8286, scimark_benchmark: 1327.5842,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8886, f_measure: 0.8553, kappa: 0.6044, kb_relative_information_score: 154.1816, mean_absolute_error: 0.1989, mean_prior_absolute_error: 0.3735, number_of_instances: 339, precision: 0.8541, predictive_accuracy: 0.8584, prior_entropy: 0.8101, recall: 0.8584, relative_absolute_error: 0.5325, root_mean_prior_squared_error: 0.4317, root_mean_squared_error: 0.33, root_relative_squared_error: 0.7644, scimark_benchmark: 1327.5842,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8609, f_measure: 0.8453, kappa: 0.5654, kb_relative_information_score: 141.9218, mean_absolute_error: 0.2109, mean_prior_absolute_error: 0.3735, number_of_instances: 339, precision: 0.8508, predictive_accuracy: 0.8555, prior_entropy: 0.8101, recall: 0.8555, relative_absolute_error: 0.5646, root_mean_prior_squared_error: 0.4317, root_mean_squared_error: 0.3411, root_relative_squared_error: 0.7902, scimark_benchmark: 1292.514, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8886, f_measure: 0.8553, kappa: 0.6044, kb_relative_information_score: 154.1816, mean_absolute_error: 0.1989, mean_prior_absolute_error: 0.3735, number_of_instances: 339, precision: 0.8541, predictive_accuracy: 0.8584, prior_entropy: 0.8101, recall: 0.8584, relative_absolute_error: 0.5325, root_mean_prior_squared_error: 0.4317, root_mean_squared_error: 0.33, root_relative_squared_error: 0.7644, scimark_benchmark: 1335.974,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8886, f_measure: 0.8553, kappa: 0.6044, kb_relative_information_score: 154.1816, mean_absolute_error: 0.1989, mean_prior_absolute_error: 0.3735, number_of_instances: 339, precision: 0.8541, predictive_accuracy: 0.8584, prior_entropy: 0.8101, recall: 0.8584, relative_absolute_error: 0.5325, root_mean_prior_squared_error: 0.4317, root_mean_squared_error: 0.33, root_relative_squared_error: 0.7644, scimark_benchmark: 1292.514,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8594, f_measure: 0.8443, kappa: 0.5707, kb_relative_information_score: 94.2661, mean_absolute_error: 0.2673, mean_prior_absolute_error: 0.3735, number_of_instances: 339, precision: 0.8434, predictive_accuracy: 0.8496, prior_entropy: 0.8101, recall: 0.8496, relative_absolute_error: 0.7156, root_mean_prior_squared_error: 0.4317, root_mean_squared_error: 0.3455, root_relative_squared_error: 0.8002, scimark_benchmark: 1314.9949, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.856, f_measure: 0.8097, kappa: 0.4685, kb_relative_information_score: 117.2083, mean_absolute_error: 0.239, mean_prior_absolute_error: 0.3735, number_of_instances: 339, precision: 0.8092, predictive_accuracy: 0.8201, prior_entropy: 0.8101, recall: 0.8201, relative_absolute_error: 0.6398, root_mean_prior_squared_error: 0.4317, root_mean_squared_error: 0.3578, root_relative_squared_error: 0.8286, scimark_benchmark: 1332.9478,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8594, f_measure: 0.8443, kappa: 0.5707, kb_relative_information_score: 94.2661, mean_absolute_error: 0.2673, mean_prior_absolute_error: 0.3735, number_of_instances: 339, precision: 0.8434, predictive_accuracy: 0.8496, prior_entropy: 0.8101, recall: 0.8496, relative_absolute_error: 0.7156, root_mean_prior_squared_error: 0.4317, root_mean_squared_error: 0.3455, root_relative_squared_error: 0.8002, scimark_benchmark: 944.4621, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.856, f_measure: 0.8097, kappa: 0.4685, kb_relative_information_score: 117.2083, mean_absolute_error: 0.239, mean_prior_absolute_error: 0.3735, number_of_instances: 339, precision: 0.8092, predictive_accuracy: 0.8201, prior_entropy: 0.8101, recall: 0.8201, relative_absolute_error: 0.6398, root_mean_prior_squared_error: 0.4317, root_mean_squared_error: 0.3578, root_relative_squared_error: 0.8286, scimark_benchmark: 1362.9924,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8886, f_measure: 0.8553, kappa: 0.6044, kb_relative_information_score: 154.1816, mean_absolute_error: 0.1989, mean_prior_absolute_error: 0.3735, number_of_instances: 339, precision: 0.8541, predictive_accuracy: 0.8584, prior_entropy: 0.8101, recall: 0.8584, relative_absolute_error: 0.5325, root_mean_prior_squared_error: 0.4317, root_mean_squared_error: 