OpenML
Supervised Classification on no2

Supervised Classification on no2

Task 4454 Supervised Classification no2 231 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5971, f_measure: 0.587, kappa: 0.215, kb_relative_information_score: 460.1427, mean_absolute_error: 0.4603, mean_prior_absolute_error: 0.5, number_of_instances: 5000, precision: 0.6348, predictive_accuracy: 0.6082, prior_entropy: 1, recall: 0.6082, relative_absolute_error: 0.9207, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4837, root_relative_squared_error: 0.9675, scimark_benchmark: 906.0979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.629, f_measure: 0.6006, kappa: 0.204, kb_relative_information_score: 394.8584, mean_absolute_error: 0.4674, mean_prior_absolute_error: 0.5, number_of_instances: 5000, precision: 0.6035, predictive_accuracy: 0.6022, prior_entropy: 1, recall: 0.6022, relative_absolute_error: 0.9347, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4892, root_relative_squared_error: 0.9784, scimark_benchmark: 972.587, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6189, f_measure: 0.5948, kappa: 0.1913, kb_relative_information_score: 570.9439, mean_absolute_error: 0.45, mean_prior_absolute_error: 0.5, number_of_instances: 5000, precision: 0.5965, predictive_accuracy: 0.5958, prior_entropy: 1, recall: 0.5958, relative_absolute_error: 0.9001, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5055, root_relative_squared_error: 1.0111, scimark_benchmark: 934.3687, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5766, f_measure: 0.5759, kappa: 0.1533, kb_relative_information_score: 767.9026, mean_absolute_error: 0.4232, mean_prior_absolute_error: 0.5, number_of_instances: 5000, precision: 0.5773, predictive_accuracy: 0.5768, prior_entropy: 1, recall: 0.5768, relative_absolute_error: 0.8464, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.6505, root_relative_squared_error: 1.3011, scimark_benchmark: 904.0772, usercpu_time_millis: 90, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5941, f_measure: 0.5847, kappa: 0.2051, kb_relative_information_score: 427.8357, mean_absolute_error: 0.4634, mean_prior_absolute_error: 0.5, number_of_instances: 5000, precision: 0.6243, predictive_accuracy: 0.6032, prior_entropy: 1, recall: 0.6032, relative_absolute_error: 0.9268, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4849, root_relative_squared_error: 0.9698, scimark_benchmark: 941.6675, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5941, f_measure: 0.5847, kappa: 0.2051, kb_relative_information_score: 427.8357, mean_absolute_error: 0.4634, mean_prior_absolute_error: 0.5, number_of_instances: 5000, precision: 0.6243, predictive_accuracy: 0.6032, prior_entropy: 1, recall: 0.6032, relative_absolute_error: 0.9268, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4849, root_relative_squared_error: 0.9698, scimark_benchmark: 941.6675,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5941, f_measure: 0.5847, kappa: 0.2051, kb_relative_information_score: 427.8357, mean_absolute_error: 0.4634, mean_prior_absolute_error: 0.5, number_of_instances: 5000, precision: 0.6243, predictive_accuracy: 0.6032, prior_entropy: 1, recall: 0.6032, relative_absolute_error: 0.9268, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4849, root_relative_squared_error: 0.9698, scimark_benchmark: 941.6675, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.678, f_measure: 0.6319, kappa: 0.2642, kb_relative_information_score: 746.3666, mean_absolute_error: 0.4345, mean_prior_absolute_error: 0.5, number_of_instances: 5000, precision: 0.6325, predictive_accuracy: 0.6322, prior_entropy: 1, recall: 0.6322, relative_absolute_error: 0.869, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4777, root_relative_squared_error: 0.9553, scimark_benchmark: 934.695,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6383, f_measure: 0.5969, kappa: 0.1939, kb_relative_information_score: 437.1744, mean_absolute_error: 0.463, mean_prior_absolute_error: 0.5, number_of_instances: 5000, precision: 0.5971, predictive_accuracy: 0.597, prior_entropy: 1, recall: 0.597, relative_absolute_error: 0.926, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4858, root_relative_squared_error: 0.9716, scimark_benchmark: 938.191, usercpu_time_millis: 8430, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 8390,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6107, f_measure: 0.6025, kappa: 0.2203, kb_relative_information_score: 475.8841, mean_absolute_error: 0.4602, mean_prior_absolute_error: 0.5, number_of_instances: 5000, precision: 0.6197, predictive_accuracy: 0.6106, prior_entropy: 1, recall: 0.6106, relative_absolute_error: 0.9205, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4898, root_relative_squared_error: 