calc_top_topic_words: Gets the most probable topical words

In clintpgeorge/ldamcmc: Markov chain Monte Carlo Algorithms for the Latent Dirichlet Allocation Model

Description

Returns num.words-most probable words for each topic in the LDA model learned for a corpus

Usage

calc_top_topic_words(beta, vocab, num.words = 30, num.digits = 2)

Arguments

beta	the β matrix in the LDA model, which is obtained from any LDA Gibbs sampler
vocab	the terms in the corpus vocabulary as a list. This should follow the same order of beta
num.words	the number of most probabale words to display. The default is 30 words.
num.digits	the number of decimal digits to be displayed for the probabilities

See Also

lda_fgs, lda_acgs, lda_fgs_blei_corpus

Examples

calc_top_topic_words(beta, vocab, num.words=30, num.digits=2)
              
 

clintpgeorge/ldamcmc documentation built on Feb. 22, 2020, 12:39 p.m.