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RTextTools - A Supervised LearningPackage for Text Classification

http://www.rtexttools.com/

The train_model() function takes each algorithm, one by one, to produce an object passable to classify_model().

A convenience train_models() function trains all models at once by passing in a vector of model requests. The syntax below demonstrates model creation for all nine algorithms:

Algorithms	Author	From package	Keyword	Comment
Support vector machine	Meyer et al., 2012	e1071	SVM	Low-memory algorithms
Glmnet	Friedman et al., 2010	glmnet	GLMNET	Low-memory algorithms
Maximum entropy	Jurka, 2012	maxent	MAXENT	Low-memory algorithms
Scaled linear discriminant analysis	Peters and Hothorn, 2012	ipred	SLDA
Bagging	Peters and Hothorn, 2012	ipred	BAGGING
Boosting	Tuszynski, 2012	caTools	BOOSTING
Random forest	Liawand Wiener, 2002	randomForest	RF
Neural networks	Venables and Ripley, 2002	nnet	NNET
Classification or regression tree	Ripley., 2012	tree	TREE

GLMNET <- train_model(container,"GLMNET")