[R] cluster analysis and supervised classification: an alternative to knn1?

[abanero]

Hi Ulrich,
 I'm studying the principles of Affinity Propagation and I'm really glad to
use your package (apcluster) in order to cluster my data.  I have just an
issue to solve..

If I apply the funcion: apcluster(sim) 

where sim is the matrix of dissimilarities, sometimes I encounter the
warning message:

"Algorithm did not converge. Turn on details
and call plot() to monitor net similarity. Consider
increasing maxits and convits, and, if oscillations occur
also increasing damping factor lam."
 
with  too high number of clusters.
 
I thought to solve the problem setting the argument "p" of the function
apcluster() to mean(PreferenceRange(sim)):


apcluster(sim, p=mean(preferenceRange(sim)))

and actually it seems to be a good solution because I don't receive any
warning message and the number of cluster is slower.

Do you think it's a good solution? I submitt that I have to use apcluster()
in an automatic procedure so I can't manipulate directly the arguments of
the funcion.

Thanks in advance.
Giuseppe
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