ROC and Precision-Recall curves - How do they compare?
The accuracy of a model is often criticized for not being informative enough to understand its performance trade offs. One has to turn to more powerful tools instead. Receiver Operating Characteristic (ROC) and Precision-Recall (PR) curves are standard metrics used to measure the accuracy of binary classification models and find an appropriate decision threshold. But how do they relate to each other?