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OpenML
Task
Supervised Classification on labor

Supervised Classification on labor

Task 4 Supervised Classification labor 6416 runs submitted
0 likes downloaded by 1 people , 4 total downloads 0 issues
Visibility: Public
  • basic mythbusting mythbusting_1 study_1 study_107 study_15 study_20 study_41 study_73 under100k under1m
Issue #Downvotes for this reason By


Metric:

6416 Runs

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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9466, f_measure: 0.8596, kappa: 0.6919, kb_relative_information_score: 34.6663, mean_absolute_error: 0.1814, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.8596, predictive_accuracy: 0.8596, prior_entropy: 0.9393, recall: 0.8596, relative_absolute_error: 0.397, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.2915, root_relative_squared_error: 0.6108, scimark_benchmark: 924.3698,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9568, f_measure: 0.8778, kappa: 0.7335, kb_relative_information_score: 38.0033, mean_absolute_error: 0.1507, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.8791, predictive_accuracy: 0.8772, prior_entropy: 0.9393, recall: 0.8772, relative_absolute_error: 0.3298, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.2756, root_relative_squared_error: 0.5775, scimark_benchmark: 939.5205,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9345, f_measure: 0.9305, kappa: 0.8494, kb_relative_information_score: 47.6876, mean_absolute_error: 0.0702, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.9336, predictive_accuracy: 0.9298, prior_entropy: 0.9393, recall: 0.9298, relative_absolute_error: 0.1535, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.2649, root_relative_squared_error: 0.555, scimark_benchmark: 1318.1432,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.511, kb_relative_information_score: 11.488, mean_absolute_error: 0.3509, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.4214, predictive_accuracy: 0.6491, prior_entropy: 0.9393, recall: 0.6491, relative_absolute_error: 0.7677, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.5923, root_relative_squared_error: 1.2411, scimark_benchmark: 1297.6599, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9365, f_measure: 0.947, kappa: 0.8831, kb_relative_information_score: 49.9501, mean_absolute_error: 0.0526, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.9474, predictive_accuracy: 0.9474, prior_entropy: 0.9393, recall: 0.9474, relative_absolute_error: 0.1152, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.2294, root_relative_squared_error: 0.4807, scimark_benchmark: 894.7222,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9824, f_measure: 0.9298, kappa: 0.8459, kb_relative_information_score: 43.269, mean_absolute_error: 0.1125, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.9298, predictive_accuracy: 0.9298, prior_entropy: 0.9393, recall: 0.9298, relative_absolute_error: 0.2461, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.228, root_relative_squared_error: 0.4778, scimark_benchmark: 1318.1432, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9345, f_measure: 0.9305, kappa: 0.8494, kb_relative_information_score: 47.6876, mean_absolute_error: 0.0702, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.9336, predictive_accuracy: 0.9298, prior_entropy: 0.9393, recall: 0.9298, relative_absolute_error: 0.1535, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.2649, root_relative_squared_error: 0.555, scimark_benchmark: 942.9708,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9851, f_measure: 0.9649, kappa: 0.923, kb_relative_information_score: 44.0304, mean_absolute_error: 0.1161, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.9649, predictive_accuracy: 0.9649, prior_entropy: 0.9393, recall: 0.9649, relative_absolute_error: 0.254, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.2, root_relative_squared_error: 0.419, scimark_benchmark: 1363.434, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.923, f_measure: 0.9298, kappa: 0.8459, kb_relative_information_score: 47.6876, mean_absolute_error: 0.0702, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.9298, predictive_accuracy: 0.9298, prior_entropy: 0.9393, recall: 0.9298, relative_absolute_error: 0.1535, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.2649, root_relative_squared_error: 0.555, scimark_benchmark: 1028.5889, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9757, f_measure: 0.8934, kappa: 0.7635, kb_relative_information_score: 42.3974, mean_absolute_error: 0.1128, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.8944, predictive_accuracy: 0.8947, prior_entropy: 0.9393, recall: 0.8947, relative_absolute_error: 0.2468, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.2628, root_relative_squared_error: 0.5506, scimark_benchmark: 1028.5889,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9689, f_measure: 0.947, kappa: 0.8831, kb_relative_information_score: 42.9502, mean_absolute_error: 0.1168, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.9474, predictive_accuracy: 0.9474, prior_entropy: 0.9393, recall: 0.9474, relative_absolute_error: 0.2556, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.2293, root_relative_squared_error: 0.4804, scimark_benchmark: 1250.8301, usercpu_time_millis: 120, usercpu_time_millis_training: 120,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8169, f_measure: 0.8246, kappa: 0.6149, kb_relative_information_score: 28.8147, mean_absolute_error: 