M = word2vec(emb,words)
returns the embedding vectors of words in the embedding
emb. If a word is not in the embedding vocabulary, then the
function returns a row of NaNs.
Load a pretrained word embedding using fastTextWordEmbedding. This function requires Text Analytics Toolbox™ Model for fastText English 16 Billion Token Word Embedding support package. If this support package is not installed, then the function provides a download link.
emb = fastTextWordEmbedding
emb =
wordEmbedding with properties:
Dimension: 300
Vocabulary: [1×1000000 string]
Map the words "Italy", "Rome", and "Paris" to vectors using word2vec.
italy = word2vec(emb,"Italy");
rome = word2vec(emb,"Rome");
paris = word2vec(emb,"Paris");
Map the vector italy - rome + paris to a word using vec2word.
Input word embedding, specified as a wordEmbedding object.
words — Input words string vector | character vector | cell array of character vectors
Input words, specified as a string vector, character vector, or cell array of character
vectors. If you specify words as a character vector, then the
function treats the argument as a single word.