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Table 3 Recognition accuracy by n-fold cross validation procedure for different feature extraction techniques for SVM classification for the EDD 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] 50.2 50.5 50.5 50.7 50.8 50.8
PF2 [23] 49.3 49.5 49.7 49.8 49.8 49.9
PF [24] 54.7 55.0 55.2 55.4 55.5 55.6
O [21] 46.4 46.6 46.6 46.7 46.7 46.9
AAC [5] 40.3 40.6 40.7 40.7 40.9 40.9
AAC+HXPZV [5] 40.2 40.4 40.6 40.7 40.9 40.9
ACC [29] 84.9 85.2 85.4 85.6 85.8 85.9
PSSM+PF1 [55] 74.1 74.5 74.7 75.0 75.1 75.2
PSSM+PF2 [55] 73.7 74.1 74.5 74.6 74.7 74.9
PSSM+PF [55] 78.2 78.6 78.8 79.0 79.1 79.3
PSSM+O [55] 67.6 68.0 68.1 68.3 68.3 68.5
PSSM+AAC [55] 60.9 61.3 61.5 61.6 61.7 61.9
PSSM+AAC+HXPZV [55] 66.7 67.2 67.4 67.7 67.8 67.9
Mono-gram [19] 76.2 76.3 76.6 76.8 77.0 76.9
Bi-gram [19] 83.6 84.0 84.1 84.3 84.3 84.5
k -AAP (this paper) 90.1 90.2 90.4 90.5 90.6 90.6