Why kmeans gives different results each time?

 * *I have square binary similarity matrix show the social relation among users, where o means no relation between two users and 1 means there is relation between them.

I used kmeans to do clustering*

f1=dlmread('d:\matlab\r2011a\bin\paper_comm\link_flixster_bin1.txt');
  c=kmeans(f1,3);

When run the kmeans more than one times, the results are different.

for example at firs time the cluster 1= 4448 users , cluster 2= 434, and cluster 3=118

But, in second times cluster 1= 4880 users , cluster 2= 119, and cluster 3=1

Why the results are different??*

Answer 1

[John D'Errico]

kmeans uses random starting values. (READ THE HELP. I just did to verify this.) So why would you expect that the solution will be identical if the start points are not?

[huda nawaf]

Thanks,

I forget this information

Answer 2

[Chetan Rawal]

As John mentioned, the clustering happens by starting at random points, automatically selected by the algorithm. That is why in such a optimization/machine learning problems, you should try multiple iterations and use a validation data set if possible. To get the results closer between different runs, you can try to:

• Increase number of iterations by increasing 'MaxIter'
• Use your own starting points with the 'start' name-value pair

Starting with your own seeds instead of randomly selected seeds by MATLAB will ensure a consistent answer.

[huda nawaf]

thanks

[huda nawaf]

how start with my seeds? and how set the seed?

thanks