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OpenML
OpenML
Supervised Classification on braziltourism

Supervised Classification on braziltourism

Task 3820 Supervised Classification braziltourism 492 runs submitted
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Visibility: Public
  • study_1 study_107 study_41 under100k under1m
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6147, f_measure: 0.7378, kappa: 0.2191, kb_relative_information_score: 2.5163, mean_absolute_error: 0.3005, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.7291, predictive_accuracy: 0.7549, prior_entropy: 0.7771, recall: 0.7549, relative_absolute_error: 0.8515, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.4528, root_relative_squared_error: 1.079, scimark_benchmark: 1324.8395, usercpu_time_millis: 20, usercpu_time_millis_testing: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5825, f_measure: 0.67, kappa: 0.1426, kb_relative_information_score: -52.4327, mean_absolute_error: 0.3495, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.7014, predictive_accuracy: 0.6505, prior_entropy: 0.7771, recall: 0.6505, relative_absolute_error: 0.9904, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.5912, root_relative_squared_error: 1.4088, scimark_benchmark: 1312.3073, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.6725, kb_relative_information_score: 108.4061, mean_absolute_error: 0.2282, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.5957, predictive_accuracy: 0.7718, prior_entropy: 0.7771, recall: 0.7718, relative_absolute_error: 0.6465, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.4777, root_relative_squared_error: 1.1382, scimark_benchmark: 1336.3256, usercpu_time_millis: 70, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5644, f_measure: 0.735, kappa: 0.1821, kb_relative_information_score: 140.5739, mean_absolute_error: 0.2039, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.7993, predictive_accuracy: 0.7961, prior_entropy: 0.7771, recall: 0.7961, relative_absolute_error: 0.5777, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.4515, root_relative_squared_error: 1.076, scimark_benchmark: 1297.6599, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5614, f_measure: 0.7241, kappa: 0.1498, kb_relative_information_score: 11.5905, mean_absolute_error: 0.3357, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.8176, predictive_accuracy: 0.7937, prior_entropy: 0.7771, recall: 0.7937, relative_absolute_error: 0.9511, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.4055, root_relative_squared_error: 0.9662, scimark_benchmark: 887.6719, usercpu_time_millis: 100, usercpu_time_millis_training: 100,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5084, f_measure: 0.64, kappa: 0.0157, kb_relative_information_score: -81.3837, mean_absolute_error: 0.3714, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.6534, predictive_accuracy: 0.6286, prior_entropy: 0.7771, recall: 0.6286, relative_absolute_error: 1.0523, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.6094, root_relative_squared_error: 1.4522, scimark_benchmark: 938.9967, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6828, f_measure: 0.7406, kappa: 0.2077, kb_relative_information_score: 30.146, mean_absolute_error: 0.3021, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.738, predictive_accuracy: 0.7743, prior_entropy: 0.7771, recall: 0.7743, relative_absolute_error: 0.856, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.411, root_relative_squared_error: 0.9795, scimark_benchmark: 918.0213, usercpu_time_millis: 7020, usercpu_time_millis_testing: 60, usercpu_time_millis_training: 6960,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5172, f_measure: 0.6916, kappa: 0.0498, kb_relative_information_score: 105.1894, mean_absolute_error: 0.2306, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.7042, predictive_accuracy: 0.7694, prior_entropy: 0.7771, recall: 0.7694, relative_absolute_error: 0.6534, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.4802, root_relative_squared_error: 1.1443, scimark_benchmark: 918.6491, usercpu_time_millis: 90, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6832, f_measure: 0.7302, kappa: 0.1677, kb_relative_information_score: 32.3567, mean_absolute_error: 0.3027, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.7455, predictive_accuracy: 0.7816, prior_entropy: 0.7771, recall: 0.7816, relative_absolute_error: 0.8578, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.4024, root_relative_squared_error: 0.9588, scimark_benchmark: 1073.494,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.676, f_measure: 0.7441, kappa: 0.2151, kb_relative_information_score: 43.9812, mean_absolute_error: 0.2983, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.7473, predictive_accuracy: 0.7816, prior_entropy: 0.7771, recall: 0.7816, relative_absolute_error: 0.8453, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.4003, root_relative_squared_error: 0.954, scimark_benchmark: 1304.9611,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6863, f_measure: 0.7357, kappa: 0.1871, kb_relative_information_score: 40.2678, mean_absolute_error: 0.2992, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.7415, predictive_accuracy: 0.7791, prior_entropy: 0.7771, recall: 0.7791, relative_absolute_error: 0.8477, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.3998, root_relative_squared_error: 0.9526, scimark_benchmark: 904.2311,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6933, f_measure: 