8905493 1935 Hilde Weerts 14 Supervised Classification 8317 sklearn.pipeline.Pipeline(imputation=hyperimp.utils.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,scaling=sklearn.preprocessing.data.StandardScaler,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,clf=sklearn.svm.classes.SVC)(1) 6843084 categorical_features [] 7644 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 7644 handle_unknown "ignore" 7644 n_values "auto" 7644 sparse true 7644 threshold 0.0 7645 copy true 7646 with_mean false 7646 with_std true 7646 C 520.2374310079729 7650 cache_size 200 7650 class_weight null 7650 coef0 0.7011513197244875 7650 decision_function_shape "ovr" 7650 degree 3 7650 gamma 0.1922057971237275 7650 kernel "rbf" 7650 max_iter -1 7650 probability false 7650 random_state 1 7650 shrinking true 7650 tol 0.006376836455014594 7650 verbose false 7650 axis 0 8316 categorical_features [] 8316 copy true 8316 fill_empty 0 8316 missing_values "NaN" 8316 strategy "mean" 8316 strategy_nominal "most_frequent" 8316 verbose 0 8316 memory null 8317 openml-python Sklearn_0.19.1. study_98 14 mfeat-fourier https://www.openml.org/data/download/14/dataset_14_mfeat-fourier.arff -1 18726730 description https://api.openml.org/data/download/18726730/description.xml -1 18726731 predictions https://api.openml.org/data/download/18726731/predictions.arff area_under_roc_curve 0.6688888888888889 [0.835,0.638611,0.77,0.575556,0.673056,0.545,0.577778,0.729444,0.765,0.579444] average_cost 0 f_measure 0.44225353100922815 [0.802395,0.429119,0.701299,0.229508,0.268391,0.165138,0.259259,0.611842,0.69281,0.262774] kappa 0.33777777777777784 kb_relative_information_score 753.4570712516663 mean_absolute_error 0.1191999999999975 mean_prior_absolute_error 0.18000000000000554 number_of_instances 2000 [200,200,200,200,200,200,200,200,200,200] precision 0.7153271632659289 [1,0.918033,1,0.194444,0.160077,1,0.5,0.894231,1,0.486486] predictive_accuracy 0.40399999999999997 prior_entropy 3.321928094887362 recall 0.404 [0.67,0.28,0.54,0.28,0.83,0.09,0.175,0.465,0.53,0.18] relative_absolute_error 0.6622222222221879 root_mean_prior_squared_error 0.3000000000000046 root_mean_squared_error 0.34525353003263776 root_relative_squared_error 1.1508451001087747 total_cost 0 area_under_roc_curve 0.6666666666666665 [0.825,0.694444,0.75,0.575,0.688889,0.575,0.616667,0.7,0.675,0.566667] area_under_roc_curve 0.7027777777777777 [0.825,0.647222,0.825,0.547222,0.744444,0.55,0.627778,0.797222,0.85,0.613889] area_under_roc_curve 0.6805555555555556 [0.775,0.747222,0.725,0.525,0.702778,0.525,0.619444,0.722222,0.875,0.588889] area_under_roc_curve 0.675 [0.825,0.55,0.75,0.55,0.691667,0.65,0.619444,0.697222,0.8,0.616667] area_under_roc_curve 0.65 [0.825,0.675,0.725,0.680556,0.622222,0.575,0.516667,0.666667,0.7,0.513889] area_under_roc_curve 0.6638888888888889 [0.875,0.65,0.8,0.525,0.680556,0.525,0.538889,0.775,0.75,0.519444] area_under_roc_curve 0.6833333333333332 [0.875,0.675,0.825,0.575,0.711111,0.5,0.538889,0.716667,0.8,0.616667] area_under_roc_curve 0.6638888888888889 [0.825,0.65,0.75,0.547222,0.641667,0.5,0.663889,0.819444,0.625,0.616667] area_under_roc_curve 0.6555555555555556 [0.825,0.575,0.775,0.680556,0.566667,0.5,0.519444,0.675,0.85,0.588889] area_under_roc_curve 0.6472222222222223 [0.875,0.522222,0.775,0.55,0.680556,0.55,0.516667,0.725,0.725,0.552778] average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 f_measure 0.4450634990909591 [0.787879,0.533333,0.666667,0.26087,0.263158,0.26087,0.357143,0.571429,0.518519,0.230769] f_measure 0.49275344502436846 [0.787879,0.444444,0.787879,0.173913,0.30303,0.181818,0.352941,0.727273,0.823529,0.344828] f_measure 0.45513409120909515 [0.709677,0.645161,0.62069,0.095238,0.272109,0.095238,0.37037,0.6,0.857143,0.285714] f_measure 0.4573858307416198 [0.787879,0.181818,0.666667,0.181818,0.264901,0.461538,0.37037,0.551724,0.75,0.357143] f_measure 0.40320649989601004 [0.787879,0.518519,0.62069,0.258065,0.384615,0.26087,0.083333,0.466667,0.571429,0.08] f_measure 0.41343687868933315 [0.857143,0.461538,0.75,0.095238,0.258065,0.095238,0.153846,0.709677,0.666667,0.086957] f_measure 0.3797691277947118 [0.857143,0.090909,0.709677,0.181818,0.258065,0.181818,0.083333,0.62069,0.62069,0.193548] kappa 0.33333333333333337 kappa 0.40555555555555556 kappa 0.36111111111111105 kappa 0.3499999999999999 kappa 0.3 kappa 0.32777777777777783 kappa 0.36666666666666664 kappa 0.32777777777777783 kappa 0.3111111111111111 kappa 0.29444444444444445 kb_relative_information_score 74.50910113271917 kb_relative_information_score 88.10394851000795 kb_relative_information_score 79.73788858552254 kb_relative_information_score 77.64637360440119 kb_relative_information_score 68.23455618935512 kb_relative_information_score 73.46334364215849 kb_relative_information_score 80.78364607608322 kb_relative_information_score 73.46334364215849 kb_relative_information_score 70.32607117047645 kb_relative_information_score 67.18879869879441 mean_absolute_error 0.11999999999999973 mean_absolute_error 0.10699999999999978 mean_absolute_error 0.11499999999999976 mean_absolute_error 0.11699999999999974 mean_absolute_error 0.12599999999999972 mean_absolute_error 0.12099999999999973 mean_absolute_error 0.11399999999999975 mean_absolute_error 0.12099999999999973 mean_absolute_error 0.12399999999999972 mean_absolute_error 0.1269999999999997 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] precision 0.8076515151515151 [1,0.8,1,1,0.151515,1,0.625,1,1,0.5] precision 0.7609584859584859 [1,0.857143,1,0.666667,0.178571,1,0.428571,0.923077,1,0.555556] precision 0.8180856938337254 [1,0.909091,1,1,0.15748,1,0.714286,0.9,1,0.5] precision 0.8380846358899794 [1,1,1,1,0.152672,1,0.714286,0.888889,1,0.625] precision 0.7131481481481481 [1,1,1,0.148148,0.833333,1,0.25,0.7,1,0.2] precision 0.7814814814814813 [1,1,1,1,0.148148,1,0.333333,1,1,0.333333] precision 0.7170875420875421 [1,0.5,1,1,0.148148,1,0.25,1,1,0.272727] predictive_accuracy 0.4 predictive_accuracy 0.465 predictive_accuracy 0.425 predictive_accuracy 0.415 predictive_accuracy 0.37 predictive_accuracy 0.395 predictive_accuracy 0.43 predictive_accuracy 0.395 predictive_accuracy 0.38 predictive_accuracy 0.365 prior_entropy 3.321928094887362 prior_entropy 3.321928094887362 prior_entropy 3.321928094887362 prior_entropy 3.321928094887362 prior_entropy 3.321928094887362 prior_entropy 3.321928094887362 prior_entropy 3.321928094887362 prior_entropy 3.321928094887362 prior_entropy 3.321928094887362 prior_entropy 3.321928094887362 recall 0.4 [0.65,0.4,0.5,0.15,1,0.15,0.25,0.4,0.35,0.15] recall 