Task
Supervised Classification on chscase_vine2

Supervised Classification on chscase_vine2

Task 4384 Supervised Classification chscase_vine2 230 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8035, f_measure: 0.791, kappa: 0.5772, kb_relative_information_score: 1911.4013, mean_absolute_error: 0.3091, mean_prior_absolute_error: 0.4956, number_of_instances: 4680, precision: 0.7936, predictive_accuracy: 0.7925, prior_entropy: 0.9937, recall: 0.7925, relative_absolute_error: 0.6238, root_mean_prior_squared_error: 0.4978, root_mean_squared_error: 0.3989, root_relative_squared_error: 0.8013, scimark_benchmark: 906.0979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.885, f_measure: 0.7921, kappa: 0.5831, kb_relative_information_score: 1887.9671, mean_absolute_error: 0.3107, mean_prior_absolute_error: 0.4956, number_of_instances: 4680, precision: 0.7957, predictive_accuracy: 0.7917, prior_entropy: 0.9937, recall: 0.7917, relative_absolute_error: 0.6269, root_mean_prior_squared_error: 0.4978, root_mean_squared_error: 0.374, root_relative_squared_error: 0.7514, scimark_benchmark: 972.587, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8872, f_measure: 0.8146, kappa: 0.6263, kb_relative_information_score: 2239.0363, mean_absolute_error: 0.2727, mean_prior_absolute_error: 0.4956, number_of_instances: 4680, precision: 0.8149, predictive_accuracy: 0.8145, prior_entropy: 0.9937, recall: 0.8145, relative_absolute_error: 0.5501, root_mean_prior_squared_error: 0.4978, root_mean_squared_error: 0.3666, root_relative_squared_error: 0.7365, scimark_benchmark: 934.3687, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7677, f_measure: 0.773, kappa: 0.5409, kb_relative_information_score: 2544.8426, mean_absolute_error: 0.2252, mean_prior_absolute_error: 0.4956, number_of_instances: 4680, precision: 0.7757, predictive_accuracy: 0.7748, prior_entropy: 0.9937, recall: 0.7748, relative_absolute_error: 0.4544, root_mean_prior_squared_error: 0.4978, root_mean_squared_error: 0.4746, root_relative_squared_error: 0.9534, scimark_benchmark: 942.2392,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7677, f_measure: 0.773, kappa: 0.5409, kb_relative_information_score: 2544.8426, mean_absolute_error: 0.2252, mean_prior_absolute_error: 0.4956, number_of_instances: 4680, precision: 0.7757, predictive_accuracy: 0.7748, prior_entropy: 0.9937, recall: 0.7748, relative_absolute_error: 0.4544, root_mean_prior_squared_error: 0.4978, root_mean_squared_error: 0.4746, root_relative_squared_error: 0.9534, scimark_benchmark: 904.0772, usercpu_time_millis: 60, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8235, f_measure: 0.7913, kappa: 0.578, kb_relative_information_score: 1963.2721, mean_absolute_error: 0.3012, mean_prior_absolute_error: 0.4956, number_of_instances: 4680, precision: 0.7942, predictive_accuracy: 0.7929, prior_entropy: 0.9937, recall: 0.7929, relative_absolute_error: 0.6077, root_mean_prior_squared_error: 0.4978, root_mean_squared_error: 0.392, root_relative_squared_error: 0.7875, scimark_benchmark: 941.6675,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8235, f_measure: 0.7913, kappa: 0.578, kb_relative_information_score: 1963.2721, mean_absolute_error: 0.3012, mean_prior_absolute_error: 0.4956, number_of_instances: 4680, precision: 0.7942, predictive_accuracy: 0.7929, prior_entropy: 0.9937, recall: 0.7929, relative_absolute_error: 0.6077, root_mean_prior_squared_error: 0.4978, root_mean_squared_error: 0.392, root_relative_squared_error: 0.7875, scimark_benchmark: 941.6675,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9286, f_measure: 0.8479, kappa: 0.6941, kb_relative_information_score: 2802.2954, mean_absolute_error: 0.2107, mean_prior_absolute_error: 0.4956, number_of_instances: 