How do you evaluate and mitigate the risk of model drift over time?
Instruction: Describe the methods to detect model drift and strategies to update models in response to it.
Context: This question tests the candidate's ability to ensure the long-term reliability and accuracy of machine learning models in dynamic environments.
Updated
Official answer available
Read the opening below, then unlock the full answer and practical guidance.
I evaluate drift with time-aware monitoring rather than one static validation score. That means watching feature distributions, calibration, segment-level performance, business KPIs, and delayed-label quality over time...