PRC (Precision-Recall Curve) analysis is a crucial technique for assessing the performance of classification models. It provides a comprehensive perspective of how the model's precision and recall vary across different decision points. By visualizing the precision-recall pairs, we can identify the optimal threshold that balances these two metrics a