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: 0.6871, average_cost: 16.6879, f_measure: 0.7583, kappa: 0.0134, kb_relative_information_score: -2586.9191, mean_absolute_error: 0.2627, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7786, predictive_accuracy: 0.8317, prior_entropy: 0.6541, recall: 0.8317, relative_absolute_error: 0.9377, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3621, root_relative_squared_error: 0.9676, scimark_benchmark: 1786.9635, total_cost: 666650, usercpu_time_millis: 149.438, usercpu_time_millis_testing: 1.76, usercpu_time_millis_training: 147.678,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6987, average_cost: 16.7313, f_measure: 0.7577, kappa: 0.0107, kb_relative_information_score: -1823.7558, mean_absolute_error: 0.2671, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8353, predictive_accuracy: 0.8325, prior_entropy: 0.6541, recall: 0.8325, relative_absolute_error: 0.9534, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3616, root_relative_squared_error: 0.9662, scimark_benchmark: 1845.779, total_cost: 668380, usercpu_time_millis: 136.774, usercpu_time_millis_testing: 8.749, usercpu_time_millis_training: 128.025,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6821, average_cost: 16.7265, f_measure: 0.7576, kappa: 0.0103, kb_relative_information_score: -2423.8642, mean_absolute_error: 0.2643, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7869, predictive_accuracy: 0.8319, prior_entropy: 0.6541, recall: 0.8319, relative_absolute_error: 0.9437, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3626, root_relative_squared_error: 0.969, scimark_benchmark: 1765.1948, total_cost: 668190, usercpu_time_millis: 144.021, usercpu_time_millis_testing: 4.747, usercpu_time_millis_training: 139.274,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6813, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -1938.6375, mean_absolute_error: 0.2717, 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: 0.9698, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3657, root_relative_squared_error: 0.9772, scimark_benchmark: 1803.1372, total_cost: 672800, usercpu_time_millis: 139.092, usercpu_time_millis_testing: 12.815, usercpu_time_millis_training: 126.277,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6707, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -3114.578, mean_absolute_error: 0.2681, 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: 0.957, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3649, root_relative_squared_error: 0.975, scimark_benchmark: 1830.155, total_cost: 672800, usercpu_time_millis: 158.983, usercpu_time_millis_testing: 5.555, usercpu_time_millis_training: 153.428,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6893, average_cost: 16.548, f_measure: 0.7616, kappa: 0.0268, kb_relative_information_score: -2592.6335, mean_absolute_error: 0.2634, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8034, predictive_accuracy: 0.833, prior_entropy: 0.6541, recall: 0.833, relative_absolute_error: 0.9403, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3615, root_relative_squared_error: 0.9659, scimark_benchmark: 1854.9533, total_cost: 661060, usercpu_time_millis: 153.137, usercpu_time_millis_testing: 6.083, usercpu_time_millis_training: 147.054,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6512, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -3341.7908, 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: 0.9748, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3681, root_relative_squared_error: 0.9836, scimark_benchmark: 1846.2342, total_cost: 672800, usercpu_time_millis: 141.701, usercpu_time_millis_testing: 11.006, usercpu_time_millis_training: 130.695,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.692, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -1990.9275, 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: 0.3634, root_relative_squared_error: 0.9709, scimark_benchmark: 1910.4004, total_cost: 672800, usercpu_time_millis: 127.494, usercpu_time_millis_testing: 9.518, usercpu_time_millis_training: 117.976,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6841, average_cost: 16.6842, f_measure: 0.7585, kappa: 0.0141, kb_relative_information_score: -2448.9647, mean_absolute_error: 0.2639, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7896, predictive_accuracy: 0.832, prior_entropy: 0.6541, recall: 0.832, relative_absolute_error: 0.942, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3624, root_relative_squared_error: 0.9684, scimark_benchmark: 1807.998, total_cost: 666500, usercpu_time_millis: 151.774, usercpu_time_millis_testing: 4.622, usercpu_time_millis_training: 147.152,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6644, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -2237.5231, mean_absolute_error: 