Performing a thorough analysis and interpretation of PRC results is crucial for effectively understanding the performance of your model. A comprehensive analysis involves scrutinizing various factors, such as precision, recall, F1-score, and AUC. These metrics provide information into the model's ability to precisely classify samples. By thoroughly