An improved kernel Fisher discriminant classifier and its applications

Abstract

In order to use kernel Fisher discriminant (KFD) classifiers to solve large-scale learning problems, this paper decomposes an n-class dataset into n two-class subsets, and use a subset only composed of a small part of the original dataset in determining the structure of a single KFD classifier. The large number of samples in a class can be further… (More)

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