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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