Cross-validation

Also written: k-fold cross-validation, k-fold

Scoring a model several times on different held-back slices of the data, for a steadier estimate.

Other terms from the same lesson

• fold: One of the equal slices that cross-validation cuts the data into. Each fold takes a turn as the held-back data.
• grid search: Trying every combination from a list of settings, scoring each with cross-validation, and keeping the best.
• hyperparameter: A setting you choose before training, such as tree depth or learning rate, rather than one the model learns.