How to design a regularization term for improving generalization

In supervised learning, the regularization method is often used for improving the level of generalization. We give a necessary and sufficient condition of an optimal regularization term, i.e., a regularization operator and parameter. The optimality is discussed based on the projection learning criterion in which the minimization of a generalization error is explicitly considered. We suggest how to design the optimal regularization term so as to satisfy the obtained condition