OpenML
Supervised Classification on Bioresponse

Supervised Classification on Bioresponse

Task 145677 Supervised Classification Bioresponse 9363 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4988, f_measure: 0.3813, kb_relative_information_score: 0.0074, mean_absolute_error: 0.4964, mean_prior_absolute_error: 0.4964, number_of_instances: 3751, precision: 0.294, predictive_accuracy: 0.5423, prior_entropy: 0.9948, recall: 0.5423, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4982, root_mean_squared_error: 0.4982, root_relative_squared_error: 1, scimark_benchmark: 1839.5885, usercpu_time_millis: 11.985, usercpu_time_millis_testing: 2.56, usercpu_time_millis_training: 9.425,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.725, f_measure: 0.7372, kappa: 0.4719, kb_relative_information_score: 982.1346, mean_absolute_error: 0.3858, mean_prior_absolute_error: 0.4964, number_of_instances: 3751, precision: 0.7383, predictive_accuracy: 0.7369, prior_entropy: 0.9948, recall: 0.7369, relative_absolute_error: 0.7771, root_mean_prior_squared_error: 0.4982, root_mean_squared_error: 0.4393, root_relative_squared_error: 0.8817, scimark_benchmark: 1772.8637, usercpu_time_millis: 20.861, usercpu_time_millis_testing: 3.816, usercpu_time_millis_training: 17.045,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4988, f_measure: 0.3813, kb_relative_information_score: 0.0074, mean_absolute_error: 0.4964, mean_prior_absolute_error: 0.4964, number_of_instances: 3751, precision: 0.294, predictive_accuracy: 0.5423, prior_entropy: 0.9948, recall: 0.5423, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4982, root_mean_squared_error: 0.4982, root_relative_squared_error: 1, scimark_benchmark: 1856.5402, usercpu_time_millis: 10.713, usercpu_time_millis_testing: 2.241, usercpu_time_millis_training: 8.472,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4988, f_measure: 0.3813, kb_relative_information_score: 0.0074, mean_absolute_error: 0.4964, mean_prior_absolute_error: 0.4964, number_of_instances: 3751, precision: 0.294, predictive_accuracy: 0.5423, prior_entropy: 0.9948, recall: 0.5423, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4982, root_mean_squared_error: 0.4982, root_relative_squared_error: 1, scimark_benchmark: 1736.9559, usercpu_time_millis: 10.77, usercpu_time_millis_testing: 2.223, usercpu_time_millis_training: 8.547,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4988, f_measure: 0.3813, kb_relative_information_score: 0.0074, mean_absolute_error: 0.4964, mean_prior_absolute_error: 0.4964, number_of_instances: 3751, precision: 0.294, predictive_accuracy: 0.5423, prior_entropy: 0.9948, recall: 0.5423, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4982, root_mean_squared_error: 0.4982, root_relative_squared_error: 1, scimark_benchmark: 1747.9508, usercpu_time_millis: 11.82, usercpu_time_millis_testing: 2.482, usercpu_time_millis_training: 9.338,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7545, f_measure: 0.7561, kappa: 0.5081, kb_relative_information_score: 1174.49, mean_absolute_error: 0.3617, mean_prior_absolute_error: 0.4964, number_of_instances: 3751, precision: 0.7602, predictive_accuracy: 0.7585, prior_entropy: 0.9948, recall: 0.7585, relative_absolute_error: 0.7286, root_mean_prior_squared_error: 0.4982, root_mean_squared_error: 0.4263, root_relative_squared_error: 0.8557, scimark_benchmark: 1849.8294, usercpu_time_millis: 17.789, usercpu_time_millis_testing: 2.325, usercpu_time_millis_training: 15.464,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4988, f_measure: 0.3813, kb_relative_information_score: 0.0074, mean_absolute_error: 0.4964, mean_prior_absolute_error: 0.4964, number_of_instances: 3751, precision: 0.294, predictive_accuracy: 0.5423, prior_entropy: 0.9948, recall: 0.5423, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4982, root_mean_squared_error: 0.4982, root_relative_squared_error: 