[scikit-learn] Bootstrapping in sklearn

[Daniel Saxton]

Olivier,

I got in touch with Constantine from the scikits-bootstrap package and he's
interested in merging the two projects.  If we were to get some
documentation together, do you feel that there is potential for inclusion
as an sklearn-contrib package?  I believe we would have most of the other
requirements (testing, continuous integration, etc.), but is there anything
else that you feel is missing?

Thanks,
Daniel

On Tue, Sep 18, 2018 at 2:42 AM Olivier Grisel <olivier.grisel at 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
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