Using ngrams with #RTextTools

This littel example shows a workaround for a bug in RTextTools.

Using ngramLength would lead to an error. But we can use the RWeka library and tm, then go back to RTextTools:

library(RTextTools) 
texts <- c("This is the first document.", 

"Is this a text?", "This is the second file.", 

"This is the third text.", 

"File is not this.") 
library(RWeka)
library(tm)
TrigramTokenizer <- function(x) NGramTokenizer(x, Weka_control(min = 3, max = 3))
dtm <- DocumentTermMatrix(Corpus(VectorSource(texts)),
                             control=list(weighting=weightTf, 
                                          tokenize = TrigramTokenizer))
as.matrix(dtm)
isText <- c(T,F,T,T,F)
container <- create_container(dtm, isText, virgin=F, trainSize=1:3, testSize=4:5)
 
models=train_models(container, algorithm=c("SVM","BOOSTING"))
classify_models(container, models)

It was an old question on stackoverflow, which I just have answered.