scikit-learn (1.6.0)
Installation
pip install --index-url About this package
A set of python modules for machine learning and data mining
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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 (>= |PythonMinVersion|)
- NumPy (>= |NumPyMinVersion|)
- SciPy (>= |SciPyMinVersion|)
- joblib (>= |JoblibMinVersion|)
- threadpoolctl (>= |ThreadpoolctlMinVersion|)
=======
**Scikit-learn 0.20 was the last version to support Python 2.7 and Python 3.4.**
scikit-learn 1.0 and later require Python 3.7 or newer.
scikit-learn 1.1 and later require Python 3.8 or newer.
Scikit-learn plotting capabilities (i.e., functions start with ``plot_`` and
classes end with ``Display``) require Matplotlib (>= |MatplotlibMinVersion|).
For running the examples Matplotlib >= |MatplotlibMinVersion| is required.
A few examples require scikit-image >= |Scikit-ImageMinVersion|, a few examples
require pandas >= |PandasMinVersion|, some examples require seaborn >=
|SeabornMinVersion| and plotly >= |PlotlyMinVersion|.
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 -c conda-forge 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`` >= |PyTestMinVersion| installed)::
pytest sklearn
See the web page https://scikit-learn.org/dev/developers/contributing.html#testing-and-improving-test-coverage
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
- Logos & Branding: https://github.com/scikit-learn/scikit-learn/tree/main/doc/logos
- Blog: https://blog.scikit-learn.org
- Calendar: https://blog.scikit-learn.org/calendar/
- Twitter: https://twitter.com/scikit_learn
- Stack Overflow: https://stackoverflow.com/questions/tagged/scikit-learn
- GitHub Discussions: https://github.com/scikit-learn/scikit-learn/discussions
- Website: https://scikit-learn.org
- LinkedIn: https://www.linkedin.com/company/scikit-learn
- Bluesky: https://bsky.app/profile/scikit-learn.org
- YouTube: https://www.youtube.com/channel/UCJosFjYm0ZYVUARxuOZqnnw/playlists
- Facebook: https://www.facebook.com/scikitlearnofficial/
- Instagram: https://www.instagram.com/scikitlearnofficial/
- TikTok: https://www.tiktok.com/@scikit.learn
- Mastodon: https://mastodon.social/@sklearn@fosstodon.org
- Discord: https://discord.gg/h9qyrK8Jc8
Citation
If you use scikit-learn in a scientific publication, we would appreciate citations: https://scikit-learn.org/stable/about.html#citing-scikit-learn