A Simple K-means Clustering Routine 1.0
Submitted By:
namespacerz
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This routine takes as input an array of data points, a desired
K value, and an error tolerance; it returns an array of cluster
labels corresponding to the data points, and optionally an
array of the final centroids.
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Comments (3)
nice coding
Posted on Wednesday, October 19, 2005
very precise code, no redundancy
not running
Posted by: naresh on Tuesday, July 31, 2007
where is the main function to this program.., i think some part (main) part of the program is missin...
several problems with clusters
Posted by: luis on Monday, October 27, 2008
Hi, I test your code and it does not seems to be robust, when I choose K>4 clusters, it only generate 1 or 2 clusters. My images are very simple so I dont think that is the reason for the error anyway I will try to fix that and I will let you know if it works
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