AWS Certified Machine Learning Engineer – Associate (MLA-C01) — Question 42

An ML engineer is evaluating several ML models and must choose one model to use in production. The cost of false negative predictions by the models is much higher than the cost of false positive predictions.
Which metric finding should the ML engineer prioritize the MOST when choosing the model?

Answer options

• A. Low precision
• B. High precision
• C. Low recall
• D. High recall

Correct answer: D

Explanation

The ML engineer should prioritize high recall because it minimizes the number of false negatives, which are more costly in this scenario. Low precision, high precision, and low recall do not address the critical need to reduce false negatives, making them less relevant in this context.