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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Analysis of Protein Folding Simulation with Moving Root Mean Square Deviation. [PDF]
J Chem Inf Model, 2023 We apply moving root-mean-square deviation (mRMSD), which does not require a reference structure, as a method for analyzing protein dynamics. This method can be used to calculate the root-mean-square deviation (RMSD) of structure between two specified ...
Maruyama Y +3 more
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Review of Root-Mean-Square Error Calculation Methods for Large Deployable Mesh Reflectors
International Journal of Aerospace Engineering, 2022 In the design of a large deployable mesh reflector, high surface accuracy is one of ultimate goals since it directly determines overall performance of the reflector. Therefore, evaluation of surface accuracy is needed in many cases of design and analysis
Sichen Yuan
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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 Layer Normalization [PDF]
Advances in Neural Information Processing Systems 32, 2019 Layer normalization (LayerNorm) has been successfully applied to various deep neural networks to help stabilize training and boost model convergence because of its capability in handling re-centering and re-scaling of both inputs and weight matrix.
Zhang, Biao, Sennrich, Rico
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A gait abnormality measure based on root mean square of trunk acceleration. [PDF]
J Neuroeng Rehabil, 2013 BackgroundRoot mean square (RMS) of trunk acceleration is seen frequently in gait analysis research. However, many studies have reported that the RMS value was related to walking speed.
Sekine M +8 more
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Voltage root mean square error calculation for solar cell parameter estimation: A novel g-function approach [PDF]
HeliyonThe existing research on estimating solar cell parameters mainly focuses on minimizing the Root-Mean-Square Error (RMSE) between the estimated and measured current values of solar cells (referred to as the RMSEI).
Martin Ćalasan +4 more
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Nucleon form factors and root-mean-square radii on a
Physical Review D, 2019 We present the nucleon form factors and root-mean-square (RMS) radii measured on a (10.8 fm$)^4$ lattice at the physical point. We compute the form factors at small momentum transfer region in $q^2\le 0.102$ GeV$^2$ with the standard plateau method ...
Eigo Shintani +4 more
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Correction to: Spasticity assessment based on the Hilbert-Huang transform marginal spectrum entropy and the root mean square of surface electromyography signals: a preliminary study. [PDF]
Biomed Eng Online, 2019 Hu B, Zhang X, Mu J, Wu M, Wang Y.
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Testing Hardy-Weinberg equilibrium with a simple root-mean-square statistic [PDF]
Biostatistics, 2013 We provide evidence that, in certain circumstances, a root-mean-square test of goodness of fit can be significantly more powerful than state-of-the-art tests in detecting deviations from Hardy-Weinberg equilibrium.
Rachel Ward, R. J. Carroll
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