1, scimark_benchmark: 1914.0415, usercpu_time_millis: 10.457, usercpu_time_millis_testing: 2.217, usercpu_time_millis_training: 8.24,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.725, f_measure: 0.7372, kappa: 0.4719, kb_relative_information_score: 982.1346, mean_absolute_error: 0.3858, mean_prior_absolute_error: 0.4964, number_of_instances: 3751, precision: 0.7383, predictive_accuracy: 0.7369, prior_entropy: 0.9948, recall: 0.7369, relative_absolute_error: 0.7771, root_mean_prior_squared_error: 0.4982, root_mean_squared_error: 0.4393, root_relative_squared_error: 0.8817, scimark_benchmark: 1751.1115, usercpu_time_millis: 12.94, usercpu_time_millis_testing: 2.442, usercpu_time_millis_training: 10.498,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4988, f_measure: 0.3813, kb_relative_information_score: 0.0074, mean_absolute_error: 0.4964, mean_prior_absolute_error: 0.4964, number_of_instances: 3751, precision: 0.294, predictive_accuracy: 0.5423, prior_entropy: 0.9948, recall: 0.5423, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4982, root_mean_squared_error: 0.4982, root_relative_squared_error: 1, scimark_benchmark: 1904.7146, usercpu_time_millis: 10.501, usercpu_time_millis_testing: 2.232, usercpu_time_millis_training: 8.269,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4988, f_measure: 0.3813, kb_relative_information_score: 0.0074, mean_absolute_error: 0.4964, mean_prior_absolute_error: 0.4964, number_of_instances: 3751, precision: 0.294, predictive_accuracy: 0.5423, prior_entropy: 0.9948, recall: 0.5423, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4982, root_mean_squared_error: 0.4982, root_relative_squared_error: 1, scimark_benchmark: 2137.2696, usercpu_time_millis: 10.49, usercpu_time_millis_testing: 2.241, usercpu_time_millis_training: 8.249,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.725, f_measure: 0.7372, kappa: 0.4719, kb_relative_information_score: 982.1346, mean_absolute_error: 0.3858, mean_prior_absolute_error: 0.4964, number_of_instances: 3751, precision: 0.7383, predictive_accuracy: 0.7369, prior_entropy: 0.9948, recall: 0.7369, relative_absolute_error: 0.7771, root_mean_prior_squared_error: 0.4982, root_mean_squared_error: 0.4393, root_relative_squared_error: 0.8817, scimark_benchmark: 1855.0231, usercpu_time_millis: 14.928, usercpu_time_millis_testing: 2.299, usercpu_time_millis_training: 12.629,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.725, f_measure: 0.7372, kappa: 0.4719, kb_relative_information_score: 982.1346, mean_absolute_error: 0.3858, mean_prior_absolute_error: 0.4964, number_of_instances: 3751, precision: 0.7383, predictive_accuracy: 0.7369, prior_entropy: 0.9948, recall: 0.7369, relative_absolute_error: 0.7771, root_mean_prior_squared_error: 0.4982, root_mean_squared_error: 0.4393, root_relative_squared_error: 0.8817, scimark_benchmark: 1918.9123, usercpu_time_millis: 13.055, usercpu_time_millis_testing: 2.234, usercpu_time_millis_training: 10.821,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4988, f_measure: 0.3813, kb_relative_information_score: 0.0074, mean_absolute_error: 0.4964, mean_prior_absolute_error: 0.4964, number_of_instances: 3751, precision: 0.294, predictive_accuracy: 0.5423, prior_entropy: 0.9948, recall: 0.5423, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4982, root_mean_squared_error: 0.4982, root_relative_squared_error: 1, scimark_benchmark: 2073.3836, usercpu_time_millis: 10.567, usercpu_time_millis_testing: 2.219, usercpu_time_millis_training: 8.348,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.725, f_measure: 0.7372, kappa: 0.4719, kb_relative_information_score: 982.1346, mean_absolute_error: 0.3858, mean_prior_absolute_error: 0.4964, number_of_instances: 3751, precision: 0.7383, predictive_accuracy: 0.7369, prior_entropy: 0.9948, recall: 0.7369, relative_absolute_error: 0.7771, root_mean_prior_squared_error: 0.4982, root_mean_squared_error: 