How to calculate mean absolute error using cross-validation?

Question

When I use 5-k cross validation, is the mean absolute error (MAE) equal to

$$\text{mean}(\text{MAEs of each 5 steps})=\frac{1}{5}(MAE_1 + \cdots + MAE_5)$$

or equal to

$$\text{mean}(\text{absolute errors of all predictions})$$?

Answer 1

CV is a simulation of running testing algorithm on unseen data, so the first one.
The second is more an OOB error approximation of a bagging ensemble of your classifiers.