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Supervised Classification on fri_c2_500_5

Supervised Classification on fri_c2_500_5

Task 4362 Supervised Classification fri_c2_500_5 237 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8948, f_measure: 0.8518, kappa: 0.6902, kb_relative_information_score: 3087.4094, mean_absolute_error: 0.1919, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.8541, predictive_accuracy: 0.8536, prior_entropy: 0.9735, recall: 0.8536, relative_absolute_error: 0.3983, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.3378, root_relative_squared_error: 0.6883, scimark_benchmark: 906.0979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.93, f_measure: 0.8592, kappa: 0.7068, kb_relative_information_score: 2958.1559, mean_absolute_error: 0.2075, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.8591, predictive_accuracy: 0.8596, prior_entropy: 0.9735, recall: 0.8596, relative_absolute_error: 0.4308, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.3141, root_relative_squared_error: 0.6401, scimark_benchmark: 972.587, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.925, f_measure: 0.8675, kappa: 0.724, kb_relative_information_score: 3237.7651, mean_absolute_error: 0.1782, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.8675, predictive_accuracy: 0.868, prior_entropy: 0.9735, recall: 0.868, relative_absolute_error: 0.3699, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.3172, root_relative_squared_error: 0.6464, scimark_benchmark: 934.3687, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8938, f_measure: 0.8974, kappa: 0.7871, kb_relative_information_score: 3916.601, mean_absolute_error: 0.1026, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.8975, predictive_accuracy: 0.8974, prior_entropy: 0.9735, recall: 0.8974, relative_absolute_error: 0.213, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.3203, root_relative_squared_error: 0.6528, scimark_benchmark: 944.1067, usercpu_time_millis: 40, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8938, f_measure: 0.8974, kappa: 0.7871, kb_relative_information_score: 3916.601, mean_absolute_error: 0.1026, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.8975, predictive_accuracy: 0.8974, prior_entropy: 0.9735, recall: 0.8974, relative_absolute_error: 0.213, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.3203, root_relative_squared_error: 0.6528, scimark_benchmark: 916.0735, usercpu_time_millis: 50, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9118, f_measure: 0.8572, kappa: 0.7017, kb_relative_information_score: 3132.1468, mean_absolute_error: 0.1869, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.8583, predictive_accuracy: 0.8584, prior_entropy: 0.9735, recall: 0.8584, relative_absolute_error: 0.3881, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.329, root_relative_squared_error: 0.6704, scimark_benchmark: 941.6675,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9118, f_measure: 0.8572, kappa: 0.7017, kb_relative_information_score: 3132.1468, mean_absolute_error: 0.1869, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.8583, predictive_accuracy: 0.8584, prior_entropy: 0.9735, recall: 0.8584, relative_absolute_error: 0.3881, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.329, root_relative_squared_error: 0.6704, scimark_benchmark: 941.6675,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9456, f_measure: 0.8888, kappa: 0.7677, kb_relative_information_score: 3428.8623, mean_absolute_error: 0.1607, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.8905, predictive_accuracy: 0.8898, prior_entropy: 0.9735, recall: 0.8898, relative_absolute_error: 0.3336, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.285, root_relative_squared_error: 0.5808, scimark_benchmark: 938.191, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8191, f_measure: 0.75, kappa: 0.4812, kb_relative_information_score: 1479.6461, mean_absolute_error: 0.3499, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.7502, predictive_accuracy: 0.7498, prior_entropy: 0.9735, recall: 0.7498, relative_absolute_error: 0.7264, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.4125, root_relative_squared_error: 0.8407, scimark_benchmark: 938.8177, usercpu_time_millis: 1420, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 1400,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9194, f_measure: 0.874, kappa: 0.7376, kb_relative_information_score: 3344.7651, mean_absolute_error: 0.1665, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.874, predictive_accuracy: 0.8744, prior_entropy: 0.9735, recall: 0.8744, relative_absolute_error: 0.3458, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.3183, root_relative_squared_error: 0.6486, scimark_benchmark: 905.2959,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8938, f_measure: 0.8974, kappa: 0.7871, kb_relative_information_score: 3916.601, mean_absolute_error: 0.1026, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.8975, predictive_accuracy: 0.8974, prior_entropy: 0.9735, recall: 0.8974, relative_absolute_error: 0.213, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.3203, root_relative_squared_error: 0.6528, scimark_benchmark: 941.3847, usercpu_time_millis: 40, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8938, f_measure: 0.8974, kappa: 0.7871, kb_relative_information_score: 3916.601, mean_absolute_error: 0.1026, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.8975, predictive_accuracy: 0.8974, prior_entropy: 0.9735, recall: 0.8974, relative_absolute_error: 0.213, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.3203, root_relative_squared_error: 0.6528, scimark_benchmark: 941.3847, usercpu_time_millis: 40, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9118, f_measure: 0.8572, kappa: 0.7017, kb_relative_information_score: 3132.1468, mean_absolute_error: 0.1869, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.8583, predictive_accuracy: 0.8584, prior_entropy: 0.9735, recall: 0.8584, relative_absolute_error: 