tCorpus$lda_fit {corpustools} R Documentation ## Estimate a LDA topic model ### Description Estimate an LDA topic model using the LDA function from the topicmodels package. The parameters other than dtm are simply passed to the sampler but provide a workable default. See the description of that function for more information Usage: ## R6 method for class tCorpus. Use as tc$method (where tc is a tCorpus object).

lda_fit(feature, create_feature=NULL, K=50, num.iterations=500, alpha=50/K,
eta=.01, burnin=250, context_level=c('document','sentence'), ...)


### Arguments

 feature the name of the feature columns create_feature optionally, add a feature column that indicates the topic to which a feature was assigned (in the last iteration). Has to be a character string, that will be the name of the new feature column K the number of clusters num.iterations the number of iterations method set method. see documentation for LDA function of the topicmodels package alpha the alpha parameter eta the eta parameter#' burnin The number of burnin iterations

### Value

A fitted LDA model, and optionally a new column in the tcorpus (added by reference)

### Examples


if (interactive()) {
tc = create_tcorpus(sotu_texts, doc_column = 'id')
tc$preprocess('token', 'feature', remove_stopwords = TRUE, use_stemming = TRUE, min_freq=10) set.seed(1) m = tc$lda_fit('feature', create_feature = 'lda', K = 5, alpha = 0.1)
m
topicmodels::terms(m, 10)
tc\$tokens
}



[Package corpustools version 0.4.10 Index]