Package: lda 1.5.2

lda: 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.

Authors:Jonathan Chang

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lda.pdf |lda.html✨
lda/json (API)

Peer review:

Bug tracker:https://github.com/solivella/lda/issues

On CRAN:

22 exports 3.74 score 0 dependencies 10 dependents 15 mentions 484 scripts 3.8k downloads

Last updated 5 months agofrom:62c5e3a614. Checks:OK: 1 WARNING: 8. Indexed: yes.

Exports:concatenate.documentsdocument.lengthsfilter.wordslda.collapsed.gibbs.samplerlda.cvb0lexicalizelinks.as.edgelistmmsb.collapsed.gibbs.samplernubbi.collapsed.gibbs.samplerpredictive.distributionpredictive.link.probabilityread.documentsread.vocabrtm.collapsed.gibbs.samplerrtm.emshift.word.indicesslda.emslda.predictslda.predict.docsumstop.topic.documentstop.topic.wordsword.counts

Dependencies: