Run 9159

Task 96 (Supervised Classification) credit-a Uploaded 25-11-2022 by Continuous Integration
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads

Issue	#Downvotes for this reason	By

Flow

TEST11e35df3e4sklearn.pipeline.Pipeline(Imputer=sklearn.compose._column_tra nsformer.ColumnTransformer(cat=sklearn.pipeline.Pipeline(simpleimputer=skle arn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoder s.OneHotEncoder),cont=sklearn.pipeline.Pipeline(customimputer=openml.testin g.CustomImputer,standardscaler=sklearn.preprocessing._data.StandardScaler)) ,VarianceThreshold=sklearn.feature_selection._variance_threshold.VarianceTh reshold,Estimator=sklearn.model_selection._search.RandomizedSearchCV(estima tor=sklearn.neighbors._classification.KNeighborsClassifier))(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``.
TEST11e35df3e4sklearn.pipeline.Pipeline(Imputer=sklearn.compose._column_transformer.ColumnTransformer(cat=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder),cont=sklearn.pipeline.Pipeline(customimputer=openml.testing.CustomImputer,standardscaler=sklearn.preprocessing._data.StandardScaler)),VarianceThreshold=sklearn.feature_selection._variance_threshold.VarianceThreshold,Estimator=sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier))(1)_memory	null
TEST11e35df3e4sklearn.pipeline.Pipeline(Imputer=sklearn.compose._column_transformer.ColumnTransformer(cat=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder),cont=sklearn.pipeline.Pipeline(customimputer=openml.testing.CustomImputer,standardscaler=sklearn.preprocessing._data.StandardScaler)),VarianceThreshold=sklearn.feature_selection._variance_threshold.VarianceThreshold,Estimator=sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier))(1)_steps	[{"oml-python:serialized_object": "component_reference", "value": {"key": "Imputer", "step_name": "Imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "VarianceThreshold", "step_name": "VarianceThreshold"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "Estimator", "step_name": "Estimator"}}]
TEST11e35df3e4sklearn.pipeline.Pipeline(Imputer=sklearn.compose._column_transformer.ColumnTransformer(cat=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder),cont=sklearn.pipeline.Pipeline(customimputer=openml.testing.CustomImputer,standardscaler=sklearn.preprocessing._data.StandardScaler)),VarianceThreshold=sklearn.feature_selection._variance_threshold.VarianceThreshold,Estimator=sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier))(1)_verbose	false
TEST11e35df3e4sklearn.compose._column_transformer.ColumnTransformer(cat=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder),cont=sklearn.pipeline.Pipeline(customimputer=openml.testing.CustomImputer,standardscaler=sklearn.preprocessing._data.StandardScaler))(1)_n_jobs	null
TEST11e35df3e4sklearn.compose._column_transformer.ColumnTransformer(cat=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder),cont=sklearn.pipeline.Pipeline(customimputer=openml.testing.CustomImputer,standardscaler=sklearn.preprocessing._data.StandardScaler))(1)_remainder	"drop"
TEST11e35df3e4sklearn.compose._column_transformer.ColumnTransformer(cat=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder),cont=sklearn.pipeline.Pipeline(customimputer=openml.testing.CustomImputer,standardscaler=sklearn.preprocessing._data.StandardScaler))(1)_sparse_threshold	0.3
TEST11e35df3e4sklearn.compose._column_transformer.ColumnTransformer(cat=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder),cont=sklearn.pipeline.Pipeline(customimputer=openml.testing.CustomImputer,standardscaler=sklearn.preprocessing._data.StandardScaler))(1)_transformer_weights	null
TEST11e35df3e4sklearn.compose._column_transformer.ColumnTransformer(cat=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder),cont=sklearn.pipeline.Pipeline(customimputer=openml.testing.CustomImputer,standardscaler=sklearn.preprocessing._data.StandardScaler))(1)_transformers	[{"oml-python:serialized_object": "component_reference", "value": {"key": "cat", "step_name": "cat", "argument_1": {"oml-python:serialized_object": "function", "value": "openml.extensions.sklearn.cat"}}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "cont", "step_name": "cont", "argument_1": {"oml-python:serialized_object": "function", "value": "openml.extensions.sklearn.cont"}}}]
