What Is Cross-Validation? How to Estimate Model Performance Reliably

Cross-validation is a method that rotates held-out data folds to reliably estimate model performance and variability, avoiding instability from a single validation split. It involves partitioning data, training on subsets, evaluating held-out folds, rotating through all folds, and aggregating results to assess model generalization.