0.7566, kappa: 0.2656, kb_relative_information_score: 40.5905, mean_absolute_error: 0.2882, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.7516, predictive_accuracy: 0.7791, prior_entropy: 0.7771, recall: 0.7791, relative_absolute_error: 0.8165, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.4101, root_relative_squared_error: 0.9773, scimark_benchmark: 1315.0767, usercpu_time_millis: 110, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 100,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6021, f_measure: 0.7287, kappa: 0.2185, kb_relative_information_score: 47.9692, mean_absolute_error: 0.2738, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.725, predictive_accuracy: 0.733, prior_entropy: 0.7771, recall: 0.733, relative_absolute_error: 0.7757, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.5051, root_relative_squared_error: 1.2037, scimark_benchmark: 1307.4861, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6501, f_measure: 0.7451, kappa: 0.2152, kb_relative_information_score: 37.2883, mean_absolute_error: 0.3069, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.7597, predictive_accuracy: 0.7888, prior_entropy: 0.7771, recall: 0.7888, relative_absolute_error: 0.8695, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.4127, root_relative_squared_error: 0.9834, scimark_benchmark: 1361.1055,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.592, f_measure: 0.7506, kappa: 0.2309, kb_relative_information_score: 52.1503, mean_absolute_error: 0.3091, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.7759, predictive_accuracy: 0.7961, prior_entropy: 0.7771, recall: 0.7961, relative_absolute_error: 0.8758, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.4017, root_relative_squared_error: 0.9572, scimark_benchmark: 1327.6929, usercpu_time_millis: 60, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5603, f_measure: 0.7002, kappa: 0.1272, kb_relative_information_score: 24.7699, mean_absolute_error: 0.2913, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.6931, predictive_accuracy: 0.7087, prior_entropy: 0.7771, recall: 0.7087, relative_absolute_error: 0.8253, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.5397, root_relative_squared_error: 1.2861, scimark_benchmark: 1307.4861, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4735, f_measure: 0.5549, kappa: -0.0401, kb_relative_information_score: -229.3555, mean_absolute_error: 0.483, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.6302, predictive_accuracy: 0.517, prior_entropy: 0.7771, recall: 0.517, relative_absolute_error: 1.3686, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.695, root_relative_squared_error: 1.6561, scimark_benchmark: 1337.7959, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6606, f_measure: 0.7403, kappa: 0.2193, kb_relative_information_score: 37.2741, mean_absolute_error: 0.294, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.732, predictive_accuracy: 0.7621, prior_entropy: 0.7771, recall: 0.7621, relative_absolute_error: 0.8331, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.4375, root_relative_squared_error: 1.0425, scimark_benchmark: 1392.1129,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5644, f_measure: 0.735, kappa: 0.1821, kb_relative_information_score: 140.5739, mean_absolute_error: 0.2039, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.7993, predictive_accuracy: 0.7961, prior_entropy: 0.7771, recall: 0.7961, relative_absolute_error: 0.5777, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.4515, root_relative_squared_error: 1.076, scimark_benchmark: 1351.788,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5156, f_measure: 0.6902, kappa: 0.045, kb_relative_information_score: 101.9726, mean_absolute_error: 0.233, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.6952, predictive_accuracy: 0.767, prior_entropy: 0.7771, recall: 0.767, relative_absolute_error: 0.6602, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.4827, root_relative_squared_error: 1.1503, scimark_benchmark: 1353.5686, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4847, f_measure: 0.6725, kb_relative_information_score: -0.9555, mean_absolute_error: 0.353, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.5957, predictive_accuracy: 0.7718, prior_entropy: 0.7771, recall: 0.7718, relative_absolute_error: 1.0003, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.4197, root_relative_squared_error: 1.0001, scimark_benchmark: 1330.0803,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6173, f_measure: 0.7499, kappa: 0.2347, kb_relative_information_score: 44.442, mean_absolute_error: 0.3046, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.7521, predictive_accuracy: 0.784, prior_entropy: 0.7771, recall: 0.784, relative_absolute_error: 0.8632, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.4196, root_relative_squared_error: 0.9999, scimark_benchmark: 1353.5686,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6582, f_measure: 0.7592, kappa: 0.2656, kb_relative_information_score: 124.7591, mean_absolute_error: 0.2168, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.7607, predictive_accuracy: 0.7888, prior_entropy: 0.7771, recall: 0.7888, relative_absolute_error: 0.6142, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.4443, root_relative_squared_error: 1.0586, scimark_benchmark: 927.0753, usercpu_time_millis: 40, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6352, f_measure: 0.7478, kappa: 0.238, kb_relative_information_score: 