Hi Andy
Great and thanks a lot! Yes, it is the package from Prof. Wehrens. So I
just run the PLS like a Logistic Regression, coding the endogenous
variable as binary.
So no need of specifying a binary-link function (as we have to when
using glm)?
And yes of course: I need the LVs which give the best error rate. What
do you mean by "discretize the predictions in {0, 1}"? Does this mean
I
assign a prediction either a 0 (if predicted values <=0.5) or a 1 if the
predicted value is >0.5?
I need to dive into the package tomorrow, so that I better understand
the material, but is there any way of calculating e.g. a leaving-one-out
cross-validation error?
Thanks and best regards
Christoph
On Wed, 2003-09-10 at 21:50, Liaw, Andy wrote:> Do you mean the pls.pcr package by Prof. Wehrens? This is what I do:
>
> o Code the two groups as 0s and 1s (numeric, not factor).
>
> o Run PLS as usual. Cases with predicted values > 0.5 get
> classified as 1s, otherwise as 0s.
>
> o Note that you need to modify the code inside the mvr()
> function a bit if you want to use the built-in selection
> of number of LVs: It selects the number that gives the
> best MSE, but what you really want is the number that
> gives the best error rate. One trick is to discretize
> the predictions in {0, 1}, then the "MSE" will be error
> rate.
>
> There are better ways to do this, but this works fairly well.
>
> HTH,
> Andy
>
> > -----Original Message-----
> > From: Christoph Lehmann [mailto:christoph.lehmann at gmx.ch]
> > Sent: Wednesday, September 10, 2003 1:38 PM
> > To: R-help at stat.math.ethz.ch
> > Subject: [R] PLS LDA
> >
> >
> > Dear R experts
> > I saw and downloaded the fresh pls package for R. Is there
> > any way of using this pls package for PLS discriminant
> > analysis? If not, is there any other package available.
> >
> > I need a way of classifying objects into e.g. two groups,
> > where nbr_observations << nbr_variables
> >
> > many thanks for your kind help
> >
> > Christoph
> > --
> > Christoph Lehmann <christoph.lehmann at gmx.ch>
> >
> > ______________________________________________
> > R-help at stat.math.ethz.ch mailing list
> > https://www.stat.math.ethz.ch/mailman/listinfo> /r-help
> >
>
>
------------------------------------------------------------------------------
> Notice: This e-mail message, together with any attachments,...{{dropped}}
>
> ______________________________________________
> R-help at stat.math.ethz.ch mailing list
> https://www.stat.math.ethz.ch/mailman/listinfo/r-help
--
Christoph Lehmann <christoph.lehmann at gmx.ch>