Nagu wrote: > Thank you Uwe Ligges. > > Yes. I had only 50 trees. I come across memory problems running for > big number of trees. Also, I am going to post my next question in a > separate thread, but, it does not harm me to ask here. How do I deal > with large datasets when using randomForests. I have approximately, > datasets of size 500000X650, and R just can't deal with it (pops up > memory allocation problems).
If you want to use all variables at the same time (otherwise use data base access), you will get into troubles with less than 4 Gb of RAM or so, but it might work well on some 32 Gb machine, I guess. > Are there any better ways to deal with > large datasets in R, for example, Splus had something like bigData > library. bigData library only works for some methods such as lm/glm, but not with random forests. Uwe Ligges > > Thank you, > Nagu > > On Mon, Feb 25, 2008 at 1:56 AM, Uwe Ligges > <[EMAIL PROTECTED]> wrote: >> >> >> Nagu wrote: >> > Hi, >> > >> > I am using randomForests for a classification problem. The predict >> > function in the randomForest library, when asked to return the >> > probabilities, has precision of two digits after the decimal. I need >> > at least four digits of precision for the predicted probabilities. How >> > do I achieve this? >> >> For me it gives the desired precision, adapting the >> ?predict.randomForest example: >> >> data(iris) >> set.seed(111) >> ind <- sample(2, nrow(iris), replace = TRUE, prob=c(0.8, 0.2)) >> iris.rf <- randomForest(Species ~ ., data=iris[ind == 1,], ntree = 2000) >> iris.pred <- predict(iris.rf, iris[ind == 2,], type = "prob") >> iris.pred >> >> Maybe you do not have much more than 1000 trees in your bag? >> >> Uwe Ligges >> >> >> >> >> >> >> >> > >> > Thank you, >> > Nagu >> > >> > ______________________________________________ >> > 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. >> ______________________________________________ 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.
