K-means Clustering Result Always Changes

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I'm working on k-means in MATLAB. Here are my codes:
load cobat.txt
k=input('Enter the number of cluster: ');
if k<8
[cidx ctrs]=kmeans(cobat, k, 'dist', 'sqEuclidean');
Z = [cobat cidx]
else
h=msgbox('Must be less than eight');
end
"cobat" is the file of mine and here it looks:
65 80 55
45 75 78
36 67 66
65 78 88
79 80 72
77 85 65
76 77 79
65 67 88
85 76 88
56 76 65
My problem is everytime I run the code, it always shows different result, different cluster. How can I keep the clustering result always the same?

Accepted Answer

Walter Roberson
Walter Roberson on 5 May 2013
%generate some initial cluster centers according to some deterministic algorithm
%in this case, I construct a space-diagonal equally spaced, but choose your
%own algorithm
minc = min(cobat, 1);
maxc = max(cobat, 1);
nsamp = size(cobat,1);
initialcenters = repmat(minc, nsamp, 1) + bsxfun(@times, (0:nsamp-1).', (maxc - minc) ./ (nsamp-1));
%Once you have constructed the initial centers, cluster using those centers
[cidx ctrs] = kmeans(cobat, k, 'dist', 'sqEuclidean', 'start', initialcenters);
  6 Comments
esmat abdallah
esmat abdallah on 26 Nov 2021
initialcenters = repmat(minc, nsamp, 1) + bsxfun(@times, (0:nsamp-1).', (maxc - minc) ./ (nsamp-1));
please, matlab out an error on this line : "Error using +
Matrix dimensions must agree."
what can i do ??
Walter Roberson
Walter Roberson on 26 Nov 2021
%generate some initial cluster centers according to some deterministic algorithm
%in this case, I construct a space-diagonal equally spaced, but choose your
%own algorithm
minc = min(cobat, [], 1);
maxc = max(cobat, [], 1);
nsamp = size(cobat,1);
initialcenters = repmat(minc, nsamp, 1) + bsxfun(@times, (0:nsamp-1).', (maxc - minc) ./ (nsamp-1));
%Once you have constructed the initial centers, cluster using those centers
[cidx ctrs] = kmeans(cobat, k, 'dist', 'sqEuclidean', 'start', initialcenters);

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More Answers (2)

the cyclist
the cyclist on 4 May 2013
K-means clustering uses randomness as part of the algorithm Try setting the seed of the random number generator before you start. If you have a relatively new version of MATLAB, you can do this with the rng() command. Put
rng(1)
at the beginning of your code.
  2 Comments
Alvi Syahrin
Alvi Syahrin on 4 May 2013
Thank you for the answer. I have MATLAB 7.11.0(R2010b), and when I tried that command, it's not working, getting an error for undefined function. Do you have any idea to solve this?
the cyclist
the cyclist on 4 May 2013
Type
>> doc randstream
to see how to do it in your version.

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Pallavi Saha
Pallavi Saha on 14 Sep 2017
I am facing the same issue inconsistency in the output of fcm. Can anyone help me
  3 Comments
Mehmet Volkan Ozdogan
Mehmet Volkan Ozdogan on 28 Mar 2019
Hi,
I have a question about rng(). If we use rng() command, K-means algortihm stil repeats until the results are getting convergenced to the best. Is that right?
Thank you
Walter Roberson
Walter Roberson on 29 Mar 2019
Yes.
rng(SomeParticularNumericSeed)
just ensures that it will always use the same random number sequence provided that no other random numbers are asked for between the rng() call and the kmeans call.

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