as.matrix.paragraph2vec: Get the document or word vectors of a paragraph2vec model

In doc2vec: Distributed Representations of Sentences, Documents and Topics

Description

Get the document or word vectors of a paragraph2vec model as a dense matrix.

Usage

## S3 method for class 'paragraph2vec'
as.matrix(
  x,
  which = c("docs", "words"),
  normalize = TRUE,
  encoding = "UTF-8",
  ...
)

Arguments

x	a paragraph2vec model as returned by paragraph2vec or read.paragraph2vec
which	either one of 'docs' or 'words'
normalize	logical indicating to normalize the embeddings. Defaults to TRUE.
encoding	set the encoding of the row names to the specified encoding. Defaults to 'UTF-8'.
...	not used

Value

a matrix with the document or word vectors where the rownames are the documents or words upon which the model was trained

See Also

paragraph2vec, read.paragraph2vec

Examples

library(tokenizers.bpe)
data(belgium_parliament, package = "tokenizers.bpe")
x <- subset(belgium_parliament, language %in% "french")
x <- subset(x, nchar(text) > 0 & txt_count_words(text) < 1000)

model <- paragraph2vec(x = x, type = "PV-DM",   dim = 15,  iter = 5)

model <- paragraph2vec(x = x, type = "PV-DBOW", dim = 100, iter = 20)


embedding <- as.matrix(model, which = "docs")
embedding <- as.matrix(model, which = "words")
embedding <- as.matrix(model, which = "docs", normalize = FALSE)
embedding <- as.matrix(model, which = "words", normalize = FALSE)

doc2vec documentation built on March 28, 2021, 1:09 a.m.