Clustering with 'agnes'

Hi,

the underlying principle of hierarchical clustering is *not* that the
clusters can be represented by some centroid points. Most methods are
distance based, i.e. they can be calculated also in absence of any R^p
representation of the points.

If you want to recover centroids, you should do kmeans, normal mixture
clustering (mclust) or pam/clara. Of course you can also take the points
belonging to an agnes cluster and compute the mean vector (or any other
summary statistic), but that's not what hierarchical clustering is
meant to do (it may be reasonable with Ward's method, though).

Christian

Hi Uwe,

Thanks for the tip. I already have row labels. My problem is, (referring to the 
example below) how can I get R to tell me that upto three clusters, the points 
are clustered around (0,0), (1,0) and (0,1)?

Perhaps it is not even possible, I am not sure.

With regards,
Arnav

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Christian Hennig
Fachbereich Mathematik-SPST/ZMS, Universitaet Hamburg
hennig at math.uni-hamburg.de, http://www.math.uni-hamburg.de/home/hennig/
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