Mean Absolute Percentage Error (MAPE)

This metric is calculated by averaging the absolute value of the percentage error between the actual values and forecasts for each unit of time. MAPE is an error metric that is easy to understand because it provides the error in terms of percentages. A lower value of MAPE implies a higher accuracy of the model. A significant disadvantage of MAPE is that it produces undefined values when the actual values are 0, which is a common occurrence in some fields. In these cases, Demand Modeler treats the actual value in the denominator as 1, thus the calculation for those units of time is the absolute difference between actual values and forecasts.

Another disadvantage of MAPE is that it puts a heavier penalty on negative errors (over forecasting) than positive errors (under forecasting), because the percentage error is unbounded for forecasts that are too high, while for low forecasts it cannot exceed 100%.