0.9797, scimark_benchmark: 905.2959,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7078, f_measure: 0.6421, kappa: 0.2846, kb_relative_information_score: 869.1943, mean_absolute_error: 0.4229, mean_prior_absolute_error: 0.5, number_of_instances: 5000, precision: 0.6428, predictive_accuracy: 0.6424, prior_entropy: 1, recall: 0.6424, relative_absolute_error: 0.8458, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4657, root_relative_squared_error: 0.9314, scimark_benchmark: 905.2959,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5766, f_measure: 0.5759, kappa: 0.1533, kb_relative_information_score: 767.9026, mean_absolute_error: 0.4232, mean_prior_absolute_error: 0.5, number_of_instances: 5000, precision: 0.5773, predictive_accuracy: 0.5768, prior_entropy: 1, recall: 0.5768, relative_absolute_error: 0.8464, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.6505, root_relative_squared_error: 1.3011, scimark_benchmark: 938.5498, usercpu_time_millis: 90, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5766, f_measure: 0.5759, kappa: 0.1533, kb_relative_information_score: 767.9026, mean_absolute_error: 0.4232, mean_prior_absolute_error: 0.5, number_of_instances: 5000, precision: 0.5773, predictive_accuracy: 0.5768, prior_entropy: 1, recall: 0.5768, relative_absolute_error: 0.8464, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.6505, root_relative_squared_error: 1.3011, scimark_benchmark: 974.2014, usercpu_time_millis: 180, usercpu_time_millis_testing: 80, usercpu_time_millis_training: 100,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5946, f_measure: 0.5837, kappa: 0.1995, kb_relative_information_score: 418.7651, mean_absolute_error: 0.4642, mean_prior_absolute_error: 0.5, number_of_instances: 5000, precision: 0.6185, predictive_accuracy: 0.6004, prior_entropy: 1, recall: 0.6004, relative_absolute_error: 0.9285, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4852, root_relative_squared_error: 0.9703, scimark_benchmark: 932.438,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7078, f_measure: 0.6421, kappa: 0.2846, kb_relative_information_score: 869.1943, mean_absolute_error: 0.4229, mean_prior_absolute_error: 0.5, number_of_instances: 5000, precision: 0.6428, predictive_accuracy: 0.6424, prior_entropy: 1, recall: 0.6424, relative_absolute_error: 0.8458, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4657, root_relative_squared_error: 0.9314, scimark_benchmark: 943.1009, usercpu_time_millis: 190, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 160,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5971, f_measure: 0.587, kappa: 0.215, kb_relative_information_score: 460.1427, mean_absolute_error: 0.4603, mean_prior_absolute_error: 0.5, number_of_instances: 5000, precision: 0.6348, predictive_accuracy: 0.6082, prior_entropy: 1, recall: 0.6082, relative_absolute_error: 0.9207, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4837, root_relative_squared_error: 0.9675, scimark_benchmark: 942.2392, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.629, f_measure: 0.6006, kappa: 0.204, kb_relative_information_score: 394.8584, mean_absolute_error: 0.4674, mean_prior_absolute_error: 0.5, number_of_instances: 5000, precision: 0.6035, predictive_accuracy: 0.6022, prior_entropy: 1, recall: 0.6022, relative_absolute_error: 0.9347, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4892, root_relative_squared_error: 0.9784, scimark_benchmark: 908.9569, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6189, f_measure: 0.5948, kappa: 0.1913, kb_relative_information_score: 570.9439, mean_absolute_error: 0.45, mean_prior_absolute_error: 0.5, number_of_instances: 5000, precision: 0.5965, predictive_accuracy: 0.5958, prior_entropy: 1, recall: 0.5958, relative_absolute_error: 0.9001, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5055, root_relative_squared_error: 1.0111, scimark_benchmark: 940.1541, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5766, f_measure: 0.5759, kappa: 0.1533, kb_relative_information_score: 767.9026, mean_absolute_error: 0.4232, mean_prior_absolute_error: 0.5, number_of_instances: 5000, precision: 0.5773, predictive_accuracy: 0.5768, prior_entropy: 1, recall: 0.5768, relative_absolute_error: 0.8464, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.6505, root_relative_squared_error: 1.3011, scimark_benchmark: 943.6618, usercpu_time_millis: 90, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5766, f_measure: 0.5759, kappa: 0.1533, kb_relative_information_score: 767.9026, mean_absolute_error: 0.4232, mean_prior_absolute_error: 0.5, number_of_instances: 5000, precision: 0.5773, predictive_accuracy: 0.5768, prior_entropy: 1, recall: 0.5768, relative_absolute_error: 