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: 0.4999, average_cost: 16.8419, 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: 1292.2813, total_cost: 672800, usercpu_time_millis: 1.012, usercpu_time_millis_testing: 0.089, usercpu_time_millis_training: 0.923,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.617, average_cost: 16.8369, f_measure: 0.7552, kappa: 0.0005, kb_relative_information_score: -2349.8194, mean_absolute_error: 0.2762, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.86, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 0.9861, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3708, root_relative_squared_error: 0.9907, scimark_benchmark: 1248.738, total_cost: 672600, usercpu_time_millis: 1.28, usercpu_time_millis_testing: 0.086, usercpu_time_millis_training: 1.194,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6019, average_cost: 16.8419, f_measure: 0.7551, kb_relative_information_score: -1857.6237, mean_absolute_error: 0.2783, 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: 0.9935, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3723, root_relative_squared_error: 0.9948, scimark_benchmark: 1272.5869, total_cost: 672800, usercpu_time_millis: 1.419, usercpu_time_millis_testing: 0.073, usercpu_time_millis_training: 1.346,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, 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: 1294.787, total_cost: 672800, usercpu_time_millis: 1.133, usercpu_time_millis_testing: 0.079, usercpu_time_millis_training: 1.054,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, 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: 1264.7331, total_cost: 672800, usercpu_time_millis: 1.624, usercpu_time_millis_testing: 0.129, usercpu_time_millis_training: 1.495,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, 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: 1283.8262, total_cost: 672800, usercpu_time_millis: 1.233, usercpu_time_millis_testing: 0.066, usercpu_time_millis_training: 1.167,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, 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: 1281.3685, total_cost: 672800, usercpu_time_millis: 1.396, usercpu_time_millis_testing: 0.07, usercpu_time_millis_training: 1.326,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, 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: 1286.0374, total_cost: 672800, usercpu_time_millis: 1.189, usercpu_time_millis_testing: 0.066, usercpu_time_millis_training: 1.123,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6198, average_cost: 16.8346, f_measure: 0.7553, kappa: 0.0007, kb_relative_information_score: -3223.0944, mean_absolute_error: 0.2745, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8179, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 0.98, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3701, root_relative_squared_error: 0.989, scimark_benchmark: 1283.629, total_cost: 672510, usercpu_time_millis: 1.623, usercpu_time_millis_testing: 0.075, usercpu_time_millis_training: 1.548,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, 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: 1283.2757, total_cost: 672800, usercpu_time_millis: 2.113, usercpu_time_millis_testing: 0.147, usercpu_time_millis_training: 1.966,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, 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: 1285.5367, total_cost: 672800, usercpu_time_millis: 1.337, usercpu_time_millis_testing: 0.073, usercpu_time_millis_training: 1.264,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, 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: 1288.5244, total_cost: 672800, usercpu_time_millis: 1.243, usercpu_time_millis_testing: 0.065, usercpu_time_millis_training: 1.178,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, 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: 1285.8015, total_cost: 672800, usercpu_time_millis: 0.881, usercpu_time_millis_testing: 0.066, usercpu_time_millis_training: 0.815,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.623, average_cost: 16.8106, f_measure: 0.7558, kappa: 0.003, kb_relative_information_score: -3158.0453, mean_absolute_error: 0.2736, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8134, predictive_accuracy: 0.8318, prior_entropy: 0.6541, recall: 0.8318, relative_absolute_error: 0.9768, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3696, root_relative_squared_error: 0.9876, scimark_benchmark: 1261.6766, total_cost: 671550, usercpu_time_millis: 1.242, usercpu_time_millis_testing: 0.07, usercpu_time_millis_training: 1.172,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, 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: 1254.2753, total_cost: 672800, usercpu_time_millis: 1.039, usercpu_time_millis_testing: 0.086, usercpu_time_millis_training: 0.953,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6176, average_cost: 16.8394, f_measure: 0.7552, kappa: 0.0002, kb_relative_information_score: -2783.9336, mean_absolute_error: 0.2756, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.86, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 0.984, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3705, root_relative_squared_error: 0.9901, scimark_benchmark: 1247.0171, total_cost: 672700, usercpu_time_millis: 1.233, usercpu_time_millis_testing: 0.07, usercpu_time_millis_training: 1.163,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6249, average_cost: 16.7883, f_measure: 0.7564, kappa: 0.0051, kb_relative_information_score: -3117.4874, mean_absolute_error: 0.2732, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8242, predictive_accuracy: 0.832, prior_entropy: 0.6541, recall: 0.832, relative_absolute_error: 0.9752, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3693, root_relative_squared_error: 