textmodels: quanteda.textmodels: Scaling Models and Classifiers for...

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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, Perry and 'Benoit's' (2017) <arXiv:1710.08963> class affinity scaling model, and 'Slapin' and 'Proksch's' (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.

Author(s)

Maintainer: Kenneth Benoit kbenoit@lse.ac.uk (ORCID) [copyright holder]

Authors:

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See Also

Useful links:


quanteda.textmodels documentation built on April 6, 2021, 9:06 a.m.