DOC: add issue and pull request template

ISSUE_TEMPLATE.md

@@ -0,0 +1,39 @@
+Please try to adhere to the guidelines below as much as possible when
+submitting your issue.
+- Verify that your issue is not being currently addressed by other
+[issues](https://github.com/scikit-learn/scikit-learn/issues?q=)
+or [pull requests](https://github.com/scikit-learn/scikit-learn/pulls?q=).
+- If your issue is a usage question or does not potentially require
+changes to the codebase to be solved, then
+[StackOverflow](http://stackoverflow.com/questions/tagged/scikit-learn)
+(using the`[scikit-learn]` tag) or our
+[mailing list](https://lists.sourceforge.net/lists/listinfo/scikit-learn-general)
+may be a better place to bring it up. For more information, see
+[User Questions](http://scikit-learn.org/stable/support.html#user-questions).
+
+If you are submitting a bug issue:
+- Please include your operating system type and version number, as well
+as your Python, scikit-learn, numpy, and scipy versions. This information
+can be found by runnning the following code snippet:
+```
+import platform; print(platform.platform())
+import sys; print("Python", sys.version)
+import numpy; print("NumPy", numpy.__version__)
+import scipy; print("SciPy", scipy.__version__)
+import sklearn; print("Scikit-Learn", sklearn.__version__)
+```
+- Please be specific about what estimators and/or functions are involved
+and the shape of the data, as appropriate; please include a
+[reproducible](http://stackoverflow.com/help/mcve) code snippet
+or link to a [gist](https://gist.github.com). If an exception is raised,
+please provide the traceback.
+- Please ensure all code snippets and error messages are formatted in
+appropriate code blocks.
+See ["Creating and highlighting code blocks"](https://help.github.com/articles/creating-and-highlighting-code-blocks).
+
+If you are submitting an algorithm or feature request:
+- Please verify that the algorithm fulfills our
+[new algorithm requirements](http://scikit-learn.org/stable/faq.html#can-i-add-this-new-algorithm-that-i-or-someone-else-just-published).
+
+Thanks for contributing! Please delete these guidelines before submitting
+your issue.

PULL_REQUEST_TEMPLATE.md

@@ -0,0 +1,33 @@
+Please try to adhere to the guidelines below as much as possible when submitting your pull request.
+
+- Please verify that your code satisfies the
+[code/documentation quality guidelines](http://scikit-learn.org/stable/developers/contributing.html#coding-guidelines).
+- Please prefix the title of your pull request with `[MRG]` if the
+contribution is complete and should be subjected to a detailed review.
+
+- Incomplete contributions should be prefixed `[WIP]` to indicate a work
+in progress (and changed to `[MRG]` when it matures). WIPs may be useful
+to: indicate you are working on something to avoid duplicated work,
+request broad review of functionality or API, or seek collaborators.
+WIPs often benefit from the inclusion of a
+[task list](https://github.com/blog/1375-task-lists-in-gfm-issues-pulls-comments)
+in the PR description.
+- Documentation and high-coverage tests are necessary for enhancements to
+be accepted.
+- If you are adding an enhancement, you may wish to provide evidence for
+its benefit with distinguishing examples in the code and benchmarks
+in the PR discussion.
+- If your pull request addresses an issue, please use the title to describe
+the issue and mention the issue number in the pull request description to
+ensure a link is created to the original issue.
+
+Please be aware that we are a loose team of volunteers so patience is
+necessary; assistance handling other issues is very welcome. We value
+all user contributions, no matter how minor they are. If we are slow to
+review, either the pull request needs some benchmarking, tinkering,
+convincing, etc. or more likely the reviewers are simply busy. In either
+case, we ask for your understanding during the review process.
+For more information, see
+[Why is my PR not getting any attention?](http://scikit-learn.org/dev/faq.html#why-is-my-pull-request-not-getting-any-attention)
+
+Thanks for contributing! Please delete these guidelines before submitting your pull request.

doc/faq.rst

@@ -257,3 +257,21 @@ Deep learning requires a rich vocabulary to define an architecture and the
 use of GPUs for efficient computing. However, neither of these fit within
 the design constraints of scikit-learn. As a result, deep learning is
 currently out of scope for what scikit-learn seeks to achieve.
+
+
+Why is my pull request not getting any attention?
+-------------------------------------------------
+The scikit-learn review process takes a significant amount of time, and
+contributors should not be discouraged by a lack of activity or review on
+their pull request. We care a lot about getting things right
+the first time, as maintenance and later change comes at a high cost.
+We rarely release any "experimental" code, so all of our contributions
+will be subject to high use immediately and should be of the highest
+quality possible initially.
+
+Beyond that, scikit-learn is limited in its reviewing bandwidth; many of the
+reviewers and core developers are working on scikit-learn on their own time.
+If a review of your pull request comes slowly, it is likely because the
+reviewers are busy. We ask for your understanding and request that you
+not close your pull request or discontinue your work solely because of
+this reason.