1.2Standard
Production feature units and distributions changed.
Investigate model degradation.
Choose two checks.
× Incorrect
Compare distributions, units, ranges, missingness, and categories with training data, and correlate changes with model version, performance, and label delay.
Detailed explanation
CorrectCompare distributions, units, ranges, missingness, and categories by feature
Input changes can be identified.
Input changes can be identified.
CorrectCorrelate changes with model version, performance, and label delay over time
Root causes can be separated.
Root causes can be separated.
IncorrectRetrain every model after one feature changes
Impact has not been established.
Impact has not been established.
IncorrectIgnore a unit change when the distribution looks similar
The feature meaning can change.
The feature meaning can change.
Try it yourself
An example you can run in a temporary verification environment.
AWS公式AIF-C01 Domain 1.2の特徴量ドリフト、データ品質、モデル監視を確認する。Expected result
特徴量の分布・意味の変化と性能劣化を関連付けて調査できる。Key points
- Feature drift
- Units
- Time series
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.
Question IDAWS-AIF-393
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
Report an error or rights issue