quanteda.textmodels

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) , 'Wordscores' model, the Perry and 'Benoit' (2017) class affinity scaling model, and the 'Slapin' and 'Proksch' (2008) '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.

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