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

scikit-learn 是一个用于机器学习的 Python 模块，建立在 SciPy 之上，并根据
3-Clause BSD 许可证进行分发。

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

安装
----

依赖

.. code:: sh


   scikit-learn requires:

   - Python (>= 3.5)
   - NumPy (>= 1.11.0)
   - SciPy (>= 0.17.0)

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

   For running the examples Matplotlib >= 1.5.1 is required.
   A few examples
   require scikit-image >= 0.12.3, a few examples require pandas >= 0.18.0
   and a few example require joblib >= 0.11.

   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/computing#linear-algebra-libraries>`_
   for known issues.

   User installation

如果您已经安装了 numpy 和 scipy，安装 scikit-learn
的最简单方法是使用\ ``pip`` :

::

   pip install -U scikit-learn

或者\ ``conda``:

::

   conda install scikit-learn

该文档包含更详细的\ `安装说明 <http://scikit-learn.org/stable/install.html>`__.

更新日志
--------

See the `changelog <http://scikit-learn.org/dev/whats_new.html>`__ for a
history of notable changes to scikit-learn.

发展
----

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.

重要链接

::


   - 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

   源代码
   ~~~~~~~~~~~

   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

测试

::


   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

项目历史
--------

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``.

帮助和支持
----------

文档

::


   - 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

   通讯

-  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

引文

::


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