41.5367, mean_absolute_error: 0.2971, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.7415, predictive_accuracy: 0.7718, prior_entropy: 0.7771, recall: 0.7718, relative_absolute_error: 0.8418, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.4168, root_relative_squared_error: 0.9932, scimark_benchmark: 945.7621, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6359, f_measure: 0.7496, kappa: 0.2428, kb_relative_information_score: 34.421, mean_absolute_error: 0.3043, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.744, predictive_accuracy: 0.7743, prior_entropy: 0.7771, recall: 0.7743, relative_absolute_error: 0.8623, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.4152, root_relative_squared_error: 0.9894, scimark_benchmark: 942.3168, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6359, f_measure: 0.7496, kappa: 0.2428, kb_relative_information_score: 34.421, mean_absolute_error: 0.3043, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.744, predictive_accuracy: 0.7743, prior_entropy: 0.7771, recall: 0.7743, relative_absolute_error: 0.8623, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.4152, root_relative_squared_error: 0.9894, scimark_benchmark: 894.7455, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7088, f_measure: 0.7361, kappa: 0.1853, kb_relative_information_score: 137.0548, mean_absolute_error: 0.2084, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.7828, predictive_accuracy: 0.7937, prior_entropy: 0.7771, recall: 0.7937, relative_absolute_error: 0.5906, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.4357, root_relative_squared_error: 1.0382, scimark_benchmark: 940.2922, usercpu_time_millis: 120, usercpu_time_millis_training: 120,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6957, f_measure: 0.7378, kappa: 0.1906, kb_relative_information_score: 133.5104, mean_absolute_error: 0.2121, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.7926, predictive_accuracy: 0.7961, prior_entropy: 0.7771, recall: 0.7961, relative_absolute_error: 0.6011, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.4343, root_relative_squared_error: 1.0349, scimark_benchmark: 938.2848, usercpu_time_millis: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6871, f_measure: 0.7208, kappa: 0.1392, kb_relative_information_score: 128.6109, mean_absolute_error: 0.2158, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.7849, predictive_accuracy: 0.7888, prior_entropy: 0.7771, recall: 0.7888, relative_absolute_error: 0.6114, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.4447, root_relative_squared_error: 1.0598, scimark_benchmark: 936.6206, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6522, f_measure: 0.7111, kappa: 0.1098, kb_relative_information_score: 126.7364, mean_absolute_error: 0.2178, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.7722, predictive_accuracy: 0.784, prior_entropy: 0.7771, recall: 0.784, relative_absolute_error: 0.6172, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.4476, root_relative_squared_error: 1.0666, scimark_benchmark: 934.5243, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6377, f_measure: 0.692, kappa: 0.0541, kb_relative_information_score: 119.5501, mean_absolute_error: 0.2216, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.7529, predictive_accuracy: 0.7767, prior_entropy: 0.7771, recall: 0.7767, relative_absolute_error: 0.6279, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.4566, root_relative_squared_error: 1.0881, scimark_benchmark: 938.4278, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6778, f_measure: 0.7453, kappa: 0.2372, kb_relative_information_score: 44.7747, mean_absolute_error: 0.2882, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.7374, predictive_accuracy: 0.7646, prior_entropy: 0.7771, recall: 0.7646, relative_absolute_error: 0.8167, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.4218, root_relative_squared_error: 1.0052, scimark_benchmark: 933.8635, usercpu_time_millis: 110, usercpu_time_millis_training: 110,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6907, f_measure: 0.7517, kappa: 0.2457, kb_relative_information_score: 49.643, mean_absolute_error: 0.2876, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.7483, predictive_accuracy: 0.7791, prior_entropy: 0.7771, recall: 0.7791, relative_absolute_error: 0.815, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.4105, root_relative_squared_error: 0.9782, scimark_benchmark: 924.6116, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6001, build_cpu_time: 4.1261, build_memory: 1554764589.4563, f_measure: 0.735, kappa: 0.2034, kb_relative_information_score: 36.8024, mean_absolute_error: 0.2862, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.7259, predictive_accuracy: 0.7573, prior_entropy: 0.7771, recall: 0.7573, relative_absolute_error: 0.8108, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.4621, root_relative_squared_error: 1.1012, scimark_benchmark: 915.8564,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6361, build_cpu_time: 0.0137, build_memory: 936355100.7767, f_measure: 0.7496, kappa: 0.2428, kb_relative_information_score: 34.6105, mean_absolute_error: 0.3043, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.744, predictive_accuracy: 0.7743, prior_entropy: 0.7771, recall: 0.7743, relative_absolute_error: 0.8621, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.4146, root_relative_squared_error: 0.988, scimark_benchmark: 929.5397,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6954, build_cpu_time: 