Task
Supervised Classification on chscase_census2

Supervised Classification on chscase_census2

Task 4477 Supervised Classification chscase_census2 226 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4874, f_measure: 0.4116, kappa: -0.0049, kb_relative_information_score: -8.9286, mean_absolute_error: 0.501, mean_prior_absolute_error: 0.4999, number_of_instances: 4000, precision: 0.4938, predictive_accuracy: 0.5035, prior_entropy: 0.9998, recall: 0.5035, relative_absolute_error: 1.0021, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.502, root_relative_squared_error: 1.004, scimark_benchmark: 906.0979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5395, f_measure: 0.518, kappa: 0.0492, kb_relative_information_score: 95.4974, mean_absolute_error: 0.4895, mean_prior_absolute_error: 0.4999, number_of_instances: 4000, precision: 0.5264, predictive_accuracy: 0.5265, prior_entropy: 0.9998, recall: 0.5265, relative_absolute_error: 0.9792, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5078, root_relative_squared_error: 1.0157, scimark_benchmark: 972.587, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.54, f_measure: 0.515, kappa: 0.0419, kb_relative_information_score: 149.3075, mean_absolute_error: 0.4827, mean_prior_absolute_error: 0.4999, number_of_instances: 4000, precision: 0.5223, predictive_accuracy: 0.5228, prior_entropy: 0.9998, recall: 0.5228, relative_absolute_error: 0.9657, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5253, root_relative_squared_error: 1.0507, scimark_benchmark: 934.3687, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5254, f_measure: 0.5046, kappa: 0.0512, kb_relative_information_score: 228.7817, mean_absolute_error: 0.4713, mean_prior_absolute_error: 0.4999, number_of_instances: 4000, precision: 0.5315, predictive_accuracy: 0.5288, prior_entropy: 0.9998, recall: 0.5288, relative_absolute_error: 0.9427, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.6865, root_relative_squared_error: 1.3731, scimark_benchmark: 901.4991,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5254, f_measure: 0.5046, kappa: 0.0512, kb_relative_information_score: 228.7817, mean_absolute_error: 0.4713, mean_prior_absolute_error: 0.4999, number_of_instances: 4000, precision: 0.5315, predictive_accuracy: 0.5288, prior_entropy: 0.9998, recall: 0.5288, relative_absolute_error: 0.9427, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.6865, root_relative_squared_error: 1.3731, scimark_benchmark: 916.0735, usercpu_time_millis: 70, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4874, f_measure: 0.4116, kappa: -0.0049, kb_relative_information_score: -8.5522, mean_absolute_error: 0.5009, mean_prior_absolute_error: 0.4999, number_of_instances: 4000, precision: 0.4938, predictive_accuracy: 0.5035, prior_entropy: 0.9998, recall: 0.5035, relative_absolute_error: 1.002, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5018, root_relative_squared_error: 1.0037, scimark_benchmark: 941.6675,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4874, f_measure: 0.4116, kappa: -0.0049, kb_relative_information_score: -8.5522, mean_absolute_error: 0.5009, mean_prior_absolute_error: 0.4999, number_of_instances: 4000, precision: 0.4938, predictive_accuracy: 0.5035, prior_entropy: 0.9998, recall: 0.5035, relative_absolute_error: 1.002, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5018, root_relative_squared_error: 1.0037, scimark_benchmark: 941.6675,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4874, f_measure: 0.4116, kappa: -0.0049, kb_relative_information_score: -8.5522, mean_absolute_error: 0.5009, mean_prior_absolute_error: 0.4999, number_of_instances: 4000, precision: 0.4938, predictive_accuracy: 0.5035, prior_entropy: 0.9998, recall: 0.5035, relative_absolute_error: 1.002, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5018, root_relative_squared_error: 1.0037, scimark_benchmark: 941.6675,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5309, f_measure: 0.517, kappa: 0.0338, kb_relative_information_score: 80.1632, mean_absolute_error: 0.4914, mean_prior_absolute_error: 0.4999, number_of_instances: 4000, precision: 0.517, predictive_accuracy: 0.5173, prior_entropy: 0.9998, recall: 0.5173, relative_absolute_error: 0.983, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5148, root_relative_squared_error: 1.0297, scimark_benchmark: 941.6675, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4891, f_measure: 0.5034, kappa: 0.0066, kb_relative_information_score: -32.1482, mean_absolute_error: 0.5034, mean_prior_absolute_error: 0.4999, number_of_instances: 4000, precision: 0.5034, predictive_accuracy: 