OpenML
Supervised Classification on schlvote

Supervised Classification on schlvote

Task 4418 Supervised Classification schlvote 231 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6848, f_measure: 0.7996, kappa: 0.4631, kb_relative_information_score: 0.2171, mean_absolute_error: 0.3003, mean_prior_absolute_error: 0.3934, weighted_recall: 0.8105, number_of_instances: 380, precision: 0.8, predictive_accuracy: 0.8105, prior_entropy: 0.832, relative_absolute_error: 0.7634, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4027, root_relative_squared_error: 0.9142, scimark_benchmark: 931.1106, unweighted_recall: 0.7107,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7391, f_measure: 0.8084, kappa: 0.4873, kb_relative_information_score: 0.2509, mean_absolute_error: 0.2809, mean_prior_absolute_error: 0.3934, weighted_recall: 0.8184, number_of_instances: 380, precision: 0.8091, predictive_accuracy: 0.8184, prior_entropy: 0.832, relative_absolute_error: 0.714, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4018, root_relative_squared_error: 0.9121, scimark_benchmark: 979.7764, unweighted_recall: 0.7225,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5727, f_measure: 0.794, kappa: 0.4383, kb_relative_information_score: 121.1689, mean_absolute_error: 0.269, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.8118, predictive_accuracy: 0.8158, prior_entropy: 0.8485, recall: 0.8158, relative_absolute_error: 0.6836, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4004, root_relative_squared_error: 0.909, scimark_benchmark: 906.0979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.73, f_measure: 0.8049, kappa: 0.4849, kb_relative_information_score: 175.1826, mean_absolute_error: 0.1895, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.8028, predictive_accuracy: 0.8105, prior_entropy: 0.8485, recall: 0.8105, relative_absolute_error: 0.4816, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4353, root_relative_squared_error: 0.9881,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6133, f_measure: 0.7344, kappa: 0.3036, kb_relative_information_score: 65.144, mean_absolute_error: 0.3087, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.7306, predictive_accuracy: 0.7395, prior_entropy: 0.8485, recall: 0.7395, relative_absolute_error: 0.7847, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4348, root_relative_squared_error: 0.987, scimark_benchmark: 972.587,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6463, f_measure: 0.699, kappa: 0.2214, kb_relative_information_score: 57.7327, mean_absolute_error: 0.3043, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.6981, predictive_accuracy: 0.7, prior_entropy: 0.8485, recall: 0.7, relative_absolute_error: 0.7734, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.5051, root_relative_squared_error: 1.1466, scimark_benchmark: 934.3687,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.73, f_measure: 0.8049, kappa: 0.4849, kb_relative_information_score: 175.1826, mean_absolute_error: 0.1895, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.8028, predictive_accuracy: 0.8105, prior_entropy: 0.8485, recall: 0.8105, relative_absolute_error: 0.4816, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4353, root_relative_squared_error: 0.9881,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6046, f_measure: 0.7279, kappa: 0.2552, kb_relative_information_score: 125.8325, mean_absolute_error: 0.2368, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.7382, predictive_accuracy: 0.7632, prior_entropy: 0.8485, recall: 0.7632, relative_absolute_error: 0.602, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4867, root_relative_squared_error: 1.1048,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.6252, kb_relative_information_score: 98.4157, mean_absolute_error: 0.2632, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.5429, predictive_accuracy: 0.7368, prior_entropy: 0.8485, recall: 0.7368, relative_absolute_error: 0.6689, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.513, root_relative_squared_error: 1.1645, scimark_benchmark: 931.771,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.6252, kb_relative_information_score: 98.4157, mean_absolute_error: 0.2632, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.5429, predictive_accuracy: 0.7368, prior_entropy: 0.8485, recall: 0.7368, relative_absolute_error: 0.6689, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.513, root_relative_squared_error: 1.1645, scimark_benchmark: 944.1067,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.659, f_measure: 0.794, kappa: 0.4383, kb_relative_information_score: 105.9615, mean_absolute_error: 0.2823, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.8118, predictive_accuracy: 0.8158, prior_entropy: 0.8485, recall: 0.8158, relative_absolute_error: 0.7175, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.3971, root_relative_squared_error: 0.9014, scimark_benchmark: 934.695,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6696, f_measure: 0.7763, kappa: 0.3902, kb_relative_information_score: 56.86, mean_absolute_error: 0.3313, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.7899, predictive_accuracy: 0.8, prior_entropy: 0.8485, recall: 0.8, relative_absolute_error: 0.842, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4081, root_relative_squared_error: 0.9264, scimark_benchmark: 