10225766 1 Jan van Rijn 9983 Supervised Classification 9666 sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),variancethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,gradientboostingclassifier=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier)(4) 8151198 copy true 9559 fill_value -1 9559 missing_values NaN 9559 strategy "constant" 9559 verbose 0 9559 n_jobs null 9606 remainder "passthrough" 9606 sparse_threshold 0.3 9606 transformer_weights null 9606 transformers [{"oml-python:serialized_object": "component_reference", "value": {"key": "numeric", "step_name": "numeric", "argument_1": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "nominal", "step_name": "nominal", "argument_1": []}}] 9606 memory null 9607 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "imputer", "step_name": "imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}] 9607 axis 0 9608 copy true 9608 missing_values "NaN" 9608 strategy "most_frequent" 9608 verbose 0 9608 copy true 9609 with_mean true 9609 with_std true 9609 memory null 9610 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder"}}] 9610 categorical_features null 9611 categories null 9611 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 9611 handle_unknown "ignore" 9611 n_values null 9611 sparse true 9611 threshold 0.0 9612 memory null 9666 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "columntransformer", "step_name": "columntransformer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "variancethreshold", "step_name": "variancethreshold"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "gradientboostingclassifier", "step_name": "gradientboostingclassifier"}}] 9666 criterion "friedman_mse" 9667 init null 9667 learning_rate 0.008450267356125375 9667 loss "deviance" 9667 max_depth 3 9667 max_features 0.4524419153287036 9667 max_leaf_nodes null 9667 min_impurity_decrease 0.5720450011377862 9667 min_impurity_split null 9667 min_samples_leaf 18 9667 min_samples_split 14 9667 min_weight_fraction_leaf 0.049346694074198505 9667 n_estimators 459 9667 n_iter_no_change 1672 9667 presort "auto" 9667 random_state 18722 9667 subsample 0.7827750462691007 9667 tol 0.07246260029162718 9667 validation_fraction 0.7975657164605423 9667 verbose 0 9667 warm_start false 9667 openml-python Sklearn_0.20.3. 1471 eeg-eye-state https://www.openml.org/data/download/1587924/phplE7q6h -1 21372448 description https://api.openml.org/data/download/21372448/description.xml -1 21372449 predictions https://api.openml.org/data/download/21372449/predictions.arff area_under_roc_curve 0.8144845877933978 [0.814485,0.814485] average_cost 0 f_measure 0.740073063375651 [0.780735,0.690133] kappa 0.4734377643521868 kb_relative_information_score 3520.1730515120225 mean_absolute_error 0.3958250172602414 mean_prior_absolute_error 0.4947574918117115 number_of_instances 14980 [8257,6723] precision 0.7442392773223234 [0.737403,0.752635] predictive_accuracy 0.7431909212283044 prior_entropy 0.9924243999391255 recall 0.7431909212283044 [0.829478,0.637216] relative_absolute_error 0.8000384507787897 root_mean_prior_squared_error 0.4973714869043071 root_mean_squared_error 0.4260896190391573 root_relative_squared_error 0.8566828422175632 total_cost 0 area_under_roc_curve 0.827762884814943 [0.827763,0.827763] area_under_roc_curve 0.8180884641992391 [0.818088,0.818088] area_under_roc_curve 0.8138520768476882 [0.813852,0.813852] area_under_roc_curve 0.8060134541104577 [0.806013,0.806013] area_under_roc_curve 0.8239489651792921 [0.823949,0.823949] area_under_roc_curve 0.8238426726622853 [0.823843,0.823843] area_under_roc_curve 0.8247326472962067 [0.824733,0.824733] area_under_roc_curve 0.8044108244405421 [0.804411,0.804411] area_under_roc_curve 