Task
Supervised Classification on fri_c1_250_5

Supervised Classification on fri_c1_250_5

Task 4301 Supervised Classification fri_c1_250_5 217 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8911, f_measure: 0.838, kappa: 0.6751, kb_relative_information_score: 1554.5805, mean_absolute_error: 0.1972, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.8392, predictive_accuracy: 0.8384, prior_entropy: 0.9984, recall: 0.8384, relative_absolute_error: 0.3952, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.348, root_relative_squared_error: 0.6968, scimark_benchmark: 906.0979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9335, f_measure: 0.8707, kappa: 0.7407, kb_relative_information_score: 1517.3063, mean_absolute_error: 0.211, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.8709, predictive_accuracy: 0.8708, prior_entropy: 0.9984, recall: 0.8708, relative_absolute_error: 0.423, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3155, root_relative_squared_error: 0.6317, scimark_benchmark: 972.587,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9342, f_measure: 0.8728, kappa: 0.7449, kb_relative_information_score: 1709.8076, mean_absolute_error: 0.1672, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.8728, predictive_accuracy: 0.8728, prior_entropy: 0.9984, recall: 0.8728, relative_absolute_error: 0.3351, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3097, root_relative_squared_error: 0.6202, scimark_benchmark: 934.3687, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8632, f_measure: 0.8632, kappa: 0.726, kb_relative_information_score: 1813.6914, mean_absolute_error: 0.1368, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.8634, predictive_accuracy: 0.8632, prior_entropy: 0.9984, recall: 0.8632, relative_absolute_error: 0.2742, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3699, root_relative_squared_error: 0.7406, scimark_benchmark: 931.771, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8632, f_measure: 0.8632, kappa: 0.726, kb_relative_information_score: 1813.6914, mean_absolute_error: 0.1368, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.8634, predictive_accuracy: 0.8632, prior_entropy: 0.9984, recall: 0.8632, relative_absolute_error: 0.2742, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3699, root_relative_squared_error: 0.7406, 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: 0.9239, f_measure: 0.8515, kappa: 0.7021, kb_relative_information_score: 1576.0152, mean_absolute_error: 0.1933, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.8517, predictive_accuracy: 0.8516, prior_entropy: 0.9984, recall: 0.8516, relative_absolute_error: 0.3876, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3277, root_relative_squared_error: 0.6562, scimark_benchmark: 941.6675,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9479, f_measure: 0.8735, kappa: 0.7463, kb_relative_information_score: 1646.8284, mean_absolute_error: 0.1827, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.8737, predictive_accuracy: 0.8736, prior_entropy: 0.9984, recall: 0.8736, relative_absolute_error: 0.3663, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.2964, root_relative_squared_error: 0.5936, scimark_benchmark: 941.6675,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8027, f_measure: 0.7289, kappa: 0.4567, kb_relative_information_score: 712.9719, mean_absolute_error: 0.3721, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.729, predictive_accuracy: 0.7288, prior_entropy: 0.9984, recall: 0.7288, relative_absolute_error: 0.7459, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4254, root_relative_squared_error: 0.8518, scimark_benchmark: 901.4991,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9181, f_measure: 0.8719, kappa: 0.743, kb_relative_information_score: 1688.6268, mean_absolute_error: 0.1713, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.8722, predictive_accuracy: 0.872, prior_entropy: 0.9984, recall: 0.872, relative_absolute_error: 0.3434, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3248, root_relative_squared_error: 0.6504, scimark_benchmark: 927.2917, usercpu_time_millis: 60, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8632, f_measure: 0.8632, kappa: 0.726, kb_relative_information_score: 1813.6914, mean_absolute_error: 0.1368, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.8634, predictive_accuracy: 0.8632, prior_entropy: 0.9984, recall: 0.8632, relative_absolute_error: 0.2742, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3699, root_relative_squared_error: 0.7406, scimark_benchmark: 938.5498, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8632, f_measure: 0.8632, kappa: 0.726, kb_relative_information_score: 1813.6914, mean_absolute_error: 0.1368, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.8634, predictive_accuracy: 0.8632, prior_entropy: 0.9984, recall: 0.8632, relative_absolute_error: 0.2742, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3699, root_relative_squared_error: 0.7406, scimark_benchmark: 947.1781, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9239, f_measure: 0.8515, kappa: 