What is sequential evaluation in time-series ML systems?

Sequential evaluation tests models in temporal order respecting causality.

In time-series or streaming ML systems, evaluation must preserve temporal ordering to avoid leakage. Techniques include rolling windows, walk-forward validation, and expanding window evaluation. This ensures models are tested on future unseen data without violating causality assumptions.