Run
10192465

Run 10192465

Task 21 (Supervised Classification) car Uploaded 17-04-2019 by Jan van Rijn
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Flow

sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transfo rmer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.pr eprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.St andardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.imput e.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder )),variancethreshold=sklearn.feature_selection.variance_threshold.VarianceT hreshold,gradientboostingclassifier=sklearn.ensemble.gradient_boosting.Grad ientBoostingClassifier)(4)Automatically created scikit-learn flow.
sklearn.impute.SimpleImputer(10)_copytrue
sklearn.impute.SimpleImputer(10)_fill_value-1
sklearn.impute.SimpleImputer(10)_missing_valuesNaN
sklearn.impute.SimpleImputer(10)_strategy"constant"
sklearn.impute.SimpleImputer(10)_verbose0
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))(4)_n_jobsnull
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))(4)_remainder"passthrough"
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))(4)_sparse_threshold0.3
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))(4)_transformer_weightsnull
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))(4)_transformers[{"oml-python:serialized_object": "component_reference", "value": {"key": "numeric", "step_name": "numeric", "argument_1": []}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "nominal", "step_name": "nominal", "argument_1": [0, 1, 2, 3, 4, 5]}}]
sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler)(4)_memorynull
sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler)(4)_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"}}]
sklearn.preprocessing.imputation.Imputer(38)_axis0
sklearn.preprocessing.imputation.Imputer(38)_copytrue
sklearn.preprocessing.imputation.Imputer(38)_missing_values"NaN"
sklearn.preprocessing.imputation.Imputer(38)_strategy"median"
sklearn.preprocessing.imputation.Imputer(38)_verbose0
sklearn.preprocessing.data.StandardScaler(25)_copytrue
sklearn.preprocessing.data.StandardScaler(25)_with_meantrue
sklearn.preprocessing.data.StandardScaler(25)_with_stdtrue
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)(4)_memorynull
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)(4)_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"}}]
sklearn.preprocessing._encoders.OneHotEncoder(9)_categorical_featuresnull
sklearn.preprocessing._encoders.OneHotEncoder(9)_categoriesnull
sklearn.preprocessing._encoders.OneHotEncoder(9)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing._encoders.OneHotEncoder(9)_handle_unknown"ignore"
sklearn.preprocessing._encoders.OneHotEncoder(9)_n_valuesnull
sklearn.preprocessing._encoders.OneHotEncoder(9)_sparsetrue
sklearn.feature_selection.variance_threshold.VarianceThreshold(24)_threshold0.0
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)_memorynull
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)_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"}}]
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(20)_criterion"friedman_mse"
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(20)_initnull
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(20)_learning_rate0.020847962004082357
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(20)_loss"deviance"
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(20)_max_depth20
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(20)_max_features0.8130253815525118
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(20)_max_leaf_nodesnull
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(20)_min_impurity_decrease0.3143806557073091
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(20)_min_impurity_splitnull
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(20)_min_samples_leaf6
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(20)_min_samples_split3
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(20)_min_weight_fraction_leaf0.45337885793977617
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(20)_n_estimators1560
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(20)_n_iter_no_change1214
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(20)_presort"auto"
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(20)_random_state10265
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(20)_subsample0.4910104807775224
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(20)_tol0.00013853680325011188
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(20)_validation_fraction0.9737066584491965
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(20)_verbose0
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(20)_warm_startfalse

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

15 Evaluation measures

0.321 ± 0.0379
Per class
Cross-validation details (10-fold Crossvalidation)
-0.1029 ± 0.0238
Cross-validation details (10-fold Crossvalidation)
-1338.9179 ± 4.1157
Cross-validation details (10-fold Crossvalidation)
0.4354 ± 0.0059
Cross-validation details (10-fold Crossvalidation)
0.229 ± 0.0006
Cross-validation details (10-fold Crossvalidation)
1728
Per class
Cross-validation details (10-fold Crossvalidation)
0.0764 ± 0.0195
Cross-validation details (10-fold Crossvalidation)
1.2099
Cross-validation details (10-fold Crossvalidation)
0.0764 ± 0.0195
Per class
Cross-validation details (10-fold Crossvalidation)
1.9016 ± 0.023
Cross-validation details (10-fold Crossvalidation)
0.3381 ± 0.0008
Cross-validation details (10-fold Crossvalidation)
0.5931 ± 0.0095
Cross-validation details (10-fold Crossvalidation)
1.7541 ± 0.028
Cross-validation details (10-fold Crossvalidation)