A sensor has values far outside its normal range.
Decide whether they are faults or real events.
Choose two appropriate practices.
Use domain and acquisition records to determine meaning, and compare removal, clipping, transformation, or indicator policies.
Detailed explanation
It may be a real failure or a measurement error.
It may be a real failure or a measurement error.
Different treatments affect model quality and detection.
Different treatments affect model quality and detection.
Important failures may be removed.
Important failures may be removed.
Training and inference meanings diverge.
Training and inference meanings diverge.
Try it yourself
An example you can run in a temporary verification environment.
AWS公式AIF-C01 Domain 1.2のデータ品質、異常値、前処理を確認する。Expected result
外れ値を意味と業務影響で扱う理由を説明できる。Key points
- Outlier
- Measurement error
- Domain knowledge
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.