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OpenML
OpenML
Supervised Classification on haberman

Supervised Classification on haberman

Task 42 Supervised Classification haberman 973 runs submitted
0 likes downloaded by 0 people , 0 total downloads 0 issues
Visibility: Public
  • basic ComplexWorkflows mythbusting mythbusting_1 study_1 study_107 study_123 study_15 study_20 study_29 study_30 study_41 study_50 study_7 under100k under1m
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973 Runs

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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6478, f_measure: 0.7137, kappa: 0.2328, kb_relative_information_score: 24.4693, mean_absolute_error: 0.3257, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.7071, predictive_accuracy: 0.732, prior_entropy: 0.836, recall: 0.732, relative_absolute_error: 0.8351, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4607, root_relative_squared_error: 1.0442, scimark_benchmark: 825.5282, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6121, f_measure: 0.7279, kappa: 0.2626, kb_relative_information_score: 93.8347, mean_absolute_error: 0.2451, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.7285, predictive_accuracy: 0.7549, prior_entropy: 0.836, recall: 0.7549, relative_absolute_error: 0.6285, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4951, root_relative_squared_error: 1.1222, scimark_benchmark: 1318.1432, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.6231, kb_relative_information_score: 76.9269, mean_absolute_error: 0.2647, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.5407, predictive_accuracy: 0.7353, prior_entropy: 0.836, recall: 0.7353, relative_absolute_error: 0.6787, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.5145, root_relative_squared_error: 1.1662, scimark_benchmark: 938.343, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4978, f_measure: 0.6215, kappa: -0.0065, kb_relative_information_score: 74.1089, mean_absolute_error: 0.268, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.54, predictive_accuracy: 0.732, prior_entropy: 0.836, recall: 0.732, relative_absolute_error: 0.6871, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.5177, root_relative_squared_error: 1.1734, scimark_benchmark: 894.7222, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6554, f_measure: 0.6829, kappa: 0.1352, kb_relative_information_score: 19.3657, mean_absolute_error: 0.3573, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.701, predictive_accuracy: 0.7418, prior_entropy: 0.836, recall: 0.7418, relative_absolute_error: 0.9162, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4266, root_relative_squared_error: 0.967, scimark_benchmark: 930.5999, usercpu_time_millis: 50, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5314, f_measure: 0.6442, kappa: 0.0658, kb_relative_information_score: 6.4777, mean_absolute_error: 0.3464, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.6366, predictive_accuracy: 0.6536, prior_entropy: 0.836, recall: 0.6536, relative_absolute_error: 0.8882, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.5886, root_relative_squared_error: 1.3341, scimark_benchmark: 1250.8301, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6795, f_measure: 0.7086, kappa: 0.2049, kb_relative_information_score: 26.7413, mean_absolute_error: 0.3442, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.7205, predictive_accuracy: 0.7516, prior_entropy: 0.836, recall: 0.7516, relative_absolute_error: 0.8826, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4259, root_relative_squared_error: 0.9653, scimark_benchmark: 1330.0694, usercpu_time_millis: 300, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 290,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6373, f_measure: 0.6964, kappa: 0.1779, kb_relative_information_score: 22.644, mean_absolute_error: 0.3456, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.6898, predictive_accuracy: 0.7255, prior_entropy: 0.836, recall: 0.7255, relative_absolute_error: 0.8862, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4325, root_relative_squared_error: 0.9803, scimark_benchmark: 1335.4072, usercpu_time_millis: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5664, f_measure: 0.6575, kappa: 0.122, kb_relative_information_score: 7.6739, mean_absolute_error: 0.3448, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.6582, predictive_accuracy: 0.6569, prior_entropy: 0.836, recall: 0.6569, relative_absolute_error: 0.884, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.5837, root_relative_squared_error: 1.323, scimark_benchmark: 1313.5726,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5736, f_measure: 0.6559, kappa: 0.0609, kb_relative_information_score: -1.5475, mean_absolute_error: 0.3769, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.6462, predictive_accuracy: 0.7124, prior_entropy: 0.836, recall: 0.7124, relative_absolute_error: 0.9664, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4643, root_relative_squared_error: 1.0524, scimark_benchmark: 1066.7184,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5865, f_measure: 0.6612, kappa: 0.0817, kb_relative_information_score: 13.0803, mean_absolute_error: 0.3707, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.6921, predictive_accuracy: 0.7386, prior_entropy: 0.836, recall: 0.7386, relative_absolute_error: 0.9506, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.437, root_relative_squared_error: 0.9905, scimark_benchmark: 1355.7054, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5585, f_measure: 0.651, kappa: 0.1143, kb_relative_information_score: 0.8418, mean_absolute_error: 