Abstract. The root-mean-squared error (RMSE) and mean absolute (MAE) are widely used metrics for evaluating models. Yet, there remains enduring confusion over their use, such that a standard practice is to present both, leaving it the reader decide which more relevant. In recent reprise 200-year debate Willmott Matsuura (2005) Chai Draxler (2014) give arguments favoring one metric or other. How...

We study in this paper the consequences of using the Mean Absolute Percentage Error (MAPE) as a measure of quality for regression models. We show that finding the best model under the MAPE is equivalent to doing weighted Mean Absolute Error (MAE) regression. We show that universal consistency of Empirical Risk Minimization remains possible using the MAPE instead of the MAE.

The paper employs Artificial Neural Network (ANN) to forecast foreign exchange rate in India during 1992-2009. We used two types of data set (daily and monthly) for US dollar, British pound, euro and Japanese yen. The performance of forecasting is quantified by using various loss functions namely root mean square error (RMSE), mean absolute error (MAE), mean absolute deviation (MAD) and mean ab...

Public health surveillance systems provide valuable data for reliable predication of future epidemic events. This paper describes a study that used nine types of infectious disease data collected through a national public health surveillance system in mainland China to evaluate and compare the performances of four time series methods, namely, two decomposition methods (regression and exponentia...

In this paper a new variation of the well known MAE (Mean Absolute Error) matching criterion for video coding applications, is introduced. The MAE criterion is simpler than the MSE criterion because of the lack of multiplication operations, but it achieves a lower performance in terms of PSNR and MSE. In this work we impose an additional statistical constraint over the MAE thus filling the perf...

–The aim of this paper is to evaluate the quality of object oriented modules. In this work neural network approach is used along with PSO (particle swarm optimization) to find out fault prone components of software. The evaluation measures used are Accuracy, MAE (Mean absolute error), RMSE (Root mean square error) and the results are calculated on different iterations. The Accuracy, MAE, RMSE i...

Platinum containing compounds are promising antitumor agents, but must enter cells before reaching their main biological target, namely DNA. Their distribution within the body, and hence their activity is to a large extent determined by their lipophilicity, thus there is a strong interest to develop computational methods to predict this important property. This study analyses accuracy of five m...