Select a machine learning task for a project.
Use the output type as the main distinction.
Which use case is best suited to regression?
Regression predicts a continuous numeric value, while classification predicts a discrete category.
Detailed explanation
A price is a continuous numeric value, which is a regression target.
A price is a continuous numeric value, which is a regression target.
This predicts a discrete category.
This predicts a discrete category.
Unlabeled grouping is clustering.
Unlabeled grouping is clustering.
Object detection is a different task involving locations and classes.
Object detection is a different task involving locations and classes.
Try it yourself
An example you can run in a temporary verification environment.
AWS公式AIF-C01ガイドのDomain 1.1で、classificationとregressionの例を確認する。Expected result
連続値の予測を回帰、カテゴリの予測を分類として説明できる。Key points
- Continuous values
- Categories
- Prediction tasks
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.