# How to calculate mean absolute error using cross-validation?

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

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

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 If there are an even number of training examples, wont this be exactly the same? With an odd number then they differ slightly. – B_Miner Sep 19 '11 at 15:20 @B_M How does that work? Perhaps you are thinking of medians? – whuber♦ Sep 19 '11 at 19:02