OpenML
Supervised Classification on cm1_req

Supervised Classification on cm1_req

Task 3906 Supervised Classification cm1_req 494 runs submitted
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  • study_1 study_107 study_123 study_41 under100k under1m
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3772, f_measure: 0.6771, kb_relative_information_score: -5.6895, mean_absolute_error: 0.3574, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.6011, predictive_accuracy: 0.7753, prior_entropy: 0.7794, recall: 0.7753, relative_absolute_error: 1.016, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.4252, root_relative_squared_error: 1.0186, scimark_benchmark: 1887.4343,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4935, f_measure: 0.6771, kb_relative_information_score: 0.7043, mean_absolute_error: 0.3485, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.6011, predictive_accuracy: 0.7753, prior_entropy: 0.7794, recall: 0.7753, relative_absolute_error: 0.9906, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.4174, root_relative_squared_error: 0.9999, scimark_benchmark: 1806.5905, usercpu_time_millis: 15.6001, usercpu_time_millis_training: 15.6001,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4935, f_measure: 0.6771, kb_relative_information_score: 0.7043, mean_absolute_error: 0.3485, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.6011, predictive_accuracy: 0.7753, prior_entropy: 0.7794, recall: 0.7753, relative_absolute_error: 0.9906, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.4174, root_relative_squared_error: 0.9999, scimark_benchmark: 1806.5905,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3736, f_measure: 0.6771, kb_relative_information_score: -4.5608, mean_absolute_error: 0.3534, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.6011, predictive_accuracy: 0.7753, prior_entropy: 0.7794, recall: 0.7753, relative_absolute_error: 1.0046, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.4264, root_relative_squared_error: 1.0215, scimark_benchmark: 1806.5905,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5185, f_measure: 0.7712, kappa: 0.2873, kb_relative_information_score: 0.2984, mean_absolute_error: 0.326, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.794, predictive_accuracy: 0.809, prior_entropy: 0.7794, recall: 0.809, relative_absolute_error: 0.9267, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.4252, root_relative_squared_error: 1.0185, scimark_benchmark: 1806.5905, usercpu_time_millis: 15.6001, usercpu_time_millis_training: 15.6001,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3504, f_measure: 0.6771, kb_relative_information_score: -4.3609, mean_absolute_error: 0.3548, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.6011, predictive_accuracy: 0.7753, prior_entropy: 0.7794, recall: 0.7753, relative_absolute_error: 1.0086, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.4264, root_relative_squared_error: 1.0214, scimark_benchmark: 1806.5905,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5159, f_measure: 0.7097, kappa: 0.0985, kb_relative_information_score: 2.6814, mean_absolute_error: 0.3204, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.6968, predictive_accuracy: 0.7528, prior_entropy: 0.7794, recall: 0.7528, relative_absolute_error: 0.9109, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.4658, root_relative_squared_error: 1.1158, scimark_benchmark: 1806.5905,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3772, f_measure: 0.6771, kb_relative_information_score: -5.6895, mean_absolute_error: 0.3574, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.6011, predictive_accuracy: 0.7753, prior_entropy: 0.7794, recall: 0.7753, relative_absolute_error: 1.016, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.4252, root_relative_squared_error: 1.0186, scimark_benchmark: 1877.5305,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4649, f_measure: 0.6869, kappa: 0.0405, kb_relative_information_score: -18.6518, mean_absolute_error: 0.3795, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.6676, predictive_accuracy: 0.7191, prior_entropy: 0.7794, recall: 0.7191, relative_absolute_error: 1.0788, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.4834, root_relative_squared_error: 1.158, scimark_benchmark: 1850.8887,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4935, f_measure: 0.6771, kb_relative_information_score: -0.32, mean_absolute_error: 0.3522, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.6011, predictive_accuracy: 0.7753, prior_entropy: 0.7794, recall: 0.7753, relative_absolute_error: 1.0011, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.4175, root_relative_squared_error: 1.0001, scimark_benchmark: 1850.8887,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4935, f_measure: 0.6771, kb_relative_information_score: 0.7043, mean_absolute_error: 0.3485, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.6011, predictive_accuracy: 0.7753, prior_entropy: 0.7794, recall: 0.7753, relative_absolute_error: 0.9906, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.4174, root_relative_squared_error: 0.9999, scimark_benchmark: 906.0979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5141, f_measure: 0.7174, kappa: 0.1196, kb_relative_information_score: -21.507, mean_absolute_error: 