makekernel.m

有监督自组织映射-偏最小二乘算法(A supervised self-organising map–partial least squares algorithm),可以用语多变量数据的回归分析

function [Ktr,Ktest]=MakeKernel(Xtr,Xtest,MLKP);

global p1 p2
p1=MLKP.KernelParameter1;
p2=MLKP.KernelParameter2;

[NobjTrain,Nvar]=size(Xtr);
[NobjTest,Nvar]=size(Xtest);

for i=1:NobjTrain
    for j=1:NobjTrain
        Ktr(i,j) = svkernel(MLKP.KernelType,Xtr(i,:),Xtr(j,:));
    end
end

for i=1:NobjTest
    for j=1:NobjTrain
        Ktest(i,j) = svkernel(MLKP.KernelType,Xtest(i,:),Xtr(j,:));
    end
end

if (upper(MLKP.SilentMode) == 'N')
    [ntr,ntr]=size(Ktr);
    [ntest,ntr]=size(Ktest);
    Message=sprintf('Square %s training and test kernels are created with sizes %dx%d and %dx%d',...
                    upper(MLKP.KernelType),ntr,ntr,ntest,ntr);
    disp(Message);
end