quanteda.textmodels: Scaling Models and Classifiers for Textual Data

Scaling models and classifiers for sparse matrix objects representing textual data in the form of a document-feature matrix. Includes original implementations of 'Laver', 'Benoit', and Garry's (2003) <doi:10.1017/S0003055403000698>, 'Wordscores' model, the Perry and 'Benoit' (2017) <arXiv:1710.08963> class affinity scaling model, and the 'Slapin' and 'Proksch' (2008) <doi:10.1111/j.1540-5907.2008.00338.x> 'wordfish' model, as well as methods for correspondence analysis, latent semantic analysis, and fast Naive Bayes and linear 'SVMs' specially designed for sparse textual data.

Package details

AuthorKenneth Benoit [cre, aut, cph] (<https://orcid.org/0000-0002-0797-564X>), Kohei Watanabe [aut] (<https://orcid.org/0000-0001-6519-5265>), Haiyan Wang [aut] (<https://orcid.org/0000-0003-4992-4311>), Patrick O. Perry [aut] (<https://orcid.org/0000-0001-7460-127X>), Benjamin Lauderdale [aut] (<https://orcid.org/0000-0003-3090-0969>), Johannes Gruber [aut] (<https://orcid.org/0000-0001-9177-1772>), William Lowe [aut] (<https://orcid.org/0000-0002-1549-6163>), Vikas Sindhwani [cph] (authored svmlin C++ source code), European Research Council [fnd] (ERC-2011-StG 283794-QUANTESS)
MaintainerKenneth Benoit <kbenoit@lse.ac.uk>
URL https://github.com/quanteda/quanteda.textmodels
Package repositoryView on CRAN
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quanteda.textmodels documentation built on March 31, 2023, 8:09 p.m.