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Function: require_once

OpenML
Task
Supervised Classification on pwLinear

Supervised Classification on pwLinear

Task 3587 Supervised Classification pwLinear 543 runs submitted
0 likes downloaded by 0 people , 0 total downloads 0 issues
Visibility: Public
  • mythbusting_1 study_1 study_107 study_123 study_15 study_20 study_41 study_7 under100k under1m
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543 Runs

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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9261, f_measure: 0.8299, kappa: 0.6595, kb_relative_information_score: 119.5532, mean_absolute_error: 0.2074, 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: 0.4152, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.3318, root_relative_squared_error: 0.6639, scimark_benchmark: 942.9518, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8226, f_measure: 0.8236, kappa: 0.6481, kb_relative_information_score: 129.9083, mean_absolute_error: 0.175, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8317, predictive_accuracy: 0.825, prior_entropy: 0.9994, recall: 0.825, relative_absolute_error: 0.3503, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.4183, root_relative_squared_error: 0.837, scimark_benchmark: 1318.1432, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8338, f_measure: 0.8346, kappa: 0.669, kb_relative_information_score: 133.9134, mean_absolute_error: 0.165, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8363, predictive_accuracy: 0.835, prior_entropy: 0.9994, recall: 0.835, relative_absolute_error: 0.3303, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.4062, root_relative_squared_error: 0.8128, scimark_benchmark: 1325.2092, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8341, f_measure: 0.8348, kappa: 0.6692, kb_relative_information_score: 133.9134, mean_absolute_error: 0.165, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8356, predictive_accuracy: 0.835, prior_entropy: 0.9994, recall: 0.835, relative_absolute_error: 0.3303, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.4062, root_relative_squared_error: 0.8128, scimark_benchmark: 1301.9956,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9182, f_measure: 0.835, kappa: 0.67, kb_relative_information_score: 106.7482, mean_absolute_error: 0.2474, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8355, predictive_accuracy: 0.835, prior_entropy: 0.9994, recall: 0.835, relative_absolute_error: 0.4952, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.3399, root_relative_squared_error: 0.6802, scimark_benchmark: 1335.643, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.845, f_measure: 0.845, kappa: 0.6898, kb_relative_information_score: 137.9185, mean_absolute_error: 0.155, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8451, predictive_accuracy: 0.845, prior_entropy: 0.9994, recall: 0.845, relative_absolute_error: 0.3103, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.3937, root_relative_squared_error: 0.7878, scimark_benchmark: 942.6843, 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: 930.5999, usercpu_time_millis: 150, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 140,
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: 1363.434, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8668, f_measure: 0.8298, kappa: 0.6593, kb_relative_information_score: 104.9839, mean_absolute_error: 0.2532, 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: 0.5069, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.3512, root_relative_squared_error: 0.7026, scimark_benchmark: 1368.9272,
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: 1304.6687, 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: 1361.1055, usercpu_time_millis: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.831, f_measure: 0.8299, kappa: 0.6605, kb_relative_information_score: 131.9108, mean_absolute_error: 0.17, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8325, predictive_accuracy: 0.83, prior_entropy: 0.9994, recall: 0.83, relative_absolute_error: 0.3403, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.4123, root_relative_squared_error: 0.825, scimark_benchmark: 1361.1055,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8293, f_measure: 0.8141, kappa: 0.6284, kb_relative_information_score: 101.7022, mean_absolute_error: 0.2615, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8183, predictive_accuracy: 0.815, prior_entropy: 0.9994, recall: 0.815, relative_absolute_error: 0.5235, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.3854, root_relative_squared_error: 0.7711, scimark_benchmark: 1319.9043,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8814, f_measure: 0.8548, kappa: 0.7093, kb_relative_information_score: 130.2532, mean_absolute_error: 0.1837, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8557, predictive_accuracy: 0.855, prior_entropy: 0.9994, recall: 0.855, relative_absolute_error: 0.3677, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.3469, root_relative_squared_error: 0.6942, scimark_benchmark: 1330.2678, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8532, f_measure: 0.8543, kappa: 0.7088, kb_relative_information_score: 141.9236, mean_absolute_error: 0.145, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8589, predictive_accuracy: 0.855, prior_entropy: 0.9994, recall: 0.855, relative_absolute_error: 0.2903, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.3808, root_relative_squared_error: 0.7619, scimark_benchmark: 1291.6995, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6267, f_measure: 0.6037, kappa: 0.2575, kb_relative_information_score: 53.8114, mean_absolute_error: 0.365, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.6818, predictive_accuracy: 0.635, prior_entropy: 0.9994, recall: 0.635, relative_absolute_error: 0.7307, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.6042, root_relative_squared_error: 1.2088, scimark_benchmark: 1308.9788,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.937, f_measure: 0.88, kappa: 0.7596, kb_relative_information_score: 149.781, mean_absolute_error: 0.1269, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8801, predictive_accuracy: 0.88, prior_entropy: 0.9994, recall: 0.88, relative_absolute_error: 0.2541, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.3195, root_relative_squared_error: 0.6392, scimark_benchmark: 868.2731, usercpu_time_millis: 340, usercpu_time_millis_training: 340,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8924, f_measure: 0.8696, kappa: 0.7391, kb_relative_information_score: 142.1378, mean_absolute_error: 0.1488, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8721, predictive_accuracy: 0.87, prior_entropy: 0.9994, recall: 0.87, relative_absolute_error: 0.2979, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.3383, root_relative_squared_error: 0.677, scimark_benchmark: 1358.4523,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8292, f_measure: 0.8298, kappa: 0.6593, kb_relative_information_score: 131.9108, mean_absolute_error: 0.17, 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: 0.3403, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.4123, root_relative_squared_error: 0.825, scimark_benchmark: 1351.788,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8092, f_measure: 0.8098, kappa: 0.6192, kb_relative_information_score: 123.9006, mean_absolute_error: 0.19, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8103, predictive_accuracy: 0.81, prior_entropy: 0.9994, recall: 0.81, relative_absolute_error: 0.3803, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.4359, root_relative_squared_error: 0.8722, scimark_benchmark: 1353.5686,
