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MNT Converting http to https (scikit-learn#12277)
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‎CONTRIBUTING.md

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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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For building the documentation, you will need
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[sphinx](http://sphinx.pocoo.org/),
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[matplotlib](http://matplotlib.org/), and
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[pillow](http://pillow.readthedocs.io/en/latest/).
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[matplotlib](https://matplotlib.org/), and
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[pillow](https://pillow.readthedocs.io/en/latest/).
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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

‎ISSUE_ 10000 TEMPLATE.md

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<!--
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If your issue is a usage question, submit it here instead:
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- StackOverflow with the scikit-learn tag: http://stackoverflow.com/questions/tagged/scikit-learn
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- StackOverflow with the scikit-learn tag: https://stackoverflow.com/questions/tagged/scikit-learn
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- Mailing List: https://mail.python.org/mailman/listinfo/scikit-learn
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For more information, see User Questions: http://scikit-learn.org/stable/support.html#user-questions
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-->

‎README.rst

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- Mailing list: https://mail.python.org/mailman/listinfo/scikit-learn
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- IRC channel: ``#scikit-learn`` at ``webchat.freenode.net``
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- Stack Overflow: http://stackoverflow.com/questions/tagged/scikit-learn
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- Stack Overflow: https://stackoverflow.com/questions/tagged/scikit-learn
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- Website: http://scikit-learn.org
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Citation

‎appveyor.yml

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global:
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# SDK v7.0 MSVC Express 2008's SetEnv.cmd script will fail if the
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# /E:ON and /V:ON options are not enabled in the batch script interpreter
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# See: http://stackoverflow.com/a/13751649/163740
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# See: https://stackoverflow.com/a/13751649/163740
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CMD_IN_ENV: "cmd /E:ON /V:ON /C .\\build_tools\\appveyor\\run_with_env.cmd"
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WHEELHOUSE_UPLOADER_USERNAME: sklearn-appveyor
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WHEELHOUSE_UPLOADER_SECRET:
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Where-Object pullRequestId -eq $env:APPVEYOR_PULL_REQUEST_NUMBER)[0].buildNumber) { `
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throw "There are newer queued builds for this pull request, failing early." }
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# Install Python (from the official .msi of http://python.org) and pip when
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# Install Python (from the official .msi of https://python.org) and pip when
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# not already installed.
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- "powershell ./build_tools/appveyor/install.ps1"
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- "SET PATH=%PYTHON%;%PYTHON%\\Scripts;%PATH%"

‎benchmarks/bench_plot_nmf.py

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----------
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C.-J. Lin. Projected gradient methods for non-negative matrix
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factorization. Neural Computation, 19(2007), 2756-2779.
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http://www.csie.ntu.edu.tw/~cjlin/nmf/
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https://www.csie.ntu.edu.tw/~cjlin/nmf/
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"""
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WtX = safe_sparse_dot(W.T, X)
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WtW = np.dot(W.T, W)

‎benchmarks/bench_plot_randomized_svd.py

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----------
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(1) Finding structure with randomness: Stochastic algorithms for constructing
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approximate matrix decompositions
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Halko, et al., 2009 http://arxiv.org/abs/arXiv:0909.4061
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Halko, et al., 2009 https://arxiv.org/abs/0909.4061
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(2) A randomized algorithm for the decomposition of matrices
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Per-Gunnar Martinsson, Vladimir Rokhlin and Mark Tygert
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MAX_MEMORY = np.int(2e9)
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# The following datasets can be dowloaded manually from:
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# CIFAR 10: http://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz
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# CIFAR 10: https://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz
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# SVHN: http://ufldl.stanford.edu/housenumbers/train_32x32.mat
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CIFAR_FOLDER = "./cifar-10-batches-py/"
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SVHN_FOLDER = "./SVHN/"

‎build_tools/appveyor/install.ps1

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# Sample script to install Python and pip under Windows
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# Authors: Olivier Grisel, Jonathan Helmus, Kyle Kastner, and Alex Willmer
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# License: CC0 1.0 Universal: http://creativecommons.org/publicdomain/zero/1.0/
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# License: CC0 1.0 Universal: https://creativecommons.org/publicdomain/zero/1.0/
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$MINICONDA_URL = "http://repo.continuum.io/miniconda/"
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$MINICONDA_URL = "https://repo.continuum.io/miniconda/"
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$BASE_URL = "https://www.python.org/ftp/python/"
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$GET_PIP_URL = "https://bootstrap.pypa.io/get-pip.py"
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$GET_PIP_PATH = "C:\get-pip.py"

