Our last baseline implements the active learning procedure as described in Tong and Koller (2002).
given that we now have a labeled set (composed of 100 manually labeled points selected by active learning and 500 unambiguous points) as well as a larger set of points that are yet to be labeled (i.e., the remaining unlabeled points in the training folds and those in the test fold), we aim to train a better classifier by using a weakly supervised learner to learn from both the labeled and unlabeled data.