

def staged_predict_score(self, X):
    X = self.get_train_vars(X)
    score = np.zeros(len(X))
    for (classifier, weight) in zip(self.estimators_, self.estimator_weights_):
        score += (self._estimator_score(X, X) * weight)
        (yield score)

dataset/ETHPy150Open anaderi/lhcb_trigger_ml/hep_ml/uboost.py uBoostBDT.staged_predict_score/VarMisuse@60/74 `classifier`->`X`