Results 21 to 30 of about 831,124 (298)
A High‐dimensional Focused Information Criterion
Scandinavian Journal of Statistics, 2017 AbstractThe focused information criterion for model selection is constructed to select the model that best estimates a particular quantity of interest, the focus, in terms of mean squared error. We extend this focused selection process to the high‐dimensional regression setting with potentially a larger number of parameters than the size of the sample.
Gueuning, Thomas, Claeskens, Gerda
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Genetic parameters and selection gain in tropical wheat populations via Bayesian inference [PDF]
Ciência Rural, 2022 : The development process of a new wheat cultivar requires time between obtaining the base population and selecting the most promising line. Estimating genetic parameters more accurately in early generations with a view to anticipating selection means ...
Henrique Caletti Mezzmo +5 more
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Sensors, 2023 A noise-resistant linearization model that reveals the true nonlinearity of the sensor is essential for retrieving accurate physical displacement from the signals captured by sensing electronics.
Wen-Hao Zhang +5 more
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Радіоелектронні і комп'ютерні системи, 2023 The subject matter of the article is the application of supervised machine learning for the task of object class recognition. The goal is enhancing functional efficiency in information-extreme technology (IET) for object class recognition.
Oleksandr Papchenko +2 more
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Stats, 2022 Model-based estimation of small area means can lead to reliable estimates when the area sample sizes are small. This is accomplished by borrowing strength across related areas using models linking area means to related covariates and random area effects.
Song Cai, J.N.K. Rao
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Prior-based Bayesian information criterion
Statistical Theory and Related Fields, 2019 We present a new approach to model selection and Bayes factor determination, based on Laplace expansions (as in BIC), which we call Prior-based Bayes Information Criterion (PBIC).
M. J. Bayarri +5 more
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, 2023 Bayesian information criterion (BIC) and Akaike information criterion (AIC) for selection of models (Step 1).
Mathieu Pelletier-Dumas (14025315) +8 more
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A New Meta-Criterion for Regularized Subspace Information Criterion
IEICE Transactions on Information and Systems, 2007 In order to obtain better generalization performance in supervised learning, model parameters should be determined appropriately, i.e., they should be determined so that the generalization error is minimized. However, since the generalization error is inaccessible in practice, the model parameters are usually determined so that an estimator of the ...
Hidaka, Y., Sugiyama, M.
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, 2023 Comparison of fitness of models based on Akaike information criterion (AIC) and Bayesian Information Criterion (BIC).
Milly Marston (181179) +5 more
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Information-extremе machine learning for object identification on the terrain [PDF]
Журнал інженерних наук, 2016 The article deals with the usage of a SURF local descriptor of key fragments to create a global descriptor BoF for objects of interest on terrain within task of recognition of armored technique in the controlled territory using images of air ...
V. V. Moskalenko, A. H. Korobov
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