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: 1857.0384, usercpu_time_millis: 13.146, usercpu_time_millis_testing: 2.766, usercpu_time_millis_training: 10.38,
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: 1739.3756, usercpu_time_millis: 12.848, usercpu_time_millis_testing: 2.297, usercpu_time_millis_training: 10.551,
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: 1853.3841, usercpu_time_millis: 11.832, usercpu_time_millis_testing: 2.65, usercpu_time_millis_training: 9.182,
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: 1857.0384, usercpu_time_millis: 10.885, usercpu_time_millis_testing: 2.334, usercpu_time_millis_training: 8.551,
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: 1737.8652, usercpu_time_millis: 13.297, usercpu_time_millis_testing: 2.425, usercpu_time_millis_training: 10.872,
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: 1782.2081, usercpu_time_millis: 14.062, usercpu_time_millis_testing: 2.705, usercpu_time_millis_training: 11.357,
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: 1857.1082, usercpu_time_millis: 11.502, usercpu_time_millis_testing: 2.459, usercpu_time_millis_training: 9.043,
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: 1857.1082, usercpu_time_millis: 11.134, usercpu_time_millis_testing: 2.35, usercpu_time_millis_training: 8.784,
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: 1857.0384, usercpu_time_millis: 13.757, usercpu_time_millis_testing: 2.562, usercpu_time_millis_training: 11.195,
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: 1731.4775, usercpu_time_millis: 16.44, usercpu_time_millis_testing: 2.42, usercpu_time_millis_training: 14.02,
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: 1849.3014, usercpu_time_millis: 13.774, usercpu_time_millis_testing: 2.574, usercpu_time_millis_training: 11.2,
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: 1852.859, usercpu_time_millis: 10.969, usercpu_time_millis_testing: 2.345, usercpu_time_millis_training: 8.624,
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: 1853.9121, usercpu_time_millis: 10.994, usercpu_time_millis_testing: 2.329, usercpu_time_millis_training: 8.665,
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: 1853.9121, usercpu_time_millis: 10.723, usercpu_time_millis_testing: 2.269, usercpu_time_millis_training: 8.454,
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: 1857.1082, usercpu_time_millis: 13.717, usercpu_time_millis_testing: 2.673, usercpu_time_millis_training: 11.044,
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: 1775.0081, usercpu_time_millis: 14.357, usercpu_time_millis_testing: 2.62, usercpu_time_millis_training: 11.737,
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: 1735.764, usercpu_time_millis: 16.132, usercpu_time_millis_testing: 3.258, usercpu_time_millis_training: 12.874,
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: 1853.3841, usercpu_time_millis: 12.098, usercpu_time_millis_testing: 2.579, usercpu_time_millis_training: 9.519,
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: 1849.8294, usercpu_time_millis: 12.276, usercpu_time_millis_testing: 2.38, usercpu_time_millis_training: 9.896,
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: 1858.0974, usercpu_time_millis: 11.225, usercpu_time_millis_testing: 2.411, usercpu_time_millis_training: 8.814,
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: 1854.9533, usercpu_time_millis: 12.023, usercpu_time_millis_testing: 2.548, usercpu_time_millis_training: 9.475,
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: 1855.0232, usercpu_time_millis: 10.752, usercpu_time_millis_testing: 2.209, usercpu_time_millis_training: 8.543,
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: 1854.4951, usercpu_time_millis: 16.263, usercpu_time_millis_testing: 2.329, usercpu_time_millis_training: 13.934,
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: 1853.9121, usercpu_time_millis: 13.829, usercpu_time_millis_testing: 2.661, usercpu_time_millis_training: 11.168,
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: 1858.6775, usercpu_time_millis: 11.305, usercpu_time_millis_testing: 2.393, usercpu_time_millis_training: 8.912,
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: 1856.0093, usercpu_time_millis: 13.589, usercpu_time_millis_testing: 2.62, usercpu_time_millis_training: 10.969,
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: 1782.8334, usercpu_time_millis: 11.253, usercpu_time_millis_testing: 2.251, usercpu_time_millis_training: 9.002,
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: 1736.9559, usercpu_time_millis: 18.667, usercpu_time_millis_testing: 3.349, usercpu_time_millis_training: 15.318,
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: 1841.5689, usercpu_time_millis: 10.892, usercpu_time_millis_testing: 2.278, usercpu_time_millis_training: 8.614,
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: 1852.9259, usercpu_time_millis: 13.623, usercpu_time_millis_testing: 2.319, usercpu_time_millis_training: 11.304,
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: 1853.454, usercpu_time_millis: 11.236, usercpu_time_millis_testing: 2.429, usercpu_time_millis_training: 8.807,
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: 1853.454, usercpu_time_millis: 11.321, usercpu_time_millis_testing: 2.408, usercpu_time_millis_training: 8.913,
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: 1738.3274, usercpu_time_millis: 11.145, usercpu_time_millis_testing: 2.263, usercpu_time_millis_training: 8.882,
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: 1853.9121, usercpu_time_millis: 11.383, usercpu_time_millis_testing: 2.425, usercpu_time_millis_training: 8.958,
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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