RTextTools: a machine learning library for text classification
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About RTextTools

Note: RTextTools is no longer actively maintained -- the software may contain bugs that will not be fixed with newer versions of R.
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RTextTools is a free, open source machine learning package for automatic text classification that makes it simple for both novice and advanced users to get started with supervised learning. The package includes nine algorithms for ensemble classification (svm, slda, boosting, bagging, random forests, glmnet, decision trees, neural networks, maximum entropy), comprehensive analytics, and thorough documentation.

The beta release was unveiled at the The 4th Annual Conference of the Comparative Policy Agendas Project on June 24, 2011 in Catania, Italy. The full release is available on the installation page.

The RTextTools repository is available via GitHub, and the help mailing list is on Google Groups.

Acknowledgements

We would like to sincerely thank those who financed the RTextTools project-- Professor Amber Boydstun at University of California at Davis, Professor Sylvain Brouard at Sciences Po Bordeaux, Professor Emiliano Grossman at Sciences Po Paris, and Professor Stefaan Walgrave at University of Antwerp.

Additionally, we'd like to acknowledge our beta testers for their time and valuable feedback- Anna Maria Palau Roque, Jon Moody, Professor John D. Wilkerson, and Paul Wolfgang.


UC Davis | UWashington | Sciences Po | Vrije Universiteit
University of California, Davis | University of Washington
Sciences Po Paris | Vrije Universiteit Amsterdam

Development Team

Timothy P. Jurka
University of California Davis

Loren Collingwood
University of Washington Seattle

Professor Amber E. Boydstun
University of California Davis

Professor Emiliano Grossman
Sciences Po Paris

Professor Wouter van Atteveldt
Vrije Universiteit Amsterdam
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