Cross validation splits the data into K partitions. Then it trains the models on the K permutations of (K - 1) sets and validates it on the remaining 1 set. For example, if you use 10-fold validation, it will train on 9 different permutations of the sets, each having 9 sets for training, and 1 for validation.
As such, there is no dependence on the parameters of the model.