3.9332, build_memory: 29779251.5922, f_measure: 0.7317, kappa: 0.1894, kb_relative_information_score: 54.4052, mean_absolute_error: 0.2703, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.7223, predictive_accuracy: 0.7573, prior_entropy: 0.7771, recall: 0.7573, relative_absolute_error: 0.7658, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.4304, root_relative_squared_error: 1.0256, scimark_benchmark: 899.4388,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6368, build_cpu_time: 31.3542, build_memory: 32095408.6019, f_measure: 0.7186, kappa: 0.1643, kb_relative_information_score: 60.8376, mean_absolute_error: 0.2633, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.7083, predictive_accuracy: 0.7354, prior_entropy: 0.7771, recall: 0.7354, relative_absolute_error: 0.7461, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.4908, root_relative_squared_error: 1.1697, scimark_benchmark: 899.4388,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6083, build_cpu_time: 42.608, build_memory: 1509861059.1845, f_measure: 0.7295, kappa: 0.2165, kb_relative_information_score: 59.5727, mean_absolute_error: 0.2652, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.7245, predictive_accuracy: 0.7354, prior_entropy: 0.7771, recall: 0.7354, relative_absolute_error: 0.7514, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.5132, root_relative_squared_error: 1.2229, scimark_benchmark: 931.9671,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5985, build_cpu_time: 20.507, build_memory: 144353237.6893, f_measure: 0.7177, kappa: 0.1838, kb_relative_information_score: 44.544, mean_absolute_error: 0.2763, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.7129, predictive_accuracy: 0.7233, prior_entropy: 0.7771, recall: 0.7233, relative_absolute_error: 0.7829, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.521, root_relative_squared_error: 1.2414, scimark_benchmark: 935.1241,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6082, build_cpu_time: 10.3481, build_memory: 1782885906.835, f_measure: 0.7189, kappa: 0.1901, kb_relative_information_score: 43.1396, mean_absolute_error: 0.2771, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.715, predictive_accuracy: 0.7233, prior_entropy: 0.7771, recall: 0.7233, relative_absolute_error: 0.785, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.5226, root_relative_squared_error: 1.2454, scimark_benchmark: 916.8903,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6717, build_cpu_time: 2.7804, build_memory: 180946247.165, f_measure: 0.7195, kappa: 0.2065, kb_relative_information_score: 37.3026, mean_absolute_error: 0.2793, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.7206, predictive_accuracy: 0.7184, prior_entropy: 0.7771, recall: 0.7184, relative_absolute_error: 0.7913, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.5069, root_relative_squared_error: 1.2079, scimark_benchmark: 902.712,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6684, build_cpu_time: 1.0917, build_memory: 245238625.6699, f_measure: 0.7396, kappa: 0.2358, kb_relative_information_score: 53.3708, mean_absolute_error: 0.2711, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.7325, predictive_accuracy: 0.75, prior_entropy: 0.7771, recall: 0.75, relative_absolute_error: 0.7681, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.4437, root_relative_squared_error: 1.0573, scimark_benchmark: 922.3661,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6807, build_cpu_time: 1.8195, build_memory: 240245635.068, f_measure: 0.732, kappa: 0.2187, kb_relative_information_score: 63.4207, mean_absolute_error: 0.2608, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.7258, predictive_accuracy: 0.7403, prior_entropy: 0.7771, recall: 0.7403, relative_absolute_error: 0.7391, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.4545, root_relative_squared_error: 1.0831, scimark_benchmark: 945.0532,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6916, build_cpu_time: 3.0846, build_memory: 954758192.835, f_measure: 0.7332, kappa: 0.2146, kb_relative_information_score: 63.2354, mean_absolute_error: 0.2604, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.7253, predictive_accuracy: 0.7451, prior_entropy: 0.7771, recall: 0.7451, relative_absolute_error: 0.7377, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.4722, root_relative_squared_error: 1.1252, scimark_benchmark: 924.2473,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7011, build_cpu_time: 0.1204, build_memory: 956911723.9612, f_measure: 0.7567, kappa: 0.2763, kb_relative_information_score: 54.9594, mean_absolute_error: 0.2792, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.7498, predictive_accuracy: 0.7718, prior_entropy: 0.7771, recall: 0.7718, relative_absolute_error: 0.7911, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.4207, root_relative_squared_error: 1.0026, scimark_benchmark: 937.5625,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7011, build_cpu_time: 0.1051, build_memory: 703452295.5534, f_measure: 0.7567, kappa: 0.2763, kb_relative_information_score: 54.9594, mean_absolute_error: 0.2792, mean_prior_absolute_error: 0.3529, number_of_instances: 412, precision: 0.7498, predictive_accuracy: 0.7718, prior_entropy: 0.7771, recall: 0.7718, relative_absolute_error: 0.7911, root_mean_prior_squared_error: 0.4196, root_mean_squared_error: 0.4207, root_relative_squared_error: 1.0026, scimark_benchmark: 917.4547,

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