0.3529, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.6553, predictive_accuracy: 0.6471, prior_entropy: 0.836, recall: 0.6471, relative_absolute_error: 0.905, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.5941, root_relative_squared_error: 1.3466, scimark_benchmark: 1442.7264,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5133, f_measure: 0.382, kappa: 0.0167, kb_relative_information_score: -221.7774, mean_absolute_error: 0.6111, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.6283, predictive_accuracy: 0.3889, prior_entropy: 0.836, recall: 0.3889, relative_absolute_error: 1.567, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.7817, root_relative_squared_error: 1.7719, scimark_benchmark: 1384.4418,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6205, f_measure: 0.6947, kappa: 0.1839, kb_relative_information_score: 18.7353, mean_absolute_error: 0.3436, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.686, predictive_accuracy: 0.7124, prior_entropy: 0.836, recall: 0.7124, relative_absolute_error: 0.881, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4721, root_relative_squared_error: 1.0702, scimark_benchmark: 1466.6185,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5847, f_measure: 0.7037, kappa: 0.1975, kb_relative_information_score: 74.1089, mean_absolute_error: 0.268, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.6985, predictive_accuracy: 0.732, prior_entropy: 0.836, recall: 0.732, relative_absolute_error: 0.6871, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.5177, root_relative_squared_error: 1.1734, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6465, f_measure: 0.6763, kappa: 0.1337, kb_relative_information_score: 40.2021, mean_absolute_error: 0.3064, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.6658, predictive_accuracy: 0.6961, prior_entropy: 0.836, recall: 0.6961, relative_absolute_error: 0.7855, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.5167, root_relative_squared_error: 1.1711, scimark_benchmark: 938.2848, usercpu_time_millis: 7030, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 7020,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5442, f_measure: 0.6733, kappa: 0.1091, kb_relative_information_score: 62.837, mean_absolute_error: 0.281, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.6671, predictive_accuracy: 0.719, prior_entropy: 0.836, recall: 0.719, relative_absolute_error: 0.7206, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.5301, root_relative_squared_error: 1.2016, scimark_benchmark: 1028.5889,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4889, f_measure: 0.6231, kb_relative_information_score: -0.3553, mean_absolute_error: 0.3901, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.5407, predictive_accuracy: 0.7353, prior_entropy: 0.836, recall: 0.7353, relative_absolute_error: 1.0003, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4412, root_relative_squared_error: 1.0001, scimark_benchmark: 1028.5889,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5704, f_measure: 0.6818, kappa: 0.1344, kb_relative_information_score: 12.9756, mean_absolute_error: 0.3638, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.6744, predictive_accuracy: 0.719, prior_entropy: 0.836, recall: 0.719, relative_absolute_error: 0.9327, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4649, root_relative_squared_error: 1.0539, scimark_benchmark: 977.6382,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6405, f_measure: 0.6985, kappa: 0.1776, kb_relative_information_score: 86.2217, mean_absolute_error: 0.2555, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.7042, predictive_accuracy: 0.7418, prior_entropy: 0.836, recall: 0.7418, relative_absolute_error: 0.655, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4746, root_relative_squared_error: 1.0758, scimark_benchmark: 942.6953, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.667, f_measure: 0.7211, kappa: 0.2422, kb_relative_information_score: 41.5981, mean_absolute_error: 0.3234, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.7229, predictive_accuracy: 0.7516, prior_entropy: 0.836, recall: 0.7516, relative_absolute_error: 0.8293, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4288, root_relative_squared_error: 0.9719, scimark_benchmark: 945.6434, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6539, f_measure: 0.7232, kappa: 0.2493, kb_relative_information_score: 31.7352, mean_absolute_error: 0.3381, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.7237, predictive_accuracy: 0.7516, prior_entropy: 0.836, recall: 0.7516, relative_absolute_error: 0.867, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4252, root_relative_squared_error: 0.9639, scimark_benchmark: 939.7623, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6539, f_measure: 0.7232, kappa: 0.2493, kb_relative_information_score: 31.7352, mean_absolute_error: 0.3381, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.7237, predictive_accuracy: 0.7516, prior_entropy: 0.836, recall: 0.7516, relative_absolute_error: 0.867, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4252, root_relative_squared_error: 0.9639, scimark_benchmark: 945.6434, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6697, f_measure: 0.7211, kappa: 0.2422, kb_relative_information_score: 83.4441, mean_absolute_error: 0.2606, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.7229, predictive_accuracy: 0.7516, prior_entropy: 0.836, recall: 0.7516, relative_absolute_error: 0.6681, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4628, root_relative_squared_error: 1.0489, scimark_benchmark: 922.9039, usercpu_time_millis: 80, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 