Semisupervised Seizure Prediction in Scalp EEG Using Consistency Regularization

Figure 1

A schematic illustration of the consistency regularization. When trained only on the limited labeled data in a supervised manner, the decision boundary does not follow the “manifold” of the data. On the other hand, consistency regularization could leverage unlabeled data to draw a decision boundary that better reflects the underlying structure of the data.