Metadata-Version: 1.1
Name: skl-groups-accel
Version: 0.1.3
Summary: Compiled components to speed up skl-groups.
Home-page: https://github.com/dougalsutherland/skl-groups-accel
Author: Dougal J. Sutherland
Author-email: dsutherl@cs.cmu.edu
License: BSD
Download-URL: https://github.com/dougalsutherland/skl-groups-accel
Description: |Travis|_
        
        .. |Travis| image:: https://api.travis-ci.org/dougalsutherland/skl-groups.png?branch=master
        .. _Travis: https://travis-ci.org/dougalsutherland/skl-groups
        
        skl-groups
        ==========
        
        skl-groups is a package to perform machine learning on sets (or "groups") of
        features in Python. It extends the `scikit-learn <http://scikit-learn.org>`_
        library with support for either transforming sets into feature vectors that
        can be operated on with standard scikit-learn constructs or obtaining
        pairwise similarity/etc matrices that can be turned into kernels for use in
        scikit-learn.
        
        For an introduction to the package, why you might want to use it, and how to
        do so, check out
        `the documentation <https://dougalsutherland.github.io/skl-groups/>`_.
        
        skl-groups is still in fairly early development.
        The precursor package, `py-sdm <https://github.com/dougalsutherland/py-sdm/>`_,
        is still somewhat easier to use for some tasks (though it has less functionality
        and less documentation); skl-groups will hopefully match it in the next few weeks.
        Feel free to get in touch (dsutherl@cs.cmu.edu) if you're interested.
        
        
        Installation
        ------------
        
        Full instructions are
        `in the documentation <https://dougalsutherland.github.io/skl-groups/installation.html>`_,
        but the short version is to do::
        
            $ conda install -c https://conda.binstar.org/dougal skl-groups
        
        if you use conda, or::
        
            $ pip install skl-groups
        
        if not. If you pip install and want to use the kNN divergence estimator,
        you'll need to install either
        `cyflann <https://github.com/dougalsutherland/cyflann/>`_
        or the regular pyflann bindings to FLANN,
        and you'll want a version of FLANN with OpenMP support.
        
        A much faster version of the kNN estimator is enabled by the
        skl-groups-accel package, which you can get via::
        
            $ pip install skl-groups-accel
        
        It requires cyflann and a working C compiler with OpenMP support
        (i.e. gcc, not clang).
        
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Image Recognition
Classifier: Topic :: Scientific/Engineering :: Information Analysis
