Semi-supervised Wrapper Method

The principle behind wrapper methods is that we train a model with labeled data and then generate pseudo-labels for the unlabeled data using the trained model iteratively.

References

Jashish, M. (n.d.). Beginner's Guide to Semi-Supervised Learning. Jashish Blog. Link.