Reduce missed findings in medical-image screening.
For fraud detection, also understand how many flagged cases are truly fraud.
Choose two correct statements.
Recall measures captured actual positives, while precision measures how many positive predictions are truly positive; both and the threshold may matter.
Detailed explanation
It is important when missed positives are costly.
It is important when missed positives are costly.
It describes false-positive burden among flagged cases.
It describes false-positive burden among flagged cases.
Precision and recall can trade off.
Precision and recall can trade off.
That describes a different metric such as specificity.
That describes a different metric such as specificity.
Try it yourself
An example you can run in a temporary verification environment.
AWS公式AIF-C01試験ガイドDomain 3.3の分類評価指標を確認する。Expected result
再現率と適合率の分母・業務上の意味を説明できる。Key points
- Recall
- Precision
- Trade-off
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
- Command output formatting can vary slightly by distribution or tool version.
- Run the example in a temporary directory or process when possible.
Foundation review
Read the scope first
Check whether the command acts on the current shell, a new process, an existing process, or a file.
Verify the observable result
Use the supplied command and compare the output with the expected result.