OpenML
Supervised Classification on pwLinear

Supervised Classification on pwLinear

Task 3587 Supervised Classification pwLinear 543 runs submitted
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  • mythbusting_1 study_1 study_107 study_123 study_15 study_20 study_41 study_7 under100k under1m
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8625, f_measure: 0.82, kappa: 0.6399, kb_relative_information_score: 102.7557, mean_absolute_error: 0.2594, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8202, predictive_accuracy: 0.82, prior_entropy: 0.9994, recall: 0.82, relative_absolute_error: 0.5193, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.3752, root_relative_squared_error: 0.7507, scimark_benchmark: 941.3057, usercpu_time_millis: 80, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 70,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9486, f_measure: 0.885, kappa: 0.7699, kb_relative_information_score: 123.3177, mean_absolute_error: 0.2088, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8851, predictive_accuracy: 0.885, prior_entropy: 0.9994, recall: 0.885, relative_absolute_error: 0.4179, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.2992, root_relative_squared_error: 0.5987, scimark_benchmark: 1051.249, usercpu_time_millis: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9606, f_measure: 0.9, kappa: 0.7997, kb_relative_information_score: 133.8757, mean_absolute_error: 0.1805, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.9001, predictive_accuracy: 0.9, prior_entropy: 0.9994, recall: 0.9, relative_absolute_error: 0.3613, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.2794, root_relative_squared_error: 0.5591, scimark_benchmark: 936.3373, usercpu_time_millis: 1160, usercpu_time_millis_testing: 510, usercpu_time_millis_training: 650,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9615, f_measure: 0.91, kappa: 0.8197, kb_relative_information_score: 134.4968, mean_absolute_error: 0.1795, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.9101, predictive_accuracy: 0.91, prior_entropy: 0.9994, recall: 0.91, relative_absolute_error: 0.3594, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.2766, root_relative_squared_error: 0.5535, scimark_benchmark: 938.988, usercpu_time_millis: 440, usercpu_time_millis_testing: 110, usercpu_time_millis_training: 330,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.957, f_measure: 0.91, kappa: 0.8197, kb_relative_information_score: 133.6487, mean_absolute_error: 0.1812, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.9101, predictive_accuracy: 0.91, prior_entropy: 0.9994, recall: 0.91, relative_absolute_error: 0.3626, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.2824, root_relative_squared_error: 0.5651, scimark_benchmark: 906.8974, usercpu_time_millis: 240, usercpu_time_millis_testing: 60, usercpu_time_millis_training: 180,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9522, f_measure: 0.9049, kappa: 0.8097, kb_relative_information_score: 131.3288, mean_absolute_error: 0.1875, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.9053, predictive_accuracy: 0.905, prior_entropy: 0.9994, recall: 0.905, relative_absolute_error: 0.3754, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.2878, root_relative_squared_error: 0.5759, scimark_benchmark: 924.2305, usercpu_time_millis: 100, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 80,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9607, f_measure: 0.8899, kappa: 0.7795, kb_relative_information_score: 132.7547, mean_absolute_error: 0.182, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8905, predictive_accuracy: 0.89, prior_entropy: 0.9994, recall: 0.89, relative_absolute_error: 0.3644, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.2821, root_relative_squared_error: 0.5644, scimark_benchmark: 936.1714, usercpu_time_millis: 60, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9288, f_measure: 0.865, kappa: 0.7298, kb_relative_information_score: 132.0677, mean_absolute_error: 0.178, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8651, predictive_accuracy: 0.865, prior_entropy: 0.9994, recall: 0.865, relative_absolute_error: 0.3564, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.3228, root_relative_squared_error: 0.6458, scimark_benchmark: 929.0296, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.929, f_measure: 0.865, kappa: 0.7298, kb_relative_information_score: 132.0747, mean_absolute_error: 0.178, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8651, predictive_accuracy: 0.865, prior_entropy: 0.9994, recall: 0.865, relative_absolute_error: 0.3563, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.3227, root_relative_squared_error: 0.6456, scimark_benchmark: 926.5859, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9304, f_measure: 