Relative Error Aggregation

Problem

Aggregate relative error as weighted absolute percentage error: sum(abs(actual - forecast)) / sum(abs(actual)).

Return 0.0 when actual is empty or its absolute sum is zero.

Hint

WAPE scales total error by total volume rather than averaging per-point ratios.

case 1

in: [[100,200],[110,190]]

expected: 0.06666666666666667

case 2

in: [[10,20,30],[12,18,33]]

expected: 0.11666666666666667

case 3

in: [[5,5],[5,5]]

expected: 0

case 4

in: [[0,0],[1,1]]

expected: 0

Starter codePython

def relative_error_aggregation(actual, forecast):
    # Your code here
    pass

4 test cases · run your code against them in the editor