OpenML
Supervised Classification on flags

Supervised Classification on flags

Task 3875 Supervised Classification flags 140 runs submitted
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  • mythbusting_1 study_1 study_107 study_15 study_20 study_7 under100k under1m
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6594, f_measure: 0.6804, kappa: 0.3027, kb_relative_information_score: 53.7861, mean_absolute_error: 0.3199, mean_prior_absolute_error: 0.4588, number_of_instances: 194, precision: 0.6804, predictive_accuracy: 0.6804, prior_entropy: 0.9403, recall: 0.6804, relative_absolute_error: 0.6973, root_mean_prior_squared_error: 0.4787, root_mean_squared_error: 0.5574, root_relative_squared_error: 1.1644, scimark_benchmark: 1860.4354,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4834, f_measure: 0.505, kb_relative_information_score: 0.1315, mean_absolute_error: 0.4584, mean_prior_absolute_error: 0.4588, number_of_instances: 194, precision: 0.4152, predictive_accuracy: 0.6443, prior_entropy: 0.9403, recall: 0.6443, relative_absolute_error: 0.9992, root_mean_prior_squared_error: 0.4787, root_mean_squared_error: 0.4788, root_relative_squared_error: 1.0001, scimark_benchmark: 1860.4354,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7062, f_measure: 0.6632, kappa: 0.2618, kb_relative_information_score: 39.8833, mean_absolute_error: 0.3576, mean_prior_absolute_error: 0.4588, number_of_instances: 194, precision: 0.6618, predictive_accuracy: 0.6649, prior_entropy: 0.9403, recall: 0.6649, relative_absolute_error: 0.7796, root_mean_prior_squared_error: 0.4787, root_mean_squared_error: 0.4903, root_relative_squared_error: 1.0241, scimark_benchmark: 1860.4354,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6365, f_measure: 0.505, kb_relative_information_score: 22.2292, mean_absolute_error: 0.3909, mean_prior_absolute_error: 0.4588, number_of_instances: 194, precision: 0.4152, predictive_accuracy: 0.6443, prior_entropy: 0.9403, recall: 0.6443, relative_absolute_error: 0.852, root_mean_prior_squared_error: 0.4787, root_mean_squared_error: 0.4422, root_relative_squared_error: 0.9237, scimark_benchmark: 1447.2612,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6365, f_measure: 0.505, kb_relative_information_score: 22.2292, mean_absolute_error: 0.3909, mean_prior_absolute_error: 0.4588, number_of_instances: 194, precision: 0.4152, predictive_accuracy: 0.6443, prior_entropy: 0.9403, recall: 0.6443, relative_absolute_error: 0.852, root_mean_prior_squared_error: 0.4787, root_mean_squared_error: 0.4422, root_relative_squared_error: 0.9237, scimark_benchmark: 1840.6094,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6576, f_measure: 0.6216, kappa: 0.2291, kb_relative_information_score: 38.9753, mean_absolute_error: 0.3514, mean_prior_absolute_error: 0.4588, number_of_instances: 194, precision: 0.6569, predictive_accuracy: 0.6134, prior_entropy: 0.9403, recall: 0.6134, relative_absolute_error: 0.7659, root_mean_prior_squared_error: 0.4787, root_mean_squared_error: 0.5056, root_relative_squared_error: 1.0561, scimark_benchmark: 1840.6094,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7067, f_measure: 0.6859, kappa: 0.3025, kb_relative_information_score: 29.3458, mean_absolute_error: 0.3912, mean_prior_absolute_error: 0.4588, number_of_instances: 194, precision: 0.6848, predictive_accuracy: 0.6959, prior_entropy: 0.9403, recall: 0.6959, relative_absolute_error: 0.8528, root_mean_prior_squared_error: 0.4787, root_mean_squared_error: 0.4473, root_relative_squared_error: 0.9343, scimark_benchmark: 