Definition
A resampling method that estimates generalization by repeatedly training and evaluating on different non-overlapping subsets of available data.
Distinguish it from nearby terms
A single train-test split produces one estimate. Cross-validation rotates which subset is held out, but it does not replace a final untouched test set when one is needed.
Check your understanding
Splits must respect time, identity, and dependency boundaries or leakage can make the estimate falsely optimistic.