OpenML
Supervised Classification on solar-flare

Supervised Classification on solar-flare

Task 2068 Supervised Classification solar-flare 1232 runs submitted
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  • at2 study_1 study_41 study_70 under100k under1m
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.2494, f_measure: 0.993, kb_relative_information_score: 45.5083, mean_absolute_error: 0.0062, mean_prior_absolute_error: 0.0075, number_of_instances: 1066, precision: 0.9906, predictive_accuracy: 0.9953, prior_entropy: 0.0626, recall: 0.9953, relative_absolute_error: 0.8354, root_mean_prior_squared_error: 0.0558, root_mean_squared_error: 0.0558, root_relative_squared_error: 1.0004, scimark_benchmark: 936.7184, usercpu_time_millis: 380, usercpu_time_millis_testing: 110, usercpu_time_millis_training: 270,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.2494, f_measure: 0.993, kb_relative_information_score: -3.0655, mean_absolute_error: 0.0062, mean_prior_absolute_error: 0.0075, number_of_instances: 1066, precision: 0.9906, predictive_accuracy: 0.9953, prior_entropy: 0.0626, recall: 0.9953, relative_absolute_error: 0.8378, root_mean_prior_squared_error: 0.0558, root_mean_squared_error: 0.0559, root_relative_squared_error: 1.0006, scimark_benchmark: 930.5033, usercpu_time_millis: 700, usercpu_time_millis_testing: 210, usercpu_time_millis_training: 490,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9694, f_measure: 0.9822, kappa: 0.1832, kb_relative_information_score: -5125.9782, mean_absolute_error: 0.0213, mean_prior_absolute_error: 0.0075, number_of_instances: 1066, precision: 0.9947, predictive_accuracy: 0.9719, prior_entropy: 0.0626, recall: 0.9719, relative_absolute_error: 2.852, root_mean_prior_squared_error: 0.0558, root_mean_squared_error: 0.1311, root_relative_squared_error: 2.3482, scimark_benchmark: 938.1282,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.993, kb_relative_information_score: 160.237, mean_absolute_error: 0.0031, mean_prior_absolute_error: 0.0075, number_of_instances: 1066, precision: 0.9906, predictive_accuracy: 0.9953, prior_entropy: 0.0626, recall: 0.9953, relative_absolute_error: 0.4192, root_mean_prior_squared_error: 0.0558, root_mean_squared_error: 0.0559, root_relative_squared_error: 1.0017, scimark_benchmark: 906.0979, usercpu_time_millis: 80, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.993, kb_relative_information_score: 160.237, mean_absolute_error: 0.0031, mean_prior_absolute_error: 0.0075, number_of_instances: 1066, precision: 0.9906, predictive_accuracy: 0.9953, prior_entropy: 0.0626, recall: 0.9953, relative_absolute_error: 0.4192, root_mean_prior_squared_error: 0.0558, root_mean_squared_error: 0.0559, root_relative_squared_error: 1.0017, scimark_benchmark: 859.5223, usercpu_time_millis: 60, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.2494, f_measure: 0.993, kb_relative_information_score: -1290.7013, mean_absolute_error: 0.0076, mean_prior_absolute_error: 0.0075, number_of_instances: 1066, precision: 0.9906, predictive_accuracy: 0.9953, prior_entropy: 0.0626, recall: 0.9953, relative_absolute_error: 1.0192, root_mean_prior_squared_error: 0.0558, root_mean_squared_error: 0.0559, root_relative_squared_error: 1.0007, scimark_benchmark: 1500.3507, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4807, f_measure: 0.993, kb_relative_information_score: -887.9776, mean_absolute_error: 0.0061, mean_prior_absolute_error: 0.0075, number_of_instances: 1066, precision: 0.9906, predictive_accuracy: 0.9953, prior_entropy: 0.0626, recall: 0.9953, relative_absolute_error: 