Run
10228783

Run 10228783

Task 3656 (Supervised Classification) diabetes_numeric Uploaded 21-06-2019 by Felix Neutatz
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  • openml-python RawFeatureBaseline Sklearn_0.20.3.
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Flow

sklearn.pipeline.C37764d6bb8b464(n1=sklearn.impute.SimpleImputer,n2=sklearn .preprocessing.data.StandardScaler,c=sklearn.linear_model.logistic.Logistic Regression)(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_state44995
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.C37764d6bb8b464(n1=sklearn.impute.SimpleImputer,n2=sklearn.preprocessing.data.StandardScaler,c=sklearn.linear_model.logistic.LogisticRegression)(1)_memorynull
sklearn.pipeline.C37764d6bb8b464(n1=sklearn.impute.SimpleImputer,n2=sklearn.preprocessing.data.StandardScaler,c=sklearn.linear_model.logistic.LogisticRegression)(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "n1", "step_name": "n1"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "n2", "step_name": "n2"}}, {"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
0.6968 ± 0.3471
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.7007 ± 0.2234
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.3864 ± 0.4515
Cross-validation details (10-fold Crossvalidation)
KB relative information score
-0.0675 ± 0.0815
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.4993 ± 0.0013
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4791 ± 0.0218
Cross-validation details (10-fold Crossvalidation)
Number of instances
43
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.7104 ± 0.196
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.6977 ± 0.2331
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9682 ± 0.0639
Cross-validation details (10-fold Crossvalidation)
Recall
0.6977 ± 0.2331
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
1.0422 ± 0.0498
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4889 ± 0.0226
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4993 ± 0.0013
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.0212 ± 0.0495
Cross-validation details (10-fold Crossvalidation)