See the tuneRF() function in the package for an implementation of the strategy recommended by Breiman & Cutler.
BTW, "randomForest" is only for the R package. See Breiman's web page for notice on trademarks. Andy > From: Weiwei Shi > > Hi, > I found the following lines from Leo's randomForest, and I am not sure > if it can be applied here but just tried to help: > > mtry0 = the number of variables to split on at each node. Default is > the square root of mdim. ATTENTION! DO NOT USE THE DEFAULT VALUES OF > MTRY0 IF YOU WANT TO OPTIMIZE THE PERFORMANCE OF RANDOM FORESTS. TRY > DIFFERENT VALUES-GROW 20-30 TREES, AND SELECT THE VALUE OF MTRY THAT > GIVES THE SMALLEST OOB ERROR RATE. > > mdim is the number of predicators. > > HTH, > > weiwei > > On 7/21/05, Liaw, Andy <[EMAIL PROTECTED]> wrote: > > > From: [EMAIL PROTECTED] > > > > > > Hello, > > > > > > I'm trying to find out the optimal number of splits (mtry > > > parameter) for a randomForest classification. The > > > classification is binary and there are 32 explanatory > > > variables (mostly factors with each up to 4 levels but also > > > some numeric variables) and 575 cases. > > > > > > I've seen that although there are only 32 explanatory > > > variables the best classification performance is reached when > > > choosing mtry=80. How is it possible that more variables can > > > used than there are in columns the data frame? > > > > It's not. The code for randomForest.default() has: > > > > ## Make sure mtry is in reasonable range. > > mtry <- max(1, min(p, round(mtry))) > > > > so it silently sets mtry to number of predictors if it's too large. > > As an example: > > > > > library(randomForest) > > randomForest 4.5-12 > > Type rfNews() to see new features/changes/bug fixes. > > > iris.rf = randomForest(Species ~ ., iris, mtry=10) > > > iris.rf$mtry > > [1] 4 > > > > I should probably add a warning in such cases... > > > > Andy > > > > > > > thanks for your help > > > + kind regards, > > > > > > Arne > > > > > > > > > > > > > > > [[alternative HTML version deleted]] > > > > > > ______________________________________________ > > > 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 > > > > > > > > > > > > > ______________________________________________ > > 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 > > > > > -- > Weiwei Shi, Ph.D > > "Did you always know?" > "No, I did not. But I believed..." > ---Matrix III > > > ______________________________________________ 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