2013/1/10 Jason Rudy <ja...@clinicast.net>
> I'm working on an implementation of MARS [1] that I'd like to share, and
it seems like sklearn would be a good place for it. The MARS algorithm is
currently available as part of the R package "earth" and is one of the only
reasons I still use R. Would sklearn be a good place for such an
algorithm? Are there any guidelines or procedures I should be aware of
before contributing?
I guess that would fit in scikit-learn, but I'm not an expert on fancy
regression analysis. The contributor guidelines can be found here:
https://github.com/scikit-learn/scikit-learn/blob/master/CONTRIBUTING.md
In addition, make sure that (1) you own the code or your employer is ok
with you publishing it under BSD license terms, and (2) apparently MARS is
a trademark so call the estimator something else, like EarthRegressor or
MARegressionSplines.
--
Lars Buitinck
Scientific programmer, ILPS
University of Amsterdam
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