0.3764, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.7109, predictive_accuracy: 0.764, prior_entropy: 0.7794, recall: 0.764, relative_absolute_error: 1.0699, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.4305, root_relative_squared_error: 1.0313, scimark_benchmark: 972.587,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.55, f_measure: 0.7621, kappa: 0.2708, kb_relative_information_score: 6.3583, mean_absolute_error: 0.3119, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.7587, predictive_accuracy: 0.7865, prior_entropy: 0.7794, recall: 0.7865, relative_absolute_error: 0.8867, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.4179, root_relative_squared_error: 1.0012, scimark_benchmark: 851.2074, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.6771, kb_relative_information_score: 23.7981, mean_absolute_error: 0.2247, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.6011, predictive_accuracy: 0.7753, prior_entropy: 0.7794, recall: 0.7753, relative_absolute_error: 0.6388, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.474, root_relative_squared_error: 1.1356, scimark_benchmark: 942.2392,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.6771, kb_relative_information_score: 23.7981, mean_absolute_error: 0.2247, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.6011, predictive_accuracy: 0.7753, prior_entropy: 0.7794, recall: 0.7753, relative_absolute_error: 0.6388, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.474, root_relative_squared_error: 1.1356, scimark_benchmark: 916.0735, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3547, f_measure: 0.6771, kb_relative_information_score: -5.067, mean_absolute_error: 0.3562, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.6011, predictive_accuracy: 0.7753, prior_entropy: 0.7794, recall: 0.7753, relative_absolute_error: 1.0127, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.426, root_relative_squared_error: 1.0205, scimark_benchmark: 941.6675,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3547, f_measure: 0.6771, kb_relative_information_score: -5.067, mean_absolute_error: 0.3562, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.6011, predictive_accuracy: 0.7753, prior_entropy: 0.7794, recall: 0.7753, relative_absolute_error: 1.0127, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.426, root_relative_squared_error: 1.0205, scimark_benchmark: 938.191,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5351, f_measure: 0.6771, kb_relative_information_score: -1.7902, mean_absolute_error: 0.3447, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.6011, predictive_accuracy: 0.7753, prior_entropy: 0.7794, recall: 0.7753, relative_absolute_error: 0.98, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.416, root_relative_squared_error: 0.9966, scimark_benchmark: 941.6675,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5467, f_measure: 0.7251, kappa: 0.1418, kb_relative_information_score: 0.7486, mean_absolute_error: 0.3315, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.7288, predictive_accuracy: 0.7753, prior_entropy: 0.7794, recall: 0.7753, relative_absolute_error: 0.9425, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.4285, root_relative_squared_error: 1.0265, scimark_benchmark: 934.695,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3547, f_measure: 0.6771, kb_relative_information_score: -5.067, mean_absolute_error: 0.3562, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.6011, predictive_accuracy: 0.7753, prior_entropy: 0.7794, recall: 0.7753, relative_absolute_error: 1.0127, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.426, root_relative_squared_error: 1.0205, scimark_benchmark: 905.2959,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3772, f_measure: 0.6771, kb_relative_information_score: -5.6895, mean_absolute_error: 0.3574, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.6011, predictive_accuracy: 0.7753, prior_entropy: 0.7794, recall: 0.7753, relative_absolute_error: 1.016, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.4252, root_relative_squared_error: 1.0186, scimark_benchmark: 927.2917, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.6771, kb_relative_information_score: 23.7981, mean_absolute_error: 0.2247, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.6011, predictive_accuracy: 0.7753, prior_entropy: 0.7794, recall: 0.7753, relative_absolute_error: 0.6388, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.474, root_relative_squared_error: 1.1356, scimark_benchmark: 932.438,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3547, f_measure: 0.6771, kb_relative_information_score: -5.067, mean_absolute_error: 0.3562, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.6011, predictive_accuracy: 0.7753, prior_entropy: 0.7794, recall: 0.7753, relative_absolute_error: 1.0127, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.426, root_relative_squared_error: 1.0205, scimark_benchmark: 974.2014,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3547, f_measure: 0.6771, kb_relative_information_score: -5.067, mean_absolute_error: 0.3562, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.6011, predictive_accuracy: 0.7753, prior_entropy: 0.7794, recall: 0.7753, relative_absolute_error: 1.0127, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.426, root_relative_squared_error: 1.0205, scimark_benchmark: 