Run
10228048

Run 10228048

Task 10101 (Supervised Classification) blood-transfusion-service-center Uploaded 13-05-2019 by Felix Neutatz
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Flow

fastsklearnfeature.feature_selection.openml_wrapper.ComplexPipelineWrapper. ComplexPipelineWrapper(my_pipeline=sklearn.pipeline.Pipeline(features=sklea rn.pipeline.Pipeline(V2=sklearn.compose._column_transformer.ColumnTransform er(identity=sklearn.preprocessing._function_transformer.FunctionTransformer )),classifier=sklearn.linear_model.logistic.LogisticRegression))(1)Automatically created scikit-learn flow.
sklearn.compose._column_transformer.ColumnTransformer(identity=sklearn.preprocessing._function_transformer.FunctionTransformer)(1)_n_jobsnull
sklearn.compose._column_transformer.ColumnTransformer(identity=sklearn.preprocessing._function_transformer.FunctionTransformer)(1)_remainder"drop"
sklearn.compose._column_transformer.ColumnTransformer(identity=sklearn.preprocessing._function_transformer.FunctionTransformer)(1)_sparse_threshold0.3
sklearn.compose._column_transformer.ColumnTransformer(identity=sklearn.preprocessing._function_transformer.FunctionTransformer)(1)_transformer_weightsnull
sklearn.compose._column_transformer.ColumnTransformer(identity=sklearn.preprocessing._function_transformer.FunctionTransformer)(1)_transformers[{"oml-python:serialized_object": "component_reference", "value": {"key": "identity", "step_name": "identity", "argument_1": [1]}}]
sklearn.preprocessing._function_transformer.FunctionTransformer(4)_accept_sparsefalse
sklearn.preprocessing._function_transformer.FunctionTransformer(4)_check_inversetrue
sklearn.preprocessing._function_transformer.FunctionTransformer(4)_func{"oml-python:serialized_object": "function", "value": "fastsklearnfeature.candidates.Identity.identity"}
sklearn.preprocessing._function_transformer.FunctionTransformer(4)_inv_kw_argsnull
sklearn.preprocessing._function_transformer.FunctionTransformer(4)_inverse_funcnull
sklearn.preprocessing._function_transformer.FunctionTransformer(4)_kw_argsnull
sklearn.preprocessing._function_transformer.FunctionTransformer(4)_pass_y"deprecated"
sklearn.preprocessing._function_transformer.FunctionTransformer(4)_validatefalse
sklearn.linear_model.logistic.LogisticRegression(23)_C0.001
sklearn.linear_model.logistic.LogisticRegression(23)_class_weight"balanced"
sklearn.linear_model.logistic.LogisticRegression(23)_dualfalse
sklearn.linear_model.logistic.LogisticRegression(23)_fit_intercepttrue
sklearn.linear_model.logistic.LogisticRegression(23)_intercept_scaling1
sklearn.linear_model.logistic.LogisticRegression(23)_max_iter10000
sklearn.linear_model.logistic.LogisticRegression(23)_multi_class"auto"
sklearn.linear_model.logistic.LogisticRegression(23)_n_jobsnull
sklearn.linear_model.logistic.LogisticRegression(23)_penalty"l2"
sklearn.linear_model.logistic.LogisticRegression(23)_random_state35360
sklearn.linear_model.logistic.LogisticRegression(23)_solver"lbfgs"
sklearn.linear_model.logistic.LogisticRegression(23)_tol0.0001
sklearn.linear_model.logistic.LogisticRegression(23)_verbose0
sklearn.linear_model.logistic.LogisticRegression(23)_warm_startfalse
sklearn.pipeline.Pipeline(features=sklearn.pipeline.Pipeline(V2=sklearn.compose._column_transformer.ColumnTransformer(identity=sklearn.preprocessing._function_transformer.FunctionTransformer)),classifier=sklearn.linear_model.logistic.LogisticRegression)(1)_memorynull
sklearn.pipeline.Pipeline(features=sklearn.pipeline.Pipeline(V2=sklearn.compose._column_transformer.ColumnTransformer(identity=sklearn.preprocessing._function_transformer.FunctionTransformer)),classifier=sklearn.linear_model.logistic.LogisticRegression)(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "features", "step_name": "features"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "classifier", "step_name": "classifier"}}]
sklearn.pipeline.Pipeline(V2=sklearn.compose._column_transformer.ColumnTransformer(identity=sklearn.preprocessing._function_transformer.FunctionTransformer))(1)_memorynull
sklearn.pipeline.Pipeline(V2=sklearn.compose._column_transformer.ColumnTransformer(identity=sklearn.preprocessing._function_transformer.FunctionTransformer))(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "V2", "step_name": "V2"}}]

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.

17 Evaluation measures

0.5933 ± 0.0697
Per class
Cross-validation details (10-fold Crossvalidation)
0.6799 ± 0.0415
Per class
Cross-validation details (10-fold Crossvalidation)
0.1684 ± 0.1198
Cross-validation details (10-fold Crossvalidation)
-28.9236 ± 10.8575
Cross-validation details (10-fold Crossvalidation)
0.3342 ± 0.0459
Cross-validation details (10-fold Crossvalidation)
0.363 ± 0.0023
Cross-validation details (10-fold Crossvalidation)
748
Per class
Cross-validation details (10-fold Crossvalidation)
0.7006 ± 0.0481
Per class
Cross-validation details (10-fold Crossvalidation)
0.6658 ± 0.0459
Cross-validation details (10-fold Crossvalidation)
0.7928
Cross-validation details (10-fold Crossvalidation)
0.6658 ± 0.0459
Per class
Cross-validation details (10-fold Crossvalidation)
0.9206 ± 0.1281
Cross-validation details (10-fold Crossvalidation)
0.4258 ± 0.0027
Cross-validation details (10-fold Crossvalidation)
0.5781 ± 0.0407
Cross-validation details (10-fold Crossvalidation)
1.3576 ± 0.0982
Cross-validation details (10-fold Crossvalidation)