0.7021, kb_relative_information_score: 1576.0152, mean_absolute_error: 0.1933, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.8517, predictive_accuracy: 0.8516, prior_entropy: 0.9984, recall: 0.8516, relative_absolute_error: 0.3876, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3277, root_relative_squared_error: 0.6562, scimark_benchmark: 932.438,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9239, f_measure: 0.8515, kappa: 0.7021, kb_relative_information_score: 1576.0152, mean_absolute_error: 0.1933, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.8517, predictive_accuracy: 0.8516, prior_entropy: 0.9984, recall: 0.8516, relative_absolute_error: 0.3876, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3277, root_relative_squared_error: 0.6562, scimark_benchmark: 941.3847,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9731, f_measure: 0.8943, kappa: 0.788, kb_relative_information_score: 1788.7893, mean_absolute_error: 0.1522, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.8946, predictive_accuracy: 0.8944, prior_entropy: 0.9984, recall: 0.8944, relative_absolute_error: 0.3051, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.2605, root_relative_squared_error: 0.5215, scimark_benchmark: 937.5117, usercpu_time_millis: 50, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.937, f_measure: 0.8619, kappa: 0.7232, kb_relative_information_score: 1683.2873, mean_absolute_error: 0.17, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.862, predictive_accuracy: 0.862, prior_entropy: 0.9984, recall: 0.862, relative_absolute_error: 0.3408, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3159, root_relative_squared_error: 0.6326, scimark_benchmark: 932.438, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8911, f_measure: 0.838, kappa: 0.6751, kb_relative_information_score: 1554.5805, mean_absolute_error: 0.1972, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.8392, predictive_accuracy: 0.8384, prior_entropy: 0.9984, recall: 0.8384, relative_absolute_error: 0.3952, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.348, root_relative_squared_error: 0.6968, scimark_benchmark: 942.2392,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9335, f_measure: 0.8707, kappa: 0.7407, kb_relative_information_score: 1517.3063, mean_absolute_error: 0.211, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.8709, predictive_accuracy: 0.8708, prior_entropy: 0.9984, recall: 0.8708, relative_absolute_error: 0.423, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3155, root_relative_squared_error: 0.6317, scimark_benchmark: 908.9569, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9342, f_measure: 0.8728, kappa: 0.7449, kb_relative_information_score: 1709.8076, mean_absolute_error: 0.1672, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.8728, predictive_accuracy: 0.8728, prior_entropy: 0.9984, recall: 0.8728, relative_absolute_error: 0.3351, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3097, root_relative_squared_error: 0.6202, scimark_benchmark: 936.2574, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8632, f_measure: 0.8632, kappa: 0.726, kb_relative_information_score: 1813.6914, mean_absolute_error: 0.1368, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.8634, predictive_accuracy: 0.8632, prior_entropy: 0.9984, recall: 0.8632, relative_absolute_error: 0.2742, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3699, root_relative_squared_error: 0.7406, scimark_benchmark: 931.7096, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8632, f_measure: 0.8632, kappa: 0.726, kb_relative_information_score: 1813.6914, mean_absolute_error: 0.1368, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.8634, predictive_accuracy: 0.8632, prior_entropy: 0.9984, recall: 0.8632, relative_absolute_error: 0.2742, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3699, root_relative_squared_error: 0.7406, scimark_benchmark: 930.404, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9146, f_measure: 0.852, kappa: 0.7032, kb_relative_information_score: 1532.1803, mean_absolute_error: 0.2036, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.852, predictive_accuracy: 0.852, prior_entropy: 0.9984, recall: 0.852, relative_absolute_error: 0.4081, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3375, root_relative_squared_error: 0.6758, scimark_benchmark: 930.404,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9239, f_measure: 0.8515, kappa: 0.7021, kb_relative_information_score: 1576.0152, mean_absolute_error: 0.1933, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.8517, predictive_accuracy: 0.8516, prior_entropy: 0.9984, recall: 0.8516, relative_absolute_error: 0.3876, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3277, root_relative_squared_error: 0.6562, scimark_benchmark: 930.404,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9239, f_measure: 0.8515, kappa: 0.7021, kb_relative_information_score: 1576.0152, mean_absolute_error: 0.1933, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.8517, predictive_accuracy: 0.8516, prior_entropy: 0.9984, recall: 