0.4393, root_relative_squared_error: 0.8817, scimark_benchmark: 1827.4655, usercpu_time_millis: 17.181, usercpu_time_millis_testing: 3.109, usercpu_time_millis_training: 14.072,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4988, f_measure: 0.3813, kb_relative_information_score: 0.0074, mean_absolute_error: 0.4964, mean_prior_absolute_error: 0.4964, number_of_instances: 3751, precision: 0.294, predictive_accuracy: 0.5423, prior_entropy: 0.9948, recall: 0.5423, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4982, root_mean_squared_error: 0.4982, root_relative_squared_error: 1, scimark_benchmark: 1943.2854, usercpu_time_millis: 10.457, usercpu_time_millis_testing: 2.187, usercpu_time_millis_training: 8.27,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4988, f_measure: 0.3813, kb_relative_information_score: 0.0074, mean_absolute_error: 0.4964, mean_prior_absolute_error: 0.4964, number_of_instances: 3751, precision: 0.294, predictive_accuracy: 0.5423, prior_entropy: 0.9948, recall: 0.5423, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4982, root_mean_squared_error: 0.4982, root_relative_squared_error: 1, scimark_benchmark: 1855.0776, usercpu_time_millis: 10.805, usercpu_time_millis_testing: 2.316, usercpu_time_millis_training: 8.489,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4988, f_measure: 0.3813, kb_relative_information_score: 0.0074, mean_absolute_error: 0.4964, mean_prior_absolute_error: 0.4964, number_of_instances: 3751, precision: 0.294, predictive_accuracy: 0.5423, prior_entropy: 0.9948, recall: 0.5423, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4982, root_mean_squared_error: 0.4982, root_relative_squared_error: 1, scimark_benchmark: 1733.299, usercpu_time_millis: 11.031, usercpu_time_millis_testing: 2.302, usercpu_time_millis_training: 8.729,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4988, f_measure: 0.3813, kb_relative_information_score: 0.0074, mean_absolute_error: 0.4964, mean_prior_absolute_error: 0.4964, number_of_instances: 3751, precision: 0.294, predictive_accuracy: 0.5423, prior_entropy: 0.9948, recall: 0.5423, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4982, root_mean_squared_error: 0.4982, root_relative_squared_error: 1, scimark_benchmark: 1854.6195, usercpu_time_millis: 10.808, usercpu_time_millis_testing: 2.323, usercpu_time_millis_training: 8.485,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.725, f_measure: 0.7372, kappa: 0.4719, kb_relative_information_score: 982.1346, mean_absolute_error: 0.3858, mean_prior_absolute_error: 0.4964, number_of_instances: 3751, precision: 0.7383, predictive_accuracy: 0.7369, prior_entropy: 0.9948, recall: 0.7369, relative_absolute_error: 0.7771, root_mean_prior_squared_error: 0.4982, root_mean_squared_error: 0.4393, root_relative_squared_error: 0.8817, scimark_benchmark: 1855.0776, usercpu_time_millis: 12.824, usercpu_time_millis_testing: 2.293, usercpu_time_millis_training: 10.531,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.725, f_measure: 0.7372, kappa: 0.4719, kb_relative_information_score: 982.1346, mean_absolute_error: 0.3858, mean_prior_absolute_error: 0.4964, number_of_instances: 3751, precision: 0.7383, predictive_accuracy: 0.7369, prior_entropy: 0.9948, recall: 0.7369, relative_absolute_error: 0.7771, root_mean_prior_squared_error: 0.4982, root_mean_squared_error: 0.4393, root_relative_squared_error: 0.8817, scimark_benchmark: 1732.3996, usercpu_time_millis: 11.401, usercpu_time_millis_testing: 2.33, usercpu_time_millis_training: 9.071,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.725, f_measure: 0.7372, kappa: 0.4719, kb_relative_information_score: 982.1346, mean_absolute_error: 0.3858, mean_prior_absolute_error: 0.4964, number_of_instances: 3751, precision: 0.7383, predictive_accuracy: 0.7369, prior_entropy: 0.9948, recall: 0.7369, relative_absolute_error: 0.7771, root_mean_prior_squared_error: 