Task
Supervised Classification on ar5

Supervised Classification on ar5

Task 3912 Supervised Classification ar5 508 runs submitted
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  • mythbusting_1 study_1 study_107 study_123 study_15 study_20 study_41 under100k under1m
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8482, f_measure: 0.8436, kappa: 0.5909, kb_relative_information_score: 5.2287, mean_absolute_error: 0.2881, mean_prior_absolute_error: 0.3538, number_of_instances: 36, precision: 0.875, predictive_accuracy: 0.8333, prior_entropy: 0.7897, recall: 0.8333, relative_absolute_error: 0.8143, root_mean_prior_squared_error: 0.416, root_mean_squared_error: 0.3906, root_relative_squared_error: 0.939, scimark_benchmark: 1321.6263,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3661, f_measure: 0.6806, kb_relative_information_score: -0.8176, mean_absolute_error: 0.3562, mean_prior_absolute_error: 0.3538, number_of_instances: 36, precision: 0.6049, predictive_accuracy: 0.7778, prior_entropy: 0.7897, recall: 0.7778, relative_absolute_error: 1.0068, root_mean_prior_squared_error: 0.416, root_mean_squared_error: 0.4184, root_relative_squared_error: 1.0057, scimark_benchmark: 926.6704,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8772, f_measure: 0.7657, kappa: 0.2941, kb_relative_information_score: 4.1366, mean_absolute_error: 0.3009, mean_prior_absolute_error: 0.3538, number_of_instances: 36, precision: 0.7593, predictive_accuracy: 0.7778, prior_entropy: 0.7897, recall: 0.7778, relative_absolute_error: 0.8504, root_mean_prior_squared_error: 0.416, root_mean_squared_error: 0.3532, root_relative_squared_error: 0.8492, scimark_benchmark: 916.6405,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.817, f_measure: 0.8395, kappa: 0.5574, kb_relative_information_score: 16.1258, mean_absolute_error: 0.1667, mean_prior_absolute_error: 0.3538, number_of_instances: 36, precision: 0.8513, predictive_accuracy: 0.8333, prior_entropy: 0.7897, recall: 0.8333, relative_absolute_error: 0.471, root_mean_prior_squared_error: 0.416, root_mean_squared_error: 0.4082, root_relative_squared_error: 0.9813, scimark_benchmark: 1324.8395,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8371, f_measure: 0.8829, kappa: 0.6471, kb_relative_information_score: 20.3657, mean_absolute_error: 0.129, mean_prior_absolute_error: 0.3538, number_of_instances: 36, precision: 0.8852, predictive_accuracy: 0.8889, prior_entropy: 0.7897, recall: 0.8889, relative_absolute_error: 0.3645, root_mean_prior_squared_error: 0.416, root_mean_squared_error: 0.3222, root_relative_squared_error: 0.7744, scimark_benchmark: 1368.9272,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7612, f_measure: 0.8008, kappa: 0.4112, kb_relative_information_score: 13.8683, mean_absolute_error: 0.1839, mean_prior_absolute_error: 0.3538, number_of_instances: 36, precision: 0.7975, predictive_accuracy: 0.8056, prior_entropy: 0.7897, recall: 0.8056, relative_absolute_error: 0.5199, root_mean_prior_squared_error: 0.416, root_mean_squared_error: 0.4212, root_relative_squared_error: 1.0125, scimark_benchmark: 1336.2976, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8214, f_measure: 0.8243, kappa: 0.4706, kb_relative_information_score: 10.982, mean_absolute_error: 0.241, mean_prior_absolute_error: 0.3538, number_of_instances: 36, precision: 0.8222, predictive_accuracy: 0.8333, prior_entropy: 0.7897, recall: 0.8333, relative_absolute_error: 0.6813, root_mean_prior_squared_error: 0.416, root_mean_squared_error: 0.3377, root_relative_squared_error: 0.8118, scimark_benchmark: 918.6005, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8304, f_measure: 0.8577, kappa: 0.5794, kb_relative_information_score: 10.671, mean_absolute_error: 0.2443, mean_prior_absolute_error: 0.3538, number_of_instances: 36, precision: 0.856, predictive_accuracy: 0.8611, prior_entropy: 0.7897, recall: 0.8611, relative_absolute_error: 0.6905, root_mean_prior_squared_error: 