  Rgtsvm provides a fast and flexible support vector machine (SVM)
implementation for the R language. The distinguishing feature of Rgtsvm is that
support vector classification and support vector regression tasks are
implemented on a graphical processing unit (GPU), allowing the libraries to
scale to millions of examples with >100-fold improvement in performance over
existing implementations. Nevertheless, Rgtsvm retains feature parity and has
an interface that is compatible with the popular e1071 SVM package in R.
Altogether, Rgtsvm enables large SVM models to be created by both experienced
and novice practitioners.
