| # ailab-bio/RetroTAC |
|
|
| Caruana-weighted ensemble of 27 per-fold PROTAC |
| synthesizability surrogate models (GNN:13, MLP:7, XGB:7), selected by greedy |
| forward ensemble selection over 5x5-CV fold models -- see |
| `scripts/models/evaluation.py`'s `EnsembleSelector.greedy_selection` / |
| `run_ensemble_strategies` in the [RetroTAC](https://github.com/ribesstefano/RetroTAC) repo. |
|
|
| - method: `caruana` |
| - rmse: 0.1320 |
|
|
| ## Usage |
|
|
| ```python |
| from retrotac.models.ensemble import RetroTAC |
| |
| model = RetroTAC.from_pretrained("ailab-bio/RetroTAC") |
| predictions = model.predict(["CCO", "c1ccccc1"]) |
| ``` |
|
|
