.. -*- mode: rst -*-
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scikit-learn
============
scikit-learn is a Python module for machine learning built on top of
SciPy and distributed under the 3-Clause BSD license.
The project was started in 2007 by David Cournapeau as a Google Summer
of Code project, and since then many volunteers have contributed. See
the `AUTHORS.rst <AUTHORS.rst>`_ file for a complete list of contributors.
It is currently maintained by a team of volunteers.
Website: http://scikit-learn.org
Installation
------------
Dependencies
~~~~~~~~~~~~
Scikit-learn requires::
- Python (>= 2.6 or >= 3.3),
- NumPy (>= 1.6.1),
- SciPy (>= 0.9).
scikit-learn also uses CBLAS, the C interface to the Basic Linear Algebra
Subprograms library. scikit-learn comes with a reference implementation, but
the system CBLAS will be detected by the build system and used if present.
CBLAS exists in many implementations; see `Linear algebra libraries
<http://scikit-learn.org/stable/modules/computational_performance.html#linear-algebra-libraries>`_
for known issues.
User installation
~~~~~~~~~~~~~~~~~
If you already have a working installation of numpy and scipy,
the easiest way to install scikit-learn is using ``pip`` ::
pip install -U scikit-learn
or ``conda``::
conda install scikit-learn
The documentation includes more detailed `installation instructions <http://scikit-learn.org/stable/install.html>`_.
Development
-----------
We welcome new contributors of all experience levels. The scikit-learn
community goals are to be helpful, welcoming, and effective. The
`Contributor's Guide <http://scikit-learn.org/stable/developers/index.html>`_
has detailed information about contributing code, documentation, tests, and
more. We've included some basic information in this README.
Important links
~~~~~~~~~~~~~~~
- Official source code repo: https://github.com/scikit-learn/scikit-learn
- Download releases: http://sourceforge.net/projects/scikit-learn/files/
- Issue tracker: https://github.com/scikit-learn/scikit-learn/issues
Source code
~~~~~~~~~~~
You can check the latest sources with the command::
git clone https://github.com/scikit-learn/scikit-learn.git
Setting up a development environment
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Quick tutorial on how to go about setting up your environment to
contribute to scikit-learn: https://github.com/scikit-learn/scikit-learn/blob/master/CONTRIBUTING.md
Testing
~~~~~~~
After installation, you can launch the test suite from outside the
source directory (you will need to have the ``nose`` package installed)::
$ nosetests -v sklearn
Under Windows, it is recommended to use the following command (adjust the path
to the ``python.exe`` program) as using the ``nosetests.exe`` program can badly
interact with tests that use ``multiprocessing``::
C:\Python34\python.exe -c "import nose; nose.main()" -v sklearn
See the web page http://scikit-learn.org/stable/install.html#testing
for more information.
Random number generation can be controlled during testing by setting
the ``SKLEARN_SEED`` environment variable.
Submitting a Pull Request
~~~~~~~~~~~~~~~~~~~~~~~~~
Before opening a Pull Request, have a look at the
full Contributing page to make sure your code complies
with our guidelines: http://scikit-learn.org/stable/developers/index.html
Project history
---------------
The project was started in 2007 by David Cournapeau as a Google Summer
of Code project, and since then many volunteers have contributed. See
the AUTHORS.rst file for a complete list of contributors.
The project is currently maintained by a team of volunteers.
**Note** `scikit-learn` was previously referred to as `scikits.learn`.
Help and Support
----------------
Documentation
~~~~~~~~~~~~~
- HTML documentation (stable release): http://scikit-learn.org
- HTML documentation (development version): http://scikit-learn.org/dev/
- FAQ: http://scikit-learn.org/stable/faq.html
Communication
~~~~~~~~~~~~~
- Mailing list: https://mail.python.org/mailman/listinfo/scikit-learn
- IRC channel: ``#scikit-learn`` at ``irc.freenode.net``
- Stack Overflow: http://stackoverflow.com/questions/tagged/scikit-learn
- Website: http://scikit-learn.org
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.. |DOI| image:: https://zenodo.org/badge/21369/scikit-learn/scikit-learn.svg
.. _DOI: https://zenodo.org/badge/latestdoi/21369/scikit-learn/scikit-learn
scikit-learn
============
scikit-learn is a Python module for machine learning built on top of
SciPy and distributed under the 3-Clause BSD license.
The project was started in 2007 by David Cournapeau as a Google Summer
of Code project, and since then many volunteers have contributed. See
the `AUTHORS.rst <AUTHORS.rst>`_ file for a complete list of contributors.
It is currently maintained by a team of volunteers.
Website: http://scikit-learn.org
Installation
------------
Dependencies
~~~~~~~~~~~~
Scikit-learn requires::
- Python (>= 2.6 or >= 3.3),
- NumPy (>= 1.6.1),
- SciPy (>= 0.9).
scikit-learn also uses CBLAS, the C interface to the Basic Linear Algebra
Subprograms library. scikit-learn comes with a reference implementation, but
the system CBLAS will be detected by the build system and used if present.
