The problem with percentage errors that is often overlooked is that they assume a meaningful zero. For example, a percentage error makes no sense when measuring the accuracy of temperature forecasts on the Fahrenheit or Celsius scales.
It means that percentage errors are useful only when changing the scale does not make any difference to the percentage error. It is said that percentage error is not useful incase of Celsius and Fahrenheit calculation because consider forecasted value is 10 degree and actual value is 11 degree then percentage error is 9.09% but the same thing gives a different solution when we convert to Fahrenheit, 10 degree Celsius is 50 Fahrenheit and 11 degree is 51.8 Fahrenheit so here the percentage error becomes 3.47%.
But when we consider a different measure like meters and inches, here we have a meaningful zero. Forecasted is 10 m and actual is 11m then percentage error is 9.09% . 10m is 393.7 inch and 11m is 433.07 inch and here the percentage error is also 9.09%.
They (MAPE) also have the disadvantage that they put a heavier penalty on negative errors than on positive errors.
This means that if there are negative errors the MAPE value becomes higher than for positive cases. Example if forecasted value is 27 and actual is 23 then MAPE is 17% and if forecasted is 23 and actual is 27 then MAPE is 14.8%. Though the absolute difference in both cases is 4 but the negative error gives a higher percentage error when compared to positive error.
Žádné komentáře:
Okomentovat