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

3 次查看（过去 30 天）

cgo 2018-8-17

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/415205-running-k-means-and-getting-different-results-run-after-run

评论： Mehmet Volkan Ozdogan 2019-4-2

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 个评论
显示 1更早的评论隐藏 1更早的评论

cgo 2018-8-17

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.

cgo 2018-8-17

image.png

请先登录，再进行评论。

请先登录，再回答此问题。

采纳的回答

Image Analyst 2018-8-17

0
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/415205-running-k-means-and-getting-different-results-run-after-run#answer_333160

在 MATLAB Online 中打开

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);