where \(\hat{y}\) is the probability that the model predicts that the sample is a positive example. \(y\) is the ground truth label, if the sample is a positive example, the value is 1, otherwise the value is 0.
The Area Under the Receiver Operator Curve (AUROC) is another well-known metric for evaluating the accuracy of a binary classification task. It is calculated by considering the TP and FP rates obtained using different decision thresholds. The AUROC value ranges from 0 to 1, with a value of 0.5 indicating a random prediction and a value of 1.00 denoting perfect predictive accuracy.
Conflict of interest
The authors declare no conflict of interest.