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scipy-wheels-nightly / packages / scikit-learn 1.3.dev0

  • 117555 total downloads
  • Last upload: 1 year and 5 months ago

Installers

pip install

To install this package run one of the following:
pip install -i https://pypi.anaconda.org/scipy-wheels-nightly/simple scikit-learn

Description

.. -- mode: rst --

|Azure|_ |Travis|_ |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&circle-token=:circle-token .. _CircleCI: https://circleci.com/gh/scikit-learn/scikit-learn

.. |Travis| image:: https://api.travis-ci.com/scikit-learn/scikit-learn.svg?branch=main .. _Travis: https://app.travis-ci.com/github/scikit-learn/scikit-learn

.. |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/badge/python-3.8%20%7C%203.9%20%7C%203.10-blue .. _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:: 3.8 .. |NumPyMinVersion| replace:: 1.17.3 .. |SciPyMinVersion| replace:: 1.3.2 .. |JoblibMinVersion| replace:: 1.1.1 .. |ThreadpoolctlMinVersion| replace:: 2.0.0 .. |MatplotlibMinVersion| replace:: 3.1.3 .. |Scikit-ImageMinVersion| replace:: 0.16.2 .. |PandasMinVersion| replace:: 1.0.5 .. |SeabornMinVersion| replace:: 0.9.0 .. |PytestMinVersion| replace:: 5.3.1 .. |PlotlyMinVersion| replace:: 5.10.0

.. 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 <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
  • 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
  • Twitter (commits): https://twitter.com/sklearn_commits
  • 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


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