Explanation
Holdout cross-validation method is suitable for very large dataset because it is the simplest and quicker to compute version of cross-validation.
Holdout method
In this method, the dataset is divided into two sets namely the training and the test set with the basic property that the training set is bigger than the test set. Later, the model is trained on the training dataset and evaluated using the test dataset.