Description:

This software implements the Dirichlet Forest (DF) Prior within the Latent Dirichlet Allocation (LDA) model. When combined with LDA, the Dirichlet Forest Prior allows the user to encode domain knowledge (must-links and cannot-links between words) into the prior on topic-word multinomials. The inference method is Collapsed Gibbs sampling. This code can also be used to do "standard" LDA by applying no domain knowledge, or setting the "strength" parameter eta to 1.

Changes to previous version:

Initial Announcement on mloss.org.

BibTeX Entry: Download

Corresponding Paper BibTeX Entry: Download

Supported Operating Systems: Linux

Data Formats: Svmlight, Ascii

Tags: Python, Topic Analysis, Topic Modeling

Archive: download here

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