0.416, root_mean_squared_error: 0.339, root_relative_squared_error: 0.815, scimark_benchmark: 929.0363, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8504, f_measure: 0.8829, kappa: 0.6471, kb_relative_information_score: 9.433, mean_absolute_error: 0.2556, mean_prior_absolute_error: 0.3538, number_of_instances: 36, precision: 0.8852, predictive_accuracy: 0.8889, prior_entropy: 0.7897, recall: 0.8889, relative_absolute_error: 0.7223, root_mean_prior_squared_error: 0.416, root_mean_squared_error: 0.3544, root_relative_squared_error: 0.852, scimark_benchmark: 1331.6907,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8504, f_measure: 0.8333, kappa: 0.5179, kb_relative_information_score: 9.281, mean_absolute_error: 0.2587, mean_prior_absolute_error: 0.3538, number_of_instances: 36, precision: 0.8333, predictive_accuracy: 0.8333, prior_entropy: 0.7897, recall: 0.8333, relative_absolute_error: 0.7312, root_mean_prior_squared_error: 0.416, root_mean_squared_error: 0.3523, root_relative_squared_error: 0.8469, scimark_benchmark: 1307.3269,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7165, f_measure: 0.8154, kappa: 0.5039, kb_relative_information_score: 11.574, mean_absolute_error: 0.2159, mean_prior_absolute_error: 0.3538, number_of_instances: 36, precision: 0.8368, predictive_accuracy: 0.8056, prior_entropy: 0.7897, recall: 0.8056, relative_absolute_error: 0.6102, root_mean_prior_squared_error: 0.416, root_mean_squared_error: 0.4076, root_relative_squared_error: 0.9799, scimark_benchmark: 918.6005,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8125, f_measure: 0.8333, kappa: 0.5179, kb_relative_information_score: 16.2007, mean_absolute_error: 0.1655, mean_prior_absolute_error: 0.3538, number_of_instances: 36, precision: 0.8333, predictive_accuracy: 0.8333, prior_entropy: 0.7897, recall: 0.8333, relative_absolute_error: 0.4679, root_mean_prior_squared_error: 0.416, root_mean_squared_error: 0.4052, root_relative_squared_error: 0.9741, scimark_benchmark: 1333.5799, usercpu_time_millis: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7589, f_measure: 0.8008, kappa: 0.4112, kb_relative_information_score: 12.4846, mean_absolute_error: 0.1992, mean_prior_absolute_error: 0.3538, number_of_instances: 36, precision: 0.7975, predictive_accuracy: 0.8056, prior_entropy: 0.7897, recall: 0.8056, relative_absolute_error: 0.563, root_mean_prior_squared_error: 0.416, root_mean_squared_error: 0.4374, root_relative_squared_error: 1.0515, scimark_benchmark: 932.0242, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8661, f_measure: 0.8008, kappa: 0.4112, kb_relative_information_score: 13.2378, mean_absolute_error: 0.191, mean_prior_absolute_error: 0.3538, number_of_instances: 36, precision: 0.7975, predictive_accuracy: 0.8056, prior_entropy: 0.7897, recall: 0.8056, relative_absolute_error: 0.5397, root_mean_prior_squared_error: 0.416, root_mean_squared_error: 0.4328, root_relative_squared_error: 1.0404, scimark_benchmark: 915.6729, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.817, f_measure: 0.8008, kappa: 0.4112, kb_relative_information_score: 13.7606, mean_absolute_error: 0.1835, mean_prior_absolute_error: 0.3538, number_of_instances: 36, precision: 0.7975, predictive_accuracy: 0.8056, prior_entropy: 0.7897, recall: 0.8056, relative_absolute_error: 0.5185, root_mean_prior_squared_error: 0.416, root_mean_squared_error: 0.4004, root_relative_squared_error: 0.9626, scimark_benchmark: 942.9518, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8147, f_measure: 0.8243, kappa: 0.4706, kb_relative_information_score: 17.7437, mean_absolute_error: 0.1566, mean_prior_absolute_error: 0.3538, number_of_instances: 36, precision: 0.8222, predictive_accuracy: 0.8333, prior_entropy: 0.7897, recall: 0.8333, relative_absolute_error: 0.4425, root_mean_prior_squared_error: 0.416, root_mean_squared_error: 0.346, root_relative_squared_error: 0.8318, scimark_benchmark: 1318.1432,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8772, f_measure: 