K-means Clustering Result Always Changes

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Alvi Syahrin
Alvi Syahrin 2013-5-4
评论： Walter Roberson 2021-11-26
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?

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采纳的回答

Walter Roberson
Walter Roberson 2013-5-5
%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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esmat abdallah
esmat abdallah 2021-11-26
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 2021-11-26
@esmat abdallah
%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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更多回答（2 个）

the cyclist
the cyclist 2013-5-4
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 个评论
Alvi Syahrin
Alvi Syahrin 2013-5-4
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 2013-5-4
Type
>> doc randstream
to see how to do it in your version.

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Pallavi Saha
Pallavi Saha 2017-9-14
I am facing the same issue inconsistency in the output of fcm. Can anyone help me
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Mehmet Volkan Ozdogan
Mehmet Volkan Ozdogan 2019-3-28
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 2019-3-29
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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