0.33, root_relative_squared_error: 0.7644, scimark_benchmark: 1313.8988,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6708, f_measure: 0.797, kappa: 0.4184, kb_relative_information_score: 158.9395, mean_absolute_error: 0.177, mean_prior_absolute_error: 0.3735, number_of_instances: 339, precision: 0.8219, predictive_accuracy: 0.823, prior_entropy: 0.8101, recall: 0.823, relative_absolute_error: 0.4738, root_mean_prior_squared_error: 0.4317, root_mean_squared_error: 0.4207, root_relative_squared_error: 0.9745, scimark_benchmark: 1303.5632, usercpu_time_millis: 50, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 30,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6708, f_measure: 0.797, kappa: 0.4184, kb_relative_information_score: 158.9395, mean_absolute_error: 0.177, mean_prior_absolute_error: 0.3735, number_of_instances: 339, precision: 0.8219, predictive_accuracy: 0.823, prior_entropy: 0.8101, recall: 0.823, relative_absolute_error: 0.4738, root_mean_prior_squared_error: 0.4317, root_mean_squared_error: 0.4207, root_relative_squared_error: 0.9745, scimark_benchmark: 1342.8584, usercpu_time_millis: 40, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.856, f_measure: 0.8097, kappa: 0.4685, kb_relative_information_score: 117.2083, mean_absolute_error: 0.239, mean_prior_absolute_error: 0.3735, number_of_instances: 339, precision: 0.8092, predictive_accuracy: 0.8201, prior_entropy: 0.8101, recall: 0.8201, relative_absolute_error: 0.6398, root_mean_prior_squared_error: 0.4317, root_mean_squared_error: 0.3578, root_relative_squared_error: 0.8286, scimark_benchmark: 930.5999,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8741, f_measure: 0.8515, kappa: 0.5872, kb_relative_information_score: 133.659, mean_absolute_error: 0.2224, mean_prior_absolute_error: 0.3735, number_of_instances: 339, precision: 0.8528, predictive_accuracy: 0.8584, prior_entropy: 0.8101, recall: 0.8584, relative_absolute_error: 0.5955, root_mean_prior_squared_error: 0.4317, root_mean_squared_error: 0.3341, root_relative_squared_error: 0.7739, scimark_benchmark: 1260.1387, usercpu_time_millis: 120, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 100,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8609, f_measure: 0.8453, kappa: 0.5654, kb_relative_information_score: 141.9218, mean_absolute_error: 0.2109, mean_prior_absolute_error: 0.3735, number_of_instances: 339, precision: 0.8508, predictive_accuracy: 0.8555, prior_entropy: 0.8101, recall: 0.8555, relative_absolute_error: 0.5646, root_mean_prior_squared_error: 0.4317, root_mean_squared_error: 0.3411, root_relative_squared_error: 0.7902, scimark_benchmark: 1280.6338, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8886, f_measure: 0.8553, kappa: 0.6044, kb_relative_information_score: 154.1816, mean_absolute_error: 0.1989, mean_prior_absolute_error: 0.3735, number_of_instances: 339, precision: 0.8541, predictive_accuracy: 0.8584, prior_entropy: 0.8101, recall: 0.8584, relative_absolute_error: 0.5325, root_mean_prior_squared_error: 0.4317, root_mean_squared_error: 0.33, root_relative_squared_error: 0.7644, scimark_benchmark: 1345.7204,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.856, f_measure: 0.8097, kappa: 0.4685, kb_relative_information_score: 117.2083, mean_absolute_error: 0.239, mean_prior_absolute_error: 0.3735, number_of_instances: 339, precision: 0.8092, predictive_accuracy: 0.8201, prior_entropy: 0.8101, recall: 0.8201, relative_absolute_error: 0.6398, root_mean_prior_squared_error: 0.4317, root_mean_squared_error: 0.3578, root_relative_squared_error: 0.8286, scimark_benchmark: 1350.073,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.856, f_measure: 0.8097, kappa: 0.4685, kb_relative_information_score: 117.2083, mean_absolute_error: 0.239, mean_prior_absolute_error: 0.3735, number_of_instances: 339, precision: 0.8092, predictive_accuracy: 0.8201, prior_entropy: 0.8101, recall: 0.8201, relative_absolute_error: 0.6398, root_mean_prior_squared_error: 0.4317, root_mean_squared_error: 0.3578, root_relative_squared_error: 0.8286, scimark_benchmark: 933.1165, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8741, f_measure: 0.8515, kappa: 0.5872, kb_relative_information_score: 133.659, mean_absolute_error: 0.2224, mean_prior_absolute_error: 