TEST11e35df3e4sklearn.compose._column_transformer.ColumnTransformer(cat=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder),cont=sklearn.pipeline.Pipeline(customimputer=openml.testing.CustomImputer,standardscaler=sklearn.preprocessing._data.StandardScaler))(1)_verbose	false
TEST11e35df3e4sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)(1)_memory	null
TEST11e35df3e4sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)(1)_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"}}]
TEST11e35df3e4sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)(1)_verbose	false
TEST11e35df3e4sklearn.impute._base.SimpleImputer(1)_add_indicator	false
TEST11e35df3e4sklearn.impute._base.SimpleImputer(1)_copy	true
TEST11e35df3e4sklearn.impute._base.SimpleImputer(1)_fill_value	null
TEST11e35df3e4sklearn.impute._base.SimpleImputer(1)_missing_values	NaN
TEST11e35df3e4sklearn.impute._base.SimpleImputer(1)_strategy	"most_frequent"
TEST11e35df3e4sklearn.impute._base.SimpleImputer(1)_verbose	0
TEST11e35df3e4sklearn.preprocessing._encoders.OneHotEncoder(1)_categories	"auto"
TEST11e35df3e4sklearn.preprocessing._encoders.OneHotEncoder(1)_drop	null
TEST11e35df3e4sklearn.preprocessing._encoders.OneHotEncoder(1)_dtype	{"oml-python:serialized_object": "type", "value": "np.float64"}
TEST11e35df3e4sklearn.preprocessing._encoders.OneHotEncoder(1)_handle_unknown	"ignore"
TEST11e35df3e4sklearn.preprocessing._encoders.OneHotEncoder(1)_sparse	true
TEST11e35df3e4sklearn.pipeline.Pipeline(customimputer=openml.testing.CustomImputer,standardscaler=sklearn.preprocessing._data.StandardScaler)(1)_memory	null
TEST11e35df3e4sklearn.pipeline.Pipeline(customimputer=openml.testing.CustomImputer,standardscaler=sklearn.preprocessing._data.StandardScaler)(1)_steps	[{"oml-python:serialized_object": "component_reference", "value": {"key": "customimputer", "step_name": "customimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}]
TEST11e35df3e4sklearn.pipeline.Pipeline(customimputer=openml.testing.CustomImputer,standardscaler=sklearn.preprocessing._data.StandardScaler)(1)_verbose	false
TEST11e35df3e4openml.testing.CustomImputer(1)_add_indicator	false
TEST11e35df3e4openml.testing.CustomImputer(1)_copy	true
TEST11e35df3e4openml.testing.CustomImputer(1)_fill_value	null
TEST11e35df3e4openml.testing.CustomImputer(1)_missing_values	NaN
TEST11e35df3e4openml.testing.CustomImputer(1)_strategy	"mean"
TEST11e35df3e4openml.testing.CustomImputer(1)_verbose	0
TEST11e35df3e4sklearn.preprocessing._data.StandardScaler(1)_copy	true
TEST11e35df3e4sklearn.preprocessing._data.StandardScaler(1)_with_mean	true
TEST11e35df3e4sklearn.preprocessing._data.StandardScaler(1)_with_std	true
TEST11e35df3e4sklearn.feature_selection._variance_threshold.VarianceThreshold(1)_threshold	0.0
TEST11e35df3e4sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_cv	3
TEST11e35df3e4sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_error_score	NaN
TEST11e35df3e4sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_iid	"deprecated"
TEST11e35df3e4sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_n_iter	10
TEST11e35df3e4sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_n_jobs	null
TEST11e35df3e4sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_param_distributions	{"n_neighbors": [2, 3, 4, 5, 6, 7, 8, 9]}
TEST11e35df3e4sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_pre_dispatch	"2*n_jobs"
TEST11e35df3e4sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_random_state	62501
TEST11e35df3e4sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_refit	true
TEST11e35df3e4sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_return_train_score	false
TEST11e35df3e4sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_scoring	null
TEST11e35df3e4sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_verbose	0
TEST11e35df3e4sklearn.neighbors._classification.KNeighborsClassifier(1)_algorithm	"auto"
TEST11e35df3e4sklearn.neighbors._classification.KNeighborsClassifier(1)_leaf_size	30
TEST11e35df3e4sklearn.neighbors._classification.KNeighborsClassifier(1)_metric	"minkowski"
TEST11e35df3e4sklearn.neighbors._classification.KNeighborsClassifier(1)_metric_params	null
TEST11e35df3e4sklearn.neighbors._classification.KNeighborsClassifier(1)_n_jobs	null
TEST11e35df3e4sklearn.neighbors._classification.KNeighborsClassifier(1)_n_neighbors	5
TEST11e35df3e4sklearn.neighbors._classification.KNeighborsClassifier(1)_p	2
TEST11e35df3e4sklearn.neighbors._classification.KNeighborsClassifier(1)_weights	"uniform"