Transform words (or sequences of words) to vectors using a word2vec model.
Transform words (or sequences of words) to vectors using a word2vec model.
## S4 method for signature 'H2OWordEmbeddingModel'
h2o.transform(model, words, aggregate_method = c("NONE", "AVERAGE"))model |
A word2vec model. |
words |
An H2OFrame made of a single column containing source words. |
aggregate_method |
Specifies how to aggregate sequences of words. If method is 'NONE' then no aggregation is performed and each input word is mapped to a single word-vector. If method is 'AVERAGE' then input is treated as sequences of words delimited by NA. Each word of a sequences is internally mapped to a vector and vectors belonging to the same sentence are averaged and returned in the result. |
## Not run:
h2o.init()
# Build a simple word2vec model
data <- as.character(as.h2o(c("a", "b", "a")))
w2v_model <- h2o.word2vec(data, sent_sample_rate = 0, min_word_freq = 0, epochs = 1, vec_size = 2)
# Transform words to vectors without aggregation
sentences <- as.character(as.h2o(c("b", "c", "a", NA, "b")))
h2o.transform(w2v_model, sentences) # -> 5 rows total, 2 rows NA ("c" is not in the vocabulary)
# Transform words to vectors and return average vector for each sentence
h2o.transform(w2v_model, sentences, aggregate_method = "AVERAGE") # -> 2 rows
## End(Not run)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.