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 On Wed, 4 Feb 2004, Arnav Sheth wrote: > > 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 *********************************************************************** Christian Hennig Fachbereich Mathematik-SPST/ZMS, Universitaet Hamburg [EMAIL PROTECTED], http://www.math.uni-hamburg.de/home/hennig/ ####################################################################### ich empfehle www.boag-online.de ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
