Task
Supervised Classification on lupus

Supervised Classification on lupus

Task 4267 Supervised Classification lupus 222 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7257, f_measure: 0.705, kappa: 0.3825, kb_relative_information_score: 0.2958, mean_absolute_error: 0.3426, mean_prior_absolute_error: 0.4813, weighted_recall: 0.708, number_of_instances: 870, precision: 0.7045, predictive_accuracy: 0.708, prior_entropy: 0.9723, relative_absolute_error: 0.7118, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.4652, root_relative_squared_error: 0.9488, scimark_benchmark: 931.1106, unweighted_recall: 0.688,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8268, f_measure: 0.7612, kappa: 0.5006, kb_relative_information_score: 0.3715, mean_absolute_error: 0.3124, mean_prior_absolute_error: 0.4813, weighted_recall: 0.7632, number_of_instances: 870, precision: 0.7611, predictive_accuracy: 0.7632, prior_entropy: 0.9723, relative_absolute_error: 0.6491, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.4057, root_relative_squared_error: 0.8274, scimark_benchmark: 979.7764, unweighted_recall: 0.7468,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6705, f_measure: 0.7461, kappa: 0.4718, kb_relative_information_score: 285.6026, mean_absolute_error: 0.3367, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.789, predictive_accuracy: 0.7644, prior_entropy: 0.9735, recall: 0.7644, relative_absolute_error: 0.6995, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.4304, root_relative_squared_error: 0.8777, scimark_benchmark: 906.0979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7561, f_measure: 0.714, kappa: 0.4, kb_relative_information_score: 237.5005, mean_absolute_error: 0.3563, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.7157, predictive_accuracy: 0.7195, prior_entropy: 0.9735, recall: 0.7195, relative_absolute_error: 0.7402, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.4346, root_relative_squared_error: 0.8862, scimark_benchmark: 972.587,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7389, f_measure: 0.7073, kappa: 0.3856, kb_relative_information_score: 276.7407, mean_absolute_error: 0.3306, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.7098, predictive_accuracy: 0.7138, prior_entropy: 0.9735, recall: 0.7138, relative_absolute_error: 0.6869, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.4663, root_relative_squared_error: 0.9508, scimark_benchmark: 934.3687, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6697, f_measure: 0.7461, kappa: 0.4718, kb_relative_information_score: 277.4633, mean_absolute_error: 0.3424, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.789, predictive_accuracy: 0.7644, prior_entropy: 0.9735, recall: 0.7644, relative_absolute_error: 0.7113, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.4289, root_relative_squared_error: 0.8746, scimark_benchmark: 941.6675,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6697, f_measure: 0.7461, kappa: 0.4718, kb_relative_information_score: 279.0959, mean_absolute_error: 0.3412, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.789, predictive_accuracy: 0.7644, prior_entropy: 0.9735, recall: 0.7644, relative_absolute_error: 0.7088, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.4293, root_relative_squared_error: 0.8755, scimark_benchmark: 941.6675,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6697, f_measure: 0.7461, kappa: 0.4718, kb_relative_information_score: 279.0959, mean_absolute_error: 0.3412, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.789, predictive_accuracy: 0.7644, prior_entropy: 0.9735, recall: 0.7644, relative_absolute_error: 0.7088, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.4293, root_relative_squared_error: 0.8755, scimark_benchmark: 941.6675,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7723, f_measure: 0.7227, kappa: 0.4178, kb_relative_information_score: 281.6391, mean_absolute_error: 0.3334, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.7315, predictive_accuracy: 0.7322, prior_entropy: 0.9735, recall: 0.7322, relative_absolute_error: 0.6928, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.4258, root_relative_squared_error: 0.8683, scimark_benchmark: 938.191,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.828, f_measure: 0.7574, kappa: 0.4922, kb_relative_information_score: 303.9753, mean_absolute_error: 0.3251, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.7575, predictive_accuracy: 0.7598, prior_entropy: 0.9735, recall: 0.7598, relative_absolute_error: 0.6755, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.403, root_relative_squared_error: 0.8219, scimark_benchmark: 934.695,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4978, f_measure: 0.476, kappa: -0.0051, kb_relative_information_score: 105.2725, mean_absolute_error: 0.4161, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.5113, predictive_accuracy: 0.5839, prior_entropy: 0.9735, recall: 0.5839, relative_absolute_error: 0.8644, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.6451, root_relative_squared_error: 1.3154, scimark_benchmark: 906.0979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4978, f_measure: 0.476, kappa: -0.0051, kb_relative_information_score: 105.2725, mean_absolute_error: 0.4161, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.5113, predictive_accuracy: 