Great, I went ahead and contacted Constantine. Documentation was actually the next thing that I wanted to work on, so hopefully he and I can put something together.
Thanks for the help. On Tue, Sep 18, 2018 at 2:42 AM Olivier Grisel <olivier.gri...@ensta.org> wrote: > This looks like a very useful project. > > There is also scikits-bootstraps [1]. Personally I prefer the flat package > namespace of resample (I am not a fan of the 'scikits' namespace package) > but I still think it would be great to contact the author to know if he > would be interested in joining efforts. > > What currently lacks from both projects is a good sphinx-based > documentation that explains in a couple of paragraphs with examples what > are the different non-parametric inference methods, what are the pros and > cons for each of them (sample complexity, computation complexity, kinds of > inference, bias, theoretical asymptotic results, practical discrepancies > observed in the finite sample setting, assumptions made on the distribution > of the data...) and ideally the doc would have reference to examples (using > sphinx-gallery) that would highlight the behavior of the tools in both > nominal and pathological cases. > > [1] https://github.com/cgevans/scikits-bootstrap > > -- > Olivier > _______________________________________________ > scikit-learn mailing list > scikit-learn@python.org > https://mail.python.org/mailman/listinfo/scikit-learn >
_______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
