Task
Supervised Classification on wine

Supervised Classification on wine

Task 4541 Supervised Classification wine 220 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9216, f_measure: 0.9177, kappa: 0.8279, kb_relative_information_score: 1443.1614, mean_absolute_error: 0.0919, mean_prior_absolute_error: 0.4798, number_of_instances: 1780, precision: 0.9178, predictive_accuracy: 0.918, prior_entropy: 0.971, recall: 0.918, relative_absolute_error: 0.1914, root_mean_prior_squared_error: 0.4897, root_mean_squared_error: 0.2758, root_relative_squared_error: 0.5632, scimark_benchmark: 906.0979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9874, f_measure: 0.9616, kappa: 0.9197, kb_relative_information_score: 1553.3609, mean_absolute_error: 0.0665, mean_prior_absolute_error: 0.4798, number_of_instances: 1780, precision: 0.9621, predictive_accuracy: 0.9618, prior_entropy: 0.971, recall: 0.9618, relative_absolute_error: 0.1385, root_mean_prior_squared_error: 0.4897, root_mean_squared_error: 0.1787, root_relative_squared_error: 0.365, scimark_benchmark: 972.587, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9843, f_measure: 0.9367, kappa: 0.8673, kb_relative_information_score: 1509.9994, mean_absolute_error: 0.0736, mean_prior_absolute_error: 0.4798, number_of_instances: 1780, precision: 0.9377, predictive_accuracy: 0.9371, prior_entropy: 0.971, recall: 0.9371, relative_absolute_error: 0.1534, root_mean_prior_squared_error: 0.4897, root_mean_squared_error: 0.2211, root_relative_squared_error: 0.4516, scimark_benchmark: 934.3687, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5437, f_measure: 0.5255, kappa: 0.1032, kb_relative_information_score: 404.7158, mean_absolute_error: 0.364, mean_prior_absolute_error: 0.4798, number_of_instances: 1780, precision: 0.7733, predictive_accuracy: 0.636, prior_entropy: 0.971, recall: 0.636, relative_absolute_error: 0.7588, root_mean_prior_squared_error: 0.4897, root_mean_squared_error: 0.6034, root_relative_squared_error: 1.2322, scimark_benchmark: 944.1067, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5437, f_measure: 0.5255, kappa: 0.1032, kb_relative_information_score: 404.7158, mean_absolute_error: 0.364, mean_prior_absolute_error: 0.4798, number_of_instances: 1780, precision: 0.7733, predictive_accuracy: 0.636, prior_entropy: 0.971, recall: 0.636, relative_absolute_error: 0.7588, root_mean_prior_squared_error: 0.4897, root_mean_squared_error: 0.6034, root_relative_squared_error: 1.2322, scimark_benchmark: 904.0772, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9991, f_measure: 0.9819, kappa: 0.9622, kb_relative_information_score: 1679.8571, mean_absolute_error: 0.0286, mean_prior_absolute_error: 0.4798, number_of_instances: 1780, precision: 0.9825, predictive_accuracy: 0.982, prior_entropy: 0.971, recall: 0.982, relative_absolute_error: 0.0597, root_mean_prior_squared_error: 0.4897, root_mean_squared_error: 0.1204, root_relative_squared_error: 0.246, scimark_benchmark: 941.6675, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9991, f_measure: 0.9819, kappa: 0.9622, kb_relative_information_score: 1679.8571, mean_absolute_error: 0.0286, mean_prior_absolute_error: 0.4798, number_of_instances: 1780, precision: 0.9825, predictive_accuracy: 0.982, prior_entropy: 0.971, recall: 0.982, relative_absolute_error: 0.0597, root_mean_prior_squared_error: 0.4897, root_mean_squared_error: 0.1204, root_relative_squared_error: 0.246, scimark_benchmark: 941.6675,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9991, f_measure: 0.9819, kappa: 0.9622, kb_relative_information_score: 1679.8571, mean_absolute_error: 