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Table 2 SVM parameters and AUC for our best models. The SVM parameter d (in polynomial kernel), g (in RBF kernel), c: parameter for trade-off between training error & margin, j: cost-factor.

From: Prediction of FAD interacting residues in a protein from its primary sequence using evolutionary information

Window

SVM parameter

AUC

15 window

Binary

d: 4 c: 1 j: 1

0.769

 

PSSM

d: 5 c: 1 j: 1

0.878

17 window

Binary

g: 0.1 c: 2 j: 1

0.773

 

PSSM

d: 4 c:5 j: 1

0.904

19 window

Binary

d: 3 j: 1 c: 1

0.770

 

PSSM

d: 5 c: 1 j: 1

0.876