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What does MAE stand for?

Mean Absolute Error


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This definition appears very rarely and is found in the following Acronym Finder categories:

  • Science, medicine, engineering, etc.

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Massachusetts Association of Electrologists, Inc.
Máster en Administración de Empresas
Master of Applied Epidemiology
Master of Arts in Economics (degree)
Master of Arts in Education
Material Adverse Event
Mathematics in Engineering (various schools)
Matlab for Engineers (class)
Maximum Allowable Emissions
Maximum Allowable Exposure
Mean Area of Effectiveness
Mechanical and Aerospace Engineering
Mechanical/Auxiliary Equipment
Medium Altitude Endurance
Member of the Academy of Experts (for expert witnesses in the UK)
Mercado Abierto Electrónico SA (Argentina)
Mercado Atacadista de Energia
Mesures AgroEnvironnementales
Metro Area Ethernet
Metropolitan Access Exchange (Worldcom)



Samples in periodicals archive:
Mean absolute error WE) is generally a more appropriate indicator of predictive variability, and is especially suitable in cases of outlying prediction errors.
Large forecast errors are given more weight in the mean square error than in the mean absolute error.
One model may perform worse compared to other model in terms of mean absolute error or root mean square error, but is that difference in performance is significant?
Over a 12-month horizon, the mean absolute error of professional forecasts of the unemployment rate is 0.
Each method of estimation was compared as mean absolute error (estimate minus actual birth weight), standardized error (absolute error/actual birth weight), and percentage of estimates within 10% of actual birth weight.
In Tables 2 to 3, we give the parameter estimates and the mean square error (MSE), the mean absolute error (MAE), the maximum absolute error (MAXABS) and the Gini index for each country, where MSE = [[[sigma].
For instance, even GARCH has a mean absolute error of about 28 basis points and a mean percentage error of around 36%.
Under this approach, the weights assigned to the forecasts are based on inverse proportions of their individual accuracy as measured by mean absolute error (MAE).

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