# BDA7.1 Cross-Validation

This skill introduces cross-validation techniques used to assess model generalization and prevent overfitting. It focuses on different strategies, statistical robustness, and integration with HPC workflows.

## Requirements

* External: Familiarity with model training and evaluation
* Internal: BDA5.1.2 Evaluation Metrics (recommended)

## Learning Outcomes

* Define cross-validation and explain its role in evaluating model generalization.
* Compare k-fold, stratified, and leave-one-out cross-validation strategies.
* Implement cross-validation efficiently on large datasets in parallel environments.
* Use cross-validation results to guide model selection and hyperparameter tuning.
* Evaluate statistical significance and variance across validation folds.


** Caution: All text is AI generated **