Run
10228220

Run 10228220

Task 10101 (Supervised Classification) blood-transfusion-service-center Uploaded 31-05-2019 by Felix Neutatz
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Flow

sklearn.pipeline.Pipeline(features=sklearn.pipeline.Pipeline2(V1=sklearn.co mpose._column_transformer.ColumnTransformer1(identity=sklearn.preprocessing ._function_transformer.FunctionTransformer0)),classifier=sklearn.linear_mod el.logistic.LogisticRegression)(1)Automatically created scikit-learn flow.
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_state17020
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.compose._column_transformer.ColumnTransformer1(identity=sklearn.preprocessing._function_transformer.FunctionTransformer0)(1)_n_jobsnull
sklearn.compose._column_transformer.ColumnTransformer1(identity=sklearn.preprocessing._function_transformer.FunctionTransformer0)(1)_remainder"drop"
sklearn.compose._column_transformer.ColumnTransformer1(identity=sklearn.preprocessing._function_transformer.FunctionTransformer0)(1)_sparse_threshold0.3
sklearn.compose._column_transformer.ColumnTransformer1(identity=sklearn.preprocessing._function_transformer.FunctionTransformer0)(1)_transformer_weightsnull
sklearn.compose._column_transformer.ColumnTransformer1(identity=sklearn.preprocessing._function_transformer.FunctionTransformer0)(1)_transformers[{"oml-python:serialized_object": "component_reference", "value": {"key": "identity", "step_name": "identity", "argument_1": [0]}}]
sklearn.preprocessing._function_transformer.FunctionTransformer0(1)_accept_sparsefalse
sklearn.preprocessing._function_transformer.FunctionTransformer0(1)_check_inversetrue
sklearn.preprocessing._function_transformer.FunctionTransformer0(1)_func{"oml-python:serialized_object": "function", "value": "fastsklearnfeature.candidates.Identity.identity"}
sklearn.preprocessing._function_transformer.FunctionTransformer0(1)_inv_kw_argsnull
sklearn.preprocessing._function_transformer.FunctionTransformer0(1)_inverse_funcnull
sklearn.preprocessing._function_transformer.FunctionTransformer0(1)_kw_argsnull
sklearn.preprocessing._function_transformer.FunctionTransformer0(1)_pass_y"deprecated"
sklearn.preprocessing._function_transformer.FunctionTransformer0(1)_validatefalse
sklearn.pipeline.Pipeline(features=sklearn.pipeline.Pipeline2(V1=sklearn.compose._column_transformer.ColumnTransformer1(identity=sklearn.preprocessing._function_transformer.FunctionTransformer0)),classifier=sklearn.linear_model.logistic.LogisticRegression)(1)_memorynull
sklearn.pipeline.Pipeline(features=sklearn.pipeline.Pipeline2(V1=sklearn.compose._column_transformer.ColumnTransformer1(identity=sklearn.preprocessing._function_transformer.FunctionTransformer0)),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.Pipeline2(V1=sklearn.compose._column_transformer.ColumnTransformer1(identity=sklearn.preprocessing._function_transformer.FunctionTransformer0))(1)_memorynull
sklearn.pipeline.Pipeline2(V1=sklearn.compose._column_transformer.ColumnTransformer1(identity=sklearn.preprocessing._function_transformer.FunctionTransformer0))(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "V1", "step_name": "V1"}}]

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

Area under ROC curve
0.6911 ± 0.0442
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.657 ± 0.0432
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.2604 ± 0.0736
Cross-validation details (10-fold Crossvalidation)
KB relative information score
-308.2744 ± 3.5754
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.439 ± 0.012
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.363 ± 0.0023
Cross-validation details (10-fold Crossvalidation)
Number of instances
748
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.7679 ± 0.0352
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.6297 ± 0.0451
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.7928
Cross-validation details (10-fold Crossvalidation)
Recall
0.6297 ± 0.0451
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
1.2091 ± 0.0332
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4258 ± 0.0027
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4685 ± 0.0111
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.1003 ± 0.0269
Cross-validation details (10-fold Crossvalidation)