1. A pattern recognition method, comprising: calculating an evaluation value by using a set of vectors obtained by mapping a set of vectors conformed to at least one learning sample in an input space respectively to a nonlinear space defined by a kernel function as a set of base vectors constituting each of plural subspaces in the nonlinear space, defined for each of categories into which a pattern is classified, the evaluation value representing a relation between the plural subspaces represented by a linear combination of corresponding sets of the base vectors and mapping of an unknown input pattern to the nonlinear space; and recognizing a category to which the unknown input pattern belongs, based on the evaluation value.