There is a great deal more even to MATLAB's pre-defined functions, although this may depend on what version/toolboxes you have available to you. Perhaps the following links may help:

Cluster Analysis: A Toolbox for MATLAB

(http://cda.psych.uiuc.edu/multivariate_fall_2013/5283-Millsap-Ch20.pdf)

Data Clustering [contains MATLAB code]

(http://people.whitman.edu/~hundledr/courses/M350S08/Chap09.pdf)

Some scripts that I think were based at least partly on An Introduction to Pattern Recognition: A MATLAB Approach:

http://mvhs.shodor.org/mvhsproj/clustering/MatClust2.html

However, I haven't examined them.

I am not sure I understand you.

This:

x=rand(10000,2);

k=5;

c=kmeans(x,5);

works in my Matlab (R2012b) without problem. As a result we get the numbers of cluster for which each data point is assigned.

@all,

My dataset included angle and distance. Angle was in degree and hence the value was not comparable with the distance (Angle was spanning 0-360 range while distance being in 0-4 range). I converted angle from degree to radian and Kmeans did the trick for me.

Thanx allo of you for your suggestions.