vectorizers
From text2vec v0.3.0
by Dmitriy Selivanov
Vocabulary and hash vectorizers
This function creates a text vectorizer function which is used in constructing a corpus.
Usage
vocab_vectorizer(vocabulary, grow_dtm = TRUE, skip_grams_window = 0L)
hash_vectorizer(hash_size = 2^18, ngram = c(1L, 1L), signed_hash = FALSE, grow_dtm = TRUE, skip_grams_window = 0L)
Arguments
- vocabulary
text2vec_vocabulary
object, see create_vocabulary.- grow_dtm
logical
Should we grow the document-term matrix during corpus construction or not.- skip_grams_window
integer
window for term-co-occurence matrix construction. A value of0L
does not construct the TCM.- hash_size
integer
The number of of hash-buckets for the feature hashing trick. The number must be greater than 0, and preferably it will be a power of 2.- ngram
integer
vector. The lower and upper boundary of the range of n-values for different n-grams to be extracted. All values ofn
such that ngram_min- signed_hash
logical
, indicating whether to use a signed hash-function to reduce collisions when hashing.
Value
-
A vectorizer
function
See Also
Examples
data("movie_review")
N <- 100
vectorizer <- hash_vectorizer(2 ^ 18, c(1L, 2L))
it <- itoken(movie_review$review[1:N], preprocess_function = tolower,
tokenizer = word_tokenizer, chunks_number = 10)
corpus <- create_corpus(it, vectorizer)
hash_dtm <- get_dtm(corpus)
it <- itoken(movie_review$review[1:N], preprocess_function = tolower,
tokenizer = word_tokenizer, chunks_number = 10)
v <- create_vocabulary(it, c(1L, 1L) )
vectorizer <- vocab_vectorizer(v)
it <- itoken(movie_review$review[1:N], preprocess_function = tolower,
tokenizer = word_tokenizer, chunks_number = 10)
corpus <- create_corpus(it, vectorizer)
voacb_dtm <- get_dtm(corpus)
Community examples
Looks like there are no examples yet.