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[MRG] DOC Update README.rst (#301)
* Update README.rst Minor shortening of url * Update CONTRIBUTING.md -Clean up urls -Made explicit HTTPS calls
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CONTRIBUTING.md

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Contributing code
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=================
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This guide is adapted from (scikit-learn)[https://github.com/scikit-learn/scikit-learn/blob/master/CONTRIBUTING.md]
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This guide is adapted from [scikit-learn](https://github.com/scikit-learn/scikit-learn/blob/master/CONTRIBUTING.md).
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How to contribute
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-----------------
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review. This will send an email to the committers.
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(If any of the above seems like magic to you, then look up the
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[Git documentation](http://git-scm.com/documentation) on the web.)
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[Git documentation](https://git-scm.com/documentation) on the web.)
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Contributing Pull Requests
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--------------------------
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following rules before submitting:
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- Verify that your issue is not being currently addressed by other
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[issues](https://github.com/scikit-learn-contrib/imbalanced-learn/issues?q=)
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or [pull requests](https://github.com/scikit-learn-contrib/imbalanced-learn/pulls?q=).
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[issues](https://github.com/scikit-learn-contrib/imbalanced-learn/issues)
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or [pull requests](https://github.com/scikit-learn-contrib/imbalanced-learn/pulls).
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- Please ensure all code snippets and error messages are formatted in
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appropriate code blocks.
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- Please be specific about what estimators and/or functions are involved
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and the shape of the data, as appropriate; please include a
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[reproducible](http://stackoverflow.com/help/mcve) code snippet
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[reproducible](https://stackoverflow.com/help/mcve) code snippet
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or link to a [gist](https://gist.github.com). If an exception is raised,
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please provide the traceback.
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README file in the doc/ directory for more information.
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For building the documentation, you will need
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[sphinx](http://sphinx.pocoo.org/),
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[matplotlib](http://matplotlib.sourceforge.net/), and
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[pillow](http://pillow.readthedocs.org/en/latest/).
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[sphinx](http://sphinx-doc.org),
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[matplotlib](https://matplotlib.org), and
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[pillow](https://pillow.readthedocs.io).
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When you are writing documentation, it is important to keep a good
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compromise between mathematical and algorithmic details, and give

README.rst

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The development of this scikit-learn-contrib is in line with the one
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of the scikit-learn community. Therefore, you can refer to their
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`Development Guide
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<http://scikit-learn.org/stable/developers/index.html>`_.
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<http://scikit-learn.org/stable/developers>`_.
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About
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-----
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volume = {18},
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number = {17},
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pages = {1-5},
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url = {http://jmlr.org/papers/v18/16-365.html}
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url = {http://jmlr.org/papers/v18/16-365}
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}
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Most classification algorithms will only perform optimally when the number of
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The different algorithms are presented in the sphinx-gallery_.
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.. _sphinx-gallery: http://contrib.scikit-learn.org/imbalanced-learn/auto_examples/index.html
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.. _sphinx-gallery: http://contrib.scikit-learn.org/imbalanced-learn/auto_examples
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References:

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