0.2236, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.8246, predictive_accuracy: 0.8246, prior_entropy: 0.9393, recall: 0.8246, relative_absolute_error: 0.4893, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.4013, root_relative_squared_error: 0.8408, scimark_benchmark: 1280.6952,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7007, f_measure: 0.7544, kappa: 0.4608, kb_relative_information_score: 20.2491, mean_absolute_error: 0.2971, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.7544, predictive_accuracy: 0.7544, prior_entropy: 0.9393, recall: 0.7544, relative_absolute_error: 0.65, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.4514, root_relative_squared_error: 0.9458, scimark_benchmark: 1280.6952,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7926, f_measure: 0.8246, kappa: 0.6149, kb_relative_information_score: 27.7117, mean_absolute_error: 0.242, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.8246, predictive_accuracy: 0.8246, prior_entropy: 0.9393, recall: 0.8246, relative_absolute_error: 0.5295, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.3927, root_relative_squared_error: 0.8227, scimark_benchmark: 1361.1055, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8804, f_measure: 0.8626, kappa: 0.7118, kb_relative_information_score: 38.6377, mean_absolute_error: 0.1404, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.8846, predictive_accuracy: 0.8596, prior_entropy: 0.9393, recall: 0.8596, relative_absolute_error: 0.3071, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.3746, root_relative_squared_error: 0.785, scimark_benchmark: 1353.6735,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7588, f_measure: 0.7045, kappa: 0.4415, kb_relative_information_score: 18.2754, mean_absolute_error: 0.2982, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.8101, predictive_accuracy: 0.7018, prior_entropy: 0.9393, recall: 0.7018, relative_absolute_error: 0.6526, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.5461, root_relative_squared_error: 1.1443, scimark_benchmark: 1384.4418,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7176, f_measure: 0.7832, kappa: 0.5156, kb_relative_information_score: 21.1071, mean_absolute_error: 0.2927, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.7856, predictive_accuracy: 0.7895, prior_entropy: 0.9393, recall: 0.7895, relative_absolute_error: 0.6405, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.4278, root_relative_squared_error: 0.8964, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6845, f_measure: 0.7357, kappa: 0.4063, kb_relative_information_score: 25.0629, mean_absolute_error: 0.2456, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.7536, predictive_accuracy: 0.7544, prior_entropy: 0.9393, recall: 0.7544, relative_absolute_error: 0.5374, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.4956, root_relative_squared_error: 1.0384, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9716, f_measure: 0.9305, kappa: 0.8494, kb_relative_information_score: 44.9893, mean_absolute_error: 0.0945, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.9336, predictive_accuracy: 0.9298, prior_entropy: 0.9393, recall: 0.9298, relative_absolute_error: 0.2068, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.2458, root_relative_squared_error: 0.5151, scimark_benchmark: 889.9795, usercpu_time_millis: 370, usercpu_time_millis_training: 370,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8595, f_measure: 0.8764, kappa: 0.7273, kb_relative_information_score: 40.9002, mean_absolute_error: 0.1228, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.8763, predictive_accuracy: 0.8772, prior_entropy: 0.9393, recall: 0.8772, relative_absolute_error: 0.2687, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.3504, root_relative_squared_error: 0.7343, scimark_benchmark: 1054.3694,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4716, f_measure: 0.511, kb_relative_information_score: -0.1249, mean_absolute_error: 0.4574, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.4214, predictive_accuracy: 0.6491, prior_entropy: 0.9393, recall: 0.6491, relative_absolute_error: 1.0009, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.4775, root_relative_squared_error: 1.0004, scimark_benchmark: 1028.5889,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7101, f_measure: 0.7832, kappa: 0.5156, kb_relative_information_score: 22.9496, mean_absolute_error: 0.2802, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.7856, predictive_accuracy: 0.7895, prior_entropy: 0.9393, recall: 0.7895, relative_absolute_error: 0.6131, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.4298, root_relative_squared_error: 0.9005, scimark_benchmark: 977.6382,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9804, f_measure: 0.9305, kappa: 0.8494, kb_relative_information_score: 48.8357, mean_absolute_error: 0.0597, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.9336, predictive_accuracy: 0.9298, prior_entropy: 0.9393, recall: 0.9298, relative_absolute_error: 0.1305, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.2229, root_relative_squared_error: 0.4671, scimark_benchmark: 945.6434, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9777, f_measure: 0.9477, kappa: 0.8858, kb_relative_information_score: 49.6463, mean_absolute_error: 0.056, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.9486, predictive_accuracy: 0.9474, prior_entropy: 0.9393, recall: 0.9474, relative_absolute_error: 0.1224, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.2274, root_relative_squared_error: 