0.86, kappa: 0.7197, kb_relative_information_score: 131.6003, mean_absolute_error: 0.1791, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.86, predictive_accuracy: 0.86, prior_entropy: 0.9994, recall: 0.86, relative_absolute_error: 0.3586, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.323, root_relative_squared_error: 0.6462, scimark_benchmark: 894.7131, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9319, f_measure: 0.86, kappa: 0.7197, kb_relative_information_score: 130.6481, mean_absolute_error: 0.1816, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.86, predictive_accuracy: 0.86, prior_entropy: 0.9994, recall: 0.86, relative_absolute_error: 0.3635, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.3212, root_relative_squared_error: 0.6427, scimark_benchmark: 926.5859, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9206, f_measure: 0.8397, kappa: 0.6791, kb_relative_information_score: 121.3594, mean_absolute_error: 0.2061, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8409, predictive_accuracy: 0.84, prior_entropy: 0.9994, recall: 0.84, relative_absolute_error: 0.4126, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.3353, root_relative_squared_error: 0.6709, scimark_benchmark: 929.0296,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.479, f_measure: 0.3501, kb_relative_information_score: -0.0687, mean_absolute_error: 0.4997, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.2652, predictive_accuracy: 0.515, prior_entropy: 0.9994, recall: 0.515, relative_absolute_error: 1.0002, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.4999, root_relative_squared_error: 1.0002, scimark_benchmark: 936.1714,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9236, f_measure: 0.8599, kappa: 0.7194, kb_relative_information_score: 139.0369, mean_absolute_error: 0.1534, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8604, predictive_accuracy: 0.86, prior_entropy: 0.9994, recall: 0.86, relative_absolute_error: 0.3071, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.3699, root_relative_squared_error: 0.7402, scimark_benchmark: 926.5859, usercpu_time_millis: 70, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9327, f_measure: 0.8599, kappa: 0.7194, kb_relative_information_score: 143.1526, mean_absolute_error: 0.1427, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8604, predictive_accuracy: 0.86, prior_entropy: 0.9994, recall: 0.86, relative_absolute_error: 0.2857, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.352, root_relative_squared_error: 0.7044, scimark_benchmark: 935.6052, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9312, f_measure: 0.8396, kappa: 0.6789, kb_relative_information_score: 138.1823, mean_absolute_error: 0.1544, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8418, predictive_accuracy: 0.84, prior_entropy: 0.9994, recall: 0.84, relative_absolute_error: 0.3091, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.3566, root_relative_squared_error: 0.7135, scimark_benchmark: 940.0055, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9335, f_measure: 0.8645, kappa: 0.729, kb_relative_information_score: 142.2467, mean_absolute_error: 0.1462, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8676, predictive_accuracy: 0.865, prior_entropy: 0.9994, recall: 0.865, relative_absolute_error: 0.2926, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.3368, root_relative_squared_error: 0.6739, scimark_benchmark: 935.6052, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8995, f_measure: 0.8, kappa: 0.5996, kb_relative_information_score: 120.8983, mean_absolute_error: 0.1977, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8, predictive_accuracy: 0.8, prior_entropy: 0.9994, recall: 0.8, relative_absolute_error: 0.3957, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.4089, root_relative_squared_error: 0.8182, scimark_benchmark: 935.6052,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.3501, kb_relative_information_score: 5.7503, mean_absolute_error: 0.485, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.2652, predictive_accuracy: 0.515, prior_entropy: 0.9994, recall: 0.515, relative_absolute_error: 0.9709, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.6964, root_relative_squared_error: 1.3935, scimark_benchmark: 941.9549, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8663, f_measure: 0.8699, kappa: 0.7396, kb_relative_information_score: 138.4069, mean_absolute_error: 0.1622, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8701, predictive_accuracy: 0.87, prior_entropy: 0.9994, recall: 0.87, relative_absolute_error: 0.3247, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.3381, root_relative_squared_error: 0.6765, scimark_benchmark: 