Model Drift
/ˈmɒdəl drɪft/
Definition
The degradation of a model's accuracy over time as real-world data patterns diverge from its training distribution.
Example in context
"Our fraud model drifted after new payment methods launched — we retrain monthly to keep accuracy above 95%."
Related terms
Practice this term
Master Model Drift in context by working through exercises in the Data Science & ML module. You'll see the term used in real engineering scenarios with multiple-choice, fill-in-the-blank, and matching drills.