0.3881, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.329, root_relative_squared_error: 0.6704, scimark_benchmark: 974.2014,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9734, f_measure: 0.9125, kappa: 0.8175, kb_relative_information_score: 3700.7514, mean_absolute_error: 0.1326, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.9132, predictive_accuracy: 0.913, prior_entropy: 0.9735, recall: 0.913, relative_absolute_error: 0.2753, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.2487, root_relative_squared_error: 0.5069, scimark_benchmark: 947.1781, usercpu_time_millis: 110, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 90,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8948, f_measure: 0.8518, kappa: 0.6902, kb_relative_information_score: 3087.4094, mean_absolute_error: 0.1919, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.8541, predictive_accuracy: 0.8536, prior_entropy: 0.9735, recall: 0.8536, relative_absolute_error: 0.3983, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.3378, root_relative_squared_error: 0.6883, scimark_benchmark: 942.2392,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.93, f_measure: 0.8592, kappa: 0.7068, kb_relative_information_score: 2958.1559, mean_absolute_error: 0.2075, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.8591, predictive_accuracy: 0.8596, prior_entropy: 0.9735, recall: 0.8596, relative_absolute_error: 0.4308, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.3141, root_relative_squared_error: 0.6401, scimark_benchmark: 908.9569, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.925, f_measure: 0.8675, kappa: 0.724, kb_relative_information_score: 3237.7651, mean_absolute_error: 0.1782, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.8675, predictive_accuracy: 0.868, prior_entropy: 0.9735, recall: 0.868, relative_absolute_error: 0.3699, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.3172, root_relative_squared_error: 0.6464, scimark_benchmark: 936.2574, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8938, f_measure: 0.8974, kappa: 0.7871, kb_relative_information_score: 3916.601, mean_absolute_error: 0.1026, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.8975, predictive_accuracy: 0.8974, prior_entropy: 0.9735, recall: 0.8974, relative_absolute_error: 0.213, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.3203, root_relative_squared_error: 0.6528, 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: 0.8938, f_measure: 0.8974, kappa: 0.7871, kb_relative_information_score: 3916.601, mean_absolute_error: 0.1026, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.8975, predictive_accuracy: 0.8974, prior_entropy: 0.9735, recall: 0.8974, relative_absolute_error: 0.213, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.3203, root_relative_squared_error: 0.6528, scimark_benchmark: 934.5964, usercpu_time_millis: 50, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9118, f_measure: 0.8572, kappa: 0.7017, kb_relative_information_score: 3132.1468, mean_absolute_error: 0.1869, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.8583, predictive_accuracy: 0.8584, prior_entropy: 0.9735, recall: 0.8584, relative_absolute_error: 0.3881, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.329, root_relative_squared_error: 0.6704, scimark_benchmark: 930.404,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9118, f_measure: 0.8572, kappa: 0.7017, kb_relative_information_score: 3132.1468, mean_absolute_error: 0.1869, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.8583, predictive_accuracy: 0.8584, prior_entropy: 0.9735, recall: 0.8584, relative_absolute_error: 0.3881, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.329, root_relative_squared_error: 0.6704, scimark_benchmark: 941.4991, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9456, f_measure: 0.8888, kappa: 0.7677, kb_relative_information_score: 3428.8623, mean_absolute_error: 0.1607, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.8905, predictive_accuracy: 0.8898, prior_entropy: 0.9735, recall: 0.8898, relative_absolute_error: 0.3336, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.285, root_relative_squared_error: 0.5808, scimark_benchmark: 903.2737, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8191, f_measure: 0.75, kappa: 0.4812, kb_relative_information_score: 1479.6461, mean_absolute_error: 0.3499, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.7502, predictive_accuracy: 0.7498, prior_entropy: 0.9735, recall: 0.7498, relative_absolute_error: 0.7264, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.4125, root_relative_squared_error: 0.8407, scimark_benchmark: 905.2959, usercpu_time_millis: 2020, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 1990,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9118, f_measure: 0.8572, kappa: 0.7017, kb_relative_information_score: 3132.1468, mean_absolute_error: 0.1869, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.8583, predictive_accuracy: 0.8584, prior_entropy: 0.9735, recall: 0.8584, relative_absolute_error: 0.3881, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.329, root_relative_squared_error: 0.6704, scimark_benchmark: 944.0133, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9194, f_measure: 0.874, kappa: 0.7376, kb_relative_information_score: 3344.7651, mean_absolute_error: 0.1665, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.874, predictive_accuracy: 0.8744, prior_entropy: 0.9735, recall: 0.8744, relative_absolute_error: 0.3458, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.3183, root_relative_squared_error: 0.6486, scimark_benchmark: 730.6551, usercpu_time_millis: 180, usercpu_time_millis_training: 180,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9734, f_measure: 0.9125, kappa: 0.8175, kb_relative_information_score: 3700.7514, mean_absolute_error: 0.1326, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.9132, predictive_accuracy: 0.913, prior_entropy: 0.9735, recall: 0.913, relative_absolute_error: 