Figure 1: Cross Validation for different Machine Learning Models The area under the precision-recall curve (PR curve) indicates how well a model balances precision and recall. Among the Random Forest, Decision Tree, and SVM models, Random Forest exhibited the highest area under the curve, indicating superior performance. The Random Forest model achieved a better trade-off between precision and recall, making it the preferred choice. The higher area under the PR curve for Random Forest Figure 3: Precision Recall Curve for Different Models signifies its enhanced ability to maintain precision while effectively identifying positive cases, demonstrating robustness and balance compared to Decision Tree and SVM.
