Topic 1 Question 44
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?
Low precision
High precision
Low recall
High recall
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- 正解だと思う選択肢: D
A. Low precision: Increases false positives; less relevant here. B. High precision: Reduces false positives; not the priority. C. Low recall: Increases false negatives; must be avoided. D. High recall: Correct; minimizes false negatives.
👍 2Saransundar2024/12/05 - 正解だと思う選択肢: D
https://docs.aws.amazon.com/comprehend/latest/dg/cer-doc-class.html "High recall means that the classifier returned most of the relevant results."
👍 1GiorgioGss2024/11/27
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