Metadata-Version: 2.0 Name: scikit-learn Version: 0.18 Summary: A set of python modules for machine learning and data mining Home-page: http://scikit-learn.org Author: Andreas Mueller Author-email: amueller@ais.uni-bonn.de License: new BSD Download-URL: http://sourceforge.net/projects/scikit-learn/files/ Platform: UNKNOWN Classifier: Intended Audience :: Science/Research Classifier: Intended Audience :: Developers Classifier: License :: OSI Approved Classifier: Programming Language :: C Classifier: Programming Language :: Python Classifier: Topic :: Software Development Classifier: Topic :: Scientific/Engineering Classifier: Operating System :: Microsoft :: Windows Classifier: Operating System :: POSIX Classifier: Operating System :: Unix Classifier: Operating System :: MacOS Classifier: Programming Language :: Python :: 2 Classifier: Programming Language :: Python :: 2.6 Classifier: Programming Language :: Python :: 2.7 Classifier: Programming Language :: Python :: 3 Classifier: Programming Language :: Python :: 3.4 Classifier: Programming Language :: Python :: 3.5 Provides-Extra: alldeps Requires-Dist: numpy (>=1.6.1); extra == 'alldeps' Requires-Dist: scipy (>=0.9); extra == 'alldeps' .. -*- mode: rst -*- |Travis|_ |AppVeyor|_ |Coveralls|_ |CircleCI|_ |Python27|_ |Python35|_ |PyPi|_ |DOI|_ .. |Travis| image:: https://api.travis-ci.org/scikit-learn/scikit-learn.svg?branch=master .. _Travis: https://travis-ci.org/scikit-learn/scikit-learn .. |AppVeyor| image:: https://ci.appveyor.com/api/projects/status/github/scikit-learn/scikit-learn?branch=master&svg=true .. _AppVeyor: https://ci.appveyor.com/project/sklearn-ci/scikit-learn/history .. |Coveralls| image:: https://coveralls.io/repos/scikit-learn/scikit-learn/badge.svg?branch=master&service=github .. _Coveralls: https://coveralls.io/r/scikit-learn/scikit-learn .. |CircleCI| image:: https://circleci.com/gh/scikit-learn/scikit-learn/tree/master.svg?style=shield&circle-token=:circle-token .. _CircleCI: https://circleci.com/gh/scikit-learn/scikit-learn .. |Python27| image:: https://img.shields.io/badge/python-2.7-blue.svg .. _Python27: https://badge.fury.io/py/scikit-learn .. |Python35| image:: https://img.shields.io/badge/python-3.5-blue.svg .. _Python35: https://badge.fury.io/py/scikit-learn .. |PyPi| image:: https://badge.fury.io/py/scikit-learn.svg .. _PyPi: https://badge.fury.io/py/scikit-learn .. |DOI| image:: https://zenodo.org/badge/21369/scikit-learn/scikit-learn.svg .. _DOI: https://zenodo.org/badge/latestdoi/21369/scikit-learn/scikit-learn 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 `AUTHORS.rst `_ file for a complete list of contributors. It is currently maintained by a team of volunteers. Website: http://scikit-learn.org Installation ------------ Dependencies ~~~~~~~~~~~~ Scikit-learn requires:: - Python (>= 2.6 or >= 3.3), - NumPy (>= 1.6.1), - SciPy (>= 0.9). 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 `_ 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 `_. Development ----------- We welcome new contributors of all experience levels. The scikit-learn community goals are to be helpful, welcoming, and effective. The `Contributor's Guide `_ 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: http://sourceforge.net/projects/scikit-learn/files/ - 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 the ``nose`` package installed):: $ nosetests -v sklearn Under Windows, it is recommended to use the following command (adjust the path to the ``python.exe`` program) as using the ``nosetests.exe`` program can badly interact with tests that use ``multiprocessing``:: C:\Python34\python.exe -c "import nose; nose.main()" -v sklearn See the web page http://scikit-learn.org/stable/install.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 AUTHORS.rst file for a complete list of 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 ``irc.freenode.net`` - Stack Overflow: http://stackoverflow.com/questions/tagged/scikit-learn - Website: http://scikit-learn.org