R: k-fold cross-validation for train data set

Question

I am doing some classification tasks on heart disease dataset using C5.0 in R, in most common case the data will be divided into 80% for training, and 20% for testing, I want to use k-fold cross validation (k=10), but I am confused about this point, as we know by using 10-fold cross validation, we will divide the whole data into 9 subsets for train and one subset for the test.

Is it possible to divide the data into 80% for training and 20% for testing and then applying k-fold cross-validation on train data? or I have to apply k-fold cross-validation on the whole data set?

Answer 1

One option would be k=5. In this case you train with 80% and test with 20%. But for that you don't need to use k-fold cross-validation.

k-fold cross-validation is always on the whole data set. So with k=5 there are 5 possible scenarios that are tested and compared.