running k-means and getting different results run after run?

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I am running k-means clustering algorithm on a data, and I don't understand why I am getting different silhouette plots each time I run this. Is there a way to stabilise this? (or set the number of iterations) so I get the same results?
  3 Comments
cgo
cgo on 17 Aug 2018
<<
These are two results of the the same data, and the same number of clusters (2). Is the data just that bad? Or I am not getting something right here?
Thanks for your insights.
>>

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Accepted Answer

Image Analyst
Image Analyst on 17 Aug 2018
That's normal. Specify 'Replicates' to get convergence.
% Do kmeans clustering on the gray scale image.
grayLevels = double(grayImage(:)); % Convert to column vector.
[clusterIndexes, clusterCenters] = kmeans(grayLevels, numberOfClusters,...
'distance', 'sqEuclidean', ...
'Replicates', 2);
labeledImage = reshape(clusterIndexes, rows, columns);
See attached demo.
  3 Comments
Image Analyst
Image Analyst on 27 Mar 2019
You forgot to attach 'ucd1.xlsx', or even any scatterplots. Please do so, so we can help you.

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