Table 3.
Performance comparison with existing method over ACPmain independent dataset.
| Predictor | Acc (%) | Sen (%) | Spe (%) | MCC |
|---|---|---|---|---|
| ACP-MHCNN | 68.40 | 67.80 | 69.00 | 0.370 |
| iACP-DRLF | 77.50 | 80.70 | 74.30 | 0.490 |
| AntiCP_2.0 | 75.43 | 77.46 | 73.4 1 | 0.510 |
| AntiCP | 50.58 | 100 | 01.16 | 0.070 |
| ACPred | 53.47 | 85.55 | 21.39 | 0.090 |
| ACPred-FL | 44.80 | 67.05 | 22.54 | − 0.120 |
| ACPpred-Fuse | 68.90 | 69.19 | 68.60 | 0.380 |
| iACP | 55.10 | 77.91 | 32.16 | 0.110 |
| ACP-check | 78.00 | 80.00 | 77.00 | 0.560 |
| TriNet | 76.60 | 79.50 | 73.70 | 0.530 |
| ACPPfel | 78.07 | 81.29 | 78.36 | 0.596 |
| PLMACPreda(Proposed) | 96.60 | 94.80 | 97.10 | 0.896 |
Best results highlighted in bold.