MAPE metric has problems when the actual value to be predicted is very small. In the extreme when the actual value is 0 then MAPE will be infinity (if the prediction is not exactly 0). What about this solution as illustrated with an example:
Suppose that the actual values are [10, 0, 20] and the corresponding predictions are [13, 2, 16].
Sum of Absolute Errors = 3 + 2 + 4 = 9 Sum of Actual Values = 10 + 0 + 20 = 30 Percentage error = (9/30)*100 = 30
What are the shortcomings of this metric? Also does this metric have a name (I could not find it)? Thanks