10223430 1 Jan van Rijn 3485 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) 8148862 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, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "nominal", "step_name": "nominal", "argument_1": [294, 295, 296, 297, 298]}}] 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 "mse" 9667 init null 9667 learning_rate 0.0049120097142137005 9667 loss "deviance" 9667 max_depth 31 9667 max_features 0.6029597926778885 9667 max_leaf_nodes null 9667 min_impurity_decrease 0.08027722789963387 9667 min_impurity_split null 9667 min_samples_leaf 16 9667 min_samples_split 13 9667 min_weight_fraction_leaf 0.1324858559300236 9667 n_estimators 144 9667 n_iter_no_change 430 9667 presort "auto" 9667 random_state 39911 9667 subsample 0.8838332154171349 9667 tol 0.0002844746152672428 9667 validation_fraction 0.8008343127385028 9667 verbose 0 9667 warm_start false 9667 openml-python Sklearn_0.20.3. 312 scene https://www.openml.org/data/download/1390080/phpuZu33P -1 21367776 description https://api.openml.org/data/download/21367776/description.xml -1 21367777 predictions https://api.openml.org/data/download/21367777/predictions.arff area_under_roc_curve 0.500107437744817 [0.500107,0.500107] average_cost 0 kappa 0 kb_relative_information_score 93.69086298071007 mean_absolute_error 0.27892543854010743 mean_prior_absolute_error 0.29416743712946186 number_of_instances 2407 [1976,431] predictive_accuracy 0.8209389281262983 prior_entropy 0.6786037019780878 recall 0.8209389281262983 [1,0] relative_absolute_error 0.9481859761974725 root_mean_prior_squared_error 0.3834035412052162 root_mean_squared_error 0.38412173944366546 root_relative_squared_error 1.0018732175404317 total_cost 0 area_under_roc_curve 0.5 [0.5,0.5] area_under_roc_curve 0.5 [0.5,0.5] area_under_roc_curve 0.5 [0.5,0.5] area_under_roc_curve 0.5 [0.5,0.5] area_under_roc_curve 0.5 [0.5,0.5] area_under_roc_curve 0.5 [0.5,0.5] area_under_roc_curve 0.5 [0.5,0.5] area_under_roc_curve 0.5 [0.5,0.5] area_under_roc_curve 0.5 [0.5,0.5] area_under_roc_curve 0.5 [0.5,0.5] 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 9.458515118461609 kb_relative_information_score 9.458515118461609 kb_relative_information_score 9.458515118461609 kb_relative_information_score 9.458515118461609 kb_relative_information_score 9.458515118461609 kb_relative_information_score 9.458515118461609 kb_relative_information_score 9.336469762094362 kb_relative_information_score 9.201100835948266 kb_relative_information_score 9.201100835948266 kb_relative_information_score 9.201100835948266 mean_absolute_error 0.2783886699092707 mean_absolute_error 0.2783886699092707 mean_absolute_error 0.2783886699092707 mean_absolute_error 0.2783886699092707 mean_absolute_error 0.2783886699092707 mean_absolute_error 0.2783886699092707 mean_absolute_error 0.28124817094269944 mean_absolute_error 0.2792259787222806 mean_absolute_error 0.2792259787222806 mean_absolute_error 0.2792259787222806 mean_prior_absolute_error 0.293758364638829 mean_prior_absolute_error 0.293758364638829 mean_prior_absolute_error 0.293758364638829 mean_prior_absolute_error 0.293758364638829 mean_prior_absolute_error 0.293758364638829 mean_prior_absolute_error 0.293758364638829 mean_prior_absolute_error 0.29641954703058604 mean_prior_absolute_error 0.2942351598173521 mean_prior_absolute_error 0.2942351598173521 mean_prior_absolute_error 0.2942351598173521 number_of_instances 241 [198,43] number_of_instances 241 [198,43] number_of_instances 241 [198,43] number_of_instances 241 [198,43] number_of_instances 241 [198,43] number_of_instances 241 [198,43] number_of_instances 241 [197,44] number_of_instances 240 [197,43] number_of_instances 240 [197,43] number_of_instances 240 [197,43] predictive_accuracy 0.8215767634854773 predictive_accuracy 0.8215767634854773 predictive_accuracy 0.8215767634854773 predictive_accuracy 0.8215767634854773 predictive_accuracy 0.8215767634854773 predictive_accuracy 0.8215767634854773 