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Table 4 Feature evaluation.

From: Automatic prediction of catalytic residues by modeling residue structural neighborhood

  

Performance % ± s.d.

 

CV Exp

P

R

FPR

F 1

MCC

AUCROC

AUCRP

1.

SVM_ 1D1-3

22 ± 11

30 ± 11

1.3 ± 0.7

24 ± 7

24 ± 8

0.9172

0.2777

2.

SVM_P 51D

26 ± 8

29 ± 12

0.9 ± 0.3

27 ± 9

26 ± 9

0.9311

0.3129

3.

SVM_P 51D_1D1-3

27 ± 10

30 ± 10

1.0 ± 0.4

27 ± 8

27 ± 8

0.9370

0.3204

4.

SVM_P 7

22 ± 11

37 ± 11

1.8 ± 1.3

26 ± 10

27 ± 10

0.9490

0.3532

5.

SVM_P 24

26 ± 10

37 ± 14

1.2 ± 0.5

30 ± 9

30 ± 10

0.9529

0.3605

6.

SVM_P 24_1D1-3

26 ± 6

44 ± 10

1.4 ± 0.3

32 ± 7

33 ± 7

0.9556

0.3659

7.

SV_M P 24_1D1-3, 3D1-6

28 ± 9

46 ± 10

1.4 ± 0.5

34 ± 8

34 ± 8

0.9635

0.3723

8.

SVM_P 24_1D1-3, 3D1-9

33 ± 14

48 ± 8

1.4 ± 0.7

37 ± 7

38 ± 6

0.9633

0.4125

  1. Summary of the results of the cross-validation on different selected attributes (linear kernel, regularization parameter c = 1).
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BMC Bioinformatics

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