OpenML
Supervised Classification on Click_prediction_small

Supervised Classification on Click_prediction_small

Task 14971 Supervised Classification Click_prediction_small 21169 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6831, f_measure: 0.7769, kappa: 0.0942, kb_relative_information_score: -3518.073, mean_absolute_error: 0.2609, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.786, predictive_accuracy: 0.8324, prior_entropy: 0.6541, recall: 0.8324, relative_absolute_error: 0.9315, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3627, root_relative_squared_error: 0.9693, scimark_benchmark: 1294.3224, usercpu_time_millis: 1371.355, usercpu_time_millis_testing: 29.847, usercpu_time_millis_training: 1341.508,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6912, f_measure: 0.7719, kappa: 0.0706, kb_relative_information_score: -2722.5935, mean_absolute_error: 0.261, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7978, predictive_accuracy: 0.8345, prior_entropy: 0.6541, recall: 0.8345, relative_absolute_error: 0.9318, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3601, root_relative_squared_error: 0.9622, scimark_benchmark: 1249.8622, usercpu_time_millis: 289.427, usercpu_time_millis_testing: 10.075, usercpu_time_millis_training: 279.352,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6944, f_measure: 0.7709, kappa: 0.0659, kb_relative_information_score: -3167.3907, mean_absolute_error: 0.263, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8037, predictive_accuracy: 0.835, prior_entropy: 0.6541, recall: 0.835, relative_absolute_error: 0.939, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3597, root_relative_squared_error: 0.9613, scimark_benchmark: 1280.1311, usercpu_time_millis: 1004.751, usercpu_time_millis_testing: 40.512, usercpu_time_millis_training: 964.239,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6982, f_measure: 0.7583, kappa: 0.013, kb_relative_information_score: -1752.5985, mean_absolute_error: 0.2666, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8234, predictive_accuracy: 0.8326, prior_entropy: 0.6541, recall: 0.8326, relative_absolute_error: 0.9518, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3614, root_relative_squared_error: 0.9656, scimark_benchmark: 1283.2836, usercpu_time_millis: 261.531, usercpu_time_millis_testing: 13.424, usercpu_time_millis_training: 248.107,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6772, f_measure: 0.7765, kappa: 0.0916, kb_relative_information_score: -3968.8549, mean_absolute_error: 0.2624, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7889, predictive_accuracy: 0.8332, prior_entropy: 0.6541, recall: 0.8332, relative_absolute_error: 0.9366, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3638, root_relative_squared_error: 0.9721, scimark_benchmark: 1257.8556, usercpu_time_millis: 254.278, usercpu_time_millis_testing: 5.998, usercpu_time_millis_training: 248.28,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6918, f_measure: 0.7686, kappa: 0.0565, kb_relative_information_score: -3480.4854, mean_absolute_error: 0.2647, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7993, predictive_accuracy: 0.8341, prior_entropy: 0.6541, recall: 0.8341, relative_absolute_error: 0.945, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3602, root_relative_squared_error: 0.9625, scimark_benchmark: 1285.9321, usercpu_time_millis: 1136.523, usercpu_time_millis_testing: 50.958, usercpu_time_millis_training: 1085.565,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6892, f_measure: 0.7711, kappa: 0.0672, kb_relative_information_score: -3572.8409, mean_absolute_error: 0.2641, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7973, predictive_accuracy: 0.8343, prior_entropy: 0.6541, recall: 0.8343, relative_absolute_error: 0.9429, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3607, root_relative_squared_error: 0.9639, scimark_benchmark: 1283.4995, usercpu_time_millis: 4016.477, usercpu_time_millis_testing: 87.454, usercpu_time_millis_training: 3929.023,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6988, f_measure: 0.758, kappa: 0.0117, kb_relative_information_score: -1746.39, mean_absolute_error: 0.2666, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8304, predictive_accuracy: 0.8326, prior_entropy: 0.6541, recall: 0.8326, relative_absolute_error: 0.9516, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3613, root_relative_squared_error: 0.9655, scimark_benchmark: 1286.5101, usercpu_time_millis: 388.54, usercpu_time_millis_testing: 21.881, usercpu_time_millis_training: 366.659,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6371, f_measure: 0.7779, kappa: 0.1107, kb_relative_information_score: -5848.2891, mean_absolute_error: 0.2625, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7664, predictive_accuracy: 0.8199, prior_entropy: 0.6541, recall: 0.8199, relative_absolute_error: 