predictive_accuracy 0.8174273858921162 predictive_accuracy 0.8208333333333333 predictive_accuracy 0.8208333333333333 predictive_accuracy 0.8208333333333333 prior_entropy 0.6786037019780878 prior_entropy 0.6786037019780878 prior_entropy 0.6786037019780878 prior_entropy 0.6786037019780878 prior_entropy 0.6786037019780878 prior_entropy 0.6786037019780878 prior_entropy 0.6786037019780878 prior_entropy 0.6786037019780878 prior_entropy 0.6786037019780878 prior_entropy 0.6786037019780878 recall 0.8215767634854771 [1,0] recall 0.8215767634854771 [1,0] recall 0.8215767634854771 [1,0] recall 0.8215767634854771 [1,0] recall 0.8215767634854771 [1,0] recall 0.8215767634854771 [1,0] recall 0.8174273858921162 [1,0] recall 0.8208333333333333 [1,0] recall 0.8208333333333333 [1,0] recall 0.8208333333333333 [1,0] relative_absolute_error 0.9476791248192878 relative_absolute_error 0.9476791248192878 relative_absolute_error 0.9476791248192878 relative_absolute_error 0.9476791248192878 relative_absolute_error 0.9476791248192878 relative_absolute_error 0.9476791248192878 relative_absolute_error 0.9488178959860527 relative_absolute_error 0.9489891653180113 relative_absolute_error 0.9489891653180113 relative_absolute_error 0.9489891653180113 root_mean_prior_squared_error 0.3828696944367244 root_mean_prior_squared_error 0.3828696944367244 root_mean_prior_squared_error 0.3828696944367244 root_mean_prior_squared_error 0.3828696944367244 root_mean_prior_squared_error 0.3828696944367244 root_mean_prior_squared_error 0.3828696944367244 root_mean_prior_squared_error 0.3863293741224291 root_mean_prior_squared_error 0.38349184880071946 root_mean_prior_squared_error 0.38349184880071946 root_mean_prior_squared_error 0.38349184880071946 root_mean_squared_error 0.38355842884966956 root_mean_squared_error 0.38355842884966956 root_mean_squared_error 0.38355842884966956 root_mean_squared_error 0.38355842884966956 root_mean_squared_error 0.38355842884966956 root_mean_squared_error 0.38355842884966956 root_mean_squared_error 0.3872680846326686 root_mean_squared_error 0.3841947535744088 root_mean_squared_error 0.3841947535744088 root_mean_squared_error 0.3841947535744088 root_relative_squared_error 1.0017988741938908 root_relative_squared_error 1.0017988741938908 root_relative_squared_error 1.0017988741938908 root_relative_squared_error 1.0017988741938908 root_relative_squared_error 1.0017988741938908 root_relative_squared_error 1.0017988741938908 root_relative_squared_error 1.0024298191468661 root_relative_squared_error 1.0018329066859897 root_relative_squared_error 1.0018329066859897 root_relative_squared_error 1.0018329066859897 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 461.83948000179953 usercpu_time_millis 399.5720410021022 usercpu_time_millis 395.30116700188955 usercpu_time_millis 402.8139740039478 usercpu_time_millis 391.66533700336004 usercpu_time_millis 394.0391290016123 usercpu_time_millis 394.0825399986352 usercpu_time_millis 394.95252999768127 usercpu_time_millis 397.293965001154 usercpu_time_millis 391.58950400087633 usercpu_time_millis_testing 4.080198999872664 usercpu_time_millis_testing 3.56173900217982 usercpu_time_millis_testing 3.5543000012694392 usercpu_time_millis_testing 3.576843002520036 usercpu_time_millis_testing 3.5194890006096102 usercpu_time_millis_testing 3.548623000824591 usercpu_time_millis_testing 3.5136779988533817 usercpu_time_millis_testing 3.431802997511113 usercpu_time_millis_testing 3.47724900348112 usercpu_time_millis_testing 3.4552739998616744 usercpu_time_millis_training 457.75928100192687 usercpu_time_millis_training 396.0103019999224 usercpu_time_millis_training 391.7468670006201 usercpu_time_millis_training 399.23713100142777 usercpu_time_millis_training 388.1458480027504 usercpu_time_millis_training 390.4905060007877 usercpu_time_millis_training 390.5688619997818 usercpu_time_millis_training 391.52072700017015 usercpu_time_millis_training 393.8167159976729 usercpu_time_millis_training 388.13423000101466