Cross-Validation

A model evaluation technique that partitions data into subsets, trains the model on some subsets and validates on others, providing a more reliable estimate of model performance.

Testing an AI by splitting your data multiple ways and checking performance each time. Instead of one test, you run five or ten, getting a more reliable picture of how the model will perform in real life.