Error made of a time series forecasting predictive model.
How to interpret the indicator?
The Expected MAPE (MAPE - mean absolute percentage error) is the evaluation of the error made when using the predictive model to estimate the future values of the target, whatever the horizon. For each actual observed value, the predictive model calculates as many forecasted values as requested by the analyst. This is called the horizon of forecasts. Each of those forecasted values is compared to the corresponding actual ones. Then, for each possible horizon, a per-horizon MAPE can be calculated, which is the mean of the absolute differences between actual and forecasted values, expressed as a percentage of actual values. The Expected MAPE is the mean of all per-horizon MAPE values that have been calculated..
ExampleA Expected MAPE of 12% indicates that the error made when using a forecasted value will be of more or less 12%.
An Expected MAPE of zero indicates a perfect predictive model.
The absolute value of the differences is taken into account to evaluate the average error.