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Table 1 Recognition accuracy by n-fold cross validation procedure for different feature extraction techniques for SVM classification for the DD-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] 48.6 49.1 49.5 50.1 50.5 50.6
PF2 [23] 46.3 47.0 47.5 47.7 47.9 48.2
PF [24] 51.2 52.2 52.6 52.9 53.4 53.4
O [21] 49.7 50.4 50.8 50.8 51.1 51.0
AAC [5] 43.6 43.9 44.2 44.8 44.6 45.1
AAC+HXPZV [5] 45.1 46.2 46.5 46.8 46.9 47.2
ACC [29] 65.7 66.6 66.8 67.5 67.7 68.0
PSSM+PF1 [55] 62.5 63.2 63.7 64.2 64.5 64.6
PSSM+PF2 [55] 62.7 63.3 64.1 64.2 64.6 64.7
PSSM+PF [55] 65.5 66.2 66.5 66.9 67.1 67.5
PSSM+O [55] 62.5 62.1 62.5 62.9 63.4 63.5
PSSM+AAC [55] 57.5 58.1 58.4 58.7 59.1 59.2
PSSM+AAC+HXPZV [55] 55.9 56.9 57.1 57.7 58.0 58.2
Mono-gram [19] 67.7 68.4 68.6 69.1 69.4 69.6
Bi-gram [19] 72.6 73.1 73.7 73.7 74.1 74.1
k-AAP (this paper) 74.3 75.2 75.2 75.7 76.1 76.1