RTextTools: Automatic Text Classification via Supervised Learning
RTextTools is a machine learning package for automatic
text classification that makes it simple for novice users to
get started with machine learning, while allowing experienced
users to easily experiment with different settings and
algorithm combinations. 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.
| Version: |
1.4.2 |
| Depends: |
R (≥ 2.15.0), SparseM |
| Imports: |
methods, randomForest, tree, nnet, tm, e1071, ipred, caTools, maxent, glmnet, tau |
| Published: |
2014-01-19 |
| Author: |
Timothy P. Jurka, Loren Collingwood, Amber E. Boydstun,
Emiliano Grossman, Wouter van Atteveldt |
| Maintainer: |
Timothy P. Jurka <tpjurka at ucdavis.edu> |
| License: |
GPL-3 |
| URL: |
http://www.rtexttools.com/ |
| NeedsCompilation: |
yes |
| Materials: |
ChangeLog |
| In views: |
NaturalLanguageProcessing |
| CRAN checks: |
RTextTools results |
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Reverse dependencies:
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