1873.1108, usercpu_time_millis: 15.625, usercpu_time_millis_testing: 15.625,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6365, f_measure: 0.505, kb_relative_information_score: 22.2292, mean_absolute_error: 0.3909, mean_prior_absolute_error: 0.4588, number_of_instances: 194, precision: 0.4152, predictive_accuracy: 0.6443, prior_entropy: 0.9403, recall: 0.6443, relative_absolute_error: 0.852, root_mean_prior_squared_error: 0.4787, root_mean_squared_error: 0.4422, root_relative_squared_error: 0.9237, scimark_benchmark: 1873.1108, usercpu_time_millis: 15.625, usercpu_time_millis_training: 15.625,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6545, f_measure: 0.65, kappa: 0.2209, kb_relative_information_score: 29.6429, mean_absolute_error: 0.384, mean_prior_absolute_error: 0.4588, number_of_instances: 194, precision: 0.6485, predictive_accuracy: 0.6649, prior_entropy: 0.9403, recall: 0.6649, relative_absolute_error: 0.8371, root_mean_prior_squared_error: 0.4787, root_mean_squared_error: 0.4775, root_relative_squared_error: 0.9975, scimark_benchmark: 1873.1108, usercpu_time_millis: 15.625, usercpu_time_millis_testing: 15.625,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6866, f_measure: 0.7186, kappa: 0.3806, kb_relative_information_score: 71.8281, mean_absolute_error: 0.2784, mean_prior_absolute_error: 0.4588, number_of_instances: 194, precision: 0.717, predictive_accuracy: 0.7216, prior_entropy: 0.9403, recall: 0.7216, relative_absolute_error: 0.6067, root_mean_prior_squared_error: 0.4787, root_mean_squared_error: 0.5276, root_relative_squared_error: 1.1021,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6849, f_measure: 0.7239, kappa: 0.3873, kb_relative_information_score: 76.3434, mean_absolute_error: 0.268, mean_prior_absolute_error: 0.4588, number_of_instances: 194, precision: 0.7242, predictive_accuracy: 0.732, prior_entropy: 0.9403, recall: 0.732, relative_absolute_error: 0.5843, root_mean_prior_squared_error: 0.4787, root_mean_squared_error: 0.5177, root_relative_squared_error: 1.0815,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6664, f_measure: 0.7072, kappa: 0.3498, kb_relative_information_score: 69.5704, mean_absolute_error: 0.2835, mean_prior_absolute_error: 0.4588, number_of_instances: 194, precision: 0.7072, predictive_accuracy: 0.7165, prior_entropy: 0.9403, recall: 0.7165, relative_absolute_error: 0.618, root_mean_prior_squared_error: 0.4787, root_mean_squared_error: 0.5325, root_relative_squared_error: 1.1122,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6946, f_measure: 0.7279, kappa: 0.3996, kb_relative_information_score: 76.3434, mean_absolute_error: 0.268, mean_prior_absolute_error: 0.4588, number_of_instances: 194, precision: 0.7264, predictive_accuracy: 0.732, prior_entropy: 0.9403, recall: 0.732, relative_absolute_error: 0.5843, root_mean_prior_squared_error: 0.4787, root_mean_squared_error: 0.5177, root_relative_squared_error: 1.0815,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6144, f_measure: 0.6483, kappa: 0.2302, kb_relative_information_score: 40.2207, mean_absolute_error: 0.3505, mean_prior_absolute_error: 0.4588, number_of_instances: 194, precision: 0.6472, predictive_accuracy: 0.6495, prior_entropy: 0.9403, recall: 0.6495, relative_absolute_error: 0.764, root_mean_prior_squared_error: 0.4787, root_mean_squared_error: 0.592, root_relative_squared_error: 1.2367, usercpu_time_millis: 5.453, usercpu_time_millis_testing: 0.515, usercpu_time_millis_training: 4.938,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.496, f_measure: 