training
Cross-Validation
A technique for evaluating model performance by splitting data into multiple subsets, training on some and testing on others in rotation. Cross-validation provides a more reliable estimate of model performance than a single train-test split.
In practice
5-fold cross-validation trains 5 models, each using a different 20% of data for testing, then averages the results.