OpenML
Supervised Classification on fri_c0_100_50

Supervised Classification on fri_c0_100_50

Task 3715 Supervised Classification fri_c0_100_50 559 runs submitted
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  • mythbusting_1 study_1 study_107 study_15 study_20 study_41 study_7 under100k under1m
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7325, f_measure: 0.6383, kappa: 0.282, kb_relative_information_score: 27.1623, mean_absolute_error: 0.3644, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.6448, predictive_accuracy: 0.64, prior_entropy: 0.9997, recall: 0.64, relative_absolute_error: 0.7291, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5451, root_relative_squared_error: 1.0903, scimark_benchmark: 935.6052, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.3445, kb_relative_information_score: 1.9445, mean_absolute_error: 0.49, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.2601, predictive_accuracy: 0.51, prior_entropy: 0.9997, recall: 0.51, relative_absolute_error: 0.9804, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.7, root_relative_squared_error: 1.4003, scimark_benchmark: 938.3115,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6357, f_measure: 0.61, kappa: 0.22, kb_relative_information_score: 22.0603, mean_absolute_error: 0.3896, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.6102, predictive_accuracy: 0.61, prior_entropy: 0.9997, recall: 0.61, relative_absolute_error: 0.7796, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5946, root_relative_squared_error: 1.1894, scimark_benchmark: 942.6192, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6487, f_measure: 0.6597, kappa: 0.3208, kb_relative_information_score: 9.1685, mean_absolute_error: 0.463, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.6616, predictive_accuracy: 0.66, prior_entropy: 0.9997, recall: 0.66, relative_absolute_error: 0.9265, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4817, root_relative_squared_error: 0.9636, scimark_benchmark: 935.8024, usercpu_time_millis: 150, usercpu_time_millis_training: 150,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6563, f_measure: 0.5997, kappa: 0.199, kb_relative_information_score: 10.6186, mean_absolute_error: 0.4548, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.5998, predictive_accuracy: 0.6, prior_entropy: 0.9997, recall: 0.6, relative_absolute_error: 0.91, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4831, root_relative_squared_error: 0.9664, scimark_benchmark: 933.0918,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6531, f_measure: 0.6774, kappa: 0.3577, kb_relative_information_score: 22.2972, mean_absolute_error: 0.3999, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.6837, predictive_accuracy: 0.68, prior_entropy: 0.9997, recall: 0.68, relative_absolute_error: 0.8001, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4968, root_relative_squared_error: 0.9938, scimark_benchmark: 899.1108,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6253, f_measure: 0.61, kappa: 0.22, kb_relative_information_score: 15.4538, mean_absolute_error: 0.4281, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.6102, predictive_accuracy: 0.61, prior_entropy: 0.9997, recall: 0.61, relative_absolute_error: 0.8566, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5341, root_relative_squared_error: 1.0684, scimark_benchmark: 926.4745, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6941, f_measure: 0.64, kappa: 0.2803, kb_relative_information_score: 25.3718, mean_absolute_error: 0.3769, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.6405, predictive_accuracy: 0.64, prior_entropy: 0.9997, recall: 0.64, relative_absolute_error: 0.754, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5226, root_relative_squared_error: 1.0454, scimark_benchmark: 934.929, usercpu_time_millis: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7399, f_measure: 0.74, kappa: 0.4798, kb_relative_information_score: 47.97, mean_absolute_error: 0.26, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.74, predictive_accuracy: 0.74, prior_entropy: 0.9997, recall: 0.74, relative_absolute_error: 0.5202, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5099, root_relative_squared_error: 1.02, scimark_benchmark: 928.8135, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7399, f_measure: 0.74, kappa: 0.4798, kb_relative_information_score: 47.97, mean_absolute_error: 0.26, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.74, predictive_accuracy: 0.74, prior_entropy: 0.9997, recall: 0.74, relative_absolute_error: 0.5202, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5099, root_relative_squared_error: 1.02, scimark_benchmark: 917.407, usercpu_time_millis: 40, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6845, f_measure: 0.6774, kappa: 0.3577, kb_relative_information_score: 19.9521, mean_absolute_error: 0.4087, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.6837, predictive_accuracy: 0.68, prior_entropy: 0.9997, recall: 