After reading a lot of semi-supervised methods, the way these methods work is by training a small labeled data, then predicting the labels of the unlabeled points incrementally. So if I want to test the algorithm on new unseen test data, does the new training data become (Labeled + Unlabeled (with predicted labels)) and then perform supervised classification? Is it like a two step supervised procedure?