AUC is a widely-used evaluation metric for assessing the effectiveness of a prediction system, especially when there is a trade-off between precision and recall. The precision-recall curve typically slopes downward. As the confidence threshold of a prediction algorithm is lowered, it generates more predictions. However, these additional predictions tend to be less accurate, resulting in a decrease in precision while potentially increasing recall.
