Instruction: Explain strategies to identify and mitigate the impact of temporal drift on machine learning models.
Context: This question evaluates the candidate's ability to deal with real-world data challenges that affect model reliability over time.
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The way I'd approach it in an interview is this: Temporal drift means the model is facing a world that changed over time, not just a static dataset split. So I approach it by evaluating and monitoring with time-aware logic. That usually means time-based...