Ensemble Methods for the NTCIR-13 NAILS Task

The QUT team participated in the NTCIR-13 Neurally Augmented Image Labeling Strategies (NAILS) task, this report describes our approach to solving the problem of developing machine learning models for classifying EEG data from an RSVP image search task. We explore the use of commonly used successful methodologies from the P300 Speller Paradigm, in particular the use of ensembles of support vector machines, and evaluate whether these methods still apply to the potentially more complex image search task.