Domain adaptation methods are the default solution for most machine learning projects.
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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.
Match each project goal to the strategy associated with it.
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?