0.274, 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: 0.978, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.368, root_relative_squared_error: 0.9833, scimark_benchmark: 1799.9077, total_cost: 672800, usercpu_time_millis: 117.082, usercpu_time_millis_testing: 10.756, usercpu_time_millis_training: 106.326,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6217, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -4081.3955, mean_absolute_error: 0.2729, 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: 0.9741, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3692, root_relative_squared_error: 0.9865, scimark_benchmark: 1836.0792, total_cost: 672800, usercpu_time_millis: 126.689, usercpu_time_millis_testing: 7.418, usercpu_time_millis_training: 119.271,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6863, average_cost: 15.9312, f_measure: 0.7735, kappa: 0.0776, kb_relative_information_score: -3942.7332, mean_absolute_error: 0.2645, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7954, predictive_accuracy: 0.8343, prior_entropy: 0.6541, recall: 0.8343, relative_absolute_error: 0.9442, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3614, root_relative_squared_error: 0.9657, scimark_benchmark: 1851.8567, total_cost: 636420, usercpu_time_millis: 112.598, usercpu_time_millis_testing: 2.767, usercpu_time_millis_training: 109.831,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6828, average_cost: 15.8549, f_measure: 0.7746, kappa: 0.0827, kb_relative_information_score: -4188.1106, mean_absolute_error: 0.2647, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7921, predictive_accuracy: 0.8339, prior_entropy: 0.6541, recall: 0.8339, relative_absolute_error: 0.945, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3624, root_relative_squared_error: 0.9684, scimark_benchmark: 1768.2025, total_cost: 633370, usercpu_time_millis: 111.483, usercpu_time_millis_testing: 3.164, usercpu_time_millis_training: 108.319,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6826, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -1960.3325, mean_absolute_error: 0.2714, 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: 0.9687, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3654, root_relative_squared_error: 0.9764, scimark_benchmark: 1829.2244, total_cost: 672800, usercpu_time_millis: 121.81, usercpu_time_millis_testing: 9.032, usercpu_time_millis_training: 112.778,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6897, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -2011.3084, 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: 0.3638, root_relative_squared_error: 0.9721, scimark_benchmark: 1915.8721, total_cost: 672800, usercpu_time_millis: 105.426, usercpu_time_millis_testing: 10.831, usercpu_time_millis_training: 94.595,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6883, average_cost: 16.7197, f_measure: 0.7578, kappa: 0.0112, kb_relative_information_score: -2475.1182, mean_absolute_error: 0.2634, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7966, predictive_accuracy: 0.8321, prior_entropy: 0.6541, recall: 0.8321, relative_absolute_error: 0.9402, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3618, root_relative_squared_error: 0.9669, scimark_benchmark: 1815.3537, total_cost: 667920, usercpu_time_millis: 119.348, usercpu_time_millis_testing: 3.068, usercpu_time_millis_training: 116.28,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.684, average_cost: 16.7302, f_measure: 0.7576, kappa: 0.0101, kb_relative_information_score: -2456.4381, mean_absolute_error: 0.264, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7908, predictive_accuracy: 0.8319, prior_entropy: 0.6541, recall: 0.8319, relative_absolute_error: 0.9425, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3625, root_relative_squared_error: 0.9686, scimark_benchmark: 1856.5802, total_cost: 668340, usercpu_time_millis: 135.02, usercpu_time_millis_testing: 2.843, usercpu_time_millis_training: 132.177,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6827, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -2494.5327, mean_absolute_error: 0.2655, 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: 0.9478, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3629, root_relative_squared_error: 0.9696, scimark_benchmark: 1849.447, total_cost: 672800, usercpu_time_millis: 135.689, usercpu_time_millis_testing: 4.961, usercpu_time_millis_training: 130.728,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6215, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -2263.7169, mean_absolute_error: 0.2759, 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: 