Compare models with a small dataset.
Prevent preprocessing and duplicate records from contaminating evaluation.
Choose two appropriate practices.
Fit preprocessing within each training fold and keep the same entity or duplicate records from crossing train and validation folds.
Detailed explanation
Validation information must not determine training preprocessing.
Validation information must not determine training preprocessing.
Overlap can overstate unseen-data performance.
Overlap can overstate unseen-data performance.
Global statistics can leak validation information.
Global statistics can leak validation information.
Reproducibility and trust would be lost.
Reproducibility and trust would be lost.
Try it yourself
An example you can run in a temporary verification environment.
AWS公式AIF-C01ガイドDomain 1.3のデータ分割、前処理、リーケージを確認する。Expected result
交差検証で前処理と重複を管理する理由を説明できる。Key points
- Cross-validation
- Preprocessing
- Duplicates
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.