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Source: simplebayes
Section: python
Priority: optional
Maintainer: Thomas Perret <thomas.perret@phyx.fr>
Build-Depends: debhelper-compat (= 13), dh-python, python3-all, python3-setuptools, python3-mock, python3-sphinx, python3-sphinx-rtd-theme
Standards-Version: 4.5.1
Homepage: https://github.com/hickeroar/simplebayes
Vcs-Browser: https://salsa.debian.org/openpaperwork-team/simplebayes
Vcs-Git: https://salsa.debian.org/openpaperwork-team/simplebayes.git
Rules-Requires-Root: no
Package: python3-simplebayes
Architecture: all
Depends: ${python3:Depends}, ${misc:Depends}
Suggests: python-simplebayes-doc
Description: Naive bayesian text classifier for Python 3
A memory-based, optional-persistence naive bayesian text classifier.
This work is heavily inspired by the Python "redisbayes" module found here:
https://github.com/jart/redisbayes and https://pypi.python.org/pypi/redisbayes
This was written to alleviate the network/time requirements when
using the bayesian classifier to classify large sets of text, or when
attempting to train with very large sets of sample data.
.
This package installs the library for Python 3.
Package: python-simplebayes-doc
Architecture: all
Section: doc
Depends: ${sphinxdoc:Depends}, ${misc:Depends}, libjs-jquery, libjs-underscore
Description: Naive bayesian text classifier - documentation
A memory-based, optional-persistence naive bayesian text classifier.
This work is heavily inspired by the Python "redisbayes" module found here:
https://github.com/jart/redisbayes and https://pypi.python.org/pypi/redisbayes
This was written to alleviate the network/time requirements when
using the bayesian classifier to classify large sets of text, or when
attempting to train with very large sets of sample data.
.
This is the common documentation package.
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