Salīdzināt metodes

	Skaidrotā MAPE (sMAPE)	Vidējā kvadrātiskā kļūda (RMSE)
Nozare	Modeļu novērtēšana	Modeļu novērtēšana
Saime	MCDM	MCDM
Izcelsmes gads	1985	1809
Autors	J. Scott Armstrong	Carl Friedrich Gauss
Tips	Symmetric percentage-based evaluation metric	Distance-based evaluation metric
Pirmavots	Armstrong, J. S. (1985). Long-range forecasting: from crystal ball to computer (2nd ed.). New York: John Wiley & Sons. ISBN: 978-0471082010	Gauss, C. F. (1809). Theoria Motus Corporum Coelestium in Sectionibus Conicis Solem Ambientium. Hamburg: Perthes and Besser.
Citi nosaukumi	sMAPE, SMAPE, symmetric MAPE	RMSE, RMS error, quadratic mean error
Saistītās	4	4
Kopsavilkums	Symmetric Mean Absolute Percentage Error is a refinement of MAPE that addresses its asymmetry by using the average of actual and predicted values as the denominator. Proposed by J. Scott Armstrong and refined by Makridakis (1993) and Hyndman & Koehler (2006), sMAPE treats over- and under-predictions symmetrically.	Root Mean Squared Error is a widely used metric that measures the average magnitude of prediction errors in regression models. Originating from Carl Friedrich Gauss's work on least-squares estimation (1809), RMSE quantifies how far predictions deviate from observed values by averaging the squared differences and taking the square root.