0.9851, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3701, root_relative_squared_error: 0.989, scimark_benchmark: 1835.6968, total_cost: 672800, usercpu_time_millis: 88.376, usercpu_time_millis_testing: 7.43, usercpu_time_millis_training: 80.946,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6465, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -2029.4104, mean_absolute_error: 0.2756, 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: 0.9839, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3696, root_relative_squared_error: 0.9876, scimark_benchmark: 1851.3986, total_cost: 672800, usercpu_time_millis: 98.753, usercpu_time_millis_testing: 10.054, usercpu_time_millis_training: 88.699,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6236, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -2538.7, mean_absolute_error: 0.2756, 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: 0.9839, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3699, root_relative_squared_error: 0.9885, scimark_benchmark: 1825.9155, total_cost: 672800, usercpu_time_millis: 107.863, usercpu_time_millis_testing: 7.392, usercpu_time_millis_training: 100.471,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6833, average_cost: 16.8309, f_measure: 0.7553, kappa: 0.0009, kb_relative_information_score: -2462.4442, mean_absolute_error: 0.2648, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7681, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 0.9454, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3627, root_relative_squared_error: 0.9691, scimark_benchmark: 1855.848, total_cost: 672360, usercpu_time_millis: 102.601, usercpu_time_millis_testing: 2.691, usercpu_time_millis_training: 99.91,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6847, average_cost: 16.8421, f_measure: 0.7551, kappa: -0.0001, kb_relative_information_score: -2509.4866, mean_absolute_error: 0.2659, 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: 0.9492, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3628, root_relative_squared_error: 0.9694, scimark_benchmark: 1850.2875, total_cost: 672810, usercpu_time_millis: 101.933, usercpu_time_millis_testing: 4.117, usercpu_time_millis_training: 97.816,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6367, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -3961.7739, mean_absolute_error: 0.2724, 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: 0.9726, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3686, root_relative_squared_error: 0.9849, scimark_benchmark: 1857.1082, total_cost: 672800, usercpu_time_millis: 112.449, usercpu_time_millis_testing: 8.881, usercpu_time_millis_training: 103.568,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6868, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -2375.1092, mean_absolute_error: 0.2681, 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: 0.9571, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3634, root_relative_squared_error: 0.9711, scimark_benchmark: 1845.1352, total_cost: 672800, usercpu_time_millis: 95.601, usercpu_time_millis_testing: 6.481, usercpu_time_millis_training: 89.12,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6791, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -1930.2803, mean_absolute_error: 0.2722, 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: 0.9716, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3661, root_relative_squared_error: 0.9783, scimark_benchmark: 1733.3606, total_cost: 672800, usercpu_time_millis: 60.467, usercpu_time_millis_testing: 5.179, usercpu_time_millis_training: 55.288,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6205, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -2290.4337, mean_absolute_error: 0.276, 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: 0.9852, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3702, root_relative_squared_error: 0.9891, scimark_benchmark: 1828.6161, total_cost: 672800, usercpu_time_millis: 99.433, usercpu_time_millis_testing: 8.012, usercpu_time_millis_training: 91.421,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6969, average_cost: 16.8229, f_measure: 0.7555, kappa: 0.0018, kb_relative_information_score: -1850.9683, mean_absolute_error: 0.2674, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8039, predictive_accuracy: 0.8317, prior_entropy: 0.6541, recall: 0.8317, relative_absolute_error: 0.9547, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.362, root_relative_squared_error: 0.9674, scimark_benchmark: 1799.2518, total_cost: 672040, usercpu_time_millis: 74.134, usercpu_time_millis_testing: 4.406, usercpu_time_millis_training: 69.728,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6222, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -2325.3035, mean_absolute_error: 