NEWS.md

In wordvector: Word and Document Vector Models

Changes in v0.3.0

• Save docvars in the textmodel_doc2vec objects.
• Set zero for empty documents in the textmodel_doc2vec objects.
• Add probability() to compute probability of words.

Changes in v0.2.0

• Rename word2vec(), doc2vec() and lsa() to textmodel_word2vec(), textmodel_doc2vec() and textmodel_lsa() respectively.
• Simplify the C++ code to make maintenance easier.
• Add normalize to word2vec to disable or enable word vector normalization.
• Add weights() to extract back-propagation weights.
• Make analogy() to convert a formula to named character vector.
• Improve the stability of word2vec() when verbose = TRUE.

Changes in v0.1.0

• Fork https://github.com/bnosac/word2vec and change the package name to wordvector.
• Replace a list of character with quanteda's tokens object as an input object.
• Recreate word2vec() with new argument names and object structures.
• Create lda() to train word vectors using Latent Semantic Analysis.
• Add similarity() and analogy() functions using proxyC.
• Add data_corpus_news2014 that contain 20,000 news summaries as package data.

wordvector documentation built on April 12, 2025, 2:23 a.m.