0.5839, prior_entropy: 0.9735, recall: 0.5839, relative_absolute_error: 0.8644, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.6451, root_relative_squared_error: 1.3154, scimark_benchmark: 941.3847,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6697, f_measure: 0.7461, kappa: 0.4718, kb_relative_information_score: 279.0959, mean_absolute_error: 0.3412, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.789, predictive_accuracy: 0.7644, prior_entropy: 0.9735, recall: 0.7644, relative_absolute_error: 0.7088, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.4293, root_relative_squared_error: 0.8755, scimark_benchmark: 947.1781,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7257, f_measure: 0.705, kappa: 0.3825, kb_relative_information_score: 257.0036, mean_absolute_error: 0.3426, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.7045, predictive_accuracy: 0.708, prior_entropy: 0.9735, recall: 0.708, relative_absolute_error: 0.7118, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.4652, root_relative_squared_error: 0.9488, scimark_benchmark: 943.1009, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6705, f_measure: 0.7461, kappa: 0.4718, kb_relative_information_score: 285.6026, mean_absolute_error: 0.3367, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.789, predictive_accuracy: 0.7644, prior_entropy: 0.9735, recall: 0.7644, relative_absolute_error: 0.6995, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.4304, root_relative_squared_error: 0.8777, scimark_benchmark: 942.2392,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7561, f_measure: 0.714, kappa: 0.4, kb_relative_information_score: 237.5005, mean_absolute_error: 0.3563, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.7157, predictive_accuracy: 0.7195, prior_entropy: 0.9735, recall: 0.7195, relative_absolute_error: 0.7402, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.4346, root_relative_squared_error: 0.8862, scimark_benchmark: 908.9569,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7389, f_measure: 0.7073, kappa: 0.3856, kb_relative_information_score: 276.7407, mean_absolute_error: 0.3306, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.7098, predictive_accuracy: 0.7138, prior_entropy: 0.9735, recall: 0.7138, relative_absolute_error: 0.6869, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.4663, root_relative_squared_error: 0.9508, scimark_benchmark: 938.1282,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4978, f_measure: 0.476, kappa: -0.0051, kb_relative_information_score: 105.2725, mean_absolute_error: 0.4161, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.5113, predictive_accuracy: 0.5839, prior_entropy: 0.9735, recall: 0.5839, relative_absolute_error: 0.8644, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.6451, root_relative_squared_error: 1.3154, scimark_benchmark: 927.2882,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6697, f_measure: 0.7461, kappa: 0.4718, kb_relative_information_score: 279.0959, mean_absolute_error: 0.3412, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.789, predictive_accuracy: 0.7644, prior_entropy: 0.9735, recall: 0.7644, relative_absolute_error: 0.7088, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.4293, root_relative_squared_error: 0.8755, scimark_benchmark: 903.2737,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6697, f_measure: 0.7461, kappa: 0.4718, kb_relative_information_score: 279.0959, mean_absolute_error: 0.3412, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.789, predictive_accuracy: 0.7644, prior_entropy: 0.9735, recall: 0.7644, relative_absolute_error: 0.7088, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.4293, root_relative_squared_error: 0.8755, scimark_benchmark: 941.4991,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7723, f_measure: 0.7227, kappa: 0.4178, kb_relative_information_score: 281.6391, mean_absolute_error: 0.3334, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.7315, predictive_accuracy: 0.7322, prior_entropy: 0.9735, recall: 0.7322, relative_absolute_error: 0.6928, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.4258, root_relative_squared_error: 0.8683, scimark_benchmark: 903.2737,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.828, f_measure: 0.7574, kappa: 0.4922, kb_relative_information_score: 303.9753, mean_absolute_error: 0.3251, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.7575, predictive_accuracy: 0.7598, prior_entropy: 0.9735, recall: 0.7598, relative_absolute_error: 0.6755, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.403, root_relative_squared_error: 0.8219, scimark_benchmark: 905.2959, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7257, f_measure: 0.705, kappa: 0.3825, kb_relative_information_score: 257.0036, mean_absolute_error: 0.3426, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.7045, predictive_accuracy: 0.708, prior_entropy: 0.9735, recall: 0.708, relative_absolute_error: 0.7118, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.4652, root_relative_squared_error: 0.9488, scimark_benchmark: 917.5013, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.747, f_measure: 0.7414, kappa: 0.4573, kb_relative_information_score: 243.1836, mean_absolute_error: 0.3616, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.7522, predictive_accuracy: 