0.5025, kappa: -0.0103, kb_relative_information_score: 35.7053, mean_absolute_error: 0.3608, mean_prior_absolute_error: 0.4588, number_of_instances: 194, precision: 0.414, predictive_accuracy: 0.6392, prior_entropy: 0.9403, recall: 0.6392, relative_absolute_error: 0.7865, root_mean_prior_squared_error: 0.4787, root_mean_squared_error: 0.6007, root_relative_squared_error: 1.2548, usercpu_time_millis: 0.747, usercpu_time_millis_testing: 0.18, usercpu_time_millis_training: 0.567,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6809, f_measure: 0.7194, kappa: 0.3777, kb_relative_information_score: 74.0857, mean_absolute_error: 0.2732, mean_prior_absolute_error: 0.4588, number_of_instances: 194, precision: 0.7189, predictive_accuracy: 0.7268, prior_entropy: 0.9403, recall: 0.7268, relative_absolute_error: 0.5955, root_mean_prior_squared_error: 0.4787, root_mean_squared_error: 0.5227, root_relative_squared_error: 1.0918, usercpu_time_millis: 13.927, usercpu_time_millis_testing: 1.084, usercpu_time_millis_training: 12.843,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6874, f_measure: 0.722, kappa: 0.386, kb_relative_information_score: 74.0857, mean_absolute_error: 0.2732, mean_prior_absolute_error: 0.4588, number_of_instances: 194, precision: 0.7205, predictive_accuracy: 0.7268, prior_entropy: 0.9403, recall: 0.7268, relative_absolute_error: 0.5955, root_mean_prior_squared_error: 0.4787, root_mean_squared_error: 0.5227, root_relative_squared_error: 1.0918, usercpu_time_millis: 0.638, usercpu_time_millis_testing: 0.336, usercpu_time_millis_training: 0.302,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6891, f_measure: 0.716, kappa: 0.3794, kb_relative_information_score: 69.5704, mean_absolute_error: 0.2835, mean_prior_absolute_error: 0.4588, number_of_instances: 194, precision: 0.7156, predictive_accuracy: 0.7165, prior_entropy: 0.9403, recall: 0.7165, relative_absolute_error: 0.618, root_mean_prior_squared_error: 0.4787, root_mean_squared_error: 0.5325, root_relative_squared_error: 1.1122, usercpu_time_millis: 143.678, usercpu_time_millis_testing: 0.288, usercpu_time_millis_training: 143.39,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.505, kb_relative_information_score: 37.963, mean_absolute_error: 0.3557, mean_prior_absolute_error: 0.4588, number_of_instances: 194, precision: 0.4152, predictive_accuracy: 0.6443, prior_entropy: 0.9403, recall: 0.6443, relative_absolute_error: 0.7753, root_mean_prior_squared_error: 0.4787, root_mean_squared_error: 0.5964, root_relative_squared_error: 1.2458, usercpu_time_millis: 13.099, usercpu_time_millis_testing: 0.413, usercpu_time_millis_training: 12.686,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6584, f_measure: 0.6982, kappa: 0.3307, kb_relative_information_score: 65.0551, mean_absolute_error: 0.2938, mean_prior_absolute_error: 0.4588, number_of_instances: 194, precision: 0.6969, predictive_accuracy: 0.7062, prior_entropy: 0.9403, recall: 0.7062, relative_absolute_error: 0.6404, root_mean_prior_squared_error: 0.4787, root_mean_squared_error: 0.542, root_relative_squared_error: 1.1323, usercpu_time_millis: 2.565, usercpu_time_millis_testing: 0.317, usercpu_time_millis_training: 2.248,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6559, f_measure: 0.6994, kappa: 0.3311, kb_relative_information_score: 67.3127, mean_absolute_error: 0.2887, mean_prior_absolute_error: 0.4588, number_of_instances: 194, precision: 0.7008, predictive_accuracy: 0.7113, prior_entropy: 0.9403, recall: 0.7113, relative_absolute_error: 