OpenML
Supervised Classification on Click_prediction_small

Supervised Classification on Click_prediction_small

Task 7295 Supervised Classification Click_prediction_small 39610 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6851, average_cost: 16.0614, f_measure: 0.7704, kappa: 0.065, kb_relative_information_score: -2647.5808, mean_absolute_error: 0.2592, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7846, predictive_accuracy: 0.8324, prior_entropy: 0.6541, recall: 0.8324, relative_absolute_error: 0.9253, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3624, root_relative_squared_error: 0.9683, scimark_benchmark: 1750.0341, total_cost: 641620, usercpu_time_millis: 1987.703, usercpu_time_millis_testing: 14.466, usercpu_time_millis_training: 1973.237,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6882, average_cost: 16.7022, f_measure: 0.7582, kappa: 0.0126, kb_relative_information_score: -2485.1893, mean_absolute_error: 0.2632, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7915, predictive_accuracy: 0.832, prior_entropy: 0.6541, recall: 0.832, relative_absolute_error: 0.9395, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3618, root_relative_squared_error: 0.9669, scimark_benchmark: 1818.1577, total_cost: 667220, usercpu_time_millis: 344.501, usercpu_time_millis_testing: 9.923, usercpu_time_millis_training: 334.578,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.687, average_cost: 16.0466, f_measure: 0.7715, kappa: 0.0687, kb_relative_information_score: -4210.7967, mean_absolute_error: 0.2667, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7967, predictive_accuracy: 0.8343, prior_entropy: 0.6541, recall: 0.8343, relative_absolute_error: 0.952, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3612, root_relative_squared_error: 0.9652, scimark_benchmark: 1829.7274, total_cost: 641030, usercpu_time_millis: 166.669, usercpu_time_millis_testing: 4.729, usercpu_time_millis_training: 161.94,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6818, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -2408.1073, mean_absolute_error: 0.2697, 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: 0.9629, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3646, root_relative_squared_error: 0.9742, scimark_benchmark: 1831.1421, total_cost: 672800, usercpu_time_millis: 81.793, usercpu_time_millis_testing: 4.388, usercpu_time_millis_training: 77.405,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -3.4242, 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: 0.9999, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3742, root_relative_squared_error: 1, scimark_benchmark: 1820.7099, total_cost: 672800, usercpu_time_millis: 26.553, usercpu_time_millis_testing: 4.658, usercpu_time_millis_training: 21.895,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6707, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -2618.4544, mean_absolute_error: 0.2711, 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: 0.9677, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3659, root_relative_squared_error: 0.9777, scimark_benchmark: 1831.6625, total_cost: 672800, usercpu_time_millis: 159.747, usercpu_time_millis_testing: 9.089, usercpu_time_millis_training: 150.658,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6946, average_cost: 16.5658, f_measure: 0.7613, kappa: 0.0254, kb_relative_information_score: -2451.3448, mean_absolute_error: 0.2627, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8063, predictive_accuracy: 0.8331, prior_entropy: 0.6541, recall: 0.8331, relative_absolute_error: 0.9378, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3605, root_relative_squared_error: 0.9632, scimark_benchmark: 1781.6622, total_cost: 661770, usercpu_time_millis: 312.063, usercpu_time_millis_testing: 14.742, usercpu_time_millis_training: 297.321,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6657, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -2954.7127, mean_absolute_error: 0.2695, 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: 0.9622, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3656, root_relative_squared_error: 0.9768, scimark_benchmark: 1782.6059, total_cost: 672800, usercpu_time_millis: 157.359, usercpu_time_millis_testing: 7.794, usercpu_time_millis_training: 149.565,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6937, average_cost: 16.2509, f_measure: 0.7676, kappa: 0.0519, kb_relative_information_score: -2566.8001, mean_absolute_error: 0.2611, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7963, predictive_accuracy: 0.8337, prior_entropy: 0.6541, recall: 0.8337, relative_absolute_error: 0.9323, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3601, root_relative_squared_error: 0.9621, scimark_benchmark: 1823.0629, total_cost: 649190, usercpu_time_millis: 679.09, usercpu_time_millis_testing: 16.059, usercpu_time_millis_training: 663.031,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6067, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -4156.8771, mean_absolute_error: 0.2731, 