running k-means and getting different results run after run?
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cgo
am 17 Aug. 2018
Kommentiert: Mehmet Volkan Ozdogan
am 2 Apr. 2019
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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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
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
am 2 Apr. 2019
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