Building MATLAB and R interfaces to Ross Quinlan's C5.0 I'm considering building MATLAB and R interfaces to Ross Quinlan's C5.0 (for those not familiar with it, C5.0 is a decision tree algorithm and software package; an extension of C4.5), and I am trying to get a sense of the components I would need to write.
The only documentation I found for C5.0 is here, which is a tutorial for See5 (a Windows interface to C5.0?) . The tar file comes with a Makefile, but no Readme files or any additional documentation. 
From what I read in the tutorial above, C5.0 uses an ASCII-based representation to handle inputs and outputs, and I am also considering building an interface that passes binary data directly between MATLAB or R and C5.0. Is C5.0's data representation used by any other machine-learning/classification software? 
Has anybody tried building a MATLAB or an R interface to ID3, C4.5 or C5.0 before?
Thanks
 A: Interfacing C/C++ code to MATLAB is pretty straightforward, all you have to do is create a MEX gateway function to handle the conversion of parameters and return parameters.  I have experience in making MEX files to do this sort of thing and would be happy to help.
A: UPDATE:
Now on CRAN:
http://cran.r-project.org/web/packages/C50/index.html
ORIGINAL:
We've been working on this for a bit now (starting with Cubist then working on C5.0).
If you'd like to contribute:
https://r-forge.r-project.org/projects/rulebasedmodels/
was created recently and we should be checking the initial code in.
We've had access to the Cubist sources for a while now (but there was an explicit agreement not to link it to other sw) and been debating the different options for incorporating the code, but I thin 
A: The C5.0 (Linux) documentation is at http://rulequest.com/see5-unix.html
A: That sounds like a great idea, especially as the page you link to shows that C5.0 is now under GPL.
I have some experience wrapping C/C++ software to R using Rcpp; I would be happy to help. 
