Visualise Latent Dirichlet Allocation Models

Visualise Latent Dirichlet Allocation models with pyLDAvis.

prepare_ldavis(model, corpus, dictionary, ...)

show_ldavis(prepared_vis)

# S3 method for pyLDAvis._prepare.PreparedData
show_ldavis(prepared_vis)

plot_ldavis(model, corpus, dictionary)

ldavis_as_html(prepared_vis)

# S3 method for pyLDAvis._prepare.PreparedData
ldavis_as_html(prepared_vis)

Arguments

model	A model as returned by model_lda.
corpus	A corpus as returned by doc2bow.
dictionary	A dictionary as returned by corpora_dictionary.
...	Additional arguments from the official documentation.
prepared_vis	Prepapred vis as returned by prepapre_ldavis.

Details

plot_ldavis is a wrapper around prepapre_ldavis and show_ldavis. Note that a plot method that can be used instead of show_ldavis.

Examples

docs <- prepare_documents(corpus)
#> → Preprocessing 9 documents
#> ← 9 documents after perprocessing
dict <- corpora_dictionary(docs)
corpora <- doc2bow(dict, docs)

# lda model
model <- model_lda(
  corpus = corpora,
  id2word = dict,
  iterations = 50L,
  num_topics = 2L
)

# visualise
vis <- prepare_ldavis(model, corpora, dict)
# NOT RUN {
plot(vis)
# }