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topicmodels (version 0.1-1)

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

11,229

Version

0.1-1

License

GPL-2

Maintainer

Bettina Gruen

Last Published

September 6th, 2011

Functions in topicmodels (0.1-1)

build_graph

Construct the adjacency matrix for a topic graph

TopicModel-class

Virtual class "TopicModel"

ldaformat2dtm

Transform data from and for use with the lda package

perplexity

Methods for Function perplexity

AssociatedPress

Associated Press data

distHellinger

Compute Hellinger distance

LDA

Latent Dirichlet Allocation

CTM

Correlated Topic Model

posterior-methods

Determine posterior probabilities

terms_and_topics

Extract most likely terms or topics.

TopicModelcontrol-class

Different classes for controlling the estimation of topic models

logLik-methods

Methods for Function logLik

terms/topics

Extract most likely terms or topics.