4680, precision: 0.8493, predictive_accuracy: 0.8477, prior_entropy: 0.9937, recall: 0.8477, relative_absolute_error: 0.4251, root_mean_prior_squared_error: 0.4978, root_mean_squared_error: 0.3253, root_relative_squared_error: 0.6535, scimark_benchmark: 941.6675, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8025, f_measure: 0.764, kappa: 0.5244, kb_relative_information_score: 828.7831, mean_absolute_error: 0.4257, mean_prior_absolute_error: 0.4956, number_of_instances: 4680, precision: 0.7771, predictive_accuracy: 0.769, prior_entropy: 0.9937, recall: 0.769, relative_absolute_error: 0.859, root_mean_prior_squared_error: 0.4978, root_mean_squared_error: 0.441, root_relative_squared_error: 0.8859, scimark_benchmark: 938.191, usercpu_time_millis: 560, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 540,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8313, f_measure: 0.7935, kappa: 0.5823, kb_relative_information_score: 1863.3068, mean_absolute_error: 0.3144, mean_prior_absolute_error: 0.4956, number_of_instances: 4680, precision: 0.7957, predictive_accuracy: 0.7949, prior_entropy: 0.9937, recall: 0.7949, relative_absolute_error: 0.6343, root_mean_prior_squared_error: 0.4978, root_mean_squared_error: 0.3907, root_relative_squared_error: 0.7849, scimark_benchmark: 905.2959,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7677, f_measure: 0.773, kappa: 0.5409, kb_relative_information_score: 2544.8426, mean_absolute_error: 0.2252, mean_prior_absolute_error: 0.4956, number_of_instances: 4680, precision: 0.7757, predictive_accuracy: 0.7748, prior_entropy: 0.9937, recall: 0.7748, relative_absolute_error: 0.4544, root_mean_prior_squared_error: 0.4978, root_mean_squared_error: 0.4746, root_relative_squared_error: 0.9534, scimark_benchmark: 941.3847, usercpu_time_millis: 60, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7677, f_measure: 0.773, kappa: 0.5409, kb_relative_information_score: 2544.8426, mean_absolute_error: 0.2252, mean_prior_absolute_error: 0.4956, number_of_instances: 4680, precision: 0.7757, predictive_accuracy: 0.7748, prior_entropy: 0.9937, recall: 0.7748, relative_absolute_error: 0.4544, root_mean_prior_squared_error: 0.4978, root_mean_squared_error: 0.4746, root_relative_squared_error: 0.9534, scimark_benchmark: 936.3373, usercpu_time_millis: 60, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8278, f_measure: 0.7901, kappa: 0.5755, kb_relative_information_score: 1852.1509, mean_absolute_error: 0.315, mean_prior_absolute_error: 0.4956, number_of_instances: 4680, precision: 0.7928, predictive_accuracy: 0.7917, prior_entropy: 0.9937, recall: 0.7917, relative_absolute_error: 0.6355, root_mean_prior_squared_error: 0.4978, root_mean_squared_error: 0.3926, root_relative_squared_error: 0.7887, scimark_benchmark: 932.438,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8235, f_measure: 0.7913, kappa: 0.578, kb_relative_information_score: 1963.2721, mean_absolute_error: 0.3012, mean_prior_absolute_error: 0.4956, number_of_instances: 4680, precision: 0.7942, predictive_accuracy: 0.7929, prior_entropy: 0.9937, recall: 0.7929, relative_absolute_error: 0.6077, root_mean_prior_squared_error: 0.4978, root_mean_squared_error: 0.392, root_relative_squared_error: 0.7875, scimark_benchmark: 974.2014,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8235, f_measure: 0.7913, kappa: 0.578, kb_relative_information_score: 1963.2721, mean_absolute_error: 0.3012, mean_prior_absolute_error: 0.4956, number_of_instances: 4680, precision: 0.7942, predictive_accuracy: 0.7929, prior_entropy: 0.9937, recall: 0.7929, relative_absolute_error: 0.6077, root_mean_prior_squared_error: 0.4978, root_mean_squared_error: 0.392, root_relative_squared_error: 0.7875, scimark_benchmark: 