topicmodels v0.2-8

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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.

Functions in topicmodels

Name Description
ldaformat2dtm Transform data from and for use with the lda package
TopicModelcontrol-class Different classes for controlling the estimation of topic models
LDA Latent Dirichlet Allocation
logLik-methods Methods for Function logLik
terms_and_topics Extract most likely terms or topics.
AssociatedPress Associated Press data
perplexity Methods for Function perplexity
CTM Correlated Topic Model
build_graph Construct the adjacency matrix for a topic graph
distHellinger Compute Hellinger distance
posterior-methods Determine posterior probabilities
TopicModel-class Virtual class "TopicModel"
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Vignettes of topicmodels

Name
topicmodels.Rnw
topicmodels.bib
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Details

Type Package
Additional_repositories https://datacube.wu.ac.at
SystemRequirements GNU Scientific Library version >= 1.8, C++11
License GPL-2
Encoding UTF-8
LazyLoad yes
NeedsCompilation yes
Packaged 2018-12-21 09:57:50 UTC; hornik
Repository CRAN
Date/Publication 2018-12-21 12:03:10 UTC

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