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Answer: Specificity
Specificity is the correct choice when false positives are unacceptable. This metric focuses on minimizing false positives, making it ideal for situations where it's better to have false negatives than false positives.
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In scenarios where it's more acceptable to have false negatives than false positives, such as incorrectly predicting a Non-Tumor as a Tumor, which classification metric should you prioritize?
A
AUC
B
Recall
C
Specificity
D
F1 Score
E
Root Mean Square Error
F
Not Applicable
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