Metadata-Version: 1.1
Name: operalib
Version: 0.2b1
Summary: A python module for learnign with operator-valued kernels
Home-page: http://operalib.github.io/operalib/documentation/
Author: Romain Brault
Author-email: romain.brault@telecom-paristech.fr
License: MIT
Download-URL: https://github.com/operalib/operalib/
Description: .. -*- mode: rst -*-
        
        .. |Travis| image:: https://travis-ci.org/operalib/operalib.svg?branch=master
        .. _Travis: https://travis-ci.org/operalib/operalib
        
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        .. _Coveralls: https://coveralls.io/github/operalib/operalib ?branch=master
        
        .. |CircleCI| image:: https://circleci.com/gh/operalib/operalib/tree/master.svg?style=shield&circle-token=:circle-token
        .. _CircleCI: https://circleci.com/gh/operalib/operalib
        
        .. |Python27| image:: https://img.shields.io/badge/python-2.7-blue.svg
        .. _Python27: https://github.com/operalib/operalib
        
        .. |Python35| image:: https://img.shields.io/badge/python-3.5-blue.svg
        .. _Python35: https://github.com/operalib/operalib
        
        Operalib
        ========
        |Travis|_ |Coveralls|_ |CircleCI|_ |Python27|_ |Python35|_
        
        Operalib is a library for structured learning and prediction for
        `python <https://www.python.org>`_ based on operator-valued kernels (OVKs).
        OVKs are an extension of scalar kernels to matrix-valued kernels.
        The idea is to predict silmultaneously several targets while, for instance,
        encoding the output structure with the operator-valued kernel.
        
        We aim at providing an easy-to-use standard implementation of operator-valued
        kernel methods. Operalib is designed for compatilibity to
        `scikit-learn <http://scikit-learn.org>`_ interface and conventions.
        It uses `numpy <http://www.numpy.org>`_,
        `scipy <http://www.scipy.org>`_ and `cvxopt <http://www.cvxopt.org>`_ as
        underlying libraries. It also relies on
        `dill <https://pypi.python.org/pypi/dill>`_ for lambda pickling.
        
        The project is developed by the
        `AROBAS <https://www.ibisc.univ-evry.fr/arobas>`_ group of the
        `IBISC laboratory <https://www.ibisc.univ-evry.fr/en/start>`_ of the
        University of Evry, France.
        
        Documentation
        =============
        Is available at: http://operalib.github.io/operalib/documentation/.
        
        Install
        =======
        The package is available on PyPi, and the installation should be as simple as::
        
          pip install nose operalib
        
        This package uses distutils, which is the default way of installing
        python modules. To install in your home directory, use::
        
          python setup.py install --user
        
        To install for all users on Unix/Linux::
        
          python setup.py build
          sudo python setup.py install
        
        .. For more detailed installation instructions,
        .. see the web page http://scikit-learn.org/stable/install.html
        
        GIT
        ~~~
        
        You can check the latest sources with the command::
        
            git clone https://github.com/operalib/operalib
        
        or if you have write privileges::
        
            git clone git@github.com:operalib/operalib.git
        
        References
        ==========
        A non-exhaustive list of publications related to operator-valued kernel is
        available here:
        
        http://operalib.github.io/operalib/documentation/reference_papers/index.html.
        
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 :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
