Task
Supervised Classification on solar-flare

Supervised Classification on solar-flare

Task 2932 Supervised Classification solar-flare 252 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3454, f_measure: 0.9676, kb_relative_information_score: 79.5989, mean_absolute_error: 0.0424, mean_prior_absolute_error: 0.0452, number_of_instances: 3230, precision: 0.9571, predictive_accuracy: 0.9783, prior_entropy: 0.1666, recall: 0.9783, relative_absolute_error: 0.9385, root_mean_prior_squared_error: 0.1456, root_mean_squared_error: 0.1458, root_relative_squared_error: 1.0009, scimark_benchmark: 906.0979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5504, f_measure: 0.965, kappa: -0.0085, kb_relative_information_score: -7109.9438, mean_absolute_error: 0.0538, mean_prior_absolute_error: 0.0452, number_of_instances: 3230, precision: 0.957, predictive_accuracy: 0.9731, prior_entropy: 0.1666, recall: 0.9731, relative_absolute_error: 1.1899, root_mean_prior_squared_error: 0.1456, root_mean_squared_error: 0.1641, root_relative_squared_error: 1.1264, scimark_benchmark: 972.587,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6248, f_measure: 0.9609, kappa: -0.0168, kb_relative_information_score: -3630.2818, mean_absolute_error: 0.0463, mean_prior_absolute_error: 0.0452, number_of_instances: 3230, precision: 0.9568, predictive_accuracy: 0.965, prior_entropy: 0.1666, recall: 0.965, relative_absolute_error: 1.024, root_mean_prior_squared_error: 0.1456, root_mean_squared_error: 0.1729, root_relative_squared_error: 1.1869, scimark_benchmark: 851.2074, usercpu_time_millis: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.9676, kb_relative_information_score: 666.8125, mean_absolute_error: 0.0217, mean_prior_absolute_error: 0.0452, number_of_instances: 3230, precision: 0.9571, predictive_accuracy: 0.9783, prior_entropy: 0.1666, recall: 0.9783, relative_absolute_error: 0.4793, root_mean_prior_squared_error: 0.1456, root_mean_squared_error: 0.1472, root_relative_squared_error: 1.0108, scimark_benchmark: 934.695,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8129, f_measure: 0.9507, kappa: 0.2, kb_relative_information_score: -6519.001, mean_absolute_error: 0.07, mean_prior_absolute_error: 0.0452, number_of_instances: 3230, precision: 0.9687, predictive_accuracy: 0.9362, prior_entropy: 0.1666, recall: 0.9362, relative_absolute_error: 1.5482, root_mean_prior_squared_error: 0.1456, root_mean_squared_error: 0.2289, root_relative_squared_error: 1.5718, scimark_benchmark: 941.6675,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7791, f_measure: 0.9643, kappa: 0.0092, kb_relative_information_score: -3363.8427, mean_absolute_error: 0.0406, mean_prior_absolute_error: 0.0452, number_of_instances: 3230, precision: 0.9581, predictive_accuracy: 0.9709, prior_entropy: 0.1666, recall: 0.9709, relative_absolute_error: 0.8986, root_mean_prior_squared_error: 0.1456, root_mean_squared_error: 0.1611, root_relative_squared_error: 1.1059, scimark_benchmark: 941.6675,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5854, f_measure: 0.9676, kb_relative_information_score: -2116.2254, mean_absolute_error: 0.0458, mean_prior_absolute_error: 0.0452, number_of_instances: 3230, precision: 0.9571, predictive_accuracy: 0.9783, prior_entropy: 0.1666, recall: 0.9783, relative_absolute_error: 1.0122, root_mean_prior_squared_error: 0.1456, root_mean_squared_error: 0.1467, root_relative_squared_error: 1.007, scimark_benchmark: 941.6675, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7528, f_measure: 0.9658, kappa: -0.0064, kb_relative_information_score: -2365.0834, mean_absolute_error: 0.0366, mean_prior_absolute_error: 0.0452, number_of_instances: 3230, precision: 0.957, predictive_accuracy: 