As you mentioned popular methods from scikit-learn-contrib could be
promoted to scikit-learn.
Conversely, methods which became obsolete in scikit-learn could move to
scikit-learn-contrib to lower the maintenance burden.
Mathieu
On Thu, Dec 4, 2014 at 12:26 AM, Mathieu Blondel <math...@mblondel.org>
wrote:
> 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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