10-fold cross-validation is easily done at R level: there is generic code
in MASS, the book knn was written to support.
knn and lda have options for leave-one-out cross-validation just because
there are compuiationally efficient algorithms for those cases.
On Tue, 6 Jun 2006, Liaw, Andy wrote:
> You might want to check out the function tune.knn() in the e1071 package.
>
> Andy
>
> _____
>
> From: [EMAIL PROTECTED] on behalf of Tim Smith
> Sent: Tue 6/6/2006 8:29 PM
> To: r-help@stat.math.ethz.ch
> Subject: [R] knn - 10 fold cross validation [Broadcast]
>
>
>
> Hi,
>
> I was trying to get the optimal 'k' for the knn. To do this I was using
> the following function :
>
>
> knn.cvk <- function(datmat, cl, k = 2:9) {
> datmatT <- (datmat)
> cv.err <- cl.pred <- c()
>
> for (i in k) {
> newpre <- as.vector(knn.cv(datmatT, cl, k = i))
> cl.pred <- cbind(cl.pred, newpre)
> cv.err <- c(cv.err, sum(cl != newpre))
>
> }
> k0 <- k[which.min(cv.err)]
> print(k0)
> return(k0)
> }
>
>
> However, the knn.cv function does a 'leave one out' cross validation. I
> checked the documentation to see if I could change this, but it appears that
> I cannot. Since I have large datasets, I would like to do 10 fold cross
> validation, instead of the 'leave one out'.
>
>
> Is there some other function that I can use that will give me a 10 fold
> cross validation for KNN ?
>
> many thanks.
>
> __________________________________________________
>
>
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help@stat.math.ethz.ch mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> <https://stat.ethz.ch/mailman/listinfo/r-help>
> PLEASE do read the posting guide!
> http://www.R-project.org/posting-guide.html
> <http://www.R-project.org/posting-guide.html>
>
> ______________________________________________
> R-help@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
>
--
Brian D. Ripley, [EMAIL PROTECTED]
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595
______________________________________________
R-help@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