0.68, relative_absolute_error: 0.8177, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4853, root_relative_squared_error: 0.9708, scimark_benchmark: 938.838,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6837, f_measure: 0.6774, kappa: 0.3577, kb_relative_information_score: 20.0291, mean_absolute_error: 0.4084, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.6837, predictive_accuracy: 0.68, prior_entropy: 0.9997, recall: 0.68, relative_absolute_error: 0.8171, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4855, root_relative_squared_error: 0.9711, scimark_benchmark: 922.5036, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6837, f_measure: 0.6774, kappa: 0.3577, kb_relative_information_score: 20.0291, mean_absolute_error: 0.4084, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.6837, predictive_accuracy: 0.68, prior_entropy: 0.9997, recall: 0.68, relative_absolute_error: 0.8171, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4855, root_relative_squared_error: 0.9711, scimark_benchmark: 922.5036,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6837, f_measure: 0.6774, kappa: 0.3577, kb_relative_information_score: 20.0291, mean_absolute_error: 0.4084, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.6837, predictive_accuracy: 0.68, prior_entropy: 0.9997, recall: 0.68, relative_absolute_error: 0.8171, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4855, root_relative_squared_error: 0.9711, scimark_benchmark: 938.838,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7239, f_measure: 0.6391, kappa: 0.2786, kb_relative_information_score: 19.1969, mean_absolute_error: 0.415, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.6403, predictive_accuracy: 0.64, prior_entropy: 0.9997, recall: 0.64, relative_absolute_error: 0.8303, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4599, root_relative_squared_error: 0.9199, scimark_benchmark: 935.627, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7787, f_measure: 0.72, kappa: 0.4398, kb_relative_information_score: 30.7844, mean_absolute_error: 0.3579, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.72, predictive_accuracy: 0.72, prior_entropy: 0.9997, recall: 0.72, relative_absolute_error: 0.7161, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4407, root_relative_squared_error: 0.8816, scimark_benchmark: 938.5476, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6837, f_measure: 0.6774, kappa: 0.3577, kb_relative_information_score: 20.0291, mean_absolute_error: 0.4084, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.6837, predictive_accuracy: 0.68, prior_entropy: 0.9997, recall: 0.68, relative_absolute_error: 0.8171, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4855, root_relative_squared_error: 0.9711, scimark_benchmark: 942.3809,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5764, f_measure: 0.6044, kappa: 0.2237, kb_relative_information_score: 14.1888, mean_absolute_error: 0.4365, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.62, predictive_accuracy: 0.61, prior_entropy: 0.9997, recall: 0.61, relative_absolute_error: 0.8733, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5623, root_relative_squared_error: 1.1247, scimark_benchmark: 946.6409, usercpu_time_millis: 170, usercpu_time_millis_training: 170,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7485, f_measure: 0.68, kappa: 0.3597, kb_relative_information_score: 12.3336, mean_absolute_error: 0.4504, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.68, predictive_accuracy: 0.68, prior_entropy: 0.9997, recall: 0.68, relative_absolute_error: 0.9012, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4616, root_relative_squared_error: 0.9233, scimark_benchmark: 949.7766, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6531, f_measure: 0.6774, kappa: 0.3577, kb_relative_information_score: 22.2972, mean_absolute_error: 0.3999, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.6837, predictive_accuracy: 0.68, prior_entropy: 0.9997, recall: 0.68, relative_absolute_error: 0.8001, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4968, root_relative_squared_error: 0.9938, scimark_benchmark: 946.9304,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7399, f_measure: 0.74, kappa: 0.4798, kb_relative_information_score: 47.97, mean_absolute_error: 0.26, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.74, predictive_accuracy: 0.74, prior_entropy: 0.9997, recall: 0.74, relative_absolute_error: 0.5202, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5099, root_relative_squared_error: 1.02, scimark_benchmark: 1324.1205, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6837, f_measure: 0.6774, kappa: 0.3577, kb_relative_information_score: 20.0291, mean_absolute_error: 0.4084, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.6837, predictive_accuracy: 0.68, prior_entropy: 0.9997, recall: 0.68, relative_absolute_error: 0.8171, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4855, root_relative_squared_error: 