0.6292, root_mean_prior_squared_error: 0.4787, root_mean_squared_error: 0.5373, root_relative_squared_error: 1.1223, usercpu_time_millis: 35.464, usercpu_time_millis_testing: 4.595, usercpu_time_millis_training: 30.869,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6566, f_measure: 0.702, kappa: 0.3362, kb_relative_information_score: 69.5704, mean_absolute_error: 0.2835, mean_prior_absolute_error: 0.4588, number_of_instances: 194, precision: 0.7063, predictive_accuracy: 0.7165, prior_entropy: 0.9403, recall: 0.7165, relative_absolute_error: 0.618, root_mean_prior_squared_error: 0.4787, root_mean_squared_error: 0.5325, root_relative_squared_error: 1.1122, usercpu_time_millis: 6.322, usercpu_time_millis_testing: 0.425, usercpu_time_millis_training: 5.897,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6311, f_measure: 0.6696, kappa: 0.2702, kb_relative_information_score: 51.509, mean_absolute_error: 0.3247, mean_prior_absolute_error: 0.4588, number_of_instances: 194, precision: 0.6668, predictive_accuracy: 0.6753, prior_entropy: 0.9403, recall: 0.6753, relative_absolute_error: 0.7079, root_mean_prior_squared_error: 0.4787, root_mean_squared_error: 0.5699, root_relative_squared_error: 1.1904, usercpu_time_millis: 6.979, usercpu_time_millis_testing: 3.139, usercpu_time_millis_training: 3.84,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5232, f_measure: 0.5742, kappa: 0.0508, kb_relative_information_score: 19.9016, mean_absolute_error: 0.3969, mean_prior_absolute_error: 0.4588, number_of_instances: 194, precision: 0.5679, predictive_accuracy: 0.6031, prior_entropy: 0.9403, recall: 0.6031, relative_absolute_error: 0.8652, root_mean_prior_squared_error: 0.4787, root_mean_squared_error: 0.63, root_relative_squared_error: 1.316, usercpu_time_millis: 3.573, usercpu_time_millis_testing: 1.506, usercpu_time_millis_training: 2.067,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5852, f_measure: 0.6328, kappa: 0.1821, kb_relative_information_score: 40.2207, mean_absolute_error: 0.3505, mean_prior_absolute_error: 0.4588, number_of_instances: 194, precision: 0.6303, predictive_accuracy: 0.6495, prior_entropy: 0.9403, recall: 0.6495, relative_absolute_error: 0.764, root_mean_prior_squared_error: 0.4787, root_mean_squared_error: 0.592, root_relative_squared_error: 1.2367, usercpu_time_millis: 2.348, usercpu_time_millis_testing: 0.444, usercpu_time_millis_training: 1.904,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6277, f_measure: 0.6761, kappa: 0.2779, kb_relative_information_score: 60.5397, mean_absolute_error: 0.3041, mean_prior_absolute_error: 0.4588, number_of_instances: 194, precision: 0.6822, predictive_accuracy: 0.6959, prior_entropy: 0.9403, recall: 0.6959, relative_absolute_error: 0.6629, root_mean_prior_squared_error: 0.4787, root_mean_squared_error: 0.5515, root_relative_squared_error: 1.152, usercpu_time_millis: 0.769, usercpu_time_millis_testing: 0.407, usercpu_time_millis_training: 0.362,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6956, f_measure: 0.7178, kappa: 0.3874, kb_relative_information_score: 69.5704, mean_absolute_error: 0.2835, mean_prior_absolute_error: 0.4588, number_of_instances: 194, precision: 0.7194, predictive_accuracy: 0.7165, prior_entropy: 0.9403, recall: 0.7165, relative_absolute_error: 0.618, root_mean_prior_squared_error: 0.4787, root_mean_squared_error: 0.5325, root_relative_squared_error: 1.1122, usercpu_time_millis: 0.774, usercpu_time_millis_testing: 0.373, usercpu_time_millis_training: 0.401,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6536, f_measure: 