974.2014,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8235, f_measure: 0.7913, kappa: 0.578, kb_relative_information_score: 1963.2721, mean_absolute_error: 0.3012, mean_prior_absolute_error: 0.4956, number_of_instances: 4680, precision: 0.7942, predictive_accuracy: 0.7929, prior_entropy: 0.9937, recall: 0.7929, relative_absolute_error: 0.6077, root_mean_prior_squared_error: 0.4978, root_mean_squared_error: 0.392, root_relative_squared_error: 0.7875, scimark_benchmark: 974.2014, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9448, f_measure: 0.8626, kappa: 0.7227, kb_relative_information_score: 3226.0991, mean_absolute_error: 0.1572, mean_prior_absolute_error: 0.4956, number_of_instances: 4680, precision: 0.8626, predictive_accuracy: 0.8626, prior_entropy: 0.9937, recall: 0.8626, relative_absolute_error: 0.3172, root_mean_prior_squared_error: 0.4978, root_mean_squared_error: 0.3166, root_relative_squared_error: 0.636, scimark_benchmark: 943.1009, usercpu_time_millis: 80, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8035, f_measure: 0.791, kappa: 0.5772, kb_relative_information_score: 1911.4013, mean_absolute_error: 0.3091, mean_prior_absolute_error: 0.4956, number_of_instances: 4680, precision: 0.7936, predictive_accuracy: 0.7925, prior_entropy: 0.9937, recall: 0.7925, relative_absolute_error: 0.6238, root_mean_prior_squared_error: 0.4978, root_mean_squared_error: 0.3989, root_relative_squared_error: 0.8013, scimark_benchmark: 942.2392,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.885, f_measure: 0.7921, kappa: 0.5831, kb_relative_information_score: 1887.9671, mean_absolute_error: 0.3107, mean_prior_absolute_error: 0.4956, number_of_instances: 4680, precision: 0.7957, predictive_accuracy: 0.7917, prior_entropy: 0.9937, recall: 0.7917, relative_absolute_error: 0.6269, root_mean_prior_squared_error: 0.4978, root_mean_squared_error: 0.374, root_relative_squared_error: 0.7514, scimark_benchmark: 908.9569,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8872, f_measure: 0.8146, kappa: 0.6263, kb_relative_information_score: 2239.0363, mean_absolute_error: 0.2727, mean_prior_absolute_error: 0.4956, number_of_instances: 4680, precision: 0.8149, predictive_accuracy: 0.8145, prior_entropy: 0.9937, recall: 0.8145, relative_absolute_error: 0.5501, root_mean_prior_squared_error: 0.4978, root_mean_squared_error: 0.3666, root_relative_squared_error: 0.7365, scimark_benchmark: 940.1541, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7677, f_measure: 0.773, kappa: 0.5409, kb_relative_information_score: 2544.8426, mean_absolute_error: 0.2252, mean_prior_absolute_error: 0.4956, number_of_instances: 4680, precision: 0.7757, predictive_accuracy: 0.7748, prior_entropy: 0.9937, recall: 0.7748, relative_absolute_error: 0.4544, root_mean_prior_squared_error: 0.4978, root_mean_squared_error: 0.4746, root_relative_squared_error: 0.9534, scimark_benchmark: 927.2882, usercpu_time_millis: 50, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7677, f_measure: 0.773, kappa: 0.5409, kb_relative_information_score: 2544.8426, mean_absolute_error: 0.2252, mean_prior_absolute_error: 0.4956, number_of_instances: 4680, precision: 0.7757, predictive_accuracy: 0.7748, prior_entropy: 0.9937, recall: 0.7748, relative_absolute_error: 0.4544, root_mean_prior_squared_error: 0.4978, root_mean_squared_error: 0.4746, root_relative_squared_error: 0.9534, scimark_benchmark: 943.6618, usercpu_time_millis: 60, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8235, f_measure: 0.7913, kappa: 0.578, kb_relative_information_score: 1963.2721, mean_absolute_error: 0.3012, mean_prior_absolute_error: 0.4956, number_of_instances: 4680, precision: 0.7942, predictive_accuracy: 0.7929, prior_entropy: 