0.9869, scimark_benchmark: 1268.9286, total_cost: 670660, usercpu_time_millis: 1.162, usercpu_time_millis_testing: 0.065, usercpu_time_millis_training: 1.097,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, 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: 1266.6372, total_cost: 672800, usercpu_time_millis: 1.477, usercpu_time_millis_testing: 0.071, usercpu_time_millis_training: 1.406,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, 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: 1253.9338, total_cost: 672800, usercpu_time_millis: 1.089, usercpu_time_millis_testing: 0.067, usercpu_time_millis_training: 1.022,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6177, average_cost: 16.8394, f_measure: 0.7552, kappa: 0.0002, kb_relative_information_score: -3077.4666, mean_absolute_error: 0.2761, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.86, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 0.9856, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3709, root_relative_squared_error: 0.991, scimark_benchmark: 1257.3561, total_cost: 672700, usercpu_time_millis: 1.721, usercpu_time_millis_testing: 0.163, usercpu_time_millis_training: 1.558,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, 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: 1283.415, total_cost: 672800, usercpu_time_millis: 0.782, usercpu_time_millis_testing: 0.066, usercpu_time_millis_training: 0.716,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, 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: 1257.0922, total_cost: 672800, usercpu_time_millis: 0.995, usercpu_time_millis_testing: 0.072, usercpu_time_millis_training: 0.923,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, 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: 1262.5318, total_cost: 672800, usercpu_time_millis: 0.989, usercpu_time_millis_testing: 0.088, usercpu_time_millis_training: 0.901,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6206, average_cost: 16.8324, f_measure: 0.7553, kappa: 0.0009, kb_relative_information_score: -3236.6024, mean_absolute_error: 0.2744, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8039, predictive_accuracy: 0.8316, prior_entropy: 0.6541, recall: 0.8316, relative_absolute_error: 0.9795, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.37, root_relative_squared_error: 0.9887, scimark_benchmark: 1286.9062, total_cost: 672420, usercpu_time_millis: 1.606, usercpu_time_millis_testing: 0.068, usercpu_time_millis_training: 1.538,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, 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: 1274.4528, total_cost: 672800, usercpu_time_millis: 1.279, usercpu_time_millis_testing: 0.066, usercpu_time_millis_training: 1.213,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, 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: 1278.8865, total_cost: 672800, usercpu_time_millis: 2.641, usercpu_time_millis_testing: 0.198, usercpu_time_millis_training: 2.443,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, 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: 1281.8246, total_cost: 672800, usercpu_time_millis: 1.228, usercpu_time_millis_testing: 0.068, usercpu_time_millis_training: 1.16,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, 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: 1280.2255, total_cost: 672800, usercpu_time_millis: 1.319, usercpu_time_millis_testing: 0.068, usercpu_time_millis_training: 1.251,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, 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: 1275.5968, total_cost: 672800, usercpu_time_millis: 1.285, usercpu_time_millis_testing: 0.071, usercpu_time_millis_training: 1.214,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, 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: 1269.1491, total_cost: 672800, usercpu_time_millis: 1.403, usercpu_time_millis_testing: 0.07, usercpu_time_millis_training: 1.333,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, 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: 1294.5349, total_cost: 672800, usercpu_time_millis: 0.763, usercpu_time_millis_testing: 0.062, usercpu_time_millis_training: 0.701,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, 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: 1296.7111, total_cost: 672800, usercpu_time_millis: 0.899, usercpu_time_millis_testing: 0.071, usercpu_time_millis_training: 0.828,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, 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: 1270.5153, total_cost: 672800, usercpu_time_millis: 1.085, usercpu_time_millis_testing: 0.069, usercpu_time_millis_training: 1.016,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6248, average_cost: 16.7836, f_measure: 0.7565, kappa: 0.0056, kb_relative_information_score: -3131.3817, mean_absolute_error: 0.273, mean_prior_absolute_error: 0.2801, number_of_instances: 39948, precision: 0.8223, predictive_accuracy: 0.832, prior_entropy: 0.6541, recall: 0.832, relative_absolute_error: 0.9745, root_mean_prior_squared_error: 0.3742, root_mean_squared_error: 0.3693, root_relative_squared_error: 0.9868, scimark_benchmark: 1265.9791, total_cost: 670470, usercpu_time_millis: 1.687, usercpu_time_millis_testing: 0.065, usercpu_time_millis_training: 1.622,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, average_cost: 16.8419, 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: 1257.1703, total_cost: 672800, usercpu_time_millis: 1.293, usercpu_time_millis_testing: 0.106, usercpu_time_millis_training: 1.187,

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

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From your own software

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

OpenML APIs