R Graphical Manual

Last data update: 2014.03.03

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TopicModelcontrol-class (Package: topicmodels) : Different classes for controlling the estimation of topic models

Classes to control the estimation of topic models which are inheriting from the virtual base class "TopicModelcontrol".

● Data Source: CranContrib
● Keywords: classes
● Alias: CTM_VEMcontrol-class, LDA_Gibbscontrol-class, LDA_VEMcontrol-class, LDAcontrol-class, OPTcontrol-class, TopicModelcontrol-class, coerce,NULL,CTM_VEMcontrol-method, coerce,NULL,LDA_VEMcontrol-method, coerce,NULL,LDcontrol-method, coerce,NULL,OPTcontrol-method, coerce,list,CTM_VEMcontrol-method, coerce,list,LDA_VEMcontrol-method, coerce,list,OPTcontrol-method
● 0 images

distHellinger (Package: topicmodels) : Compute Hellinger distance

The Hellinger distance between the rows of two data matrices are determined or if the second argument is missing between the rows of one data matrix.

● Data Source: CranContrib
● Keywords: cluster
● Alias: distHellinger, distHellinger.default, distHellinger.simple_triplet_matrix
● 0 images

posterior-methods (Package: topicmodels) : Determine posterior probabilities

Determine the posterior probabilities of the topics for each document and of the terms for each topic for a fitted topic model.

● Data Source: CranContrib
● Keywords: methods
● Alias: posterior,TopicModel,ANY-method, posterior,TopicModel,missing-method
● 0 images

ldaformat2dtm (Package: topicmodels) : Transform data from and for use with the pkg{lda

Data from the lda package is transformed to a document-term matrix. This data format can be used to fit topic models using package topicmodels.

● Data Source: CranContrib
● Keywords: utilities
● Alias: dtm2ldaformat, ldaformat2dtm
● 0 images

LDA (Package: topicmodels) : Latent Dirichlet Allocation

Estimate a LDA model using for example the VEM algorithm or Gibbs Sampling.

● Data Source: CranContrib
● Keywords: models
● Alias: LDA
● 0 images

TopicModel-class (Package: topicmodels) : Virtual class "TopicModel"

Fitted topic model.

● Data Source: CranContrib
● Keywords: classes
● Alias: CTM-class, LDA-class, TopicModel-class, show,TopicModel-method
● 0 images

CTM (Package: topicmodels) : Correlated Topic Model

Estimate a CTM model using for example the VEM algorithm.

● Data Source: CranContrib
● Keywords: models
● Alias: CTM
● 0 images

build_graph (Package: topicmodels) : Construct the adjacency matrix for a topic graph

The lasso is used to determine which edges are present in a topic graph. The original R code was written by David M. Blei and co-authors and is available together with the C code for fitting the CTM.

● Data Source: CranContrib
● Keywords: dplot
● Alias: build_graph
● 0 images

logLik-methods (Package: topicmodels) : Methods for Function logLik

Compute the log-likelihood.

● Data Source: CranContrib
● Keywords: methods
● Alias: logLik,Gibbs_list-method, logLik,TopicModel-method
● 0 images

perplexity (Package: topicmodels) : Methods for Function perplexity

Determine the perplexity of a fitted model.

● Data Source: CranContrib
● Keywords: methods
● Alias: perplexity, perplexity,ANY,DocumentTermMatrix-method, perplexity,ANY,matrix-method, perplexity,Gibbs,simple_triplet_matrix-method, perplexity,Gibbs_list,simple_triplet_matrix-method, perplexity,VEM,missing-method, perplexity,VEM,simple_triplet_matrix-method, perplexity,list,missing-method, perplexity,list,simple_triplet_matrix-method
● 0 images