OpenML
Supervised Classification on chscase_census6

Supervised Classification on chscase_census6

Task 3763 Supervised Classification chscase_census6 585 runs submitted
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  • mythbusting_1 study_1 study_107 study_15 study_20 study_41 study_7 under100k under1m
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4871, f_measure: 0.4348, kb_relative_information_score: -0.0512, mean_absolute_error: 0.4848, mean_prior_absolute_error: 0.4848, number_of_instances: 400, precision: 0.3452, predictive_accuracy: 0.5875, prior_entropy: 0.978, recall: 0.5875, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4923, root_mean_squared_error: 0.4923, root_relative_squared_error: 1.0001, scimark_benchmark: 1363.434,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4871, f_measure: 0.4348, kb_relative_information_score: -0.0512, mean_absolute_error: 0.4848, mean_prior_absolute_error: 0.4848, number_of_instances: 400, precision: 0.3452, predictive_accuracy: 0.5875, prior_entropy: 0.978, recall: 0.5875, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4923, root_mean_squared_error: 0.4923, root_relative_squared_error: 1.0001, scimark_benchmark: 909.3537, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4871, f_measure: 0.4348, kb_relative_information_score: -0.1035, mean_absolute_error: 0.4848, mean_prior_absolute_error: 0.4848, number_of_instances: 400, precision: 0.3452, predictive_accuracy: 0.5875, prior_entropy: 0.978, recall: 0.5875, relative_absolute_error: 1.0001, root_mean_prior_squared_error: 0.4923, root_mean_squared_error: 0.4923, root_relative_squared_error: 1.0001, scimark_benchmark: 935.1887, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4697, f_measure: 0.4865, kappa: -0.0571, kb_relative_information_score: -9.3489, mean_absolute_error: 0.4902, mean_prior_absolute_error: 0.4848, number_of_instances: 400, precision: 0.4828, predictive_accuracy: 0.52, prior_entropy: 0.978, recall: 0.52, relative_absolute_error: 1.0113, root_mean_prior_squared_error: 0.4923, root_mean_squared_error: 0.5143, root_relative_squared_error: 1.0447, scimark_benchmark: 1331.6907, usercpu_time_millis: 130, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 120,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5048, f_measure: 0.52, kappa: 0.0097, kb_relative_information_score: -1.4425, mean_absolute_error: 0.48, mean_prior_absolute_error: 0.4848, number_of_instances: 400, precision: 0.52, predictive_accuracy: 0.52, prior_entropy: 0.978, recall: 0.52, relative_absolute_error: 0.9902, root_mean_prior_squared_error: 0.4923, root_mean_squared_error: 0.6928, root_relative_squared_error: 1.4074, scimark_benchmark: 1346.9602,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4375, f_measure: 0.4708, kappa: -0.0854, kb_relative_information_score: -23.8745, mean_absolute_error: 0.5075, mean_prior_absolute_error: 0.4848, number_of_instances: 400, precision: 0.465, predictive_accuracy: 0.51, prior_entropy: 0.978, recall: 0.51, relative_absolute_error: 1.0468, root_mean_prior_squared_error: 0.4923, root_mean_squared_error: 0.5635, root_relative_squared_error: 1.1446, scimark_benchmark: 1320.2556,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.471, f_measure: 0.4302, kappa: -0.0199, kb_relative_information_score: -3.0967, mean_absolute_error: 0.4876, mean_prior_absolute_error: 0.4848, number_of_instances: 400, precision: 0.3427, predictive_accuracy: 0.5775, prior_entropy: 0.978, recall: 0.5775, relative_absolute_error: 1.0058, root_mean_prior_squared_error: 0.4923, root_mean_squared_error: 0.496, root_relative_squared_error: 1.0075, scimark_benchmark: 1354.2491, usercpu_time_millis: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5302, f_measure: 0.5381, kappa: 0.0593, kb_relative_information_score: 11.0998, mean_absolute_error: 0.465, mean_prior_absolute_error: 0.4848, number_of_instances: 400, precision: 0.5444, predictive_accuracy: 0.535, prior_entropy: 0.978, recall: 0.535, relative_absolute_error: 0.9592, root_mean_prior_squared_error: 0.4923, root_mean_squared_error: 0.6819, root_relative_squared_error: 1.3852, scimark_benchmark: 1341.5768, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5383, f_measure: 0.5424, kappa: 0.0844, kb_relative_information_score: 63.3592, mean_absolute_error: 0.4025, mean_prior_absolute_error: 0.4848, number_of_instances: 400, precision: 0.5776, predictive_accuracy: 0.5975, prior_entropy: 0.978, recall: 0.5975, relative_absolute_error: 0.8303, root_mean_prior_squared_error: 0.4923, root_mean_squared_error: 0.6344, root_relative_squared_error: 1.2887, scimark_benchmark: 1290.1085, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4871, f_measure: 0.4348, kb_relative_information_score: 0.0012, mean_absolute_error: 0.4847, mean_prior_absolute_error: 0.4848, number_of_instances: 400, precision: 0.3452, predictive_accuracy: 0.5875, prior_entropy: 0.978, recall: 0.5875, relative_absolute_error: 0.9999, root_mean_prior_squared_error: 0.4923, root_mean_squared_error: 0.4923, root_relative_squared_error: 1.0001, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5596, f_measure: 0.5781, kappa: 0.1228, kb_relative_information_score: 54.9977, mean_absolute_error: 0.4125, mean_prior_absolute_error: 0.4848, number_of_instances: 400, precision: 0.5767, predictive_accuracy: 0.5875, prior_entropy: 0.978, recall: 0.5875, relative_absolute_error: 0.8509, root_mean_prior_squared_error: 0.4923, root_mean_squared_error: 0.6423, root_relative_squared_error: 1.3047, scimark_benchmark: 1351.788,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4785, f_measure: 0.4758, kappa: -0.0474, kb_relative_information_score: 15.2805, mean_absolute_error: 0.46, mean_prior_absolute_error: 0.4848, number_of_instances: 400, precision: 0.48, predictive_accuracy: 0.54, prior_entropy: 0.978, recall: 0.54, relative_absolute_error: 0.9489, root_mean_prior_squared_error: 0.4923, root_mean_squared_error: 0.6782, root_relative_squared_error: 1.3777, scimark_benchmark: 1353.5686,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4871, f_measure: 0.4348, kb_relative_information_score: -0.1035, mean_absolute_error: 0.4848, mean_prior_absolute_error: 0.4848, number_of_instances: 400, precision: 0.3452, predictive_accuracy: 0.5875, prior_entropy: 0.978, recall: 0.5875, relative_absolute_error: 1.0001, root_mean_prior_squared_error: 0.4923, root_mean_squared_error: 0.4923, root_relative_squared_error: 1.0001, scimark_benchmark: 1445.6675,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4871, f_measure: 0.4348, kb_relative_information_score: 0.0012, mean_absolute_error: 0.4847, mean_prior_absolute_error: 0.4848, number_of_instances: 400, precision: 0.3452, predictive_accuracy: 0.5875, prior_entropy: 0.978, recall: 0.5875, relative_absolute_error: 0.9999, root_mean_prior_squared_error: 0.4923, root_mean_squared_error: 0.4923, root_relative_squared_error: 1.0001, scimark_benchmark: 1605.6303,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4794, f_measure: 0.4994, kappa: 0.0186, kb_relative_information_score: 12.3583, mean_absolute_error: 0.4697, mean_prior_absolute_error: 0.4848, number_of_instances: 400, precision: 0.5321, predictive_accuracy: 0.575, prior_entropy: 0.978, recall: 0.575, relative_absolute_error: 0.9689, root_mean_prior_squared_error: 