Task
Supervised Classification on Click_prediction_small

Supervised Classification on Click_prediction_small

Task 7295 Supervised Classification Click_prediction_small 39609 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6943, average_cost: 16.166, f_measure: 0.7692, kappa: 0.0588, kb_relative_information_score: -2279.698, mean_absolute_error: 0.2597, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7956, predictive_accuracy: 0.8338, prior_entropy: 0.6541, recall: 0.8338, relative_absolute_error: 0.927, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3603, root_relative_squared_error: 0.9627, scimark_benchmark: 1727.044, total_cost: 645800, usercpu_time_millis: 1062.139, usercpu_time_millis_testing: 12.668, usercpu_time_millis_training: 1049.471,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6935, average_cost: 16.1678, f_measure: 0.7692, kappa: 0.0591, kb_relative_information_score: -2422.5979, mean_absolute_error: 0.2599, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.798, predictive_accuracy: 0.8341, prior_entropy: 0.6541, recall: 0.8341, relative_absolute_error: 0.9279, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.36, root_relative_squared_error: 0.9621, scimark_benchmark: 1734.2259, total_cost: 645870, usercpu_time_millis: 950.011, usercpu_time_millis_testing: 11.62, usercpu_time_millis_training: 938.391,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6935, average_cost: 16.6644, f_measure: 0.7591, kappa: 0.0163, kb_relative_information_score: -2370.0845, mean_absolute_error: 0.2621, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8016, predictive_accuracy: 0.8324, prior_entropy: 0.6541, recall: 0.8324, relative_absolute_error: 0.9355, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3609, root_relative_squared_error: 0.9645, scimark_benchmark: 1702.1725, total_cost: 665710, usercpu_time_millis: 929.678, usercpu_time_millis_testing: 23.496, usercpu_time_millis_training: 906.182,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6896, average_cost: 16.5643, f_measure: 0.7613, kappa: 0.0254, kb_relative_information_score: -2491.9325, mean_absolute_error: 0.2627, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.804, predictive_accuracy: 0.833, prior_entropy: 0.6541, recall: 0.833, relative_absolute_error: 0.938, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3615, root_relative_squared_error: 0.9659, scimark_benchmark: 1734.3333, total_cost: 661710, usercpu_time_millis: 385.295, usercpu_time_millis_testing: 12.801, usercpu_time_millis_training: 372.494,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6822, average_cost: 16.8184, f_measure: 0.7556, kappa: 0.0019, kb_relative_information_score: -2589.3559, mean_absolute_error: 0.2654, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7603, predictive_accuracy: 0.8315, prior_entropy: 0.6541, recall: 0.8315, relative_absolute_error: 0.9476, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3629, root_relative_squared_error: 0.9697, scimark_benchmark: 1735.1328, total_cost: 671860, usercpu_time_millis: 259.295, usercpu_time_millis_testing: 11.928, usercpu_time_millis_training: 247.367,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6898, average_cost: 15.952, f_measure: 0.7732, kappa: 0.0763, kb_relative_information_score: -3230.052, mean_absolute_error: 0.2614, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7967, predictive_accuracy: 0.8345, prior_entropy: 0.6541, recall: 0.8345, relative_absolute_error: 0.9332, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3607, root_relative_squared_error: 0.9637, scimark_benchmark: 1729.728, total_cost: 637250, usercpu_time_millis: 221.047, usercpu_time_millis_testing: 4.744, usercpu_time_millis_training: 216.303,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.622, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -4077.8301, mean_absolute_error: 0.2728, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 0.974, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3692, root_relative_squared_error: 0.9865, scimark_benchmark: 1727.4447, total_cost: 672800, usercpu_time_millis: 196.91, usercpu_time_millis_testing: 10.241, usercpu_time_millis_training: 186.669,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6634, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -3113.7262, mean_absolute_error: 0.2721, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 0.9712, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.367, root_relative_squared_error: 0.9808, scimark_benchmark: 1736.9559, total_cost: 672800, usercpu_time_millis: 186.916, usercpu_time_millis_testing: 11.308, usercpu_time_millis_training: 175.608,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6959, average_cost: 16.7938, f_measure: 0.7562, kappa: 0.0045, kb_relative_information_score: -2023.9743, mean_absolute_error: 0.2681, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8121, predictive_accuracy: 0.8319, prior_entropy: 0.6541, recall: 0.8319, relative_absolute_error: 0.9571, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3621, root_relative_squared_error: 