Task
Supervised Classification on heart-statlog

Supervised Classification on heart-statlog

Task 52 Supervised Classification heart-statlog 887 runs submitted
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  • basic mythbusting mythbusting_1 study_1 study_107 study_123 study_15 study_20 study_29 study_30 study_41 study_50 study_7 under100k under1m
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8983, f_measure: 0.8291, kappa: 0.6533, kb_relative_information_score: 152.0919, mean_absolute_error: 0.2265, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.8294, predictive_accuracy: 0.8296, prior_entropy: 0.9912, recall: 0.8296, relative_absolute_error: 0.4586, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.3548, root_relative_squared_error: 0.7141, scimark_benchmark: 930.5999, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.3968, kb_relative_information_score: -0.0044, mean_absolute_error: 0.4939, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.3086, predictive_accuracy: 0.5556, prior_entropy: 0.9912, recall: 0.5556, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.4969, root_relative_squared_error: 1, scimark_benchmark: 1321.6263,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7787, f_measure: 0.7636, kappa: 0.5199, kb_relative_information_score: 122.8335, mean_absolute_error: 0.2777, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.7684, predictive_accuracy: 0.7667, prior_entropy: 0.9912, recall: 0.7667, relative_absolute_error: 0.5623, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.4426, root_relative_squared_error: 0.8907, scimark_benchmark: 825.5282, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6925, f_measure: 0.7221, kappa: 0.437, kb_relative_information_score: 70.8179, mean_absolute_error: 0.3814, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.722, predictive_accuracy: 0.7222, prior_entropy: 0.9912, recall: 0.7222, relative_absolute_error: 0.7723, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.4501, root_relative_squared_error: 0.9059, scimark_benchmark: 912.5006,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8989, f_measure: 0.837, kappa: 0.67, kb_relative_information_score: 174.4226, mean_absolute_error: 0.1776, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.837, predictive_accuracy: 0.837, prior_entropy: 0.9912, recall: 0.837, relative_absolute_error: 0.3596, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.3661, root_relative_squared_error: 0.7368, scimark_benchmark: 1324.8395, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8905, f_measure: 0.8135, kappa: 0.6212, kb_relative_information_score: 102.63, mean_absolute_error: 0.3282, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.8155, predictive_accuracy: 0.8148, prior_entropy: 0.9912, recall: 0.8148, relative_absolute_error: 0.6645, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.3756, root_relative_squared_error: 0.7559, scimark_benchmark: 938.343, usercpu_time_millis: 80, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 70,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8702, f_measure: 0.7986, kappa: 0.5909, kb_relative_information_score: 101.1155, mean_absolute_error: 0.3292, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.8004, predictive_accuracy: 0.8, prior_entropy: 0.9912, recall: 0.8, relative_absolute_error: 0.6665, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.3836, root_relative_squared_error: 0.7721, scimark_benchmark: 1330.0694, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.804, f_measure: 0.809, kappa: 0.612, kb_relative_information_score: 139.3458, mean_absolute_error: 0.252, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.8135, predictive_accuracy: 0.8111, prior_entropy: 0.9912, recall: 0.8111, relative_absolute_error: 0.5103, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.4034, root_relative_squared_error: 0.8119, scimark_benchmark: 869.6028, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8732, f_measure: 0.7956, kappa: 0.5851, kb_relative_information_score: 149.4522, mean_absolute_error: 0.2245, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.7959, predictive_accuracy: 0.7963, prior_entropy: 0.9912, recall: 0.7963, relative_absolute_error: 0.4547, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.392, root_relative_squared_error: 0.7888, scimark_benchmark: 1325.2092, usercpu_time_millis: 100, usercpu_time_millis_training: 100,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8831, f_measure: 0.7998, kappa: 0.5943, kb_relative_information_score: 151.1689, mean_absolute_error: 0.2226, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.7997, predictive_accuracy: 0.8, prior_entropy: 0.9912, recall: 0.8, relative_absolute_error: 0.4508, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.3828, root_relative_squared_error: 0.7704, scimark_benchmark: 932.0242, usercpu_time_millis: 60, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8855, f_measure: 