0.4923, root_mean_squared_error: 0.5343, root_relative_squared_error: 1.0853, scimark_benchmark: 927.0753,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4831, f_measure: 0.4994, kappa: 0.0186, kb_relative_information_score: 12.5691, mean_absolute_error: 0.4696, mean_prior_absolute_error: 0.4848, number_of_instances: 400, precision: 0.5321, predictive_accuracy: 0.575, prior_entropy: 0.978, recall: 0.575, relative_absolute_error: 0.9688, root_mean_prior_squared_error: 0.4923, root_mean_squared_error: 0.5324, root_relative_squared_error: 1.0814, scimark_benchmark: 945.6434,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4831, f_measure: 0.4994, kappa: 0.0186, kb_relative_information_score: 12.5691, mean_absolute_error: 0.4696, mean_prior_absolute_error: 0.4848, number_of_instances: 400, precision: 0.5321, predictive_accuracy: 0.575, prior_entropy: 0.978, recall: 0.575, relative_absolute_error: 0.9688, root_mean_prior_squared_error: 0.4923, root_mean_squared_error: 0.5324, root_relative_squared_error: 1.0814, scimark_benchmark: 941.7954,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4831, f_measure: 0.4994, kappa: 0.0186, kb_relative_information_score: 12.5691, mean_absolute_error: 0.4696, mean_prior_absolute_error: 0.4848, number_of_instances: 400, precision: 0.5321, predictive_accuracy: 0.575, prior_entropy: 0.978, recall: 0.575, relative_absolute_error: 0.9688, root_mean_prior_squared_error: 0.4923, root_mean_squared_error: 0.5324, root_relative_squared_error: 1.0814, scimark_benchmark: 923.7642,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4831, f_measure: 0.4994, kappa: 0.0186, kb_relative_information_score: 12.5691, mean_absolute_error: 0.4696, mean_prior_absolute_error: 0.4848, number_of_instances: 400, precision: 0.5321, predictive_accuracy: 0.575, prior_entropy: 0.978, recall: 0.575, relative_absolute_error: 0.9688, root_mean_prior_squared_error: 0.4923, root_mean_squared_error: 0.5324, root_relative_squared_error: 1.0814, scimark_benchmark: 894.7455, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4412, f_measure: 0.4775, kappa: -0.0427, kb_relative_information_score: 5.7309, mean_absolute_error: 0.4753, mean_prior_absolute_error: 0.4848, number_of_instances: 400, precision: 0.4831, predictive_accuracy: 0.5425, prior_entropy: 0.978, recall: 0.5425, relative_absolute_error: 0.9805, root_mean_prior_squared_error: 0.4923, root_mean_squared_error: 0.5868, root_relative_squared_error: 1.1919, scimark_benchmark: 936.6206, usercpu_time_millis: 210, usercpu_time_millis_training: 210,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4314, f_measure: 0.4677, kappa: -0.0511, kb_relative_information_score: 3.5442, mean_absolute_error: 0.4781, mean_prior_absolute_error: 0.4848, number_of_instances: 400, precision: 0.4725, predictive_accuracy: 0.5425, prior_entropy: 0.978, recall: 0.5425, relative_absolute_error: 0.9863, root_mean_prior_squared_error: 0.4923, root_mean_squared_error: 0.5824, root_relative_squared_error: 1.1831, scimark_benchmark: 938.2848, usercpu_time_millis: 90, usercpu_time_millis_training: 90,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4395, f_measure: 0.451, kappa: -0.0566, kb_relative_information_score: 7.7009, mean_absolute_error: 0.4729, mean_prior_absolute_error: 0.4848, number_of_instances: 400, precision: 0.4519, predictive_accuracy: 0.5475, prior_entropy: 0.978, recall: 0.5475, relative_absolute_error: 0.9756, root_mean_prior_squared_error: 0.4923, root_mean_squared_error: 0.5734, root_relative_squared_error: 1.1647, scimark_benchmark: 936.6206, usercpu_time_millis: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4291, f_measure: 