Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

https://github.com/scikit-learn/scikit-learn

scikit-learn: machine learning in Python
https://github.com/scikit-learn/scikit-learn

data-analysis data-science machine-learning python statistics

Last synced: 30 days ago
JSON representation

scikit-learn: machine learning in Python

Lists

README 

        
.. -*- mode: rst -*-



|Azure|_ |CirrusCI|_ |Codecov|_ |CircleCI|_ |Nightly wheels|_ |Black|_ |PythonVersion|_ |PyPi|_ |DOI|_ |Benchmark|_



.. |Azure| image:: https://dev.azure.com/scikit-learn/scikit-learn/_apis/build/status/scikit-learn.scikit-learn?branchName=main

.. _Azure: https://dev.azure.com/scikit-learn/scikit-learn/_build/latest?definitionId=1&branchName=main



.. |CircleCI| image:: https://circleci.com/gh/scikit-learn/scikit-learn/tree/main.svg?style=shield

.. _CircleCI: https://circleci.com/gh/scikit-learn/scikit-learn



.. |CirrusCI| image:: https://img.shields.io/cirrus/github/scikit-learn/scikit-learn/main?label=Cirrus%20CI

.. _CirrusCI: https://cirrus-ci.com/github/scikit-learn/scikit-learn/main



.. |Codecov| image:: https://codecov.io/gh/scikit-learn/scikit-learn/branch/main/graph/badge.svg?token=Pk8G9gg3y9

.. _Codecov: https://codecov.io/gh/scikit-learn/scikit-learn



.. |Nightly wheels| image:: https://github.com/scikit-learn/scikit-learn/workflows/Wheel%20builder/badge.svg?event=schedule

.. _`Nightly wheels`: https://github.com/scikit-learn/scikit-learn/actions?query=workflow%3A%22Wheel+builder%22+event%3Aschedule



.. |PythonVersion| image:: https://img.shields.io/pypi/pyversions/scikit-learn.svg

.. _PythonVersion: https://pypi.org/project/scikit-learn/



.. |PyPi| image:: https://img.shields.io/pypi/v/scikit-learn

.. _PyPi: https://pypi.org/project/scikit-learn



.. |Black| image:: https://img.shields.io/badge/code%20style-black-000000.svg

.. _Black: https://github.com/psf/black



.. |DOI| image:: https://zenodo.org/badge/21369/scikit-learn/scikit-learn.svg

.. _DOI: https://zenodo.org/badge/latestdoi/21369/scikit-learn/scikit-learn



.. |Benchmark| image:: https://img.shields.io/badge/Benchmarked%20by-asv-blue

.. _`Benchmark`: https://scikit-learn.org/scikit-learn-benchmarks/



.. |PythonMinVersion| replace:: 3.9

.. |NumPyMinVersion| replace:: 1.19.5

.. |SciPyMinVersion| replace:: 1.6.0

.. |JoblibMinVersion| replace:: 1.2.0

.. |ThreadpoolctlMinVersion| replace:: 2.0.0

.. |MatplotlibMinVersion| replace:: 3.3.4

.. |Scikit-ImageMinVersion| replace:: 0.17.2

.. |PandasMinVersion| replace:: 1.1.5

.. |SeabornMinVersion| replace:: 0.9.0

.. |PytestMinVersion| replace:: 7.1.2

.. |PlotlyMinVersion| replace:: 5.14.0



.. image:: https://raw.githubusercontent.com/scikit-learn/scikit-learn/main/doc/logos/scikit-learn-logo.png

  :target: https://scikit-learn.org/



**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 `__ 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 `_.



Changelog

---------



See the `changelog `__

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 `_

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

`_.



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 `__ 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

- Gitter: https://gitter.im/scikit-learn/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

- 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



Citation

~~~~~~~~



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