974.2014,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3772, f_measure: 0.6771, kb_relative_information_score: -5.6895, mean_absolute_error: 0.3574, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.6011, predictive_accuracy: 0.7753, prior_entropy: 0.7794, recall: 0.7753, relative_absolute_error: 1.016, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.4252, root_relative_squared_error: 1.0186, scimark_benchmark: 938.5498, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5185, f_measure: 0.7712, kappa: 0.2873, kb_relative_information_score: 0.2984, mean_absolute_error: 0.326, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.794, predictive_accuracy: 0.809, prior_entropy: 0.7794, recall: 0.809, relative_absolute_error: 0.9267, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.4252, root_relative_squared_error: 1.0185, scimark_benchmark: 943.1009, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4935, f_measure: 0.6771, kb_relative_information_score: 0.7043, mean_absolute_error: 0.3485, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.6011, predictive_accuracy: 0.7753, prior_entropy: 0.7794, recall: 0.7753, relative_absolute_error: 0.9906, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.4174, root_relative_squared_error: 0.9999, scimark_benchmark: 942.2392,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5141, f_measure: 0.7174, kappa: 0.1196, kb_relative_information_score: -21.507, mean_absolute_error: 0.3764, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.7109, predictive_accuracy: 0.764, prior_entropy: 0.7794, recall: 0.764, relative_absolute_error: 1.0699, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.4305, root_relative_squared_error: 1.0313, scimark_benchmark: 901.6243,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.6771, kb_relative_information_score: 23.7981, mean_absolute_error: 0.2247, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.6011, predictive_accuracy: 0.7753, prior_entropy: 0.7794, recall: 0.7753, relative_absolute_error: 0.6388, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.474, root_relative_squared_error: 1.1356, scimark_benchmark: 908.9569,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3616, f_measure: 0.6771, kb_relative_information_score: -5.0095, mean_absolute_error: 0.356, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.6011, predictive_accuracy: 0.7753, prior_entropy: 0.7794, recall: 0.7753, relative_absolute_error: 1.0121, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.4257, root_relative_squared_error: 1.0199, scimark_benchmark: 938.1282,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3547, f_measure: 0.6771, kb_relative_information_score: -5.067, mean_absolute_error: 0.3562, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.6011, predictive_accuracy: 0.7753, prior_entropy: 0.7794, recall: 0.7753, relative_absolute_error: 1.0127, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.426, root_relative_squared_error: 1.0205, scimark_benchmark: 938.1282,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3547, f_measure: 0.6771, kb_relative_information_score: -5.067, mean_absolute_error: 0.3562, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.6011, predictive_accuracy: 0.7753, prior_entropy: 0.7794, recall: 0.7753, relative_absolute_error: 1.0127, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.426, root_relative_squared_error: 1.0205, scimark_benchmark: 903.2737,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3547, f_measure: 0.6771, kb_relative_information_score: -5.067, mean_absolute_error: 0.3562, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.6011, predictive_accuracy: 0.7753, prior_entropy: 0.7794, recall: 0.7753, relative_absolute_error: 1.0127, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.426, root_relative_squared_error: 1.0205, scimark_benchmark: 933.3455,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5351, f_measure: 0.6771, kb_relative_information_score: -1.7902, mean_absolute_error: 0.3447, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.6011, predictive_accuracy: 0.7753, prior_entropy: 0.7794, recall: 0.7753, relative_absolute_error: 0.98, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.416, root_relative_squared_error: 0.9966, scimark_benchmark: 941.4991,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5467, f_measure: 0.7251, kappa: 0.1418, kb_relative_information_score: 0.7486, mean_absolute_error: 0.3315, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.7288, predictive_accuracy: 0.7753, prior_entropy: 0.7794, recall: 0.7753, relative_absolute_error: 0.9425, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.4285, root_relative_squared_error: 1.0265, scimark_benchmark: 903.2737, usercpu_time_millis: 70, usercpu_time_millis_training: 70,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3547, f_measure: 0.6771, kb_relative_information_score: -5.067, mean_absolute_error: 0.3562, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.6011, predictive_accuracy: 0.7753, prior_entropy: 0.7794, recall: 0.7753, relative_absolute_error: 1.0127, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.426, root_relative_squared_error: 1.0205, scimark_benchmark: 945.6228,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3772, f_measure: 0.6771, kb_relative_information_score: -5.6895, mean_absolute_error: 0.3574, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.6011, predictive_accuracy: 0.7753, prior_entropy: 0.7794, recall: 0.7753, relative_absolute_error: 1.016, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.4252, root_relative_squared_error: 1.0186, scimark_benchmark: 941.3057, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5185, f_measure: 0.7712, kappa: 0.2873, kb_relative_information_score: 0.2984, mean_absolute_error: 0.326, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.794, predictive_accuracy: 0.809, prior_entropy: 0.7794, recall: 0.809, relative_absolute_error: 0.9267, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.4252, root_relative_squared_error: 1.0185, scimark_benchmark: 1051.249, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5612, f_measure: 0.7193, kappa: 0.1225, kb_relative_information_score: 1.9003, mean_absolute_error: 0.3358, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.7628, predictive_accuracy: 0.7865, prior_entropy: 0.7794, recall: 0.7865, relative_absolute_error: 0.9545, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.4097, root_relative_squared_error: 0.9814, scimark_benchmark: 935.5664, usercpu_time_millis: 460, usercpu_time_millis_testing: 200, usercpu_time_millis_training: 260,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5793, f_measure: 0.7193, kappa: 0.1225, kb_relative_information_score: 2.3058, mean_absolute_error: 0.3342, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.7628, predictive_accuracy: 0.7865, prior_entropy: 0.7794, recall: 0.7865, relative_absolute_error: 0.9501, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.4086, root_relative_squared_error: 0.9787, scimark_benchmark: 904.5548, usercpu_time_millis: 160, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 120,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4935, f_measure: 0.6771, kb_relative_information_score: 0.7043, mean_absolute_error: 0.3485, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.6011, predictive_accuracy: 0.7753, prior_entropy: 0.7794, recall: 0.7753, relative_absolute_error: 0.9906, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.4174, root_relative_squared_error: 0.9999, scimark_benchmark: 1322.3407,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3547, f_measure: 0.6771, kb_relative_information_score: -5.067, mean_absolute_error: 0.3562, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.6011, predictive_accuracy: 0.7753, prior_entropy: 0.7794, recall: 0.7753, relative_absolute_error: 1.0127, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.426, root_relative_squared_error: 1.0205, scimark_benchmark: 1340.9749,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5467, f_measure: 0.7251, kappa: 0.1418, kb_relative_information_score: 0.7486, mean_absolute_error: 0.3315, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.7288, predictive_accuracy: 0.7753, prior_entropy: 0.7794, recall: 0.7753, relative_absolute_error: 0.9425, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.4285, root_relative_squared_error: 1.0265, scimark_benchmark: 1340.5125, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3616, f_measure: 0.6771, kb_relative_information_score: -5.0095, mean_absolute_error: 0.356, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.6011, predictive_accuracy: 0.7753, prior_entropy: 0.7794, recall: 0.7753, relative_absolute_error: 1.0121, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.4257, root_relative_squared_error: 1.0199, scimark_benchmark: 1335.6555,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4935, f_measure: 0.6771, kb_relative_information_score: 0.7043, mean_absolute_error: 0.3485, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.6011, predictive_accuracy: 0.7753, prior_entropy: 0.7794, recall: 0.7753, relative_absolute_error: 0.9906, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.4174, root_relative_squared_error: 0.9999, scimark_benchmark: 1310.3168,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3616, f_measure: 0.6771, kb_relative_information_score: -5.0095, mean_absolute_error: 0.356, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.6011, predictive_accuracy: 0.7753, prior_entropy: 0.7794, recall: 0.7753, relative_absolute_error: 1.0121, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.4257, root_relative_squared_error: 1.0199, scimark_benchmark: 1333.6736,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3547, f_measure: 0.6771, kb_relative_information_score: -5.067, mean_absolute_error: 0.3562, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.6011, predictive_accuracy: 0.7753, prior_entropy: 0.7794, recall: 0.7753, relative_absolute_error: 1.0127, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.426, root_relative_squared_error: 1.0205, scimark_benchmark: 1321.8321,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3547, f_measure: 0.6771, kb_relative_information_score: -5.067, mean_absolute_error: 0.3562, mean_prior_absolute_error: 0.3518, number_of_instances: 89, precision: 0.6011, predictive_accuracy: 0.7753, prior_entropy: 0.7794, recall: 0.7753, relative_absolute_error: 1.0127, root_mean_prior_squared_error: 0.4174, root_mean_squared_error: 0.426, root_relative_squared_error: 1.0205, scimark_benchmark: 1337.9552,

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