Hi Jonathan,

This is very interesting. However, the bar in terms of quality and scope
of scikit-learn is very high. The best way to move forward is to build a
package outside of scikit-learn, possibly in scikit-learn-contrib, and
maybe in the longer run, consider contributing some methods to
scikit-learn.

In terms of what algorithms and method can go in scikit-learn, the
criteria are written here:
https://scikit-learn.org/dev/faq.html#what-are-the-inclusion-criteria-for-new-algorithms
Keep in mind that new methods cannot go in: scikit-learn is only for very
established work.

Cheers,

Gaël

On Tue, Jun 18, 2019 at 02:43:00PM +0200, Jonatan Gøttcke wrote:
> Hi Scikit-Learn developers.

> I’m a masters student in Data Mining and Machine Learning from Denmark. I’m
> finishing my masters in two months time.

> As a part of my thesis I’m comparing a theoretically sound and interesting
> semi-supervised algorithm I came up with, to a bunch of other algorithms. The
> problem was, that all of these basic graph based algorithms didn’t exist in
> scikit-learn, so I’ve implemented them following a scikit-learn like
> ”methodology”, but it’s not 100% compatible. Compatibility will require a bit
> more work, but dependant on how much it is (I don’t know cause I’ve never
> contributed to scikit-learn before), I might have time to put that in before
> the deadline (or I could do it as a part of my PhD, and get that as an easy
> first publication). I’m sure you are more interested in getting the basic 
> graph
> algorithms in there, than my own interesting (and still unpublished) methods  
> 😉
> .


> I would however love to hear if you guys are interested in getting this
> contribution into scikit-learn.?



> Cheers
> Jonatan M. Gøttcke

> CEO @ OpGo
> +45 23 65 01 96




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-- 
    Gael Varoquaux
    Senior Researcher, INRIA 
    http://gael-varoquaux.info            http://twitter.com/GaelVaroquaux
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