# Modern Text Mining Framework for R

## Documentation for package ‘text2vec’ version 0.4.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

text2vec-package | text2vec
as.lda_c | Converts document-term matrix sparse matrix to 'lda_c' format
char_tokenizer | Simple tokenization functions, which performs string splitting
check_analogy_accuracy | Checks accuracy of word embeddings on the analogy task
create_corpus | Create a corpus
create_dtm | Document-term matrix construction
create_dtm.itoken | Document-term matrix construction
create_dtm.list | Document-term matrix construction
create_tcm | Term-co-occurence matrix construction
create_tcm.itoken | Term-co-occurence matrix construction
create_tcm.list | Term-co-occurence matrix construction
create_vocabulary | Creates a vocabulary of unique terms
create_vocabulary.character | Creates a vocabulary of unique terms
create_vocabulary.itoken | Creates a vocabulary of unique terms
create_vocabulary.list | Creates a vocabulary of unique terms
dist2 | Pairwise Distance Matrix Computation
distances | Pairwise Distance Matrix Computation
fit | Fits model to data
fit.Matrix | Fits model to data
fit.matrix | Fits model to data
fit_transform | Fit model to data, then transform it
fit_transform.Matrix | Fit model to data, then transform it
fit_transform.matrix | Fit model to data, then transform it
get_dtm | Extract document-term matrix
get_idf | Inverse document-frequency scaling matrix
get_tcm | Extract term-co-occurence matrix
get_tf | Term-frequency scaling matrix
GlobalVectors | Creates Global Vectors word-embeddings model.
GloVe | Creates Global Vectors word-embeddings model.
glove | Fit a GloVe word-embedded model
hash_vectorizer | Vocabulary and hash vectorizers
idir | Creates iterator over text files from the disk
ifiles | Creates iterator over text files from the disk
itoken | Iterators over input objects
itoken.character | Iterators over input objects
itoken.iterator | Iterators over input objects
itoken.list | Iterators over input objects
LatentDirichletAllocation | Creates Latent Dirichlet Allocation model.
LatentSemanticAnalysis | Latent Semantic Analysis model
LDA | Creates Latent Dirichlet Allocation model.
LSA | Latent Semantic Analysis model
movie_review | IMDB movie reviews
normalize | Matrix normalization
pdist2 | Pairwise Distance Matrix Computation
prepare_analogy_questions | Prepares list of analogy questions
prune_vocabulary | Prune vocabulary
psim2 | Pairwise Similarity Matrix Computation
regexp_tokenizer | Simple tokenization functions, which performs string splitting
RelaxedWordMoversDistance | Creates model which can be used for calculation of "relaxed word movers distance".
RWMD | Creates model which can be used for calculation of "relaxed word movers distance".
sim2 | Pairwise Similarity Matrix Computation
similarities | Pairwise Similarity Matrix Computation
space_tokenizer | Simple tokenization functions, which performs string splitting
split_into | Split a vector for parallel processing
text2vec | text2vec
TfIdf | TfIdf
tokenizers | Simple tokenization functions, which performs string splitting
transform | Transforms Matrix-like object using 'model'
transform.Matrix | Transforms Matrix-like object using 'model'
transform.matrix | Transforms Matrix-like object using 'model'
transform_binary | Scale a document-term matrix
transform_filter_commons | Remove terms from a document-term matrix
transform_tf | Scale a document-term matrix
transform_tfidf | Scale a document-term matrix
vectorizers | Vocabulary and hash vectorizers
vocabulary | Creates a vocabulary of unique terms
vocab_vectorizer | Vocabulary and hash vectorizers
word_tokenizer | Simple tokenization functions, which performs string splitting