What is Area Under the PR Curve in Machine Learning?

Area Under the PR Curve (AUC-PR) is a metric used to evaluate the performance of a machine learning model. It is used to measure the ability of a model to accurately classify a given set of data points. AUC-PR is calculated by plotting the precision and recall values of a model on a graph, and then calculating the area under the curve. A model with a higher AUC-PR score is considered to be more accurate in its predictions. AUC-PR is a useful metric for evaluating models with imbalanced datasets, as it takes into account both precision and recall.