0.9937, recall: 0.7929, relative_absolute_error: 0.6077, root_mean_prior_squared_error: 0.4978, root_mean_squared_error: 0.392, root_relative_squared_error: 0.7875, scimark_benchmark: 930.404,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8235, f_measure: 0.7913, kappa: 0.578, kb_relative_information_score: 1963.2721, mean_absolute_error: 0.3012, mean_prior_absolute_error: 0.4956, number_of_instances: 4680, precision: 0.7942, predictive_accuracy: 0.7929, prior_entropy: 0.9937, recall: 0.7929, relative_absolute_error: 0.6077, root_mean_prior_squared_error: 0.4978, root_mean_squared_error: 0.392, root_relative_squared_error: 0.7875, scimark_benchmark: 930.404,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9286, f_measure: 0.8479, kappa: 0.6941, kb_relative_information_score: 2802.2954, mean_absolute_error: 0.2107, mean_prior_absolute_error: 0.4956, number_of_instances: 4680, precision: 0.8493, predictive_accuracy: 0.8477, prior_entropy: 0.9937, recall: 0.8477, relative_absolute_error: 0.4251, root_mean_prior_squared_error: 0.4978, root_mean_squared_error: 0.3253, root_relative_squared_error: 0.6535, scimark_benchmark: 930.404,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8025, f_measure: 0.764, kappa: 0.5244, kb_relative_information_score: 828.7831, mean_absolute_error: 0.4257, mean_prior_absolute_error: 0.4956, number_of_instances: 4680, precision: 0.7771, predictive_accuracy: 0.769, prior_entropy: 0.9937, recall: 0.769, relative_absolute_error: 0.859, root_mean_prior_squared_error: 0.4978, root_mean_squared_error: 0.441, root_relative_squared_error: 0.8859, scimark_benchmark: 936.2574, usercpu_time_millis: 640, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 610,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8235, f_measure: 0.7913, kappa: 0.578, kb_relative_information_score: 1963.2721, mean_absolute_error: 0.3012, mean_prior_absolute_error: 0.4956, number_of_instances: 4680, precision: 0.7942, predictive_accuracy: 0.7929, prior_entropy: 0.9937, recall: 0.7929, relative_absolute_error: 0.6077, root_mean_prior_squared_error: 0.4978, root_mean_squared_error: 0.392, root_relative_squared_error: 0.7875, scimark_benchmark: 932.438,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8313, f_measure: 0.7935, kappa: 0.5823, kb_relative_information_score: 1863.3068, mean_absolute_error: 0.3144, mean_prior_absolute_error: 0.4956, number_of_instances: 4680, precision: 0.7957, predictive_accuracy: 0.7949, prior_entropy: 0.9937, recall: 0.7949, relative_absolute_error: 0.6343, root_mean_prior_squared_error: 0.4978, root_mean_squared_error: 0.3907, root_relative_squared_error: 0.7849, scimark_benchmark: 936.9595, usercpu_time_millis: 60, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9448, f_measure: 0.8626, kappa: 0.7227, kb_relative_information_score: 3226.0991, mean_absolute_error: 0.1572, mean_prior_absolute_error: 0.4956, number_of_instances: 4680, precision: 0.8626, predictive_accuracy: 0.8626, prior_entropy: 0.9937, recall: 0.8626, relative_absolute_error: 0.3172, root_mean_prior_squared_error: 0.4978, root_mean_squared_error: 0.3166, root_relative_squared_error: 0.636, scimark_benchmark: 901.4991, usercpu_time_millis: 80, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7707, f_measure: 0.6591, kappa: 0.3335, kb_relative_information_score: 620.0419, mean_absolute_error: 0.4428, mean_prior_absolute_error: 0.4956, number_of_instances: 4680, precision: 0.7153, predictive_accuracy: 0.6835, prior_entropy: 0.9937, recall: 0.6835, relative_absolute_error: 0.8934, root_mean_prior_squared_error: 0.4978, root_mean_squared_error: 0.4571, root_relative_squared_error: 0.9182, scimark_benchmark: 936.2574, usercpu_time_millis: 380, usercpu_time_millis_testing: 