Movatterモバイル変換


[0]ホーム

URL:


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.

Version:1.5.2
Depends:R (≥ 4.3.0)
Imports:methods (≥ 4.3.0)
Suggests:Matrix,reshape2,ggplot2 (≥ 3.4.4),penalized,nnet
Published:2024-04-27
DOI:10.32614/CRAN.package.lda
Author:Jonathan Chang
Maintainer:Santiago Olivella <olivella at unc.edu>
License:LGPL-2.1 |LGPL-3 [expanded from: LGPL (≥ 2.1)]
NeedsCompilation:yes
Materials:README
In views:NaturalLanguageProcessing
CRAN checks:lda results

Documentation:

Reference manual:lda.html ,lda.pdf

Downloads:

Package source: lda_1.5.2.tar.gz
Windows binaries: r-devel:lda_1.5.2.zip, r-release:lda_1.5.2.zip, r-oldrel:lda_1.5.2.zip
macOS binaries: r-release (arm64):lda_1.5.2.tgz, r-oldrel (arm64):lda_1.5.2.tgz, r-release (x86_64):lda_1.5.2.tgz, r-oldrel (x86_64):lda_1.5.2.tgz
Old sources: lda archive

Reverse dependencies:

Reverse imports:ldaPrototype,NetMix,stm,tosca
Reverse suggests:LDAvis,qdap,sentopics,textmineR,topicmodels
Reverse enhances:quanteda

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=ldato link to this page.


[8]ページ先頭

©2009-2025 Movatter.jp