0.8134, root_mean_prior_squared_error: 0.0558, root_mean_squared_error: 0.0563, root_relative_squared_error: 1.0087, scimark_benchmark: 941.4991, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.932, f_measure: 0.9924, kappa: 0.1966, kb_relative_information_score: -2313.5654, mean_absolute_error: 0.0074, mean_prior_absolute_error: 0.0075, number_of_instances: 1066, precision: 0.9923, predictive_accuracy: 0.9925, prior_entropy: 0.0626, recall: 0.9925, relative_absolute_error: 0.9975, root_mean_prior_squared_error: 0.0558, root_mean_squared_error: 0.0659, root_relative_squared_error: 1.1796, scimark_benchmark: 930.404, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5914, f_measure: 0.9925, kappa: -0.0009, kb_relative_information_score: -133.8877, mean_absolute_error: 0.004, mean_prior_absolute_error: 0.0075, number_of_instances: 1066, precision: 0.9906, predictive_accuracy: 0.9944, prior_entropy: 0.0626, recall: 0.9944, relative_absolute_error: 0.5332, root_mean_prior_squared_error: 0.0558, root_mean_squared_error: 0.0602, root_relative_squared_error: 1.0791, scimark_benchmark: 926.5859, usercpu_time_millis: 180, usercpu_time_millis_training: 180,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.2494, f_measure: 0.993, kb_relative_information_score: -1277.503, mean_absolute_error: 0.0076, mean_prior_absolute_error: 0.0075, number_of_instances: 1066, precision: 0.9906, predictive_accuracy: 0.9953, prior_entropy: 0.0626, recall: 0.9953, relative_absolute_error: 1.0186, root_mean_prior_squared_error: 0.0558, root_mean_squared_error: 0.0559, root_relative_squared_error: 1.0007, scimark_benchmark: 941.9549,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5918, f_measure: 0.993, kb_relative_information_score: 5.6458, mean_absolute_error: 0.0034, mean_prior_absolute_error: 0.0075, number_of_instances: 1066, precision: 0.9906, predictive_accuracy: 0.9953, prior_entropy: 0.0626, recall: 0.9953, relative_absolute_error: 0.4541, root_mean_prior_squared_error: 0.0558, root_mean_squared_error: 0.0566, root_relative_squared_error: 1.0138, scimark_benchmark: 936.1714, usercpu_time_millis: 100, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 90,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5978, f_measure: 0.9925, kappa: -0.0014, kb_relative_information_score: -62.3504, mean_absolute_error: 0.0038, mean_prior_absolute_error: 0.0075, number_of_instances: 1066, precision: 0.9906, predictive_accuracy: 0.9944, prior_entropy: 0.0626, recall: 0.9944, relative_absolute_error: 0.5144, root_mean_prior_squared_error: 0.0558, root_mean_squared_error: 0.0608, root_relative_squared_error: 1.0897, scimark_benchmark: 1348.3531, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4812, f_measure: 0.993, kb_relative_information_score: 160.0301, mean_absolute_error: 0.0031, mean_prior_absolute_error: 0.0075, number_of_instances: 1066, precision: 0.9906, predictive_accuracy: 0.9953, prior_entropy: 0.0626, recall: 0.9953, relative_absolute_error: 0.42, root_mean_prior_squared_error: 0.0558, root_mean_squared_error: 0.0559, root_relative_squared_error: 1.0017, scimark_benchmark: 1329.2636, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4995, f_measure: 0.9925, kappa: -0.0014, kb_relative_information_score: -95759.7371, mean_absolute_error: 0.2237, mean_prior_absolute_error: 0.0075, number_of_instances: 1066, precision: 0.9906, predictive_accuracy: 0.9944, prior_entropy: 0.0626, recall: 0.9944, relative_absolute_error: 29.9879, root_mean_prior_squared_error: 0.0558, root_mean_squared_error: 0.2748, root_relative_squared_error: 4.9232, scimark_benchmark: 