Finding the right number of clusters

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

______________________________________________
R-help at 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