0.9746, prior_entropy: 0.1666, recall: 0.9746, relative_absolute_error: 0.8092, root_mean_prior_squared_error: 0.1456, root_mean_squared_error: 0.1549, root_relative_squared_error: 1.0637, scimark_benchmark: 943.8235, usercpu_time_millis: 1250, usercpu_time_millis_testing: 60, usercpu_time_millis_training: 1190,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7791, f_measure: 0.9643, kappa: 0.0092, kb_relative_information_score: -3363.8427, mean_absolute_error: 0.0406, mean_prior_absolute_error: 0.0452, number_of_instances: 3230, precision: 0.9581, predictive_accuracy: 0.9709, prior_entropy: 0.1666, recall: 0.9709, relative_absolute_error: 0.8986, root_mean_prior_squared_error: 0.1456, root_mean_squared_error: 0.1611, root_relative_squared_error: 1.1059, scimark_benchmark: 905.2959,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7478, f_measure: 0.9634, kappa: -0.0122, kb_relative_information_score: -3369.573, mean_absolute_error: 0.0395, mean_prior_absolute_error: 0.0452, number_of_instances: 3230, precision: 0.9569, predictive_accuracy: 0.97, prior_entropy: 0.1666, recall: 0.97, relative_absolute_error: 0.8744, root_mean_prior_squared_error: 0.1456, root_mean_squared_error: 0.1607, root_relative_squared_error: 1.1031, scimark_benchmark: 931.771, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.9676, kb_relative_information_score: 666.8125, mean_absolute_error: 0.0217, mean_prior_absolute_error: 0.0452, number_of_instances: 3230, precision: 0.9571, predictive_accuracy: 0.9783, prior_entropy: 0.1666, recall: 0.9783, relative_absolute_error: 0.4793, root_mean_prior_squared_error: 0.1456, root_mean_squared_error: 0.1472, root_relative_squared_error: 1.0108, scimark_benchmark: 974.2014, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8129, f_measure: 0.9507, kappa: 0.2, kb_relative_information_score: -6519.001, mean_absolute_error: 0.07, mean_prior_absolute_error: 0.0452, number_of_instances: 3230, precision: 0.9687, predictive_accuracy: 0.9362, prior_entropy: 0.1666, recall: 0.9362, relative_absolute_error: 1.5482, root_mean_prior_squared_error: 0.1456, root_mean_squared_error: 0.2289, root_relative_squared_error: 1.5718, scimark_benchmark: 974.2014,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7791, f_measure: 0.9643, kappa: 0.0092, kb_relative_information_score: -3363.8427, mean_absolute_error: 0.0406, mean_prior_absolute_error: 0.0452, number_of_instances: 3230, precision: 0.9581, predictive_accuracy: 0.9709, prior_entropy: 0.1666, recall: 0.9709, relative_absolute_error: 0.8986, root_mean_prior_squared_error: 0.1456, root_mean_squared_error: 0.1611, root_relative_squared_error: 1.1059, scimark_benchmark: 974.2014, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6938, f_measure: 0.967, kappa: -0.0023, kb_relative_information_score: -1748.1077, mean_absolute_error: 0.0305, mean_prior_absolute_error: 0.0452, number_of_instances: 3230, precision: 0.9571, predictive_accuracy: 0.9771, prior_entropy: 0.1666, recall: 0.9771, relative_absolute_error: 0.675, root_mean_prior_squared_error: 0.1456, root_mean_squared_error: 0.1524, root_relative_squared_error: 1.0461, scimark_benchmark: 939.8002,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7478, f_measure: 0.9634, kappa: -0.0122, kb_relative_information_score: -3369.573, mean_absolute_error: 0.0395, mean_prior_absolute_error: 0.0452, number_of_instances: 3230, precision: 0.9569, predictive_accuracy: 0.97, prior_entropy: 0.1666, recall: 0.97, relative_absolute_error: 0.8744, root_mean_prior_squared_error: 0.1456, root_mean_squared_error: 0.1607, root_relative_squared_error: 1.1031, scimark_benchmark: 943.1009, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3454, f_measure: 