Skip to main content

Naive discriminative learning implements learning and classification models based on the Rescorla-Wagner equations.

Project description

https://travis-ci.org/quantling/pyndl.svg?branch=master Code Health https://coveralls.io/repos/github/quantling/pyndl/badge.svg?branch=master https://img.shields.io/pypi/pyversions/pyndl.svg https://img.shields.io/github/license/quantling/pyndl.svg https://zenodo.org/badge/80022085.svg

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:

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 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.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pyndl-0.4.1.tar.gz (531.0 kB view details)

Uploaded Source

File details

Details for the file pyndl-0.4.1.tar.gz.

File metadata

  • Download URL: pyndl-0.4.1.tar.gz
  • Upload date:
  • Size: 531.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for pyndl-0.4.1.tar.gz
Algorithm Hash digest
SHA256 b0795bbf91e755aca253353d3d1a2fcb95c37dc1b0ed5fd7dd376bb06b520da0
MD5 9558c1c285ddb331c9ccf5d420c3dc9f
BLAKE2b-256 bd9bece99b6c6c7da2f63c607e86eb13bc299fc26b22d560f6747d17cbf7e2d3

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page