Table 5 Classification results of different feature extraction methods
Dataset | Feature extraction method | Jackknife test (%) | ||||||
|---|---|---|---|---|---|---|---|---|
| Â | Â | Sensitivity | ||||||
| Â | Â | Cy | En | Me | Mi | Nu | Se | OA |
CL317 | CTM | 91.96 | 93.62 | 90.91 | 88.24 | 86.54 | 76.47 | 89.91 |
| Â | AECA-PSSM | 91.07 | 91.49 | 94.55 | 91.18 | 84.62 | 76.47 | 89.91 |
| Â | CTM-AECA-PSSM | 92.86 | 91.49 | 92.73 | 85.29 | 88.46 | 76.47 | 90.22 |
| Â | CTM-AECA-PSSM-LDA | 99.11 | 100 | 100 | 100 | 100 | 100 | 99.68 |
ZW225 | CTM | 84.29 | \ | 90.01 | 72.00 | 85.37 | \ | 85.78 |
| Â | AECA-PSSM | 87.14 | \ | 94.38 | 68.00 | 75.61 | \ | 85.78 |
| Â | CTM-AECA-PSSM | 87.14 | \ | 88.76 | 76.00 | 80.49 | \ | 85.33 |
| Â | CTM-AECA-PSSM-LDA | 97.14 | \ | 91.01 | 100 | 100 | \ | 95.56 |