0.0286, mean_prior_absolute_error: 0.4798, number_of_instances: 1780, precision: 0.9825, predictive_accuracy: 0.982, prior_entropy: 0.971, recall: 0.982, relative_absolute_error: 0.0597, root_mean_prior_squared_error: 0.4897, root_mean_squared_error: 0.1204, root_relative_squared_error: 0.246, scimark_benchmark: 934.695,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9723, f_measure: 0.9224, kappa: 0.8373, kb_relative_information_score: 1358.26, mean_absolute_error: 0.1223, mean_prior_absolute_error: 0.4798, number_of_instances: 1780, precision: 0.9238, predictive_accuracy: 0.923, prior_entropy: 0.971, recall: 0.923, relative_absolute_error: 0.2549, root_mean_prior_squared_error: 0.4897, root_mean_squared_error: 0.2346, root_relative_squared_error: 0.4791, scimark_benchmark: 938.191,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9984, f_measure: 0.9826, kappa: 0.9636, kb_relative_information_score: 1580.5105, mean_absolute_error: 0.0625, mean_prior_absolute_error: 0.4798, number_of_instances: 1780, precision: 0.9826, predictive_accuracy: 0.9826, prior_entropy: 0.971, recall: 0.9826, relative_absolute_error: 0.1302, root_mean_prior_squared_error: 0.4897, root_mean_squared_error: 0.1351, root_relative_squared_error: 0.2759, scimark_benchmark: 934.3687, usercpu_time_millis: 270, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 260,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9968, f_measure: 0.9729, kappa: 0.9434, kb_relative_information_score: 1647.083, mean_absolute_error: 0.0373, mean_prior_absolute_error: 0.4798, number_of_instances: 1780, precision: 0.9733, predictive_accuracy: 0.973, prior_entropy: 0.971, recall: 0.973, relative_absolute_error: 0.0778, root_mean_prior_squared_error: 0.4897, root_mean_squared_error: 0.1474, root_relative_squared_error: 0.301, scimark_benchmark: 905.2959,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9982, f_measure: 0.9752, kappa: 0.9481, kb_relative_information_score: 1501.4059, mean_absolute_error: 0.0868, mean_prior_absolute_error: 0.4798, number_of_instances: 1780, precision: 0.9757, predictive_accuracy: 0.9753, prior_entropy: 0.971, recall: 0.9753, relative_absolute_error: 0.1809, root_mean_prior_squared_error: 0.4897, root_mean_squared_error: 0.1607, root_relative_squared_error: 0.3282, scimark_benchmark: 905.2959,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5437, f_measure: 0.5255, kappa: 0.1032, kb_relative_information_score: 404.7158, mean_absolute_error: 0.364, mean_prior_absolute_error: 0.4798, number_of_instances: 1780, precision: 0.7733, predictive_accuracy: 0.636, prior_entropy: 0.971, recall: 0.636, relative_absolute_error: 0.7588, root_mean_prior_squared_error: 0.4897, root_mean_squared_error: 0.6034, root_relative_squared_error: 1.2322, scimark_benchmark: 906.0979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5437, f_measure: 0.5255, kappa: 0.1032, kb_relative_information_score: 404.7158, mean_absolute_error: 0.364, mean_prior_absolute_error: 0.4798, number_of_instances: 1780, precision: 0.7733, predictive_accuracy: 0.636, prior_entropy: 0.971, recall: 0.636, relative_absolute_error: 0.7588, root_mean_prior_squared_error: 0.4897, root_mean_squared_error: 0.6034, root_relative_squared_error: 1.2322, scimark_benchmark: 932.438, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9991, f_measure: 0.9819, kappa: 0.9622, kb_relative_information_score: 1679.8571, mean_absolute_error: 0.0286, mean_prior_absolute_error: 0.4798, number_of_instances: 1780, precision: 0.9825, predictive_accuracy: 0.982, prior_entropy: 0.971, recall: 0.982, relative_absolute_error: 0.0597, root_mean_prior_squared_error: 