934.695,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6046, f_measure: 0.7279, kappa: 0.2552, kb_relative_information_score: 125.8325, mean_absolute_error: 0.2368, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.7382, predictive_accuracy: 0.7632, prior_entropy: 0.8485, recall: 0.7632, relative_absolute_error: 0.602, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4867, root_relative_squared_error: 1.1048,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6046, f_measure: 0.7279, kappa: 0.2552, kb_relative_information_score: 125.8325, mean_absolute_error: 0.2368, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.7382, predictive_accuracy: 0.7632, prior_entropy: 0.8485, recall: 0.7632, relative_absolute_error: 0.602, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4867, root_relative_squared_error: 1.1048,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.727, f_measure: 0.6688, kappa: 0.0944, kb_relative_information_score: 47.9247, mean_absolute_error: 0.3316, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.6852, predictive_accuracy: 0.7368, prior_entropy: 0.8485, recall: 0.7368, relative_absolute_error: 0.8429, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4121, root_relative_squared_error: 0.9355, scimark_benchmark: 938.9588, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6046, f_measure: 0.7279, kappa: 0.2552, kb_relative_information_score: 125.8325, mean_absolute_error: 0.2368, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.7382, predictive_accuracy: 0.7632, prior_entropy: 0.8485, recall: 0.7632, relative_absolute_error: 0.602, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4867, root_relative_squared_error: 1.1048,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6046, f_measure: 0.7279, kappa: 0.2552, kb_relative_information_score: 125.8325, mean_absolute_error: 0.2368, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.7382, predictive_accuracy: 0.7632, prior_entropy: 0.8485, recall: 0.7632, relative_absolute_error: 0.602, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4867, root_relative_squared_error: 1.1048,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6046, f_measure: 0.7279, kappa: 0.2552, kb_relative_information_score: 125.8325, mean_absolute_error: 0.2368, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.7382, predictive_accuracy: 0.7632, prior_entropy: 0.8485, recall: 0.7632, relative_absolute_error: 0.602, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4867, root_relative_squared_error: 1.1048,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6046, f_measure: 0.7279, kappa: 0.2552, kb_relative_information_score: 125.8325, mean_absolute_error: 0.2368, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.7382, predictive_accuracy: 0.7632, prior_entropy: 0.8485, recall: 0.7632, relative_absolute_error: 0.602, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4867, root_relative_squared_error: 1.1048,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6434, f_measure: 0.7895, kappa: 0.4373, kb_relative_information_score: 106.3418, mean_absolute_error: 0.2839, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.7883, predictive_accuracy: 0.8, prior_entropy: 0.8485, recall: 0.8, relative_absolute_error: 0.7217, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.3967, root_relative_squared_error: 0.9005, scimark_benchmark: 905.2959,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6046, f_measure: 0.7279, kappa: 0.2552, kb_relative_information_score: 125.8325, mean_absolute_error: 0.2368, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.7382, predictive_accuracy: 0.7632, prior_entropy: 0.8485, recall: 0.7632, relative_absolute_error: 0.602, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4867, root_relative_squared_error: 1.1048,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.6252, kb_relative_information_score: 98.4157, mean_absolute_error: 0.2632, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.5429, predictive_accuracy: 0.7368, prior_entropy: 0.8485, recall: 0.7368, relative_absolute_error: 0.6689, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.513, root_relative_squared_error: 1.1645, scimark_benchmark: 937.5117,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.6252, kb_relative_information_score: 98.4157, mean_absolute_error: 0.2632, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.5429, predictive_accuracy: 0.7368, prior_entropy: 0.8485, recall: 0.7368, relative_absolute_error: 0.6689, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.513, root_relative_squared_error: 1.1645, scimark_benchmark: 974.2014,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.646, f_measure: 0.794, kappa: 0.4383, kb_relative_information_score: 107.154, mean_absolute_error: 0.2842, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.8118, predictive_accuracy: 0.8158, prior_entropy: 0.8485, recall: 0.8158, relative_absolute_error: 0.7224, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.3967, root_relative_squared_error: 0.9006, scimark_benchmark: 932.438,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.659, f_measure: 0.794, kappa: 0.4383, kb_relative_information_score: 105.9615, mean_absolute_error: 0.2823, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.8118, predictive_accuracy: 0.8158, prior_entropy: 0.8485, recall: 0.8158, relative_absolute_error: 