Keeping feature scaling consistent | AWS Certified AI Practitioner (AIF-C01) original practice question

1.2Standard

Use income and age in a distance-based model.

Avoid scale dominating the result.

Choose two practices.

Hint 1: Focus on the requirement

Identify what must change and what must remain unchanged. Then choose the command whose scope matches that requirement.

Hint 2: Check each command's role

Separate commands that display information, change state, remove data, or affect a child process.

Detailed explanation

CorrectLearn scaling statistics from training data only

Evaluation information does not leak.

CorrectReproduce the same units, transformations, and missing handling in production

Training and inference meanings align.

IncorrectCompute the mean over all data before splitting

Evaluation information leaks.

IncorrectUse a different unit in production

Feature meaning changes.

An example you can run in a temporary verification environment.

AWS公式AIF-C01 Domain 1.2の特徴量前処理とリーケージを確認する。

訓練・推論で一貫した特徴量変換を実装できる。

Foundation review

Check whether the command acts on the current shell, a new process, an existing process, or a file.

Use the supplied command and compare the output with the expected result.

Question IDAWS-AIF-317

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