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) <doi:10.48550/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.
Version: 0.9.10 Depends: R (≥ 3.1.0), methods Imports: glmnet, Matrix (≥ 1.2), quanteda (≥ 4.0.0), RSpectra, Rcpp (≥ 0.12.12), stringi LinkingTo: Rcpp, RcppArmadillo (≥ 0.7.600.1.0), quanteda Suggests: ca, covr, fastNaiveBayes, knitr, lsa, microbenchmark, naivebayes, quanteda.textplots, spelling, testthat, rmarkdown Published: 2025-02-10 DOI: 10.32614/CRAN.package.quanteda.textmodels Author: Kenneth Benoit [cre, aut, cph], Kohei Watanabe [aut], Haiyan Wang [aut], Patrick O. Perry [aut], Benjamin Lauderdale [aut], Johannes Gruber [aut], William Lowe [aut], Vikas Sindhwani [cph] (authored svmlin C++ source code), European Research Council [fnd] (ERC-2011-StG 283794-QUANTESS) Maintainer: Kenneth Benoit <kbenoit at quanteda.org> License: GPL-3 URL: https://github.com/quanteda/quanteda.textmodels NeedsCompilation: yes Language: en-GB Materials: README NEWS CRAN checks: quanteda.textmodels resultsRetroSearch is an open source project built by @garambo | Open a GitHub Issue
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