TDBF: Two‐dimensional belief function
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DOI: 10.1002/int.22135
Abstract: How to efficiently handle uncertain information is still an open issue. In this paper, a new method to deal with uncertain information, named as two‐dimensional belief function (TDBF), is presented. A TDBF has two components,… read more here.
Keywords: tdbf two; belief; dimensional belief; two dimensional ... See more keywords
An active multi-class classification using privileged information and belief function
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DOI: 10.1007/s13042-019-00991-w
Abstract: Many classification models, based on support vector machine, have been designed so far to improve classification performance in both supervised and semi-supervised learning. One of the studies which is done in this case is about… read more here.
Keywords: belief function; function active; privileged information; classification ... See more keywords
A note on the approximation of Shenoy's expectation operator using probabilistic transforms
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DOI: 10.1080/03081079.2019.1692006
Abstract: ABSTRACT Recently, a new way of computing an expected value in the Dempster–Shafer theory of evidence was introduced by Prakash P. Shenoy. Up to now, when they needed the expected value of a utility function… read more here.
Keywords: shenoy; approximation shenoy; expectation; operator ... See more keywords
Modeling Belief Propensity Degree: Measures of Evenness and Diversity of Belief Functions
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DOI: 10.1109/tsmc.2022.3219996
Abstract: Based on Klir’s framework of uncertainty, the total uncertainty (also called ambiguity) of belief function is linear addition of discord and nonspecificity. Though uncertainty measures of belief function have been discussed widely, there is no… read more here.
Keywords: belief function; uncertainty; belief; belief propensity ... See more keywords