0.811, kappa: 0.6172, kb_relative_information_score: 150.4959, mean_absolute_error: 0.2255, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.811, predictive_accuracy: 0.8111, prior_entropy: 0.9912, recall: 0.8111, relative_absolute_error: 0.4565, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.3754, root_relative_squared_error: 0.7554, scimark_benchmark: 1304.9611, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8891, f_measure: 0.815, kappa: 0.6256, kb_relative_information_score: 151.1045, mean_absolute_error: 0.2253, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.8152, predictive_accuracy: 0.8148, prior_entropy: 0.9912, recall: 0.8148, relative_absolute_error: 0.4561, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.3682, root_relative_squared_error: 0.741, scimark_benchmark: 942.9518, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8894, f_measure: 0.8298, kappa: 0.6556, kb_relative_information_score: 148.462, mean_absolute_error: 0.2324, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.83, predictive_accuracy: 0.8296, prior_entropy: 0.9912, recall: 0.8296, relative_absolute_error: 0.4706, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.3634, root_relative_squared_error: 0.7313, scimark_benchmark: 1333.5799, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.848, f_measure: 0.7848, kappa: 0.5635, kb_relative_information_score: 134.0948, mean_absolute_error: 0.2537, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.7847, predictive_accuracy: 0.7852, prior_entropy: 0.9912, recall: 0.7852, relative_absolute_error: 0.5138, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.3995, root_relative_squared_error: 0.804, scimark_benchmark: 916.6405, usercpu_time_millis: 20, usercpu_time_millis_testing: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8144, f_measure: 0.7807, kappa: 0.5549, kb_relative_information_score: 130.1217, mean_absolute_error: 0.2599, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.781, predictive_accuracy: 0.7815, prior_entropy: 0.9912, recall: 0.7815, relative_absolute_error: 0.5263, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.4252, root_relative_squared_error: 0.8557, scimark_benchmark: 1324.8395, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8358, f_measure: 0.8402, kappa: 0.6756, kb_relative_information_score: 182.4355, mean_absolute_error: 0.1593, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.8407, predictive_accuracy: 0.8407, prior_entropy: 0.9912, recall: 0.8407, relative_absolute_error: 0.3225, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.3991, root_relative_squared_error: 0.8031, scimark_benchmark: 916.5955, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8183, f_measure: 0.8246, kappa: 0.6436, kb_relative_information_score: 174.2933, mean_absolute_error: 0.1741, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.8271, predictive_accuracy: 0.8259, prior_entropy: 0.9912, recall: 0.8259, relative_absolute_error: 0.3525, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.4172, root_relative_squared_error: 0.8396, scimark_benchmark: 1363.434, usercpu_time_millis: 40, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8292, f_measure: 0.8329, kappa: 0.6611, kb_relative_information_score: 178.3644, mean_absolute_error: 0.1667, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.8331, predictive_accuracy: 0.8333, prior_entropy: 0.9912, recall: 0.8333, relative_absolute_error: 0.3375, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.4082, root_relative_squared_error: 0.8216, scimark_benchmark: 894.7222, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8894, f_measure: 0.8143, kappa: 0.6231, kb_relative_information_score: 144.2824, mean_absolute_error: 0.2406, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.8145, predictive_accuracy: 0.8148, prior_entropy: 0.9912, recall: 0.8148, relative_absolute_error: 0.4871, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.3646, root_relative_squared_error: 0.7338, scimark_benchmark: 930.5999, usercpu_time_millis: 60, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7083, f_measure: 0.7083, kappa: 0.4129, kb_relative_information_score: 109.1555, mean_absolute_error: 0.2926, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.7114, predictive_accuracy: 0.7074, prior_entropy: 0.9912, recall: 0.7074, relative_absolute_error: 0.5924, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.5409, root_relative_squared_error: 1.0886, scimark_benchmark: 1386.5717, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8968, f_measure: 0.8217, kappa: 0.6382, kb_relative_information_score: 147.8359, mean_absolute_error: 0.2339, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.822, predictive_accuracy: 0.8222, prior_entropy: 0.9912, recall: 0.8222, relative_absolute_error: 0.4735, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.3591, root_relative_squared_error: 