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Function: require_once

OpenML
Task
Supervised Classification on chscase_census4

Supervised Classification on chscase_census4

Task 3770 Supervised Classification chscase_census4 547 runs submitted
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Visibility: Public
  • study_1 study_107 study_41 study_7 under100k under1m
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4771, f_measure: 0.4974, kappa: -0.0036, kb_relative_information_score: -11.2872, mean_absolute_error: 0.515, mean_prior_absolute_error: 0.4996, number_of_instances: 400, precision: 0.4986, predictive_accuracy: 0.4975, prior_entropy: 0.9994, recall: 0.4975, relative_absolute_error: 1.0309, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.5923, root_relative_squared_error: 1.185, scimark_benchmark: 1363.454, usercpu_time_millis: 20, usercpu_time_millis_testing: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5027, f_measure: 0.36, kappa: 0.0056, kb_relative_information_score: 13.5007, mean_absolute_error: 0.4825, mean_prior_absolute_error: 0.4996, number_of_instances: 400, precision: 0.5893, predictive_accuracy: 0.5175, prior_entropy: 0.9994, recall: 0.5175, relative_absolute_error: 0.9659, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.6946, root_relative_squared_error: 1.3899, scimark_benchmark: 1313.9994, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.3501, kb_relative_information_score: 11.4982, mean_absolute_error: 0.485, mean_prior_absolute_error: 0.4996, number_of_instances: 400, precision: 0.2652, predictive_accuracy: 0.515, prior_entropy: 0.9994, recall: 0.515, relative_absolute_error: 0.9709, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.6964, root_relative_squared_error: 1.3935, scimark_benchmark: 1333.5799, usercpu_time_millis: 70, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4862, f_measure: 0.413, kappa: -0.0283, kb_relative_information_score: -2.5198, mean_absolute_error: 0.5025, mean_prior_absolute_error: 0.4996, number_of_instances: 400, precision: 0.469, predictive_accuracy: 0.4975, prior_entropy: 0.9994, recall: 0.4975, relative_absolute_error: 1.0059, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.7089, root_relative_squared_error: 1.4184, scimark_benchmark: 1337.7959,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4738, f_measure: 0.3867, kappa: -0.0311, kb_relative_information_score: -2.0411, mean_absolute_error: 0.5014, mean_prior_absolute_error: 0.4996, number_of_instances: 400, precision: 0.4487, predictive_accuracy: 0.4975, prior_entropy: 0.9994, recall: 0.4975, relative_absolute_error: 1.0038, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.5023, root_relative_squared_error: 1.005, scimark_benchmark: 1335.643, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5016, f_measure: 0.4985, kappa: 0.0031, kb_relative_information_score: 3.4879, mean_absolute_error: 0.495, mean_prior_absolute_error: 0.4996, number_of_instances: 400, precision: 0.5021, predictive_accuracy: 0.505, prior_entropy: 0.9994, recall: 0.505, relative_absolute_error: 0.9909, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.7036, root_relative_squared_error: 1.4078, scimark_benchmark: 940.3347, usercpu_time_millis: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4799, f_measure: 0.4648, kappa: -0.0664, kb_relative_information_score: -1.9124, mean_absolute_error: 0.5012, mean_prior_absolute_error: 0.4996, number_of_instances: 400, precision: 0.4663, predictive_accuracy: 0.47, prior_entropy: 0.9994, recall: 0.47, relative_absolute_error: 1.0033, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.5126, root_relative_squared_error: 1.0256, scimark_benchmark: 915.9324, usercpu_time_millis: 7130, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 7110,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4793, f_measure: 0.4461, kappa: -0.042, kb_relative_information_score: -10.5301, mean_absolute_error: 0.5125, mean_prior_absolute_error: 0.4996, number_of_instances: 400, precision: 0.4715, predictive_accuracy: 0.4875, prior_entropy: 0.9994, recall: 0.4875, relative_absolute_error: 1.0259, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.7159, root_relative_squared_error: 1.4324, scimark_benchmark: 934.0566, usercpu_time_millis: 110, usercpu_time_millis_testing: 50, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.488, f_measure: 0.3501, kb_relative_information_score: -0.0384, mean_absolute_error: 0.4996, mean_prior_absolute_error: 0.4996, number_of_instances: 400, precision: 0.2652, predictive_accuracy: 0.515, prior_entropy: 