pyndl 1.2.3

Description:

pyndl 1.2.3

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:
pip install --user pyndl
For more information have a look at the Installation Guide.


Documentation
pyndl uses sphinx to create a documentation manual. The documentation is
hosted on Read the Docs.


Getting involved
The pyndl project welcomes help in the following ways:

Making Pull Requests for
code,
tests
or documentation.
Commenting on open issues
and pull requests.
Helping to answer questions in the issue section.
Creating feature requests or adding bug reports in the issue section.

For more information on how to contribute to pyndl have a look at the
development section.


Authors and Contributers
pyndl was mainly developed by
Konstantin Sering,
Marc Weitz,
David-Elias Künstle,
Elnaz Shafaei Bajestan
and Lennart Schneider. For the full list of
contributers have a look at Github’s Contributor summary.
Currently, it is maintained by Konstantin Sering
and Marc Weitz.

Funding
pyndl was partially funded by the Humboldt grant, the ERC advanced grant (no.
742545) and by the University of Tübingen.


Acknowledgements
This package is build as a python replacement for the R ndl2 package. Some
ideas on how to build the API and how to efficiently run the Rescorla Wagner
iterative learning on large text corpora are inspired by the way the ndl2
package solves this problems. The ndl2 package is available on Github here.