0.9676, scimark_benchmark: 1728.4155, total_cost: 670880, usercpu_time_millis: 145.425, usercpu_time_millis_testing: 10.411, usercpu_time_millis_training: 135.014,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6553, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -3124.9751, mean_absolute_error: 0.273, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 0.9744, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3678, root_relative_squared_error: 0.9828, scimark_benchmark: 1729.7915, total_cost: 672800, usercpu_time_millis: 124.687, usercpu_time_millis_testing: 8.146, usercpu_time_millis_training: 116.541,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.686, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -1984.4153, mean_absolute_error: 0.2705, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 0.9657, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3647, root_relative_squared_error: 0.9746, scimark_benchmark: 1733.7613, total_cost: 672800, usercpu_time_millis: 121.745, usercpu_time_millis_testing: 9.22, usercpu_time_millis_training: 112.525,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6474, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -3829.8549, mean_absolute_error: 0.2719, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 0.9708, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3679, root_relative_squared_error: 0.9831, scimark_benchmark: 1733.7613, total_cost: 672800, usercpu_time_millis: 79.508, usercpu_time_millis_testing: 4.039, usercpu_time_millis_training: 75.469,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6908, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -2037.5019, mean_absolute_error: 0.2691, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 0.9607, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3633, root_relative_squared_error: 0.9709, scimark_benchmark: 1732.8983, total_cost: 672800, usercpu_time_millis: 77.021, usercpu_time_millis_testing: 8.539, usercpu_time_millis_training: 68.482,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6748, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -1826.7911, mean_absolute_error: 0.2733, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 0.9756, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3671, root_relative_squared_error: 0.9808, scimark_benchmark: 1723.1219, total_cost: 672800, usercpu_time_millis: 53.416, usercpu_time_millis_testing: 5.778, usercpu_time_millis_training: 47.638,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6897, average_cost: 16.6909, f_measure: 0.7583, kappa: 0.0133, kb_relative_information_score: -2523.8466, mean_absolute_error: 0.2622, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7828, predictive_accuracy: 0.8318, prior_entropy: 0.6541, recall: 0.8318, relative_absolute_error: 0.936, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3617, root_relative_squared_error: 0.9664, scimark_benchmark: 1732.9618, total_cost: 666770, usercpu_time_millis: 863.127, usercpu_time_millis_testing: 16.032, usercpu_time_millis_training: 847.095,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6875, average_cost: 16.703, f_measure: 0.7581, kappa: 0.0125, kb_relative_information_score: -2531.1518, mean_absolute_error: 0.2629, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7887, predictive_accuracy: 0.832, prior_entropy: 0.6541, recall: 0.832, relative_absolute_error: 0.9385, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.362, root_relative_squared_error: 0.9672, scimark_benchmark: 1728.4155, total_cost: 667250, usercpu_time_millis: 605.656, usercpu_time_millis_testing: 13.243, usercpu_time_millis_training: 592.413,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6914, average_cost: 16.57, f_measure: 0.7611, kappa: 0.0248, kb_relative_information_score: -2484.6995, mean_absolute_error: 0.2624, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8015, predictive_accuracy: 0.8329, prior_entropy: 0.6541, recall: 0.8329, relative_absolute_error: 0.9368, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3611, root_relative_squared_error: 0.965, scimark_benchmark: 1728.4155, total_cost: 661940, usercpu_time_millis: 567.543, usercpu_time_millis_testing: 19.723, usercpu_time_millis_training: 547.82,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6946, average_cost: 16.157, f_measure: 0.7693, kappa: 0.0595, kb_relative_information_score: -2214.318, mean_absolute_error: 0.2594, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7954, predictive_accuracy: 0.8338, prior_entropy: 0.6541, recall: 0.8338, relative_absolute_error: 0.9262, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.36, root_relative_squared_error: 0.9619, scimark_benchmark: 1731.9625, total_cost: 645440, usercpu_time_millis: 556.678, usercpu_time_millis_testing: 5.781, usercpu_time_millis_training: 550.897,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6905, average_cost: 16.6619, f_measure: 0.7591, kappa: 0.0163, kb_relative_information_score: -2457.2596, mean_absolute_error: 