1.1Basic
There are labeled customer records and unlabeled usage logs.
Choose the learning method for each goal.
Choose two descriptions.
× Incorrect
Supervised learning uses labeled targets for prediction, while unsupervised learning explores structure without labels.
Detailed explanation
CorrectClassification or regression from target labels is supervised learning
It learns a mapping from inputs to targets.
CorrectClustering and dimensionality reduction without labels are unsupervised learning
They explore hidden structure.
IncorrectRegression only predicts categories
It can predict continuous values.
IncorrectUnsupervised learning always requires human labels
Labels are not assumed.
Check official documentation
Compare the following points with the official documentation.
AWS公式AIF-C01 Domain 1.1の教師あり学習、教師なし学習、分類、回帰を確認する。
Official references
What to confirm
ラベルの有無と予測・構造探索の目的から学習方法を説明できる。
Key points
- Supervised
- Unsupervised
- Regression
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
Supervised learning
Learning a mapping from examples paired with known target labels.
Unsupervised learning
Finding structure or patterns in data without target labels.
Question IDAWS-AIF-412
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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