quanteda.textmodels
Scaling Models and Classifiers for Textual Data
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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.9.10 |
rolling source/ R- | quanteda.textmodels_0.9.10.tar.gz |
2.8 MiB |
0.9.10 |
latest source/ R- | quanteda.textmodels_0.9.10.tar.gz |
2.8 MiB |
0.9.10 |
2026-04-23 source/ R- | quanteda.textmodels_0.9.10.tar.gz |
2.8 MiB |
0.9.10 |
2026-04-09 windows/windows R-4.5 | quanteda.textmodels_0.9.10.zip |
4.3 MiB |