Topic Models

Provides an interface to the C code for Latent Dirichlet Allocation (LDA) models and Correlated Topics Models (CTM) by David M. Blei and co-authors and the C++ code for fitting LDA models using Gibbs sampling by Xuan-Hieu Phan and co-authors.


Reference manual

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0.2-11 by Bettina Grün, 5 months ago

Browse source code at

Authors: Bettina Grün [aut, cre] , Kurt Hornik [aut] , David M Blei [ctb, cph] (VEM estimation of LDA and CTM) , John D Lafferty [ctb, cph] (VEM estimation of CTM) , Xuan-Hieu Phan [ctb, cph] (MCMC estimation of LDA) , Makoto Matsumoto [ctb, cph] (Mersenne Twister RNG) , Takuji Nishimura [ctb, cph] (Mersenne Twister RNG) , Shawn Cokus [ctb] (Mersenne Twister RNG)

Documentation:   PDF Manual  

Task views: Natural Language Processing

GPL-2 license

Imports stats4, methods, modeltools, slam, tm

Suggests lasso2, lattice, lda, OAIHarvester, SnowballC, corpus.JSS.papers

System requirements: GNU Scientific Library version >= 1.8, C++11

Imported by LDATS, MoMPCA, ldatuning, oRus, revtools, topicdoc.

Depended on by BullsEyeR.

Suggested by GermaParl, LDAvis, PivotalR, TextMiningGUI, corpustools, oolong, quanteda, textmineR, tidytext, udpipe.

See at CRAN