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model argument to
textmodel_word2vec() to update existing models.normalize argument is moved from
textmodel_word2vec() to as.matrix(). The
original argument is deprecated and set to FALSE by
default.weights().tolower argument and set to TRUE
to lower-case tokens.x to be quanteda’s tokens_xptr object to enhance
efficiency.textmodel_doc2vec objects.textmodel_doc2vec
objects.probability() to compute probability of words.word2vec(), doc2vec() and
lsa() to textmodel_word2vec(),
textmodel_doc2vec() and textmodel_lsa()
respectively.normalize to word2vec to disable or
enable word vector normalization.weights() to extract back-propagation weights.analogy() to convert a formula to named character
vector.word2vec() when
verbose = TRUE.word2vec() with new argument names and object
structures.lda() to train word vectors using Latent
Semantic Analysis.similarity() and analogy() functions
using proxyC.data_corpus_news2014 that contain 20,000 news
summaries as package data.These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.