The dataset is split into multiple folds, where the number of folds is denoted by $k$. One fold is withheld each training run. A metric, such as the [[residual sum of squares]], is calculated from the reserved fold, which serves as a pseudo test set. The process is repeated for each fold and the average of the metric across all runs is calculated.