0.4765, scimark_benchmark: 942.6953, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9736, f_measure: 0.9477, kappa: 0.8858, kb_relative_information_score: 49.7781, mean_absolute_error: 0.0545, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.9486, predictive_accuracy: 0.9474, prior_entropy: 0.9393, recall: 0.9474, relative_absolute_error: 0.1193, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.2273, root_relative_squared_error: 0.4764, scimark_benchmark: 945.6434, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9446, f_measure: 0.9117, kappa: 0.8052, kb_relative_information_score: 44.974, mean_absolute_error: 0.0925, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.9118, predictive_accuracy: 0.9123, prior_entropy: 0.9393, recall: 0.9123, relative_absolute_error: 0.2025, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.2954, root_relative_squared_error: 0.6189, scimark_benchmark: 940.2922, usercpu_time_millis: 70, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9324, f_measure: 0.9117, kappa: 0.8052, kb_relative_information_score: 45.2593, mean_absolute_error: 0.0895, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.9118, predictive_accuracy: 0.9123, prior_entropy: 0.9393, recall: 0.9123, relative_absolute_error: 0.1959, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.2943, root_relative_squared_error: 0.6167, scimark_benchmark: 926.6717, usercpu_time_millis: 190, usercpu_time_millis_testing: 50, usercpu_time_millis_training: 140,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9345, f_measure: 0.9289, kappa: 0.8423, kb_relative_information_score: 47.6876, mean_absolute_error: 0.0702, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.9306, predictive_accuracy: 0.9298, prior_entropy: 0.9393, recall: 0.9298, relative_absolute_error: 0.1535, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.2649, root_relative_squared_error: 0.555, scimark_benchmark: 942.1229, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9561, f_measure: 0.9289, kappa: 0.8423, kb_relative_information_score: 47.6877, mean_absolute_error: 0.0702, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.9306, predictive_accuracy: 0.9298, prior_entropy: 0.9393, recall: 0.9298, relative_absolute_error: 0.1535, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.2649, root_relative_squared_error: 0.555, scimark_benchmark: 938.4278, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9723, f_measure: 0.9289, kappa: 0.8423, kb_relative_information_score: 47.5375, mean_absolute_error: 0.0718, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.9306, predictive_accuracy: 0.9298, prior_entropy: 0.9393, recall: 0.9298, relative_absolute_error: 0.1571, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.2617, root_relative_squared_error: 0.5484, scimark_benchmark: 934.5243, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9743, f_measure: 0.8916, kappa: 0.7578, kb_relative_information_score: 42.101, mean_absolute_error: 0.1148, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.8989, predictive_accuracy: 0.8947, prior_entropy: 0.9393, recall: 0.8947, relative_absolute_error: 0.2512, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.317, root_relative_squared_error: 0.6643, scimark_benchmark: 939.7623,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9486, f_measure: 0.8746, kappa: 0.7208, kb_relative_information_score: 37.5109, mean_absolute_error: 0.1514, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.8776, predictive_accuracy: 0.8772, prior_entropy: 0.9393, recall: 0.8772, relative_absolute_error: 0.3314, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.3533, root_relative_squared_error: 0.7402, scimark_benchmark: 933.8635,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9378, f_measure: 0.9298, kappa: 0.8459, kb_relative_information_score: 46.8965, mean_absolute_error: 0.0771, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.9298, predictive_accuracy: 0.9298, prior_entropy: 0.9393, recall: 0.9298, relative_absolute_error: 0.1686, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.269, root_relative_squared_error: 0.5636, scimark_benchmark: 924.6116, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.973, f_measure: 0.9117, kappa: 0.8052, kb_relative_information_score: 46.0955, mean_absolute_error: 0.0809, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.9118, predictive_accuracy: 0.9123, prior_entropy: 0.9393, recall: 0.9123, relative_absolute_error: 0.1771, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.2745, root_relative_squared_error: 0.5752, scimark_benchmark: 924.6116, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9074, build_cpu_time: 0.0352, build_memory: 897924215.2982, f_measure: 0.9117, kappa: 0.8052, kb_relative_information_score: 45.509, mean_absolute_error: 0.0868, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.9118, predictive_accuracy: 0.9123, prior_entropy: 0.9393, recall: 0.9123, relative_absolute_error: 0.1899, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.2931, root_relative_squared_error: 0.6141, scimark_benchmark: 939.0159,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9642, build_cpu_time: 0.1488, build_memory: 27752453.614, f_measure: 0.9477, kappa: 0.8858, kb_relative_information_score: 48.7968, mean_absolute_error: 0.0618, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.9486, predictive_accuracy: 0.9474, prior_entropy: 0.9393, recall: 0.9474, relative_absolute_error: 0.1353, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.2372, root_relative_squared_error: 