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From information to evidence in a Bayesian network
conference contribution
posted on 2016-10-12, 13:40 authored by Ali Ben Mrad, Veronique Delcroix, Sylvain Piechowiak, Philip LeicesterPhilip LeicesterEvidence in a Bayesian network comes from information based on the observation of one or more variables. A review of the terminology leads to the assessment that two main types of non-deterministic evidence have been defined, namely likelihood evidence and probabilistic evidence but the distinction between fixed probabilistic evidence and not fixed probabilistic evidence is not clear, and neither terminology nor concepts have been clearly defined. In particular, the term soft evidence is confusing. The article presents definitions and concepts related to the use of non-deterministic evidence in Bayesian networks, in terms of specification and propagation. Several examples help to understand how an initial piece of information can be specified as a finding in a Bayesian network.
History
School
- Mechanical, Electrical and Manufacturing Engineering
Published in
7th European Workshop on Probabilistic Graphical Models Lecture Notes in Artificial IntelligencePages
33 - 48Citation
MRAD, A. ... et al., 2014. From information to evidence in a Bayesian network. IN: Proceedings of 2014 7th European Workshop on Probabilistic Graphical Models (PGM 2014), Utrecht, Netherlands, 17-19 September 2014, pp.33-48.Publisher
© SpringerVersion
- VoR (Version of Record)
Publisher statement
This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/Publication date
2014Notes
The final publication is available at Springer via: http://dx.doi.org/10.1007/978-3-319-11433-0_3.ISBN
9783319114323;9783319114330ISSN
0302-9743eISSN
1611-3349Publisher version
Book series
Lecture Notes in Artificial Intelligence;8754Language
- en