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Table 2 Recognition accuracy by n-fold cross validation procedure for different feature extraction techniques for SVM classification for the TG dataset.

From: Improving protein fold recognition using the amalgamation of evolutionary-based and structural based information

Feature sets n= 5 n= 6 n= 7 n= 8 n= 9 n= 10
PF1 [23] 38.1 38.4 38.6 38.7 38.8 38.8
PF2 [23] 38.0 38.4 38.5 38.6 38.7 38.8
PF [24] 42.3 42.6 42.7 43.0 43.0 43.1
O [21] 35.8 36.1 36.2 36.1 36.3 36.3
AAC [5] 31.5 31.5 31.7 31.8 31.9 32.0
AAC+HXPZV [5] 35.7 36.0 36.1 36.2 36.3 36.3
ACC [29] 64.9 65.4 65.9 66.2 66.4 66.4
PSSM+PF1 [55] 51.1 51.5 52.0 52.3 52.4 52.7
PSSM+PF2 [55] 50.2 50.4 50.7 50.8 51.0 51.1
PSSM+PF [55] 57.2 57.8 58.0 58.3 58.5 58.8
PSSM+O [55] 46.0 46.3 46.5 46.5 46.7 46.7
PSSM+AAC [55] 43.2 43.5 43.6 43.8 43.8 44.0
PSSM+AAC+HXPZV [55] 45.6 45.9 46.0 46.2 46.3 46.6
Mono-gram [19] 57.2 57.3 58.2 58.4 58.8 58.8
Bi-gram [19] 67.1 67.5 67.6 67.8 68.1 68.1
k -AAP (this paper) 75.9 76.2 76.6 76.7 76.9 77.0