What is performance degradation attribution in ML systems?

It identifies root causes of model performance drops in production.

Performance degradation attribution isolates whether drops are caused by data drift, feature pipeline changes, label shifts, or model decay. It often uses monitoring dashboards, feature importance shifts, and statistical comparisons. This is critical in production ML observability.