How to Evaluate Models in the Presence of Class Imbalance?
Traditional evaluation metrics like accuracy may not be suitable for imbalanced datasets. Metrics such as precision, recall, F1 score, and the ROC curve are better suited for this purpose. These metrics provide a more comprehensive view of model performance, especially for the minority class.