0.9371, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3786, root_relative_squared_error: 1.0118, scimark_benchmark: 1269.9909, usercpu_time_millis: 90.806, usercpu_time_millis_testing: 2.171, usercpu_time_millis_training: 88.635,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6958, f_measure: 0.771, kappa: 0.0662, kb_relative_information_score: -2628.3515, mean_absolute_error: 0.2612, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8036, predictive_accuracy: 0.835, prior_entropy: 0.6541, recall: 0.835, relative_absolute_error: 0.9325, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3594, root_relative_squared_error: 0.9602, scimark_benchmark: 1276.1613, usercpu_time_millis: 852.362, usercpu_time_millis_testing: 30.792, usercpu_time_millis_training: 821.57,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6978, f_measure: 0.7573, kappa: 0.0088, kb_relative_information_score: -1894.3483, mean_absolute_error: 0.2673, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8228, predictive_accuracy: 0.8323, prior_entropy: 0.6541, recall: 0.8323, relative_absolute_error: 0.9544, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3617, root_relative_squared_error: 0.9666, scimark_benchmark: 1289.2523, usercpu_time_millis: 458.296, usercpu_time_millis_testing: 31.739, usercpu_time_millis_training: 426.557,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6958, f_measure: 0.7696, kappa: 0.0604, kb_relative_information_score: -2686.7498, mean_absolute_error: 0.2618, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8022, predictive_accuracy: 0.8346, prior_entropy: 0.6541, recall: 0.8346, relative_absolute_error: 0.9346, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3594, root_relative_squared_error: 0.9603, scimark_benchmark: 1291.7289, usercpu_time_millis: 326.624, usercpu_time_millis_testing: 12.815, usercpu_time_millis_training: 313.809,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.682, f_measure: 0.7755, kappa: 0.0869, kb_relative_information_score: -3779.1473, mean_absolute_error: 0.2624, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7911, predictive_accuracy: 0.8337, prior_entropy: 0.6541, recall: 0.8337, relative_absolute_error: 0.9369, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3625, root_relative_squared_error: 0.9687, scimark_benchmark: 1295.491, usercpu_time_millis: 508.454, usercpu_time_millis_testing: 11.602, usercpu_time_millis_training: 496.852,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.688, f_measure: 0.772, kappa: 0.071, kb_relative_information_score: -3460.9821, mean_absolute_error: 0.2629, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7999, predictive_accuracy: 0.8348, prior_entropy: 0.6541, recall: 0.8348, relative_absolute_error: 0.9384, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3608, root_relative_squared_error: 0.9642, scimark_benchmark: 1297.4465, usercpu_time_millis: 367.161, usercpu_time_millis_testing: 10.254, usercpu_time_millis_training: 356.907,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6934, f_measure: 0.7693, kappa: 0.0592, kb_relative_information_score: -3272.5736, mean_absolute_error: 0.2636, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7985, predictive_accuracy: 0.8342, prior_entropy: 0.6541, recall: 0.8342, relative_absolute_error: 0.9409, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3599, root_relative_squared_error: 0.9617, scimark_benchmark: 1286.123, usercpu_time_millis: 2027.686, usercpu_time_millis_testing: 80.012, usercpu_time_millis_training: 1947.674,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6945, f_measure: 0.7685, kappa: 0.0558, kb_relative_information_score: -3221.5558, mean_absolute_error: 0.2641, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8014, predictive_accuracy: 0.8343, prior_entropy: 0.6541, recall: 0.8343, relative_absolute_error: 0.9427, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3597, root_relative_squared_error: 0.9612, scimark_benchmark: 1289.9982, usercpu_time_millis: 1346.323, usercpu_time_millis_testing: 67.966, usercpu_time_millis_training: 1278.357,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6985, f_measure: 0.7579, kappa: 0.0113, kb_relative_information_score: -1765.9759, mean_absolute_error: 0.2667, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8213, predictive_accuracy: 0.8324, prior_entropy: 0.6541, recall: 0.8324, relative_absolute_error: 0.9522, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3615, root_relative_squared_error: 0.9659, scimark_benchmark: 1263.2825, usercpu_time_millis: 365.38, usercpu_time_millis_testing: 19.827, usercpu_time_millis_training: 345.553,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6972, f_measure: 0.7665, kappa: 0.0472, kb_relative_information_score: -2760.2915, mean_absolute_error: 0.2637, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8037, predictive_accuracy: 