Efficient Learning of Word Representations and Sentence Classification

An interface to the 'fastText' < https://github.com/facebookresearch/fastText> library for efficient learning of word representations and sentence classification. The 'fastText' algorithm is explained in detail in (i) "Enriching Word Vectors with subword Information", Piotr Bojanowski, Edouard Grave, Armand Joulin, Tomas Mikolov, 2017, ; (ii) "Bag of Tricks for Efficient Text Classification", Armand Joulin, Edouard Grave, Piotr Bojanowski, Tomas Mikolov, 2017, ; (iii) "FastText.zip: Compressing text classification models", Armand Joulin, Edouard Grave, Piotr Bojanowski, Matthijs Douze, Herve Jegou, Tomas Mikolov, 2016, .


Reference manual

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1.0.1 by Lampros Mouselimis, 8 months ago

Browse source code at https://github.com/cran/fastText

Authors: Lampros Mouselimis [aut, cre] , Facebook Inc [cph]

Documentation:   PDF Manual  

MIT + file LICENSE license

Imports Rcpp, ggplot2, grid, utils, glue, data.table, stats

Suggests testthat, covr, knitr, rmarkdown

Linking to Rcpp

System requirements: Generally, fastText builds on modern Mac OS and Linux distributions. Since it uses some C++11 features, it requires a compiler with good C++11 support. These include a (g++-4.7.2 or newer) or a (clang-3.3 or newer).

See at CRAN