Codestin Search App

This fork is intended to extend lda to a form of disclda.

It amounts to a simple matrix manipulation of the topic vector for a document for that is based on the label of a document

In DIscLDA, each document has a label $y_d$ and there is a stochastic matrix $T^y$ associated with each label.

Where in vanilla LDA you draw the word topics $z_{d,i} ~ Cat(theta_d)$, in DiscLDA you draw $z_{d,i} ~ Cat(T^{y_d}theta_d)$

Name		Name	Last commit message	Last commit date
Latest commit History 140 Commits
bench		bench
continuous_integration		continuous_integration
disclda		disclda
doc/source		doc/source
.gitignore		.gitignore
.testr.conf		.testr.conf
.travis.yml		.travis.yml
AUTHORS		AUTHORS
CONTRIBUTING.rst		CONTRIBUTING.rst
ChangeLog		ChangeLog
LICENSE		LICENSE
MANIFEST.in		MANIFEST.in
Makefile		Makefile
README.rst		README.rst
appveyor.yml		appveyor.yml
requirements.txt		requirements.txt
setup.cfg		setup.cfg
setup.py		setup.py
test-requirements.txt		test-requirements.txt
tox.ini		tox.ini

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