[R] Help predicting random forest-like data
Uwe Ligges
ligges at statistik.tu-dortmund.de
Tue Apr 10 23:10:09 CEST 2012
On 10.04.2012 23:03, Katharine Miller wrote:
> Hi,
>
> I have been using some code for multivariate random forests. The output
> from this code is a list object with all the same values as from
> randomForest, but the model object is, of course, not of the class
> randomForest. So, I was hoping to modify the code for predict.randomForest
> to work for predicting the multivariate model to new data. This is my
> first attempt at modifying code from a library ....and I am afraid I am
> already out of my depth. I was able to access the predict.randomForest
> code, and extract the relevant information, but this code it calls a
> function regForest that I cannot seem to find/access.
>
> Another blog gave the following instructions for accessing the regForest
> function: "Download the source package of randomForest, extract the tar.gz
> and look in the src directory. In rf.c you will see the function
> classForest (and for regression look at regForest in regrf.c)."
>
> I downloaded the randomForest tar.gz and extracted it using 7 zip, but I do
> not get an src directory. I only get a gz file called
> randomForest_4.6-6.tar.gz.
Then you have not extracted it. 7zip should be capable, but installing
Rtools and using
tar xfz randomForest_4.6-6.tar.gz
from the operating system's shell should do as documented.
Uwe Ligges
The randomForest library already is installed
> in R, so I looked in the main src directory in R, but there isn't any rf.c
> or other randomForest related information there. I am sure I am making
> some easy to remedy mistake, but I can't figure it out.
>
> Any assistance would be greatly appreciated.
>
> - Katharine
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help at 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.
More information about the R-help
mailing list