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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. Paragraph from paper Can anyone explain how to calculate AUC_DS, AUC_BW, and AUC_0? Thank you.

J S
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