Cross Validation

Take random samples of data and calculate parameters on the several samples and compare.

K-fold Cross Validation (CV)

For each fold, split the data into training and testing data. Errors are averaged across the folds.

Large K’s make model training time consuming. Large K’s typically usually lead to low bias.