0.8341, prior_entropy: 0.6541, recall: 0.8341, relative_absolute_error: 0.9414, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3595, root_relative_squared_error: 0.9605, scimark_benchmark: 1285.0227, usercpu_time_millis: 660.079, usercpu_time_millis_testing: 38.593, usercpu_time_millis_training: 621.486,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6897, f_measure: 0.7708, kappa: 0.0656, kb_relative_information_score: -3529.0327, mean_absolute_error: 0.264, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7984, predictive_accuracy: 0.8344, prior_entropy: 0.6541, recall: 0.8344, relative_absolute_error: 0.9424, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3606, root_relative_squared_error: 0.9635, scimark_benchmark: 1288.089, usercpu_time_millis: 1995.152, usercpu_time_millis_testing: 53.939, usercpu_time_millis_training: 1941.213,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6973, f_measure: 0.7565, kappa: 0.0058, kb_relative_information_score: -1943.0567, mean_absolute_error: 0.2678, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8195, predictive_accuracy: 0.832, prior_entropy: 0.6541, recall: 0.832, relative_absolute_error: 0.9559, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3619, root_relative_squared_error: 0.967, scimark_benchmark: 1283.2834, usercpu_time_millis: 1338.355, usercpu_time_millis_testing: 96.498, usercpu_time_millis_training: 1241.857,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6686, f_measure: 0.7787, kappa: 0.106, kb_relative_information_score: -4091.5587, mean_absolute_error: 0.2604, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7762, predictive_accuracy: 0.828, prior_entropy: 0.6541, recall: 0.828, relative_absolute_error: 0.9295, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3677, root_relative_squared_error: 0.9826, scimark_benchmark: 1283.9796, usercpu_time_millis: 1736.18, usercpu_time_millis_testing: 16.141, usercpu_time_millis_training: 1720.039,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6919, f_measure: 0.7587, kappa: 0.0147, kb_relative_information_score: -1857.7154, mean_absolute_error: 0.2667, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8224, predictive_accuracy: 0.8327, prior_entropy: 0.6541, recall: 0.8327, relative_absolute_error: 0.9519, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3618, root_relative_squared_error: 0.9667, scimark_benchmark: 1290.1355, usercpu_time_millis: 65.452, usercpu_time_millis_testing: 4.149, usercpu_time_millis_training: 61.303,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6869, f_measure: 0.7731, kappa: 0.076, kb_relative_information_score: -3689.8465, mean_absolute_error: 0.2638, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7958, predictive_accuracy: 0.8344, prior_entropy: 0.6541, recall: 0.8344, relative_absolute_error: 0.9416, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3612, root_relative_squared_error: 0.9653, scimark_benchmark: 1283.9609, usercpu_time_millis: 2400.707, usercpu_time_millis_testing: 42.751, usercpu_time_millis_training: 2357.956,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6742, f_measure: 0.7699, kappa: 0.0623, kb_relative_information_score: -4046.031, mean_absolute_error: 0.2643, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7874, predictive_accuracy: 0.8328, prior_entropy: 0.6541, recall: 0.8328, relative_absolute_error: 0.9437, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3636, root_relative_squared_error: 0.9717, scimark_benchmark: 1287.8556, usercpu_time_millis: 87.236, usercpu_time_millis_testing: 4.176, usercpu_time_millis_training: 83.06,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6887, f_measure: 0.7739, kappa: 0.0796, kb_relative_information_score: -3346.9153, mean_absolute_error: 0.2618, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7936, predictive_accuracy: 0.8341, prior_entropy: 0.6541, recall: 0.8341, relative_absolute_error: 0.9347, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3609, root_relative_squared_error: 0.9645, scimark_benchmark: 1287.2341, usercpu_time_millis: 1409.037, usercpu_time_millis_testing: 39.907, usercpu_time_millis_training: 1369.13,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6837, f_measure: 0.7737, kappa: 0.0784, kb_relative_information_score: -3748.6786, mean_absolute_error: 0.2632, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.794, predictive_accuracy: 0.8341, prior_entropy: 0.6541, recall: 0.8341, relative_absolute_error: 0.9395, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3619, root_relative_squared_error: 0.9671, scimark_benchmark: 1292.1918, usercpu_time_millis: 654.126, usercpu_time_millis_testing: 13.221, usercpu_time_millis_training: 640.905,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6948, f_measure: 0.7695, kappa: 0.0601, kb_relative_information_score: -3064.5926, mean_absolute_error: 