[R] Re : Running random forest using different training andtesting schemes

[Liaw, Andy]

The R News article we put out after the first version of the package was released has examples of doing CV.  You can also use the facilities in the caret package (on CRAN) or the MLInterface package (part of Bioconductor, not on CRAN).

randomForest() itself does not do CV per se, but the OOB estimates are very close to what you'd get from CV, without all the work.

Andy

From: Chrysanthi A.
> 
> Hi Pierre,
> 
> Thanks a lot for your help..
> So, using that script, I just separate my data in two parts, 
> right? For
> using as training set the 70 % of the data and the rest as 
> test, should I
> multiply the n with the 0.70 (for this case)?
> 
> Many thanks,
> 
> Chrysanthi
> 
> 
> 
> 2009/4/12 Pierre Moffard <pier.moff at yahoo.fr>
> 
> > Hi Chysanthi,
> >
> > check out the randomForest package, with the function 
> randomForest. It has
> > a CV option. Sorry for not providing you with a lengthier 
> response at the
> > moment but I'm rather busy on a project. Let me know if you 
> need more help.
> >
> > Also, to split your data into two parts- the training and 
> the test set you
> > can do (n the number of data points):
> > n<-length(data[,1])
> > indices<-sample(rep(c(TRUE,FALSE),each=n/2),round(n/2),replace=TRUE)
> > training_indices<-(1:n)[indices]
> > test_indices<-(1:n)[!indices]
> > Then, data[train,] is the training set and data[test,] is 
> the test set.
> >
> > Best,
> > Pierre
> > ------------------------------
> > *De :* Chrysanthi A. <chrysain at gmail.com>
> > *À :* r-help at r-project..org
> > *Envoyé le :* Dimanche, 12 Avril 2009, 17h26mn 59s
> > *Objet :* [R] Running random forest using different 
> training and testing
> > schemes
> >
> > Hi,
> >
> > I would like to run random Forest classification algorithm 
> and check the
> > accuracy of the prediction according to different training 
> and testing
> > schemes. For example, extracting 70% of the samples for 
> training and the
> > rest for testing, or using 10-fold cross validation scheme.
> > How can I do that? Is there a function?
> >
> > Thanks a lot,
> >
> > Chrysanthi.
> >
> >     [[alternative HTML version deleted]]
> >
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> > http://www.R-project.org/posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
> >
> >
> 
> 	[[alternative HTML version deleted]]
> 
> 
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