0.9676, kb_relative_information_score: 79.5989, mean_absolute_error: 0.0424, mean_prior_absolute_error: 0.0452, number_of_instances: 3230, precision: 0.9571, predictive_accuracy: 0.9783, prior_entropy: 0.1666, recall: 0.9783, relative_absolute_error: 0.9385, root_mean_prior_squared_error: 0.1456, root_mean_squared_error: 0.1458, root_relative_squared_error: 1.0009, scimark_benchmark: 819.5729,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5504, f_measure: 0.965, kappa: -0.0085, kb_relative_information_score: -7109.9438, mean_absolute_error: 0.0538, mean_prior_absolute_error: 0.0452, number_of_instances: 3230, precision: 0.957, predictive_accuracy: 0.9731, prior_entropy: 0.1666, recall: 0.9731, relative_absolute_error: 1.1899, root_mean_prior_squared_error: 0.1456, root_mean_squared_error: 0.1641, root_relative_squared_error: 1.1264, scimark_benchmark: 935.2002,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6248, f_measure: 0.9609, kappa: -0.0168, kb_relative_information_score: -3630.2818, mean_absolute_error: 0.0463, mean_prior_absolute_error: 0.0452, number_of_instances: 3230, precision: 0.9568, predictive_accuracy: 0.965, prior_entropy: 0.1666, recall: 0.965, relative_absolute_error: 1.024, root_mean_prior_squared_error: 0.1456, root_mean_squared_error: 0.1729, root_relative_squared_error: 1.1869, scimark_benchmark: 608.4057, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.9676, kb_relative_information_score: 666.8125, mean_absolute_error: 0.0217, mean_prior_absolute_error: 0.0452, number_of_instances: 3230, precision: 0.9571, predictive_accuracy: 0.9783, prior_entropy: 0.1666, recall: 0.9783, relative_absolute_error: 0.4793, root_mean_prior_squared_error: 0.1456, root_mean_squared_error: 0.1472, root_relative_squared_error: 1.0108, scimark_benchmark: 936.2574, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7791, f_measure: 0.9643, kappa: 0.0092, kb_relative_information_score: -3363.8427, mean_absolute_error: 0.0406, mean_prior_absolute_error: 0.0452, number_of_instances: 3230, precision: 0.9581, predictive_accuracy: 0.9709, prior_entropy: 0.1666, recall: 0.9709, relative_absolute_error: 0.8986, root_mean_prior_squared_error: 0.1456, root_mean_squared_error: 0.1611, root_relative_squared_error: 1.1059, scimark_benchmark: 930.404,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7791, f_measure: 0.9643, kappa: 0.0092, kb_relative_information_score: -3363.8427, mean_absolute_error: 0.0406, mean_prior_absolute_error: 0.0452, number_of_instances: 3230, precision: 0.9581, predictive_accuracy: 0.9709, prior_entropy: 0.1666, recall: 0.9709, relative_absolute_error: 0.8986, root_mean_prior_squared_error: 0.1456, root_mean_squared_error: 0.1611, root_relative_squared_error: 1.1059, scimark_benchmark: 938.1282, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7791, f_measure: 0.9643, kappa: 0.0092, kb_relative_information_score: -3363.8427, mean_absolute_error: 0.0406, mean_prior_absolute_error: 0.0452, number_of_instances: 3230, precision: 0.9581, predictive_accuracy: 0.9709, prior_entropy: 0.1666, recall: 0.9709, relative_absolute_error: 0.8986, root_mean_prior_squared_error: 0.1456, root_mean_squared_error: 0.1611, root_relative_squared_error: 1.1059, scimark_benchmark: 930.404, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5854, f_measure: 0.9676, kb_relative_information_score: -2116.2254, mean_absolute_error: 0.0458, mean_prior_absolute_error: 0.0452, number_of_instances: 3230, precision: 0.9571, predictive_accuracy: 0.9783, prior_entropy: 0.1666, recall: 0.9783, relative_absolute_error: 1.0122, root_mean_prior_squared_error: 0.1456, root_mean_squared_error: 0.1467, root_relative_squared_error: 1.007, scimark_benchmark: 