0.8889, kappa: 0.6786, kb_relative_information_score: 13.5596, mean_absolute_error: 0.2092, mean_prior_absolute_error: 0.3538, number_of_instances: 36, precision: 0.8889, predictive_accuracy: 0.8889, prior_entropy: 0.7897, recall: 0.8889, relative_absolute_error: 0.5912, root_mean_prior_squared_error: 0.416, root_mean_squared_error: 0.3181, root_relative_squared_error: 0.7646, scimark_benchmark: 924.3698,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8839, f_measure: 0.8829, kappa: 0.6471, kb_relative_information_score: 12.9547, mean_absolute_error: 0.2006, mean_prior_absolute_error: 0.3538, number_of_instances: 36, precision: 0.8852, predictive_accuracy: 0.8889, prior_entropy: 0.7897, recall: 0.8889, relative_absolute_error: 0.567, root_mean_prior_squared_error: 0.416, root_mean_squared_error: 0.3189, root_relative_squared_error: 0.7667, scimark_benchmark: 929.0363,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8214, f_measure: 0.8639, kappa: 0.6154, kb_relative_information_score: 19.2501, mean_absolute_error: 0.1389, mean_prior_absolute_error: 0.3538, number_of_instances: 36, precision: 0.8683, predictive_accuracy: 0.8611, prior_entropy: 0.7897, recall: 0.8611, relative_absolute_error: 0.3926, root_mean_prior_squared_error: 0.416, root_mean_squared_error: 0.3727, root_relative_squared_error: 0.8959, scimark_benchmark: 937.6212, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.6806, kb_relative_information_score: 9.8752, mean_absolute_error: 0.2222, mean_prior_absolute_error: 0.3538, number_of_instances: 36, precision: 0.6049, predictive_accuracy: 0.7778, prior_entropy: 0.7897, recall: 0.7778, relative_absolute_error: 0.6281, root_mean_prior_squared_error: 0.416, root_mean_squared_error: 0.4714, root_relative_squared_error: 1.1332, scimark_benchmark: 1034.1273,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7768, f_measure: 0.8577, kappa: 0.5794, kb_relative_information_score: 19.2501, mean_absolute_error: 0.1389, mean_prior_absolute_error: 0.3538, number_of_instances: 36, precision: 0.856, predictive_accuracy: 0.8611, prior_entropy: 0.7897, recall: 0.8611, relative_absolute_error: 0.3926, root_mean_prior_squared_error: 0.416, root_mean_squared_error: 0.3727, root_relative_squared_error: 0.8959, scimark_benchmark: 1333.5799,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8839, f_measure: 0.8577, kappa: 0.5794, kb_relative_information_score: 7.689, mean_absolute_error: 0.2695, mean_prior_absolute_error: 0.3538, number_of_instances: 36, precision: 0.856, predictive_accuracy: 0.8611, prior_entropy: 0.7897, recall: 0.8611, relative_absolute_error: 0.7618, root_mean_prior_squared_error: 0.416, root_mean_squared_error: 0.366, root_relative_squared_error: 0.8798, scimark_benchmark: 939.449,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5893, f_measure: 0.7481, kappa: 0.2174, kb_relative_information_score: 9.8752, mean_absolute_error: 0.2222, mean_prior_absolute_error: 0.3538, number_of_instances: 36, precision: 0.7431, predictive_accuracy: 0.7778, prior_entropy: 0.7897, recall: 0.7778, relative_absolute_error: 0.6281, root_mean_prior_squared_error: 0.416, root_mean_squared_error: 0.4714, root_relative_squared_error: 1.1332, scimark_benchmark: 942.6843, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8616, f_measure: 0.8577, kappa: 0.5794, kb_relative_information_score: 14.5209, mean_absolute_error: 0.1974, mean_prior_absolute_error: 0.3538, number_of_instances: 36, precision: 0.856, predictive_accuracy: 0.8611, prior_entropy: 0.7897, recall: 0.8611, relative_absolute_error: 0.5579, root_mean_prior_squared_error: 0.416, root_mean_squared_error: 0.3331, root_relative_squared_error: 0.8006, scimark_benchmark: 939.449, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.6806, kb_relative_information_score: 9.8752, mean_absolute_error: 0.2222, mean_prior_absolute_error: 0.3538, number_of_instances: 36, precision: 0.6049, predictive_accuracy: 0.7778, prior_entropy: 