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	Metadata-Version: 2.1
	Name: scikit-learn
	Version: 1.6.1
	Summary: A set of python modules for machine learning and data mining
	Maintainer-Email: scikit-learn developers <[email protected]>
	License: BSD 3-Clause License

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	----

	This binary distribution of scikit-learn also bundles the following software:

	----

	Name: libomp runtime library
	Files: sklearn/.dylibs/libomp.dylib
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	==============================================================================
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	==============================================================================
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	Open Source License

	Copyright (c) 2003-2019 University of Illinois at Urbana-Champaign.
	All rights reserved.

	Developed by:

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	Classifier: Intended Audience :: Science/Research
	Classifier: Intended Audience :: Developers
	Classifier: License :: OSI Approved :: BSD License
	Classifier: Programming Language :: C
	Classifier: Programming Language :: Python
	Classifier: Topic :: Software Development
	Classifier: Topic :: Scientific/Engineering
	Classifier: Development Status :: 5 - Production/Stable
	Classifier: Operating System :: Microsoft :: Windows
	Classifier: Operating System :: POSIX
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	Classifier: Operating System :: MacOS
	Classifier: Programming Language :: Python :: 3
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	Classifier: Programming Language :: Python :: 3.11
	Classifier: Programming Language :: Python :: 3.12
	Classifier: Programming Language :: Python :: 3.13
	Classifier: Programming Language :: Python :: Implementation :: CPython
	Project-URL: homepage, https://scikit-learn.org
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	.. -- mode: rst --

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	.. 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
	- 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
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	Citation
	~~~~~~~~

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