Sentence examples for average absolute percentage error from inspiring English sources

Secondly, a generalised neural network was trained to predict fibre diameter with an average absolute percentage error of 22.3% for the validation data.

A comparative analysis of the proposed models and existing slug frequency correlation on a high viscosity databank showed that the proposed correlation gave the best prediction with an average absolute percentage error (AAPE) of 19.91%.

ANFIS is proved to be the best among all the networks tried in this case with average absolute percentage error of 0.03% and regression coefficient of 1, whereas best performance shown by the FFBP RPP) with average absolute error of 2.26%.

Statistical parameters used in the study are average percentage error 'APE', average absolute percentage error (AAPE), average percentage error (APE), correlation coefficient (R), and standard deviation.

The average absolute percentage error (MAPE) is calculated from relation MAPE = frac{1}{n}mathop sum limits_{i = 1}^{n} frac{{left| {y_{i} - y_{i}^ right|}}{{y_{i}^ (3)The root mean squared error (RMSE) is calculated from relation RMSE = sqrt {MSE}.

and an average absolute percentage error of 2.78 ± 4.39%.

For example, the results from the public holidays in France showed an average mean absolute percentage error (MAPE) of 0.863%, and the accuracy improvements over a simple average combination method, the best individual method, and a weighted combination are 15.887%, 13.353%, and 3.034%, respectively.

The LMFF model was able to improve the average of root mean square error (RMSEave) and average of mean absolute percentage error (MAPEave) values of the multiple linear regression forecasts by about 18% and 21%, respectively.

> -wrap-foot> Abbreviations: MA, moving average; MAPE, mean absolute percentage error.

In particular, the upper third of Table 1 presents averages of mean absolute percentage error (MAPE) estimates from M = 50 replications of the same out-of-sample prediction exercises for six benchmark procedures.

Panel (a) visualizes the differences between the (averaged) cross-city mean absolute percentage error estimates for g) together with Eq. 3a and fitted with regularization and the corresponding estimates for c).