70,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6559, f_measure: 0.7185, kappa: 0.2358, kb_relative_information_score: 83.5927, mean_absolute_error: 0.2614, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.7187, predictive_accuracy: 0.7484, prior_entropy: 0.836, recall: 0.7484, relative_absolute_error: 0.6703, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4578, root_relative_squared_error: 1.0378, scimark_benchmark: 926.6717, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6542, f_measure: 0.7114, kappa: 0.2149, kb_relative_information_score: 80.414, mean_absolute_error: 0.2628, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.7126, predictive_accuracy: 0.7451, prior_entropy: 0.836, recall: 0.7451, relative_absolute_error: 0.6739, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.463, root_relative_squared_error: 1.0495, scimark_benchmark: 876.8277, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6581, f_measure: 0.7228, kappa: 0.2499, kb_relative_information_score: 75.1376, mean_absolute_error: 0.2709, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.7208, predictive_accuracy: 0.7484, prior_entropy: 0.836, recall: 0.7484, relative_absolute_error: 0.6947, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4585, root_relative_squared_error: 1.0393, scimark_benchmark: 939.7623,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6467, f_measure: 0.7014, kappa: 0.19, kb_relative_information_score: 69.9965, mean_absolute_error: 0.2727, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.6968, predictive_accuracy: 0.732, prior_entropy: 0.836, recall: 0.732, relative_absolute_error: 0.6993, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4727, root_relative_squared_error: 1.0714, scimark_benchmark: 933.8635,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6075, f_measure: 0.7037, kappa: 0.1975, kb_relative_information_score: 24.4879, mean_absolute_error: 0.3397, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.6985, predictive_accuracy: 0.732, prior_entropy: 0.836, recall: 0.732, relative_absolute_error: 0.8711, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4492, root_relative_squared_error: 1.0183, scimark_benchmark: 934.5243, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6329, f_measure: 0.7125, kappa: 0.2251, kb_relative_information_score: 25.1989, mean_absolute_error: 0.34, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.7068, predictive_accuracy: 0.7353, prior_entropy: 0.836, recall: 0.7353, relative_absolute_error: 0.8717, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4406, root_relative_squared_error: 0.9986, scimark_benchmark: 902.4773, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6571, f_measure: 0.7176, kappa: 0.2374, kb_relative_information_score: 26.6732, mean_absolute_error: 0.3401, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.7136, predictive_accuracy: 0.7418, prior_entropy: 0.836, recall: 0.7418, relative_absolute_error: 0.8721, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4342, root_relative_squared_error: 0.9841, scimark_benchmark: 910.8389, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6725, f_measure: 0.7125, kappa: 0.2251, kb_relative_information_score: 27.5492, mean_absolute_error: 0.3401, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.7068, predictive_accuracy: 0.7353, prior_entropy: 0.836, recall: 0.7353, relative_absolute_error: 0.872, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4299, root_relative_squared_error: 0.9744, scimark_benchmark: 933.8635, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6962, f_measure: 0.7293, kappa: 0.2696, kb_relative_information_score: 33.3516, mean_absolute_error: 0.3355, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.7267, predictive_accuracy: 0.7516, prior_entropy: 0.836, recall: 0.7516, relative_absolute_error: 0.8604, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4206, root_relative_squared_error: 0.9534, scimark_benchmark: 938.9865,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4889, f_measure: 0.6231, kb_relative_information_score: -0.3553, mean_absolute_error: 0.3901, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.5407, predictive_accuracy: 0.7353, prior_entropy: 0.836, recall: 0.7353, relative_absolute_error: 1.0003, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4412, root_relative_squared_error: 1.0001, scimark_benchmark: 938.9865,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5497, build_cpu_time: 0.0038, build_memory: 791756914.5098, f_measure: 0.6796, kappa: 0.1307, kb_relative_information_score: 7.6586, mean_absolute_error: 0.3594, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.67, predictive_accuracy: 0.7124, prior_entropy: 0.836, recall: 0.7124, relative_absolute_error: 0.9215, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4684, root_relative_squared_error: 1.0618, scimark_benchmark: 929.5397,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6151, build_cpu_time: 1.1376, build_memory: 304400611.7124, f_measure: 0.6727, kappa: 0.1324, kb_relative_information_score: 20.5223, mean_absolute_error: 0.3339, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.6637, predictive_accuracy: 0.6863, prior_entropy: 0.836, recall: 0.6863, relative_absolute_error: 0.8563, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4907, root_relative_squared_error: 1.1122, scimark_benchmark: 892.8005,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5961, build_cpu_time: 9.3219, build_memory: 36255298.5098, f_measure: 0.6602, kappa: 0.1062, kb_relative_information_score: 12.6289, mean_absolute_error: 0.3387, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.6526, predictive_accuracy: 0.6699, prior_entropy: 