0.4897, root_mean_squared_error: 0.1204, root_relative_squared_error: 0.246, scimark_benchmark: 974.2014,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9982, f_measure: 0.9752, kappa: 0.9481, kb_relative_information_score: 1501.4059, mean_absolute_error: 0.0868, mean_prior_absolute_error: 0.4798, number_of_instances: 1780, precision: 0.9757, predictive_accuracy: 0.9753, prior_entropy: 0.971, recall: 0.9753, relative_absolute_error: 0.1809, root_mean_prior_squared_error: 0.4897, root_mean_squared_error: 0.1607, root_relative_squared_error: 0.3282, scimark_benchmark: 947.1781, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9216, f_measure: 0.9177, kappa: 0.8279, kb_relative_information_score: 1443.1614, mean_absolute_error: 0.0919, mean_prior_absolute_error: 0.4798, number_of_instances: 1780, precision: 0.9178, predictive_accuracy: 0.918, prior_entropy: 0.971, recall: 0.918, relative_absolute_error: 0.1914, root_mean_prior_squared_error: 0.4897, root_mean_squared_error: 0.2758, root_relative_squared_error: 0.5632, scimark_benchmark: 942.2392,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9874, f_measure: 0.9616, kappa: 0.9197, kb_relative_information_score: 1553.3609, mean_absolute_error: 0.0665, mean_prior_absolute_error: 0.4798, number_of_instances: 1780, precision: 0.9621, predictive_accuracy: 0.9618, prior_entropy: 0.971, recall: 0.9618, relative_absolute_error: 0.1385, root_mean_prior_squared_error: 0.4897, root_mean_squared_error: 0.1787, root_relative_squared_error: 0.365, scimark_benchmark: 908.9569, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9843, f_measure: 0.9367, kappa: 0.8673, kb_relative_information_score: 1509.9994, mean_absolute_error: 0.0736, mean_prior_absolute_error: 0.4798, number_of_instances: 1780, precision: 0.9377, predictive_accuracy: 0.9371, prior_entropy: 0.971, recall: 0.9371, relative_absolute_error: 0.1534, root_mean_prior_squared_error: 0.4897, root_mean_squared_error: 0.2211, root_relative_squared_error: 0.4516, scimark_benchmark: 938.1282, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5437, f_measure: 0.5255, kappa: 0.1032, kb_relative_information_score: 404.7158, mean_absolute_error: 0.364, mean_prior_absolute_error: 0.4798, number_of_instances: 1780, precision: 0.7733, predictive_accuracy: 0.636, prior_entropy: 0.971, recall: 0.636, relative_absolute_error: 0.7588, root_mean_prior_squared_error: 0.4897, root_mean_squared_error: 0.6034, root_relative_squared_error: 1.2322, scimark_benchmark: 937.5683, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5437, f_measure: 0.5255, kappa: 0.1032, kb_relative_information_score: 404.7158, mean_absolute_error: 0.364, mean_prior_absolute_error: 0.4798, number_of_instances: 1780, precision: 0.7733, predictive_accuracy: 0.636, prior_entropy: 0.971, recall: 0.636, relative_absolute_error: 0.7588, root_mean_prior_squared_error: 0.4897, root_mean_squared_error: 0.6034, root_relative_squared_error: 1.2322, scimark_benchmark: 859.5223, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9991, f_measure: 0.9803, kappa: 0.9587, kb_relative_information_score: 1680.68, mean_absolute_error: 0.0278, mean_prior_absolute_error: 0.4798, number_of_instances: 1780, precision: 0.9809, predictive_accuracy: 0.9803, prior_entropy: 0.971, recall: 0.9803, relative_absolute_error: 0.0579, root_mean_prior_squared_error: 0.4897, root_mean_squared_error: 0.1209, root_relative_squared_error: 0.2469, scimark_benchmark: 938.1282,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9991, f_measure: 0.9819, kappa: 0.9622, kb_relative_information_score: 1679.8571, mean_absolute_error: 0.0286, mean_prior_absolute_error: 