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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.
El error escalado absoluto medio (MASE) es una métrica de error sin escala que proporciona cada error como una proporción en comparación con el error promedio de una línea de base.
17 de nov. de 2014 · Mean absolute scaled error (MASE) is a measure of forecast accuracy proposed by Koehler & Hyndman (2006). $$MASE=\frac{MAE}{MAE_{in-sample, \, naive}}$$ where $MAE$ is the mean absolute error produced by the actual forecast;
Calcula el error de escala absoluta de media (MASE) entre el pronóstico y los eventuales resultados. Sintaxis. MASE(X, F, M) X es el resultado eventual de la muestra de datos de una serie de tiempo (un despliegue de celdas unidimensional (Ej. fila o columna). F
What is Mean Absolute Scaled Error? Mean Absolute Scaled Error (MASE) is a scale-free error metric that gives each error as a ratio compared to a baseline’s average error.
11 de ene. de 2021 · In time series forecasting, Mean Absolute Scaled Error (MASE) is a measure for determining the effectiveness of forecasts generated through an algorithm by comparing the predictions with...
Calculate the mean absolute scaled error. This metric is scale independent and symmetric. It is generally used for comparing forecast error in time series settings. Due to the time series nature of this metric, it is necessary to order observations in ascending order by time.
