[R] Cluster on both categorical and numerical data

Gavin Simpson gavin.simpson at ucl.ac.uk
Wed Jun 18 13:43:28 CEST 2008


On Wed, 2008-06-18 at 03:45 -0700, Birgitle wrote:
> You could have a look at library(analogue) , function ?distance

Thanks for the plug Birgit, but (and I say this as the author of
distance), if you just want to compute a dissimilarity matrix using
Gower's coefficient for mixed data, use daisy() from recommended package
cluster because i) as cluster is recommended you don't need to install
further packages, and ii) I haven't done timings, but daisy() will be
much faster, and potentially use less memory, than distance() because
daisy() is in compiled FORTRAN and is doing half the computations that
distance does, which uses a pure R approach.

distance was written with a very specific use-case in mind; of
dissimilarities between rows of matrix A and rows of matrix B. That it
does full dissimilarity matrix computation when provided a single matrix
is a side effect (one that I intend to keep however).

Eventually, distance will move to compiled C code, but that is
immediately below "Learn C" on the ever lengthening TODO list ;-)

> 
> and library (cluster), function ?agnes

I think you mean daisy() here. agnes() is for /clustering/.

G

> 
> B.
> 
> 
> Chua Siang Li wrote:
> > 
> > 
> >    Hello there.  Is there any function in R that can do cluster on a set
> > of
> >    data that has both categorical and numerical variables?  thanks.
> >    siangli
> > ______________________________________________
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> > and provide commented, minimal, self-contained, reproducible code.
> > 
> > 
> 
> 
> -----
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