CBLAS exists in many implementations; see `Linear algebra libraries
<http://scikit-learn.org/stable/modules/computational_performance.html#linear-algebra-libraries>`_
for known issues.
User installation
~~~~~~~~~~~~~~~~~
If you already have a working installation of numpy and scipy,
the easiest way to install scikit-learn is using ``pip`` ::
pip install -U scikit-learn
or ``conda``::
conda install scikit-learn
The documentation includes more detailed `installation instructions <http://scikit-learn.org/stable/install.html>`_.
Development
-----------
We welcome new contributors of all experience levels. The scikit-learn
community goals are to be helpful, welcoming, and effective. The
`Contributor's Guide <http://scikit-learn.org/stable/developers/index.html>`_
has detailed information about contributing code, documentation, tests, and
more. We've included some basic information in this README.
Important links
~~~~~~~~~~~~~~~
- Official source code repo: https://github.com/scikit-learn/scikit-learn
- Download releases: http://sourceforge.net/projects/scikit-learn/files/
- Issue tracker: https://github.com/scikit-learn/scikit-learn/issues
Source code
~~~~~~~~~~~
You can check the latest sources with the command::
git clone https://github.com/scikit-learn/scikit-learn.git
Setting up a development environment
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Quick tutorial on how to go about setting up your environment to
contribute to scikit-learn: https://github.com/scikit-learn/scikit-learn/blob/master/CONTRIBUTING.md
Testing
~~~~~~~
After installation, you can launch the test suite from outside the
source directory (you will need to have the ``nose`` package installed)::
$ nosetests -v sklearn
Under Windows, it is recommended to use the following command (adjust the path
to the ``python.exe`` program) as using the ``nosetests.exe`` program can badly
interact with tests that use ``multiprocessing``::
C:\Python34\python.exe -c "import nose; nose.main()" -v sklearn
See the web page http://scikit-learn.org/stable/install.html#testing
for more information.
Random number generation can be controlled during testing by setting
the ``SKLEARN_SEED`` environment variable.
Submitting a Pull Request
~~~~~~~~~~~~~~~~~~~~~~~~~
Before opening a Pull Request, have a look at the
full Contributing page to make sure your code complies
with our guidelines: http://scikit-learn.org/stable/developers/index.html
Project history
---------------
The project was started in 2007 by David Cournapeau as a Google Summer
of Code project, and since then many volunteers have contributed. See
the AUTHORS.rst file for a complete list of contributors.
The project is currently maintained by a team of volunteers.
**Note** `scikit-learn` was previously referred to as `scikits.learn`.
Help and Support
----------------
Documentation
~~~~~~~~~~~~~
- HTML documentation (stable release): http://scikit-learn.org
- HTML documentation (development version): http://scikit-learn.org/dev/
- FAQ: http://scikit-learn.org/stable/faq.html
Communication
~~~~~~~~~~~~~
- Mailing list: https://mail.python.org/mailman/listinfo/scikit-learn
- IRC channel: ``#scikit-learn`` at ``irc.freenode.net``
- Stack Overflow: http://stackoverflow.com/questions/tagged/scikit-learn
- Website: http://scikit-learn.org
6 maintainers
Metadata
6 maintainers
Release files for scikit-learn 0.18
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
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| scikit-learn-0.18.win32-py3.5.exe | Details | |||
| scikit-learn-0.18.win32-py2.7.exe | Details |
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Release files / scikit_learn-0.18-cp27-cp27m-win_amd64.whl
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Release files / scikit_learn-0.18-cp27-cp27m-win32.whl
| Download URL | scikit_learn-0.18-cp27-cp27m-win32.whl |
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| Size | 3.8 MB |
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Release files / scikit_learn-0.18-cp27-cp27m-manylinux1_x86_64.whl
| Download URL | scikit_learn-0.18-cp27-cp27m-manylinux1_x86_64.whl |
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| Size | 11.4 MB |
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Release files / scikit_learn-0.18-cp27-cp27m-manylinux1_i686.whl
| Download URL | scikit_learn-0.18-cp27-cp27m-manylinux1_i686.whl |
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| Size | 10.6 MB |
| Tags | CPython 2.7 CPython 2.7 pymalloc Linux glibc 2.5+ x86-32 |
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Release files / scikit_learn-0.18-cp27-cp27m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl
| Download URL | scikit_learn-0.18-cp27-cp27m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl |
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| Size | 7.1 MB |
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Release files / scikit-learn-0.18.win-amd64-py3.5.exe
| Download URL | scikit-learn-0.18.win-amd64-py3.5.exe |
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| Size | 4.7 MB |
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Release files / scikit-learn-0.18.win-amd64-py2.7.exe
| Download URL | scikit-learn-0.18.win-amd64-py2.7.exe |
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Release files / scikit-learn-0.18.win32-py3.5.exe
| Download URL | scikit-learn-0.18.win32-py3.5.exe |
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| Size | 4.2 MB |
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Release files / scikit-learn-0.18.win32-py2.7.exe
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