When should your validation setup be revised?
A model is being built for same-day food delivery, but the hold-out set was collected from a much older warehouse system with different customer behavior and package types. What does this situation suggest about the dev/test split or the evaluation metric?
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When Evaluation Data Does Not Match Deployment Data
When Repeated Validation Checks Distort Model Selection
When the Metric Rewards the Wrong Goal
When should your validation setup be revised?
True or False: If your initial validation split or evaluation metric turns out to be poorly chosen, you cannot revise it without abandoning the project.
If your evaluation metric no longer reflects your main objective, what should you change?
What is the clearest sign that your dev/test set or evaluation metric may need revision?
If a validation set or metric turns out to be poorly matched to the real goal, the team should rebuild the whole project before making any changes.
What to revise when the evaluation no longer matches the goal
Match each reason a validation metric can mislead the team to the recommended remedy.
What should a team do when its evaluation setup stops matching its goal?
When Validation Data Does Not Match Deployment Data
After revising your dev/test sets or evaluation metric, updating the project documentation is enough; the team does not need to be told about the new direction.
What should be expanded after repeated tuning to the validation set?
Match each situation to the underlying problem category it illustrates.
Order the reasoning steps for deciding whether to replace an evaluation metric that no longer matches the product goal.
When validation results stop matching the best product choice
When Evaluation Scores and Product Needs Disagree
What should a team do after the development set stops guiding decisions?