Run
10229933

Run 10229933

Task 31 (Supervised Classification) credit-g Uploaded 15-07-2019 by Felix Neutatz
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  • openml-python RawFeatureBaseline Sklearn_0.20.3.
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Flow

sklearn.pipeline.C378925ada5495e(n10=sklearn.impute.SimpleImputer,n11=sklea rn.preprocessing._encoders.OneHotEncoder,n12=sklearn.preprocessing.data.Sta ndardScaler,c=sklearn.linear_model.logistic.LogisticRegression)(1)Automatically created scikit-learn flow.
sklearn.impute.SimpleImputer(10)_copytrue
sklearn.impute.SimpleImputer(10)_fill_valuenull
sklearn.impute.SimpleImputer(10)_missing_valuesNaN
sklearn.impute.SimpleImputer(10)_strategy"mean"
sklearn.impute.SimpleImputer(10)_verbose0
sklearn.preprocessing.data.StandardScaler(25)_copytrue
sklearn.preprocessing.data.StandardScaler(25)_with_meanfalse
sklearn.preprocessing.data.StandardScaler(25)_with_stdtrue
sklearn.preprocessing._encoders.OneHotEncoder(9)_categorical_features[0, 2, 3, 5, 6, 8, 9, 11, 13, 14, 16, 18, 19]
sklearn.preprocessing._encoders.OneHotEncoder(9)_categoriesnull
sklearn.preprocessing._encoders.OneHotEncoder(9)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing._encoders.OneHotEncoder(9)_handle_unknown"error"
sklearn.preprocessing._encoders.OneHotEncoder(9)_n_valuesnull
sklearn.preprocessing._encoders.OneHotEncoder(9)_sparsetrue
sklearn.linear_model.logistic.LogisticRegression(23)_C0.01
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_state33161
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.C378925ada5495e(n10=sklearn.impute.SimpleImputer,n11=sklearn.preprocessing._encoders.OneHotEncoder,n12=sklearn.preprocessing.data.StandardScaler,c=sklearn.linear_model.logistic.LogisticRegression)(1)_memorynull
sklearn.pipeline.C378925ada5495e(n10=sklearn.impute.SimpleImputer,n11=sklearn.preprocessing._encoders.OneHotEncoder,n12=sklearn.preprocessing.data.StandardScaler,c=sklearn.linear_model.logistic.LogisticRegression)(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "n10", "step_name": "n10"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "n11", "step_name": "n11"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "n12", "step_name": "n12"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "c", "step_name": "c"}}]

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
0.7922 ± 0.0401
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.7361 ± 0.0471
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.407 ± 0.1045
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.0578 ± 0.0426
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.3835 ± 0.0123
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4202
Cross-validation details (10-fold Crossvalidation)
Number of instances
1000
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.7596 ± 0.0453
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.727 ± 0.0488
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.8813
Cross-validation details (10-fold Crossvalidation)
Recall
0.727 ± 0.0488
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.9129 ± 0.0292
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4583
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4306 ± 0.0159
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9397 ± 0.0347
Cross-validation details (10-fold Crossvalidation)