kmeanscode.m

这里包含了聚类的工具箱还有很详细的文档说明

function [centro,nvoro] = lvqcode(X,centri)

[N,d] = size(X);
[M,dc] = size(centri);

if dc ~= d
    disp('Dimensions from data and centroids is not equal?!')
    return;
end

% d = data dimension
% N = number of points
% L = number of iterations

centro = zeros(size(centri));
nvoro = zeros(M,1);

for n = 1:N

    datum = X(n,:);

    diff = sqrt(sum((centri - ones(M,1)*datum).^2,2));
    minpos = find(diff == min(diff));
    minpos = minpos(1); % case there are two centroids, we choose the first one
    nvoro(minpos) = nvoro(minpos) + 1;
    
    centro(minpos,:) = centro(minpos,:) + datum;

end

npoint = nvoro; npoint(npoint==0) = 1;

centro = centro./(npoint*ones(1,d));