The performance of PreHom-PCLM predictors based on different components and their combinations
| Method . | 2D CNN . | TRM . | ROC1 . | ROC50 . |
|---|---|---|---|---|
| PreHom-PCLM | ✔ | ✔ | 0.9857 | 0.9937 |
| ✔ | ✗ | 0.9820 | 0.9926 | |
| ✗ | ✔ | 0.9538 | 0.9797 | |
| ✗ | ✗ | 0.9453 | 0.9770 |
| Method . | 2D CNN . | TRM . | ROC1 . | ROC50 . |
|---|---|---|---|---|
| PreHom-PCLM | ✔ | ✔ | 0.9857 | 0.9937 |
| ✔ | ✗ | 0.9820 | 0.9926 | |
| ✗ | ✔ | 0.9538 | 0.9797 | |
| ✗ | ✗ | 0.9453 | 0.9770 |
The performance of PreHom-PCLM predictors based on different components and their combinations
| Method . | 2D CNN . | TRM . | ROC1 . | ROC50 . |
|---|---|---|---|---|
| PreHom-PCLM | ✔ | ✔ | 0.9857 | 0.9937 |
| ✔ | ✗ | 0.9820 | 0.9926 | |
| ✗ | ✔ | 0.9538 | 0.9797 | |
| ✗ | ✗ | 0.9453 | 0.9770 |
| Method . | 2D CNN . | TRM . | ROC1 . | ROC50 . |
|---|---|---|---|---|
| PreHom-PCLM | ✔ | ✔ | 0.9857 | 0.9937 |
| ✔ | ✗ | 0.9820 | 0.9926 | |
| ✗ | ✔ | 0.9538 | 0.9797 | |
| ✗ | ✗ | 0.9453 | 0.9770 |
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