vectorize.words: Word vectorization

In fdm2id: Data Mining and R Programming for Beginners

Word vectorization

Description

Vectorize words from a corpus of documents.

Usage

vectorize.words(
  corpus = NULL,
  ndim = 50,
  maxwords = NULL,
  mincount = 5,
  minphrasecount = NULL,
  window = 5,
  maxcooc = 10,
  maxiter = 10,
  epsilon = 0.01,
  lang = "en",
  stopwords = lang,
  ...
)

Arguments

corpus	The corpus of documents (a vector of characters).
ndim	The number of dimensions of the vector space.
maxwords	The maximum number of words.
mincount	Minimum word count to be considered as frequent.
minphrasecount	Minimum collocation of words count to be considered as frequent.
window	Window for term-co-occurence matrix construction.
maxcooc	Maximum number of co-occurrences to use in the weighting function.
maxiter	The maximum number of iteration to fit the GloVe model.
epsilon	Defines early stopping strategy when fit the GloVe model.
lang	The language of the documents (NULL if no stemming).
stopwords	Stopwords, or the language of the documents. NULL if stop words should not be removed.
...	Other parameters.

Value

The vectorized words.

See Also

query.words, stopwords, vectorizers

Examples

## Not run: 
text = loadtext ("http://mattmahoney.net/dc/text8.zip")
words = vectorize.words (text, minphrasecount = 50)
query.words (words, origin = "paris", sub = "france", add = "germany")
query.words (words, origin = "berlin", sub = "germany", add = "france")
query.words (words, origin = "new_zealand")

## End(Not run)

fdm2id documentation built on July 9, 2023, 6:05 p.m.