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

Stephen Henderson s.henderson@ucl.ac.uk
Fri, 24 Jan 2003 13:08:23 -0000


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

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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