Table 3.
Results from reduction the features.
| Method | Classifier | AUC | F-Measure |
|---|---|---|---|
| 188D + ACC | RF | 0.9814 | 0.9520 |
| J48 | 0.8840 | 0.8854 | |
| Naïve bayes | 0.9148 | 0.8240 | |
| 188D + kmer | RF | 0.9816 | 0.9542 |
| J48 | 0.8652 | 0.8662 | |
| Naïve bayes | 0.9174 | 0.8650 | |
| 188D-Pse-AAC | RF | 0.9802 | 0.9478 |
| J48 | 0.8748 | 0.8836 | |
| Naïve bayes | 0.9166 | 0.8318 | |
| ACC + kmer | RF | 0.9840 | 0.9556 |
| J48 | 0.8500 | 0.8572 | |
| Naïve bayes s | 0.9512 | 0.8808 | |
| PseAAC + kmer | RF | 0.9820 | 0.9508 |
| J48 | 0.8400 | 0.8400 | |
| Naïve bayes | 0.9412 | 0.8706 | |
| ACC + Pse-AAC | RF | 0.9778 | 0.9394 |
| J48 | 0.8682 | 0.8830 | |
| Naïve bayes | 0.9738 | 0.9210 |
Bold values indicates Best result in that experiment results which is a combination of Method and Classifier.