120, usercpu_time_millis_training: 260,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7674, f_measure: 0.6541, kappa: 0.3267, kb_relative_information_score: 571.7586, mean_absolute_error: 0.4473, mean_prior_absolute_error: 0.4956, number_of_instances: 4680, precision: 0.7171, predictive_accuracy: 0.681, prior_entropy: 0.9937, recall: 0.681, relative_absolute_error: 0.9026, root_mean_prior_squared_error: 0.4978, root_mean_squared_error: 0.4599, root_relative_squared_error: 0.9238, scimark_benchmark: 943.6618, usercpu_time_millis: 220, usercpu_time_millis_testing: 80, usercpu_time_millis_training: 140,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7634, f_measure: 0.6638, kappa: 0.3408, kb_relative_information_score: 630.616, mean_absolute_error: 0.4415, mean_prior_absolute_error: 0.4956, number_of_instances: 4680, precision: 0.7159, predictive_accuracy: 0.6865, prior_entropy: 0.9937, recall: 0.6865, relative_absolute_error: 0.8909, root_mean_prior_squared_error: 0.4978, root_mean_squared_error: 0.457, root_relative_squared_error: 0.918, scimark_benchmark: 933.9243, usercpu_time_millis: 100, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 70,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.759, f_measure: 0.66, kappa: 0.3347, kb_relative_information_score: 639.4178, mean_absolute_error: 0.4405, mean_prior_absolute_error: 0.4956, number_of_instances: 4680, precision: 0.7151, predictive_accuracy: 0.684, prior_entropy: 0.9937, recall: 0.684, relative_absolute_error: 0.8888, root_mean_prior_squared_error: 0.4978, root_mean_squared_error: 0.4569, root_relative_squared_error: 0.9179, scimark_benchmark: 901.5805, usercpu_time_millis: 50, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7461, f_measure: 0.6506, kappa: 0.3205, kb_relative_information_score: 631.7309, mean_absolute_error: 0.4405, mean_prior_absolute_error: 0.4956, number_of_instances: 4680, precision: 0.7144, predictive_accuracy: 0.6782, prior_entropy: 0.9937, recall: 0.6782, relative_absolute_error: 0.8889, root_mean_prior_squared_error: 0.4978, root_mean_squared_error: 0.4587, root_relative_squared_error: 0.9215, scimark_benchmark: 941.8684, usercpu_time_millis: 40, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8719, f_measure: 0.8, kappa: 0.5955, kb_relative_information_score: 2141.3707, mean_absolute_error: 0.2819, mean_prior_absolute_error: 0.4956, number_of_instances: 4680, precision: 0.8029, predictive_accuracy: 0.8015, prior_entropy: 0.9937, recall: 0.8015, relative_absolute_error: 0.5687, root_mean_prior_squared_error: 0.4978, root_mean_squared_error: 0.3791, root_relative_squared_error: 0.7617, scimark_benchmark: 936.1714, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8719, f_measure: 0.8, kappa: 0.5955, kb_relative_information_score: 2141.3707, mean_absolute_error: 0.2819, mean_prior_absolute_error: 0.4956, number_of_instances: 4680, precision: 0.8029, predictive_accuracy: 0.8015, prior_entropy: 0.9937, recall: 0.8015, relative_absolute_error: 0.5687, root_mean_prior_squared_error: 0.4978, root_mean_squared_error: 0.3791, root_relative_squared_error: 0.7617, scimark_benchmark: 889.4922, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8719, f_measure: 0.8, kappa: 0.5955, kb_relative_information_score: 2141.3707, mean_absolute_error: 0.2819, mean_prior_absolute_error: 0.4956, number_of_instances: 4680, precision: 0.8029, predictive_accuracy: 0.8015, prior_entropy: 0.9937, recall: 0.8015, relative_absolute_error: 0.5687, root_mean_prior_squared_error: 0.4978, root_mean_squared_error: 0.3791, root_relative_squared_error: 0.7617, 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

OpenML bootcamp

From your own software

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

OpenML APIs