A family of kernel subspace classifiers

Abstract We present a family of kernel subspace classifiers and their extensions. There are two kinds of regularization methods and they have a degree of freedom about a null space of the operator in the family. Regularization is important to avoid the over-fitting problem in the machine learning theory. The applicable null space of an operator is able to… CONTINUE READING