0.8516, relative_absolute_error: 0.3876, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3277, root_relative_squared_error: 0.6562, scimark_benchmark: 903.2737,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9239, f_measure: 0.8515, kappa: 0.7021, kb_relative_information_score: 1576.0152, mean_absolute_error: 0.1933, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.8517, predictive_accuracy: 0.8516, prior_entropy: 0.9984, recall: 0.8516, relative_absolute_error: 0.3876, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3277, root_relative_squared_error: 0.6562, scimark_benchmark: 930.404,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9479, f_measure: 0.8735, kappa: 0.7463, kb_relative_information_score: 1646.8284, mean_absolute_error: 0.1827, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.8737, predictive_accuracy: 0.8736, prior_entropy: 0.9984, recall: 0.8736, relative_absolute_error: 0.3663, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.2964, root_relative_squared_error: 0.5936, scimark_benchmark: 903.2737, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8027, f_measure: 0.7289, kappa: 0.4567, kb_relative_information_score: 712.9719, mean_absolute_error: 0.3721, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.729, predictive_accuracy: 0.7288, prior_entropy: 0.9984, recall: 0.7288, relative_absolute_error: 0.7459, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4254, root_relative_squared_error: 0.8518, scimark_benchmark: 1051.249, usercpu_time_millis: 330, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 320,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9239, f_measure: 0.8515, kappa: 0.7021, kb_relative_information_score: 1576.0152, mean_absolute_error: 0.1933, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.8517, predictive_accuracy: 0.8516, prior_entropy: 0.9984, recall: 0.8516, relative_absolute_error: 0.3876, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3277, root_relative_squared_error: 0.6562, scimark_benchmark: 936.9595,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9181, f_measure: 0.8719, kappa: 0.743, kb_relative_information_score: 1688.6268, mean_absolute_error: 0.1713, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.8722, predictive_accuracy: 0.872, prior_entropy: 0.9984, recall: 0.872, relative_absolute_error: 0.3434, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3248, root_relative_squared_error: 0.6504, scimark_benchmark: 932.438, usercpu_time_millis: 60, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9731, f_measure: 0.8943, kappa: 0.788, kb_relative_information_score: 1788.7893, mean_absolute_error: 0.1522, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.8946, predictive_accuracy: 0.8944, prior_entropy: 0.9984, recall: 0.8944, relative_absolute_error: 0.3051, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.2605, root_relative_squared_error: 0.5215, scimark_benchmark: 941.4991, usercpu_time_millis: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9791, f_measure: 0.9231, kappa: 0.8458, kb_relative_information_score: 1649.3661, mean_absolute_error: 0.1915, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.9235, predictive_accuracy: 0.9232, prior_entropy: 0.9984, recall: 0.9232, relative_absolute_error: 0.3839, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.2569, root_relative_squared_error: 0.5145, scimark_benchmark: 1051.249, usercpu_time_millis: 870, usercpu_time_millis_testing: 250, usercpu_time_millis_training: 620,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9785, f_measure: 0.9235, kappa: 0.8466, kb_relative_information_score: 1645.9097, mean_absolute_error: 0.192, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.9239, predictive_accuracy: 0.9236, prior_entropy: 0.9984, recall: 0.9236, relative_absolute_error: 0.3849, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.2581, root_relative_squared_error: 0.5167, scimark_benchmark: 933.4823, usercpu_time_millis: 300, usercpu_time_millis_testing: 80, usercpu_time_millis_training: 220,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9774, f_measure: 0.9175, kappa: 0.8346, kb_relative_information_score: 1642.1773, mean_absolute_error: 0.1918, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.9179, predictive_accuracy: 0.9176, prior_entropy: 0.9984, recall: 0.9176, relative_absolute_error: 0.3846, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.261, root_relative_squared_error: 0.5226, scimark_benchmark: 929.7512, usercpu_time_millis: 160, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 130,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9755, f_measure: 0.9211, kappa: 0.8418, kb_relative_information_score: 1640.1712, mean_absolute_error: 0.1919, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.9215, predictive_accuracy: 0.9212, prior_entropy: 0.9984, recall: 0.9212, relative_absolute_error: 0.3846, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.2636, root_relative_squared_error: 0.5278, scimark_benchmark: 930.2337, usercpu_time_millis: 80, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9681, f_measure: 0.9083, kappa: 