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: 0.9749, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3696, root_relative_squared_error: 0.9876, scimark_benchmark: 1830.2533, total_cost: 672800, usercpu_time_millis: 79.712, usercpu_time_millis_testing: 3.624, usercpu_time_millis_training: 76.088,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6832, average_cost: 16.7818, f_measure: 0.7564, kappa: 0.0054, kb_relative_information_score: -2539.1269, mean_absolute_error: 0.2651, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7871, predictive_accuracy: 0.8317, prior_entropy: 0.6541, recall: 0.8317, relative_absolute_error: 0.9462, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3627, root_relative_squared_error: 0.9691, scimark_benchmark: 1835.2001, total_cost: 670400, usercpu_time_millis: 132.666, usercpu_time_millis_testing: 5.261, usercpu_time_millis_training: 127.405,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6945, average_cost: 16.534, f_measure: 0.7618, kappa: 0.0278, kb_relative_information_score: -2318.4053, mean_absolute_error: 0.2605, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7981, predictive_accuracy: 0.8329, prior_entropy: 0.6541, recall: 0.8329, relative_absolute_error: 0.9299, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3604, root_relative_squared_error: 0.963, scimark_benchmark: 1750.037, total_cost: 660500, usercpu_time_millis: 109.286, usercpu_time_millis_testing: 1.27, usercpu_time_millis_training: 108.016,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6969, average_cost: 16.3402, f_measure: 0.7659, kappa: 0.0448, kb_relative_information_score: -2234.4403, mean_absolute_error: 0.2602, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8006, predictive_accuracy: 0.8338, prior_entropy: 0.6541, recall: 0.8338, relative_absolute_error: 0.9288, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3598, root_relative_squared_error: 0.9614, scimark_benchmark: 1813.5458, total_cost: 652760, usercpu_time_millis: 135.608, usercpu_time_millis_testing: 2.24, usercpu_time_millis_training: 133.368,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6695, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -3238.2437, mean_absolute_error: 0.269, 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: 0.9603, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3653, root_relative_squared_error: 0.976, scimark_benchmark: 1811.9963, total_cost: 672800, usercpu_time_millis: 81.463, usercpu_time_millis_testing: 4.851, usercpu_time_millis_training: 76.612,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6833, average_cost: 16.7037, f_measure: 0.7581, kappa: 0.0123, kb_relative_information_score: -2419.7632, mean_absolute_error: 0.2637, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.786, predictive_accuracy: 0.8319, prior_entropy: 0.6541, recall: 0.8319, relative_absolute_error: 0.9413, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3626, root_relative_squared_error: 0.9688, scimark_benchmark: 1838.7663, total_cost: 667280, usercpu_time_millis: 750.156, usercpu_time_millis_testing: 16.425, usercpu_time_millis_training: 733.731,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -12.1408, 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: 0.9999, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3742, root_relative_squared_error: 1, scimark_benchmark: 1835.5868, total_cost: 672800, usercpu_time_millis: 25.698, usercpu_time_millis_testing: 4.334, usercpu_time_millis_training: 21.364,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6933, average_cost: 16.1437, f_measure: 0.7697, kappa: 0.0612, kb_relative_information_score: -2375.2265, mean_absolute_error: 0.2592, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7987, predictive_accuracy: 0.8343, prior_entropy: 0.6541, recall: 0.8343, relative_absolute_error: 0.9252, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.36, root_relative_squared_error: 0.9619, scimark_benchmark: 1832.1165, total_cost: 644910, usercpu_time_millis: 683.422, usercpu_time_millis_testing: 6.997, usercpu_time_millis_training: 676.425,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6968, average_cost: 16.548, f_measure: 0.7617, kappa: 0.0271, kb_relative_information_score: -2252.335, mean_absolute_error: 0.2615, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8092, predictive_accuracy: 0.8333, prior_entropy: 0.6541, recall: 0.8333, relative_absolute_error: 0.9334, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3601, root_relative_squared_error: 0.9623, scimark_benchmark: 1709.1398, total_cost: 661060, usercpu_time_millis: 657.301, usercpu_time_millis_testing: 21.426, usercpu_time_millis_training: 635.875,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6858, average_cost: 16.6807, f_measure: 0.7585, kappa: 0.0141, kb_relative_information_score: -2561.2687, mean_absolute_error: 0.263, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7798, predictive_accuracy: 0.8317, prior_entropy: 0.6541, recall: 0.8317, relative_absolute_error: 