0.7897, recall: 0.7778, relative_absolute_error: 0.6281, root_mean_prior_squared_error: 0.416, root_mean_squared_error: 0.4714, root_relative_squared_error: 1.1332, scimark_benchmark: 1331.6907,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8527, f_measure: 0.8681, kappa: 0.6457, kb_relative_information_score: 18.9573, mean_absolute_error: 0.143, mean_prior_absolute_error: 0.3538, number_of_instances: 36, precision: 0.8881, predictive_accuracy: 0.8611, prior_entropy: 0.7897, recall: 0.8611, relative_absolute_error: 0.4042, root_mean_prior_squared_error: 0.416, root_mean_squared_error: 0.3735, root_relative_squared_error: 0.8977, scimark_benchmark: 1325.2092,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9018, f_measure: 0.8333, kappa: 0.5179, kb_relative_information_score: 17.2594, mean_absolute_error: 0.1579, mean_prior_absolute_error: 0.3538, number_of_instances: 36, precision: 0.8333, predictive_accuracy: 0.8333, prior_entropy: 0.7897, recall: 0.8333, relative_absolute_error: 0.4462, root_mean_prior_squared_error: 0.416, root_mean_squared_error: 0.3629, root_relative_squared_error: 0.8725, scimark_benchmark: 1331.6907, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9018, f_measure: 0.8333, kappa: 0.5179, kb_relative_information_score: 17.4436, mean_absolute_error: 0.1573, mean_prior_absolute_error: 0.3538, number_of_instances: 36, precision: 0.8333, predictive_accuracy: 0.8333, prior_entropy: 0.7897, recall: 0.8333, relative_absolute_error: 0.4445, root_mean_prior_squared_error: 0.416, root_mean_squared_error: 0.3663, root_relative_squared_error: 0.8804, scimark_benchmark: 909.3537, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7768, f_measure: 0.8639, kappa: 0.6154, kb_relative_information_score: 14.5226, mean_absolute_error: 0.205, mean_prior_absolute_error: 0.3538, number_of_instances: 36, precision: 0.8683, predictive_accuracy: 0.8611, prior_entropy: 0.7897, recall: 0.8611, relative_absolute_error: 0.5793, root_mean_prior_squared_error: 0.416, root_mean_squared_error: 0.3617, root_relative_squared_error: 0.8694, scimark_benchmark: 940.7131, usercpu_time_millis: 110, usercpu_time_millis_training: 110,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8616, f_measure: 0.8486, kappa: 0.5361, kb_relative_information_score: 13.1587, mean_absolute_error: 0.2069, mean_prior_absolute_error: 0.3538, number_of_instances: 36, precision: 0.8552, predictive_accuracy: 0.8611, prior_entropy: 0.7897, recall: 0.8611, relative_absolute_error: 0.5849, root_mean_prior_squared_error: 0.416, root_mean_squared_error: 0.3331, root_relative_squared_error: 0.8007, scimark_benchmark: 1330.0694, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6786, f_measure: 0.7778, kappa: 0.3571, kb_relative_information_score: 9.8752, mean_absolute_error: 0.2222, mean_prior_absolute_error: 0.3538, number_of_instances: 36, precision: 0.7778, predictive_accuracy: 0.7778, prior_entropy: 0.7897, recall: 0.7778, relative_absolute_error: 0.6281, root_mean_prior_squared_error: 0.416, root_mean_squared_error: 0.4714, root_relative_squared_error: 1.1332, scimark_benchmark: 1307.4861, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4933, f_measure: 0.7407, kappa: 0.1818, kb_relative_information_score: 3.576, mean_absolute_error: 0.3175, mean_prior_absolute_error: 0.3538, number_of_instances: 36, precision: 0.8444, predictive_accuracy: 0.8056, prior_entropy: 0.7897, recall: 0.8056, relative_absolute_error: 0.8974, root_mean_prior_squared_error: 0.416, root_mean_squared_error: 0.3971, root_relative_squared_error: 0.9545, scimark_benchmark: 1318.5526,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7344, f_measure: 0.8008, kappa: 0.4112, kb_relative_information_score: 10.304, mean_absolute_error: 0.233, mean_prior_absolute_error: 0.3538, number_of_instances: 36, precision: 0.7975, predictive_accuracy: 0.8056, prior_entropy: 0.7897, recall: 0.8056, relative_absolute_error: 0.6585, root_mean_prior_squared_error: 0.416, root_mean_squared_error: 