Bayesian Optimization

The Bayesian optimization is one of the machine learning methods to find the optimal value (maximum value or minimum value) of a function whose shape is unknown (black box function). From the function values at a finite number of points, the Bayesian optimization predicts the functional form by the Gaussian process from the function values at a limited number of points. Then, a point, which is expected to have the optimum value or that with large uncertainty is examined preferentially. By sequentially adding search points and gradually increasing the accuracy of prediction, this method can find the optimum point even in a relatively high-dimensional search space.