DESCRIPTION

Package: quanteda.textmodels
Type: Package
Title: Scaling Models and Classifiers for Textual Data
Version: 0.9.9
Description: 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.
Authors@R: c( 
    person("Kenneth", "Benoit", email = "kbenoit@lse.ac.uk", role = c("cre", "aut", "cph"), comment = c(ORCID = "0000-0002-0797-564X")), 
    person("Kohei", "Watanabe", email = "watanabe.kohei@gmail.com", role = "aut", comment = c(ORCID = "0000-0001-6519-5265")), 
    person("Haiyan", "Wang", email = "whyinsa@yahoo.com", role = "aut", comment = c(ORCID = "0000-0003-4992-4311")),
    person("Patrick O.", "Perry", email = "patperry@gmail.com", role = "aut", comment = c(ORCID = "0000-0001-7460-127X")),
    person("Benjamin", "Lauderdale", email = "b.e.lauderdale@lse.ac.uk", role = "aut", comment = c(ORCID = "0000-0003-3090-0969")),    
    person("Johannes", "Gruber", email = "JohannesB.Gruber@gmail.com", role = "aut", comment = c(ORCID = "0000-0001-9177-1772")),
    person("William", "Lowe", email = "lowe@hertie-school.org", role = "aut", comment = c(ORCID = "0000-0002-1549-6163")),
    person("Vikas", "Sindhwani", email = "vikas.sindhwani@gmail.com", role = "cph", 
           comment = "authored svmlin C++ source code"),
    person("European Research Council", role = "fnd", comment = "ERC-2011-StG 283794-QUANTESS")
    )
Depends:
    R (>= 3.1.0),
    methods
Imports:
    glmnet,
    LiblineaR,
    Matrix (>= 1.2),
    quanteda (>= 4.0.0),
    RSpectra,
    Rcpp (>= 0.12.12),
    SparseM,
    stringi
Suggests:
    ca,
    covr,
    fastNaiveBayes,
    knitr,
    lsa,
    microbenchmark,
    naivebayes,
    quanteda.textplots,
    spelling,
    testthat,
    rmarkdown
LinkingTo: Rcpp, RcppArmadillo (>= 0.7.600.1.0), quanteda
URL: /~https://github.com/quanteda/quanteda.textmodels
License: GPL-3
Encoding: UTF-8
LazyData: true
Language: en-GB
RoxygenNote: 7.3.2
Roxygen: list(markdown = TRUE)
Collate: 
    'RcppExports.R'
    'quanteda.textmodels-package.R'
    'data-documentation.R'
    'textmodel-methods.R'
    'textmodel_affinity.R'
    'textmodel_ca.R'
    'textmodel_lsa.R'
    'textmodel_lr.R'
    'textmodel_nb.R'
    'textmodel_svm.R'
    'textmodel_svmlin.R'
    'textmodel_wordfish.R'
    'textmodel_wordscores.R'
    'textplot_influence.R'
    'utils.R'
VignetteBuilder: knitr