Cross-validation

Also: k-fold cross-validation

Splitting the data into k parts, training k times with a different part held out each time, and averaging the scores. It uses every row for both training and evaluation, which matters when data is scarce.

A definition is not an understanding. This is taught properly in Regularisation and validation, hands on, part of Overfitting & regularisation.

Learn this properly

Terms from the same topic

Overfitting Underfitting Regularisation Dropout Early stopping Held-out set Train/validation/test split Data leakage