Run 9145

Task 119 (Supervised Classification) diabetes Uploaded 25-11-2022 by Continuous Integration
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TESTf2ab954fcbsklearn.pipeline.Pipeline(transformer=sklearn.compose._column _transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(simpleimpu ter=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing ._data.StandardScaler),nominal=sklearn.pipeline.Pipeline(customimputer=open ml.testing.CustomImputer,onehotencoder=sklearn.preprocessing._encoders.OneH otEncoder)),classifier=sklearn.tree._classes.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 it to 'passthrough' or ``None``.
TESTf2ab954fcbsklearn.pipeline.Pipeline(transformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing._data.StandardScaler),nominal=sklearn.pipeline.Pipeline(customimputer=openml.testing.CustomImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),classifier=sklearn.tree._classes.DecisionTreeClassifier)(1)_memory	null
TESTf2ab954fcbsklearn.pipeline.Pipeline(transformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing._data.StandardScaler),nominal=sklearn.pipeline.Pipeline(customimputer=openml.testing.CustomImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),classifier=sklearn.tree._classes.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"}}]
TESTf2ab954fcbsklearn.pipeline.Pipeline(transformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing._data.StandardScaler),nominal=sklearn.pipeline.Pipeline(customimputer=openml.testing.CustomImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),classifier=sklearn.tree._classes.DecisionTreeClassifier)(1)_verbose	false
TESTf2ab954fcbsklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing._data.StandardScaler),nominal=sklearn.pipeline.Pipeline(customimputer=openml.testing.CustomImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder))(1)_n_jobs	null
TESTf2ab954fcbsklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing._data.StandardScaler),nominal=sklearn.pipeline.Pipeline(customimputer=openml.testing.CustomImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder))(1)_remainder	"passthrough"
TESTf2ab954fcbsklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing._data.StandardScaler),nominal=sklearn.pipeline.Pipeline(customimputer=openml.testing.CustomImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder))(1)_sparse_threshold	0.3
TESTf2ab954fcbsklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing._data.StandardScaler),nominal=sklearn.pipeline.Pipeline(customimputer=openml.testing.CustomImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder))(1)_transformer_weights	null
TESTf2ab954fcbsklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.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": [0, 1, 2, 3, 4, 5, 6, 7]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "nominal", "step_name": "nominal", "argument_1": []}}]
TESTf2ab954fcbsklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing._data.StandardScaler),nominal=sklearn.pipeline.Pipeline(customimputer=openml.testing.CustomImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder))(1)_verbose	false
TESTf2ab954fcbsklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing._data.StandardScaler)(1)_memory	null
TESTf2ab954fcbsklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.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"}}]
TESTf2ab954fcbsklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing._data.StandardScaler)(1)_verbose	false
TESTf2ab954fcbsklearn.impute._base.SimpleImputer(1)_add_indicator	false
TESTf2ab954fcbsklearn.impute._base.SimpleImputer(1)_copy	true
TESTf2ab954fcbsklearn.impute._base.SimpleImputer(1)_fill_value	null
TESTf2ab954fcbsklearn.impute._base.SimpleImputer(1)_missing_values	NaN
TESTf2ab954fcbsklearn.impute._base.SimpleImputer(1)_strategy	"mean"
TESTf2ab954fcbsklearn.impute._base.SimpleImputer(1)_verbose	0
TESTf2ab954fcbsklearn.preprocessing._data.StandardScaler(1)_copy	true
TESTf2ab954fcbsklearn.preprocessing._data.StandardScaler(1)_with_mean	true
TESTf2ab954fcbsklearn.preprocessing._data.StandardScaler(1)_with_std	true
TESTf2ab954fcbsklearn.pipeline.Pipeline(customimputer=openml.testing.CustomImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)(1)_memory	null
TESTf2ab954fcbsklearn.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"}}]
TESTf2ab954fcbsklearn.pipeline.Pipeline(customimputer=openml.testing.CustomImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)(1)_verbose	false
TESTf2ab954fcbopenml.testing.CustomImputer(1)_add_indicator	false
TESTf2ab954fcbopenml.testing.CustomImputer(1)_copy	true
TESTf2ab954fcbopenml.testing.CustomImputer(1)_fill_value	null
TESTf2ab954fcbopenml.testing.CustomImputer(1)_missing_values	NaN
TESTf2ab954fcbopenml.testing.CustomImputer(1)_strategy	"most_frequent"
TESTf2ab954fcbopenml.testing.CustomImputer(1)_verbose	0
TESTf2ab954fcbsklearn.preprocessing._encoders.OneHotEncoder(1)_categories	"auto"
TESTf2ab954fcbsklearn.preprocessing._encoders.OneHotEncoder(1)_drop	null
TESTf2ab954fcbsklearn.preprocessing._encoders.OneHotEncoder(1)_dtype	{"oml-python:serialized_object": "type", "value": "np.float64"}
TESTf2ab954fcbsklearn.preprocessing._encoders.OneHotEncoder(1)_handle_unknown	"ignore"
TESTf2ab954fcbsklearn.preprocessing._encoders.OneHotEncoder(1)_sparse	true
TESTf2ab954fcbsklearn.tree._classes.DecisionTreeClassifier(1)_ccp_alpha	0.0
TESTf2ab954fcbsklearn.tree._classes.DecisionTreeClassifier(1)_class_weight	null
TESTf2ab954fcbsklearn.tree._classes.DecisionTreeClassifier(1)_criterion	"gini"
TESTf2ab954fcbsklearn.tree._classes.DecisionTreeClassifier(1)_max_depth	null
TESTf2ab954fcbsklearn.tree._classes.DecisionTreeClassifier(1)_max_features	null
TESTf2ab954fcbsklearn.tree._classes.DecisionTreeClassifier(1)_max_leaf_nodes	null
TESTf2ab954fcbsklearn.tree._classes.DecisionTreeClassifier(1)_min_impurity_decrease	0.0
TESTf2ab954fcbsklearn.tree._classes.DecisionTreeClassifier(1)_min_impurity_split	null
TESTf2ab954fcbsklearn.tree._classes.DecisionTreeClassifier(1)_min_samples_leaf	1
TESTf2ab954fcbsklearn.tree._classes.DecisionTreeClassifier(1)_min_samples_split	2
TESTf2ab954fcbsklearn.tree._classes.DecisionTreeClassifier(1)_min_weight_fraction_leaf	0.0
TESTf2ab954fcbsklearn.tree._classes.DecisionTreeClassifier(1)_random_state	62501
TESTf2ab954fcbsklearn.tree._classes.DecisionTreeClassifier(1)_splitter	"best"