[source] # K Fold K Fold is a cross validation technique that splits the training set into *k* individual folds and for each training round uses 1 of the folds to test the model and the rest as training data. The final score is the average validation score over all of the *k* rounds. K Fold has the advantage of both training and testing on each sample in the dataset at least once. **Interfaces:** [Validator](api.md#validator), [Parallel](#parallel) ## Parameters | # | Name | Default | Type | Description | |---|---|---|---|---| | 1 | k | 5 | int | The number of folds to split the dataset into. | ## Example ```php use Rubix\ML\CrossValidation\KFold; $validator = new KFold(5, true); ```