[BioC] How to do k-fold validation using SVM

[Torsten Hothorn]

On Fri, 24 Jan 2003, Stephen Henderson wrote:

> Is there a simple??? way to do a gene/feature selection for each round of
> cross validation-- using the ipred errorest function?
>

by supplying your own `model' argument / function to `errorest':

model <- function(formula, data, ....) {
  # 1) evaluate the formula, so you end up with
  # y (classes) and X (matrix of expression values, I guess)
  # look at any of the foo.formula methods or errorest.data.frame, for
  # example
  ...
  # 2) perform the gene / feature selection, so you endup with a
  # subset of features from X, say Xsub

  # 3) and finally call your favorite classifier and return its output

  randomForests(y ~ ., data=Xsub)
}

then `cv.factor' calls `model' for each fold. No idea if this is "simple"
(no. 1 probably isn't) but relying on the `model(formula, data, ...)'
interface makes it flexible. You
can pass more arguments to `model' by "...": for example the number of
genes to be selected...

Hope this helps,

Torsten

> I do not mean select some set of genes and then do a cv on this subset, but
> rather to reselect the subset for each fold?
>
> I had written a rather long winded loop previous to this posting (had missed
> ipred) but now wonder if there is a shortcut?
>
> -----Original Message-----
> From: Torsten Hothorn [mailto:Torsten.Hothorn@rzmail.uni-erlangen.de]
> Sent: Friday, January 24, 2003 7:13 AM
> To: Adaikalavan Ramasamy
> Cc: Song, Guangchun; bioconductor@stat.math.ethz.ch
> Subject: RE: [BioC] How to do k-fold validation using SVM
>
> On Fri, 24 Jan 2003, Adaikalavan Ramasamy wrote:
>
> > You might want to use the function svm() in the e1071 library with the
> > option 'cross'.
> >
> > Or you can manually break the dataset into k subsets and write a loop.
> > This might be better if you prefer to do stratified sampling for the
> > fold rather than random sampling.
> >
>
> or you can use the "errorest" function in the ipred-package (see R News
> 2(2) for examples)
>
> Torsten
>
> > -----Original Message-----
> > From: Song, Guangchun [mailto:Guangchun.Song@stjude.org]
> > Sent: Friday, January 24, 2003 7:35 AM
> > To: bioconductor@stat.math.ethz.ch
> > Subject: [BioC] How to do k-fold validation using SVM
> >
> >
> >
> > Did anyone know how to do the k-fold validation on the training data set
> > by SVM?
> >
> > Thanks.
> >
> >
> > Guangchun
> >
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