lda (1.4.2)

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Collapsed Gibbs Sampling Methods for Topic Models.


Implements latent Dirichlet allocation (LDA) and related models. This includes (but is not limited to) sLDA, corrLDA, and the mixed-membership stochastic blockmodel. Inference for all of these models is implemented via a fast collapsed Gibbs sampler written in C. Utility functions for reading/writing data typically used in topic models, as well as tools for examining posterior distributions are also included.

Maintainer: Jonathan Chang
Author(s): Jonathan Chang

License: LGPL

Uses: Matrix, ggplot2, penalized, nnet, reshape2
Reverse suggests: LDAvis, qdap, quanteda, textmineR, topicmodels

Released over 4 years ago.

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