Area Under the Precision-Recall Curve

The Area Under the Precision-Recall Curve (AUPRC) measures how well a model can distinguish positive cases from negative ones, especially when positives are rare. The curve plots the trade-off between precision (accuracy of positive predictions) and recall (ability to find all positives) at different thresholds. A higher AUPRC indicates that the model is good at identifying positives accurately without missing many. It’s a valuable metric in imbalanced datasets, where traditional accuracy can be misleading, as it focuses specifically on the model’s performance in detecting positive instances.