[R] which function to use to do classification
Liaw, Andy
andy_liaw at merck.com
Thu Mar 30 01:52:18 CEST 2006
In addition to Brian's comment, Gordon's book, already in 2nd edition, is
all about clustering, but the title is simply `Classification'.
Andy
From: Sean Davis
>
> We have to be careful here. Classification (which is the
> terminology that the original poster used) is NOT the same as
> clustering, although the two are often confused. If the
> original poster wants to do clustering and examine the
> results for the presence of three clusters, that is fine and
> there are many methods for clustering that could be used.
> However, classification will require a different set of
> tools. If the clustering tools already pointed out are not
> doing what is needed (that is, that Cao actually is
> interested in clustering and not classification), then
> perhaps a further explanation of what the problem would help clarify.
>
> Sean
>
>
> On 3/29/06 1:46 AM, "Jacques VESLOT" <jacques.veslot at cirad.fr> wrote:
>
> > try this (suppose mat is your matrix):
> >
> > hc <- hclust(dist(mat,"manhattan"), "ward")
> > plot(hc, hang=-1)
> > (x <- identify(hc)) # rightclick to stop
> > cutree(hc, 3)
> >
> > km<- kmeans(mat, 3)
> > km$cluster
> > km$centers
> >
> > pam(daisy(mat, metric = "manhattan"), k=3, diss=T)$clust
> >
> >
> >
> > Baoqiang Cao a écrit :
> >
> >> Thanks!
> >> I tried kmeans, the results is not very positive. Anyway, thanks
> >> Jacques! Please let me know if you have any other thoughts!
> >>
> >> Best regards,
> >> Baoqiang Cao
> >>
> >> ======= At 2006-03-29, 00:08:44 you wrote: =======
> >>
> >>
> >>
> >>> if you want to classify rows or columns, read:
> >>> ?hclust
> >>> ?kmeans
> >>> library(cluster)
> >>> ?pam
> >>>
> >>>
> >>> Baoqiang Cao a écrit :
> >>>
> >>>
> >>>
> >>>> Dear All,
> >>>>
> >>>> I have a data, suppose it is an N*M matrix data. All I
> want is to
> >>>> classify it into, let see, 3 classes. Which method(s) do
> you think
> >>>> is(are) appropriate for this purpose? Any reference will be
> >>>> welcome! Thanks!
> >>>>
> >>>> Best,
> >>>> Baoqiang Cao
> >>>>
> >>>>
> >>>>
> >>>>
> -------------------------------------------------------------------
> >>>> -----
> >>>>
> >>>> ______________________________________________
> >>>> R-help at stat.math.ethz.ch mailing list
> >>>> https://stat.ethz.ch/mailman/listinfo/r-help
> >>>> PLEASE do read the posting guide!
> >>>> http://www.R-project.org/posting-guide.html
> >>>>
> >>>>
> >>>>
> >>> .
> >>>
> >>>
> >>
> >> = = = = = = = = = = = = = = = = = = = =
> >>
> >> Baoqiang Cao
> >> caobg at email.uc.edu
> >> 2006-03-29
> >>
> >>
> >>
> >>
> >
> > ______________________________________________
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> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide!
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>
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