# scikit-learn

**Repository Path**: mirrors_IntelPython/scikit-learn

## Basic Information

- **Project Name**: scikit-learn
- **Description**: scikit-learn: machine learning in Python
- **Primary Language**: Unknown
- **License**: BSD-3-Clause
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-09-25
- **Last Updated**: 2025-12-21

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# DISCONTINUATION OF PROJECT #
This project will no longer be maintained by Intel.
Intel has ceased development and contributions including, but not limited to, maintenance, bug fixes, new releases, or updates, to this project.
Intel no longer accepts patches to this project.
.. -*- mode: rst -*-

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scikit-learn
============

scikit-learn is a Python module for machine learning built on top of
SciPy and 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 <http://scikit-learn.org/dev/about.html#authors>`_ page
for a list of core contributors.

It is currently maintained by a team of volunteers.

Website: http://scikit-learn.org


Installation
------------

Dependencies
~~~~~~~~~~~~

scikit-learn requires:

- Python (>= 2.7 or >= 3.4)
- NumPy (>= 1.8.2)
- SciPy (>= 0.13.3)

**Scikit-learn 0.20 is the last version to support Python2.7.**
Scikit-learn 0.21 and later will require Python 3.5 or newer.

For running the examples Matplotlib >= 1.4 is required. A few examples
require scikit-image >= 0.11.3 and a few examples require pandas >= 0.17.1.

scikit-learn also uses CBLAS, the C interface to the Basic Linear Algebra
Subprograms library. scikit-learn comes with a reference implementation, but
the system CBLAS will be detected by the build system and used if present.
CBLAS exists in many implementations; see `Linear algebra libraries
<http://scikit-learn.org/stable/modules/computational_performance.html#linear-algebra-libraries>`_
for known issues.

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 scikit-learn

The documentation includes more detailed `installation instructions <http://scikit-learn.org/stable/install.html>`_.


Changelog
---------

See the `changelog <http://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 <http://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

Setting up a development environment
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Quick tutorial on how to go about setting up your environment to
contribute to scikit-learn: https://github.com/scikit-learn/scikit-learn/blob/master/CONTRIBUTING.md

Testing
~~~~~~~

After installation, you can launch the test suite from outside the
source directory (you will need to have ``pytest`` >= 3.3.0 installed)::

    pytest sklearn

See the web page http://scikit-learn.org/dev/developers/advanced_installation.html#testing
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: http://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 <http://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): http://scikit-learn.org
- HTML documentation (development version): http://scikit-learn.org/dev/
- FAQ: http://scikit-learn.org/stable/faq.html

Communication
~~~~~~~~~~~~~

- Mailing list: https://mail.python.org/mailman/listinfo/scikit-learn
- IRC channel: ``#scikit-learn`` at ``webchat.freenode.net``
- Stack Overflow: https://stackoverflow.com/questions/tagged/scikit-learn
- Website: http://scikit-learn.org

Citation
~~~~~~~~

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