This is a fully vectorized version kmedoids clustering methods (http://en.wikipedia.org/wiki/K-medoids). It is usually more robust than kmeans algorithm. Please try following code for a demo:
close all; clear;
d = 2;
k = 3;
n = 500;
[X,label] = kmeansRnd(d,k,n);
y = kmedoids(X,k);
plotClass(X,label);
figure;
plotClass(X,y);
Input data are assumed COLUMN vectors!
You can only visualize 2d data!
This function is now a part of the PRML toolbox (//www.tianjin-qmedu.com/matlabcentral/fileexchange/55826-pattern-recognition-and-machine-learning-toolbox)