1.2Standard
Customer data must be split to evaluate a model.
Estimate performance on unseen data.
Choose two practices.
× Incorrect
Keep test data out of training and tuning, and check duplicates, time order, and customer boundaries for leakage.
Detailed explanation
CorrectKeep test data out of model training and hyperparameter tuning
Unseen performance can be measured.
Unseen performance can be measured.
CorrectCheck duplicates, time order, and same-customer leakage before splitting
Evaluation contamination is reduced.
Evaluation contamination is reduced.
IncorrectTune repeatedly on the test result and report it as final
The test becomes tuning data.
The test becomes tuning data.
IncorrectUse training accuracy alone for production performance
Overfitting is missed.
Overfitting is missed.
Try it yourself
An example you can run in a temporary verification environment.
AWS公式AIF-C01 Domain 1.2の訓練・検証・テスト分割、データ漏洩を確認する。Expected result
評価データを調整に再利用せず、分割単位の漏洩も確認できる。Key points
- Test data
- Leakage
- Unseen data
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-414
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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