I know AUC is for binary classification, but in a paper, the authors seemingly used AUC_DS, AUC_BW, and AUC_0 to compare vector values, like
ground truth of one sample [3,2,1,0,1,2,3]
prediction value of the sample [8.1, 7.9, 7.3, 6.9, 7.5, 7.8, 8.6]
they compared ground truth values and prediction values for many samples and gave a score.
Can anyone explain how to calculate AUC_DS, AUC_BW, and AUC_0? Thank you.