0.4982, root_mean_squared_error: 0.4393, root_relative_squared_error: 0.8817, scimark_benchmark: 1858.762, usercpu_time_millis: 12.44, usercpu_time_millis_testing: 2.304, usercpu_time_millis_training: 10.136,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4988, f_measure: 0.3813, kb_relative_information_score: 0.0074, mean_absolute_error: 0.4964, mean_prior_absolute_error: 0.4964, number_of_instances: 3751, precision: 0.294, predictive_accuracy: 0.5423, prior_entropy: 0.9948, recall: 0.5423, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4982, root_mean_squared_error: 0.4982, root_relative_squared_error: 1, scimark_benchmark: 1734.2699, usercpu_time_millis: 15.218, usercpu_time_millis_testing: 3.134, usercpu_time_millis_training: 12.084,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4988, f_measure: 0.3813, kb_relative_information_score: 0.0074, mean_absolute_error: 0.4964, mean_prior_absolute_error: 0.4964, number_of_instances: 3751, precision: 0.294, predictive_accuracy: 0.5423, prior_entropy: 0.9948, recall: 0.5423, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4982, root_mean_squared_error: 0.4982, root_relative_squared_error: 1, scimark_benchmark: 1933.0696, usercpu_time_millis: 10.462, usercpu_time_millis_testing: 2.183, usercpu_time_millis_training: 8.279,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.725, f_measure: 0.7372, kappa: 0.4719, kb_relative_information_score: 982.1346, mean_absolute_error: 0.3858, mean_prior_absolute_error: 0.4964, number_of_instances: 3751, precision: 0.7383, predictive_accuracy: 0.7369, prior_entropy: 0.9948, recall: 0.7369, relative_absolute_error: 0.7771, root_mean_prior_squared_error: 0.4982, root_mean_squared_error: 0.4393, root_relative_squared_error: 0.8817, scimark_benchmark: 1933.1832, usercpu_time_millis: 10.805, usercpu_time_millis_testing: 2.219, usercpu_time_millis_training: 8.586,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.725, f_measure: 0.7372, kappa: 0.4719, kb_relative_information_score: 982.1346, mean_absolute_error: 0.3858, mean_prior_absolute_error: 0.4964, number_of_instances: 3751, precision: 0.7383, predictive_accuracy: 0.7369, prior_entropy: 0.9948, recall: 0.7369, relative_absolute_error: 0.7771, root_mean_prior_squared_error: 0.4982, root_mean_squared_error: 0.4393, root_relative_squared_error: 0.8817, scimark_benchmark: 1830.9008, usercpu_time_millis: 16.048, usercpu_time_millis_testing: 3.217, usercpu_time_millis_training: 12.831,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.725, f_measure: 0.7372, kappa: 0.4719, kb_relative_information_score: 982.1346, mean_absolute_error: 0.3858, mean_prior_absolute_error: 0.4964, number_of_instances: 3751, precision: 0.7383, predictive_accuracy: 0.7369, prior_entropy: 0.9948, recall: 0.7369, relative_absolute_error: 0.7771, root_mean_prior_squared_error: 0.4982, root_mean_squared_error: 0.4393, root_relative_squared_error: 0.8817, scimark_benchmark: 1736.5552, usercpu_time_millis: 15.771, usercpu_time_millis_testing: 2.689, usercpu_time_millis_training: 13.082,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4988, f_measure: 0.3813, kb_relative_information_score: 0.0074, mean_absolute_error: 0.4964, mean_prior_absolute_error: 0.4964, number_of_instances: 3751, precision: 0.294, predictive_accuracy: 0.5423, prior_entropy: 0.9948, recall: 0.5423, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4982, root_mean_squared_error: 0.4982, root_relative_squared_error: 1, scimark_benchmark: 1824.9527, usercpu_time_millis: 15.709, usercpu_time_millis_testing: 3.277, usercpu_time_millis_training: 12.432,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.725, f_measure: 0.7372, kappa: 0.4719, kb_relative_information_score: 982.1346, mean_absolute_error: 0.3858, mean_prior_absolute_error: 0.4964, number_of_instances: 3751, precision: 0.7383, predictive_accuracy: 0.7369, prior_entropy: 0.9948, recall: 0.7369, relative_absolute_error: 