Package: RTextTools
Type: Package
Title: Automatic Text Classification via Supervised Learning
Version: 1.3
Date: 2011-08-22
Author: Timothy P. Jurka, Loren Collingwood, Amber E. Boydstun,
Emiliano Grossman, Wouter van Atteveldt
Maintainer: Timothy P. Jurka <tpjurka@ucdavis.edu>
Depends: R (>= 2.13.0), methods, SparseM, randomForest, tree, nnet, tm,
e1071, ipred, caTools, maxent, RODBC, glmnet, Rstem
Description: 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, RF,
GLMNET, TREE, NNET, MAXENT), comprehensive analytics, and
thorough documentation.
License: GPL-3
URL: http://www.rtexttools.com/
LazyLoad: yes
Packaged: 2011-08-21 08:59:44 UTC; timjurka
Repository: CRAN
Date/Publication: 2011-08-21 15:17:49

Package: RTextTools
Type: Package
Title: Automatic Text Classification via Supervised Learning
Version: 1.4.0
Date: 2012-09-22
Author: Timothy P. Jurka, Loren Collingwood, Amber E. Boydstun,
Emiliano Grossman, Wouter van Atteveldt
Maintainer: Timothy P. Jurka <tpjurka@ucdavis.edu>
Depends: R (>= 2.15.0), methods, SparseM, randomForest, tree, nnet, tm,
e1071, ipred, caTools, maxent, glmnet, tau
Description: 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.
License: GPL-3
URL: http://www.rtexttools.com/
Packaged: 2012-09-22 19:17:07 UTC; timjurka
Repository: CRAN
Date/Publication: 2012-09-23 06:36:30