Playing with randomForest, samples run fine. But on real data, no go. Here's the setup: OS X, same behavior whether I'm using R-Aqua 1.8.1 or the Fink compile-of-my-own with X-11, R version 1.8.1.
This is on OS X 10.3 (aka "Panther"), G4 800Mhz with 512M physical RAM. I have not altered the Startup options of R. Data set is read in from a text file with "read.table", and has 46 variables and 1,855 cases. Trying the following: The DV is categorical, 0 or 1. Most of the IV's are either continuous, or correctly read in as factors. The largest factor has 30 levels.... Only the DV seems to need identifying as a factor to force class trees over regresssion: >Mydata$V46<-as.factor(Mydata$V46) >Myforest.rf<-randomForest(V46~.,data=Mydata,ntrees=100,mtry=7,proximities=FALSE , importance=FALSE) 5 hours later, R.bin was still taking up 75% of my processor. When I've tried this with larger data, I get errors referring to the buffer (sorry, not in front of me right now). Any ideas on this? The data don't seem horrifically large. Seems like there are a few options for setting memory size, but I'm not sure which of them to try tweaking, or if that's even the issue. ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
