You are a Machine Learning Engineer at a aws video

Full Certification Question

You are a Machine Learning Engineer at a healthcare company working on a binary classification model to predict whether a patient has a particular disease based on several medical features. The consequences of misclassifications are severe: false positives lead to unnecessary and expensive follow-up tests, while false negatives could result in a failure to provide critical treatment. You need to evaluate the model using appropriate metrics to balance the risks associated with these types of errors. Given the critical nature of the application, which combination of evaluation metrics should you prioritize to minimize both false positives and false negatives while ensuring that the model is reliable for deployment? (Select two)