0.465 [0.65,0.3,0.65,0.1,1,0.1,0.3,0.6,0.7,0.25] recall 0.425 [0.55,0.5,0.45,0.05,1,0.05,0.25,0.45,0.75,0.2] recall 0.415 [0.65,0.1,0.5,0.1,1,0.3,0.25,0.4,0.6,0.25] recall 0.37 [0.65,0.35,0.45,1,0.25,0.15,0.05,0.35,0.4,0.05] recall 0.395 [0.75,0.3,0.6,0.05,1,0.05,0.1,0.55,0.5,0.05] recall 0.43 [0.75,0.35,0.65,0.15,1,0,0.1,0.45,0.6,0.25] recall 0.395 [0.65,0.3,0.5,0.1,0.9,0,0.35,0.65,0.25,0.25] recall 0.38 [0.65,0.15,0.55,1,0.15,0,0.05,0.35,0.7,0.2] recall 0.365 [0.75,0.05,0.55,0.1,1,0.1,0.05,0.45,0.45,0.15] relative_absolute_error 0.6666666666666659 relative_absolute_error 0.5944444444444439 relative_absolute_error 0.6388888888888882 relative_absolute_error 0.6499999999999992 relative_absolute_error 0.6999999999999993 relative_absolute_error 0.6722222222222214 relative_absolute_error 0.6333333333333326 relative_absolute_error 0.6722222222222214 relative_absolute_error 0.6888888888888881 relative_absolute_error 0.7055555555555546 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_squared_error 0.3464101615137751 root_mean_squared_error 0.32710854467592215 root_mean_squared_error 0.3391164991562631 root_mean_squared_error 0.342052627529741 root_mean_squared_error 0.35496478698597655 root_mean_squared_error 0.34785054261852133 root_mean_squared_error 0.33763886032268225 root_mean_squared_error 0.34785054261852133 root_mean_squared_error 0.3521363372331798 root_mean_squared_error 0.3563705936241088 root_relative_squared_error 1.154700538379251 root_relative_squared_error 1.0903618155864079 root_relative_squared_error 1.1303883305208775 root_relative_squared_error 1.1401754250991374 root_relative_squared_error 1.1832159566199225 root_relative_squared_error 1.159501808728405 root_relative_squared_error 1.1254628677422749 root_relative_squared_error 1.159501808728405 root_relative_squared_error 1.1737877907772667 root_relative_squared_error 1.1879019787470302 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 usercpu_time_millis 3502.7666830000044 usercpu_time_millis 3450.864626999987 usercpu_time_millis 3530.84149 usercpu_time_millis 3440.5916119999915 usercpu_time_millis 3535.5545710000056 usercpu_time_millis 3482.1441619999973 usercpu_time_millis 3443.4473000000307 usercpu_time_millis 3110.0867110000363 usercpu_time_millis 2657.176386000003 usercpu_time_millis 2666.507330999991 usercpu_time_millis_testing 52.319916000016065 usercpu_time_millis_testing 52.419096999983594 usercpu_time_millis_testing 51.178577000001724 usercpu_time_millis_testing 52.67947300001197 usercpu_time_millis_testing 52.679060000002664 usercpu_time_millis_testing 52.498431999993045 usercpu_time_millis_testing 52.405514000014364 usercpu_time_millis_testing 43.79088500002126 usercpu_time_millis_testing 43.72739900000511 usercpu_time_millis_testing 43.82168699999056 usercpu_time_millis_training 3450.4467669999885 usercpu_time_millis_training 3398.4455300000036 usercpu_time_millis_training 3479.6629129999983 usercpu_time_millis_training 3387.9121389999796 usercpu_time_millis_training 3482.875511000003 usercpu_time_millis_training 3429.6457300000043 usercpu_time_millis_training 3391.0417860000166 usercpu_time_millis_training 3066.295826000015 usercpu_time_millis_training 2613.448986999998 usercpu_time_millis_training 2622.6856440000006