9200270 3886 Benjamin Strang 3996 Supervised Classification predictive_accuracy 7722 sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.pipeline.Pipeline(imputation=mylib.preprocessing_openml14.ConditionalImputer,one-hot-encoder=sklearn.preprocessing.data.OneHotEncoder,variance-thresholding=sklearn.feature_selection.variance_threshold.VarianceThreshold,feature-scaling=sklearn.preprocessing.data.StandardScaler,classifier=sklearn.linear_model.stochastic_gradient.SGDClassifier))(1) 7130158 axis 0 7633 categorical_features [] 7633 copy true 7633 fill_empty 0 7633 missing_values "NaN" 7633 strategy "median" 7633 strategy_nominal "most_frequent" 7633 verbose 0 7633 categorical_features [] 7644 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 7644 handle_unknown "ignore" 7644 n_values "auto" 7644 sparse false 7644 threshold 0.0 7645 copy true 7646 with_mean true 7646 with_std true 7646 cv 3 7722 error_score "raise" 7722 fit_params null 7722 iid true 7722 n_iter 250 7722 n_jobs -1 7722 param_distributions {"classifier__alpha": {"oml-python:serialized_object": "rv_frozen", "value": {"dist": "mylib.distributions.loguniform_gen", "a": 1e-07, "b": 0.1, "args": [], "kwds": {"base": 10, "low": 1e-07, "high": 0.1}}}, "classifier__penalty": ["l2", "l1", "elasticnet"], "classifier__tol": {"oml-python:serialized_object": "rv_frozen", "value": {"dist": "mylib.distributions.loguniform_gen", "a": 1e-05, "b": 0.1, "args": [], "kwds": {"base": 10, "low": 1e-05, "high": 0.1}}}, "imputation__strategy": ["mean", "median", "most_frequent"]} 7722 pre_dispatch "2*n_jobs" 7722 random_state 3 7722 refit true 7722 return_train_score "warn" 7722 scoring null 7722 verbose 0 7722 memory null 7723 alpha 0.0001 7724 average false 7724 class_weight null 7724 epsilon 0.1 7724 eta0 0.0 7724 fit_intercept true 7724 l1_ratio 0.15 7724 learning_rate "optimal" 7724 loss "log" 7724 max_iter 2000 7724 n_iter null 7724 n_jobs 1 7724 penalty "l2" 7724 power_t 0.5 7724 random_state 3 7724 shuffle true 7724 tol null 7724 verbose 0 7724 warm_start false 7724 openml-python Sklearn_0.19.1. study_123 1162 AP_Ovary_Uterus https://www.openml.org/data/download/54045/AP_Ovary_Uterus.arff -1 19326965 description https://api.openml.org/data/download/19326965/description.xml -1 19326966 predictions https://api.openml.org/data/download/19326966/predictions.arff area_under_roc_curve 0.8562629905547157 [0.85602,0.856651] average_cost 0 f_measure 0.8639168431705235 [0.887179,0.826772] kappa 0.714055057721805 kb_relative_information_score 226.29405613445874 mean_absolute_error 0.13764415835336627 mean_prior_absolute_error 0.47375584694425227 number_of_instances 322 [198,124] precision 0.8650934663162925 [0.901042,0.807692] predictive_accuracy 0.8633540372670808 prior_entropy 0.9620372403199735 recall 0.8633540372670807 [0.873737,0.846774] relative_absolute_error 0.29053817328309006 root_mean_prior_squared_error 0.4866178408152876 root_mean_squared_error 0.3694439318271337 root_relative_squared_error 0.7592075358522844 total_cost 0 area_under_roc_curve 0.9692307692307691 [0.969231,0.969231] area_under_roc_curve 0.9154428904428905 [0.894231,0.948077] area_under_roc_curve 0.74765625 [0.75,0.74375] area_under_roc_curve 0.9458333333333333 [0.945833,0.945833] area_under_roc_curve 0.9692708333333334 [0.958333,0.9875] area_under_roc_curve 0.7916666666666666 [0.791667,0.791667] area_under_roc_curve 0.8549479166666667 [0.841667,0.877083] area_under_roc_curve 0.8354166666666666 [0.841667,0.825] area_under_roc_curve 0.9493927125506074 [0.949393,0.949393] area_under_roc_curve 0.8041497975708503 [0.771255,0.852227] 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 0.9383116883116883 [0.952381,0.916667] f_measure 0.908381374722838 [0.926829,0.88] f_measure 0.7530364372469636 [0.789474,0.692308] f_measure 0.938259109311741 [0.947368,0.923077] f_measure 0.9684517497348887 [0.97561,0.956522] f_measure 0.7845345345345345 [0.810811,0.740741] f_measure 0.844871794871795 [0.871795,0.8] f_measure 0.844871794871795 [0.871795,0.8] f_measure 0.8445136852394917 [0.848485,0.83871] f_measure 0.8043831168831169 [0.857143,0.727273] kappa 0.8695652173913044 kappa 0.8070175438596491 kappa 0.4838709677419355 kappa 0.8709677419354839 kappa 0.9322033898305084 kappa 0.5555555555555556 kappa 0.6721311475409836 kappa 0.6721311475409836 kappa 0.6946564885496184 kappa 0.5914893617021276 kb_relative_information_score 28.40294819880317 kb_relative_information_score 26.547358986685097 kb_relative_information_score 14.484852432892401 kb_relative_information_score 27.440428455323012 kb_relative_information_score 