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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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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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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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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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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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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Indian natural rubber price forecast–An Autoregressive Integrated Moving Average (ARIMA) approach
The Indian Journal of Agricultural Sciences, 2022 The objective of this study was to forecast the price of natural rubber in India during April 2019 to March 2020 by employing autoregressive integrated moving average (ARIMA).
SHYJU MATHEW, RAMASAMY MURUGESAN
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Mid-Term Residential Load Forecasting Based on Neighborhood Component Analysis Feature Selection [PDF]
هوش محاسباتی در مهندسی برق, 2022 Residential load forecasting plays an important role in management and planning in modern smart grids. In planning to keep demand and supply balanced, accurate residential load forecasting is needed.
Iman Bahadornejad +4 more
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The coefficient of determination R-squared is more informative than SMAPE, MAE, MAPE, MSE and RMSE in regression analysis evaluation [PDF]
PeerJ Computer Science, 2021 Regression analysis makes up a large part of supervised machine learning, and consists of the prediction of a continuous independent target from a set of other predictor variables.
Davide Chicco +2 more
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