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9377

Run 9377

Task 96 (Supervised Classification) credit-a Uploaded 25-11-2022 by Continuous Integration
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TESTc42659da09sklearn.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``.
TESTc42659da09sklearn.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
TESTc42659da09sklearn.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"}}]
TESTc42659da09sklearn.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
TESTc42659da09sklearn.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
TESTc42659da09sklearn.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"
TESTc42659da09sklearn.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
TESTc42659da09sklearn.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
TESTc42659da09sklearn.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"}}}]
TESTc42659da09sklearn.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
TESTc42659da09sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)(1)_memorynull
TESTc42659da09sklearn.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"}}]
TESTc42659da09sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)(1)_verbosefalse
TESTc42659da09sklearn.impute._base.SimpleImputer(1)_add_indicatorfalse
TESTc42659da09sklearn.impute._base.SimpleImputer(1)_copytrue
TESTc42659da09sklearn.impute._base.SimpleImputer(1)_fill_valuenull
TESTc42659da09sklearn.impute._base.SimpleImputer(1)_missing_valuesNaN
TESTc42659da09sklearn.impute._base.SimpleImputer(1)_strategy"most_frequent"
TESTc42659da09sklearn.impute._base.SimpleImputer(1)_verbose0
TESTc42659da09sklearn.preprocessing._encoders.OneHotEncoder(1)_categories"auto"
TESTc42659da09sklearn.preprocessing._encoders.OneHotEncoder(1)_dropnull
TESTc42659da09sklearn.preprocessing._encoders.OneHotEncoder(1)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
TESTc42659da09sklearn.preprocessing._encoders.OneHotEncoder(1)_handle_unknown"ignore"
TESTc42659da09sklearn.preprocessing._encoders.OneHotEncoder(1)_sparsetrue
TESTc42659da09sklearn.pipeline.Pipeline(customimputer=openml.testing.CustomImputer,standardscaler=sklearn.preprocessing._data.StandardScaler)(1)_memorynull
TESTc42659da09sklearn.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"}}]
TESTc42659da09sklearn.pipeline.Pipeline(customimputer=openml.testing.CustomImputer,standardscaler=sklearn.preprocessing._data.StandardScaler)(1)_verbosefalse
TESTc42659da09openml.testing.CustomImputer(1)_add_indicatorfalse
TESTc42659da09openml.testing.CustomImputer(1)_copytrue
TESTc42659da09openml.testing.CustomImputer(1)_fill_valuenull
TESTc42659da09openml.testing.CustomImputer(1)_missing_valuesNaN
TESTc42659da09openml.testing.CustomImputer(1)_strategy"mean"
TESTc42659da09openml.testing.CustomImputer(1)_verbose0
TESTc42659da09sklearn.preprocessing._data.StandardScaler(1)_copytrue
TESTc42659da09sklearn.preprocessing._data.StandardScaler(1)_with_meantrue
TESTc42659da09sklearn.preprocessing._data.StandardScaler(1)_with_stdtrue
TESTc42659da09sklearn.feature_selection._variance_threshold.VarianceThreshold(1)_threshold0.0
TESTc42659da09sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_cv3
TESTc42659da09sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_error_scoreNaN
TESTc42659da09sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_n_iter10
TESTc42659da09sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_n_jobsnull
TESTc42659da09sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_param_distributions{"n_neighbors": [2, 3, 4, 5, 6, 7, 8, 9]}
TESTc42659da09sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_pre_dispatch"2*n_jobs"
TESTc42659da09sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_random_state62501
TESTc42659da09sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_refittrue
TESTc42659da09sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_return_train_scorefalse
TESTc42659da09sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_scoringnull
TESTc42659da09sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_verbose0
TESTc42659da09sklearn.neighbors._classification.KNeighborsClassifier(1)_algorithm"auto"
TESTc42659da09sklearn.neighbors._classification.KNeighborsClassifier(1)_leaf_size30
TESTc42659da09sklearn.neighbors._classification.KNeighborsClassifier(1)_metric"minkowski"
TESTc42659da09sklearn.neighbors._classification.KNeighborsClassifier(1)_metric_paramsnull
TESTc42659da09sklearn.neighbors._classification.KNeighborsClassifier(1)_n_jobsnull
TESTc42659da09sklearn.neighbors._classification.KNeighborsClassifier(1)_n_neighbors5
TESTc42659da09sklearn.neighbors._classification.KNeighborsClassifier(1)_p2
TESTc42659da09sklearn.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