0.8464, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.6505, root_relative_squared_error: 1.3011, scimark_benchmark: 936.2574, usercpu_time_millis: 100, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5946, f_measure: 0.5837, kappa: 0.1995, kb_relative_information_score: 418.7651, mean_absolute_error: 0.4642, mean_prior_absolute_error: 0.5, number_of_instances: 5000, precision: 0.6185, predictive_accuracy: 0.6004, prior_entropy: 1, recall: 0.6004, relative_absolute_error: 0.9285, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4852, root_relative_squared_error: 0.9703, scimark_benchmark: 930.404,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5941, f_measure: 0.5847, kappa: 0.2051, kb_relative_information_score: 427.8357, mean_absolute_error: 0.4634, mean_prior_absolute_error: 0.5, number_of_instances: 5000, precision: 0.6243, predictive_accuracy: 0.6032, prior_entropy: 1, recall: 0.6032, relative_absolute_error: 0.9268, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4849, root_relative_squared_error: 0.9698, scimark_benchmark: 930.404, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5941, f_measure: 0.5847, kappa: 0.2051, kb_relative_information_score: 427.8357, mean_absolute_error: 0.4634, mean_prior_absolute_error: 0.5, number_of_instances: 5000, precision: 0.6243, predictive_accuracy: 0.6032, prior_entropy: 1, recall: 0.6032, relative_absolute_error: 0.9268, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4849, root_relative_squared_error: 0.9698, scimark_benchmark: 933.3455, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.678, f_measure: 0.6319, kappa: 0.2642, kb_relative_information_score: 746.3666, mean_absolute_error: 0.4345, mean_prior_absolute_error: 0.5, number_of_instances: 5000, precision: 0.6325, predictive_accuracy: 0.6322, prior_entropy: 1, recall: 0.6322, relative_absolute_error: 0.869, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4777, root_relative_squared_error: 0.9553, scimark_benchmark: 903.2737, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6383, f_measure: 0.5969, kappa: 0.1939, kb_relative_information_score: 437.1744, mean_absolute_error: 0.463, mean_prior_absolute_error: 0.5, number_of_instances: 5000, precision: 0.5971, predictive_accuracy: 0.597, prior_entropy: 1, recall: 0.597, relative_absolute_error: 0.926, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4858, root_relative_squared_error: 0.9716, scimark_benchmark: 936.3213, usercpu_time_millis: 6190, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 6170,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5941, f_measure: 0.5847, kappa: 0.2051, kb_relative_information_score: 427.8357, mean_absolute_error: 0.4634, mean_prior_absolute_error: 0.5, number_of_instances: 5000, precision: 0.6243, predictive_accuracy: 0.6032, prior_entropy: 1, recall: 0.6032, relative_absolute_error: 0.9268, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4849, root_relative_squared_error: 0.9698, scimark_benchmark: 945.6228,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6107, f_measure: 0.6025, kappa: 0.2203, kb_relative_information_score: 475.8841, mean_absolute_error: 0.4602, mean_prior_absolute_error: 0.5, number_of_instances: 5000, precision: 0.6197, predictive_accuracy: 0.6106, prior_entropy: 1, recall: 0.6106, relative_absolute_error: 0.9205, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4898, root_relative_squared_error: 0.9797, scimark_benchmark: 730.6551, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7078, f_measure: 0.6421, kappa: 0.2846, kb_relative_information_score: 869.1943, mean_absolute_error: 0.4229, mean_prior_absolute_error: 0.5, number_of_instances: 5000, precision: 0.6428, predictive_accuracy: 0.6424, prior_entropy: 1, recall: 0.6424, relative_absolute_error: 0.8458, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4657, root_relative_squared_error: 0.9314, scimark_benchmark: 936.9595, usercpu_time_millis: 190, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 170,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6752, f_measure: 0.6259, kappa: 0.2544, kb_relative_information_score: 387.5709, mean_absolute_error: 0.4692, mean_prior_absolute_error: 0.5, number_of_instances: 5000, precision: 0.6291, predictive_accuracy: 0.6274, prior_entropy: 1, recall: 0.6274, relative_absolute_error: 0.9384, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4786, root_relative_squared_error: 0.9572, scimark_benchmark: 908.9569, usercpu_time_millis: 3750, usercpu_time_millis_testing: 1940, usercpu_time_millis_training: 1810,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.675, f_measure: 0.6277, kappa: 0.2573, kb_relative_information_score: 391.0711, mean_absolute_error: 0.4689, mean_prior_absolute_error: 0.5, number_of_instances: 5000, precision: 0.63, predictive_accuracy: 