logit_rules.py 文件源码

def likelihood_y_given_X_beta(self, X, beta):
        psi = np.dot(X,beta)
        probabilities = 1.0/(1.0+np.exp(-1.0*psi))
        return np.sum(
            np.log(np.where(self.data.y,probabilities,1.0-probabilities))
        )