10222637 1 Jan van Rijn 3543 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) 8148069 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": [1, 3]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "nominal", "step_name": "nominal", "argument_1": [0, 2, 4]}}] 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 "median" 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 3.3058496822474024e-05 9667 loss "deviance" 9667 max_depth 5 9667 max_features 0.3712520122396866 9667 max_leaf_nodes null 9667 min_impurity_decrease 0.7505509550421775 9667 min_impurity_split null 9667 min_samples_leaf 7 9667 min_samples_split 3 9667 min_weight_fraction_leaf 0.10833943903836213 9667 n_estimators 1468 9667 n_iter_no_change 621 9667 presort "auto" 9667 random_state 55299 9667 subsample 0.3235366701796184 9667 tol 0.0008439498139005972 9667 validation_fraction 0.4693489849493405 9667 verbose 0 9667 warm_start false 9667 openml-python Sklearn_0.20.3. 451 irish https://www.openml.org/data/download/52563/irish.arff -1 21366190 description https://api.openml.org/data/download/21366190/description.xml -1 21366191 predictions https://api.openml.org/data/download/21366191/predictions.arff area_under_roc_curve 0.9971482273640547 [0.997148,0.997148] average_cost 0 kappa 0 kb_relative_information_score 20.239704163663145 mean_absolute_error 0.47815904978109863 mean_prior_absolute_error 0.49375298804780854 number_of_instances 500 [278,222] predictive_accuracy 0.556 prior_entropy 0.9910046621528215 recall 0.556 [1,0] relative_absolute_error 0.9684175313482862 root_mean_prior_squared_error 0.49685415342632255 root_mean_squared_error 0.4833061803902836 root_relative_squared_error 0.9727324951545404 total_cost 0 area_under_roc_curve 1 [1,1] area_under_roc_curve 0.9935064935064934 [0.993506,0.993506] area_under_roc_curve 0.9983766233766234 [0.998377,0.998377] area_under_roc_curve 0.991883116883117 [0.991883,0.991883] area_under_roc_curve 1 [1,1] area_under_roc_curve 1 [1,1] area_under_roc_curve 1 [1,1] area_under_roc_curve 1 [1,1] area_under_roc_curve 0.998389694041868 [0.99839,0.99839] area_under_roc_curve 0.9903381642512078 [0.990338,0.990338] 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 kappa 0 kappa 0 kappa 0 kappa 0 kappa 0 kappa 0 kappa 0 kappa 0 kappa 0 kappa 0 kb_relative_information_score 2.2514757164416555 kb_relative_information_score 1.844675114054745 kb_relative_information_score 2.008242355803002 kb_relative_information_score 1.750142093524635 kb_relative_information_score 2.1020860760432494 kb_relative_information_score 2.0151912152218245 kb_relative_information_score 2.0133225286269796 kb_relative_information_score 2.220570576054223 kb_relative_information_score 2.143021085638008 kb_relative_information_score 1.8909774022548347 mean_absolute_error 0.47618219816102064 mean_absolute_error 0.4791296159772231 mean_absolute_error 0.47783982302392564 mean_absolute_error 0.47974145340266555 mean_absolute_error 0.47722735365332936 mean_absolute_error 0.4777512563295359 mean_absolute_error 0.47780797705823347 mean_absolute_error 0.47633664197258996 mean_absolute_error 0.4788259055010991 mean_absolute_error 0.4807482727313628 mean_prior_absolute_error 0.49330677290836705 mean_prior_absolute_error 0.49330677290836705 mean_prior_absolute_error 0.49330677290836705 mean_prior_absolute_error 0.49330677290836705 mean_prior_absolute_error 0.49330677290836705 mean_prior_absolute_error 0.49330677290836705 mean_prior_absolute_error 0.49330677290836705 mean_prior_absolute_error 0.49330677290836705 mean_prior_absolute_error 0.49553784860557826 mean_prior_absolute_error 0.49553784860557826 number_of_instances 50 [28,22] number_of_instances 50 [28,22] number_of_instances 50 [28,22] number_of_instances 50 [28,22] number_of_instances 50 [28,22] number_of_instances 50 [28,22] number_of_instances 50 [28,22] number_of_instances 50 [28,22] number_of_instances 50 [27,23] number_of_instances 50 [27,23] predictive_accuracy 0.56 predictive_accuracy 0.56 predictive_accuracy 0.56 predictive_accuracy 0.56 predictive_accuracy 0.56 predictive_accuracy 0.56 predictive_accuracy 0.56 predictive_accuracy 0.56 predictive_accuracy 0.54 predictive_accuracy 0.54 prior_entropy 0.9910046621528215 prior_entropy 0.9910046621528215 prior_entropy 0.9910046621528215 prior_entropy 0.9910046621528215 prior_entropy 0.9910046621528215 prior_entropy 0.9910046621528215 prior_entropy 0.9910046621528215 prior_entropy 0.9910046621528215 prior_entropy 0.9910046621528215 prior_entropy 0.9910046621528215 recall 0.56 [1,0] recall 0.56 [1,0] recall 0.56 [1,0] recall 0.56 [1,0] recall 0.56 [1,0] recall 0.56 [1,0] recall 0.56 [1,0] recall 0.56 [1,0] recall 0.54 [1,0] recall 0.54 [1,0] relative_absolute_error 0.9652861552125347 relative_absolute_error 0.9712609724623071 relative_absolute_error 0.968646386520798 relative_absolute_error 0.9725012502347675 relative_absolute_error 0.9674048277094617 relative_absolute_error 0.9684668497715505 relative_absolute_error 0.9685818304120213 relative_absolute_error 0.9655992338484893 relative_absolute_error 0.966275142955264 relative_absolute_error 0.9701544979544293 root_mean_prior_squared_error 0.49640490996518694 root_mean_prior_squared_error 0.49640490996518694 root_mean_prior_squared_error 0.49640490996518694 root_mean_prior_squared_error 0.49640490996518694 root_mean_prior_squared_error 0.49640490996518694 root_mean_prior_squared_error 0.49640490996518694 root_mean_prior_squared_error 0.49640490996518694 root_mean_prior_squared_error 0.49640490996518694 root_mean_prior_squared_error 0.49864707994207336 root_mean_prior_squared_error 0.49864707994207336 root_mean_squared_error 0.480983568423162 root_mean_squared_error 0.48433735495360947 root_mean_squared_error 0.48290928220574575 root_mean_squared_error 0.48495225003772974 root_mean_squared_error 0.48209136358475446 root_mean_squared_error 0.4828758304706202 root_mean_squared_error 0.48293266016011016 root_mean_squared_error 0.4812561964540522 root_mean_squared_error 0.48434491575621086 root_mean_squared_error 0.4863518120573405 root_relative_squared_error 0.9689339463964882 root_relative_squared_error 0.9756900973996737 root_relative_squared_error 0.9728132669751643 root_relative_squared_error 0.9769287940196635 root_relative_squared_error 0.9711655825857237 root_relative_squared_error 0.9727458789730433 root_relative_squared_error 0.9728603615020215 root_relative_squared_error 0.9694831513407128 root_relative_squared_error 0.9713180628922485 root_relative_squared_error 0.975342745642547 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 1135.3066279989434 usercpu_time_millis 1027.5725840037921 usercpu_time_millis 1024.621800002933 usercpu_time_millis 1026.0046550029074 usercpu_time_millis 1029.6523430006346 usercpu_time_millis 1021.5859370000544 usercpu_time_millis 1029.2838020031922 usercpu_time_millis 1034.6964250020392 usercpu_time_millis 1032.8493019987945 usercpu_time_millis 1024.6263620028913 usercpu_time_millis_testing 5.179110001336085 usercpu_time_millis_testing 5.064598000899423 usercpu_time_millis_testing 5.220508002821589 usercpu_time_millis_testing 5.4390430013882 usercpu_time_millis_testing 5.49347900232533 usercpu_time_millis_testing 5.068902999482816 usercpu_time_millis_testing 5.1150550025340635 usercpu_time_millis_testing 5.958936002571136 usercpu_time_millis_testing 5.089186000986956 usercpu_time_millis_testing 5.311779001203831 usercpu_time_millis_training 1130.1275179976074 usercpu_time_millis_training 1022.5079860028927 usercpu_time_millis_training 1019.4012920001114 usercpu_time_millis_training 1020.5656120015192 usercpu_time_millis_training 1024.1588639983092 usercpu_time_millis_training 1016.5170340005716 usercpu_time_millis_training 1024.1687470006582 usercpu_time_millis_training 1028.737488999468 usercpu_time_millis_training 1027.7601159978076 usercpu_time_millis_training 1019.3145830016874