Metadata-Version: 2.0
Name: simple-lda
Version: 0.1.3
Summary: Python library for Latent Dirichlet allocation (lda)
Home-page: https://github.com/Sylhare/simple-lda
Author: sylhare
Author-email: sylhare@outlook.com
License: Apache License 2.0
Description-Content-Type: UNKNOWN
Platform: any
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.5
Classifier: Environment :: Other Environment
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Education
Classifier: Natural Language :: English
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Text Processing
Classifier: Topic :: Utilities

simple-lda
==========

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Latent Dirichlet allocation (LDA) is a topic model that generates topics
based on word frequency from a set of documents. LDA is particularly
useful for finding reasonably accurate mixtures of topics within a given
document set.

Installation
------------

The library is available on PyPI:

::

        pip install simple-lda

Sources
-------

-  `Edwin Chen Introduction to latent Dirichlet
   Allocation <http://blog.echen.me/2011/08/22/introduction-to-latent-dirichlet-allocation/>`__
-  `Jordan Barder LDA with Python
   walkthrough <https://rstudio-pubs-static.s3.amazonaws.com/79360_850b2a69980c4488b1db95987a24867a.html>`__
-  `Gensim library for lda based on M Hoffman's
   paper <https://radimrehurek.com/gensim/models/ldamodel.html>`__
-  `Snowball for Porter stemming
   algorithm <http://snowball.tartarus.org/algorithms/english/stemmer.html>`__
-  `Bird, Steven, Edward Loper and Ewan Klein (2009), Natural Language
   Processing with Python. O’Reilly Media
   Inc <http://www.nltk.org/index.html>`__

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