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Table 3 Publc validation set performance for all models and descriptor sets

From: Feature combination networks for the interpretation of statistical machine learning models: application to Ames mutagenicity

 

MACCS

Pubchem

CDK standard

 

AUC

BAC

SEN

SPEC

AUC

BAC

SEN

SPEC

AUC

BAC

SEN

SPEC

SVM

0.87

0.81

0.82

0.79

0.88

0.82

0.84

0.80

0.87

0.81

0.84

0.78

RF

0.88

0.82

0.86

0.77

0.88

0.81

0.86

0.76

0.88

0.81

0.83

0.79

DT

0.81

0.77

0.80

0.74

0.79

0.76

0.78

0.74

0.80

0.75

0.79

0.72

kNN

0.84

0.76

0.84

0.68

0.84

0.77

0.81

0.73

0.83

0.75

0.81

0.70

 

CDK Extended

Atom centered

    
 

AUC

BAC

SEN

SPEC

AUC

BAC

SEN

SPEC

    

SVM

0.87

0.81

0.83

0.79

0.88

0.82

0.84

0.80

    

RF

0.87

0.80

0.82

0.78

0.88

0.81

0.82

0.80

    

DT

0.78

0.75

0.80

0.71

0.79

0.75

0.79

0.71

    

kNN

0.84

0.77

0.81

0.73

0.84

0.77

0.82

0.72

    
  1. AUC = area under curve, BAC = balanced accuracy, SEN = sensitivity, SPEC = specificity.