29.5996911257358 kb_relative_information_score 16.6441151032986 kb_relative_information_score 20.962640444111003 kb_relative_information_score 20.962640444111003 kb_relative_information_score 21.748695567887122 kb_relative_information_score 19.500685375611663 mean_absolute_error 0.0689827887143846 mean_absolute_error 0.09401372910823969 mean_absolute_error 0.25 mean_absolute_error 0.06250000000013725 mean_absolute_error 0.03125 mean_absolute_error 0.21875 mean_absolute_error 0.15625 mean_absolute_error 0.15625 mean_absolute_error 0.15445408792949963 mean_absolute_error 0.18750009649652963 mean_prior_absolute_error 0.4757762813318369 mean_prior_absolute_error 0.4757762813318369 mean_prior_absolute_error 0.47145061728395066 mean_prior_absolute_error 0.47145061728395066 mean_prior_absolute_error 0.47145061728395066 mean_prior_absolute_error 0.47145061728395066 mean_prior_absolute_error 0.47145061728395066 mean_prior_absolute_error 0.47145061728395066 mean_prior_absolute_error 0.478587962962963 mean_prior_absolute_error 0.478587962962963 number_of_instances 33 [20,13] number_of_instances 33 [20,13] number_of_instances 32 [20,12] number_of_instances 32 [20,12] number_of_instances 32 [20,12] number_of_instances 32 [20,12] number_of_instances 32 [20,12] number_of_instances 32 [20,12] number_of_instances 32 [19,13] number_of_instances 32 [19,13] precision 0.9449035812672175 [0.909091,1] precision 0.9094516594516594 [0.904762,0.916667] precision 0.761904761904762 [0.833333,0.642857] precision 0.9464285714285714 [1,0.857143] precision 0.9702380952380952 [0.952381,1] precision 0.8014705882352942 [0.882353,0.666667] precision 0.8476720647773279 [0.894737,0.769231] precision 0.8476720647773279 [0.894737,0.769231] precision 0.8871527777777778 [1,0.722222] precision 0.8257850241545894 [0.782609,0.888889] predictive_accuracy 0.9393939393939393 predictive_accuracy 0.9090909090909091 predictive_accuracy 0.75 predictive_accuracy 0.9375 predictive_accuracy 0.96875 predictive_accuracy 0.78125 predictive_accuracy 0.84375 predictive_accuracy 0.84375 predictive_accuracy 0.84375 predictive_accuracy 0.8125 prior_entropy 0.9620372403199735 prior_entropy 0.9620372403199735 prior_entropy 0.9620372403199735 prior_entropy 0.9620372403199735 prior_entropy 0.9620372403199735 prior_entropy 0.9620372403199735 prior_entropy 0.9620372403199735 prior_entropy 0.9620372403199735 prior_entropy 0.9620372403199735 prior_entropy 0.9620372403199735 recall 0.9393939393939394 [1,0.846154] recall 0.9090909090909091 [0.95,0.846154] recall 0.75 [0.75,0.75] recall 0.9375 [0.9,1] recall 0.96875 [1,0.916667] recall 0.78125 [0.75,0.833333] recall 0.84375 [0.85,0.833333] recall 0.84375 [0.85,0.833333] recall 0.84375 [0.736842,1] recall 0.8125 [0.947368,0.615385] relative_absolute_error 0.14498996991039906 relative_absolute_error 0.19760070603996435 relative_absolute_error 0.5302782324058919 relative_absolute_error 0.1325695581017641 relative_absolute_error 0.06628477905073649 relative_absolute_error 0.4639934533551554 relative_absolute_error 0.33142389525368243 relative_absolute_error 0.33142389525368243 relative_absolute_error 0.3227287351175034 relative_absolute_error 0.39177771069649714 root_mean_prior_squared_error 0.48868942835641166 root_mean_prior_squared_error 0.48868942835641166 root_mean_prior_squared_error 0.484243423640869 root_mean_prior_squared_error 0.484243423640869 root_mean_prior_squared_error 0.484243423640869 root_mean_prior_squared_error 0.484243423640869 root_mean_prior_squared_error 0.484243423640869 root_mean_prior_squared_error 0.484243423640869 root_mean_prior_squared_error 0.49155776773278886 root_mean_prior_squared_error 0.49155776773278886 root_mean_squared_error 0.24927722749363973 root_mean_squared_error 0.30203835947535235 root_mean_squared_error 0.5 root_mean_squared_error 0.25 root_mean_squared_error 0.1767766952966369 root_mean_squared_error 0.46770717334674267 root_mean_squared_error 0.39528470752104744 root_mean_squared_error 0.39528470752104744 root_mean_squared_error 0.39084489888472906 root_mean_squared_error 0.4330127018925634 root_relative_squared_error 0.5100933497416206 root_relative_squared_error 0.618057895156818 root_relative_squared_error 1.032538544851394 root_relative_squared_error 0.516269272425697 root_relative_squared_error 0.3650575034504555 root_relative_squared_error 0.9658513683680087 root_relative_squared_error 0.8162933934115825 root_relative_squared_error 0.8162933934115825 root_relative_squared_error 0.7951148868777365 root_relative_squared_error 0.8808989101926865 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