0.8082606150659641 [0.808261,0.808261] area_under_roc_curve 0.7980872619208429 [0.798087,0.798087] 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 0.7483521881595019 [0.788876,0.698541] f_measure 0.7349139246562348 [0.777273,0.682848] f_measure 0.7485367103841422 [0.785755,0.702789] f_measure 0.7313937926945286 [0.774816,0.678021] f_measure 0.7451455786230149 [0.790151,0.689826] f_measure 0.748692294588434 [0.787913,0.700483] f_measure 0.7365676486319864 [0.782267,0.680395] f_measure 0.7339652953085413 [0.772072,0.687253] f_measure 0.7455853455791148 [0.786606,0.6953] f_measure 0.7270274534181966 [0.760729,0.685714] kappa 0.4902543349640141 kappa 0.4629999487888564 kappa 0.4903916135704892 kappa 0.4559205891770734 kappa 0.484327408721132 kappa 0.4908281525827002 kappa 0.4668276269488609 kappa 0.4610205185847768 kappa 0.4848778060883864 kappa 0.4470961224197377 kb_relative_information_score 380.03346683808434 kb_relative_information_score 355.18242564213074 kb_relative_information_score 351.35892958815947 kb_relative_information_score 339.2685524952065 kb_relative_information_score 358.0739100399338 kb_relative_information_score 354.45140664998115 kb_relative_information_score 353.69115672293697 kb_relative_information_score 340.495848280703 kb_relative_information_score 355.2927837046448 kb_relative_information_score 332.3245715502229 mean_absolute_error 0.3876220000200914 mean_absolute_error 0.3950383817603672 mean_absolute_error 0.3963084798192364 mean_absolute_error 0.3996572514864823 mean_absolute_error 0.39408856255390423 mean_absolute_error 0.3955993415212358 mean_absolute_error 0.3950792506307291 mean_absolute_error 0.39910210085530495 mean_absolute_error 0.39466711428426127 mean_absolute_error 0.40108768967081715 mean_prior_absolute_error 0.494736986564547 mean_prior_absolute_error 0.494736986564547 mean_prior_absolute_error 0.494736986564547 mean_prior_absolute_error 0.494736986564547 mean_prior_absolute_error 0.494736986564547 mean_prior_absolute_error 0.494736986564547 mean_prior_absolute_error 0.494736986564547 mean_prior_absolute_error 0.49480533738838384 mean_prior_absolute_error 0.49480533738838384 mean_prior_absolute_error 0.49480533738838384 number_of_instances 1498 [826,672] number_of_instances 1498 [826,672] number_of_instances 1498 [826,672] number_of_instances 1498 [826,672] number_of_instances 1498 [826,672] number_of_instances 1498 [826,672] number_of_instances 1498 [826,672] number_of_instances 1498 [825,673] number_of_instances 1498 [825,673] number_of_instances 1498 [825,673] precision 0.7534593325618368 [0.742521,0.766904] precision 0.7394635737987341 [0.732334,0.748227] precision 0.7515295877449023 [0.747541,0.756432] precision 0.7361785915654925 [0.728922,0.745098] precision 0.753440896253962 [0.734651,0.776536] precision 0.7529316917414387 [0.744612,0.763158] precision 0.7438442629254822 [0.729079,0.761993] precision 0.7362491011933878 [0.736784,0.735593] precision 0.7508761551279663 [0.739594,0.764706] precision 0.7274615063253376 [0.738584,0.713826] predictive_accuracy 0.7516688918558078 predictive_accuracy 0.7383177570093459 predictive_accuracy 0.7510013351134845 predictive_accuracy 0.7349799732977302 predictive_accuracy 0.7496662216288386 predictive_accuracy 0.7516688918558078 predictive_accuracy 0.7409879839786382 predictive_accuracy 0.7363150867823766 predictive_accuracy 0.7489986648865155 predictive_accuracy 0.7283044058744993 prior_entropy 0.9924243999391255 prior_entropy 0.9924243999391255 prior_entropy 0.9924243999391255 prior_entropy 0.9924243999391255 prior_entropy 0.9924243999391255 prior_entropy 0.9924243999391255 prior_entropy 0.9924243999391255 prior_entropy 0.9924243999391255 