Run
10159567

Run 10159567

Task 10101 (Supervised Classification) blood-transfusion-service-center Uploaded 30-03-2019 by Vishal R
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Flow

sklearn.pipeline.Pipeline(selectkbest=sklearn.feature_selection.univariate_ selection.SelectKBest,standardscaler=sklearn.preprocessing.data.StandardSca ler,gaussiannb=sklearn.naive_bayes.GaussianNB)(1)Automatically created scikit-learn flow.
sklearn.pipeline.Pipeline(selectkbest=sklearn.feature_selection.univariate_selection.SelectKBest,standardscaler=sklearn.preprocessing.data.StandardScaler,gaussiannb=sklearn.naive_bayes.GaussianNB)(1)_memorynull
sklearn.pipeline.Pipeline(selectkbest=sklearn.feature_selection.univariate_selection.SelectKBest,standardscaler=sklearn.preprocessing.data.StandardScaler,gaussiannb=sklearn.naive_bayes.GaussianNB)(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "selectkbest", "step_name": "selectkbest"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "gaussiannb", "step_name": "gaussiannb"}}]
sklearn.feature_selection.univariate_selection.SelectKBest(3)_k3
sklearn.feature_selection.univariate_selection.SelectKBest(3)_score_func{"oml-python:serialized_object": "function", "value": "sklearn.feature_selection.univariate_selection.f_regression"}
sklearn.preprocessing.data.StandardScaler(26)_copytrue
sklearn.preprocessing.data.StandardScaler(26)_with_meantrue
sklearn.preprocessing.data.StandardScaler(26)_with_stdtrue
sklearn.naive_bayes.GaussianNB(14)_priorsnull
sklearn.naive_bayes.GaussianNB(14)_var_smoothing1e-09

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
0.6973 ± 0.0473
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.7091 ± 0.0426
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.1417 ± 0.1287
Cross-validation details (10-fold Crossvalidation)
KB relative information score
99.4465 ± 6.4782
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.291 ± 0.0246
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
0.6996 ± 0.0543
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.7447 ± 0.0382
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.7928
Cross-validation details (10-fold Crossvalidation)
Recall
0.7447 ± 0.0382
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.8016 ± 0.0676
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
0.4346 ± 0.0326
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.0206 ± 0.0754
Cross-validation details (10-fold Crossvalidation)