[R] ariable Importance Measure in Package RandomForest

[Liaw, Andy]

The randomForest package is based on Breiman & Cutler's original code,
which grows trees using the CART algorithm.  The Gini criterion for
splitting nodes is hard-coded in the Fortran.  If you want info gain as
measure of variable importance, you should be growing trees using that
as the splitting criterion.  It may (or may not) be possible with the
party package, as that's a more modular design.  That's something you
can look into.

Best,
Andy 

From:  Uwe Ligges
> 
> Given you do not want to touch the randomForest 
> implementation itself, 
> the answer is "no, there is no particular function to do it 
> in package 
> randomForest. More particular:
> 
> ?randomForest tells us that a value "importance" is returned 
> that is `a 
> matrix with nclass + 2 (for classification) or two (for regression) 
> columns. For classification, the first nclass columns are the 
> class-specific measures computed as mean descrease in accuracy. The 
> nclass + 1st column is the mean descrease in accuracy over 
> all classes. 
> The last column is the mean decrease in Gini index. For 
> Regression, the 
> first column is the mean decrease in accuracy and the second the mean 
> decrease in MSE. If importance=FALSE, the last measure is 
> still returned 
> as a vector.'
> 
> So as far as I can see, you would have to change randomForest itself 
> that has to return some relevant values in order to calculate the 
> criterion(s) you are interested in.
> 
> Best wishes,
> Uwe Ligges
> 
> 
> 
> 
> 
> 
> linuxkaffee at gmx.net wrote:
> > Hi,
> > 
> > I've a question about the RandomForest package.
> > 
> > The package allows the extraction of a variable importance 
> measure. As far as
> > I could see from the documentation, the computation is 
> based on the Gini index.
> > 
> > Do you know if this extraction can be also based on other 
> criteria? In particular,
> > I'm interested in the info gain criterion.
> > 
> > Best regards,
> > Chris
> > --
> > 
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