0.2753, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.2487, root_relative_squared_error: 0.5069, scimark_benchmark: 901.4991, usercpu_time_millis: 110, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 90,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9808, f_measure: 0.9297, kappa: 0.8537, kb_relative_information_score: 3502.2655, mean_absolute_error: 0.161, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.9297, predictive_accuracy: 0.9298, prior_entropy: 0.9735, recall: 0.9298, relative_absolute_error: 0.3343, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.2401, root_relative_squared_error: 0.4894, scimark_benchmark: 934.695, usercpu_time_millis: 1470, usercpu_time_millis_testing: 460, usercpu_time_millis_training: 1010,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9806, f_measure: 0.9291, kappa: 0.8526, kb_relative_information_score: 3488.7486, mean_absolute_error: 0.1623, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.9291, predictive_accuracy: 0.9292, prior_entropy: 0.9735, recall: 0.9292, relative_absolute_error: 0.337, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.2415, root_relative_squared_error: 0.4922, scimark_benchmark: 937.5683, usercpu_time_millis: 630, usercpu_time_millis_testing: 140, usercpu_time_millis_training: 490,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9796, f_measure: 0.9282, kappa: 0.8507, kb_relative_information_score: 3496.0588, mean_absolute_error: 0.1612, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.9283, predictive_accuracy: 0.9284, prior_entropy: 0.9735, recall: 0.9284, relative_absolute_error: 0.3347, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.2427, root_relative_squared_error: 0.4945, scimark_benchmark: 862.7006, usercpu_time_millis: 340, usercpu_time_millis_testing: 80, usercpu_time_millis_training: 260,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9782, f_measure: 0.9243, kappa: 0.8426, kb_relative_information_score: 3514.5441, mean_absolute_error: 0.1584, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.9243, predictive_accuracy: 0.9244, prior_entropy: 0.9735, recall: 0.9244, relative_absolute_error: 0.329, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.2439, root_relative_squared_error: 0.497, scimark_benchmark: 890.4736, usercpu_time_millis: 160, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 120,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.972, f_measure: 0.9168, kappa: 0.8269, kb_relative_information_score: 3453.1467, mean_absolute_error: 0.1632, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.9168, predictive_accuracy: 0.917, prior_entropy: 0.9735, recall: 0.917, relative_absolute_error: 0.3388, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.2552, root_relative_squared_error: 0.52, scimark_benchmark: 939.7241, usercpu_time_millis: 80, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9143, f_measure: 0.8623, kappa: 0.7123, kb_relative_information_score: 3040.8995, mean_absolute_error: 0.1996, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.8633, predictive_accuracy: 0.8634, prior_entropy: 0.9735, recall: 0.8634, relative_absolute_error: 0.4145, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.3241, root_relative_squared_error: 0.6605, scimark_benchmark: 936.1714, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9143, f_measure: 0.8623, kappa: 0.7123, kb_relative_information_score: 3040.8995, mean_absolute_error: 0.1996, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.8633, predictive_accuracy: 0.8634, prior_entropy: 0.9735, recall: 0.8634, relative_absolute_error: 0.4145, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.3241, root_relative_squared_error: 0.6605, scimark_benchmark: 889.4922, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9143, f_measure: 0.8623, kappa: 0.7123, kb_relative_information_score: 3040.8995, mean_absolute_error: 0.1996, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.8633, predictive_accuracy: 0.8634, prior_entropy: 0.9735, recall: 0.8634, relative_absolute_error: 0.4145, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.3241, root_relative_squared_error: 0.6605, scimark_benchmark: 929.0296, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9143, f_measure: 0.8623, kappa: 0.7123, kb_relative_information_score: 3040.8995, mean_absolute_error: 0.1996, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.8633, predictive_accuracy: 0.8634, prior_entropy: 0.9735, recall: 0.8634, relative_absolute_error: 0.4145, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.3241, root_relative_squared_error: 0.6605, scimark_benchmark: 936.1714, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9136, f_measure: 0.8607, kappa: 0.709, kb_relative_information_score: 3016.691, mean_absolute_error: 0.2023, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.8617, predictive_accuracy: 0.8618, prior_entropy: 0.9735, recall: 0.8618, relative_absolute_error: 0.4201, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.3247, root_relative_squared_error: 0.6616, scimark_benchmark: 929.0296, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4934, f_measure: 0.4451, kb_relative_information_score: -0.733, mean_absolute_error: 0.4817, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.3552, predictive_accuracy: 0.596, prior_entropy: 0.9735, recall: 0.596, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.4907, root_relative_squared_error: 1, scimark_benchmark: 941.9549, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9537, f_measure: 0.8963, kappa: 0.7835, kb_relative_information_score: 3883.2931, mean_absolute_error: 0.1063, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.8973, predictive_accuracy: 0.897, prior_entropy: 0.9735, recall: 0.897, relative_absolute_error: 0.2208, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.304, root_relative_squared_error: 0.6194, scimark_benchmark: 926.5859, usercpu_time_millis: 200, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 190,
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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