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Mean Squared Error, Deconstructed [PDF]
Journal of Advances in Modeling Earth Systems, 2021 AbstractAs science becomes increasingly crossâdisciplinary and scientific models become increasingly crossâcoupled, standardized practices of model evaluation are more important than ever. For normally distributed data, mean squared error (MSE) is ideal as an objective measure of model performance, but it gives little insight into what aspects of model
Thomas Over +2 more
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Grid Search for Lowest Root Mean Squared Error in Predicting Optimal Sensor Location in Protected Cultivation Systems [PDF]
Frontiers in Plant Science, 2022 Irregular changes in the internal climates of protected cultivation systems can prevent attainment of optimal yield when the environmental conditions are not adequately monitored and controlled.
Daniel Dooyum Uyeh +12 more
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Mean Squared Error Representative Points of Pareto Distributions and Their Estimation [PDF]
EntropyPareto distributions are widely applied in various fields, such as economics, finance, and environmental studies. The modeling of real-world data has created a demand for the discretization of Pareto distributions.
Xinyang Li, Xiaoling Peng
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Journal of Hydrology, 2009 The mean squared error (MSE) and the related normalization, the Nash-Sutcliffe efficiency (NSE), are the two criteria most widely used for calibration and evaluation of hydrological models with observed data. Here, we present a diagnostically interesting
Hoshin Vijai Gupta +2 more
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Ensemble Averaging and Mean Squared Error
Journal of Climate, 2016 Abstract In fields such as climate science, it is common to compile an ensemble of different simulators for the same underlying process. It is a striking observation that the ensemble mean often outperforms at least half of the ensemble members in mean squared error (measured with respect to observations). In fact, as demonstrated in the
J. Rougier
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Exact Mean Integrated Squared Error
The Annals of Statistics, 1992 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Marron, J. S., Wand, M. P.
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Minimum Mean Squared Error Estimation and Mutual Information Gain
InformationInformation theoretic quantities such as entropy, entropy rate, information gain, and relative entropy are often used to understand the performance of intelligent agents in learning applications. Mean squared error has not played a role in these analyses,
Jerry Gibson
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Perceptual Fidelity Aware Mean Squared Error [PDF]
2013 IEEE International Conference on Computer Vision, 2013 How to measure the perceptual quality of natural images is an important problem in low level vision. It is known that the Mean Squared Error (MSE) is not an effective index to describe the perceptual fidelity of images. Numerous perceptual fidelity indices have been developed, while the representatives include the Structural SIMilarity (SSIM) index and
Wufeng Xue +3 more
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Comparing Kullback-Leibler Divergence and Mean Squared Error Loss in Knowledge Distillation [PDF]
International Joint Conference on Artificial Intelligence, 2021 Knowledge distillation (KD), transferring knowledge from a cumbersome teacher model to a lightweight student model, has been investigated to design efficient neural architectures.
Taehyeon Kim +4 more
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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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