This paper investigates the utility of using the Fast Johnson-Lindenstrauss Transform to produce a low-dimensional random projection of eye-tracking data features that can be used for classifying emotion in an Intelligent Tutoring System. Interestingly, the FJLT provides similar or superior performance to more computationally expensive techniques.
