Description Usage Arguments See Also Examples
Returns num.words
-most probable words for each topic in the LDA
model learned for a corpus
1 | calc_top_topic_words(beta, vocab, num.words = 30, num.digits = 2)
|
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 |
lda_fgs
, lda_acgs
, lda_fgs_blei_corpus
1 | calc_top_topic_words(beta, vocab, num.words=30, num.digits=2)
|
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