0.7506, prior_entropy: 0.9735, recall: 0.7506, relative_absolute_error: 0.7512, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.4293, root_relative_squared_error: 0.8754, scimark_benchmark: 904.5548, usercpu_time_millis: 120, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 90,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7463, f_measure: 0.7462, kappa: 0.4673, kb_relative_information_score: 242.1959, mean_absolute_error: 0.3622, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.7573, predictive_accuracy: 0.7552, prior_entropy: 0.9735, recall: 0.7552, relative_absolute_error: 0.7525, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.4296, root_relative_squared_error: 0.8762, scimark_benchmark: 933.4823, usercpu_time_millis: 60, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7488, f_measure: 0.748, kappa: 0.4712, kb_relative_information_score: 242.468, mean_absolute_error: 0.3619, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.7606, predictive_accuracy: 0.7575, prior_entropy: 0.9735, recall: 0.7575, relative_absolute_error: 0.7518, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.4298, root_relative_squared_error: 0.8765, scimark_benchmark: 938.8535, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7437, f_measure: 0.7378, kappa: 0.4494, kb_relative_information_score: 237.875, mean_absolute_error: 0.3638, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.7459, predictive_accuracy: 0.746, prior_entropy: 0.9735, recall: 0.746, relative_absolute_error: 0.7557, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.4337, root_relative_squared_error: 0.8844, scimark_benchmark: 945.2015, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7443, f_measure: 0.7464, kappa: 0.468, kb_relative_information_score: 240.8844, mean_absolute_error: 0.3625, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.7599, predictive_accuracy: 0.7563, prior_entropy: 0.9735, recall: 0.7563, relative_absolute_error: 0.753, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.4325, root_relative_squared_error: 0.8819, scimark_benchmark: 935.6052, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7719, f_measure: 0.7312, kappa: 0.4362, kb_relative_information_score: 322.6614, mean_absolute_error: 0.3043, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.7456, predictive_accuracy: 0.7425, prior_entropy: 0.9735, recall: 0.7425, relative_absolute_error: 0.6322, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.428, root_relative_squared_error: 0.8729, scimark_benchmark: 929.0296,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4497, f_measure: 0.4472, kb_relative_information_score: -1.8235, mean_absolute_error: 0.4818, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.3572, predictive_accuracy: 0.5977, prior_entropy: 0.9735, recall: 0.5977, relative_absolute_error: 1.001, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.4909, root_relative_squared_error: 1.001, scimark_benchmark: 926.5859,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7561, f_measure: 0.714, kappa: 0.4, kb_relative_information_score: 237.5005, mean_absolute_error: 0.3563, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.7157, predictive_accuracy: 0.7195, prior_entropy: 0.9735, recall: 0.7195, relative_absolute_error: 0.7402, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.4346, root_relative_squared_error: 0.8862, scimark_benchmark: 1358.6198,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4978, f_measure: 0.476, kappa: -0.0051, kb_relative_information_score: 105.2725, mean_absolute_error: 0.4161, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.5113, predictive_accuracy: 0.5839, prior_entropy: 0.9735, recall: 0.5839, relative_absolute_error: 0.8644, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.6451, root_relative_squared_error: 1.3154, scimark_benchmark: 1334.863, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6697, f_measure: 0.7461, kappa: 0.4718, kb_relative_information_score: 279.0959, mean_absolute_error: 0.3412, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.789, predictive_accuracy: 0.7644, prior_entropy: 0.9735, recall: 0.7644, relative_absolute_error: 0.7088, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.4293, root_relative_squared_error: 0.8755, scimark_benchmark: 1346.4374,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6697, f_measure: 0.7461, kappa: 0.4718, kb_relative_information_score: 279.0959, mean_absolute_error: 0.3412, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.789, predictive_accuracy: 0.7644, prior_entropy: 0.9735, recall: 0.7644, relative_absolute_error: 0.7088, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.4293, root_relative_squared_error: 0.8755, scimark_benchmark: 1337.1928,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6697, f_measure: 0.7461, kappa: 0.4718, kb_relative_information_score: 279.0959, mean_absolute_error: 0.3412, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.789, predictive_accuracy: 0.7644, prior_entropy: 0.9735, recall: 0.7644, relative_absolute_error: 0.7088, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.4293, root_relative_squared_error: 0.8755, scimark_benchmark: 1338.5214,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6697, f_measure: 0.7461, kappa: 0.4718, kb_relative_information_score: 