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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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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Moments and Root-Mean-Square Error of the Bayesian MMSE Estimator of Classification Error in the Gaussian Model. [PDF]
Pattern Recognit, 2014 The most important aspect of any classifier is its error rate, because this quantifies its predictive capacity. Thus, the accuracy of error estimation is critical. Error estimation is problematic in small-sample classifier design because the error must be estimated using the same data from which the classifier has been designed. Use of prior knowledge,
Zollanvari A, Dougherty ER.
europepmc +8 more sources
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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Potential root mean square error skill score [PDF]
Journal of Renewable and Sustainable EnergyConsistency, in a narrow sense, denotes the alignment between the forecast-optimization strategy and the verification directive. The current recommended deterministic solar forecast verification practice is to report the skill score based on root mean ...
Martin János Mayer, Dazhi Yang
semanticscholar +4 more sources
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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Root mean square error (RMSE) or mean absolute error (MAE) [PDF]
, 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 a ...
T. Chai, R. Draxler
semanticscholar +2 more sources
Soundness and completeness of quantum root-mean-square errors [PDF]
npj Quantum Information, 2018 Defining and measuring the error of a measurement is one of the most fundamental activities in experimental science. However, quantum theory shows a peculiar difficulty in extending the classical notion of root-mean-square (rms) error to quantum ...
M. Ozawa
semanticscholar +5 more sources
Colloquium: Quantum root-mean-square error and measurement uncertainty relations [PDF]
Reviews of Modern Physics, 2013 Recent years have witnessed a controversy over Heisenberg's famous error-disturbance relation. Here we resolve the conflict by way of an analysis of the possible conceptualizations of measurement error and disturbance in quantum mechanics. We discuss two
P. Busch, P. Lahti, R. Werner
semanticscholar +4 more sources
Root Mean Square Error of Neural Spike Train Sequence Matching with Optogenetics [PDF]
GLOBECOM 2017 - 2017 IEEE Global Communications Conference, 2017 Optogenetics is an emerging field of neuroscience where neurons are genetically modified to express light-sensitive receptors that enable external control over when the neurons fire.
Eckford, Andrew W. +2 more
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