0.4435, kappa: -0.073, kb_relative_information_score: 2.9982, mean_absolute_error: 0.479, mean_prior_absolute_error: 0.4848, number_of_instances: 400, precision: 0.4354, predictive_accuracy: 0.54, prior_entropy: 0.978, recall: 0.54, relative_absolute_error: 0.988, root_mean_prior_squared_error: 0.4923, root_mean_squared_error: 0.5696, root_relative_squared_error: 1.1571, scimark_benchmark: 922.9039, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4365, f_measure: 0.4575, kappa: -0.0176, kb_relative_information_score: 11.973, mean_absolute_error: 0.4686, mean_prior_absolute_error: 0.4848, number_of_instances: 400, precision: 0.4863, predictive_accuracy: 0.57, prior_entropy: 0.978, recall: 0.57, relative_absolute_error: 0.9667, root_mean_prior_squared_error: 0.4923, root_mean_squared_error: 0.5695, root_relative_squared_error: 1.1569, scimark_benchmark: 938.9865, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5213, f_measure: 0.53, kappa: 0.0227, kb_relative_information_score: 5.0651, mean_absolute_error: 0.4741, mean_prior_absolute_error: 0.4848, number_of_instances: 400, precision: 0.5266, predictive_accuracy: 0.54, prior_entropy: 0.978, recall: 0.54, relative_absolute_error: 0.9781, root_mean_prior_squared_error: 0.4923, root_mean_squared_error: 0.5354, root_relative_squared_error: 1.0875, scimark_benchmark: 933.8635, usercpu_time_millis: 130, usercpu_time_millis_training: 130,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4371, f_measure: 0.4576, kappa: -0.1189, kb_relative_information_score: -21.2957, mean_absolute_error: 0.5033, mean_prior_absolute_error: 0.4848, number_of_instances: 400, precision: 0.449, predictive_accuracy: 0.49, prior_entropy: 0.978, recall: 0.49, relative_absolute_error: 1.0382, root_mean_prior_squared_error: 0.4923, root_mean_squared_error: 0.5309, root_relative_squared_error: 1.0784, scimark_benchmark: 947.9494, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4134, f_measure: 0.4537, kappa: -0.1071, kb_relative_information_score: -22.1263, mean_absolute_error: 0.5046, mean_prior_absolute_error: 0.4848, number_of_instances: 400, precision: 0.4451, predictive_accuracy: 0.5075, prior_entropy: 0.978, recall: 0.5075, relative_absolute_error: 1.0409, root_mean_prior_squared_error: 0.4923, root_mean_squared_error: 0.528, root_relative_squared_error: 1.0726, scimark_benchmark: 929.566,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4871, f_measure: 0.4348, kb_relative_information_score: -0.1035, mean_absolute_error: 0.4848, mean_prior_absolute_error: 0.4848, number_of_instances: 400, precision: 0.3452, predictive_accuracy: 0.5875, prior_entropy: 0.978, recall: 0.5875, relative_absolute_error: 1.0001, root_mean_prior_squared_error: 0.4923, root_mean_squared_error: 0.4923, root_relative_squared_error: 1.0001, scimark_benchmark: 938.9865,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4642, f_measure: 0.2481, kappa: -0.0297, kb_relative_information_score: -38.5924, mean_absolute_error: 0.5175, mean_prior_absolute_error: 0.4848, number_of_instances: 400, precision: 0.3267, predictive_accuracy: 0.4, prior_entropy: 0.978, recall: 0.4, relative_absolute_error: 1.0676, root_mean_prior_squared_error: 0.4923, root_mean_squared_error: 0.5265, root_relative_squared_error: 1.0694, scimark_benchmark: 943.2745,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4177, f_measure: 0.47, kappa: -0.0709, kb_relative_information_score: -23.4281, mean_absolute_error: 0.5072, mean_prior_absolute_error: 0.4848, number_of_instances: 400, precision: 0.4676, predictive_accuracy: 0.525, prior_entropy: 0.978, recall: 0.525, relative_absolute_error: 