0.6288, prior_entropy: 1, recall: 0.6288, relative_absolute_error: 0.9378, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4785, root_relative_squared_error: 0.957, scimark_benchmark: 906.5979, usercpu_time_millis: 840, usercpu_time_millis_testing: 200, usercpu_time_millis_training: 640,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6743, f_measure: 0.6237, kappa: 0.2496, kb_relative_information_score: 395.1231, mean_absolute_error: 0.4685, mean_prior_absolute_error: 0.5, number_of_instances: 5000, precision: 0.6265, predictive_accuracy: 0.625, prior_entropy: 1, recall: 0.625, relative_absolute_error: 0.9369, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4785, root_relative_squared_error: 0.9571, scimark_benchmark: 935.3212, usercpu_time_millis: 380, usercpu_time_millis_testing: 100, usercpu_time_millis_training: 280,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6653, f_measure: 0.6182, kappa: 0.2392, kb_relative_information_score: 385.6233, mean_absolute_error: 0.4691, mean_prior_absolute_error: 0.5, number_of_instances: 5000, precision: 0.6215, predictive_accuracy: 0.6198, prior_entropy: 1, recall: 0.6198, relative_absolute_error: 0.9383, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4798, root_relative_squared_error: 0.9597, scimark_benchmark: 944.235, usercpu_time_millis: 190, usercpu_time_millis_testing: 50, usercpu_time_millis_training: 140,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.655, f_measure: 0.6116, kappa: 0.2256, kb_relative_information_score: 384.4097, mean_absolute_error: 0.4689, mean_prior_absolute_error: 0.5, number_of_instances: 5000, precision: 0.6143, predictive_accuracy: 0.613, prior_entropy: 1, recall: 0.613, relative_absolute_error: 0.9379, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4813, root_relative_squared_error: 0.9626, scimark_benchmark: 918.0831, usercpu_time_millis: 90, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 70,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6358, f_measure: 0.5924, kappa: 0.1861, kb_relative_information_score: 643.063, mean_absolute_error: 0.4407, mean_prior_absolute_error: 0.5, number_of_instances: 5000, precision: 0.5938, predictive_accuracy: 0.5932, prior_entropy: 1, recall: 0.5932, relative_absolute_error: 0.8815, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4973, root_relative_squared_error: 0.9947, scimark_benchmark: 941.9549, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6358, f_measure: 0.5924, kappa: 0.1861, kb_relative_information_score: 643.063, mean_absolute_error: 0.4407, mean_prior_absolute_error: 0.5, number_of_instances: 5000, precision: 0.5938, predictive_accuracy: 0.5932, prior_entropy: 1, recall: 0.5932, relative_absolute_error: 0.8815, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4973, root_relative_squared_error: 0.9947, scimark_benchmark: 889.4922, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6364, f_measure: 0.5926, kappa: 0.1865, kb_relative_information_score: 645.38, mean_absolute_error: 0.4405, mean_prior_absolute_error: 0.5, number_of_instances: 5000, precision: 0.594, predictive_accuracy: 0.5934, prior_entropy: 1, recall: 0.5934, relative_absolute_error: 0.8811, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4971, root_relative_squared_error: 0.9942, scimark_benchmark: 894.7131, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6374, f_measure: 0.5924, kappa: 0.1861, kb_relative_information_score: 642.0913, mean_absolute_error: 0.441, mean_prior_absolute_error: 0.5, number_of_instances: 5000, precision: 0.5938, predictive_accuracy: 0.5932, prior_entropy: 1, recall: 0.5932, relative_absolute_error: 0.882, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4951, root_relative_squared_error: 0.9902, scimark_benchmark: 929.0296, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.65, f_measure: 0.6041, kappa: 0.2104, kb_relative_information_score: 653.6648, mean_absolute_error: 0.4412, mean_prior_absolute_error: 0.5, number_of_instances: 5000, precision: 0.6066, predictive_accuracy: 0.6054, prior_entropy: 1, recall: 0.6054, relative_absolute_error: 0.8823, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.487, root_relative_squared_error: 0.9739, scimark_benchmark: 926.5859, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4964, f_measure: 0.3356, kb_relative_information_score: -0.1152, mean_absolute_error: 0.5, mean_prior_absolute_error: 0.5, number_of_instances: 5000, precision: 0.252, predictive_accuracy: 0.502, prior_entropy: 1, recall: 0.502, relative_absolute_error: 1, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5, root_relative_squared_error: 1, scimark_benchmark: 929.0296,
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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