Table 1.
Performance of SVM-based method using amino acid composition
| Threshold | Sensitivity | Specificity | Accuracy | PPV | NPV | MCC |
|---|---|---|---|---|---|---|
| 1.0 | 0.3374 | 0.9829 | 0.6918 | 0.9417 | 0.6442 | 0.4336 |
| 0.8 | 0.4243 | 0.9700 | 0.7239 | 0.9208 | 0.6729 | 0.4843 |
| 0.6 | 0.5200 | 0.9586 | 0.7608 | 0.9116 | 0.7093 | 0.5456 |
| 0.4 | 0.5878 | 0.9386 | 0.7804 | 0.8871 | 0.7357 | 0.5732 |
| 0.2 | 0.6539 | 0.9243 | 0.8024 | 0.8765 | 0.7657 | 0.6099 |
| 0.0 | 0.7357 | 0.8929 | 0.8220 | 0.8494 | 0.8054 | 0.6422 |
| −0.2 | 0.8383 | 0.8543 | 0.8471 | 0.8253 | 0.8667 | 0.6930 |
| −0.4 | 0.8887 | 0.8186 | 0.8502 | 0.8009 | 0.9009 | 0.7053 |
| −0.6 | 0.9061 | 0.7614 | 0.8267 | 0.7573 | 0.9096 | 0.6680 |
| −0.8 | 0.9391 | 0.6957 | 0.8055 | 0.7171 | 0.9347 | 0.6441 |
| −1.0 | 0.9583 | 0.6100 | 0.7671 | 0.6687 | 0.9489 | 0.5933 |
The boldface indicates the best result