What is cross-validation and when should you use it?

Cross-validation estimates model performance by training on multiple folds and validating on the remaining fold. Use it when: - Data is limited - You need robust comparison across models For time series, use time-series CV (rolling windows) instead of random K-fold to preserve temporal order.