1. A method of processing a first classification model that classifies an input into one of a plurality of classes, wherein the first classification model was built using labeled training data having a first set of weights, wherein each item of labeled training data is labeled with one of the plurality of classes, the method comprising acts of: (A) obtaining unlabeled input for the first classification model; (B) using the unlabeled input to reweight the labeled training data to have a second set of weights that is different from the first set of weights; and (C) using the labeled training data reweighted according to the second set of weights to: retrain the first classification model; and/or build a second classification model.