Hi Satra,
I can't find the link but there was a discussion some time ago about
creating a scikit-learn-contrib organization on github for this purpose.
Two differences with what you suggest:
1) this wouldn't be a fork, i.e., the intersection with scikit-learn would
be empty
2) we were thinking of creating repositories for different sub-topics
(multilabel classification, kernel approximations, etc)
2) might require too much work in terms of making releases so a global
scikit-learn-contrib might be more realistic.
scikit-learn-contrib would have its own website
http://contrib.scikit-learn.org.
There would still be some work involved for minimal reviewing and
releasing, though.
Mathieu
On Wed, Dec 3, 2014 at 11:56 PM, Satrajit Ghosh <sa...@mit.edu> wrote:
> hi folks,
>
> since this comes up from time to time and i completely understand the
> needed focus and limited resources within scikit-learn, how about the
> following approach:
>
> - let the community (to put zero additional burden on the current
> maintainers) maintain a fork of scikit-learn that provides no guarantees
> other than it is kept upto date with scikit-learn/master.
> - people are welcome to add any algorithms to this (trivial, non-trivial,
> recent)
> - if things prove useful within this branch/fork/labs they can be
> incorporated into the main stream through the current standard PR mechanism
>
> people will use it at their own discretion, but what it would allow is for
> people to have a single place within which to toy with things while still
> maintaining the core benefits of scikit-learn.
>
> with the different kinds of data (types and size) coming online, algorithm
> development has gone in many different directions. some variants are on
> speed/hardware, others on generalizability, yet others on domain specific
> apps, etc.,.. what works in one domain/app may completely fail in another.
>
> the hope here is that this fork would let interested people toy with this
> developmental eco-system as opposed to the stable maintained ecosystem. the
> key advantages of having a fork are that:
> - folks don't have to recreate packaging
> - it brings all the folks who are forking anyway together instead of
> splitting off into forks (multiple forks are harder to use)
> - it makes for increased availability of algorithms that may be useful in
> practice but never makes it out because the world is biased towards
> loudspeakers
> - it doesn't add anything to the current maintainers plates, nor take away
> anything from the main project. perhaps those wishing to add things will
> take it upon themselves to maintain this fork.
> - and if you find that more people are using this fork rather than the
> mainstream (that might tell you something about the current culture of
> science and engineering in practice).
> - there might be fixes that can be incorporated into master coming into
> this fork because more people end up toying within it
> - if this fork goes bust, nobody cares.
>
> you could even call the fork:
>
> scikit-learn-minefield
> scikit-learn-teenage-mutants
> ...
> scikit-learn-labs
>
> cheers,
>
> satra
>
> On Wed, Dec 3, 2014 at 5:25 AM, Joel Nothman <joel.noth...@gmail.com>
> wrote:
>
>>
>> I agree. We should ammend this sentence to say that if the paper is an
>>> clear-cut improvement on top of a very used method, it should be
>>> examinded.
>>
>>
>> Done <http://scikit-learn.org/dev/faq.html>.
>>
>>
>> On 3 December 2014 at 20:07, Gael Varoquaux <
>> gael.varoqu...@normalesup.org> wrote:
>>
>>> On Wed, Dec 03, 2014 at 06:04:58PM +0900, Mathieu Blondel wrote:
>>> > I think 1000 citations is a bit too much to ask. We should probably
>>> > update the FAQ with something more reasonable, like say 200 citations.
>>> > That said, I agree that the citation threshold is just an indicator.
>>> > For example, SAG and AdaGrad, which are considerely considered for
>>> > inclusion, have around 75 and 250 citations currently.
>>>
>>> I agree. We should ammend this sentence to say that if the paper is an
>>> clear-cut improvement on top of a very used method, it should be
>>> examinded.
>>>
>>> > Perhaps scikit-learn needs to strengthen and formalise its support
>>> > for external related projects that adopt its API design to
>>> > implement less established techniques. The listing
>>> > at https://github.com/scikit-learn/
>>> > scikit-learn/wiki/Third-party-projects-and-code-snippets lacks
>>> > glamour, and could be easier to find and navigate.
>>>
>>> > +1
>>>
>>> +1
>>>
>>> > We need to bring this page to the main documentation and make it more
>>> sexy.
>>>
>>> Good with me.
>>>
>>> G
>>>
>>>
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