Package: quanteda.textmodels 0.9.9
Kenneth Benoit
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.
Authors:
quanteda.textmodels_0.9.9.tar.gz
quanteda.textmodels_0.9.9.zip(r-4.5)quanteda.textmodels_0.9.9.zip(r-4.4)quanteda.textmodels_0.9.9.zip(r-4.3)
quanteda.textmodels_0.9.9.tgz(r-4.4-x86_64)quanteda.textmodels_0.9.9.tgz(r-4.4-arm64)quanteda.textmodels_0.9.9.tgz(r-4.3-x86_64)quanteda.textmodels_0.9.9.tgz(r-4.3-arm64)
quanteda.textmodels_0.9.9.tar.gz(r-4.5-noble)quanteda.textmodels_0.9.9.tar.gz(r-4.4-noble)
quanteda.textmodels_0.9.9.tgz(r-4.4-emscripten)quanteda.textmodels_0.9.9.tgz(r-4.3-emscripten)
quanteda.textmodels.pdf |quanteda.textmodels.html✨
quanteda.textmodels/json (API)
NEWS
| # Install 'quanteda.textmodels' in R: |
| install.packages('quanteda.textmodels', repos = c('https://quanteda.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/quanteda/quanteda.textmodels/issues
- data_corpus_EPcoaldebate - Crowd-labelled sentence corpus from a 2010 EP debate on coal subsidies
- data_corpus_dailnoconf1991 - Confidence debate from 1991 Irish Parliament
- data_corpus_irishbudget2010 - Irish budget speeches from 2010
- data_corpus_moviereviews - Movie reviews with polarity from Pang and Lee
Last updated 4 months agofrom:96c6ae6d6d. Checks:OK: 3 NOTE: 6. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 02 2024 |
| R-4.5-win-x86_64 | OK | Dec 02 2024 |
| R-4.5-linux-x86_64 | OK | Dec 02 2024 |
| R-4.4-win-x86_64 | NOTE | Dec 02 2024 |
| R-4.4-mac-x86_64 | NOTE | Dec 02 2024 |
| R-4.4-mac-aarch64 | NOTE | Dec 02 2024 |
| R-4.3-win-x86_64 | NOTE | Dec 02 2024 |
| R-4.3-mac-x86_64 | NOTE | Dec 02 2024 |
| R-4.3-mac-aarch64 | NOTE | Dec 02 2024 |
Exports:affinityas.coefficients_textmodelas.statistics_textmodelas.summary.textmodelcoefficients.textmodel_cacoefficients.textmodel_lsacoefficients.textmodel_wordfishtextmodel_affinitytextmodel_catextmodel_lrtextmodel_lsatextmodel_nbtextmodel_svmtextmodel_svmlintextmodel_wordfishtextmodel_wordscorestextplot_influence
Dependencies:clicodetoolsfastmatchforeachglmnetglueISOcodesiteratorsjsonlitelatticeLiblineaRlifecyclemagrittrMatrixquantedaRcppRcppArmadilloRcppEigenrlangRSpectrashapeSnowballCSparseMstopwordsstringisurvivalxml2yaml
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Confidence debate from 1991 Irish Parliament | data_corpus_dailnoconf1991 |
| Crowd-labelled sentence corpus from a 2010 EP debate on coal subsidies | data_corpus_EPcoaldebate |
| Irish budget speeches from 2010 | data_corpus_irishbudget2010 |
| Movie reviews with polarity from Pang and Lee (2004) | data_corpus_moviereviews |
| Class affinity maximum likelihood text scaling model | textmodel_affinity |
| Correspondence analysis of a document-feature matrix | textmodel_ca |
| Logistic regression classifier for texts | textmodel_lr |
| Latent Semantic Analysis | textmodel_lsa |
| Naive Bayes classifier for texts | textmodel_nb |
| Linear SVM classifier for texts | textmodel_svm |
| Wordfish text model | textmodel_wordfish |
| Wordscores text model | textmodel_wordscores |