0.4969, scimark_benchmark: 923.9118,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9649, build_cpu_time: 0.3565, build_memory: 478709964.2105, f_measure: 0.9305, kappa: 0.8494, kb_relative_information_score: 47.5941, mean_absolute_error: 0.0712, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.9336, predictive_accuracy: 0.9298, prior_entropy: 0.9393, recall: 0.9298, relative_absolute_error: 0.1558, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.2645, root_relative_squared_error: 0.5542, scimark_benchmark: 927.3354,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.948, build_cpu_time: 0.5379, build_memory: 1175890860.4912, f_measure: 0.9477, kappa: 0.8858, kb_relative_information_score: 49.9501, mean_absolute_error: 0.0526, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.9486, predictive_accuracy: 0.9474, prior_entropy: 0.9393, recall: 0.9474, relative_absolute_error: 0.1152, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.2294, root_relative_squared_error: 0.4807, scimark_benchmark: 935.6292,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9595, build_cpu_time: 0.8703, build_memory: 1470238238.0351, f_measure: 0.9649, kappa: 0.923, kb_relative_information_score: 51.1524, mean_absolute_error: 0.0439, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.9649, predictive_accuracy: 0.9649, prior_entropy: 0.9393, recall: 0.9649, relative_absolute_error: 0.096, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.1985, root_relative_squared_error: 0.4158, scimark_benchmark: 931.9671,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9574, build_cpu_time: 0.4348, build_memory: 271379549.4737, f_measure: 0.9477, kappa: 0.8858, kb_relative_information_score: 50.0641, mean_absolute_error: 0.0514, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.9486, predictive_accuracy: 0.9474, prior_entropy: 0.9393, recall: 0.9474, relative_absolute_error: 0.1124, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.2236, root_relative_squared_error: 0.4685, scimark_benchmark: 902.712,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9838, build_cpu_time: 0.2573, build_memory: 499381455.4386, f_measure: 0.9477, kappa: 0.8858, kb_relative_information_score: 49.8427, mean_absolute_error: 0.0538, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.9486, predictive_accuracy: 0.9474, prior_entropy: 0.9393, recall: 0.9474, relative_absolute_error: 0.1178, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.2294, root_relative_squared_error: 0.4807, scimark_benchmark: 923.9118,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9365, build_cpu_time: 0.0511, build_memory: 271979738.1053, f_measure: 0.8958, kappa: 0.7741, kb_relative_information_score: 42.5265, mean_absolute_error: 0.1118, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.8991, predictive_accuracy: 0.8947, prior_entropy: 0.9393, recall: 0.8947, relative_absolute_error: 0.2447, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.3214, root_relative_squared_error: 0.6734, scimark_benchmark: 942.3919,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9068, build_cpu_time: 0.0751, build_memory: 768681465.4035, f_measure: 0.8596, kappa: 0.6919, kb_relative_information_score: 38.7137, mean_absolute_error: 0.1398, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.8596, predictive_accuracy: 0.8596, prior_entropy: 0.9393, recall: 0.8596, relative_absolute_error: 0.3059, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.3602, root_relative_squared_error: 0.7547, scimark_benchmark: 919.5971,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9068, build_cpu_time: 0.0697, build_memory: 453743215.1579, f_measure: 0.8596, kappa: 0.6919, kb_relative_information_score: 38.7137, mean_absolute_error: 0.1398, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.8596, predictive_accuracy: 0.8596, prior_entropy: 0.9393, recall: 0.8596, relative_absolute_error: 0.3059, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.3602, root_relative_squared_error: 0.7547, scimark_benchmark: 924.2473,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9068, build_cpu_time: 0.1001, build_memory: 1490563242.386, f_measure: 0.8596, kappa: 0.6919, kb_relative_information_score: 38.7137, mean_absolute_error: 0.1398, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.8596, predictive_accuracy: 0.8596, prior_entropy: 0.9393, recall: 0.8596, relative_absolute_error: 0.3059, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.3602, root_relative_squared_error: 0.7547, scimark_benchmark: 919.8064,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9068, build_cpu_time: 0.0949, build_memory: 411107078.0351, f_measure: 0.8596, kappa: 0.6919, kb_relative_information_score: 38.7137, mean_absolute_error: 0.1398, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.8596, predictive_accuracy: 0.8596, prior_entropy: 0.9393, recall: 0.8596, relative_absolute_error: 0.3059, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.3602, root_relative_squared_error: 0.7547, scimark_benchmark: 924.2473,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9561, build_cpu_time: 0.0403, build_memory: 1112227343.579, f_measure: 0.947, kappa: 0.8831, kb_relative_information_score: 48.8099, mean_absolute_error: 0.0633, mean_prior_absolute_error: 0.457, number_of_instances: 57, precision: 0.9474, predictive_accuracy: 0.9474, prior_entropy: 0.9393, recall: 0.9474, relative_absolute_error: 0.1385, root_mean_prior_squared_error: 0.4773, root_mean_squared_error: 0.2362, root_relative_squared_error: 0.4949, 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