Run 664

Task 119 (Supervised Classification) diabetes Uploaded 03-07-2024 by Continuous Integration
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads

Issue	#Downvotes for this reason	By

Flow

TEST02666bb74csklearn.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``.
TEST02666bb74csklearn.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
TEST02666bb74csklearn.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"}}]
TEST02666bb74csklearn.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
TEST02666bb74csklearn.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
TEST02666bb74csklearn.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"
TEST02666bb74csklearn.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
TEST02666bb74csklearn.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
TEST02666bb74csklearn.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": []}}]
TEST02666bb74csklearn.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
TEST02666bb74csklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing._data.StandardScaler)(1)_memory	null
TEST02666bb74csklearn.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"}}]
TEST02666bb74csklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing._data.StandardScaler)(1)_verbose	false
TEST02666bb74csklearn.impute._base.SimpleImputer(1)_add_indicator	false
TEST02666bb74csklearn.impute._base.SimpleImputer(1)_copy	true
TEST02666bb74csklearn.impute._base.SimpleImputer(1)_fill_value	null
TEST02666bb74csklearn.impute._base.SimpleImputer(1)_missing_values	NaN
TEST02666bb74csklearn.impute._base.SimpleImputer(1)_strategy	"mean"
TEST02666bb74csklearn.impute._base.SimpleImputer(1)_verbose	0
TEST02666bb74csklearn.preprocessing._data.StandardScaler(1)_copy	true
TEST02666bb74csklearn.preprocessing._data.StandardScaler(1)_with_mean	true
TEST02666bb74csklearn.preprocessing._data.StandardScaler(1)_with_std	true
TEST02666bb74csklearn.pipeline.Pipeline(customimputer=openml.testing.CustomImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)(1)_memory	null
TEST02666bb74csklearn.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"}}]
TEST02666bb74csklearn.pipeline.Pipeline(customimputer=openml.testing.CustomImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)(1)_verbose	false
TEST02666bb74copenml.testing.CustomImputer(1)_add_indicator	false
TEST02666bb74copenml.testing.CustomImputer(1)_copy	true
TEST02666bb74copenml.testing.CustomImputer(1)_fill_value	null
TEST02666bb74copenml.testing.CustomImputer(1)_missing_values	NaN
TEST02666bb74copenml.testing.CustomImputer(1)_strategy	"most_frequent"
TEST02666bb74copenml.testing.CustomImputer(1)_verbose	0
TEST02666bb74csklearn.preprocessing._encoders.OneHotEncoder(1)_categories	"auto"
TEST02666bb74csklearn.preprocessing._encoders.OneHotEncoder(1)_drop	null
TEST02666bb74csklearn.preprocessing._encoders.OneHotEncoder(1)_dtype	{"oml-python:serialized_object": "type", "value": "np.float64"}
TEST02666bb74csklearn.preprocessing._encoders.OneHotEncoder(1)_handle_unknown	"ignore"
TEST02666bb74csklearn.preprocessing._encoders.OneHotEncoder(1)_sparse	true
TEST02666bb74csklearn.tree._classes.DecisionTreeClassifier(1)_ccp_alpha	0.0
TEST02666bb74csklearn.tree._classes.DecisionTreeClassifier(1)_class_weight	null
TEST02666bb74csklearn.tree._classes.DecisionTreeClassifier(1)_criterion	"gini"
TEST02666bb74csklearn.tree._classes.DecisionTreeClassifier(1)_max_depth	null
TEST02666bb74csklearn.tree._classes.DecisionTreeClassifier(1)_max_features	null
TEST02666bb74csklearn.tree._classes.DecisionTreeClassifier(1)_max_leaf_nodes	null
TEST02666bb74csklearn.tree._classes.DecisionTreeClassifier(1)_min_impurity_decrease	0.0
TEST02666bb74csklearn.tree._classes.DecisionTreeClassifier(1)_min_impurity_split	null
TEST02666bb74csklearn.tree._classes.DecisionTreeClassifier(1)_min_samples_leaf	1
TEST02666bb74csklearn.tree._classes.DecisionTreeClassifier(1)_min_samples_split	2
TEST02666bb74csklearn.tree._classes.DecisionTreeClassifier(1)_min_weight_fraction_leaf	0.0
TEST02666bb74csklearn.tree._classes.DecisionTreeClassifier(1)_presort	"deprecated"
TEST02666bb74csklearn.tree._classes.DecisionTreeClassifier(1)_random_state	62501
TEST02666bb74csklearn.tree._classes.DecisionTreeClassifier(1)_splitter	"best"