https://github.com/davidandrzej/cvbLDA

Collapsed variational Bayesian inference for LDA
https://github.com/davidandrzej/cvbLDA

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Collapsed variational Bayesian inference for LDA

• Host: GitHub
• URL: https://github.com/davidandrzej/cvbLDA
• Owner: davidandrzej
• Created: 2011-11-05T21:35:56.000Z (about 13 years ago)
• Default Branch: master
• Last Pushed: 2011-11-05T21:39:18.000Z (about 13 years ago)
• Last Synced: 2024-08-03T18:21:51.370Z (5 months ago)
• Language: C
• Homepage:
• Size: 97.7 KB
• Stars: 21
• Watchers: 4
• Forks: 5
• Open Issues: 0
• Metadata Files:
  • Readme: README

Awesome Lists containing this project

• awesome-topic-models - cvbLDA - Python C extension implementation of collapsed variational Bayesian inference for LDA (Research Implementations / Embedding based Topic Models)

README

        
COLLAPSED VARIATIONAL BAYESIAN INFERENCE FOR

LATENT DIRICHLET ALLOCATION (CVB-LDA)

Version 0.1

David Andrzejewski ([email protected])

Department of Computer Sciences

University of Wisconsin-Madison, USA

This software implements Collapsed Variational Bayesian (CVB)

inference [1] for the LDA model [2] of discrete count data.  The code

is based on the Teh et al paper [1], but also uses some practical

implementation details kindly provided by the authors on the extremely

helpful topic-models mailing list:

https://lists.cs.princeton.edu/mailman/listinfo/topic-models

The code implements the collapsed variational inference for LDA as a

Python C extension module.

DISCLAIMER

Importantly, I wrote this code as an educational exercise for *my own

benefit only*. This software has no connection with [1] or its authors

whatsoever. Any errors contained herein are my own.

BUILD/INSTALL

Building this module requires installation of Python and NumPy, as

well as a C compiler.  From the command-line, do:

% python setup.py install

(Note that if NumPy or Python are installed to non-standard locations,

you may need to make the appropriate changes in setup.py)

You can then test the installation with:

% python test/testCvbLDA.py -v

There is also a simple example scipt showing how to use the software:

% python example.py

LOCAL INSTALL

If you do not have write access to your Python installation directories,

you will need to tell setup.py to install this module somewhere else.

For example:

% python setup.py install --prefix=~/local

will install the module under a subdirectory of your home directory called 

"local".

It may then be necessary to let Python know where that is by setting

the PYTHONPATH environment variable (e.g., in .bashrc or .cshrc).  For

our example this might involve adding something like the line:

setenv PYTHONPATH ~/local/lib/python2.5/site-packages

HOW TO USE

The commenting in the example.py script explains the meanings and

types of all input and return arguments.  For more detailed examples

of good/bad inputs, you can examine the tests in test/testCvbLDA.py.

LICENSE

This software is open-source, released under the terms of the GNU

General Public License version 3, or any later version of the GPL (see

LICENSE.txt).

REFERENCES

[1] 

A Collapsed Variational Bayesian Inference Algorithm for Latent Dirichlet Allocation 

Teh Y.W., Newman D., and Welling, M.

Advances in Neural Information Processing Systems (NIPS) 19, 2007.

[2] 

Latent Dirichlet Allocation

Blei, D. M., Ng, A. Y., and Jordan, M. I. 

Journal of Machine Learning Research (JMLR), 3, Mar. 2003, 993-1022.

VERSION HISTORY

0.1     Initial release

0.1.1   Return (phi,theta,gamma) instead of just (phi,theta)

        gamma is a length D List of T x Md NumPy arrays