If you use 10-fold cross validation to derive the error in, say, a C4.5 algorithm, then you are essentially building 10 separate trees on 90% of the data to test on 10% - 10 times. Which one of the 10 trees is representative? Won't they all be different?
For example - how does WEKA give me a C4.5 tree and a cross-validation error, but only one. I feel I must have fundamentally misunderstood this.
Thanks for any help