Two punting strategies. (A) Two classifiers are combined to produce a hybrid classifier with improved accuracy and coverage. The punting thresholds (T = [T1, ..., T
]) are class-dependent and are set using held-out data. (B) This approach is similar to (A), except that using two vectors of punting thresholds – T1 for the primary classifier and T2 for the secondary classifier – allows the method sometimes to make no prediction at all.