Hi Chris. Thanks for replying. I want to take the pruned list of subtrees, and select the final tree from this list using a bootstrap technique (rather than cross validation). I think, and I could be wrong, that bagging takes a bunch of bootstrap samples, grows one tree per boostrap sample and then combines the estimates, but this is not want I want to do. I hope this is clearer. It is difficult to describe these things with eamil. Cheers Fiona > Fiona Callaghan wrote: >> I was wondering if someone could help me with an rpart problem. I can >> see >> that cross-validation is the default for tree selection in rpart -- has >> a >> bootstrap method been implemented anywhere? I think this is a different >> thing to 'bagging' or 'boosting' -- I still want 'one' tree at the end, >> I >> just would like it chosen using a bootstrap method. Any ideas??? > > Hi Fiona, > > I'm not sure if I understand you correctly. > To get one single rpart tree trained on one bootstrap sample, try > bagging() from the 'ipred' package and set nbagg=1. > > Bye, > Chris > >
-- Fiona Callaghan, MA MS A432 Crabtree Hall Department of Biostatistics Graduate School of Public Health University of Pittsburgh Phone 412 624 3063 ______________________________________________ [email protected] 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.
