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 repo.

method: caruana
rmse: 0.1320

Usage

from retrotac.models.ensemble import RetroTAC

model = RetroTAC.from_pretrained("ailab-bio/RetroTAC")
predictions = model.predict(["CCO", "c1ccccc1"])