You are configuring an automated machine learning classification job in Azure Machine Learning to predict fraudulent transactions. Only about 2% of the transactions in your training dataset are labeled as fraud. Your business goal is to correctly identify as many fraudulent transactions as possible while keeping false positives manageable. Which primary metric should you configure for the AutoML job to best guide model selection?