For each iteration, a variable number (m is ranged from 100 to 500) of classified instances in the decreasing order of confidence are first chosen as the base examples, then at most 100 examples are selected from the base examples to be augmented to the labeled set.
when m is equal to 100, the whole set of the base example is added to the labeled data, i.e.