903.2737, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7528, f_measure: 0.9658, kappa: -0.0064, kb_relative_information_score: -2365.0834, mean_absolute_error: 0.0366, mean_prior_absolute_error: 0.0452, number_of_instances: 3230, precision: 0.957, predictive_accuracy: 0.9746, prior_entropy: 0.1666, recall: 0.9746, relative_absolute_error: 0.8092, root_mean_prior_squared_error: 0.1456, root_mean_squared_error: 0.1549, root_relative_squared_error: 1.0637, scimark_benchmark: 906.0979, usercpu_time_millis: 1130, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 1100,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7791, f_measure: 0.9643, kappa: 0.0092, kb_relative_information_score: -3363.8427, mean_absolute_error: 0.0406, mean_prior_absolute_error: 0.0452, number_of_instances: 3230, precision: 0.9581, predictive_accuracy: 0.9709, prior_entropy: 0.1666, recall: 0.9709, relative_absolute_error: 0.8986, root_mean_prior_squared_error: 0.1456, root_mean_squared_error: 0.1611, root_relative_squared_error: 1.1059, scimark_benchmark: 932.438,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6938, f_measure: 0.967, kappa: -0.0023, kb_relative_information_score: -1748.1077, mean_absolute_error: 0.0305, mean_prior_absolute_error: 0.0452, number_of_instances: 3230, precision: 0.9571, predictive_accuracy: 0.9771, prior_entropy: 0.1666, recall: 0.9771, relative_absolute_error: 0.675, root_mean_prior_squared_error: 0.1456, root_mean_squared_error: 0.1524, root_relative_squared_error: 1.0461, scimark_benchmark: 945.6228, usercpu_time_millis: 200, usercpu_time_millis_training: 200,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7478, f_measure: 0.9634, kappa: -0.0122, kb_relative_information_score: -3369.573, mean_absolute_error: 0.0395, mean_prior_absolute_error: 0.0452, number_of_instances: 3230, precision: 0.9569, predictive_accuracy: 0.97, prior_entropy: 0.1666, recall: 0.97, relative_absolute_error: 0.8744, root_mean_prior_squared_error: 0.1456, root_mean_squared_error: 0.1607, root_relative_squared_error: 1.1031, scimark_benchmark: 901.4991, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3326, f_measure: 0.9676, kb_relative_information_score: -109.7172, mean_absolute_error: 0.0426, mean_prior_absolute_error: 0.0452, number_of_instances: 3230, precision: 0.9571, predictive_accuracy: 0.9783, prior_entropy: 0.1666, recall: 0.9783, relative_absolute_error: 0.942, root_mean_prior_squared_error: 0.1456, root_mean_squared_error: 0.1458, root_relative_squared_error: 1.0013, scimark_benchmark: 1158.055, usercpu_time_millis: 2930, usercpu_time_millis_testing: 1500, usercpu_time_millis_training: 1430,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3451, f_measure: 0.9676, kb_relative_information_score: -100.5269, mean_absolute_error: 0.0426, mean_prior_absolute_error: 0.0452, number_of_instances: 3230, precision: 0.9571, predictive_accuracy: 0.9783, prior_entropy: 0.1666, recall: 0.9783, relative_absolute_error: 0.9414, root_mean_prior_squared_error: 0.1456, root_mean_squared_error: 0.1458, root_relative_squared_error: 1.0011, scimark_benchmark: 936.3213, usercpu_time_millis: 820, usercpu_time_millis_testing: 290, usercpu_time_millis_training: 530,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3425, f_measure: 0.9676, kb_relative_information_score: -121.6502, mean_absolute_error: 0.0426, mean_prior_absolute_error: 0.0452, number_of_instances: 3230, precision: 0.9571, predictive_accuracy: 0.9783, prior_entropy: 0.1666, recall: 0.9783, relative_absolute_error: 0.9427, root_mean_prior_squared_error: 0.1456, root_mean_squared_error: 0.1459, root_relative_squared_error: 1.0015, scimark_benchmark: 939.7883, usercpu_time_millis: 390, usercpu_time_millis_testing: 