269.8169, mean_absolute_error: 0.3475, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.789, predictive_accuracy: 0.7644, prior_entropy: 0.9735, recall: 0.7644, relative_absolute_error: 0.722, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.4279, root_relative_squared_error: 0.8726, scimark_benchmark: 1320.8283,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7257, f_measure: 0.705, kappa: 0.3825, kb_relative_information_score: 257.0036, mean_absolute_error: 0.3426, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.7045, predictive_accuracy: 0.708, prior_entropy: 0.9735, recall: 0.708, relative_absolute_error: 0.7118, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.4652, root_relative_squared_error: 0.9488, scimark_benchmark: 1313.5633, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7389, f_measure: 0.7073, kappa: 0.3856, kb_relative_information_score: 276.7407, mean_absolute_error: 0.3306, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.7098, predictive_accuracy: 0.7138, prior_entropy: 0.9735, recall: 0.7138, relative_absolute_error: 0.6869, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.4663, root_relative_squared_error: 0.9508, scimark_benchmark: 1344.0499,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8185, f_measure: 0.7461, kappa: 0.468, kb_relative_information_score: 288.8091, mean_absolute_error: 0.3322, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.7468, predictive_accuracy: 0.7494, prior_entropy: 0.9735, recall: 0.7494, relative_absolute_error: 0.6901, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.4063, root_relative_squared_error: 0.8287, scimark_benchmark: 1324.5762, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6697, f_measure: 0.7461, kappa: 0.4718, kb_relative_information_score: 279.0959, mean_absolute_error: 0.3412, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.789, predictive_accuracy: 0.7644, prior_entropy: 0.9735, recall: 0.7644, relative_absolute_error: 0.7088, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.4293, root_relative_squared_error: 0.8755, scimark_benchmark: 1354.7111,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6697, f_measure: 0.7461, kappa: 0.4718, kb_relative_information_score: 279.0959, mean_absolute_error: 0.3412, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.789, predictive_accuracy: 0.7644, prior_entropy: 0.9735, recall: 0.7644, relative_absolute_error: 0.7088, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.4293, root_relative_squared_error: 0.8755, scimark_benchmark: 1336.4701,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6697, f_measure: 0.7461, kappa: 0.4718, kb_relative_information_score: 279.0959, mean_absolute_error: 0.3412, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.789, predictive_accuracy: 0.7644, prior_entropy: 0.9735, recall: 0.7644, relative_absolute_error: 0.7088, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.4293, root_relative_squared_error: 0.8755, scimark_benchmark: 1317.2327,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7723, f_measure: 0.7227, kappa: 0.4178, kb_relative_information_score: 281.6391, mean_absolute_error: 0.3334, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.7315, predictive_accuracy: 0.7322, prior_entropy: 0.9735, recall: 0.7322, relative_absolute_error: 0.6928, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.4258, root_relative_squared_error: 0.8683, scimark_benchmark: 1303.9481,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4978, f_measure: 0.476, kappa: -0.0051, kb_relative_information_score: 105.2725, mean_absolute_error: 0.4161, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.5113, predictive_accuracy: 0.5839, prior_entropy: 0.9735, recall: 0.5839, relative_absolute_error: 0.8644, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.6451, root_relative_squared_error: 1.3154, scimark_benchmark: 1359.7293,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4978, f_measure: 0.476, kappa: -0.0051, kb_relative_information_score: 105.2725, mean_absolute_error: 0.4161, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.5113, predictive_accuracy: 0.5839, prior_entropy: 0.9735, recall: 0.5839, relative_absolute_error: 0.8644, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.6451, root_relative_squared_error: 1.3154, scimark_benchmark: 1274.7011, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6697, f_measure: 0.7461, kappa: 0.4718, kb_relative_information_score: 269.8169, mean_absolute_error: 0.3475, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.789, predictive_accuracy: 0.7644, prior_entropy: 0.9735, recall: 0.7644, relative_absolute_error: 0.722, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.4279, root_relative_squared_error: 0.8726, scimark_benchmark: 1350.8432, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7257, f_measure: 0.705, kappa: 0.3825, kb_relative_information_score: 257.0036, mean_absolute_error: 0.3426, mean_prior_absolute_error: 0.4813, number_of_instances: 870, precision: 0.7045, predictive_accuracy: 0.708, prior_entropy: 0.9735, recall: 0.708, relative_absolute_error: 0.7118, root_mean_prior_squared_error: 0.4904, root_mean_squared_error: 0.4652, root_relative_squared_error: 0.9488, scimark_benchmark: 1333.202,

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