Skip to main content

Table 2 10-fold cross-validation with forty selected features using different machine learning methods on RSC758

From: Prediction of redox-sensitive cysteines using sequential distance and other sequence-based features

 

ACC

SN

SP

MCC

AUC

SVM

0.679

0.602

0.756

0.362

0.727

Naive Bayes

0.648

0.450

0.846

0.322

0.713

Random Forest

0.664

0.611

0.718

0.330

0.711

Artificial Neural Network

0.662

0.615

0.708

0.325

0.698

  1. The results are sorted by AUC value
Back to article page

BMC Bioinformatics

ISSN: 1471-2105

Contact us