0.4798, number_of_instances: 1780, precision: 0.9825, predictive_accuracy: 0.982, prior_entropy: 0.971, recall: 0.982, relative_absolute_error: 0.0597, root_mean_prior_squared_error: 0.4897, root_mean_squared_error: 0.1204, root_relative_squared_error: 0.246, scimark_benchmark: 903.2737,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9991, f_measure: 0.9819, kappa: 0.9622, kb_relative_information_score: 1679.8571, mean_absolute_error: 0.0286, mean_prior_absolute_error: 0.4798, number_of_instances: 1780, precision: 0.9825, predictive_accuracy: 0.982, prior_entropy: 0.971, recall: 0.982, relative_absolute_error: 0.0597, root_mean_prior_squared_error: 0.4897, root_mean_squared_error: 0.1204, root_relative_squared_error: 0.246, scimark_benchmark: 938.1282,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9723, f_measure: 0.9224, kappa: 0.8373, kb_relative_information_score: 1358.26, mean_absolute_error: 0.1223, mean_prior_absolute_error: 0.4798, number_of_instances: 1780, precision: 0.9238, predictive_accuracy: 0.923, prior_entropy: 0.971, recall: 0.923, relative_absolute_error: 0.2549, root_mean_prior_squared_error: 0.4897, root_mean_squared_error: 0.2346, root_relative_squared_error: 0.4791, scimark_benchmark: 930.404, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9984, f_measure: 0.9826, kappa: 0.9636, kb_relative_information_score: 1580.5105, mean_absolute_error: 0.0625, mean_prior_absolute_error: 0.4798, number_of_instances: 1780, precision: 0.9826, predictive_accuracy: 0.9826, prior_entropy: 0.971, recall: 0.9826, relative_absolute_error: 0.1302, root_mean_prior_squared_error: 0.4897, root_mean_squared_error: 0.1351, root_relative_squared_error: 0.2759, scimark_benchmark: 931.9419, usercpu_time_millis: 120, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 110,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9991, f_measure: 0.9819, kappa: 0.9622, kb_relative_information_score: 1679.8571, mean_absolute_error: 0.0286, mean_prior_absolute_error: 0.4798, number_of_instances: 1780, precision: 0.9825, predictive_accuracy: 0.982, prior_entropy: 0.971, recall: 0.982, relative_absolute_error: 0.0597, root_mean_prior_squared_error: 0.4897, root_mean_squared_error: 0.1204, root_relative_squared_error: 0.246, scimark_benchmark: 944.0133, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9968, f_measure: 0.9729, kappa: 0.9434, kb_relative_information_score: 1647.083, mean_absolute_error: 0.0373, mean_prior_absolute_error: 0.4798, number_of_instances: 1780, precision: 0.9733, predictive_accuracy: 0.973, prior_entropy: 0.971, recall: 0.973, relative_absolute_error: 0.0778, root_mean_prior_squared_error: 0.4897, root_mean_squared_error: 0.1474, root_relative_squared_error: 0.301, scimark_benchmark: 936.3213, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9982, f_measure: 0.9752, kappa: 0.9481, kb_relative_information_score: 1501.4059, mean_absolute_error: 0.0868, mean_prior_absolute_error: 0.4798, number_of_instances: 1780, precision: 0.9757, predictive_accuracy: 0.9753, prior_entropy: 0.971, recall: 0.9753, relative_absolute_error: 0.1809, root_mean_prior_squared_error: 0.4897, root_mean_squared_error: 0.1607, root_relative_squared_error: 0.3282, scimark_benchmark: 936.3213, usercpu_time_millis: 40, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9982, f_measure: 0.9769, kappa: 0.9515, kb_relative_information_score: 1494.1385, mean_absolute_error: 0.0902, mean_prior_absolute_error: 0.4798, number_of_instances: 1780, precision: 0.9776, predictive_accuracy: 0.977, prior_entropy: 0.971, recall: 0.977, relative_absolute_error: 0.1881, root_mean_prior_squared_error: 