0.816, kb_relative_information_score: 1606.5297, mean_absolute_error: 0.1972, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.909, predictive_accuracy: 0.9084, prior_entropy: 0.9984, recall: 0.9084, relative_absolute_error: 0.3954, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.2748, root_relative_squared_error: 0.5501, scimark_benchmark: 939.7883, usercpu_time_millis: 40, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9365, f_measure: 0.8647, kappa: 0.7288, kb_relative_information_score: 1703.5728, mean_absolute_error: 0.1654, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.8648, predictive_accuracy: 0.8648, prior_entropy: 0.9984, recall: 0.8648, relative_absolute_error: 0.3316, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3159, root_relative_squared_error: 0.6325, scimark_benchmark: 941.9549, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9365, f_measure: 0.8647, kappa: 0.7288, kb_relative_information_score: 1703.5728, mean_absolute_error: 0.1654, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.8648, predictive_accuracy: 0.8648, prior_entropy: 0.9984, recall: 0.8648, relative_absolute_error: 0.3316, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3159, root_relative_squared_error: 0.6325, scimark_benchmark: 938.3115, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9365, f_measure: 0.8639, kappa: 0.7272, kb_relative_information_score: 1699.1753, mean_absolute_error: 0.1663, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.864, predictive_accuracy: 0.864, prior_entropy: 0.9984, recall: 0.864, relative_absolute_error: 0.3334, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3164, root_relative_squared_error: 0.6336, scimark_benchmark: 894.7131, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4928, f_measure: 0.3603, kb_relative_information_score: -0.2572, mean_absolute_error: 0.4989, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.2746, predictive_accuracy: 0.524, prior_entropy: 0.9984, recall: 0.524, relative_absolute_error: 1.0001, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4995, root_relative_squared_error: 1.0001, scimark_benchmark: 941.9549,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8027, f_measure: 0.7289, kappa: 0.4567, kb_relative_information_score: 712.9719, mean_absolute_error: 0.3721, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.729, predictive_accuracy: 0.7288, prior_entropy: 0.9984, recall: 0.7288, relative_absolute_error: 0.7459, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4254, root_relative_squared_error: 0.8518, scimark_benchmark: 1319.952, usercpu_time_millis: 300, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 290,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9146, f_measure: 0.852, kappa: 0.7032, kb_relative_information_score: 1532.1803, mean_absolute_error: 0.2036, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.852, predictive_accuracy: 0.852, prior_entropy: 0.9984, recall: 0.852, relative_absolute_error: 0.4081, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3375, root_relative_squared_error: 0.6758, scimark_benchmark: 1338.5214,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9181, f_measure: 0.8719, kappa: 0.743, kb_relative_information_score: 1688.6268, mean_absolute_error: 0.1713, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.8722, predictive_accuracy: 0.872, prior_entropy: 0.9984, recall: 0.872, relative_absolute_error: 0.3434, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3248, root_relative_squared_error: 0.6504, scimark_benchmark: 1317.6232, usercpu_time_millis: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9731, f_measure: 0.8943, kappa: 0.788, kb_relative_information_score: 1788.7893, mean_absolute_error: 0.1522, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.8946, predictive_accuracy: 0.8944, prior_entropy: 0.9984, recall: 0.8944, relative_absolute_error: 0.3051, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.2605, root_relative_squared_error: 0.5215, scimark_benchmark: 1330.9181, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8615, f_measure: 0.7611, kappa: 0.521, kb_relative_information_score: 877.4936, mean_absolute_error: 0.3441, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.7629, predictive_accuracy: 0.762, prior_entropy: 0.9984, recall: 0.762, relative_absolute_error: 0.6898, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4138, root_relative_squared_error: 0.8285, scimark_benchmark: 1318.3027, usercpu_time_millis: 140, usercpu_time_millis_testing: 140,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9342, f_measure: 0.8728, kappa: 0.7449, kb_relative_information_score: 1709.8076, mean_absolute_error: 0.1672, mean_prior_absolute_error: 0.4989, number_of_instances: 2500, precision: 0.8728, predictive_accuracy: 0.8728, prior_entropy: 0.9984, recall: 0.8728, relative_absolute_error: 0.3351, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3097, root_relative_squared_error: 0.6202, scimark_benchmark: 1319.5773, usercpu_time_millis: 10, usercpu_time_millis_training: 10,

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