0.7175, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.3971, root_relative_squared_error: 0.9014, scimark_benchmark: 974.2014,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.659, f_measure: 0.794, kappa: 0.4383, kb_relative_information_score: 105.9615, mean_absolute_error: 0.2823, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.8118, predictive_accuracy: 0.8158, prior_entropy: 0.8485, recall: 0.8158, relative_absolute_error: 0.7175, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.3971, root_relative_squared_error: 0.9014, scimark_benchmark: 947.1781,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6848, f_measure: 0.7996, kappa: 0.4631, kb_relative_information_score: 80.8752, mean_absolute_error: 0.3003, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.8, predictive_accuracy: 0.8105, prior_entropy: 0.8485, recall: 0.8105, relative_absolute_error: 0.7634, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4027, root_relative_squared_error: 0.9142, scimark_benchmark: 974.2014, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5727, f_measure: 0.794, kappa: 0.4383, kb_relative_information_score: 121.1689, mean_absolute_error: 0.269, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.8118, predictive_accuracy: 0.8158, prior_entropy: 0.8485, recall: 0.8158, relative_absolute_error: 0.6836, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4004, root_relative_squared_error: 0.909, scimark_benchmark: 942.2392,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6046, f_measure: 0.7279, kappa: 0.2552, kb_relative_information_score: 125.8325, mean_absolute_error: 0.2368, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.7382, predictive_accuracy: 0.7632, prior_entropy: 0.8485, recall: 0.7632, relative_absolute_error: 0.602, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4867, root_relative_squared_error: 1.1048,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6133, f_measure: 0.7344, kappa: 0.3036, kb_relative_information_score: 65.144, mean_absolute_error: 0.3087, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.7306, predictive_accuracy: 0.7395, prior_entropy: 0.8485, recall: 0.7395, relative_absolute_error: 0.7847, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4348, root_relative_squared_error: 0.987, scimark_benchmark: 908.9569,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6463, f_measure: 0.699, kappa: 0.2214, kb_relative_information_score: 57.7327, mean_absolute_error: 0.3043, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.6981, predictive_accuracy: 0.7, prior_entropy: 0.8485, recall: 0.7, relative_absolute_error: 0.7734, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.5051, root_relative_squared_error: 1.1466, scimark_benchmark: 936.2574,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.6252, kb_relative_information_score: 98.4157, mean_absolute_error: 0.2632, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.5429, predictive_accuracy: 0.7368, prior_entropy: 0.8485, recall: 0.7368, relative_absolute_error: 0.6689, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.513, root_relative_squared_error: 1.1645, scimark_benchmark: 926.5462,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.646, f_measure: 0.794, kappa: 0.4383, kb_relative_information_score: 107.154, mean_absolute_error: 0.2842, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.8118, predictive_accuracy: 0.8158, prior_entropy: 0.8485, recall: 0.8158, relative_absolute_error: 0.7224, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.3967, root_relative_squared_error: 0.9006, scimark_benchmark: 938.1282,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.659, f_measure: 0.794, kappa: 0.4383, kb_relative_information_score: 105.9615, mean_absolute_error: 0.2823, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.8118, predictive_accuracy: 0.8158, prior_entropy: 0.8485, recall: 0.8158, relative_absolute_error: 0.7175, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.3971, root_relative_squared_error: 0.9014, scimark_benchmark: 930.404,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.659, f_measure: 0.794, kappa: 0.4383, kb_relative_information_score: 105.9615, mean_absolute_error: 0.2823, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.8118, predictive_accuracy: 0.8158, prior_entropy: 0.8485, recall: 0.8158, relative_absolute_error: 0.7175, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.3971, root_relative_squared_error: 0.9014, scimark_benchmark: 930.404,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.659, f_measure: 0.794, kappa: 0.4383, kb_relative_information_score: 105.9615, mean_absolute_error: 0.2823, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.8118, predictive_accuracy: 0.8158, prior_entropy: 0.8485, recall: 0.8158, relative_absolute_error: 0.7175, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.3971, root_relative_squared_error: 0.9014, scimark_benchmark: 933.3455,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6696, f_measure: 0.7763, kappa: 0.3902, kb_relative_information_score: 56.86, mean_absolute_error: 0.3313, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.7899, predictive_accuracy: 0.8, prior_entropy: 0.8485, recall: 0.8, relative_absolute_error: 0.842, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4081, root_relative_squared_error: 0.9264, scimark_benchmark: 