110, usercpu_time_millis_training: 280,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3417, f_measure: 0.9676, kb_relative_information_score: 22.4593, mean_absolute_error: 0.0425, mean_prior_absolute_error: 0.0452, number_of_instances: 3230, precision: 0.9571, predictive_accuracy: 0.9783, prior_entropy: 0.1666, recall: 0.9783, relative_absolute_error: 0.9394, root_mean_prior_squared_error: 0.1456, root_mean_squared_error: 0.1458, root_relative_squared_error: 1.0011, scimark_benchmark: 939.0589, usercpu_time_millis: 200, usercpu_time_millis_testing: 60, usercpu_time_millis_training: 140,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3452, f_measure: 0.9676, kb_relative_information_score: -13.9579, mean_absolute_error: 0.0426, mean_prior_absolute_error: 0.0452, number_of_instances: 3230, precision: 0.9571, predictive_accuracy: 0.9783, prior_entropy: 0.1666, recall: 0.9783, relative_absolute_error: 0.9413, root_mean_prior_squared_error: 0.1456, root_mean_squared_error: 0.1459, root_relative_squared_error: 1.0015, scimark_benchmark: 935.6052, usercpu_time_millis: 110, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 80,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5596, f_measure: 0.9674, kappa: 0.1597, kb_relative_information_score: -2390.2535, mean_absolute_error: 0.0362, mean_prior_absolute_error: 0.0452, number_of_instances: 3230, precision: 0.9647, predictive_accuracy: 0.9706, prior_entropy: 0.1666, recall: 0.9706, relative_absolute_error: 0.8001, root_mean_prior_squared_error: 0.1456, root_mean_squared_error: 0.1634, root_relative_squared_error: 1.1221, scimark_benchmark: 926.5859,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5589, f_measure: 0.9674, kappa: 0.1597, kb_relative_information_score: -2390.3655, mean_absolute_error: 0.0362, mean_prior_absolute_error: 0.0452, number_of_instances: 3230, precision: 0.9647, predictive_accuracy: 0.9706, prior_entropy: 0.1666, recall: 0.9706, relative_absolute_error: 0.8002, root_mean_prior_squared_error: 0.1456, root_mean_squared_error: 0.1634, root_relative_squared_error: 1.1222, scimark_benchmark: 929.0296, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5543, f_measure: 0.9674, kappa: 0.1597, kb_relative_information_score: -2397.8972, mean_absolute_error: 0.0361, mean_prior_absolute_error: 0.0452, number_of_instances: 3230, precision: 0.9647, predictive_accuracy: 0.9706, prior_entropy: 0.1666, recall: 0.9706, relative_absolute_error: 0.7972, root_mean_prior_squared_error: 0.1456, root_mean_squared_error: 0.1626, root_relative_squared_error: 1.1167, scimark_benchmark: 936.1714,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5538, f_measure: 0.9678, kappa: 0.1632, kb_relative_information_score: -2426.2766, mean_absolute_error: 0.036, mean_prior_absolute_error: 0.0452, number_of_instances: 3230, precision: 0.965, predictive_accuracy: 0.9712, prior_entropy: 0.1666, recall: 0.9712, relative_absolute_error: 0.7955, root_mean_prior_squared_error: 0.1456, root_mean_squared_error: 0.1619, root_relative_squared_error: 1.1115, scimark_benchmark: 929.0296,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.548, f_measure: 0.9686, kappa: 0.1706, kb_relative_information_score: -2825.1074, mean_absolute_error: 0.0371, mean_prior_absolute_error: 0.0452, number_of_instances: 3230, precision: 0.9655, predictive_accuracy: 0.9724, prior_entropy: 0.1666, recall: 0.9724, relative_absolute_error: 0.8204, root_mean_prior_squared_error: 0.1456, root_mean_squared_error: 0.1598, root_relative_squared_error: 1.0975, scimark_benchmark: 894.7131, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
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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