Kernel Discriminant Analysis

In paper [2], we present an efficientapproach

Examples:
%
% fea = rand(50,70);
% gnd = [ones(10,1);ones(15,1)*2;ones(10,1)*3;ones(15,1)*4];
% options.KernelType = 'Gaussian';
% options.t = 1;
% [eigvector, eigvalue] = KDA(gnd, options, fea);
%
% feaTest = rand(3,10);
% Ktest = constructKernel(feaTest,fea,options)
% Y = Ktest*eigvector;