Re: [R] Document clustering for R

2005-09-13 Thread Christian Hennig
on the outcome. Best, Christian On Mon, 12 Sep 2005, Raymond K Pon wrote: 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

Re: [R] Document clustering for R

2005-09-13 Thread David Ruau
regards, David On Sep 12, 2005, at 21:47, Raymond K Pon wrote: 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

Re: [R] Document clustering for R

2005-09-13 Thread Jari Oksanen
On Mon, 2005-09-12 at 12:47 -0700, Raymond K Pon wrote: 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

Re: [R] Document clustering for R

2005-09-13 Thread Christian Hennig
On Tue, 13 Sep 2005, Jari Oksanen wrote: On Mon, 2005-09-12 at 12:47 -0700, Raymond K Pon wrote: 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

[R] Document clustering for R

2005-09-12 Thread Raymond K Pon
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

Re: [R] Document clustering for R

2005-09-12 Thread Mulholland, Tom
@stat.math.ethz.ch Subject: [R] Document clustering for R 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