0.2623, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.794, predictive_accuracy: 0.8322, prior_entropy: 0.6541, recall: 0.8322, relative_absolute_error: 0.9364, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3614, root_relative_squared_error: 0.9658, scimark_benchmark: 1727.5086, total_cost: 665610, usercpu_time_millis: 330.13, usercpu_time_millis_testing: 8.195, usercpu_time_millis_training: 321.935,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6803, average_cost: 16.6484, f_measure: 0.7594, kappa: 0.0177, kb_relative_information_score: -2722.5326, mean_absolute_error: 0.2653, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7998, predictive_accuracy: 0.8325, prior_entropy: 0.6541, recall: 0.8325, relative_absolute_error: 0.9472, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3631, root_relative_squared_error: 0.9701, scimark_benchmark: 1727.4447, total_cost: 665070, usercpu_time_millis: 251.883, usercpu_time_millis_testing: 12.545, usercpu_time_millis_training: 239.338,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6803, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -2607.8295, mean_absolute_error: 0.2658, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 0.9491, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3632, root_relative_squared_error: 0.9706, scimark_benchmark: 1731.9625, total_cost: 672800, usercpu_time_millis: 238.296, usercpu_time_millis_testing: 8.124, usercpu_time_millis_training: 230.172,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6984, average_cost: 16.7811, f_measure: 0.7565, kappa: 0.0058, kb_relative_information_score: -1764.9137, mean_absolute_error: 0.2671, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8235, predictive_accuracy: 0.832, prior_entropy: 0.6541, recall: 0.832, relative_absolute_error: 0.9534, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3618, root_relative_squared_error: 0.9668, scimark_benchmark: 1734.3333, total_cost: 670370, usercpu_time_millis: 202.389, usercpu_time_millis_testing: 11.644, usercpu_time_millis_training: 190.745,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6764, average_cost: 16.8421, f_measure: 0.7551, kappa: -0.0001, kb_relative_information_score: -2921.4368, mean_absolute_error: 0.267, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 0.9531, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3639, root_relative_squared_error: 0.9724, scimark_benchmark: 1732.0988, total_cost: 672810, usercpu_time_millis: 165.566, usercpu_time_millis_testing: 8.063, usercpu_time_millis_training: 157.503,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6721, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -2978.5264, mean_absolute_error: 0.2693, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 0.9613, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3651, root_relative_squared_error: 0.9756, scimark_benchmark: 1730.678, total_cost: 672800, usercpu_time_millis: 159.696, usercpu_time_millis_testing: 9.89, usercpu_time_millis_training: 149.806,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6756, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -2921.8542, mean_absolute_error: 0.2679, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 0.9565, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3643, root_relative_squared_error: 0.9735, scimark_benchmark: 1718.2809, total_cost: 672800, usercpu_time_millis: 101.841, usercpu_time_millis_testing: 4.943, usercpu_time_millis_training: 96.898,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6815, average_cost: 15.7878, f_measure: 0.7758, kappa: 0.0879, kb_relative_information_score: -3375.159, mean_absolute_error: 0.2601, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7926, predictive_accuracy: 0.834, prior_entropy: 0.6541, recall: 0.834, relative_absolute_error: 0.9284, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3627, root_relative_squared_error: 0.9693, scimark_benchmark: 1733.3606, total_cost: 630690, usercpu_time_millis: 81.443, usercpu_time_millis_testing: 0.7, usercpu_time_millis_training: 80.743,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6937, average_cost: 16.3132, f_measure: 0.7665, kappa: 0.0473, kb_relative_information_score: -2473.8793, mean_absolute_error: 0.2614, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8022, predictive_accuracy: 0.834, prior_entropy: 0.6541, recall: 0.834, relative_absolute_error: 0.9333, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3598, root_relative_squared_error: 0.9614, scimark_benchmark: 1731.9625, total_cost: 651680, usercpu_time_millis: 25.3, usercpu_time_millis_testing: 0.812, usercpu_time_millis_training: 24.488,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6865, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -2022.2731, mean_absolute_error: 0.2696, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 0.9623, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3641, root_relative_squared_error: 0.9728, scimark_benchmark: 1733.8252, total_cost: 672800, usercpu_time_millis: 