Metadata-Version: 1.1
Name: scikit-learn
Version: 0.12.1
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/
Description: .. -*- mode: rst -*-
        
        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.
        
        **Note** `scikit-learn` was previously referred to as `scikits.learn`.
        
        
        Important links
        ===============
        
        - Official source code repo: https://github.com/scikit-learn/scikit-learn
        - HTML documentation (stable release): http://scikit-learn.org
        - HTML documentation (development version): http://scikit-learn.org/dev/
        - Download releases: http://sourceforge.net/projects/scikit-learn/files/
        - Issue tracker: https://github.com/scikit-learn/scikit-learn/issues
        - Mailing list: https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
        - IRC channel: ``#scikit-learn`` at ``irc.freenode.net``
        
        Dependencies
        ============
        
        The required dependencies to build the software are Python >= 2.6,
        setuptools, Numpy >= 1.3, SciPy >= 0.7 and a working C/C++ compiler.
        This configuration matches the Ubuntu 10.04 LTS release from April 2010.
        
        To run the tests you will also need nose >= 0.10.
        
        
        Install
        =======
        
        This package uses distutils, which is the default way of installing
        python modules. To install in your home directory, use::
        
          python setup.py install --home
        
        To install for all users on Unix/Linux::
        
          python setup.py build
          sudo python setup.py install
        
        
        Development
        ===========
        
        Code
        ----
        
        GIT
        ~~~
        
        You can check the latest sources with the command::
        
            git clone git://github.com/scikit-learn/scikit-learn.git
        
        or if you have write privileges::
        
            git clone git@github.com:scikit-learn/scikit-learn.git
        
        
        Testing
        -------
        
        After installation, you can launch the test suite from outside the
        source directory (you will need to have nosetest installed)::
        
           $ nosetest --exe sklearn 
        
        See web page http://scikit-learn.org/stable/install.html#testing
        for more information.
        
            Random number generation can be controled during testing by setting
            the SKLEARN_SEED environment variable
        
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
