Table 1 Recognition accuracy by n-fold cross validation procedure for different feature extraction techniques for SVM classification for the DD-dataset.
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 |