you need to include in your code something like:
tree<-rpart(result~., data, control=rpart.control(xval=10)). this xval=10 is 10-fold CV. Best, Pierre ________________________________ De : Chrysanthi A. <chrys...@gmail.com> À : r-help@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]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. [[alternative HTML version deleted]]
______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.