How AI describes Deep Abstaining Classifier (DAC)

The Deep Abstaining Classifier (DAC) is a PyTorch implementation of a method that uses an abstention loss function to identify and handle label noise during deep neural network training. It can detect both systematic label noise, such as corrupted features or transformations, and arbitrary label noise, and includes a stabilization feature to maintain a desired abstention rate.