Run
10228049

Run 10228049

Task 10103 (Supervised Classification) volcanoes-a1 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(V3=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": [2]}}]
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_state41267
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(V3=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(V3=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(V3=sklearn.compose._column_transformer.ColumnTransformer(identity=sklearn.preprocessing._function_transformer.FunctionTransformer))(1)_memorynull
sklearn.pipeline.Pipeline(V3=sklearn.compose._column_transformer.ColumnTransformer(identity=sklearn.preprocessing._function_transformer.FunctionTransformer))(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "V3", "step_name": "V3"}}]

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.

15 Evaluation measures

Area under ROC curve
0.7791 ± 0.0437
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.3805 ± 0.0436
Cross-validation details (10-fold Crossvalidation)
KB relative information score
619.8896 ± 15.0248
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0406 ± 0.0023
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.0699 ± 0.0007
Cross-validation details (10-fold Crossvalidation)
Number of instances
3252
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8985 ± 0.0058
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.6323
Cross-validation details (10-fold Crossvalidation)
Recall
0.8985 ± 0.0058
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.5806 ± 0.0348
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.1864 ± 0.0018
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.2015 ± 0.0058
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.0806 ± 0.035
Cross-validation details (10-fold Crossvalidation)