1384.9816, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4995, f_measure: 0.9925, kappa: -0.0014, kb_relative_information_score: -95759.7371, mean_absolute_error: 0.2237, mean_prior_absolute_error: 0.0075, number_of_instances: 1066, precision: 0.9906, predictive_accuracy: 0.9944, prior_entropy: 0.0626, recall: 0.9944, relative_absolute_error: 29.9879, root_mean_prior_squared_error: 0.0558, root_mean_squared_error: 0.2748, root_relative_squared_error: 4.9232, scimark_benchmark: 1286.9416, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4995, f_measure: 0.9925, kappa: -0.0014, kb_relative_information_score: -95759.7371, mean_absolute_error: 0.2237, mean_prior_absolute_error: 0.0075, number_of_instances: 1066, precision: 0.9906, predictive_accuracy: 0.9944, prior_entropy: 0.0626, recall: 0.9944, relative_absolute_error: 29.9879, root_mean_prior_squared_error: 0.0558, root_mean_squared_error: 0.2748, root_relative_squared_error: 4.9232, scimark_benchmark: 1382.7948, usercpu_time_millis: 50, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4995, f_measure: 0.9925, kappa: -0.0014, kb_relative_information_score: -95759.7371, mean_absolute_error: 0.2237, mean_prior_absolute_error: 0.0075, number_of_instances: 1066, precision: 0.9906, predictive_accuracy: 0.9944, prior_entropy: 0.0626, recall: 0.9944, relative_absolute_error: 29.9879, root_mean_prior_squared_error: 0.0558, root_mean_squared_error: 0.2748, root_relative_squared_error: 4.9232, scimark_benchmark: 1274.2195, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4995, f_measure: 0.9925, kappa: -0.0014, kb_relative_information_score: -95759.7371, mean_absolute_error: 0.2237, mean_prior_absolute_error: 0.0075, number_of_instances: 1066, precision: 0.9906, predictive_accuracy: 0.9944, prior_entropy: 0.0626, recall: 0.9944, relative_absolute_error: 29.9879, root_mean_prior_squared_error: 0.0558, root_mean_squared_error: 0.2748, root_relative_squared_error: 4.9232, scimark_benchmark: 1257.7807, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4995, f_measure: 0.9925, kappa: -0.0014, kb_relative_information_score: -95759.7371, mean_absolute_error: 0.2237, mean_prior_absolute_error: 0.0075, number_of_instances: 1066, precision: 0.9906, predictive_accuracy: 0.9944, prior_entropy: 0.0626, recall: 0.9944, relative_absolute_error: 29.9879, root_mean_prior_squared_error: 0.0558, root_mean_squared_error: 0.2748, root_relative_squared_error: 4.9232, scimark_benchmark: 1940.7069, usercpu_time_millis: 40, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4995, f_measure: 0.9925, kappa: -0.0014, kb_relative_information_score: -95759.7371, mean_absolute_error: 0.2237, mean_prior_absolute_error: 0.0075, number_of_instances: 1066, precision: 0.9906, predictive_accuracy: 0.9944, prior_entropy: 0.0626, recall: 0.9944, relative_absolute_error: 29.9879, root_mean_prior_squared_error: 0.0558, root_mean_squared_error: 0.2748, root_relative_squared_error: 4.9232, scimark_benchmark: 976.5714, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4995, f_measure: 0.9925, kappa: -0.0014, kb_relative_information_score: -95759.7371, mean_absolute_error: 0.2237, mean_prior_absolute_error: 0.0075, number_of_instances: 1066, precision: 0.9906, predictive_accuracy: 0.9944, prior_entropy: 0.0626, recall: 0.9944, relative_absolute_error: 29.9879, root_mean_prior_squared_error: 0.0558, root_mean_squared_error: 0.2748, root_relative_squared_error: 4.9232, scimark_benchmark: 1061.5523, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4995, f_measure: 0.9925, kappa: -0.0014, kb_relative_information_score: -95759.7371, mean_absolute_error: 