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Metadata-Version: 1.1
Name: scikit-learn
Version: 0.20.2
Summary: A set of python modules for machine learning and data mining
Home-page: http://scikit-learn.org
Author: Andreas Mueller
Author-email: amueller@ais.uni-bonn.de
License: new BSD
Download-URL: https://pypi.org/project/scikit-learn/#files
Description: .. -*- mode: rst -*-
|Travis|_ |AppVeyor|_ |Codecov|_ |CircleCI|_ |Python27|_ |Python35|_ |PyPi|_ |DOI|_
.. |Travis| image:: https://api.travis-ci.org/scikit-learn/scikit-learn.svg?branch=master
.. _Travis: https://travis-ci.org/scikit-learn/scikit-learn
.. |AppVeyor| image:: https://ci.appveyor.com/api/projects/status/github/scikit-learn/scikit-learn?branch=master&svg=true
.. _AppVeyor: https://ci.appveyor.com/project/sklearn-ci/scikit-learn/history
.. |Codecov| image:: https://codecov.io/github/scikit-learn/scikit-learn/badge.svg?branch=master&service=github
.. _Codecov: https://codecov.io/github/scikit-learn/scikit-learn?branch=master
.. |CircleCI| image:: https://circleci.com/gh/scikit-learn/scikit-learn/tree/master.svg?style=shield&circle-token=:circle-token
.. _CircleCI: https://circleci.com/gh/scikit-learn/scikit-learn
.. |Python27| image:: https://img.shields.io/badge/python-2.7-blue.svg
.. _Python27: https://badge.fury.io/py/scikit-learn
.. |Python35| image:: https://img.shields.io/badge/python-3.5-blue.svg
.. _Python35: https://badge.fury.io/py/scikit-learn
.. |PyPi| image:: https://badge.fury.io/py/scikit-learn.svg
.. _PyPi: https://badge.fury.io/py/scikit-learn
.. |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 `About us <http://scikit-learn.org/dev/about.html#authors>`_ page
for a list of core contributors.
It is currently maintained by a team of volunteers.
Website: http://scikit-learn.org
Installation
------------
Dependencies
~~~~~~~~~~~~
scikit-learn requires:
- Python (>= 2.7 or >= 3.4)
- NumPy (>= 1.8.2)
- SciPy (>= 0.13.3)
**Scikit-learn 0.20 is the last version to support Python2.7.**
Scikit-learn 0.21 and later will require Python 3.5 or newer.
For running the examples Matplotlib >= 1.4 is required. A few examples
require scikit-image >= 0.11.3, a few examples require pandas >= 0.17.1
and a few example require joblib >= 0.11.
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/computing#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>`_.
Changelog
---------
See the `changelog <http://scikit-learn.org/dev/whats_new.html>`__
for a history of notable changes to scikit-learn.
Development
-----------
We welcome new contributors of all experience levels. The scikit-learn
community goals are to be helpful, welcoming, and effective. The
`Development 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: https://pypi.org/project/scikit-learn/
- 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 ``pytest`` >= 3.3.0 installed)::
pytest sklearn
See the web page http://scikit-learn.org/dev/developers/advanced_installation.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 `About us <http://scikit-learn.org/dev/about.html#authors>`_ page
for a list of core 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 ``webchat.freenode.net``
- Stack Overflow: https://stackoverflow.com/questions/tagged/scikit-learn
- Website: http://scikit-learn.org
Citation
~~~~~~~~
If you use scikit-learn in a scientific publication, we would appreciate citations: http://scikit-learn.org/stable/about.html#citing-scikit-learn
Platform: UNKNOWN
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved
Classifier: Programming Language :: C
Classifier: Programming Language :: Python
Classifier: Topic :: Software Development
Classifier: Topic :: Scientific/Engineering
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Classifier: Operating System :: MacOS
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Programming Language :: Python :: Implementation :: PyPy
|
