3.3Basic
Evaluate a fraud detector.
Explain misses and false alarms.
Choose two correct statements.
× Incorrect
A true positive is correctly detected fraud and a false negative is fraud missed as normal; business cost matters beyond accuracy.
Detailed explanation
CorrectA true positive is fraud correctly classified as fraud
The target class is correctly detected.
CorrectA false negative is fraud classified as normal
It represents a missed fraud case.
IncorrectAccuracy alone fully represents missed-fraud cost
Class imbalance and error cost can be hidden.
IncorrectA false positive is fraud that was missed
It is a normal case incorrectly flagged.
Check official documentation
Compare the following points with the official documentation.
AWS公式AIF-C01 Domain 3.3の分類評価、混同行列、適合率・再現率を確認する。
Official references
What to confirm
偽陽性と偽陰性の意味を業務影響へ結び付けられる。
Key points
- True positive
- False positive
- False negative
Notes
- Environment: AWS公式AIF-C01試験ガイドとAWS公式ドキュメントの確認
- Compare the definition with the AIF-C01 objective and the service documentation before applying it.
- Keep the concept separate from a particular answer choice or implementation step.
Foundation review
Confusion matrix
A table counting combinations of actual classes and predicted classes.
True positive
A positive case correctly identified as positive.
Question IDAWS-AIF-260
EnvironmentAWS公式AIF-C01試験ガイドとAWS公式ドキュメントの確認
Last technical review2026-08-20
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