0.2237, mean_prior_absolute_error: 0.0075, number_of_instances: 1066, precision: 0.9906, predictive_accuracy: 0.9944, prior_entropy: 0.0626, recall: 0.9944, relative_absolute_error: 29.9879, root_mean_prior_squared_error: 0.0558, root_mean_squared_error: 0.2748, root_relative_squared_error: 4.9232, scimark_benchmark: 1847.5227, usercpu_time_millis: 40, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4995, f_measure: 0.9925, kappa: -0.0014, kb_relative_information_score: -95759.7371, mean_absolute_error: 0.2237, mean_prior_absolute_error: 0.0075, number_of_instances: 1066, precision: 0.9906, predictive_accuracy: 0.9944, prior_entropy: 0.0626, recall: 0.9944, relative_absolute_error: 29.9879, root_mean_prior_squared_error: 0.0558, root_mean_squared_error: 0.2748, root_relative_squared_error: 4.9232, scimark_benchmark: 1142.1378, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4995, f_measure: 0.9925, kappa: -0.0014, kb_relative_information_score: -95759.7371, mean_absolute_error: 0.2237, mean_prior_absolute_error: 0.0075, number_of_instances: 1066, precision: 0.9906, predictive_accuracy: 0.9944, prior_entropy: 0.0626, recall: 0.9944, relative_absolute_error: 29.9879, root_mean_prior_squared_error: 0.0558, root_mean_squared_error: 0.2748, root_relative_squared_error: 4.9232, scimark_benchmark: 1913.0433, usercpu_time_millis: 50, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4995, f_measure: 0.9925, kappa: -0.0014, kb_relative_information_score: -95759.7371, mean_absolute_error: 0.2237, mean_prior_absolute_error: 0.0075, number_of_instances: 1066, precision: 0.9906, predictive_accuracy: 0.9944, prior_entropy: 0.0626, recall: 0.9944, relative_absolute_error: 29.9879, root_mean_prior_squared_error: 0.0558, root_mean_squared_error: 0.2748, root_relative_squared_error: 4.9232, scimark_benchmark: 978.0867, usercpu_time_millis: 40, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4995, f_measure: 0.9925, kappa: -0.0014, kb_relative_information_score: -95759.7371, mean_absolute_error: 0.2237, mean_prior_absolute_error: 0.0075, number_of_instances: 1066, precision: 0.9906, predictive_accuracy: 0.9944, prior_entropy: 0.0626, recall: 0.9944, relative_absolute_error: 29.9879, root_mean_prior_squared_error: 0.0558, root_mean_squared_error: 0.2748, root_relative_squared_error: 4.9232, scimark_benchmark: 1302.5926, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4995, f_measure: 0.9925, kappa: -0.0014, kb_relative_information_score: -95759.7371, mean_absolute_error: 0.2237, mean_prior_absolute_error: 0.0075, number_of_instances: 1066, precision: 0.9906, predictive_accuracy: 0.9944, prior_entropy: 0.0626, recall: 0.9944, relative_absolute_error: 29.9879, root_mean_prior_squared_error: 0.0558, root_mean_squared_error: 0.2748, root_relative_squared_error: 4.9232, scimark_benchmark: 1447.8725, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4995, f_measure: 0.9925, kappa: -0.0014, kb_relative_information_score: -95759.7371, mean_absolute_error: 0.2237, mean_prior_absolute_error: 0.0075, number_of_instances: 1066, precision: 0.9906, predictive_accuracy: 0.9944, prior_entropy: 0.0626, recall: 0.9944, relative_absolute_error: 29.9879, root_mean_prior_squared_error: 0.0558, root_mean_squared_error: 0.2748, root_relative_squared_error: 4.9232, scimark_benchmark: 1060.3168, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4995, f_measure: 0.9925, kappa: -0.0014, kb_relative_information_score: -95759.7371, mean_absolute_error: 0.2237, mean_prior_absolute_error: 0.0075, number_of_instances: 1066, precision: 0.9906, predictive_accuracy: 0.9944, prior_entropy: 0.0626, recall: 