

def score_to_proba(self, score):
    proba = np.empty((len(score), 2), dtype=float)
    proba[:, 1] = (score / self.efficiency_steps)
    proba[:, 0] = (1.0 - proba[:, 1])
    return score

dataset/ETHPy150Open anaderi/lhcb_trigger_ml/hep_ml/uboost.py uBoostClassifier.score_to_proba/VarMisuse@66/76 `proba`->`score`