1.2Basic
Income and age are inputs to a distance-based model.
Prevent one unit from dominating.
Choose two preprocessing practices.
× Incorrect
Fit scaling statistics on training data only and apply the same transform to validation and production while checking outliers and performance.
Detailed explanation
IncorrectCompute statistics on all data before splitting
Test information leaks.
IncorrectDifferent units never affect distance models
Scale can dominate distance.
CorrectCompute mean and scale from training data and apply the same transform elsewhere
Evaluation leakage is avoided.
CorrectCheck outliers, distributions, and model performance after scaling
Side effects are measured.
Check official documentation
Compare the following points with the official documentation.
AWS公式AIF-C01 Domain 1.2の特徴量前処理、標準化、データ漏洩を確認する。
Official references
What to confirm
前処理の統計量を訓練データから分離して管理できる。
Key points
- Standardization
- Leakage
- Outlier
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
Standardization
Transforming values using a training-set mean and standard deviation.
Normalization
Rescaling values to a defined range or comparable magnitude.
Question IDAWS-AIF-434
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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