Cross Validation and training set In RapidMiner I want to create a k-NN model in order to create a classifier. To generate the test sets and the training sets I use the the cross-validation.

If I choose 10 as the number of folds, the cross-validation algorithm will do 10 iterations with different test sets and training sets. 

At the end, what training set will be used to create my k-NN model ?
Apart from having an average accuracy of the trained model, also you can use cross-validation to approximate the optimal value for the k parameter and the optimal metric.