quanteda.textmodels: Scaling Models and Classifiers for Textual Data (original) (raw)
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: | 0.9.9 |
---|---|
Depends: | R (≥ 3.1.0), methods |
Imports: | glmnet, LiblineaR, Matrix (≥ 1.2), quanteda (≥ 4.0.0), RSpectra, Rcpp (≥ 0.12.12), SparseM, stringi |
LinkingTo: | Rcpp, RcppArmadillo (≥ 0.7.600.1.0), quanteda |
Suggests: | ca, covr, fastNaiveBayes, knitr, lsa, microbenchmark, naivebayes, quanteda.textplots, spelling, testthat, rmarkdown |
Published: | 2024-09-03 |
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 |
License: | GPL-3 |
URL: | https://github.com/quanteda/quanteda.textmodels |
NeedsCompilation: | yes |
Language: | en-GB |
Materials: | README NEWS |
CRAN checks: | quanteda.textmodels results |
Documentation:
Downloads:
Reverse dependencies:
Linking:
Please use the canonical formhttps://CRAN.R-project.org/package=quanteda.textmodelsto link to this page.