Help in k means clustering

Dear all, I am still not comfortable with k-means clustering in classification. Especially while rerunning with the code

eva = evalclusters(params,'kmeans','silhouette','KList',[2:20]);

It gives me different cases. Also while using separate code like

[idx,cent,sumdist, meansilh] =kcluster('param2W_sac.cld', optkn, s);

there is different answers. I think I am concemptually wrong in using rng-function. Is there some one to help me in this manner. It will be great is there availability to have online tutor in such cases.

Answer 1

[the cyclist]

There is a randomness component in k-means clustering, as you surmise.

Have you tried putting the statement

rng(1)

at the beginning of your code? This will set the generator seed, and therefore produce the same series of pseudorandom numbers each time you run it.

Answer 2

[Mahesh]

Thanks for reply. However I got following error message while trying with ring(1). I could not understand what it asks for. Moreover, I am using Matlab R2013b.

Error using rng (line 96) The current random number generator is the legacy generator. This is because you have executed a command such as rand('state',0), which activates MATLAB's legacy random number behavior. You may not use RNG to reseed the legacy random number generator.

Use rng('default') to reinitialize the random number generator to its startup configuration, or call RNG using a specific generator type, such as rng(seed,'twister').

Error in Cluster_runoff (line 12) s = rng(1);

Thanks for response again.