0.5035, prior_entropy: 0.9998, recall: 0.5035, relative_absolute_error: 1.0071, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5148, root_relative_squared_error: 1.0297, scimark_benchmark: 932.2692, usercpu_time_millis: 8780, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 8750,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4971, f_measure: 0.4993, kappa: 0.0044, kb_relative_information_score: 16.8643, mean_absolute_error: 0.4979, mean_prior_absolute_error: 0.4999, number_of_instances: 4000, precision: 0.5023, predictive_accuracy: 0.5013, prior_entropy: 0.9998, recall: 0.5013, relative_absolute_error: 0.996, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.504, root_relative_squared_error: 1.0082, scimark_benchmark: 905.2959,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5254, f_measure: 0.5046, kappa: 0.0512, kb_relative_information_score: 228.7817, mean_absolute_error: 0.4713, mean_prior_absolute_error: 0.4999, number_of_instances: 4000, precision: 0.5315, predictive_accuracy: 0.5288, prior_entropy: 0.9998, recall: 0.5288, relative_absolute_error: 0.9427, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.6865, root_relative_squared_error: 1.3731, scimark_benchmark: 936.3373, usercpu_time_millis: 60, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5254, f_measure: 0.5046, kappa: 0.0512, kb_relative_information_score: 228.7817, mean_absolute_error: 0.4713, mean_prior_absolute_error: 0.4999, number_of_instances: 4000, precision: 0.5315, predictive_accuracy: 0.5288, prior_entropy: 0.9998, recall: 0.5288, relative_absolute_error: 0.9427, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.6865, root_relative_squared_error: 1.3731, scimark_benchmark: 944.1783, usercpu_time_millis: 70, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4874, f_measure: 0.4116, kappa: -0.0049, kb_relative_information_score: -8.5522, mean_absolute_error: 0.5009, mean_prior_absolute_error: 0.4999, number_of_instances: 4000, precision: 0.4938, predictive_accuracy: 0.5035, prior_entropy: 0.9998, recall: 0.5035, relative_absolute_error: 1.002, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5018, root_relative_squared_error: 1.0037, scimark_benchmark: 941.3847,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4874, f_measure: 0.4116, kappa: -0.0049, kb_relative_information_score: -8.5522, mean_absolute_error: 0.5009, mean_prior_absolute_error: 0.4999, number_of_instances: 4000, precision: 0.4938, predictive_accuracy: 0.5035, prior_entropy: 0.9998, recall: 0.5035, relative_absolute_error: 1.002, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5018, root_relative_squared_error: 1.0037, scimark_benchmark: 947.1781, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5363, f_measure: 0.5172, kappa: 0.0343, kb_relative_information_score: 102.6182, mean_absolute_error: 0.4886, mean_prior_absolute_error: 0.4999, number_of_instances: 4000, precision: 0.5172, predictive_accuracy: 0.5173, prior_entropy: 0.9998, recall: 0.5173, relative_absolute_error: 0.9775, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5091, root_relative_squared_error: 1.0183, scimark_benchmark: 937.5117, usercpu_time_millis: 150, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 130,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4874, f_measure: 0.4116, kappa: -0.0049, kb_relative_information_score: -8.9286, mean_absolute_error: 0.501, mean_prior_absolute_error: 0.4999, number_of_instances: 4000, precision: 0.4938, predictive_accuracy: 0.5035, prior_entropy: 0.9998, recall: 0.5035, relative_absolute_error: 1.0021, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.502, root_relative_squared_error: 1.004, scimark_benchmark: 942.2392,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5395, f_measure: 0.518, kappa: 0.0492, kb_relative_information_score: 95.4974, mean_absolute_error: 0.4895, mean_prior_absolute_error: 0.4999, number_of_instances: 4000, precision: 0.5264, predictive_accuracy: 0.5265, prior_entropy: 0.9998, recall: 0.5265, relative_absolute_error: 0.9792, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5078, root_relative_squared_error: 1.0157, scimark_benchmark: 908.9569, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.54, f_measure: 0.515, kappa: 0.0419, kb_relative_information_score: 149.3075, mean_absolute_error: 0.4827, mean_prior_absolute_error: 0.4999, number_of_instances: 4000, precision: 0.5223, predictive_accuracy: 0.5228, prior_entropy: 0.9998, recall: 0.5228, relative_absolute_error: 0.9657, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5253, root_relative_squared_error: 1.0507, scimark_benchmark: 