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Say that I have a set of training examples with binary 0-1 labels, and corresponding regression labels ranging from 0 to 1. Normally, to compute AUC I've used the ROCR package in R, which also allows me to compute the optimal cutoff point. In addition to these labels and predictions, I also have a weight column which ranges from 0 to 1 and signifies the importance of each example. I was wondering how I could compute the AUC and optimal cutoff point of these examples, taking these weights into account.

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Not sure if this question is still valid, but you can use PRROC package in R for weighted AUC computations.

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    $\begingroup$ glmnet package also has it $\endgroup$ – seanv507 Dec 12 '18 at 18:16

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