Question 154
CCA-F is a newly released exam. These practice questions reflect our best current understanding — the exact wording and question formats may change in the live exam until the certification matures. Use them to learn the concepts, not to memorize.
Scenario: Structured Data Extraction - A support-ticket classifier uses the enum `["bug", "feature", "docs"]`. Around 12% of real tickets fit none of these, and the model is forced to pick a wrong category, losing information and skewing the metrics. How should the enum be extended?
- AAdd 20 more narrowly defined categories to cover every conceivable ticket.
- BRemove the enum constraint and accept any free-text label.
- CForce the model to always pick the closest of the three existing categories.
- DAdd `"other"` (with a detail string) and `"unclear"` so out-of-scope or ambiguous tickets are captured honestly.