938.1282, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5254, f_measure: 0.5046, kappa: 0.0512, kb_relative_information_score: 228.7817, mean_absolute_error: 0.4713, mean_prior_absolute_error: 0.4999, number_of_instances: 4000, precision: 0.5315, predictive_accuracy: 0.5288, prior_entropy: 0.9998, recall: 0.5288, relative_absolute_error: 0.9427, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.6865, root_relative_squared_error: 1.3731, scimark_benchmark: 904.5548, usercpu_time_millis: 70, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4874, f_measure: 0.4116, kappa: -0.0049, kb_relative_information_score: -8.5522, mean_absolute_error: 0.5009, mean_prior_absolute_error: 0.4999, number_of_instances: 4000, precision: 0.4938, predictive_accuracy: 0.5035, prior_entropy: 0.9998, recall: 0.5035, relative_absolute_error: 1.002, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5018, root_relative_squared_error: 1.0037, scimark_benchmark: 930.404,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4874, f_measure: 0.4116, kappa: -0.0049, kb_relative_information_score: -8.5522, mean_absolute_error: 0.5009, mean_prior_absolute_error: 0.4999, number_of_instances: 4000, precision: 0.4938, predictive_accuracy: 0.5035, prior_entropy: 0.9998, recall: 0.5035, relative_absolute_error: 1.002, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5018, root_relative_squared_error: 1.0037, scimark_benchmark: 930.404,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4874, f_measure: 0.4116, kappa: -0.0049, kb_relative_information_score: -8.5522, mean_absolute_error: 0.5009, mean_prior_absolute_error: 0.4999, number_of_instances: 4000, precision: 0.4938, predictive_accuracy: 0.5035, prior_entropy: 0.9998, recall: 0.5035, relative_absolute_error: 1.002, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5018, root_relative_squared_error: 1.0037, scimark_benchmark: 930.404,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4874, f_measure: 0.4116, kappa: -0.0049, kb_relative_information_score: -8.5522, mean_absolute_error: 0.5009, mean_prior_absolute_error: 0.4999, number_of_instances: 4000, precision: 0.4938, predictive_accuracy: 0.5035, prior_entropy: 0.9998, recall: 0.5035, relative_absolute_error: 1.002, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5018, root_relative_squared_error: 1.0037, scimark_benchmark: 903.2737,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5309, f_measure: 0.517, kappa: 0.0338, kb_relative_information_score: 80.1632, mean_absolute_error: 0.4914, mean_prior_absolute_error: 0.4999, number_of_instances: 4000, precision: 0.517, predictive_accuracy: 0.5173, prior_entropy: 0.9998, recall: 0.5173, relative_absolute_error: 0.983, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5148, root_relative_squared_error: 1.0297, scimark_benchmark: 941.4991, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4891, f_measure: 0.5034, kappa: 0.0066, kb_relative_information_score: -32.1482, mean_absolute_error: 0.5034, mean_prior_absolute_error: 0.4999, number_of_instances: 4000, precision: 0.5034, predictive_accuracy: 0.5035, prior_entropy: 0.9998, recall: 0.5035, relative_absolute_error: 1.0071, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5148, root_relative_squared_error: 1.0297, scimark_benchmark: 938.4601, usercpu_time_millis: 6550, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 6520,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4874, f_measure: 0.4116, kappa: -0.0049, kb_relative_information_score: -8.5522, mean_absolute_error: 0.5009, mean_prior_absolute_error: 0.4999, number_of_instances: 4000, precision: 0.4938, predictive_accuracy: 0.5035, prior_entropy: 0.9998, recall: 0.5035, relative_absolute_error: 1.002, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5018, root_relative_squared_error: 1.0037, scimark_benchmark: 945.6228, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4971, f_measure: 0.4993, kappa: 0.0044, kb_relative_information_score: 16.8643, mean_absolute_error: 0.4979, mean_prior_absolute_error: 0.4999, number_of_instances: 4000, precision: 0.5023, predictive_accuracy: 0.5013, prior_entropy: 0.9998, recall: 0.5013, relative_absolute_error: 0.996, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.504, root_relative_squared_error: 1.0082, scimark_benchmark: 945.6228, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5363, f_measure: 0.5172, kappa: 0.0343, kb_relative_information_score: 102.6182, mean_absolute_error: 0.4886, mean_prior_absolute_error: 0.4999, number_of_instances: 4000, precision: 0.5172, predictive_accuracy: 0.5173, prior_entropy: 0.9998, recall: 