Metadata-Version: 2.1
Name: pyndl
Version: 0.8.1
Summary: Naive discriminative learning implements learning and classification models based on the Rescorla-Wagner equations.
Home-page: https://github.com/quantling/pyndl
Author: Konstantin Sering, Marc Weitz, David-Elias Künstle, Lennard Schneider, Elnaz Shafaei-Bajestan
Author-email: konstantin.sering@uni-tuebingen.de
License: MIT
Description: ===============================================
        Pyndl - Naive Discriminative Learning in Python
        ===============================================
        
        .. image:: https://travis-ci.com/quantling/pyndl.svg?branch=master
            :target: https://travis-ci.com/quantling/pyndl
        
        .. image:: https://coveralls.io/repos/github/quantling/pyndl/badge.svg?branch=master
            :target: https://coveralls.io/github/quantling/pyndl?branch=master
        
        .. image:: https://img.shields.io/lgtm/grade/python/g/quantling/pyndl.svg?logo=lgtm&logoWidth=18
            :target: https://lgtm.com/projects/g/quantling/pyndl/context:python
        
        .. image:: https://img.shields.io/pypi/pyversions/pyndl.svg
            :target: https://pypi.python.org/pypi/pyndl/
        
        .. image:: https://img.shields.io/github/license/quantling/pyndl.svg
            :target: https://github.com/quantling/pyndl/blob/master/LICENSE.txt
        
        .. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.597964.svg
           :target: https://doi.org/10.5281/zenodo.597964
        
        *pyndl* is an implementation of Naive Discriminative Learning in Python. It was
        created to analyse huge amounts of text file corpora. Especially, it allows to
        efficiently apply the Rescorla-Wagner learning rule to these corpora.
        
        
        Installation
        ============
        
        The easiest way to install *pyndl* is using
        `pip <https://pip.pypa.io/en/stable/>`_:
        
        .. code:: bash
        
            pip install --user pyndl
        
        For more information have a look at the `Installation Guide
        <http://pyndl.readthedocs.io/en/latest/installation.html>`_.
        
        
        Documentation
        =============
        
        *pyndl* uses ``sphinx`` to create a documentation manual. The documentation is
        hosted on `Read the Docs <http://pyndl.readthedocs.io/en/latest/>`_.
        
        
        Getting involved
        ================
        
        The *pyndl* project welcomes help in the following ways:
        
        * Making Pull Requests for
          `code <https://github.com/quantling/pyndl/tree/master/pyndl>`_,
          `tests <https://github.com/quantling/pyndl/tree/master/tests>`_
          or `documentation <https://github.com/quantling/pyndl/tree/master/doc>`_.
        * Commenting on `open issues <https://github.com/quantling/pyndl/issues>`_
          and `pull requests <https://github.com/quantling/pyndl/pulls>`_.
        * Helping to answer `questions in the issue section
          <https://github.com/quantling/pyndl/labels/question>`_.
        * Creating feature requests or adding bug reports in the `issue section
          <https://github.com/quantling/pyndl/issues/new>`_.
        
        For more information on how to contribute to *pyndl* have a look at the
        `development section <http://pyndl.readthedocs.io/en/latest/development.html>`_.
        
        
        Authors and Contributers
        ========================
        
        *pyndl* was mainly developed by
        `Konstantin Sering <https://github.com/derNarr>`_,
        `Marc Weitz <https://github.com/trybnetic>`_,
        `David-Elias Künstle <https://github.com/dekuenstle/>`_
        and `Lennart Schneider <https://github.com/sumny>`_. For the full list of
        contributers have a look at `Github's Contributor summary
        <https://github.com/quantling/pyndl/contributors>`_.
        
        Currently, it is maintained by `Konstantin Sering <https://github.com/derNarr>`_
        and `Marc Weitz <https://github.com/trybnetic>`_.
        
        
        Acknowledgments
        ===============
        This research was supported by an ERC advanced Grant (no. 742545) and by the
        Alexander von Humboldt Professorship awarded to R. H. Baayen and by the
        University of Tübingen.
        
        
Platform: Linux
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: Console
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: POSIX :: Linux
Classifier: Operating System :: MacOS
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Provides-Extra: tests
Provides-Extra: docs