0.2629, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8, predictive_accuracy: 0.8344, prior_entropy: 0.6541, recall: 0.8344, relative_absolute_error: 0.9384, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3596, root_relative_squared_error: 0.9609, scimark_benchmark: 1282.9487, usercpu_time_millis: 1078.995, usercpu_time_millis_testing: 48.32, usercpu_time_millis_training: 1030.675,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6949, f_measure: 0.7561, kappa: 0.0042, kb_relative_information_score: -2066.2871, mean_absolute_error: 0.2684, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8236, predictive_accuracy: 0.8319, prior_entropy: 0.6541, recall: 0.8319, relative_absolute_error: 0.9582, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3623, root_relative_squared_error: 0.9681, scimark_benchmark: 1287.3254, usercpu_time_millis: 1257.378, usercpu_time_millis_testing: 98.726, usercpu_time_millis_training: 1158.652,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6792, f_measure: 0.7779, kappa: 0.0983, kb_relative_information_score: -3973.0978, mean_absolute_error: 0.2624, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7869, predictive_accuracy: 0.8326, prior_entropy: 0.6541, recall: 0.8326, relative_absolute_error: 0.9366, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3638, root_relative_squared_error: 0.9722, scimark_benchmark: 1284.4825, usercpu_time_millis: 1182.161, usercpu_time_millis_testing: 17.89, usercpu_time_millis_training: 1164.271,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6904, f_measure: 0.7732, kappa: 0.0761, kb_relative_information_score: -3439.4437, mean_absolute_error: 0.2627, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7963, predictive_accuracy: 0.8344, prior_entropy: 0.6541, recall: 0.8344, relative_absolute_error: 0.9378, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3605, root_relative_squared_error: 0.9634, scimark_benchmark: 1296.5671, usercpu_time_millis: 2006.633, usercpu_time_millis_testing: 57.429, usercpu_time_millis_training: 1949.204,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.694, f_measure: 0.7564, kappa: 0.0053, kb_relative_information_score: -1994.2308, mean_absolute_error: 0.2681, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8169, predictive_accuracy: 0.832, prior_entropy: 0.6541, recall: 0.832, relative_absolute_error: 0.9569, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3622, root_relative_squared_error: 0.9679, scimark_benchmark: 1298.5031, usercpu_time_millis: 276.985, usercpu_time_millis_testing: 21.966, usercpu_time_millis_training: 255.019,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6818, f_measure: 0.777, kappa: 0.094, kb_relative_information_score: -3548.5132, mean_absolute_error: 0.2609, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7885, predictive_accuracy: 0.8331, prior_entropy: 0.6541, recall: 0.8331, relative_absolute_error: 0.9314, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3629, root_relative_squared_error: 0.9696, scimark_benchmark: 1267.7233, usercpu_time_millis: 2497.117, usercpu_time_millis_testing: 38.561, usercpu_time_millis_training: 2458.556,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6868, f_measure: 0.7726, kappa: 0.0737, kb_relative_information_score: -3748.9548, mean_absolute_error: 0.2641, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7949, predictive_accuracy: 0.8342, prior_entropy: 0.6541, recall: 0.8342, relative_absolute_error: 0.9426, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3613, root_relative_squared_error: 0.9655, scimark_benchmark: 1274.5264, usercpu_time_millis: 1542.449, usercpu_time_millis_testing: 26.848, usercpu_time_millis_training: 1515.601,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6897, f_measure: 0.7687, kappa: 0.0568, kb_relative_information_score: -3607.5614, mean_absolute_error: 0.2648, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.7957, predictive_accuracy: 0.8338, prior_entropy: 0.6541, recall: 0.8338, relative_absolute_error: 0.9455, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3606, root_relative_squared_error: 0.9637, scimark_benchmark: 1269.1201, usercpu_time_millis: 2298.408, usercpu_time_millis_testing: 73.208, usercpu_time_millis_training: 2225.2,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, f_measure: 0.7551, kb_relative_information_score: 1.0609, 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: 1283.4341, usercpu_time_millis: 1.368, usercpu_time_millis_testing: 0.031, usercpu_time_millis_training: 1.337,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, f_measure: 0.7551, kb_relative_information_score: 1.0609, 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: 1278.2514, usercpu_time_millis: 1.706, usercpu_time_millis_testing: 0.032, usercpu_time_millis_training: 1.674,
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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