Document clustering for R

If you are able to implement the computation of the distance matrix, you
can use methods such as pam, agnes and hclust, which operate on
dissimilarity matrices of any kind. You may also perform a
multidimensional scaling with isoMDS, sammon or cmdscale and use any
clustering algorithm for n*p data on the outcome.

Best,
Christian

I'm working on a project related to document clustering. I know that R
has clustering algorithms such as clara, but only supports two distance
metrics: euclidian and manhattan, which are not very useful for
clustering documents. I was wondering how easy it would be to extend the
clustering package in R to support other distance metrics, such as
cosine distance, or if there was an API for custom distance metrics.

Best regards,
Raymond Pon
pon3 at llnl.gov
x43062

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*** --- ***
Christian Hennig
University College London, Department of Statistical Science
Gower St., London WC1E 6BT, phone +44 207 679 1698
chrish at stats.ucl.ac.uk, www.homepages.ucl.ac.uk/~ucakche