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topicmodels (version 0.2-9)

Topic Models

Description

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.

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Version

Install

install.packages('topicmodels')

Monthly Downloads

9,388

Version

0.2-9

License

GPL-2

Maintainer

Bettina Gruen

Last Published

December 3rd, 2019

Functions in topicmodels (0.2-9)

distHellinger

Compute Hellinger distance

posterior-methods

Determine posterior probabilities

logLik-methods

Methods for Function logLik

ldaformat2dtm

Transform data from and for use with the lda package

build_graph

Construct the adjacency matrix for a topic graph

CTM

Correlated Topic Model

AssociatedPress

Associated Press data

perplexity

Methods for Function perplexity

terms_and_topics

Extract most likely terms or topics.

LDA

Latent Dirichlet Allocation

TopicModel-class

Virtual class "TopicModel"

TopicModelcontrol-class

Different classes for controlling the estimation of topic models