0.9994, recall: 0.515, relative_absolute_error: 1.0001, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.4998, root_relative_squared_error: 1.0001, scimark_benchmark: 1073.494,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.488, f_measure: 0.3501, kb_relative_information_score: -0.0384, mean_absolute_error: 0.4996, mean_prior_absolute_error: 0.4996, number_of_instances: 400, precision: 0.2652, predictive_accuracy: 0.515, prior_entropy: 0.9994, recall: 0.515, relative_absolute_error: 1.0001, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.4998, root_relative_squared_error: 1.0001, scimark_benchmark: 918.6491, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.488, f_measure: 0.3501, kb_relative_information_score: -0.0384, mean_absolute_error: 0.4996, mean_prior_absolute_error: 0.4996, number_of_instances: 400, precision: 0.2652, predictive_accuracy: 0.515, prior_entropy: 0.9994, recall: 0.515, relative_absolute_error: 1.0001, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.4998, root_relative_squared_error: 1.0001, scimark_benchmark: 934.0566, usercpu_time_millis: 20, usercpu_time_millis_testing: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.488, f_measure: 0.3501, kb_relative_information_score: -0.0397, mean_absolute_error: 0.4996, mean_prior_absolute_error: 0.4996, number_of_instances: 400, precision: 0.2652, predictive_accuracy: 0.515, prior_entropy: 0.9994, recall: 0.515, relative_absolute_error: 1.0001, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.4998, root_relative_squared_error: 1.0001, scimark_benchmark: 890.2894, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4945, f_measure: 0.5043, kappa: 0.0076, kb_relative_information_score: -1.9608, mean_absolute_error: 0.5016, mean_prior_absolute_error: 0.4996, number_of_instances: 400, precision: 0.5043, predictive_accuracy: 0.505, prior_entropy: 0.9994, recall: 0.505, relative_absolute_error: 1.0041, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.5184, root_relative_squared_error: 1.0373, scimark_benchmark: 825.5282, usercpu_time_millis: 180, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 160,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4921, f_measure: 0.4925, kappa: -0.0158, kb_relative_information_score: -6.525, mean_absolute_error: 0.5075, mean_prior_absolute_error: 0.4996, number_of_instances: 400, precision: 0.4926, predictive_accuracy: 0.4925, prior_entropy: 0.9994, recall: 0.4925, relative_absolute_error: 1.0159, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.7124, root_relative_squared_error: 1.4254, scimark_benchmark: 1319.9043,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5017, f_measure: 0.4776, kappa: -0.0448, kb_relative_information_score: -0.1223, mean_absolute_error: 0.498, mean_prior_absolute_error: 0.4996, number_of_instances: 400, precision: 0.478, predictive_accuracy: 0.4775, prior_entropy: 0.9994, recall: 0.4775, relative_absolute_error: 0.9969, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.5513, root_relative_squared_error: 1.1031, scimark_benchmark: 1066.7184,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4854, f_measure: 0.483, kappa: -0.0152, kb_relative_information_score: -3.9974, mean_absolute_error: 0.5043, mean_prior_absolute_error: 0.4996, number_of_instances: 400, precision: 0.4921, predictive_accuracy: 0.4975, prior_entropy: 0.9994, recall: 0.4975, relative_absolute_error: 1.0095, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.5563, root_relative_squared_error: 1.113, scimark_benchmark: 1354.2491, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5038, f_measure: 0.5017, kappa: 0.0075, kb_relative_information_score: 1.4853, mean_absolute_error: 0.4975, mean_prior_absolute_error: 0.4996, number_of_instances: 400, precision: 0.5043, predictive_accuracy: 0.5025, prior_entropy: 0.9994, recall: 0.5025, relative_absolute_error: 0.9959, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.7053, root_relative_squared_error: 1.4113, scimark_benchmark: 1341.5768, usercpu_time_millis: 40, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5012, f_measure: 0.4305, kappa: 0.0024, kb_relative_information_score: 9.4956, mean_absolute_error: 0.4875, mean_prior_absolute_error: 0.4996, number_of_instances: 400, precision: 0.5031, predictive_accuracy: 0.5125, prior_entropy: 0.9994, recall: 0.5125, relative_absolute_error: 0.9759, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.6982, root_relative_squared_error: 1.3971, scimark_benchmark: 1287.514, usercpu_time_millis: 50, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.488, f_measure: 