0.7228, scimark_benchmark: 1310.3951, usercpu_time_millis: 490, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 480,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.903, f_measure: 0.8221, kappa: 0.6394, kb_relative_information_score: 164.8697, mean_absolute_error: 0.1957, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.822, predictive_accuracy: 0.8222, prior_entropy: 0.9912, recall: 0.8222, relative_absolute_error: 0.3962, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.3669, root_relative_squared_error: 0.7384, scimark_benchmark: 1325.2092,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.871, f_measure: 0.8187, kappa: 0.6334, kb_relative_information_score: 142.7494, mean_absolute_error: 0.2426, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.8191, predictive_accuracy: 0.8185, prior_entropy: 0.9912, recall: 0.8185, relative_absolute_error: 0.4913, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.3849, root_relative_squared_error: 0.7746, scimark_benchmark: 1073.494, usercpu_time_millis: 190, usercpu_time_millis_training: 190,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8894, f_measure: 0.8104, kappa: 0.6153, kb_relative_information_score: 128.9436, mean_absolute_error: 0.273, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.8109, predictive_accuracy: 0.8111, prior_entropy: 0.9912, recall: 0.8111, relative_absolute_error: 0.5528, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.3625, root_relative_squared_error: 0.7295, scimark_benchmark: 1354.2491, usercpu_time_millis: 60, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7442, f_measure: 0.7479, kappa: 0.4891, kb_relative_information_score: 131.5466, mean_absolute_error: 0.2519, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.7478, predictive_accuracy: 0.7481, prior_entropy: 0.9912, recall: 0.7481, relative_absolute_error: 0.51, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.5018, root_relative_squared_error: 1.01, scimark_benchmark: 1313.5726,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8193, f_measure: 0.7486, kappa: 0.4894, kb_relative_information_score: 110.3302, mean_absolute_error: 0.303, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.753, predictive_accuracy: 0.7519, prior_entropy: 0.9912, recall: 0.7519, relative_absolute_error: 0.6134, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.4184, root_relative_squared_error: 0.842, scimark_benchmark: 1066.7184,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8113, f_measure: 0.7991, kappa: 0.5923, kb_relative_information_score: 128.0168, mean_absolute_error: 0.2747, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.7997, predictive_accuracy: 0.8, prior_entropy: 0.9912, recall: 0.8, relative_absolute_error: 0.5563, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.4049, root_relative_squared_error: 0.8149, scimark_benchmark: 1066.7184, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7717, f_measure: 0.7768, kappa: 0.547, kb_relative_information_score: 147.8311, mean_absolute_error: 0.2222, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.7773, predictive_accuracy: 0.7778, prior_entropy: 0.9912, recall: 0.7778, relative_absolute_error: 0.45, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.4714, root_relative_squared_error: 0.9487, scimark_benchmark: 1372.2145, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6375, f_measure: 0.6224, kappa: 0.2965, kb_relative_information_score: 92.8711, mean_absolute_error: 0.3222, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.7961, predictive_accuracy: 0.6778, prior_entropy: 0.9912, recall: 0.6778, relative_absolute_error: 0.6524, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.5676, root_relative_squared_error: 1.1424, scimark_benchmark: 1384.4418, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7602, f_measure: 0.7699, kappa: 0.5334, kb_relative_information_score: 136.7809, mean_absolute_error: 0.2465, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.7698, predictive_accuracy: 0.7704, prior_entropy: 0.9912, recall: 0.7704, relative_absolute_error: 0.4991, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.4625, root_relative_squared_error: 0.9307, scimark_benchmark: 1466.6185, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7183, f_measure: 0.7221, kappa: 0.437, kb_relative_information_score: 117.2977, mean_absolute_error: 0.2778, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.722, predictive_accuracy: 0.7222, prior_entropy: 0.9912, recall: 0.7222, relative_absolute_error: 0.5624, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.527, root_relative_squared_error: 1.0607, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8355, f_measure: 0.7928, kappa: 0.5807, kb_relative_information_score: 156.6721, mean_absolute_error: 0.2059, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.793, predictive_accuracy: 0.7926, prior_entropy: 0.9912, recall: 