gituser/docker_multiarch/: scikit-learn-1.5.2 metadata and description

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A set of python modules for machine learning and data mining

classifiers
  • Intended Audience :: Science/Research
  • Intended Audience :: Developers
  • License :: OSI Approved :: BSD License
  • Programming Language :: C
  • Programming Language :: Python
  • Topic :: Software Development
  • Topic :: Scientific/Engineering
  • Development Status :: 5 - Production/Stable
  • Operating System :: Microsoft :: Windows
  • Operating System :: POSIX
  • Operating System :: Unix
  • Operating System :: MacOS
  • Programming Language :: Python :: 3
  • Programming Language :: Python :: 3.9
  • Programming Language :: Python :: 3.10
  • Programming Language :: Python :: 3.11
  • Programming Language :: Python :: 3.12
  • Programming Language :: Python :: Implementation :: CPython
  • Programming Language :: Python :: Implementation :: PyPy
description_content_type text/x-rst
license BSD 3-Clause License Copyright (c) 2007-2024 The scikit-learn developers. All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. * Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
maintainer_email scikit-learn developers <scikit-learn@python.org>
project_urls
  • Homepage, https://scikit-learn.org
  • Source, https://github.com/scikit-learn/scikit-learn
  • Download, https://pypi.org/project/scikit-learn/#files
  • Tracker, https://github.com/scikit-learn/scikit-learn/issues
  • Release notes, https://scikit-learn.org/stable/whats_new
provides_extras maintenance
requires_dist
  • numpy>=1.19.5
  • scipy>=1.6.0
  • joblib>=1.2.0
  • threadpoolctl>=3.1.0
  • numpy>=1.19.5; extra == "build"
  • scipy>=1.6.0; extra == "build"
  • cython>=3.0.10; extra == "build"
  • meson-python>=0.16.0; extra == "build"
  • numpy>=1.19.5; extra == "install"
  • scipy>=1.6.0; extra == "install"
  • joblib>=1.2.0; extra == "install"
  • threadpoolctl>=3.1.0; extra == "install"
  • matplotlib>=3.3.4; extra == "benchmark"
  • pandas>=1.1.5; extra == "benchmark"
  • memory_profiler>=0.57.0; extra == "benchmark"
  • matplotlib>=3.3.4; extra == "docs"
  • scikit-image>=0.17.2; extra == "docs"
  • pandas>=1.1.5; extra == "docs"
  • seaborn>=0.9.0; extra == "docs"
  • memory_profiler>=0.57.0; extra == "docs"
  • sphinx>=7.3.7; extra == "docs"
  • sphinx-copybutton>=0.5.2; extra == "docs"
  • sphinx-gallery>=0.16.0; extra == "docs"
  • numpydoc>=1.2.0; extra == "docs"
  • Pillow>=7.1.2; extra == "docs"
  • pooch>=1.6.0; extra == "docs"
  • sphinx-prompt>=1.4.0; extra == "docs"
  • sphinxext-opengraph>=0.9.1; extra == "docs"
  • plotly>=5.14.0; extra == "docs"
  • polars>=0.20.30; extra == "docs"
  • sphinx-design>=0.5.0; extra == "docs"
  • sphinx-design>=0.6.0; extra == "docs"
  • sphinxcontrib-sass>=0.3.4; extra == "docs"
  • pydata-sphinx-theme>=0.15.3; extra == "docs"
  • sphinx-remove-toctrees>=1.0.0.post1; extra == "docs"
  • matplotlib>=3.3.4; extra == "examples"
  • scikit-image>=0.17.2; extra == "examples"
  • pandas>=1.1.5; extra == "examples"
  • seaborn>=0.9.0; extra == "examples"
  • pooch>=1.6.0; extra == "examples"
  • plotly>=5.14.0; extra == "examples"
  • matplotlib>=3.3.4; extra == "tests"
  • scikit-image>=0.17.2; extra == "tests"
  • pandas>=1.1.5; extra == "tests"
  • pytest>=7.1.2; extra == "tests"
  • pytest-cov>=2.9.0; extra == "tests"
  • ruff>=0.2.1; extra == "tests"
  • black>=24.3.0; extra == "tests"
  • mypy>=1.9; extra == "tests"
  • pyamg>=4.0.0; extra == "tests"
  • polars>=0.20.30; extra == "tests"
  • pyarrow>=12.0.0; extra == "tests"
  • numpydoc>=1.2.0; extra == "tests"
  • pooch>=1.6.0; extra == "tests"
  • conda-lock==2.5.6; extra == "maintenance"
requires_python >=3.9
File Tox results History
scikit_learn-1.5.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Size
12 MB
Type
Python Wheel
Python
3.1.0
scikit_learn-1.5.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Size
13 MB
Type
Python Wheel
Python
3.1.0
scikit_learn-1.5.2-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Size
12 MB
Type
Python Wheel
Python
3.9
scikit_learn-1.5.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Size
13 MB
Type
Python Wheel
Python
3.9

Azure CirrusCI Codecov CircleCI Nightly wheels Black PythonVersion PyPi DOI Benchmark

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 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 (>= 3.9)

  • NumPy (>= 1.19.5)

  • SciPy (>= 1.6.0)

  • joblib (>= 1.2.0)

  • threadpoolctl (>= 3.1.0)

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 (>= 3.3.4). For running the examples Matplotlib >= 3.3.4 is required. A few examples require scikit-image >= 0.17.2, a few examples require pandas >= 1.1.5, 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 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.

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 >= 7.1.2 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

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