1.0463, root_mean_prior_squared_error: 0.4923, root_mean_squared_error: 0.5323, root_relative_squared_error: 1.0812, scimark_benchmark: 930.32, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4787, f_measure: 0.5118, kappa: -0.0136, kb_relative_information_score: -10.6319, mean_absolute_error: 0.4923, mean_prior_absolute_error: 0.4848, number_of_instances: 400, precision: 0.5082, predictive_accuracy: 0.53, prior_entropy: 0.978, recall: 0.53, relative_absolute_error: 1.0154, root_mean_prior_squared_error: 0.4923, root_mean_squared_error: 0.5545, root_relative_squared_error: 1.1265, scimark_benchmark: 933.8635, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4871, f_measure: 0.4348, kb_relative_information_score: -0.1035, mean_absolute_error: 0.4848, mean_prior_absolute_error: 0.4848, number_of_instances: 400, precision: 0.3452, predictive_accuracy: 0.5875, prior_entropy: 0.978, recall: 0.5875, relative_absolute_error: 1.0001, root_mean_prior_squared_error: 0.4923, root_mean_squared_error: 0.4923, root_relative_squared_error: 1.0001, scimark_benchmark: 932.3943,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4538, f_measure: 0.4336, kappa: -0.0601, kb_relative_information_score: -20.6192, mean_absolute_error: 0.5022, mean_prior_absolute_error: 0.4848, number_of_instances: 400, precision: 0.4123, predictive_accuracy: 0.5525, prior_entropy: 0.978, recall: 0.5525, relative_absolute_error: 1.0359, root_mean_prior_squared_error: 0.4923, root_mean_squared_error: 0.5093, root_relative_squared_error: 1.0345, scimark_benchmark: 911.0478, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.4348, kb_relative_information_score: 54.9977, mean_absolute_error: 0.4125, mean_prior_absolute_error: 0.4848, number_of_instances: 400, precision: 0.3452, predictive_accuracy: 0.5875, prior_entropy: 0.978, recall: 0.5875, relative_absolute_error: 0.8509, root_mean_prior_squared_error: 0.4923, root_mean_squared_error: 0.6423, root_relative_squared_error: 1.3047, scimark_benchmark: 901.0726,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4389, f_measure: 0.4337, kappa: -0.0353, kb_relative_information_score: -14.3445, mean_absolute_error: 0.4956, mean_prior_absolute_error: 0.4848, number_of_instances: 400, precision: 0.4094, predictive_accuracy: 0.5675, prior_entropy: 0.978, recall: 0.5675, relative_absolute_error: 1.0223, root_mean_prior_squared_error: 0.4923, root_mean_squared_error: 0.4965, root_relative_squared_error: 1.0085, scimark_benchmark: 933.8635, usercpu_time_millis: 70, usercpu_time_millis_training: 70,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4409, f_measure: 0.4656, kappa: -0.0459, kb_relative_information_score: -8.413, mean_absolute_error: 0.4911, mean_prior_absolute_error: 0.4848, number_of_instances: 400, precision: 0.4731, predictive_accuracy: 0.5475, prior_entropy: 0.978, recall: 0.5475, relative_absolute_error: 1.0131, root_mean_prior_squared_error: 0.4923, root_mean_squared_error: 0.5014, root_relative_squared_error: 1.0184, scimark_benchmark: 917.7039,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.519, f_measure: 0.5019, kappa: -0.0224, kb_relative_information_score: -6.1328, mean_absolute_error: 0.4828, mean_prior_absolute_error: 0.4848, number_of_instances: 400, precision: 0.5044, predictive_accuracy: 0.5, prior_entropy: 0.978, recall: 0.5, relative_absolute_error: 0.9959, root_mean_prior_squared_error: 0.4923, root_mean_squared_error: 0.5822, root_relative_squared_error: 1.1827, scimark_benchmark: 932.236, usercpu_time_millis: 590, usercpu_time_millis_testing: 590,
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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