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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 <https://scikit-learn.org/dev/about.html#authors>__ page for a list of core contributors.

It is currently maintained by a team of volunteers.

Website: https://scikit-learn.org

Installation

Dependencies

scikit-learn requires:

- Python (>= 3.6)
- NumPy (>= 1.13.3)
- SciPy (>= 0.19.1)
- joblib (>= 0.11)

**Scikit-learn 0.20 was the last version to support Python 2.7 and Python 3.4.**
scikit-learn 0.23 and later require Python 3.6 or newer.

Scikit-learn plotting capabilities (i.e., functions start with ``plot_``
and classes end with "Display") require Matplotlib (>= 2.1.1). For running the
examples Matplotlib >= 2.1.1 is required. A few examples require
scikit-image >= 0.13, a few examples require pandas >= 0.18.0, some examples
require seaborn >= 0.9.0.

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 <https://scikit-learn.org/stable/install.html>_.

Changelog

See the changelog <https://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 <https://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 https://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: https://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 <https://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): https://scikit-learn.org
• HTML documentation (development version): https://scikit-learn.org/dev/
• FAQ: https://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: https://scikit-learn.org

Citation

If you use scikit-learn in a scientific publication, we would appreciate citations: https://scikit-learn.org/stable/about.html#citing-scikit-learn