[scikit-learn] Bootstrapping in sklearn

Daniel Saxton daniel.saxton at gmail.com
Thu Sep 20 09:01:36 EDT 2018


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?


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

> 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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