0.7771, root_mean_prior_squared_error: 0.4982, root_mean_squared_error: 0.4393, root_relative_squared_error: 0.8817, scimark_benchmark: 1830.9008, usercpu_time_millis: 16.287, usercpu_time_millis_testing: 3.289, usercpu_time_millis_training: 12.998,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4988, f_measure: 0.3813, kb_relative_information_score: 0.0074, mean_absolute_error: 0.4964, mean_prior_absolute_error: 0.4964, number_of_instances: 3751, precision: 0.294, predictive_accuracy: 0.5423, prior_entropy: 0.9948, recall: 0.5423, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4982, root_mean_squared_error: 0.4982, root_relative_squared_error: 1, scimark_benchmark: 1855.6765, usercpu_time_millis: 11.066, usercpu_time_millis_testing: 2.358, usercpu_time_millis_training: 8.708,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4988, f_measure: 0.3813, kb_relative_information_score: 0.0074, mean_absolute_error: 0.4964, mean_prior_absolute_error: 0.4964, number_of_instances: 3751, precision: 0.294, predictive_accuracy: 0.5423, prior_entropy: 0.9948, recall: 0.5423, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4982, root_mean_squared_error: 0.4982, root_relative_squared_error: 1, scimark_benchmark: 1735.7557, usercpu_time_millis: 13.088, usercpu_time_millis_testing: 2.514, usercpu_time_millis_training: 10.574,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.725, f_measure: 0.7372, kappa: 0.4719, kb_relative_information_score: 982.1346, mean_absolute_error: 0.3858, mean_prior_absolute_error: 0.4964, number_of_instances: 3751, precision: 0.7383, predictive_accuracy: 0.7369, prior_entropy: 0.9948, recall: 0.7369, relative_absolute_error: 0.7771, root_mean_prior_squared_error: 0.4982, root_mean_squared_error: 0.4393, root_relative_squared_error: 0.8817, scimark_benchmark: 1857.5664, usercpu_time_millis: 15.544, usercpu_time_millis_testing: 2.361, usercpu_time_millis_training: 13.183,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.725, f_measure: 0.7372, kappa: 0.4719, kb_relative_information_score: 982.1346, mean_absolute_error: 0.3858, mean_prior_absolute_error: 0.4964, number_of_instances: 3751, precision: 0.7383, predictive_accuracy: 0.7369, prior_entropy: 0.9948, recall: 0.7369, relative_absolute_error: 0.7771, root_mean_prior_squared_error: 0.4982, root_mean_squared_error: 0.4393, root_relative_squared_error: 0.8817, scimark_benchmark: 1851.9726, usercpu_time_millis: 12.8, usercpu_time_millis_testing: 2.348, usercpu_time_millis_training: 10.452,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4988, f_measure: 0.3813, kb_relative_information_score: 0.0074, mean_absolute_error: 0.4964, mean_prior_absolute_error: 0.4964, number_of_instances: 3751, precision: 0.294, predictive_accuracy: 0.5423, prior_entropy: 0.9948, recall: 0.5423, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4982, root_mean_squared_error: 0.4982, root_relative_squared_error: 1, scimark_benchmark: 1861.2461, usercpu_time_millis: 14.036, usercpu_time_millis_testing: 2.761, usercpu_time_millis_training: 11.275,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.725, f_measure: 0.7372, kappa: 0.4719, kb_relative_information_score: 982.1346, mean_absolute_error: 0.3858, mean_prior_absolute_error: 0.4964, number_of_instances: 3751, precision: 0.7383, predictive_accuracy: 0.7369, prior_entropy: 0.9948, recall: 0.7369, relative_absolute_error: 0.7771, root_mean_prior_squared_error: 0.4982, root_mean_squared_error: 0.4393, root_relative_squared_error: 0.8817, scimark_benchmark: 1856.5802, usercpu_time_millis: 13.28, usercpu_time_millis_testing: 2.353, usercpu_time_millis_training: 10.927,
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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

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From your own software

Use one of our APIs to download data from OpenML and upload your results

OpenML APIs