Run
10230167

Run 10230167

Task 3913 (Supervised Classification) kc2 Uploaded 16-07-2019 by Felix Neutatz
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  • openml-python RawFeatureBaseline Sklearn_0.20.3.
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Flow

sklearn.pipeline.C3789ed6d34d838(n11=sklearn.impute.SimpleImputer,n12=sklea rn.preprocessing.data.StandardScaler,c=sklearn.linear_model.logistic.Logist icRegression)(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.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_state8166
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.C3789ed6d34d838(n11=sklearn.impute.SimpleImputer,n12=sklearn.preprocessing.data.StandardScaler,c=sklearn.linear_model.logistic.LogisticRegression)(1)_memorynull
sklearn.pipeline.C3789ed6d34d838(n11=sklearn.impute.SimpleImputer,n12=sklearn.preprocessing.data.StandardScaler,c=sklearn.linear_model.logistic.LogisticRegression)(1)_steps[{"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
0.8373 ± 0.0862
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.8288 ± 0.0628
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.5002 ± 0.1628
Cross-validation details (10-fold Crossvalidation)
KB relative information score
-0.6825 ± 0.0659
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.4198 ± 0.0129
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.3266 ± 0.0052
Cross-validation details (10-fold Crossvalidation)
Number of instances
522
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.8406 ± 0.056
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8218 ± 0.0692
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.7318 ± 0.0173
Cross-validation details (10-fold Crossvalidation)
Recall
0.8218 ± 0.0692
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
1.2853 ± 0.0432
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4037 ± 0.0065
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4318 ± 0.0164
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.0695 ± 0.0428
Cross-validation details (10-fold Crossvalidation)