Mean Absolute Percentage Error (MAPE)

The MAPE is commonly used in quantitative forecasting methods because it produces a measure of relative overall fit. The absolute values of all the percentage errors are summed up and the average is computed. In comparison to “mean error”, which is determined simply as the average error value and affected by outliers (large positive and negative errors can cancel each other out resulting in a zero error), or “mean absolute error”, which de-emphasizes outliers by their average, the MAPE isa more meaningful measurement. For example, if you are forecasting sales that vary greatly from month to month and the MAPE is +5%, it is a more useful result than a mean error. The MAPE also de-emphasizes outliers, but produces results calculated as the average absolute error in percentage terms (which are easily interpretable).

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