Active Learning with Nonparallel Support Vector Machine for Binary Classification

Labeled data, in real world, is quite scarce compared with unlabeled data. Manual annotation is usually expensive and inefficient. Active learning paradigm is used to handle this problem by identifying the most informative instances to annotate. In this paper, we proposed a new active learning algorithm based on nonparallel support vector machine. Numeric experiment shows the effective performance of the proposed method compared with classical active learning based on support vector machine.