Table 4 Performance of ML models on the best feature selection approach.
Classifier | Acc (%) | Sn (%) | Sp (%) | PR-AUC (%) | MCC |
|---|---|---|---|---|---|
RF | 80.68 | 81.35 | 80.01 | 86.44 | 0.684 |
ERT | 83.65 | 82.65 | 84.27 | 89.13 | 0.709 |
Adaboost | 85.72 | 84.25 | 86.16 | 91.36 | 0.735 |
ERCNN-EGFR | 93.48 | 94.53 | 92.58 | 97.38 | 0.816 |