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: 1503.3362,
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: 1384.4418,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7689, f_measure: 0.7, kappa: 0.3995, kb_relative_information_score: 80.6854, mean_absolute_error: 0.2983, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.7, predictive_accuracy: 0.7, prior_entropy: 0.9994, recall: 0.7, relative_absolute_error: 0.5971, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.5239, root_relative_squared_error: 1.0483, scimark_benchmark: 931.2336, usercpu_time_millis: 50, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7334, f_measure: 0.7046, kappa: 0.4086, kb_relative_information_score: 72.584, mean_absolute_error: 0.3217, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.7051, predictive_accuracy: 0.705, prior_entropy: 0.9994, recall: 0.705, relative_absolute_error: 0.644, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.502, root_relative_squared_error: 1.0044, scimark_benchmark: 932.3943, usercpu_time_millis: 70, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7347, f_measure: 0.6848, kappa: 0.3689, kb_relative_information_score: 60.2553, mean_absolute_error: 0.3589, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.6849, predictive_accuracy: 0.685, prior_entropy: 0.9994, recall: 0.685, relative_absolute_error: 0.7185, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.4752, root_relative_squared_error: 0.9509, scimark_benchmark: 941.7954, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7347, f_measure: 0.6848, kappa: 0.3689, kb_relative_information_score: 60.2553, mean_absolute_error: 0.3589, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.6849, predictive_accuracy: 0.685, prior_entropy: 0.9994, recall: 0.685, relative_absolute_error: 0.7185, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.4752, root_relative_squared_error: 0.9509, scimark_benchmark: 923.7642, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7347, f_measure: 0.6848, kappa: 0.3689, kb_relative_information_score: 60.2553, mean_absolute_error: 0.3589, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.6849, predictive_accuracy: 0.685, prior_entropy: 0.9994, recall: 0.685, relative_absolute_error: 0.7185, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.4752, root_relative_squared_error: 0.9509, scimark_benchmark: 894.7455, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9236, 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: 936.6206, usercpu_time_millis: 100, usercpu_time_millis_training: 100,
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: 936.6206, 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: 942.1229, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
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: 922.9039, 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: 938.9865,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9147, f_measure: 0.8446, kappa: 0.6891, kb_relative_information_score: 127.3319, mean_absolute_error: 0.1881, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8464, predictive_accuracy: 0.845, prior_entropy: 0.9994, recall: 0.845, relative_absolute_error: 0.3766, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.3504, root_relative_squared_error: 0.701, scimark_benchmark: 936.6206, usercpu_time_millis: 50, usercpu_time_millis_training: 50,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9351, build_cpu_time: 2.0441, build_memory: 988587111.2, f_measure: 0.845, kappa: 0.69, kb_relative_information_score: 135.0387, mean_absolute_error: 0.163, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8455, predictive_accuracy: 0.845, prior_entropy: 0.9994, recall: 0.845, relative_absolute_error: 0.3263, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.3733, root_relative_squared_error: 0.7469, scimark_benchmark: 939.0159,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.927, build_cpu_time: 3.6404, build_memory: 99607107.2, f_measure: 0.855, kappa: 0.7098, kb_relative_information_score: 139.7492, mean_absolute_error: 0.1514, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8551, predictive_accuracy: 0.855, prior_entropy: 0.9994, recall: 0.855, relative_absolute_error: 0.303, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.373, root_relative_squared_error: 0.7462, scimark_benchmark: 946.4503,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9224, build_cpu_time: 0.2353, build_memory: 827401673.6, f_measure: 0.885, kappa: 0.7699, kb_relative_information_score: 152.0817, mean_absolute_error: 0.1205, 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: 0.2412, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.3312, root_relative_squared_error: 0.6627, scimark_benchmark: 944.4197,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9049, build_cpu_time: 0.6318, build_memory: 475479100.8, f_measure: 0.865, kappa: 0.7298, kb_relative_information_score: 147.6274, mean_absolute_error: 0.1298, 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: 0.2598, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.3512, root_relative_squared_error: 0.7028, scimark_benchmark: 924.6733,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.929, build_cpu_time: 0.0618, build_memory: 727422492.8, f_measure: 0.875, kappa: 0.7499, kb_relative_information_score: 149.3511, mean_absolute_error: 0.1273, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.8751, predictive_accuracy: 0.875, prior_entropy: 0.9994, recall: 0.875, relative_absolute_error: 0.2547, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.336, root_relative_squared_error: 0.6723, scimark_benchmark: 893.4088,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9396, build_cpu_time: 0.0437, build_memory: 687873201.6, f_measure: 0.875, kappa: 0.7497, kb_relative_information_score: 148.2947, mean_absolute_error: 0.1302, mean_prior_absolute_error: 0.4996, number_of_instances: 200, precision: 0.875, predictive_accuracy: 0.875, prior_entropy: 0.9994, recall: 0.875, relative_absolute_error: 0.2606, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.3316, root_relative_squared_error: 0.6634, scimark_benchmark: 920.7965,

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