0.6906, kappa: 0.3165, kb_relative_information_score: 60.5397, mean_absolute_error: 0.3041, mean_prior_absolute_error: 0.4588, number_of_instances: 194, precision: 0.6883, predictive_accuracy: 0.6959, prior_entropy: 0.9403, recall: 0.6959, relative_absolute_error: 0.6629, root_mean_prior_squared_error: 0.4787, root_mean_squared_error: 0.5515, root_relative_squared_error: 1.152, usercpu_time_millis: 0.532, usercpu_time_millis_testing: 0.511, usercpu_time_millis_training: 0.021,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6574, f_measure: 0.7045, kappa: 0.3414, kb_relative_information_score: 71.8281, mean_absolute_error: 0.2784, mean_prior_absolute_error: 0.4588, number_of_instances: 194, precision: 0.7128, predictive_accuracy: 0.7216, prior_entropy: 0.9403, recall: 0.7216, relative_absolute_error: 0.6067, root_mean_prior_squared_error: 0.4787, root_mean_squared_error: 0.5276, root_relative_squared_error: 1.1021, usercpu_time_millis: 0.666, usercpu_time_millis_testing: 0.169, usercpu_time_millis_training: 0.497,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7211, f_measure: 0.7535, kappa: 0.4555, kb_relative_information_score: 87.6318, mean_absolute_error: 0.2423, mean_prior_absolute_error: 0.4588, number_of_instances: 194, precision: 0.7527, predictive_accuracy: 0.7577, prior_entropy: 0.9403, recall: 0.7577, relative_absolute_error: 0.5281, root_mean_prior_squared_error: 0.4787, root_mean_squared_error: 0.4922, root_relative_squared_error: 1.0282, usercpu_time_millis: 420.95, usercpu_time_millis_testing: 31.167, usercpu_time_millis_training: 389.783,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6296, f_measure: 0.6632, kappa: 0.2618, kb_relative_information_score: 46.9937, mean_absolute_error: 0.3351, mean_prior_absolute_error: 0.4588, number_of_instances: 194, precision: 0.6618, predictive_accuracy: 0.6649, prior_entropy: 0.9403, recall: 0.6649, relative_absolute_error: 0.7303, root_mean_prior_squared_error: 0.4787, root_mean_squared_error: 0.5788, root_relative_squared_error: 1.2091, usercpu_time_millis: 6.211, usercpu_time_millis_testing: 2.788, usercpu_time_millis_training: 3.423,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6696, f_measure: 0.7088, kappa: 0.3542, kb_relative_information_score: 69.5704, mean_absolute_error: 0.2835, mean_prior_absolute_error: 0.4588, number_of_instances: 194, precision: 0.7079, predictive_accuracy: 0.7165, prior_entropy: 0.9403, recall: 0.7165, relative_absolute_error: 0.618, root_mean_prior_squared_error: 0.4787, root_mean_squared_error: 0.5325, root_relative_squared_error: 1.1122, usercpu_time_millis: 4.932, usercpu_time_millis_testing: 2.094, usercpu_time_millis_training: 2.838,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6514, f_measure: 0.6804, kappa: 0.3027, kb_relative_information_score: 53.7667, mean_absolute_error: 0.3196, mean_prior_absolute_error: 0.4588, number_of_instances: 194, precision: 0.6804, predictive_accuracy: 0.6804, prior_entropy: 0.9403, recall: 0.6804, relative_absolute_error: 0.6966, root_mean_prior_squared_error: 0.4787, root_mean_squared_error: 0.5653, root_relative_squared_error: 1.1809, usercpu_time_millis: 5.728, usercpu_time_millis_testing: 2.572, usercpu_time_millis_training: 3.156,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7203, f_measure: 0.7499, kappa: 0.4495, kb_relative_information_score: 85.3741, mean_absolute_error: 0.2474, mean_prior_absolute_error: 0.4588, number_of_instances: 194, precision: 0.7486, predictive_accuracy: 0.7526, prior_entropy: 0.9403, recall: 