0.9711, scimark_benchmark: 1327.5842,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6837, f_measure: 0.6774, kappa: 0.3577, kb_relative_information_score: 20.0291, mean_absolute_error: 0.4084, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.6837, predictive_accuracy: 0.68, prior_entropy: 0.9997, recall: 0.68, relative_absolute_error: 0.8171, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4855, root_relative_squared_error: 0.9711, scimark_benchmark: 1327.5842,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6845, f_measure: 0.6774, kappa: 0.3577, kb_relative_information_score: 19.9521, mean_absolute_error: 0.4087, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.6837, predictive_accuracy: 0.68, prior_entropy: 0.9997, recall: 0.68, relative_absolute_error: 0.8177, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4853, root_relative_squared_error: 0.9708, scimark_benchmark: 1318.6467, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5764, f_measure: 0.6044, kappa: 0.2237, kb_relative_information_score: 14.1888, mean_absolute_error: 0.4365, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.62, predictive_accuracy: 0.61, prior_entropy: 0.9997, recall: 0.61, relative_absolute_error: 0.8733, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5623, root_relative_squared_error: 1.1247, scimark_benchmark: 1318.6467, usercpu_time_millis: 170, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 160,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6837, f_measure: 0.6774, kappa: 0.3577, kb_relative_information_score: 20.0291, mean_absolute_error: 0.4084, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.6837, predictive_accuracy: 0.68, prior_entropy: 0.9997, recall: 0.68, relative_absolute_error: 0.8171, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4855, root_relative_squared_error: 0.9711, scimark_benchmark: 1353.0836,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6531, f_measure: 0.6774, kappa: 0.3577, kb_relative_information_score: 22.2972, mean_absolute_error: 0.3999, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.6837, predictive_accuracy: 0.68, prior_entropy: 0.9997, recall: 0.68, relative_absolute_error: 0.8001, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4968, root_relative_squared_error: 0.9938, scimark_benchmark: 1324.9519,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6837, f_measure: 0.6774, kappa: 0.3577, kb_relative_information_score: 20.0291, mean_absolute_error: 0.4084, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.6837, predictive_accuracy: 0.68, prior_entropy: 0.9997, recall: 0.68, relative_absolute_error: 0.8171, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4855, root_relative_squared_error: 0.9711, scimark_benchmark: 1339.2472,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6837, f_measure: 0.6774, kappa: 0.3577, kb_relative_information_score: 20.0291, mean_absolute_error: 0.4084, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.6837, predictive_accuracy: 0.68, prior_entropy: 0.9997, recall: 0.68, relative_absolute_error: 0.8171, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4855, root_relative_squared_error: 0.9711, scimark_benchmark: 1362.9924, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6845, f_measure: 0.6774, kappa: 0.3577, kb_relative_information_score: 19.9521, mean_absolute_error: 0.4087, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.6837, predictive_accuracy: 0.68, prior_entropy: 0.9997, recall: 0.68, relative_absolute_error: 0.8177, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4853, root_relative_squared_error: 0.9708, scimark_benchmark: 1322.5413,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6837, f_measure: 0.6774, kappa: 0.3577, kb_relative_information_score: 20.0291, mean_absolute_error: 0.4084, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.6837, predictive_accuracy: 0.68, prior_entropy: 0.9997, recall: 0.68, relative_absolute_error: 0.8171, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4855, root_relative_squared_error: 0.9711, scimark_benchmark: 908.2231, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6837, f_measure: 0.6774, kappa: 0.3577, kb_relative_information_score: 20.0291, mean_absolute_error: 0.4084, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.6837, predictive_accuracy: 0.68, prior_entropy: 0.9997, recall: 0.68, relative_absolute_error: 0.8171, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4855, root_relative_squared_error: 0.9711, scimark_benchmark: 1349.1517,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6837, f_measure: 0.6774, kappa: 0.3577, kb_relative_information_score: 20.0291, mean_absolute_error: 0.4084, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.6837, predictive_accuracy: 0.68, prior_entropy: 0.9997, recall: 0.68, relative_absolute_error: 0.8171, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4855, root_relative_squared_error: 0.9711, scimark_benchmark: 1303.5632, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6845, f_measure: 