Movatterモバイル変換


[0]ホーム

URL:


Skip to content

Navigation Menu

Search code, repositories, users, issues, pull requests...

Provide feedback

We read every piece of feedback, and take your input very seriously.

Saved searches

Use saved searches to filter your results more quickly

Sign up
Appearance settings

scikit-learn: machine learning in Python

License

NotificationsYou must be signed in to change notification settings

scikit-learn/scikit-learn

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

AzureCodecovCircleCINightly wheelsRuffPythonVersionPyPiDOIBenchmark

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

scikit-learn is a Python module for machine learning built on top ofSciPy and is distributed under the 3-Clause BSD license.

The project was started in 2007 by David Cournapeau as a Google Summerof Code project, and since then many volunteers have contributed. SeetheAbout us pagefor 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 (>= 3.10)
  • NumPy (>= 1.22.0)
  • SciPy (>= 1.8.0)
  • joblib (>= 1.2.0)
  • threadpoolctl (>= 3.1.0)

Scikit-learn plotting capabilities (i.e., functions start withplot_ andclasses end withDisplay) require Matplotlib (>= 3.5.0).For running the examples Matplotlib >= 3.5.0 is required.A few examples require scikit-image >= 0.19.0, a few examplesrequire pandas >= 1.4.0, some examples require seaborn >=0.9.0 and plotly >= 5.14.0.

User installation

If you already have a working installation of NumPy and SciPy,the easiest way to install scikit-learn is usingpip:

pip install -U scikit-learn

orconda:

conda install -c conda-forge scikit-learn

The documentation includes more detailedinstallation instructions.

Changelog

See thechangelogfor a history of notable changes to scikit-learn.

Development

We welcome new contributors of all experience levels. The scikit-learncommunity goals are to be helpful, welcoming, and effective. TheDevelopment Guidehas detailed information about contributing code, documentation, tests, andmore. We've included some basic information in this README.

Important links

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 ourContributing guide.

Testing

After installation, you can launch the test suite from outside the sourcedirectory (you will need to havepytest >= 7.1.2 installed):

pytest sklearn

See the web pagehttps://scikit-learn.org/dev/developers/contributing.html#testing-and-improving-test-coveragefor more information.

Random number generation can be controlled during testing by settingtheSKLEARN_SEED environment variable.

Submitting a Pull Request

Before opening a Pull Request, have a look at thefull Contributing page to make sure your code complieswith our guidelines:https://scikit-learn.org/stable/developers/index.html

Project History

The project was started in 2007 by David Cournapeau as a Google Summerof Code project, and since then many volunteers have contributed. SeetheAbout us pagefor 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

Communication

Citation

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


[8]ページ先頭

©2009-2025 Movatter.jp