Table 7. The training performance of CNN_4 on the GWH dataset with different window sizes.
The training performance on the GWH dataset with different window sizes were collected from 5-fold cross-validation. The average values of each evaluation matrix are shown.
| Site | Window size (nt) | Model | |||
|---|---|---|---|---|---|
| CNN_4 | |||||
| AUPRC | Precision | Recall | MCC | ||
| Donor | 40 | 0.924 | 0.848 | 0.890 | 0.849 |
| 80 | 0.933 | 0.871 | 0.894 | 0.866 | |
| 160 | 0.948 | 0.886 | 0.908 | 0.882 | |
| 240 | 0.951 | 0.888 | 0.916 | 0.888 | |
| 398 | 0.951 | 0.888 | 0.918 | 0.889 | |
| Acceptor | 40 | 0.846 | 0.774 | 0.788 | 0.749 |
| 80 | 0.890 | 0.818 | 0.834 | 0.801 | |
| 160 | 0.922 | 0.856 | 0.860 | 0.838 | |
| 240 | 0.933 | 0.880 | 0.870 | 0.857 | |
| 398 | 0.938 | 0.886 | 0.880 | 0.867 | |
Notes.
Bold styling emphasizes the highest values regarding the evaluation metrics used in the study.