Implementation of Gaussian RBF in Matlab

Question

I'm starting with Machine Learning and needed help with implementing Gaussian RBF in Matlab.

I know what it is doing, but not sure how to implement this in matlab

Answer 1

function K = rbf(coord,sig)

%function K = rbf(coord,sig)
%
% Computes an rbf kernel matrix from the input coordinates
%
%INPUTS
% coord =  a matrix containing all samples as rows
% sig = sigma, the kernel width; squared distances are divided by
%       squared sig in the exponent
%
%OUTPUTS
% K = the rbf kernel matrix ( = exp(-1/(2*sigma^2)*(coord*coord')^2) )
%

n=size(coord,1);
K=coord*coord'/sig^2;
d=diag(K);
K=K-ones(n,1)*d'/2;
K=K-d*ones(1,n)/2;
K=exp(K);

%% Previous version:
%%
% n = size(coord,1);
% for i=1:n
%     K(i,i)=1;
%     for j=1:i-1
%         K(i,j)=exp(-norm(coord(i,:)-coord(j,:))^2/sig^2);% Should be
%         % 2*sig^2!
%         K(j,i)=K(i,j);
%     end
% end

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