Root-mean-square error (RMSE) or mean absolute error (MAE): when to use them or not [PDF]
Geoscientific Model Development, 2022 The root-mean-squared error (RMSE) and mean absolute error (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 to the reader to decide ...
T. O. Hodson
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Decomposition of the mean absolute error (MAE) into systematic and unsystematic components. [PDF]
PLoS ONE, 2023 When evaluating the performance of quantitative models, dimensioned errors often are characterized by sums-of-squares measures such as the mean squared error (MSE) or its square root, the root mean squared error (RMSE).
Scott M Robeson, Cort J Willmott
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Root mean square error (RMSE) or mean absolute error (MAE)? – Arguments against avoiding RMSE in the literature [PDF]
Geoscientific Model Development, 2014 Both the root mean square error (RMSE) and the mean absolute error (MAE) are regularly employed in model evaluation studies. Willmott and Matsuura (2005) have suggested that the RMSE is not a good indicator of average model performance and might be
T. Chai, R. R. Draxler
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Mean Absolute Percentage Error untuk Evaluasi Hasil Prediksi Komoditas Laut [PDF]
JOINS (Journal of Information System), 2020 Volume ekspor komoditas gurita mengalami kenaikan dan stok di suatu daerah akan tidak merata dan berlebih, serta bahwa permintaan gurita di beberapa negara tujuan di Asia, Eropa dan Amerika telah meningkat secara signifikan.
Ida Nabillah, Indra Ranggadara
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Mean Absolute Percentage Error for regression models [PDF]
Neurocomputing, 2016 We study in this paper the consequences of using the Mean Absolute Percentage Error (MAPE) as a measure of quality for regression models. We prove the existence of an optimal MAPE model and we show the universal consistency of Empirical Risk Minimization based on the MAPE.
de Myttenaere, Arnaud +3 more
semanticscholar +13 more sources
Optimizing LSTM Models for EUR/USD Prediction in the context of reducing energy consumption: An Analysis of Mean Squared Error, Mean Absolute Error and R-Squared [PDF]
E3S Web of Conferences, 2023 The purpose of this study was to develop and evaluate a Long Short-Term Memory (LSTM) model for Forex prediction. The data used was reprocessed and the LSTM model was developed and trained using a supervised learning approach with popular deep learning ...
Echrigui Rania, Hamiche Mhamed
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The proximal map of the weighted mean absolute error [PDF]
PAMM, 2023 AbstractWe investigate the proximal map for the weighted mean absolute error function. An algorithm for its efficient and vectorized evaluation is presented. As a demonstration, this algorithm is applied to a nonsmooth energy minimization problem.
Lukas Baumgärtner +3 more
semanticscholar +6 more sources
Optimum design of chamfer masks using symmetric mean absolute percentage error [PDF]
EURASIP Journal on Image and Video Processing, 2019 Distance transform, a central operation in image and video analysis, involves finding the shortest path between feature and non-feature entries of a binary image.
Baraka Jacob Maiseli
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JOIV: International Journal on Informatics Visualization, 2020 — After being introduced in 2008, the rise in the price of bitcoin and the popularity of other cryptocurrencies triggered a growing discussion about how much energy was consumed during the production of this currency.
Febri Liantoni, Arif Agusti
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Lossless Image Compression Using Context-Dependent Linear Prediction Based on Mean Absolute Error Minimization [PDF]
EntropyThis paper presents a method for lossless compression of images with fast decoding time and the option to select encoder parameters for individual image characteristics to increase compression efficiency.
Grzegorz Ulacha, Mirosław Łazoryszczak
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