942.6192,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9288, f_measure: 0.8599, kappa: 0.7196, kb_relative_information_score: 118.1865, mean_absolute_error: 0.2234, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8601, predictive_accuracy: 0.86, prior_entropy: 0.9994, recall: 0.86, relative_absolute_error: 0.4473, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.3137, root_relative_squared_error: 0.6277, scimark_benchmark: 923.7471, usercpu_time_millis: 160, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 150,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8404, f_measure: 0.8298, kappa: 0.6593, kb_relative_information_score: 81.8749, mean_absolute_error: 0.3204, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8303, predictive_accuracy: 0.83, prior_entropy: 0.9994, recall: 0.83, relative_absolute_error: 0.6414, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.3834, root_relative_squared_error: 0.7672, scimark_benchmark: 933.0918,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7958, f_measure: 0.81, kappa: 0.6201, kb_relative_information_score: 95.5646, mean_absolute_error: 0.2818, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8107, predictive_accuracy: 0.81, prior_entropy: 0.9994, recall: 0.81, relative_absolute_error: 0.5641, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.3815, root_relative_squared_error: 0.7634, scimark_benchmark: 923.509,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9473, f_measure: 0.8749, kappa: 0.7495, kb_relative_information_score: 114.5223, mean_absolute_error: 0.2325, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8752, predictive_accuracy: 0.875, prior_entropy: 0.9994, recall: 0.875, relative_absolute_error: 0.4654, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.3099, root_relative_squared_error: 0.6202, scimark_benchmark: 919.6941, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9296, f_measure: 0.885, kappa: 0.7697, kb_relative_information_score: 130.4293, mean_absolute_error: 0.189, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.885, predictive_accuracy: 0.885, prior_entropy: 0.9994, recall: 0.885, relative_absolute_error: 0.3784, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.3044, root_relative_squared_error: 0.6091, scimark_benchmark: 934.929, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8593, f_measure: 0.8599, kappa: 0.7194, kb_relative_information_score: 143.9261, mean_absolute_error: 0.14, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8604, predictive_accuracy: 0.86, prior_entropy: 0.9994, recall: 0.86, relative_absolute_error: 0.2803, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.3742, root_relative_squared_error: 0.7487, scimark_benchmark: 928.8135, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8593, f_measure: 0.8599, kappa: 0.7194, kb_relative_information_score: 143.9261, mean_absolute_error: 0.14, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8604, predictive_accuracy: 0.86, prior_entropy: 0.9994, recall: 0.86, relative_absolute_error: 0.2803, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.3742, root_relative_squared_error: 0.7487, scimark_benchmark: 946.8777, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8678, f_measure: 0.8298, kappa: 0.6593, kb_relative_information_score: 103.0868, mean_absolute_error: 0.2592, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8303, predictive_accuracy: 0.83, prior_entropy: 0.9994, recall: 0.83, relative_absolute_error: 0.5189, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.3524, root_relative_squared_error: 0.7052, scimark_benchmark: 922.5036,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8669, f_measure: 0.8298, kappa: 0.6593, kb_relative_information_score: 104.0818, mean_absolute_error: 0.2561, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8303, predictive_accuracy: 0.83, prior_entropy: 0.9994, recall: 0.83, relative_absolute_error: 0.5126, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.3517, root_relative_squared_error: 0.7036, scimark_benchmark: 922.5036, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8669, f_measure: 0.8298, kappa: 0.6593, kb_relative_information_score: 104.0818, mean_absolute_error: 0.2561, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8303, predictive_accuracy: 0.83, prior_entropy: 0.9994, recall: 0.83, relative_absolute_error: 0.5126, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.3517, root_relative_squared_error: 0.7036, scimark_benchmark: 945.0194,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8669, f_measure: 0.8298, kappa: 0.6593, kb_relative_information_score: 104.0818, mean_absolute_error: 0.2561, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8303, predictive_accuracy: 0.83, prior_entropy: 0.9994, recall: 0.83, relative_absolute_error: 