Open Science Research Excellence
%0 Journal Article
%A D.N. Zheng and  J.X. Wang and  Y.N. Zhao and  Z.H. Yang
%D 2007 
%J  International Journal of Computer, Electrical, Automation, Control and Information Engineering
%B World Academy of Science, Engineering and Technology
%I International Science Index 4, 2007
%T An Iterative Algorithm for KLDA Classifier 
%U http://waset.org/publications/4549
%V 4
%X The Linear discriminant analysis (LDA) can be
generalized into a nonlinear form - kernel LDA (KLDA) expediently
by using the kernel functions. But KLDA is often referred to a general
eigenvalue problem in singular case. To avoid this complication, this
paper proposes an iterative algorithm for the two-class KLDA. The
proposed KLDA is used as a nonlinear discriminant classifier, and the
experiments show that it has a comparable performance with SVM.
%P 1082 - 1085