OpenAUC: Towards AUC-Oriented Open-Set Recognition. (arXiv:2210.13458v1 [cs.LG])

Traditional machine learning follows a close-set assumption that the training
and test set share the same label space. While in many practical scenarios, it
is inevitable that some test samples belong to unknown classes (open-set). To
fix this issue, Open-Set Recognition (OSR), whose goal is to make correct
predictions on both close-set samples and open-set samples, has attracted
rising attention. In this direction, the vast majority of literature focuses on
the pattern of open-set samples. However, how to evaluate model …

arxiv auc set