Interpreting a PR Curve

  • It is desired that the algorithm should have both high precision, and high recall. However, most machine learning algorithms often involve a trade-off between the two. A good PR curve has greater AUC (area under curve). source

Relation to ROC Curve

  • In certain applications (e.g. searching a pool of documents to find ones which are relevant to a particular user query) PR curves are more useful than ROC curves.
  • It is important to note that the classifier that has a higher AUC on the ROC curve will always have a higher AUC on the PR curve as well. source