Recent technological advances have enabled researchers to collect large amounts of electroencephalography (EEG) signals in\nlabeled and unlabeled datasets. It is expensive and time consuming to collect labeled EEG data for use in brain-computer interface\n(BCI) systems, however. In this paper, a novel active learning method is proposed to minimize the amount of labeled, subjectspecific\nEEG data required for effective classifier training, by combining measures of uncertainty and representativeness within an\nextreme learning machine (ELM)..........................
Loading....