‎build_tools/appveyor/run_with_env.cmd

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::
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:: More details at:
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:: https://github.com/cython/cython/wiki/64BitCythonExtensionsOnWindows
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:: http://stackoverflow.com/a/13751649/163740
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:: https://stackoverflow.com/a/13751649/163740
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::
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:: Author: Olivier Grisel
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:: License: CC0 1.0 Universal: http://creativecommons.org/publicdomain/zero/1.0/
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:: License: CC0 1.0 Universal: https://creativecommons.org/publicdomain/zero/1.0/
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::
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:: Notes about batch files for Python people:
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‎build_tools/travis/after_success.sh

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#!/bin/bash
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# This script is meant to be called by the "after_success" step defined in
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# .travis.yml. See http://docs.travis-ci.com/ for more details.
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# .travis.yml. See https://docs.travis-ci.com/ for more details.
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# License: 3-clause BSD
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‎build_tools/travis/install.sh

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#!/bin/bash
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# This script is meant to be called by the "install" step defined in
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# .travis.yml. See http://docs.travis-ci.com/ for more details.
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# .travis.yml. See https://docs.travis-ci.com/ for more details.
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# The behavior of the script is controlled by environment variabled defined
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# in the .travis.yml in the top level folder of the project.
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‎build_tools/travis/test_script.sh

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#!/bin/bash
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# This script is meant to be called by the "script" step defined in
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# .travis.yml. See http://docs.travis-ci.com/ for more details.
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# .travis.yml. See https://docs.travis-ci.com/ for more details.
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# The behavior of the script is controlled by environment variabled defined
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‎build_tools/windows/windows_testing_downloader.ps1

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$AdminKey = "HKLM:\SOFTWARE\Microsoft\Active Setup\Installed Components\{A509B1A7-37EF-4b3f-8CFC-4F3A74704073}"
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‎doc/about.rst

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`API design for machine learning software: experiences from the scikit-learn
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project <http://arxiv.org/abs/1309.0238>`_, Buitinck *et al.*, 2013.
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project <https://arxiv.org/abs/1309.0238>`_, Buitinck *et al.*, 2013.
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`NYU Moore-Sloan Data Science Environment <http://cds.nyu.edu/mooresloan/>`_
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`NYU Moore-Sloan Data Science Environment <https://cds.nyu.edu/mooresloan/>`_
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funded Andreas Mueller (2014-2016) to work on this project. The Moore-Sloan Data Science
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`The University of Sydney <https://sydney.edu.au/>`_ funds Joel Nothman since July 2017.
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`The Labex DigiCosme <https://digicosme.lri.fr>`_ funded Nicolas Goix (2015-2016),
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Tom Dupré la Tour (2015-2016 and 2017-2018), Mathurin Massias (2018-2019) to work part time
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- 2015 - `Raghav RV <https://github.com/raghavrv>`_, Wei Xue
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- 2016 - `Nelson Liu <http://nelsonliu.me>`_, `YenChen Lin <http://yclin.me>`_
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- 2016 - `Nelson Liu <http://nelsonliu.me>`_, `YenChen Lin <https://yclin.me/>`_
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It also provided funding for sprints and events around scikit-learn. If
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<http://www.debian.org>`_ packaging and contributions is supported by
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<https://www.debian.org/>`_ packaging and contributions is supported by
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`Dr. James V. Haxby <http://haxbylab.dartmouth.edu/>`_ (`Dartmouth
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College <https://pbs.dartmouth.edu/>`_).
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the *Paypal* button below or the `NumFOCUS Donations Page <https://www.numfocus.org/support-numfocus.html>`_ (if you use the latter, please indicate that you are donating for the scikit-learn project).
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All donations will be handled by `NumFOCUS
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<https://numfocus.org/>`_, a non-profit-organization which is
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<http://www.numfocus.org/board.html>`_. NumFOCUS's mission is to foster
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‎doc/datasets/index.rst

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‎doc/developers/advanced_installation.rst

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‎doc/developers/contributing.rst

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‎doc/developers/performance.rst

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‎doc/developers/tips.rst

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Every feature we include has a [maintenance cost](http://scikit-learn.org/dev/faq.html#why-are-you-so-selective-on-what-algorithms-you-include-in-scikit-learn). Our maintainers are mostly volunteers. For a new feature to be included, we need evidence that it is often useful and, ideally, [well-established](http://scikit-learn.org/dev/faq.html#what-are-the-inclusion-criteria-for-new-algorithms) in the literature or in practice. That doesn't stop you implementing it for yourself and publishing it in a separate repository, or even [scikit-learn-contrib](https://scikit-learn-contrib.github.io).
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.. _`README.valgrind`: https://svn.python.org/projects/python/trunk/Misc/README.valgrind
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.. _`valgrind-python.supp`: https://svn.python.org/projects/python/trunk/Misc/valgrind-python.supp
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The result will be a list of all the memory-related errors, which reference

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