6.134, usercpu_time_millis_testing: 0.319, usercpu_time_millis_training: 5.815,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6935, average_cost: 16.2191, f_measure: 0.7681, kappa: 0.0545, kb_relative_information_score: -2479.4355, mean_absolute_error: 0.2608, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7957, predictive_accuracy: 0.8337, prior_entropy: 0.6541, recall: 0.8337, relative_absolute_error: 0.931, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3602, root_relative_squared_error: 0.9624, scimark_benchmark: 1073.5991, total_cost: 647920, usercpu_time_millis: 1740.479, usercpu_time_millis_testing: 29.521, usercpu_time_millis_training: 1710.958,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6744, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -2934.2649, mean_absolute_error: 0.268, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 0.9569, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3645, root_relative_squared_error: 0.9739, scimark_benchmark: 1061.826, total_cost: 672800, usercpu_time_millis: 433.165, usercpu_time_millis_testing: 17.761, usercpu_time_millis_training: 415.404,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6981, average_cost: 16.7398, f_measure: 0.7575, kappa: 0.0097, kb_relative_information_score: -1851.8266, mean_absolute_error: 0.2671, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8232, predictive_accuracy: 0.8323, prior_entropy: 0.6541, recall: 0.8323, relative_absolute_error: 0.9535, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3616, root_relative_squared_error: 0.9662, scimark_benchmark: 1814.6589, total_cost: 668720, usercpu_time_millis: 67.144, usercpu_time_millis_testing: 4.676, usercpu_time_millis_training: 62.468,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6594, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -2714.4342, mean_absolute_error: 0.2734, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 0.976, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3678, root_relative_squared_error: 0.9827, scimark_benchmark: 1737.4645, total_cost: 672800, usercpu_time_millis: 80.598, usercpu_time_millis_testing: 6.641, usercpu_time_millis_training: 73.957,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -11.1375, mean_absolute_error: 0.2801, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.6915, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 1, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3742, root_relative_squared_error: 1, scimark_benchmark: 1871.5782, total_cost: 672800, usercpu_time_millis: 22.604, usercpu_time_millis_testing: 2.952, usercpu_time_millis_training: 19.652,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6921, average_cost: 16.551, f_measure: 0.7615, kappa: 0.0262, kb_relative_information_score: -2437.1841, mean_absolute_error: 0.2609, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7968, predictive_accuracy: 0.8327, prior_entropy: 0.6541, recall: 0.8327, relative_absolute_error: 0.9314, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.361, root_relative_squared_error: 0.9645, scimark_benchmark: 1802.5355, total_cost: 661180, usercpu_time_millis: 1822.853, usercpu_time_millis_testing: 19.858, usercpu_time_millis_training: 1802.995,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.692, average_cost: 16.559, f_measure: 0.7613, kappa: 0.0257, kb_relative_information_score: -2501.2258, mean_absolute_error: 0.2616, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7997, predictive_accuracy: 0.8328, prior_entropy: 0.6541, recall: 0.8328, relative_absolute_error: 0.934, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.361, root_relative_squared_error: 0.9645, scimark_benchmark: 1770.4881, total_cost: 661500, usercpu_time_millis: 1176.858, usercpu_time_millis_testing: 20.799, usercpu_time_millis_training: 1156.059,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6895, average_cost: 16.6429, f_measure: 0.7595, kappa: 0.018, kb_relative_information_score: -2468.4553, mean_absolute_error: 0.2625, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7951, predictive_accuracy: 0.8323, prior_entropy: 0.6541, recall: 0.8323, relative_absolute_error: 0.9369, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3616, root_relative_squared_error: 0.9663, scimark_benchmark: 1784.986, total_cost: 664850, usercpu_time_millis: 629.36, usercpu_time_millis_testing: 16.262, usercpu_time_millis_training: 613.098,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6849, average_cost: 16.6802, f_measure: 0.7585, kappa: 0.0139, kb_relative_information_score: -2591.0158, mean_absolute_error: 0.2631, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7756, predictive_accuracy: 0.8315, prior_entropy: 0.6541, recall: 0.8315, relative_absolute_error: 0.9394, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3624, root_relative_squared_error: 0.9683, scimark_benchmark: 1808.733, total_cost: 666340, usercpu_time_millis: 596.081, usercpu_time_millis_testing: 10.913, usercpu_time_millis_training: 585.168,

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