rbfkernel.m.svn-base

a function inside machine learning

function rbfK = rbfKernel(X1, X2, kernelParams)
%Compute the RBF kernel on some data. 
%
sigma = kernelParams.sigma;

numX1Examples = size(X1, 1); 
numX2Examples = size(X2, 1);
numFeatures = size(X1, 2);

j0 = ones(numFeatures, 1);
j1 = ones(numX1Examples, 1); 
j2 = ones(numX2Examples, 1); 

diagK1 = (X1.^2)*j0;
diagK2 = (X2.^2)*j0;

X1X2 = X1*X2'; 

Q = (2*X1X2 - diagK1*j2' - j1*diagK2')/(2*sigma^2);

rbfK = exp(Q);