Semisupervised classification, active learning, and transfer learning are useful for situations in which unlabeled data are abundant.

a. Describe semisupervised classification, active learning, and transfer learning. Elaborate on applications for which they are useful, as well as the challenges of these approaches to classification.

b. Research and describe an approach to semisupervised classification other than self-training and cotraining.

c. Research and describe an approach to active learning other than pool-based learning.

d. Research and describe an alternative approach to instance-based transfer learning.