0.9944, relative_absolute_error: 29.9879, root_mean_prior_squared_error: 0.0558, root_mean_squared_error: 0.2748, root_relative_squared_error: 4.9232, scimark_benchmark: 1394.0962, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4995, f_measure: 0.9925, kappa: -0.0014, kb_relative_information_score: -95759.7371, mean_absolute_error: 0.2237, mean_prior_absolute_error: 0.0075, number_of_instances: 1066, precision: 0.9906, predictive_accuracy: 0.9944, prior_entropy: 0.0626, recall: 0.9944, relative_absolute_error: 29.9879, root_mean_prior_squared_error: 0.0558, root_mean_squared_error: 0.2748, root_relative_squared_error: 4.9232, scimark_benchmark: 1937.5189, usercpu_time_millis: 30, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4995, f_measure: 0.9925, kappa: -0.0014, kb_relative_information_score: -95759.7371, mean_absolute_error: 0.2237, mean_prior_absolute_error: 0.0075, number_of_instances: 1066, precision: 0.9906, predictive_accuracy: 0.9944, prior_entropy: 0.0626, recall: 0.9944, relative_absolute_error: 29.9879, root_mean_prior_squared_error: 0.0558, root_mean_squared_error: 0.2748, root_relative_squared_error: 4.9232, scimark_benchmark: 1595.1859, usercpu_time_millis: 40, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4995, f_measure: 0.9925, kappa: -0.0014, kb_relative_information_score: -95759.7371, mean_absolute_error: 0.2237, mean_prior_absolute_error: 0.0075, number_of_instances: 1066, precision: 0.9906, predictive_accuracy: 0.9944, prior_entropy: 0.0626, recall: 0.9944, relative_absolute_error: 29.9879, root_mean_prior_squared_error: 0.0558, root_mean_squared_error: 0.2748, root_relative_squared_error: 4.9232, scimark_benchmark: 1959.1466, usercpu_time_millis: 50, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4995, f_measure: 0.9925, kappa: -0.0014, kb_relative_information_score: -95759.7371, mean_absolute_error: 0.2237, mean_prior_absolute_error: 0.0075, number_of_instances: 1066, precision: 0.9906, predictive_accuracy: 0.9944, prior_entropy: 0.0626, recall: 0.9944, relative_absolute_error: 29.9879, root_mean_prior_squared_error: 0.0558, root_mean_squared_error: 0.2748, root_relative_squared_error: 4.9232, scimark_benchmark: 1361.2564, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4995, f_measure: 0.9925, kappa: -0.0014, kb_relative_information_score: -95759.7371, mean_absolute_error: 0.2237, mean_prior_absolute_error: 0.0075, number_of_instances: 1066, precision: 0.9906, predictive_accuracy: 0.9944, prior_entropy: 0.0626, recall: 0.9944, relative_absolute_error: 29.9879, root_mean_prior_squared_error: 0.0558, root_mean_squared_error: 0.2748, root_relative_squared_error: 4.9232, scimark_benchmark: 1887.6273, usercpu_time_millis: 50, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4995, f_measure: 0.9925, kappa: -0.0014, kb_relative_information_score: -95759.7371, mean_absolute_error: 0.2237, mean_prior_absolute_error: 0.0075, number_of_instances: 1066, precision: 0.9906, predictive_accuracy: 0.9944, prior_entropy: 0.0626, recall: 0.9944, relative_absolute_error: 29.9879, root_mean_prior_squared_error: 0.0558, root_mean_squared_error: 0.2748, root_relative_squared_error: 4.9232, scimark_benchmark: 1904.8367, usercpu_time_millis: 40, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 20,
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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

estimation_procedure 10-fold Crossvalidation
evaluation_measures predictive_accuracy
source_data solar-flare (2)
target_feature X-class_flares_production_by_this_region

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