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) 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.