903.2737, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.727, f_measure: 0.6688, kappa: 0.0944, kb_relative_information_score: 47.9247, mean_absolute_error: 0.3316, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.6852, predictive_accuracy: 0.7368, prior_entropy: 0.8485, recall: 0.7368, relative_absolute_error: 0.8429, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4121, root_relative_squared_error: 0.9355, scimark_benchmark: 930.404, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.659, f_measure: 0.794, kappa: 0.4383, kb_relative_information_score: 105.9615, mean_absolute_error: 0.2823, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.8118, predictive_accuracy: 0.8158, prior_entropy: 0.8485, recall: 0.8158, relative_absolute_error: 0.7175, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.3971, root_relative_squared_error: 0.9014, scimark_benchmark: 945.6228,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6434, f_measure: 0.7895, kappa: 0.4373, kb_relative_information_score: 106.3418, mean_absolute_error: 0.2839, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.7883, predictive_accuracy: 0.8, prior_entropy: 0.8485, recall: 0.8, relative_absolute_error: 0.7217, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.3967, root_relative_squared_error: 0.9005, scimark_benchmark: 730.6551, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6848, f_measure: 0.7996, kappa: 0.4631, kb_relative_information_score: 80.8752, mean_absolute_error: 0.3003, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.8, predictive_accuracy: 0.8105, prior_entropy: 0.8485, recall: 0.8105, relative_absolute_error: 0.7634, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4027, root_relative_squared_error: 0.9142, scimark_benchmark: 936.9595,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.659, f_measure: 0.794, kappa: 0.4383, kb_relative_information_score: 105.9615, mean_absolute_error: 0.2823, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.8118, predictive_accuracy: 0.8158, prior_entropy: 0.8485, recall: 0.8158, relative_absolute_error: 0.7175, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.3971, root_relative_squared_error: 0.9014, scimark_benchmark: 908.2231,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6133, f_measure: 0.7344, kappa: 0.3036, kb_relative_information_score: 65.144, mean_absolute_error: 0.3087, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.7306, predictive_accuracy: 0.7395, prior_entropy: 0.8485, recall: 0.7395, relative_absolute_error: 0.7847, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4348, root_relative_squared_error: 0.987, scimark_benchmark: 1339.6197, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.646, f_measure: 0.794, kappa: 0.4383, kb_relative_information_score: 107.154, mean_absolute_error: 0.2842, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.8118, predictive_accuracy: 0.8158, prior_entropy: 0.8485, recall: 0.8158, relative_absolute_error: 0.7224, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.3967, root_relative_squared_error: 0.9006, scimark_benchmark: 1338.5214,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.659, f_measure: 0.794, kappa: 0.4383, kb_relative_information_score: 105.9615, mean_absolute_error: 0.2823, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.8118, predictive_accuracy: 0.8158, prior_entropy: 0.8485, recall: 0.8158, relative_absolute_error: 0.7175, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.3971, root_relative_squared_error: 0.9014, scimark_benchmark: 930.5999,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.646, f_measure: 0.794, kappa: 0.4383, kb_relative_information_score: 107.154, mean_absolute_error: 0.2842, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.8118, predictive_accuracy: 0.8158, prior_entropy: 0.8485, recall: 0.8158, relative_absolute_error: 0.7224, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.3967, root_relative_squared_error: 0.9006, scimark_benchmark: 1350.2591,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.659, f_measure: 0.794, kappa: 0.4383, kb_relative_information_score: 105.9615, mean_absolute_error: 0.2823, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.8118, predictive_accuracy: 0.8158, prior_entropy: 0.8485, recall: 0.8158, relative_absolute_error: 0.7175, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.3971, root_relative_squared_error: 0.9014, scimark_benchmark: 1306.9281,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.659, f_measure: 0.794, kappa: 0.4383, kb_relative_information_score: 105.9615, mean_absolute_error: 0.2823, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.8118, predictive_accuracy: 0.8158, prior_entropy: 0.8485, recall: 0.8158, relative_absolute_error: 0.7175, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.3971, root_relative_squared_error: 0.9014, scimark_benchmark: 1317.5857,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.659, f_measure: 0.794, kappa: 0.4383, kb_relative_information_score: 105.9615, mean_absolute_error: 0.2823, mean_prior_absolute_error: 0.3934, number_of_instances: 380, precision: 0.8118, predictive_accuracy: 0.8158, prior_entropy: 0.8485, recall: 0.8158, relative_absolute_error: 0.7175, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.3971, root_relative_squared_error: 0.9014, scimark_benchmark: 1317.2327,

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