Use Matching Dev and Test Distributions for Application Work

For an application project, what data-splitting rule is most helpful?

Domain adaptation methods are the default solution for most machine learning projects.

Domain adaptation means training on one _____ and expecting useful performance on another.

Match each machine-learning concept to its description.

Order the steps for choosing dev/test data when the project data differs from deployment data.

When are domain adaptation methods usually a good fit?

Selecting development and test sets from the same data distribution can improve team efficiency.

Dev and test sets should come from the _____ distribution.

Order the main ideas behind matching dev and test data to the deployment setting.

Domain Adaptation Research Versus Application-Focused Data Splits

Choose evaluation strategy for a crop disease app.

Why choose dev and test sets from the same distribution instead of building a special adaptation method?