TopicModel-class {topicmodels} | R Documentation |
Fitted topic models.
Objects of class "LDA"
are returned by LDA()
and
of class "CTM"
by CTM()
.
Class "TopicModel"
contains
call
:"call"
Dim
:"integer"
; number of
documents and terms.control
:"TopicModelcontrol"
;
options using for estimating the topic model.k
:"integer"
; number of
topics.terms
:documents
:beta
:"matrix"
; parameters of
the word distribution for each topic.gamma
:"matrix"
; parameters for
the posterior topic distribution for each document.wordassignments
:"simple_triplet_matrix"
; most probable topic for each
observed word in each document.
Class "VEM"
contains
loglikelihood
:"numeric"
; the
log likelihood of each document given the parameters for the topic
distribution and for the word distribution of each topic is
approximated using the variational parameters and underestimates
the log likelihood by the Kullback-Leibler divergence between the
variational posterior probability and the true posterior
probability
Class "LDA"
extends class "TopicModel"
and has the additional
slots
alpha
:"numeric"
; parameter of
the Dirichlet distribution for topics over documents.
Class "LDA_Gibbs"
extends class "LDA"
and has
the additional slots
delta
:"numeric"
; parameter for
the prior distribution of the words distribution for topics.
Class "CTM"
extends class "TopicModel"
and has the additional
slots
mu
:"numeric"
; mean of the
topic distribution on the logit scale.Sigma
:"matrix"
;
variance-covariance matrix of topics on the logit scale.
Class "CTM_VEM"
extends classes "CTM"
and
"VEM"
and has the additional
slots
nusqared
:"matrix"
; variance of the
variational distribution on the mu.Bettina Gruen