Re: [R] Finding the right number of clusters

From: TEMPL Matthias <Matthias.Templ_at_statistik.gv.at>
Date: Tue 17 May 2005 - 23:18:46 EST


Hello,

It depends, *which clustering method you will use*. Model-based Clustering algorithms have the BIC criterion implemented (Mclust).
Partition Based clustering algorithms have other criterias (Sum of Squares withhin and between clusters and you can easely implement other criterias).
Most of the criterias in fuzzy clustering are very different. With hierarchical clustering algorithms, you can also determine the number of cluster, very different from the other methods. Note that there is no optimal criteria for all these different methods and it is not so easy to find the optimal number of clusters - the optimal number of clusters depends on your data and which criteria you have to use depends also on your data.

Best,
Matthias

> SAS has something called the "cubic criterion" cutoff for finding the
> most appropriate number of clusters. Does R have anything that would
> replicate that? I've been searching the lists and can't seem to find
> anything that would point me in the right direction.
>
> Thank in advance,
> Philip Bermingham
>
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R-help@stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Tue May 17 23:24:33 2005

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