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Which practice detects when model performance degrades due to changing data distributions?
- Data Drift Detection
- Concept Drift Detection
- Both A and B
- Neither
Answer: Both A and B
Data drift: input feature distribution changes; concept drift: relationship between features and target changes. Monitoring both enables timely model retraining. Critical for production ML reliability.