0.7926, relative_absolute_error: 0.4169, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.445, root_relative_squared_error: 0.8956, scimark_benchmark: 942.1229, usercpu_time_millis: 6060, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 6050,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.805, f_measure: 0.8102, kappa: 0.6146, kb_relative_information_score: 166.1511, mean_absolute_error: 0.1889, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.8111, predictive_accuracy: 0.8111, prior_entropy: 0.9912, recall: 0.8111, relative_absolute_error: 0.3825, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.4346, root_relative_squared_error: 0.8746, scimark_benchmark: 1028.5889,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.3968, kb_relative_information_score: -0.0044, mean_absolute_error: 0.4939, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.3086, predictive_accuracy: 0.5556, prior_entropy: 0.9912, recall: 0.5556, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.4969, root_relative_squared_error: 1, scimark_benchmark: 1028.5889,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7861, f_measure: 0.7843, kappa: 0.5621, kb_relative_information_score: 140.5144, mean_absolute_error: 0.2433, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.7848, predictive_accuracy: 0.7852, prior_entropy: 0.9912, recall: 0.7852, relative_absolute_error: 0.4927, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.4297, root_relative_squared_error: 0.8648, scimark_benchmark: 977.6382, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8643, f_measure: 0.8296, kappa: 0.655, kb_relative_information_score: 174.5465, mean_absolute_error: 0.1748, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.8296, predictive_accuracy: 0.8296, prior_entropy: 0.9912, recall: 0.8296, relative_absolute_error: 0.3539, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.401, root_relative_squared_error: 0.8071, scimark_benchmark: 942.6953, usercpu_time_millis: 40, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8514, f_measure: 0.8109, kappa: 0.6165, kb_relative_information_score: 152.097, mean_absolute_error: 0.2219, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.8108, predictive_accuracy: 0.8111, prior_entropy: 0.9912, recall: 0.8111, relative_absolute_error: 0.4492, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.3963, root_relative_squared_error: 0.7975, scimark_benchmark: 945.6434, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8534, f_measure: 0.8147, kappa: 0.6244, kb_relative_information_score: 153.4296, mean_absolute_error: 0.2202, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.8146, predictive_accuracy: 0.8148, prior_entropy: 0.9912, recall: 0.8148, relative_absolute_error: 0.4458, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.3871, root_relative_squared_error: 0.779, scimark_benchmark: 939.7623, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.856, build_cpu_time: 0.0314, build_memory: 704479152, f_measure: 0.8183, kappa: 0.6316, kb_relative_information_score: 154.718, mean_absolute_error: 0.2183, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.8182, predictive_accuracy: 0.8185, prior_entropy: 0.9912, recall: 0.8185, relative_absolute_error: 0.4421, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.3842, root_relative_squared_error: 0.7732, scimark_benchmark: 943.2074,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8534, build_cpu_time: 0.037, build_memory: 917988335.2, f_measure: 0.8147, kappa: 0.6244, kb_relative_information_score: 153.4296, mean_absolute_error: 0.2202, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.8146, predictive_accuracy: 0.8148, prior_entropy: 0.9912, recall: 0.8148, relative_absolute_error: 0.4458, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.3871, root_relative_squared_error: 0.779, scimark_benchmark: 937.9119,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8147, build_cpu_time: 2.3705, build_memory: 61938248.8, f_measure: 0.7295, kappa: 0.452, kb_relative_information_score: 123.1574, mean_absolute_error: 0.2683, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.7294, predictive_accuracy: 0.7296, prior_entropy: 0.9912, recall: 0.7296, relative_absolute_error: 0.5432, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.4589, root_relative_squared_error: 0.9235, scimark_benchmark: 872.1114,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8232, build_cpu_time: 6.5852, build_memory: 404601132, f_measure: 0.7467, kappa: 0.4857, kb_relative_information_score: 132.1545, mean_absolute_error: 0.2508, mean_prior_absolute_error: 0.4939, number_of_instances: 270, precision: 0.7474, predictive_accuracy: 0.7481, prior_entropy: 0.9912, recall: 0.7481, relative_absolute_error: 0.5079, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.4735, root_relative_squared_error: 0.9529, scimark_benchmark: 927.3354,

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