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Maybe I don't get how it works, but I am following the example in the package text2vec:
library(text2vec) data("movie_review") N = 500 tokens = word_tokenizer(tolower(movie_review$review[1:N])) it = itoken(tokens, ids = movie_review$id[1:N]) v = create_vocabulary(it) v = prune_vocabulary(v, term_count_min = 5, doc_proportion_max = 0.2) dtm = create_dtm(it, vocab_vectorizer(v)) lda_model = LDA$new(n_topics = 10) doc_topic_distr = lda_model$fit_transform(dtm, n_iter = 20) # run LDAvis visualisation if needed (make sure LDAvis package installed) lda_model$plot()
Notice how for the token "end" the bars are different (one crosses the tick , and the other - does not)
This becomes more obvious if you have few tokens in corpus, then the width changes considerably. Any explanation to this? Thanks!
The text was updated successfully, but these errors were encountered:
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Maybe I don't get how it works, but I am following the example in the package text2vec:
Notice how for the token "end" the bars are different (one crosses the tick , and the other - does not)
This becomes more obvious if you have few tokens in corpus, then the width changes considerably.
Any explanation to this? Thanks!
The text was updated successfully, but these errors were encountered: