Hi Tim, As far as I know you can not weigh predictors (and I believe that you really should not). You may weigh classes (and, in a sense, cases), but this is an entirely different issue.
--- On Wed, 5/8/09, "Häring, Tim (LWF)" <tim.haer...@lwf.bayern.de> wrote: > From: "Häring, Tim (LWF)" <tim.haer...@lwf.bayern.de> > Subject: [R] feature weighting in randomForest > To: r-help@r-project.org > Received: Wednesday, 5 August, 2009, 5:59 PM > Hello ! > > I´m using randomForest for classifacation problems. My > dataset has 21.000 observations and 96 predictors. I know > that some predictors of my dataset have more influence to > classify my data than others. > Therefore I would like to know if there is a way to weight > my predictors. I know that for constructing each tree in a > forest the most influencial predictor is used for > partitioning the data. But maybe it would have an effect if > I weight my predictors. > > Thanks in advance > > TIM > > ----------------------------------------------------------------------------------- > > Tim Haering > Bavarian State Institute of Forest Research > Department of Forest Ecology > Am Hochanger 11 > D-85354 Freising > > http://www.lwf.bayern.de > > ______________________________________________ > 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.