0.836, recall: 0.6699, relative_absolute_error: 0.8685, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.5624, root_relative_squared_error: 1.2748, scimark_benchmark: 937.9406,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.638, build_cpu_time: 9.0086, build_memory: 481976522.0654, f_measure: 0.6667, kappa: 0.1437, kb_relative_information_score: 8.5396, mean_absolute_error: 0.346, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.6667, predictive_accuracy: 0.6667, prior_entropy: 0.836, recall: 0.6667, relative_absolute_error: 0.8873, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.5607, root_relative_squared_error: 1.2709, scimark_benchmark: 940.067,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6364, build_cpu_time: 7.1841, build_memory: 150878185.1503, f_measure: 0.6641, kappa: 0.1387, kb_relative_information_score: 11.147, mean_absolute_error: 0.343, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.6647, predictive_accuracy: 0.6634, prior_entropy: 0.836, recall: 0.6634, relative_absolute_error: 0.8794, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.5577, root_relative_squared_error: 1.2642, scimark_benchmark: 938.1146,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6517, build_cpu_time: 4.1279, build_memory: 1007037797.2549, f_measure: 0.6496, kappa: 0.0982, kb_relative_information_score: 8.5719, mean_absolute_error: 0.3415, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.6489, predictive_accuracy: 0.6503, prior_entropy: 0.836, recall: 0.6503, relative_absolute_error: 0.8756, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.5468, root_relative_squared_error: 1.2394, scimark_benchmark: 930.5854,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6537, build_cpu_time: 1.9344, build_memory: 503907587.7647, f_measure: 0.6824, kappa: 0.1824, kb_relative_information_score: 23.1872, mean_absolute_error: 0.3246, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.6818, predictive_accuracy: 0.683, prior_entropy: 0.836, recall: 0.683, relative_absolute_error: 0.8324, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.5119, root_relative_squared_error: 1.1604, scimark_benchmark: 914.1182,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6702, build_cpu_time: 0.213, build_memory: 251736976.366, f_measure: 0.6862, kappa: 0.1562, kb_relative_information_score: 40.4371, mean_absolute_error: 0.3154, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.6765, predictive_accuracy: 0.7092, prior_entropy: 0.836, recall: 0.7092, relative_absolute_error: 0.8088, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4619, root_relative_squared_error: 1.047, scimark_benchmark: 942.3919,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6622, build_cpu_time: 0.4206, build_memory: 714369031.0327, f_measure: 0.6645, kappa: 0.1043, kb_relative_information_score: 30.4218, mean_absolute_error: 0.3208, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.6532, predictive_accuracy: 0.683, prior_entropy: 0.836, recall: 0.683, relative_absolute_error: 0.8225, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4846, root_relative_squared_error: 1.0985, scimark_benchmark: 923.3659,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6473, build_cpu_time: 0.8185, build_memory: 209791437.3072, f_measure: 0.6677, kappa: 0.1218, kb_relative_information_score: 25.3335, mean_absolute_error: 0.3252, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.6591, predictive_accuracy: 0.6797, prior_entropy: 0.836, recall: 0.6797, relative_absolute_error: 0.8338, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.5113, root_relative_squared_error: 1.1589, scimark_benchmark: 913.3372,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6365, build_cpu_time: 3.503, build_memory: 274110703.3203, f_measure: 0.6498, kappa: 0.0731, kb_relative_information_score: 16.1192, mean_absolute_error: 0.3332, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.6398, predictive_accuracy: 0.6634, prior_entropy: 0.836, recall: 0.6634, relative_absolute_error: 0.8543, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.5458, root_relative_squared_error: 1.2372, scimark_benchmark: 920.7965,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6976, build_cpu_time: 0.027, build_memory: 1120582822.2484, f_measure: 0.7093, kappa: 0.22, kb_relative_information_score: 34.7441, mean_absolute_error: 0.3267, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.7023, predictive_accuracy: 0.7288, prior_entropy: 0.836, recall: 0.7288, relative_absolute_error: 0.8377, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4376, root_relative_squared_error: 0.9918, scimark_benchmark: 893.4088,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6976, build_cpu_time: 0.0262, build_memory: 647101996.0784, f_measure: 0.7093, kappa: 0.22, kb_relative_information_score: 34.7441, mean_absolute_error: 0.3267, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.7023, predictive_accuracy: 0.7288, prior_entropy: 0.836, recall: 0.7288, relative_absolute_error: 0.8377, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4376, root_relative_squared_error: 0.9918, scimark_benchmark: 923.9118,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6976, build_cpu_time: 0.0291, build_memory: 1448462710.2745, f_measure: 0.7093, kappa: 0.22, kb_relative_information_score: 34.7441, mean_absolute_error: 0.3267, mean_prior_absolute_error: 0.39, number_of_instances: 306, precision: 0.7023, predictive_accuracy: 0.7288, prior_entropy: 0.836, recall: 0.7288, relative_absolute_error: 0.8377, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4376, root_relative_squared_error: 0.9918, scimark_benchmark: 923.9118,

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