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9344

Run 9344

Task 96 (Supervised Classification) credit-a Uploaded 25-11-2022 by Continuous Integration
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TEST5d2f8c242fsklearn.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``.
TEST5d2f8c242fsklearn.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)_memorynull
TEST5d2f8c242fsklearn.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"}}]
TEST5d2f8c242fsklearn.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)_verbosefalse
TEST5d2f8c242fsklearn.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_jobsnull
TEST5d2f8c242fsklearn.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"
TEST5d2f8c242fsklearn.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_threshold0.3
TEST5d2f8c242fsklearn.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_weightsnull
TEST5d2f8c242fsklearn.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"}}}]
TEST5d2f8c242fsklearn.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)_verbosefalse
TEST5d2f8c242fsklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)(1)_memorynull
TEST5d2f8c242fsklearn.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"}}]
TEST5d2f8c242fsklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)(1)_verbosefalse
TEST5d2f8c242fsklearn.impute._base.SimpleImputer(1)_add_indicatorfalse
TEST5d2f8c242fsklearn.impute._base.SimpleImputer(1)_copytrue
TEST5d2f8c242fsklearn.impute._base.SimpleImputer(1)_fill_valuenull
TEST5d2f8c242fsklearn.impute._base.SimpleImputer(1)_missing_valuesNaN
TEST5d2f8c242fsklearn.impute._base.SimpleImputer(1)_strategy"most_frequent"
TEST5d2f8c242fsklearn.impute._base.SimpleImputer(1)_verbose0
TEST5d2f8c242fsklearn.preprocessing._encoders.OneHotEncoder(1)_categories"auto"
TEST5d2f8c242fsklearn.preprocessing._encoders.OneHotEncoder(1)_dropnull
TEST5d2f8c242fsklearn.preprocessing._encoders.OneHotEncoder(1)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
TEST5d2f8c242fsklearn.preprocessing._encoders.OneHotEncoder(1)_handle_unknown"ignore"
TEST5d2f8c242fsklearn.preprocessing._encoders.OneHotEncoder(1)_sparsetrue
TEST5d2f8c242fsklearn.pipeline.Pipeline(customimputer=openml.testing.CustomImputer,standardscaler=sklearn.preprocessing._data.StandardScaler)(1)_memorynull
TEST5d2f8c242fsklearn.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"}}]
TEST5d2f8c242fsklearn.pipeline.Pipeline(customimputer=openml.testing.CustomImputer,standardscaler=sklearn.preprocessing._data.StandardScaler)(1)_verbosefalse
TEST5d2f8c242fopenml.testing.CustomImputer(1)_add_indicatorfalse
TEST5d2f8c242fopenml.testing.CustomImputer(1)_copytrue
TEST5d2f8c242fopenml.testing.CustomImputer(1)_fill_valuenull
TEST5d2f8c242fopenml.testing.CustomImputer(1)_missing_valuesNaN
TEST5d2f8c242fopenml.testing.CustomImputer(1)_strategy"mean"
TEST5d2f8c242fopenml.testing.CustomImputer(1)_verbose0
TEST5d2f8c242fsklearn.preprocessing._data.StandardScaler(1)_copytrue
TEST5d2f8c242fsklearn.preprocessing._data.StandardScaler(1)_with_meantrue
TEST5d2f8c242fsklearn.preprocessing._data.StandardScaler(1)_with_stdtrue
TEST5d2f8c242fsklearn.feature_selection._variance_threshold.VarianceThreshold(1)_threshold0.0
TEST5d2f8c242fsklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_cv3
TEST5d2f8c242fsklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_error_scoreNaN
TEST5d2f8c242fsklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_n_iter10
TEST5d2f8c242fsklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_n_jobsnull
TEST5d2f8c242fsklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_param_distributions{"n_neighbors": [2, 3, 4, 5, 6, 7, 8, 9]}
TEST5d2f8c242fsklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_pre_dispatch"2*n_jobs"
TEST5d2f8c242fsklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_random_state62501
TEST5d2f8c242fsklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_refittrue
TEST5d2f8c242fsklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_return_train_scorefalse
TEST5d2f8c242fsklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_scoringnull
TEST5d2f8c242fsklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_verbose0
TEST5d2f8c242fsklearn.neighbors._classification.KNeighborsClassifier(1)_algorithm"auto"
TEST5d2f8c242fsklearn.neighbors._classification.KNeighborsClassifier(1)_leaf_size30
TEST5d2f8c242fsklearn.neighbors._classification.KNeighborsClassifier(1)_metric"minkowski"
TEST5d2f8c242fsklearn.neighbors._classification.KNeighborsClassifier(1)_metric_paramsnull
TEST5d2f8c242fsklearn.neighbors._classification.KNeighborsClassifier(1)_n_jobsnull
TEST5d2f8c242fsklearn.neighbors._classification.KNeighborsClassifier(1)_n_neighbors5
TEST5d2f8c242fsklearn.neighbors._classification.KNeighborsClassifier(1)_p2
TEST5d2f8c242fsklearn.neighbors._classification.KNeighborsClassifier(1)_weights"uniform"

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