0.5126, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.3517, root_relative_squared_error: 0.7036, scimark_benchmark: 938.838,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9329, f_measure: 0.865, kappa: 0.7297, kb_relative_information_score: 124.9567, mean_absolute_error: 0.2014, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.865, predictive_accuracy: 0.865, prior_entropy: 0.9994, recall: 0.865, relative_absolute_error: 0.4032, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.3099, root_relative_squared_error: 0.6201, scimark_benchmark: 946.9304, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9535, f_measure: 0.865, kappa: 0.7297, kb_relative_information_score: 131.3052, mean_absolute_error: 0.1832, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.865, predictive_accuracy: 0.865, prior_entropy: 0.9994, recall: 0.865, relative_absolute_error: 0.3668, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.2971, root_relative_squared_error: 0.5944, scimark_benchmark: 946.6409, usercpu_time_millis: 250, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 240,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8669, f_measure: 0.8298, kappa: 0.6593, kb_relative_information_score: 104.0818, mean_absolute_error: 0.2561, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8303, predictive_accuracy: 0.83, prior_entropy: 0.9994, recall: 0.83, relative_absolute_error: 0.5126, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.3517, root_relative_squared_error: 0.7036, scimark_benchmark: 942.3809,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8625, f_measure: 0.82, kappa: 0.6399, kb_relative_information_score: 102.7557, mean_absolute_error: 0.2594, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8202, predictive_accuracy: 0.82, prior_entropy: 0.9994, recall: 0.82, relative_absolute_error: 0.5193, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.3752, root_relative_squared_error: 0.7507, scimark_benchmark: 946.6409, usercpu_time_millis: 70, usercpu_time_millis_training: 70,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9486, f_measure: 0.885, kappa: 0.7699, kb_relative_information_score: 123.3177, mean_absolute_error: 0.2088, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8851, predictive_accuracy: 0.885, prior_entropy: 0.9994, recall: 0.885, relative_absolute_error: 0.4179, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.2992, root_relative_squared_error: 0.5987, scimark_benchmark: 949.7766, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7958, f_measure: 0.81, kappa: 0.6201, kb_relative_information_score: 95.5646, mean_absolute_error: 0.2818, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8107, predictive_accuracy: 0.81, prior_entropy: 0.9994, recall: 0.81, relative_absolute_error: 0.5641, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.3815, root_relative_squared_error: 0.7634, scimark_benchmark: 901.8743,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8663, f_measure: 0.8699, kappa: 0.7396, kb_relative_information_score: 138.4069, mean_absolute_error: 0.1622, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8701, predictive_accuracy: 0.87, prior_entropy: 0.9994, recall: 0.87, relative_absolute_error: 0.3247, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.3381, root_relative_squared_error: 0.6765, scimark_benchmark: 1346.3935,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9473, f_measure: 0.8749, kappa: 0.7495, kb_relative_information_score: 114.5223, mean_absolute_error: 0.2325, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8752, predictive_accuracy: 0.875, prior_entropy: 0.9994, recall: 0.875, relative_absolute_error: 0.4654, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.3099, root_relative_squared_error: 0.6202, scimark_benchmark: 1345.3152, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8661, f_measure: 0.8299, kappa: 0.6595, kb_relative_information_score: 127.0095, mean_absolute_error: 0.1867, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.83, predictive_accuracy: 0.83, prior_entropy: 0.9994, recall: 0.83, relative_absolute_error: 0.3738, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.3709, root_relative_squared_error: 0.7422, scimark_benchmark: 1350.073, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9296, f_measure: 0.885, kappa: 0.7697, kb_relative_information_score: 130.4293, mean_absolute_error: 0.189, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.885, predictive_accuracy: 0.885, prior_entropy: 0.9994, recall: 0.885, relative_absolute_error: 0.3784, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.3044, root_relative_squared_error: 0.6091, scimark_benchmark: 1320.9026, usercpu_time_millis: 20, usercpu_time_millis_training: 20,

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