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9336

Run 9336

Task 96 (Supervised Classification) credit-a Uploaded 25-11-2022 by Continuous Integration
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TEST207088071csklearn.pipeline.Pipeline(transformer=sklearn.compose._column _transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(simpleimpu ter=sklearn.impute.SimpleImputer,standardscaler=sklearn.preprocessing.data. StandardScaler),nominal=sklearn.pipeline.Pipeline(customimputer=openml.test ing.CustomImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncod er)),classifier=sklearn.tree.tree.DecisionTreeClassifier)(1)Pipeline of transforms with a final estimator. Sequentially apply a list of transforms and a final estimator. Intermediate steps of the pipeline must be 'transforms', that is, they must implement fit and transform methods. The final estimator only needs to implement fit. The transformers in the pipeline can be cached using ``memory`` argument. The purpose of the pipeline is to assemble several steps that can be cross-validated together while setting different parameters. For this, it enables setting parameters of the various steps using their names and the parameter name separated by a '__', as in the example below. A step's estimator may be replaced entirely by setting the parameter with its name to another estimator, or a transformer removed by setting to None.
TEST207088071csklearn.pipeline.Pipeline(transformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(customimputer=openml.testing.CustomImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),classifier=sklearn.tree.tree.DecisionTreeClassifier)(1)_memorynull
TEST207088071csklearn.pipeline.Pipeline(transformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(customimputer=openml.testing.CustomImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),classifier=sklearn.tree.tree.DecisionTreeClassifier)(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "transformer", "step_name": "transformer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "classifier", "step_name": "classifier"}}]
TEST207088071csklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(customimputer=openml.testing.CustomImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder))(1)_n_jobsnull
TEST207088071csklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(customimputer=openml.testing.CustomImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder))(1)_remainder"passthrough"
TEST207088071csklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(customimputer=openml.testing.CustomImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder))(1)_sparse_threshold0.3
TEST207088071csklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(customimputer=openml.testing.CustomImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder))(1)_transformer_weightsnull
TEST207088071csklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(customimputer=openml.testing.CustomImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder))(1)_transformers[{"oml-python:serialized_object": "component_reference", "value": {"key": "numeric", "step_name": "numeric", "argument_1": [1, 2, 7, 10, 13, 14]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "nominal", "step_name": "nominal", "argument_1": [0, 3, 4, 5, 6, 8, 9, 11, 12]}}]
TEST207088071csklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler)(1)_memorynull
TEST207088071csklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler)(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}]
TEST207088071csklearn.impute.SimpleImputer(1)_copytrue
TEST207088071csklearn.impute.SimpleImputer(1)_fill_valuenull
TEST207088071csklearn.impute.SimpleImputer(1)_missing_valuesNaN
TEST207088071csklearn.impute.SimpleImputer(1)_strategy"mean"
TEST207088071csklearn.impute.SimpleImputer(1)_verbose0
TEST207088071csklearn.preprocessing.data.StandardScaler(1)_copytrue
TEST207088071csklearn.preprocessing.data.StandardScaler(1)_with_meantrue
TEST207088071csklearn.preprocessing.data.StandardScaler(1)_with_stdtrue
TEST207088071csklearn.pipeline.Pipeline(customimputer=openml.testing.CustomImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)(1)_memorynull
TEST207088071csklearn.pipeline.Pipeline(customimputer=openml.testing.CustomImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "customimputer", "step_name": "customimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder"}}]
TEST207088071copenml.testing.CustomImputer(1)_copytrue
TEST207088071copenml.testing.CustomImputer(1)_fill_valuenull
TEST207088071copenml.testing.CustomImputer(1)_missing_valuesNaN
TEST207088071copenml.testing.CustomImputer(1)_strategy"most_frequent"
TEST207088071copenml.testing.CustomImputer(1)_verbose0
TEST207088071csklearn.preprocessing._encoders.OneHotEncoder(1)_categorical_featuresnull
TEST207088071csklearn.preprocessing._encoders.OneHotEncoder(1)_categoriesnull
TEST207088071csklearn.preprocessing._encoders.OneHotEncoder(1)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
TEST207088071csklearn.preprocessing._encoders.OneHotEncoder(1)_handle_unknown"ignore"
TEST207088071csklearn.preprocessing._encoders.OneHotEncoder(1)_n_valuesnull
TEST207088071csklearn.preprocessing._encoders.OneHotEncoder(1)_sparsetrue
TEST207088071csklearn.tree.tree.DecisionTreeClassifier(1)_class_weightnull
TEST207088071csklearn.tree.tree.DecisionTreeClassifier(1)_criterion"gini"
TEST207088071csklearn.tree.tree.DecisionTreeClassifier(1)_max_depthnull
TEST207088071csklearn.tree.tree.DecisionTreeClassifier(1)_max_featuresnull
TEST207088071csklearn.tree.tree.DecisionTreeClassifier(1)_max_leaf_nodesnull
TEST207088071csklearn.tree.tree.DecisionTreeClassifier(1)_min_impurity_decrease0.0
TEST207088071csklearn.tree.tree.DecisionTreeClassifier(1)_min_impurity_splitnull
TEST207088071csklearn.tree.tree.DecisionTreeClassifier(1)_min_samples_leaf1
TEST207088071csklearn.tree.tree.DecisionTreeClassifier(1)_min_samples_split2
TEST207088071csklearn.tree.tree.DecisionTreeClassifier(1)_min_weight_fraction_leaf0.0
TEST207088071csklearn.tree.tree.DecisionTreeClassifier(1)_presortfalse
TEST207088071csklearn.tree.tree.DecisionTreeClassifier(1)_random_state62501
TEST207088071csklearn.tree.tree.DecisionTreeClassifier(1)_splitter"best"

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.

18 Evaluation measures