0.3501, kb_relative_information_score: -0.037, mean_absolute_error: 0.4996, mean_prior_absolute_error: 0.4996, number_of_instances: 400, precision: 0.2652, predictive_accuracy: 0.515, prior_entropy: 0.9994, recall: 0.515, relative_absolute_error: 1.0001, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.4998, root_relative_squared_error: 1.0001, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4877, f_measure: 0.4876, kappa: -0.0245, kb_relative_information_score: -10.5301, mean_absolute_error: 0.5125, mean_prior_absolute_error: 0.4996, number_of_instances: 400, precision: 0.4882, predictive_accuracy: 0.4875, prior_entropy: 0.9994, recall: 0.4875, relative_absolute_error: 1.0259, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.7159, root_relative_squared_error: 1.4324, scimark_benchmark: 1351.788,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4908, f_measure: 0.485, kappa: -0.0186, kb_relative_information_score: -4.5224, mean_absolute_error: 0.505, mean_prior_absolute_error: 0.4996, number_of_instances: 400, precision: 0.4906, predictive_accuracy: 0.495, prior_entropy: 0.9994, recall: 0.495, relative_absolute_error: 1.0109, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.7106, root_relative_squared_error: 1.4219, scimark_benchmark: 1353.5686,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.488, f_measure: 0.3501, kb_relative_information_score: -0.0397, mean_absolute_error: 0.4996, mean_prior_absolute_error: 0.4996, number_of_instances: 400, precision: 0.2652, predictive_accuracy: 0.515, prior_entropy: 0.9994, recall: 0.515, relative_absolute_error: 1.0001, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.4998, root_relative_squared_error: 1.0001, scimark_benchmark: 1380.2233,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.488, f_measure: 0.3501, kb_relative_information_score: -0.037, mean_absolute_error: 0.4996, mean_prior_absolute_error: 0.4996, number_of_instances: 400, precision: 0.2652, predictive_accuracy: 0.515, prior_entropy: 0.9994, recall: 0.515, relative_absolute_error: 1.0001, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.4998, root_relative_squared_error: 1.0001, scimark_benchmark: 1353.5686,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.467, f_measure: 0.4791, kappa: -0.0121, kb_relative_information_score: -5.6623, mean_absolute_error: 0.5057, mean_prior_absolute_error: 0.4996, number_of_instances: 400, precision: 0.4934, predictive_accuracy: 0.5, prior_entropy: 0.9994, recall: 0.5, relative_absolute_error: 1.0123, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.5168, root_relative_squared_error: 1.034, scimark_benchmark: 927.0753, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4766, f_measure: 0.4914, kappa: 0.0173, kb_relative_information_score: -0.9926, mean_absolute_error: 0.5009, mean_prior_absolute_error: 0.4996, number_of_instances: 400, precision: 0.5108, predictive_accuracy: 0.515, prior_entropy: 0.9994, recall: 0.515, relative_absolute_error: 1.0027, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.5062, root_relative_squared_error: 1.0128, scimark_benchmark: 945.6434,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4766, f_measure: 0.4914, kappa: 0.0173, kb_relative_information_score: -0.9926, mean_absolute_error: 0.5009, mean_prior_absolute_error: 0.4996, number_of_instances: 400, precision: 0.5108, predictive_accuracy: 0.515, prior_entropy: 0.9994, recall: 0.515, relative_absolute_error: 1.0027, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.5062, root_relative_squared_error: 1.0128, scimark_benchmark: 941.7954, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4766, f_measure: 0.4914, kappa: 0.0173, kb_relative_information_score: -0.9926, mean_absolute_error: 0.5009, mean_prior_absolute_error: 0.4996, number_of_instances: 400, precision: 0.5108, predictive_accuracy: 0.515, prior_entropy: 0.9994, recall: 0.515, relative_absolute_error: 1.0027, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.5062, root_relative_squared_error: 1.0128, scimark_benchmark: 945.6434, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4766, f_measure: 0.4914, kappa: 0.0173, kb_relative_information_score: -0.9926, mean_absolute_error: 0.5009, mean_prior_absolute_error: 0.4996, number_of_instances: 400, precision: 0.5108, predictive_accuracy: 0.515, prior_entropy: 0.9994, recall: 0.515, relative_absolute_error: 1.0027, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.5062, root_relative_squared_error: 1.0128, scimark_benchmark: 894.7455, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4048, f_measure: 