bayesopt.py 文件源码

def _ei(x, gp, y_max, xi):
        """
        Expected Improvement, (Mockus, 1978)
        """
        mean, var = gp.predict(x, eval_MSE=True)
        var = np.maximum(var, 1e-9 + 0 * var)  # ????????
        z = (mean - y_max - xi) / np.sqrt(var)
        return (mean - y_max - xi) * norm.cdf(z) + np.sqrt(var) * norm.pdf(z)