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scikit-learn

scikit-learn is a Python module for machine learning built on top of
SciPy and is 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 (>= 3.5)
- NumPy (>= 1.11.0)
- SciPy (>= 0.17.0)
- joblib (>= 0.11)

**Scikit-learn 0.20 was the last version to support Python 2.7 and Python 3.4.**
scikit-learn 0.21 and later require Python 3.5 or newer.

Scikit-learn plotting capabilities (i.e., functions start with ``plot_``
and classes end with "Display") require Matplotlib (>= 1.5.1). For running the
examples Matplotlib >= 1.5.1 is required. A few examples require
scikit-image >= 0.12.3, a few examples require pandas >= 0.18.0.

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

Contributing
~~~~~~~~~~~~

To learn more about making a contribution to scikit-learn, please see our
`Contributing guide
<https://scikit-learn.org/dev/developers/contributing.html>`_.

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