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[MRG] Explain why we are somewhat selective, lower citiation rule of thumb #4131

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[MRG] Explain why we are somewhat selective, lower citiation rule of thumb #4131

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18 changes: 17 additions & 1 deletion doc/faq.rst
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Expand Up @@ -27,21 +27,37 @@ See :ref:`contributing`.
Can I add this new algorithm that I (or someone else) just published?
-------------------------------------------------------------------------
No. As a rule we only add well-established algorithms. A rule of thumb is at least
3 years since publications, 1000+ citations and wide use and usefullness. A
3 years since publications, 200+ citations and wide use and usefullness. A
technique that provides a clear-cut improvement (e.g. an enhanced data
structure or efficient approximation) on a widely-used method will also be
considered for inclusion.
Your implementation doesn't need to be in scikit-learn to be used together
with scikit-learn tools, though. Implement your favorite algorithm
in a scikit-learn compatible way, upload it to github and we will list
it under :ref:`related_projects`.
Also see :selectiveness:


Can I add this classical algorithm from the 80s?
---------------------------------------------------
Depends. If there is a common usecase within the scope of scikit-learn, such
as classification, regression or clustering, where it outperforms methods
that are already implemented in scikit-learn, we will consider it.

.. _selectiveness:

Why are you so selective on what algorithms you include in scikit-learn?
------------------------------------------------------------------------
Code is maintenance cost, and we need to balance the amount of
code we have with the size of the team (and add to this the fact that
complexity scales non linearly with the number of features).
The package relies on core developers using their free time to
fix bugs, maintain code and review contributions.
Any algorithm that is added needs future attention by the developers,
at which point the original author might long have lost interest.
Also see `this thread on the mailing list
<http://sourceforge.net/p/scikit-learn/mailman/scikit-learn-general/thread/CAAkaFLWcBG%2BgtsFQzpTLfZoCsHMDv9UG5WaqT0LwUApte0TVzg%40mail.gmail.com/#msg33104380>`_.

Why did you remove HMMs from scikit-learn?
--------------------------------------------
See :ref:`adding_graphical_models`.
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