2013/1/10 Lars Buitinck <l.j.buiti...@uva.nl>:
> 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'd love to see MARS in the sklearn - is your implementation currently
publicly available?

>
> 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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-- 
Peter Prettenhofer

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