

def _estimator_score(self, estimator, X):
    if (self.algorithm == 'SAMME'):
        return ((2 * estimator.predict(X)) - 1.0)
    else:
        p = estimator.predict_proba(X)
        p[(p <= 1e-05)] = 1e-05
        return np.log((p[:, 1] / p[:, 0]))

dataset/ETHPy150Open anaderi/lhcb_trigger_ml/hep_ml/uboost.py uBoostBDT._estimator_score/original