0.5173, relative_absolute_error: 0.9775, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5091, root_relative_squared_error: 1.0183, scimark_benchmark: 938.988, usercpu_time_millis: 190, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 160,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5021, f_measure: 0.4684, kappa: -0.0021, kb_relative_information_score: 3.3782, mean_absolute_error: 0.4996, mean_prior_absolute_error: 0.4999, number_of_instances: 4000, precision: 0.4987, predictive_accuracy: 0.5028, prior_entropy: 0.9998, recall: 0.5028, relative_absolute_error: 0.9994, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4999, root_relative_squared_error: 1, scimark_benchmark: 943.6618, usercpu_time_millis: 1140, usercpu_time_millis_testing: 520, usercpu_time_millis_training: 620,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.497, f_measure: 0.4762, kappa: 0.0077, kb_relative_information_score: 2.5897, mean_absolute_error: 0.4997, mean_prior_absolute_error: 0.4999, number_of_instances: 4000, precision: 0.5051, predictive_accuracy: 0.5075, prior_entropy: 0.9998, recall: 0.5075, relative_absolute_error: 0.9996, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5001, root_relative_squared_error: 1.0002, scimark_benchmark: 934.695, usercpu_time_millis: 470, usercpu_time_millis_testing: 160, usercpu_time_millis_training: 310,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4993, f_measure: 0.4793, kappa: 0.0128, kb_relative_information_score: 3.6007, mean_absolute_error: 0.4996, mean_prior_absolute_error: 0.4999, number_of_instances: 4000, precision: 0.5084, predictive_accuracy: 0.51, prior_entropy: 0.9998, recall: 0.51, relative_absolute_error: 0.9994, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5, root_relative_squared_error: 1.0001, scimark_benchmark: 593.4115, usercpu_time_millis: 240, usercpu_time_millis_testing: 90, usercpu_time_millis_training: 150,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5001, f_measure: 0.4812, kappa: 0.0017, kb_relative_information_score: 1.0044, mean_absolute_error: 0.4998, mean_prior_absolute_error: 0.4999, number_of_instances: 4000, precision: 0.5011, predictive_accuracy: 0.504, prior_entropy: 0.9998, recall: 0.504, relative_absolute_error: 0.9999, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5004, root_relative_squared_error: 1.0008, scimark_benchmark: 891.6381, usercpu_time_millis: 120, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 80,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5026, f_measure: 0.4748, kappa: -0.0043, kb_relative_information_score: 1.0709, mean_absolute_error: 0.4998, mean_prior_absolute_error: 0.4999, number_of_instances: 4000, precision: 0.4975, predictive_accuracy: 0.5013, prior_entropy: 0.9998, recall: 0.5013, relative_absolute_error: 0.9998, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5005, root_relative_squared_error: 1.0011, scimark_benchmark: 930.0399, usercpu_time_millis: 50, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4925, f_measure: 0.4936, kappa: -0.012, kb_relative_information_score: -24.0181, mean_absolute_error: 0.5024, mean_prior_absolute_error: 0.4999, number_of_instances: 4000, precision: 0.4941, predictive_accuracy: 0.4938, prior_entropy: 0.9998, recall: 0.4938, relative_absolute_error: 1.0051, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5421, root_relative_squared_error: 1.0844, scimark_benchmark: 936.1714, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4925, f_measure: 0.4936, kappa: -0.012, kb_relative_information_score: -24.0181, mean_absolute_error: 0.5024, mean_prior_absolute_error: 0.4999, number_of_instances: 4000, precision: 0.4941, predictive_accuracy: 0.4938, prior_entropy: 0.9998, recall: 0.4938, relative_absolute_error: 1.0051, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5421, root_relative_squared_error: 1.0844, scimark_benchmark: 938.3115, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4938, f_measure: 0.4944, kappa: -0.0105, kb_relative_information_score: -20.1209, mean_absolute_error: 0.502, mean_prior_absolute_error: 0.4999, number_of_instances: 4000, precision: 0.4949, predictive_accuracy: 0.4945, prior_entropy: 0.9998, recall: 0.4945, relative_absolute_error: 1.0042, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5416, root_relative_squared_error: 1.0833, scimark_benchmark: 894.7131, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
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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

OpenML bootcamp

From your own software

Use one of our APIs to download data from OpenML and upload your results

OpenML APIs