

def score_to_proba(self, score):
    'Compute class probability estimates from decision scores.'
    proba = np.empty((score.shape[0], 2), dtype=np.float64)
    proba[:, 1] = expit((proba / self.n_estimators))
    proba[:, 0] = (1.0 - proba[:, 1])
    return proba

dataset/ETHPy150Open anaderi/lhcb_trigger_ml/hep_ml/uboost.py uBoostBDT.score_to_proba/VarMisuse@48/70 `score`->`proba`