0.6774, kappa: 0.3577, kb_relative_information_score: 19.9521, mean_absolute_error: 0.4087, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.6837, predictive_accuracy: 0.68, prior_entropy: 0.9997, recall: 0.68, relative_absolute_error: 0.8177, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4853, root_relative_squared_error: 0.9708, scimark_benchmark: 1338.5214,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6837, f_measure: 0.6774, kappa: 0.3577, kb_relative_information_score: 20.0291, mean_absolute_error: 0.4084, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.6837, predictive_accuracy: 0.68, prior_entropy: 0.9997, recall: 0.68, relative_absolute_error: 0.8171, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4855, root_relative_squared_error: 0.9711, scimark_benchmark: 1317.5857,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6837, f_measure: 0.6774, kappa: 0.3577, kb_relative_information_score: 20.0291, mean_absolute_error: 0.4084, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.6837, predictive_accuracy: 0.68, prior_entropy: 0.9997, recall: 0.68, relative_absolute_error: 0.8171, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4855, root_relative_squared_error: 0.9711, scimark_benchmark: 1333.202, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7239, f_measure: 0.6391, kappa: 0.2786, kb_relative_information_score: 19.1969, mean_absolute_error: 0.415, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.6403, predictive_accuracy: 0.64, prior_entropy: 0.9997, recall: 0.64, relative_absolute_error: 0.8303, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4599, root_relative_squared_error: 0.9199, scimark_benchmark: 1324.7884, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7485, f_measure: 0.68, kappa: 0.3597, kb_relative_information_score: 12.3336, mean_absolute_error: 0.4504, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.68, predictive_accuracy: 0.68, prior_entropy: 0.9997, recall: 0.68, relative_absolute_error: 0.9012, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4616, root_relative_squared_error: 0.9233, scimark_benchmark: 1317.5857, usercpu_time_millis: 40, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 30,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7485, f_measure: 0.68, kappa: 0.3597, kb_relative_information_score: 12.3336, mean_absolute_error: 0.4504, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.68, predictive_accuracy: 0.68, prior_entropy: 0.9997, recall: 0.68, relative_absolute_error: 0.9012, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4616, root_relative_squared_error: 0.9233, scimark_benchmark: 1260.1387, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7485, f_measure: 0.68, kappa: 0.3597, kb_relative_information_score: 12.3336, mean_absolute_error: 0.4504, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.68, predictive_accuracy: 0.68, prior_entropy: 0.9997, recall: 0.68, relative_absolute_error: 0.9012, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4616, root_relative_squared_error: 0.9233, scimark_benchmark: 1311.9814, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6837, f_measure: 0.6774, kappa: 0.3577, kb_relative_information_score: 20.0291, mean_absolute_error: 0.4084, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.6837, predictive_accuracy: 0.68, prior_entropy: 0.9997, recall: 0.68, relative_absolute_error: 0.8171, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4855, root_relative_squared_error: 0.9711, scimark_benchmark: 1335.643,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7647, f_measure: 0.68, kappa: 0.3603, kb_relative_information_score: 13.608, mean_absolute_error: 0.4456, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.6805, predictive_accuracy: 0.68, prior_entropy: 0.9997, recall: 0.68, relative_absolute_error: 0.8915, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.458, root_relative_squared_error: 0.9163, scimark_benchmark: 1342.1678, usercpu_time_millis: 170, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 160,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6941, f_measure: 0.64, kappa: 0.2803, kb_relative_information_score: 25.3718, mean_absolute_error: 0.3769, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.6405, predictive_accuracy: 0.64, prior_entropy: 0.9997, recall: 0.64, relative_absolute_error: 0.754, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5226, root_relative_squared_error: 1.0454, scimark_benchmark: 1342.1678, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6531, f_measure: 0.6774, kappa: 0.3577, kb_relative_information_score: 22.2972, mean_absolute_error: 0.3999, mean_prior_absolute_error: 0.4998, number_of_instances: 100, precision: 0.6837, predictive_accuracy: 0.68, prior_entropy: 0.9997, recall: 0.68, relative_absolute_error: 0.8001, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4968, root_relative_squared_error: 0.9938, scimark_benchmark: 1335.643,

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