0.4056, root_relative_squared_error: 0.975, scimark_benchmark: 1310.8451,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8482, f_measure: 0.8436, kappa: 0.5909, kb_relative_information_score: 16.1252, mean_absolute_error: 0.1667, mean_prior_absolute_error: 0.3538, number_of_instances: 36, precision: 0.875, predictive_accuracy: 0.8333, prior_entropy: 0.7897, recall: 0.8333, relative_absolute_error: 0.4711, root_mean_prior_squared_error: 0.416, root_mean_squared_error: 0.4082, root_relative_squared_error: 0.9814, scimark_benchmark: 1341.5768,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.6806, kb_relative_information_score: 9.8752, mean_absolute_error: 0.2222, mean_prior_absolute_error: 0.3538, number_of_instances: 36, precision: 0.6049, predictive_accuracy: 0.7778, prior_entropy: 0.7897, recall: 0.7778, relative_absolute_error: 0.6281, root_mean_prior_squared_error: 0.416, root_mean_squared_error: 0.4714, root_relative_squared_error: 1.1332, scimark_benchmark: 1313.5005, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8259, f_measure: 0.8639, kappa: 0.6154, kb_relative_information_score: 17.2984, mean_absolute_error: 0.1673, mean_prior_absolute_error: 0.3538, number_of_instances: 36, precision: 0.8683, predictive_accuracy: 0.8611, prior_entropy: 0.7897, recall: 0.8611, relative_absolute_error: 0.4728, root_mean_prior_squared_error: 0.416, root_mean_squared_error: 0.3522, root_relative_squared_error: 0.8466, scimark_benchmark: 1392.1129,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8393, f_measure: 0.8889, kappa: 0.6786, kb_relative_information_score: 22.3751, mean_absolute_error: 0.1111, mean_prior_absolute_error: 0.3538, number_of_instances: 36, precision: 0.8889, predictive_accuracy: 0.8889, prior_entropy: 0.7897, recall: 0.8889, relative_absolute_error: 0.3141, root_mean_prior_squared_error: 0.416, root_mean_squared_error: 0.3333, root_relative_squared_error: 0.8013, scimark_benchmark: 1351.788,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8661, f_measure: 0.8681, kappa: 0.6457, kb_relative_information_score: 19.2501, mean_absolute_error: 0.1389, mean_prior_absolute_error: 0.3538, number_of_instances: 36, precision: 0.8881, predictive_accuracy: 0.8611, prior_entropy: 0.7897, recall: 0.8611, relative_absolute_error: 0.3926, root_mean_prior_squared_error: 0.416, root_mean_squared_error: 0.3727, root_relative_squared_error: 0.8959, scimark_benchmark: 1464.9318, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3661, f_measure: 0.6806, kb_relative_information_score: -0.8176, mean_absolute_error: 0.3562, mean_prior_absolute_error: 0.3538, number_of_instances: 36, precision: 0.6049, predictive_accuracy: 0.7778, prior_entropy: 0.7897, recall: 0.7778, relative_absolute_error: 1.0068, root_mean_prior_squared_error: 0.416, root_mean_squared_error: 0.4184, root_relative_squared_error: 1.0057, scimark_benchmark: 1380.2233,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8259, f_measure: 0.8889, kappa: 0.6786, kb_relative_information_score: 20.8568, mean_absolute_error: 0.132, mean_prior_absolute_error: 0.3538, number_of_instances: 36, precision: 0.8889, predictive_accuracy: 0.8889, prior_entropy: 0.7897, recall: 0.8889, relative_absolute_error: 0.373, root_mean_prior_squared_error: 0.416, root_mean_squared_error: 0.3386, root_relative_squared_error: 0.814, scimark_benchmark: 931.2336, 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: 0.7701, build_cpu_time: 0.0539, build_memory: 511278944.6667, f_measure: 0.8577, kappa: 0.5794, kb_relative_information_score: 19.2021, mean_absolute_error: 0.1396, mean_prior_absolute_error: 0.3538, number_of_instances: 36, precision: 0.856, predictive_accuracy: 0.8611, prior_entropy: 0.7897, recall: 0.8611, relative_absolute_error: 0.3946, root_mean_prior_squared_error: 0.416, root_mean_squared_error: 0.3727, root_relative_squared_error: 0.8959, scimark_benchmark: 927.3354,
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Metric:

