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?
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cgo
cgo am 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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Image Analyst
Image Analyst am 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 Kommentare
Image Analyst
Image Analyst am 27 Mär. 2019
You forgot to attach 'ucd1.xlsx', or even any scatterplots. Please do so, so we can help you.
Mehmet Volkan Ozdogan
Mehmet Volkan Ozdogan am 2 Apr. 2019
You can find Ucd1 and ucd2.xlsx file in attachment. Thank you

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