0.9391, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3622, root_relative_squared_error: 0.9679, scimark_benchmark: 1830.7073, total_cost: 666360, usercpu_time_millis: 1016.019, usercpu_time_millis_testing: 20.656, usercpu_time_millis_training: 995.363,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -6.4255, 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: 0.9999, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3742, root_relative_squared_error: 1, scimark_benchmark: 1831.1542, total_cost: 672800, usercpu_time_millis: 37.96, usercpu_time_millis_testing: 6.574, usercpu_time_millis_training: 31.386,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6552, average_cost: 15.3602, f_measure: 0.7783, kappa: 0.1062, kb_relative_information_score: -5067.2527, mean_absolute_error: 0.2623, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7723, predictive_accuracy: 0.8256, prior_entropy: 0.6541, recall: 0.8256, relative_absolute_error: 0.9363, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3714, root_relative_squared_error: 0.9925, scimark_benchmark: 1830.2533, total_cost: 613610, usercpu_time_millis: 22.646, usercpu_time_millis_testing: 0.402, usercpu_time_millis_training: 22.244,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6933, average_cost: 16.4777, f_measure: 0.763, kappa: 0.0328, kb_relative_information_score: -2458.7833, mean_absolute_error: 0.2612, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7983, predictive_accuracy: 0.8331, prior_entropy: 0.6541, recall: 0.8331, relative_absolute_error: 0.9325, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3604, root_relative_squared_error: 0.963, scimark_benchmark: 1853.9849, total_cost: 658250, usercpu_time_millis: 690.108, usercpu_time_millis_testing: 17.085, usercpu_time_millis_training: 673.023,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6946, average_cost: 16.6804, f_measure: 0.7588, kappa: 0.0152, kb_relative_information_score: -2325.4264, mean_absolute_error: 0.2645, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8153, predictive_accuracy: 0.8326, prior_entropy: 0.6541, recall: 0.8326, relative_absolute_error: 0.9441, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3611, root_relative_squared_error: 0.9649, scimark_benchmark: 1847.2753, total_cost: 666350, usercpu_time_millis: 312.067, usercpu_time_millis_testing: 18.844, usercpu_time_millis_training: 293.223,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6795, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -2689.4931, mean_absolute_error: 0.269, 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: 0.9601, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3644, root_relative_squared_error: 0.9738, scimark_benchmark: 1849.7595, total_cost: 672800, usercpu_time_millis: 148.823, usercpu_time_millis_testing: 8.63, usercpu_time_millis_training: 140.193,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6483, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -3651.704, mean_absolute_error: 0.2711, 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: 0.9679, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3671, root_relative_squared_error: 0.981, scimark_benchmark: 1855.4813, total_cost: 672800, usercpu_time_millis: 127.2, usercpu_time_millis_testing: 6.16, usercpu_time_millis_training: 121.04,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6988, average_cost: 16.718, f_measure: 0.758, kappa: 0.0118, kb_relative_information_score: -1794.926, mean_absolute_error: 0.2668, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8225, predictive_accuracy: 0.8325, prior_entropy: 0.6541, recall: 0.8325, relative_absolute_error: 0.9524, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3614, root_relative_squared_error: 0.9656, scimark_benchmark: 1783.763, total_cost: 667850, usercpu_time_millis: 107.997, usercpu_time_millis_testing: 7.033, usercpu_time_millis_training: 100.964,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6943, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -1881.9451, mean_absolute_error: 0.2682, 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: 0.9576, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3629, root_relative_squared_error: 0.9696, scimark_benchmark: 1751.4847, total_cost: 672800, usercpu_time_millis: 82.553, usercpu_time_millis_testing: 4.713, usercpu_time_millis_training: 77.84,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6843, average_cost: 16.6992, f_measure: 0.7582, kappa: 0.0127, kb_relative_information_score: -2435.8399, mean_absolute_error: 0.2636, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7857, predictive_accuracy: 0.8319, prior_entropy: 0.6541, recall: 0.8319, relative_absolute_error: 0.941, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3624, root_relative_squared_error: 0.9684, scimark_benchmark: 1849.3014, total_cost: 667100, usercpu_time_millis: 77.92, usercpu_time_millis_testing: 1.587, usercpu_time_millis_training: 76.333,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6967, average_cost: 16.7438, f_measure: 0.7574, kappa: 0.0094, kb_relative_information_score: -1901.5235, mean_absolute_error: 0.2672, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8325, predictive_accuracy: 0.8324, prior_entropy: 0.6541, recall: 0.8324, relative_absolute_error: 0.954, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3617, root_relative_squared_error: 0.9666, scimark_benchmark: 1774.6206, total_cost: 668880, usercpu_time_millis: 48.159, usercpu_time_millis_testing: 2.404, usercpu_time_millis_training: 45.755,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6925, average_cost: 16.8043, f_measure: 0.756, kappa: 0.0034, kb_relative_information_score: -2313.9503, mean_absolute_error: 0.2654, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7954, predictive_accuracy: 0.8317, prior_entropy: 0.6541, recall: 0.8317, relative_absolute_error: 0.9473, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3618, root_relative_squared_error: 0.9666, scimark_benchmark: 1745.1197, total_cost: 671300, usercpu_time_millis: 43.525, usercpu_time_millis_testing: 2.182, usercpu_time_millis_training: 41.343,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6172, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -2624.385, mean_absolute_error: 0.2761, 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: 0.9857, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3704, root_relative_squared_error: 0.9899, scimark_benchmark: 1849.7595, total_cost: 672800, usercpu_time_millis: 11.536, usercpu_time_millis_testing: 0.577, usercpu_time_millis_training: 10.959,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6821, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -2628.9923, mean_absolute_error: 0.2661, 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: 0.95, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3631, root_relative_squared_error: 0.9704, scimark_benchmark: 1823.2863, total_cost: 672800, usercpu_time_millis: 105.47, usercpu_time_millis_testing: 3.93, usercpu_time_millis_training: 101.54,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6466, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -1021.1346, mean_absolute_error: 0.2776, 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: 0.9912, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3713, root_relative_squared_error: 0.9922, scimark_benchmark: 1843.4532, total_cost: 672800, usercpu_time_millis: 37.85, usercpu_time_millis_testing: 5.059, usercpu_time_millis_training: 32.791,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.695, average_cost: 16.6181, f_measure: 0.76, kappa: 0.0201, kb_relative_information_score: -2363.5293, mean_absolute_error: 0.2611, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7928, predictive_accuracy: 0.8323, prior_entropy: 0.6541, recall: 0.8323, relative_absolute_error: 0.9323, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3605, root_relative_squared_error: 0.9634, scimark_benchmark: 1845.3208, total_cost: 663860, usercpu_time_millis: 186.893, usercpu_time_millis_testing: 4.042, usercpu_time_millis_training: 182.851,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6754, average_cost: 16.8291, f_measure: 0.7554, kappa: 0.001, kb_relative_information_score: -2969.7621, mean_absolute_error: 0.2672, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.759, predictive_accuracy: 0.8315, prior_entropy: 0.6541, recall: 0.8315, relative_absolute_error: 0.9537, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3641, root_relative_squared_error: 0.9728, scimark_benchmark: 1842.1399, total_cost: 672290, usercpu_time_millis: 7.159, usercpu_time_millis_testing: 0.268, usercpu_time_millis_training: 6.891,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6652, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -2255.5257, mean_absolute_error: 0.2738, 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: 0.9775, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3678, root_relative_squared_error: 0.9829, scimark_benchmark: 1851.8785, total_cost: 672800, usercpu_time_millis: 90.508, usercpu_time_millis_testing: 8.635, usercpu_time_millis_training: 81.873,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -9.622, 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: 0.9999, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3742, root_relative_squared_error: 1, scimark_benchmark: 1854.4431, total_cost: 672800, usercpu_time_millis: 45.373, usercpu_time_millis_testing: 7.671, usercpu_time_millis_training: 37.702,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6913, average_cost: 16.6081, f_measure: 0.7604, kappa: 0.0216, kb_relative_information_score: -2502.1096, mean_absolute_error: 0.2641, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8077, predictive_accuracy: 0.8329, prior_entropy: 0.6541, recall: 0.8329, relative_absolute_error: 0.943, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3614, root_relative_squared_error: 0.9657, scimark_benchmark: 1837.7821, total_cost: 663460, usercpu_time_millis: 63.904, usercpu_time_millis_testing: 2.236, usercpu_time_millis_training: 61.668,

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