0.2759, 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: 0.9849, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3701, root_relative_squared_error: 0.9889, scimark_benchmark: 1832.1397, total_cost: 672800, usercpu_time_millis: 83.579, usercpu_time_millis_testing: 6.378, usercpu_time_millis_training: 77.201,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6361, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -2068.7364, mean_absolute_error: 0.2758, 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: 0.9846, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3698, root_relative_squared_error: 0.9883, scimark_benchmark: 1820.9468, total_cost: 672800, usercpu_time_millis: 90.647, usercpu_time_millis_testing: 9.449, usercpu_time_millis_training: 81.198,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.683, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -2421.94, 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: 0.3644, root_relative_squared_error: 0.9737, scimark_benchmark: 1832.5979, total_cost: 672800, usercpu_time_millis: 78.204, usercpu_time_millis_testing: 5.203, usercpu_time_millis_training: 73.001,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6666, average_cost: 16.7993, f_measure: 0.7561, kappa: 0.0039, kb_relative_information_score: -3168.7315, mean_absolute_error: 0.2685, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8001, predictive_accuracy: 0.8318, prior_entropy: 0.6541, recall: 0.8318, relative_absolute_error: 0.9586, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3653, root_relative_squared_error: 0.9761, scimark_benchmark: 1857.0384, total_cost: 671100, usercpu_time_millis: 87.351, usercpu_time_millis_testing: 4.916, usercpu_time_millis_training: 82.435,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6907, average_cost: 16.2824, f_measure: 0.767, kappa: 0.0494, kb_relative_information_score: -2719.5125, mean_absolute_error: 0.2618, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7973, predictive_accuracy: 0.8337, prior_entropy: 0.6541, recall: 0.8337, relative_absolute_error: 0.9346, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3606, root_relative_squared_error: 0.9636, scimark_benchmark: 1836.204, total_cost: 650450, usercpu_time_millis: 478.445, usercpu_time_millis_testing: 11.162, usercpu_time_millis_training: 467.283,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6945, average_cost: 16.5425, f_measure: 0.7617, kappa: 0.0272, kb_relative_information_score: -2406.7565, mean_absolute_error: 0.2609, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7999, predictive_accuracy: 0.8329, prior_entropy: 0.6541, recall: 0.8329, relative_absolute_error: 0.9313, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3604, root_relative_squared_error: 0.963, scimark_benchmark: 1820.2848, total_cost: 660840, usercpu_time_millis: 486.378, usercpu_time_millis_testing: 9.438, usercpu_time_millis_training: 476.94,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6827, average_cost: 16.7395, f_measure: 0.7574, kappa: 0.0093, kb_relative_information_score: -2449.4691, mean_absolute_error: 0.2643, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.791, predictive_accuracy: 0.8319, prior_entropy: 0.6541, recall: 0.8319, relative_absolute_error: 0.9436, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3626, root_relative_squared_error: 0.969, scimark_benchmark: 1843.2914, total_cost: 668710, usercpu_time_millis: 458.215, usercpu_time_millis_testing: 15.604, usercpu_time_millis_training: 442.611,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6857, average_cost: 16.7593, f_measure: 0.7569, kappa: 0.0073, kb_relative_information_score: -2484.0692, mean_absolute_error: 0.2638, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7839, predictive_accuracy: 0.8317, prior_entropy: 0.6541, recall: 0.8317, relative_absolute_error: 0.9417, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3622, root_relative_squared_error: 0.9679, scimark_benchmark: 1846.4279, total_cost: 669500, usercpu_time_millis: 448.304, usercpu_time_millis_testing: 13.71, usercpu_time_millis_training: 434.594,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7005, average_cost: 16.4972, f_measure: 0.7627, kappa: 0.0315, kb_relative_information_score: -2030.5957, mean_absolute_error: 0.2615, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8058, predictive_accuracy: 0.8334, prior_entropy: 0.6541, recall: 0.8334, relative_absolute_error: 0.9335, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3595, root_relative_squared_error: 0.9607, scimark_benchmark: 1785.9278, total_cost: 659030, usercpu_time_millis: 431.593, usercpu_time_millis_testing: 14.951, usercpu_time_millis_training: 416.642,

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