model_logentropy: Log Entropy Model
In news-r/gensimr: Topic Modelling

This module allows simple Bag of Words (BoW) represented corpus to be transformed into log entropy space. It implements Log Entropy Model that produces entropy-weighted logarithmic term frequency representation.

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model_logentropy(corpus, normalize = FALSE)

load_logentropy(file)

`corpus`	Model as returned by `doc2bow`.
`normalize`	If `TRUE`, the resulted log entropy weighted vector will be normalized to length of 1, If `FALSE` - do nothing.
`file`	Path to a saved model.

docs <- prepare_documents(corpus)
dictionary <- corpora_dictionary(docs)
corpora <- doc2bow(dictionary, docs)

# fit model
log_entropy <- model_logentropy(corpora)
wrap(log_entropy, corpora)