0.7526, relative_absolute_error: 0.5393, root_mean_prior_squared_error: 0.4787, root_mean_squared_error: 0.4974, root_relative_squared_error: 1.0391, usercpu_time_millis: 3.157, usercpu_time_millis_testing: 0.68, usercpu_time_millis_training: 2.477,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.505, kb_relative_information_score: 37.963, mean_absolute_error: 0.3557, mean_prior_absolute_error: 0.4588, number_of_instances: 194, precision: 0.4152, predictive_accuracy: 0.6443, prior_entropy: 0.9403, recall: 0.6443, relative_absolute_error: 0.7753, root_mean_prior_squared_error: 0.4787, root_mean_squared_error: 0.5964, root_relative_squared_error: 1.2458, usercpu_time_millis: 0.715, usercpu_time_millis_testing: 0.154, usercpu_time_millis_training: 0.561,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6516, f_measure: 0.6654, kappa: 0.29, kb_relative_information_score: 44.736, mean_absolute_error: 0.3402, mean_prior_absolute_error: 0.4588, number_of_instances: 194, precision: 0.6777, predictive_accuracy: 0.6598, prior_entropy: 0.9403, recall: 0.6598, relative_absolute_error: 0.7416, root_mean_prior_squared_error: 0.4787, root_mean_squared_error: 0.5833, root_relative_squared_error: 1.2184, usercpu_time_millis: 1.763, usercpu_time_millis_testing: 0.479, usercpu_time_millis_training: 1.284,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6759, f_measure: 0.7219, kappa: 0.3802, kb_relative_information_score: 78.6011, mean_absolute_error: 0.2629, mean_prior_absolute_error: 0.4588, number_of_instances: 194, precision: 0.7307, predictive_accuracy: 0.7371, prior_entropy: 0.9403, recall: 0.7371, relative_absolute_error: 0.573, root_mean_prior_squared_error: 0.4787, root_mean_squared_error: 0.5127, root_relative_squared_error: 1.071, usercpu_time_millis: 24.611, usercpu_time_millis_testing: 1.69, usercpu_time_millis_training: 22.921,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6896, f_measure: 0.7316, kappa: 0.4028, kb_relative_information_score: 80.8588, mean_absolute_error: 0.2577, mean_prior_absolute_error: 0.4588, number_of_instances: 194, precision: 0.7352, predictive_accuracy: 0.7423, prior_entropy: 0.9403, recall: 0.7423, relative_absolute_error: 0.5618, root_mean_prior_squared_error: 0.4787, root_mean_squared_error: 0.5077, root_relative_squared_error: 1.0605, usercpu_time_millis: 65.255, usercpu_time_millis_testing: 3.657, usercpu_time_millis_training: 61.598,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7076, f_measure: 0.732, kappa: 0.4152, kb_relative_information_score: 76.3434, mean_absolute_error: 0.268, mean_prior_absolute_error: 0.4588, number_of_instances: 194, precision: 0.732, predictive_accuracy: 0.732, prior_entropy: 0.9403, recall: 0.732, relative_absolute_error: 0.5843, root_mean_prior_squared_error: 0.4787, root_mean_squared_error: 0.5177, root_relative_squared_error: 1.0815, usercpu_time_millis: 42.502, usercpu_time_millis_testing: 13.935, usercpu_time_millis_training: 28.567,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6826, f_measure: 0.7139, kappa: 0.3712, kb_relative_information_score: 69.5704, mean_absolute_error: 0.2835, mean_prior_absolute_error: 0.4588, number_of_instances: 194, precision: 0.7124, predictive_accuracy: 0.7165, prior_entropy: 0.9403, recall: 0.7165, relative_absolute_error: 0.618, root_mean_prior_squared_error: 0.4787, root_mean_squared_error: 0.5325, root_relative_squared_error: 1.1122, usercpu_time_millis: 9.178, usercpu_time_millis_testing: 1.58, usercpu_time_millis_training: 7.598,

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