What is the role of cross-validation in data mining?

Cross-validation evaluates model performance on multiple data splits to ensure generalization.

Cross-validation partitions data into training and validation sets multiple times (e.g., k-fold CV). Each fold is used once as validation while the rest are used for training. This reduces bias in performance estimation and helps select robust models in data mining pipelines.