Mean absolute scaled error
Measure of forecasting quality
In statistics, the mean absolute scaled error (MASE) is a measure of the accuracy of forecasts. It is the mean absolute error of the forecast values, divided by the mean absolute error of the in-sample one-step naive forecast.
Nº Q6803610 ★
Común · Historia
Mean absolute scaled error
Measure of forecasting quality
In statistics, the mean absolute scaled error (MASE) is a measure of the accuracy of forecasts. It is the mean absolute error of the forecast values, divided by the mean absolute error of the in-sample one-step naive forecast.
En Wikipedia
Texto en inglés Aún no hay artículo en tu idioma: extracto en inglés.
In statistics, the mean absolute scaled error (MASE) is a measure of the accuracy of forecasts. It is the mean absolute error of the forecast values, divided by the mean absolute error of the in-sample one-step naive forecast. It was proposed in 2005 by statistician Rob J. Hyndman and decision scientist Anne B. Koehler, who described it as a "generally applicable measurement of forecast accuracy without the problems seen in the other measurements." The mean absolute scaled error has favorable properties when compared to other methods for calculating forecast errors, such as root-mean-square-deviation, and is therefore recommended for determining comparative accuracy of forecasts.
Texto: Wikipedia en inglés, CC BY-SA 4.0. ·
Cartas cercanas
-
MAPE
Measure of prediction accuracy of a forecast
Nº Q6803607 ★★
Sin ofertas
-
E
Error cuadrático medio
Nº Q1940696 ★★
Sin ofertas
-
M
Mean percentage error
Measure of statistical error
Nº Q6803635 ★
Sin ofertas
-
S
Symmetric mean absolute percentage error
Statistical accuracy measure
Nº Q7661311 ★
Sin ofertas
-
E
Error absoluto medio
Medida estadística simple del desajuste entre datos previstos y datos observados
Nº Q6803609 ★★
Sin ofertas
-
Error estándar
Propiedad estadística
Nº Q620994 ★★★
Sin ofertas