www.pudn.com > kernelSVM.rar > Kernel.m

function mat_kernel=Kernel(mat_train,mat_test,kernelType,kPara) 
% input parameters: 
% mat_train--£­the train data, a row represents a sample 
% mat_test---- the test data, a row represents a sample 
% kernelType-- the kernel type 
% kPara------- the kernel parameter(s) 
% output parameter: 
% mat_kernel-- the kernel matrix 
 
% Written by WangZhe on 2004-09-27.  
 
switch lower(kernelType) 
    case 'linear' 
        mat_kernel=mat_train*mat_test'; 
    case 'poly' 
        mat_kernel=(mat_train*mat_test'+1).^kPara; 
    case 'rbf' 
        TrainSampleNum=size(mat_train,1); 
        TestSampleNum=size(mat_test,1); 
        mat_temp=sum(mat_train.^2,2)*ones(1,TestSampleNum)... 
                +ones(TrainSampleNum,1)*sum(mat_test.^2,2)'... 
                -2*mat_train*mat_test'; 
        mat_kernel=exp(-mat_temp/(kPara^2)); 
    case 'sigmoid' 
        mat_kernel=tan(kPara(1)*mat_train*mat_test'/256-kPara(2));         
    case 'exp' 
        mat_kernel=(1+exp(kPara*mat_train*mat_test')).^(-1); 
    otherwise  
        mat_kernel=mat_train*mat_test'; 
end