Robust Classification Using Posterior Probability Threshold Computation Followed by Voronoi Cell Based Class Assignment Circumventing Pitfalls of Bayesian Analysis of Biomedical Data. [PDF]
Int J Mol Sci, 2022 Ultsch A, Lötsch J.
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Correction: Chatzimichail, T.; Hatjimihail, A.T. A Software Tool for Estimating Uncertainty of Bayesian Posterior Probability for Disease. Diagnostics 2024, 14, 402. [PDF]
Diagnostics (Basel)Chatzimichail T, Hatjimihail AT.
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On Focal Loss for Class-Posterior Probability Estimation: A Theoretical Perspective [PDF]
Computer Vision and Pattern Recognition, 2020 The focal loss has demonstrated its effectiveness in many real-world applications such as object detection and image classification, but its theoretical understanding has been limited so far.
Nontawat Charoenphakdee +3 more
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Change threshold selection (CTS) plays an important role in land cover change detection. The traditional CTS methods are mainly based on the information contained in grayscale histogram distributions or pixel neighborhoods.
H. Xing +6 more
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Reconnecting p-Value and Posterior Probability Under One- and Two-Sided Tests [PDF]
American Statistician, 2018 As a convention, p-value is often computed in frequentist hypothesis testing and compared with the nominal significance level of 0.05 to determine whether or not to reject the null hypothesis. The smaller the p-value, the more significant the statistical
Haolun Shi, Guosheng Yin
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Deterministic and stochastic models of infection spread and testing in an isolated contingent
Журнал Белорусского государственного университета: Математика, информатика, 2021 The mathematical SIR model generalisation for description of the infectious process dynamics development by adding a testing model is considered. The proposed procedure requires the expansion of states’ space dimension due to variables that cannot be ...
Anatoliy V. Chigarev +2 more
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Incentive-Compatible Surveys via Posterior Probabilities [PDF]
Theory of Probability & Its Applications, 2020 We consider the problem of eliciting truthful responses to a survey question when the respondents share a common prior that the survey planner is agnostic about. The planner would therefore like to have a “universal” mechanism, which would induce honest answers for all possible priors. If the planner also requires a locality condition that ensures that
Cvitanić, J +3 more
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ACM Trans. Inf. Syst., 2020 We critically re-examine the Saerens-Latinne-Decaestecker (SLD) algorithm, a well-known method for estimating class prior probabilities (“priors”) and adjusting posterior probabilities (“posteriors”) in scenarios characterized by distribution shift, i.e.,
Andrea Esuli +2 more
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Posterior probability maps and SPMs [PDF]
NeuroImage, 2003 This technical note describes the construction of posterior probability maps that enable conditional or Bayesian inferences about regionally specific effects in neuroimaging. Posterior probability maps are images of the probability or confidence that an activation exceeds some specified threshold, given the data.
K J, Friston, W, Penny
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Probabilistic River Water Mapping from Landsat-8 Using the Support Vector Machine Method
Remote Sensing, 2020 River water extent is essential for river hydrological surveys. Traditional methods for river water mapping often result in significant uncertainties. This paper proposes a support vector machine (SVM)-based river water mapping method that can quantify ...
Qihang Liu +3 more
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