0.4493, kappa: -0.093, kb_relative_information_score: -30.0495, mean_absolute_error: 0.5352, mean_prior_absolute_error: 0.4996, number_of_instances: 400, precision: 0.4517, predictive_accuracy: 0.4575, prior_entropy: 0.9994, recall: 0.4575, relative_absolute_error: 1.0713, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.5853, root_relative_squared_error: 1.1711, scimark_benchmark: 940.2922, usercpu_time_millis: 210, usercpu_time_millis_training: 210,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3897, f_measure: 0.4461, kappa: -0.1056, kb_relative_information_score: -36.2295, mean_absolute_error: 0.5406, mean_prior_absolute_error: 0.4996, number_of_instances: 400, precision: 0.4466, predictive_accuracy: 0.45, prior_entropy: 0.9994, recall: 0.45, relative_absolute_error: 1.0821, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.5777, root_relative_squared_error: 1.156, scimark_benchmark: 938.2848, usercpu_time_millis: 100, usercpu_time_millis_training: 100,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.39, f_measure: 0.4451, kappa: -0.1063, kb_relative_information_score: -32.3364, mean_absolute_error: 0.5362, mean_prior_absolute_error: 0.4996, number_of_instances: 400, precision: 0.4459, predictive_accuracy: 0.45, prior_entropy: 0.9994, recall: 0.45, relative_absolute_error: 1.0735, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.5689, root_relative_squared_error: 1.1384, scimark_benchmark: 936.6206, usercpu_time_millis: 60, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4045, f_measure: 0.4679, kappa: -0.0642, kb_relative_information_score: -26.8024, mean_absolute_error: 0.5288, mean_prior_absolute_error: 0.4996, number_of_instances: 400, precision: 0.4681, predictive_accuracy: 0.47, prior_entropy: 0.9994, recall: 0.47, relative_absolute_error: 1.0586, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.5513, root_relative_squared_error: 1.1031, scimark_benchmark: 922.9039, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.387, f_measure: 0.4267, kappa: -0.1344, kb_relative_information_score: -22.8754, mean_absolute_error: 0.5235, mean_prior_absolute_error: 0.4996, number_of_instances: 400, precision: 0.429, predictive_accuracy: 0.4375, prior_entropy: 0.9994, recall: 0.4375, relative_absolute_error: 1.0479, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.5394, root_relative_squared_error: 1.0794, scimark_benchmark: 938.4285, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5378, build_cpu_time: 7.5304, build_memory: 21154445.6, f_measure: 0.5451, kappa: 0.0895, kb_relative_information_score: 13.9486, mean_absolute_error: 0.4847, mean_prior_absolute_error: 0.4996, number_of_instances: 400, precision: 0.5451, predictive_accuracy: 0.545, prior_entropy: 0.9994, recall: 0.545, relative_absolute_error: 0.9704, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.5485, root_relative_squared_error: 1.0975, scimark_benchmark: 929.5397,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5246, build_cpu_time: 0.0614, build_memory: 1483023920.8, f_measure: 0.5215, kappa: 0.0486, kb_relative_information_score: 4.5605, mean_absolute_error: 0.4952, mean_prior_absolute_error: 0.4996, number_of_instances: 400, precision: 0.5257, predictive_accuracy: 0.5275, prior_entropy: 0.9994, recall: 0.5275, relative_absolute_error: 0.9914, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.518, root_relative_squared_error: 1.0365, scimark_benchmark: 922.3661,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5115, build_cpu_time: 0.0396, build_memory: 181615471.2, f_measure: 0.5294, kappa: 0.0638, kb_relative_information_score: 1.1491, mean_absolute_error: 0.4989, mean_prior_absolute_error: 0.4996, number_of_instances: 400, precision: 0.5335, predictive_accuracy: 0.535, prior_entropy: 0.9994, recall: 0.535, relative_absolute_error: 0.9987, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.5189, root_relative_squared_error: 1.0383, scimark_benchmark: 945.0532,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.488, build_cpu_time: 0.0029, build_memory: 757621496, f_measure: 0.3501, kb_relative_information_score: -0.037, mean_absolute_error: 0.4996, mean_prior_absolute_error: 0.4996, number_of_instances: 400, precision: 0.2652, predictive_accuracy: 0.515, prior_entropy: 0.9994, recall: 0.515, relative_absolute_error: 1.0001, root_mean_prior_squared_error: 0.4998, root_mean_squared_error: 0.4998, root_relative_squared_error: 1.0001, scimark_benchmark: 935.6292,
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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