Table 3 5-Fold cross-validation performances of methods on Pan dataset
Method | Accuracy (%) | Precision (%) | Recall (%) | Specificity (%) | F1-Score (%) | MCC (%) |
|---|---|---|---|---|---|---|
PIPR (2019) | 98.26 ± 0.02 | 98.68 ± 0.04 | 97.40 ± 0.04 | 97.93 ± 0.03 | 98.04 ± 0.02 | 96.49 ± 0.03 |
FSNN-LGBM (2021) | 99.50 ± 0.28 | 98.48 ± 0.12 | 99.39 ± 0.54 | 99.58 ± 0.10 | 99.43 ± 0.32 | 98.98 ± 0.57 |
Graph-BERT (2023) | 99.02 ± 0.13 | 98.94 ± 0.88 | 99.15 ± 0.95 | 98.57 ± 1.19 | 99.04 ± 0.10 | 98.00 ± 0.28 |
Our xCAPT5 | 99.77 ± 0.02 | 99.75 ± 0.03 | 99.75 ± 0.02 | 99.80 ± 0.02 | 99.62 ± 0.06 | 99.55 ± 0.03 |