Pool-based active learning techniques have had success producing multi-class classifiers that achieve high accuracy with fewer labels compared to random labeling. However, in an industrial setting where we often have class-level business targets to achieve (e.g., 95% recall at 95% precision for each class), active learning techniques continue to acquire labels for classes that have already met their targets