0.3735, number_of_instances: 339, precision: 0.8528, predictive_accuracy: 0.8584, prior_entropy: 0.8101, recall: 0.8584, relative_absolute_error: 0.5955, root_mean_prior_squared_error: 0.4317, root_mean_squared_error: 0.3341, root_relative_squared_error: 0.7739, scimark_benchmark: 1345.7204, usercpu_time_millis: 100, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 80,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8594, f_measure: 0.8443, kappa: 0.5707, kb_relative_information_score: 94.2661, mean_absolute_error: 0.2673, mean_prior_absolute_error: 0.3735, number_of_instances: 339, precision: 0.8434, predictive_accuracy: 0.8496, prior_entropy: 0.8101, recall: 0.8496, relative_absolute_error: 0.7156, root_mean_prior_squared_error: 0.4317, root_mean_squared_error: 0.3455, root_relative_squared_error: 0.8002, scimark_benchmark: 1345.7204, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8594, f_measure: 0.8443, kappa: 0.5707, kb_relative_information_score: 94.2661, mean_absolute_error: 0.2673, mean_prior_absolute_error: 0.3735, number_of_instances: 339, precision: 0.8434, predictive_accuracy: 0.8496, prior_entropy: 0.8101, recall: 0.8496, relative_absolute_error: 0.7156, root_mean_prior_squared_error: 0.4317, root_mean_squared_error: 0.3455, root_relative_squared_error: 0.8002, scimark_benchmark: 1328.941,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7946, f_measure: 0.7822, kappa: 0.3928, kb_relative_information_score: 101.9096, mean_absolute_error: 0.2515, mean_prior_absolute_error: 0.3735, number_of_instances: 339, precision: 0.7792, predictive_accuracy: 0.7935, prior_entropy: 0.8101, recall: 0.7935, relative_absolute_error: 0.6733, root_mean_prior_squared_error: 0.4317, root_mean_squared_error: 0.3929, root_relative_squared_error: 0.9102, scimark_benchmark: 1301.7387,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8609, f_measure: 0.8453, kappa: 0.5654, kb_relative_information_score: 141.9218, mean_absolute_error: 0.2109, mean_prior_absolute_error: 0.3735, number_of_instances: 339, precision: 0.8508, predictive_accuracy: 0.8555, prior_entropy: 0.8101, recall: 0.8555, relative_absolute_error: 0.5646, root_mean_prior_squared_error: 0.4317, root_mean_squared_error: 0.3411, root_relative_squared_error: 0.7902, scimark_benchmark: 1342.1678, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8822, f_measure: 0.862, kappa: 0.624, kb_relative_information_score: 168.483, mean_absolute_error: 0.1806, mean_prior_absolute_error: 0.3735, number_of_instances: 339, precision: 0.8608, predictive_accuracy: 0.8643, prior_entropy: 0.8101, recall: 0.8643, relative_absolute_error: 0.4834, root_mean_prior_squared_error: 0.4317, root_mean_squared_error: 0.3224, root_relative_squared_error: 0.7468, scimark_benchmark: 934.4732, usercpu_time_millis: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8594, f_measure: 0.8443, kappa: 0.5707, kb_relative_information_score: 94.2661, mean_absolute_error: 0.2673, mean_prior_absolute_error: 0.3735, number_of_instances: 339, precision: 0.8434, predictive_accuracy: 0.8496, prior_entropy: 0.8101, recall: 0.8496, relative_absolute_error: 0.7156, root_mean_prior_squared_error: 0.4317, root_mean_squared_error: 0.3455, root_relative_squared_error: 0.8002, scimark_benchmark: 1360.2999, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7946, f_measure: 0.7822, kappa: 0.3928, kb_relative_information_score: 101.9096, mean_absolute_error: 0.2515, mean_prior_absolute_error: 0.3735, number_of_instances: 339, precision: 0.7792, predictive_accuracy: 0.7935, prior_entropy: 0.8101, recall: 0.7935, relative_absolute_error: 0.6733, root_mean_prior_squared_error: 0.4317, root_mean_squared_error: 0.3929, root_relative_squared_error: 0.9102, scimark_benchmark: 1249.4068,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8594, f_measure: 0.8443, kappa: 0.5707, kb_relative_information_score: 94.2661, mean_absolute_error: 0.2673, mean_prior_absolute_error: 0.3735, number_of_instances: 339, precision: 0.8434, predictive_accuracy: 0.8496, prior_entropy: 0.8101, recall: 0.8496, relative_absolute_error: 0.7156, root_mean_prior_squared_error: 0.4317, root_mean_squared_error: 0.3455, root_relative_squared_error: 0.8002, scimark_benchmark: 1206.8386,

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