[R] Dump decision trees of randomForest object

[Liaw, Andy]

If you just want to be able to use the trained RF model in some future R session for prediction on new data, just use save() to save the RF object, and load() it back in the future.

If you really want to write your own low-level code for prediction, you can take a look at the predictRegTree() function in randomForest/src/regTree.c (the last function in that file).  It shows how prediction is done using the data structure from a randomForest object.

Andy 

From: Christian Sturz 
> 
> I've tried the getTree() function and printed a decision tree 
> with print().
> However, it seems to me that it's hard to parse this 
> representation and
> translate it into equivalent if-then-else C constructs. Are 
> there no other
> ways to dump the trees into a more hierarchical form?
> 
> What do you exactly mean with the prediction in the source package?
> 
> Maybe what I wanted to ask goes in the same direction: let's 
> say I've learned
> a random forest model from a learning set. Now I would like 
> to use it in the
> future as classifier to predict new examples. How can this be 
> done? Can I save
> a learned model and than invoke R with new examples and 
> applied them to
> the saved model without again training the random forest from 
> scratch? If so,
> please give me some hints how to do that.
> 
> Regards,
> Chris
> 
> -------- Original-Nachricht --------
> > Datum: Thu, 9 Oct 2008 14:38:44 -0400
> > Von: "Liaw, Andy" <andy_liaw at merck.com>
> > An: "Christian Sturz" <linuxkaffee at gmx.net>, r-help at r-project.org
> > Betreff: RE: [R] Dump decision trees of randomForest object
> 
> > See the getTree() function in the package.  Also, the source package
> > contains C code that does the prediction that you may be 
> able to work
> > from.
> > 
> > Andy 
> > 
> > From: Christian Sturz
> > > 
> > > Hi,
> > > 
> > > I'm using the package randomForest to generate a classifier 
> > > for the exemplary
> > > iris data set:
> > > 
> > > data(iris)
> > > iris.rf<-randomForest(Species~.,iris)
> > > 
> > > Is it possible to print all decision trees in the 
> generated forest?
> > > If so, can the trees be also written to disk?
> > > 
> > > What I actually need is to translate the decision trees in a 
> > > random forest
> > > into equivalent C++ if-then-else constructs to integrate 
> them in a C++
> > > project. Have this been done in the past and are there already any
> > > implemented approaches/parser for that?
> > > 
> > > Cheers,
> > > Chris
> > > --
> > > 
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