10223388 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) 8148820 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 "friedman_mse" 9667 init null 9667 learning_rate 1.676296003220604e-05 9667 loss "deviance" 9667 max_depth 21 9667 max_features 0.5764107279512857 9667 max_leaf_nodes null 9667 min_impurity_decrease 0.972300057381092 9667 min_impurity_split null 9667 min_samples_leaf 16 9667 min_samples_split 10 9667 min_weight_fraction_leaf 0.20063577589476922 9667 n_estimators 1116 9667 n_iter_no_change 756 9667 presort "auto" 9667 random_state 42750 9667 subsample 0.03224485750637662 9667 tol 0.013514716781893183 9667 validation_fraction 0.15482625720934973 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 21367692 description https://api.openml.org/data/download/21367692/description.xml -1 21367693 predictions https://api.openml.org/data/download/21367693/predictions.arff area_under_roc_curve 0.8355415801685188 [0.835542,0.835542] average_cost 0 kappa 0 kb_relative_information_score -10.697708780307012 mean_absolute_error 0.2945042280205025 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 1.0011448952145319 root_mean_prior_squared_error 0.3834035412052162 root_mean_squared_error 0.38293421433909836 root_relative_squared_error 0.9987758932412504 total_cost 0 area_under_roc_curve 0.8562367864693446 [0.856237,0.856237] area_under_roc_curve 0.8540051679586564 [0.854005,0.854005] area_under_roc_curve 0.8101949729856706 [0.810195,0.810195] area_under_roc_curve 0.8423772609819121 [0.842377,0.842377] area_under_roc_curve 0.8292224571294339 [0.829222,0.829222] area_under_roc_curve 0.8264035705896171 [0.826404,0.826404] area_under_roc_curve 0.8897092754960775 [0.889709,0.889709] area_under_roc_curve 0.8772281902963052 [0.877228,0.877228] area_under_roc_curve 0.8470074371384725 [0.847007,0.847007] area_under_roc_curve 0.858694369023728 [0.858694,0.858694] 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 -0.7995983445690623 kb_relative_information_score -0.9788256711644238 kb_relative_information_score -1.0410480647338485 kb_relative_information_score -1.0377707532723404 kb_relative_information_score -0.9127845225317864 kb_relative_information_score -0.9147288894341006 kb_relative_information_score -0.16295966771147719 kb_relative_information_score -1.381103100782032 kb_relative_information_score -1.8050242388877813 kb_relative_information_score -1.6638655272201441 mean_absolute_error 0.29399020058183695 mean_absolute_error 0.2940673950843322 mean_absolute_error 0.2940820018420542 mean_absolute_error 0.2940911418338059 mean_absolute_error 0.29403407642779705 mean_absolute_error 0.29404616121949273 mean_absolute_error 0.2963285203425892 mean_absolute_error 0.2947176986541168 mean_absolute_error 0.29486806349279016 mean_absolute_error 0.29482072947126464 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 1.0007892062692172 relative_absolute_error 1.0010519885821232 relative_absolute_error 1.0011017122988928 relative_absolute_error 1.0011328262784485 relative_absolute_error 1.000938566598119 relative_absolute_error 1.0009797051430949 relative_absolute_error 0.9996929126675056 relative_absolute_error 1.0016399768031266 relative_absolute_error 1.0021510130734577 relative_absolute_error 1.001990141675373 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 0.3823960872378561 root_mean_squared_error 0.38241029628120543 root_mean_squared_error 0.38245619325694136 root_mean_squared_error 0.38241720180256433 root_mean_squared_error 0.38242421106651825 root_mean_squared_error 0.38244794347694633 root_mean_squared_error 0.3858145125320757 root_mean_squared_error 0.38295464871512996 root_mean_squared_error 0.38300725884078024 root_mean_squared_error 0.38300157964661274 root_relative_squared_error 0.9987630068251679 root_relative_squared_error 0.9988001187814177 root_relative_squared_error 0.9989199950119024 root_relative_squared_error 0.9988181549996383 root_relative_squared_error 0.9988364621784401 root_relative_squared_error 0.9988984477854834 root_relative_squared_error 0.9986672988780028 root_relative_squared_error 0.998599187734317 root_relative_squared_error 0.998736374810952 root_relative_squared_error 0.9987215656456847 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 1603.5878660004528 usercpu_time_millis 1539.6851350014913 usercpu_time_millis 1545.0962590002746 usercpu_time_millis 1642.204469000717 usercpu_time_millis 1548.7847219992545 usercpu_time_millis 1635.586198000965 usercpu_time_millis 1527.0608050013834 usercpu_time_millis 1534.435867000866 usercpu_time_millis 1529.4938540027943 usercpu_time_millis 1539.218025001901 usercpu_time_millis_testing 5.51982600154588 usercpu_time_millis_testing 5.580847002420342 usercpu_time_millis_testing 5.613328998151701 usercpu_time_millis_testing 5.7063770000240766 usercpu_time_millis_testing 5.590251999819884 usercpu_time_millis_testing 5.681820002791937 usercpu_time_millis_testing 5.591236000327626 usercpu_time_millis_testing 5.454621001263149 usercpu_time_millis_testing 5.626261001452804 usercpu_time_millis_testing 5.480059000547044 usercpu_time_millis_training 1598.068039998907 usercpu_time_millis_training 1534.104287999071 usercpu_time_millis_training 1539.4829300021229 usercpu_time_millis_training 1636.4980920006928 usercpu_time_millis_training 1543.1944699994347 usercpu_time_millis_training 1629.904377998173 usercpu_time_millis_training 1521.4695690010558 usercpu_time_millis_training 1528.9812459996028 usercpu_time_millis_training 1523.8675930013414 usercpu_time_millis_training 1533.737966001354