Skip to Main content Skip to Navigation
Conference papers

Why Dempster's fusion rule is not a generalization of Bayes fusion rule

Abstract : In this paper, we analyze Bayes fusion rule in details from a fusion standpoint, as well as the emblematic Dempster's rule of combination introduced by Shafer in his Mathematical Theory of evidence based on belief functions. We propose a new interesting formulation of Bayes rule and point out some of its properties. A deep analysis of the compatibility of Dempster's fusion rule with Bayes fusion rule is done. We show that Dempster's rule is compatible with Bayes fusion rule only in the very particular case where the basic belief assignments (bba's) to combine are Bayesian, and when the prior information is modeled either by a uniform probability measure, or by a vacuous bba. We show clearly that Dempster's rule becomes incompatible with Bayes rule in the more general case where the prior is truly informative (not uniform, nor vacuous). Consequently, this paper proves that Dempster's rule is not a generalization of Bayes fusion rule.
Keywords : INFORMATION FUSION
Document type :
Conference papers
Complete list of metadata

https://hal.inrae.fr/hal-02605934
Contributor : Migration Irstea Publications Connect in order to contact the contributor
Submitted on : Saturday, May 16, 2020 - 11:38:40 AM
Last modification on : Tuesday, September 7, 2021 - 3:54:53 PM

Identifiers

  • HAL Id : hal-02605934, version 1
  • IRSTEA : PUB00053638

Collections

Citation

J. Dezert, A. Tchamova, D. Han, J.M. Tacnet. Why Dempster's fusion rule is not a generalization of Bayes fusion rule. 16th International Conference on Information Fusion, Jul 2013, Istanbul, Turkey. pp.8. ⟨hal-02605934⟩

Share

Metrics

Record views

27