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9936

Run 9936

Task 96 (Supervised Classification) credit-a Uploaded 28-11-2022 by Continuous Integration
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TEST1f4e847cf8sklearn.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``.
TEST1f4e847cf8sklearn.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
TEST1f4e847cf8sklearn.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"}}]
TEST1f4e847cf8sklearn.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
TEST1f4e847cf8sklearn.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
TEST1f4e847cf8sklearn.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"
TEST1f4e847cf8sklearn.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
TEST1f4e847cf8sklearn.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
TEST1f4e847cf8sklearn.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"}}}]
TEST1f4e847cf8sklearn.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
TEST1f4e847cf8sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)(1)_memorynull
TEST1f4e847cf8sklearn.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"}}]
TEST1f4e847cf8sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)(1)_verbosefalse
TEST1f4e847cf8sklearn.impute._base.SimpleImputer(1)_add_indicatorfalse
TEST1f4e847cf8sklearn.impute._base.SimpleImputer(1)_copytrue
TEST1f4e847cf8sklearn.impute._base.SimpleImputer(1)_fill_valuenull
TEST1f4e847cf8sklearn.impute._base.SimpleImputer(1)_missing_valuesNaN
TEST1f4e847cf8sklearn.impute._base.SimpleImputer(1)_strategy"most_frequent"
TEST1f4e847cf8sklearn.impute._base.SimpleImputer(1)_verbose0
TEST1f4e847cf8sklearn.preprocessing._encoders.OneHotEncoder(1)_categories"auto"
TEST1f4e847cf8sklearn.preprocessing._encoders.OneHotEncoder(1)_dropnull
TEST1f4e847cf8sklearn.preprocessing._encoders.OneHotEncoder(1)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
TEST1f4e847cf8sklearn.preprocessing._encoders.OneHotEncoder(1)_handle_unknown"ignore"
TEST1f4e847cf8sklearn.preprocessing._encoders.OneHotEncoder(1)_sparsetrue
TEST1f4e847cf8sklearn.pipeline.Pipeline(customimputer=openml.testing.CustomImputer,standardscaler=sklearn.preprocessing._data.StandardScaler)(1)_memorynull
TEST1f4e847cf8sklearn.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"}}]
TEST1f4e847cf8sklearn.pipeline.Pipeline(customimputer=openml.testing.CustomImputer,standardscaler=sklearn.preprocessing._data.StandardScaler)(1)_verbosefalse
TEST1f4e847cf8openml.testing.CustomImputer(1)_add_indicatorfalse
TEST1f4e847cf8openml.testing.CustomImputer(1)_copytrue
TEST1f4e847cf8openml.testing.CustomImputer(1)_fill_valuenull
TEST1f4e847cf8openml.testing.CustomImputer(1)_missing_valuesNaN
TEST1f4e847cf8openml.testing.CustomImputer(1)_strategy"mean"
TEST1f4e847cf8openml.testing.CustomImputer(1)_verbose0
TEST1f4e847cf8sklearn.preprocessing._data.StandardScaler(1)_copytrue
TEST1f4e847cf8sklearn.preprocessing._data.StandardScaler(1)_with_meantrue
TEST1f4e847cf8sklearn.preprocessing._data.StandardScaler(1)_with_stdtrue
TEST1f4e847cf8sklearn.feature_selection._variance_threshold.VarianceThreshold(1)_threshold0.0
TEST1f4e847cf8sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_cv3
TEST1f4e847cf8sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_error_scoreNaN
TEST1f4e847cf8sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_iid"deprecated"
TEST1f4e847cf8sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_n_iter10
TEST1f4e847cf8sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_n_jobsnull
TEST1f4e847cf8sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_param_distributions{"n_neighbors": [2, 3, 4, 5, 6, 7, 8, 9]}
TEST1f4e847cf8sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_pre_dispatch"2*n_jobs"
TEST1f4e847cf8sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_random_state62501
TEST1f4e847cf8sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_refittrue
TEST1f4e847cf8sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_return_train_scorefalse
TEST1f4e847cf8sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_scoringnull
TEST1f4e847cf8sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.neighbors._classification.KNeighborsClassifier)(1)_verbose0
TEST1f4e847cf8sklearn.neighbors._classification.KNeighborsClassifier(1)_algorithm"auto"
TEST1f4e847cf8sklearn.neighbors._classification.KNeighborsClassifier(1)_leaf_size30
TEST1f4e847cf8sklearn.neighbors._classification.KNeighborsClassifier(1)_metric"minkowski"
TEST1f4e847cf8sklearn.neighbors._classification.KNeighborsClassifier(1)_metric_paramsnull
TEST1f4e847cf8sklearn.neighbors._classification.KNeighborsClassifier(1)_n_jobsnull
TEST1f4e847cf8sklearn.neighbors._classification.KNeighborsClassifier(1)_n_neighbors5
TEST1f4e847cf8sklearn.neighbors._classification.KNeighborsClassifier(1)_p2
TEST1f4e847cf8sklearn.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