Timeline

Plotting contribution timeline

Leaderboard

Rank Name Top Score Entries Highest rank

Note: The leaderboard ignores resubmissions of previous solutions, as well as parameter variations that do not improve performance.

Challenge

In supervised classification, you are given an input dataset in which instances are labeled with a certain class. The goal is to build a model that predicts the class for future unlabeled instances. The model is evaluated using a train-test procedure, e.g. cross-validation.

To make results by different users comparable, you are given the exact train-test folds to be used, and you need to return at least the predictions generated by your model for each of the test instances. OpenML will use these predictions to calculate a range of evaluation measures on the server.

You can also upload your own evaluation measures, provided that the code for doing so is available from the implementation used. For extremely large datasets, it may be infeasible to upload all predictions. In those cases, you need to compute and provide the evaluations yourself.

Optionally, you can upload the model trained on all the input data. There is no restriction on the file format, but please use a well-known format or PMML.

Given inputs

Expected outputs

evaluations A list of user-defined evaluations of the task as key-value pairs. KeyValue (optional)
model A file containing the model built on all the input data. File (optional)
predictions The desired output format Predictions (optional)

How to submit runs

Using your favorite machine learning environment

Download this task directly in your environment and automatically upload your results

OpenML bootcamp

From your own software

Use one of our APIs to download data from OpenML and upload your results

OpenML APIs