prior_entropy 0.9924243999391255 prior_entropy 0.9924243999391255 recall 0.7516688918558078 [0.841404,0.641369] recall 0.7383177570093458 [0.828087,0.627976] recall 0.7510013351134847 [0.828087,0.65625] recall 0.7349799732977303 [0.826877,0.622024] recall 0.7496662216288384 [0.854722,0.620536] recall 0.7516688918558078 [0.836562,0.647321] recall 0.7409879839786382 [0.843826,0.614583] recall 0.7363150867823764 [0.810909,0.644874] recall 0.7489986648865153 [0.84,0.637444] recall 0.7283044058744993 [0.784242,0.659733] relative_absolute_error 0.7834910478631041 relative_absolute_error 0.7984816023227073 relative_absolute_error 0.8010488210537925 relative_absolute_error 0.8078176128728555 relative_absolute_error 0.7965617555510751 relative_absolute_error 0.799615456827429 relative_absolute_error 0.7985642095897437 relative_absolute_error 0.8065840658910288 relative_absolute_error 0.7976209722541415 relative_absolute_error 0.8105969345193106 root_mean_prior_squared_error 0.4973508728636661 root_mean_prior_squared_error 0.4973508728636661 root_mean_prior_squared_error 0.4973508728636661 root_mean_prior_squared_error 0.4973508728636661 root_mean_prior_squared_error 0.4973508728636661 root_mean_prior_squared_error 0.4973508728636661 root_mean_prior_squared_error 0.4973508728636661 root_mean_prior_squared_error 0.4974195830102464 root_mean_prior_squared_error 0.4974195830102464 root_mean_prior_squared_error 0.4974195830102464 root_mean_squared_error 0.41911568571407115 root_mean_squared_error 0.4252080311258201 root_mean_squared_error 0.4262507372142241 root_mean_squared_error 0.42916771971239615 root_mean_squared_error 0.4240679109520968 root_mean_squared_error 0.42380372881640493 root_mean_squared_error 0.42446381705893343 root_mean_squared_error 0.4292992347911796 root_mean_squared_error 0.4271825020853219 root_mean_squared_error 0.43219640840096657 root_relative_squared_error 0.8426961901179959 root_relative_squared_error 0.8549457823961198 root_relative_squared_error 0.8570423024693636 root_relative_squared_error 0.8629073419361218 root_relative_squared_error 0.8526533964048001 root_relative_squared_error 0.8521222178141791 root_relative_squared_error 0.8534494261866663 root_relative_squared_error 0.8630525404592614 root_relative_squared_error 0.8587971134954739 root_relative_squared_error 0.8688769464712927 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 1453.043327004707 usercpu_time_millis 1353.9982509973925 usercpu_time_millis 1358.105235005496 usercpu_time_millis 1369.8537379968911 usercpu_time_millis 1370.4350769985467 usercpu_time_millis 1367.1419100064668 usercpu_time_millis 1365.3957639980945 usercpu_time_millis 1382.4959000048693 usercpu_time_millis 1368.6470600005123 usercpu_time_millis 1379.6964449938969 usercpu_time_millis_testing 13.112505999743007 usercpu_time_millis_testing 12.79547900048783 usercpu_time_millis_testing 13.018383004236966 usercpu_time_millis_testing 13.356110997847281 usercpu_time_millis_testing 13.695228997676168 usercpu_time_millis_testing 13.335396004549693 usercpu_time_millis_testing 13.6510480006109 usercpu_time_millis_testing 13.567497000622097 usercpu_time_millis_testing 12.995877004868817 usercpu_time_millis_testing 13.413483997283038 usercpu_time_millis_training 1439.930821004964 usercpu_time_millis_training 1341.2027719969046 usercpu_time_millis_training 1345.086852001259 usercpu_time_millis_training 1356.4976269990439 usercpu_time_millis_training 1356.7398480008706 usercpu_time_millis_training 1353.806514001917 usercpu_time_millis_training 1351.7447159974836 usercpu_time_millis_training 1368.9284030042472 usercpu_time_millis_training 1355.6511829956435 usercpu_time_millis_training 1366.2829609966138