PRC (Precision-Recall Curve) analysis is a crucial technique for evaluating the performance of classification models. It provides a comprehensive insight of how the model's precision and recall change across different decision points. By graphing the precision-recall pairs, we can determine the optimal point that balances these two metrics accordin