What is model evaluation in non-stationary environments?

Model evaluation in non-stationary environments measures performance under changing data distributions over time.

In non-stationary environments, traditional static evaluation metrics are insufficient. Instead, evaluation uses time-windowed metrics, rolling averages, and delayed ground truth feedback. It requires continuous benchmarking and shadow evaluation systems. This ensures models remain reliable even as underlying data evolves.