[R] Can't seem to finish a randomForest.... Just goes and goe s!

[Liaw, Andy]

No, that's not the problem.  You still need to take Bill's and Torsten's
advise.  If the categorical variables (class labels included) are read into
R as factors, then the conversion to integers is automagic:  Factors in R
_are_ integers 1 through the number of levels, with the levels attribute.
randomForest() just takes advantage of that fact.

Andy

> From: David L. Van Brunt, Ph.D.
> 
> D'OH!
> 
> I clearly just needed to Re-RTFM!!!  I had a column still 
> coded as TEXT
> (yup, "Monday", etc), and the randomForest manual by Breiman 
> says they need
> to be numerically coded. Easy recode. I'll try running it 
> RIGHT this time,
> and let you all know how this goes.  Grumble mumble mumble....
> 
> On 4/5/04 1:40, "Bill.Venables at csiro.au" 
> <Bill.Venables at csiro.au> wrote:
> 
> > Alternatively, if you can arrive at a sensible ordering of 
> the levels
> > you can declare them ordered factors and make the 
> computation feasible
> > once again.
> > 
> > Bill Venables.
> > 
> > -----Original Message-----
> > From: r-help-bounces at stat.math.ethz.ch
> > [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of 
> Torsten Hothorn
> > Sent: Monday, 5 April 2004 4:27 PM
> > To: David L. Van Brunt, Ph.D.
> > Cc: R-Help
> > Subject: Re: [R] Can't seem to finish a randomForest.... 
> Just goes and
> > goes!
> > 
> > 
> > On Sun, 4 Apr 2004, David L. Van Brunt, Ph.D. wrote:
> > 
> >> 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
> >                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
> > 
> > This means: there are 2^(30-1) = 536.870.912 possible splits to be
> > evaluated everytime this variable is picked up (minus 
> something due to
> > empty levels). At least the last time I looked at the code, 
> randomForest
> > used an exhaustive search over all possible splits. Try reducing the
> > number of levels to something reasonable (or for a first 
> shot: remove
> > this variable from the learning sample).
> > 
> > Best,
> > 
> > Torsten
> > 
> > 
> >> 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,proximi
> >>> ties=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.
> >> 
> >> ______________________________________________
> >> R-help at stat.math.ethz.ch 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
> >> 
> >> 
> > 
> > ______________________________________________
> > R-help at stat.math.ethz.ch 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
> 
> -- 
> David L. Van Brunt, Ph.D.
> Outlier Consulting & Development
> mailto: <ocd at well-wired.com>
> 
> ______________________________________________
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>