0.4897, root_mean_squared_error: 0.159, root_relative_squared_error: 0.3246, scimark_benchmark: 917.5013, usercpu_time_millis: 1280, usercpu_time_millis_testing: 610, usercpu_time_millis_training: 670,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9979, f_measure: 0.9774, kappa: 0.9528, kb_relative_information_score: 1496.9667, mean_absolute_error: 0.0894, mean_prior_absolute_error: 0.4798, number_of_instances: 1780, precision: 0.978, predictive_accuracy: 0.9775, prior_entropy: 0.971, recall: 0.9775, relative_absolute_error: 0.1863, root_mean_prior_squared_error: 0.4897, root_mean_squared_error: 0.1586, root_relative_squared_error: 0.3238, scimark_benchmark: 859.5223, usercpu_time_millis: 510, usercpu_time_millis_testing: 170, usercpu_time_millis_training: 340,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9977, f_measure: 0.9757, kappa: 0.9492, kb_relative_information_score: 1493.2357, mean_absolute_error: 0.0899, mean_prior_absolute_error: 0.4798, number_of_instances: 1780, precision: 0.9763, predictive_accuracy: 0.9758, prior_entropy: 0.971, recall: 0.9758, relative_absolute_error: 0.1874, root_mean_prior_squared_error: 0.4897, root_mean_squared_error: 0.1611, root_relative_squared_error: 0.329, scimark_benchmark: 917.5013, usercpu_time_millis: 220, usercpu_time_millis_testing: 50, usercpu_time_millis_training: 170,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9974, f_measure: 0.9775, kappa: 0.9529, kb_relative_information_score: 1495.2069, mean_absolute_error: 0.0892, mean_prior_absolute_error: 0.4798, number_of_instances: 1780, precision: 0.9777, predictive_accuracy: 0.9775, prior_entropy: 0.971, recall: 0.9775, relative_absolute_error: 0.1859, root_mean_prior_squared_error: 0.4897, root_mean_squared_error: 0.1618, root_relative_squared_error: 0.3305, scimark_benchmark: 891.6381, usercpu_time_millis: 110, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 80,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9939, f_measure: 0.9707, kappa: 0.9388, kb_relative_information_score: 1480.3536, mean_absolute_error: 0.0924, mean_prior_absolute_error: 0.4798, number_of_instances: 1780, precision: 0.9709, predictive_accuracy: 0.9708, prior_entropy: 0.971, recall: 0.9708, relative_absolute_error: 0.1926, root_mean_prior_squared_error: 0.4897, root_mean_squared_error: 0.1746, root_relative_squared_error: 0.3566, scimark_benchmark: 933.9243, usercpu_time_millis: 70, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9897, f_measure: 0.9718, kappa: 0.941, kb_relative_information_score: 1672.5768, mean_absolute_error: 0.0282, mean_prior_absolute_error: 0.4798, number_of_instances: 1780, precision: 0.9723, predictive_accuracy: 0.9719, prior_entropy: 0.971, recall: 0.9719, relative_absolute_error: 0.0588, root_mean_prior_squared_error: 0.4897, root_mean_squared_error: 0.1621, root_relative_squared_error: 0.331, scimark_benchmark: 941.9549, usercpu_time_millis: 110, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 100,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9923, f_measure: 0.9735, kappa: 0.9445, kb_relative_information_score: 1675.8173, mean_absolute_error: 0.0274, mean_prior_absolute_error: 0.4798, number_of_instances: 1780, precision: 0.974, predictive_accuracy: 0.9736, prior_entropy: 0.971, recall: 0.9736, relative_absolute_error: 0.0572, root_mean_prior_squared_error: 0.4897, root_mean_squared_error: 0.1586, root_relative_squared_error: 0.3239, scimark_benchmark: 941.9549, usercpu_time_millis: 50, usercpu_time_millis_training: 50,
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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