[R] own distance

[Gavin Simpson]

On Tue, 2010-09-07 at 12:16 +0100, Christian Hennig wrote:
> The kmeans function doesn't accept a distance object or distance matrix as 
> input (which you can of course generate from your own definition), but pam 
> in package cluster does. (Note that the term "k-means" refers to cluster 
> mean vectors, which can only computed from a cases*variables data matrix, 
> not from distances alone.)
> 
> There are also several other clustering methods that work with distance 
> matrices as input, see for example hclust, agnes from package cluster or 
> dbscan from package fpc, but if you want something that is 
> conceptually close to k-means, you should probably go for pam.

In addition to Christian's comments, the flexclust package also allows
k-centroids clustering with arbitrary distance coefficients and
computation of centroids.

G

> 
> Best regards,
> Christian
> 
> On Tue, 7 Sep 2010, Karen Sargsyan wrote:
> 
> > Is it possible to implement my own distance and mean for k-means clustering 
> > for any clustering package in R?
> > Just looking for simple way, without creating a new package.
> >
> > karsar
> >
> > ______________________________________________
> > R-help at r-project.org mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
> >
> 
> *** --- ***
> 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
> 
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.

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