The computational models generate different types of scores, such as the probability a compound is active or the predicted % inhibition. In all cases, compounds can be sorted by these scores so that those most likely to be active are first. We consider performance metrics that are based only on these compound ranks. For instance, one can move from most likely to be active to least likely, applying thresholds to compute the true positive rate (TPR), false positive rate (FPR), recall, and precision. implementation, the AP metric computes the precision P and recall R at each threshold k, then sums as follows: