Abstract
A semantics for possibilistic evidential reasoning is presented based on similarity with paradigmatic examples. The acquisition of evidence generates a pseudo-metric on the universe of discourse. It is shown that every possibility distribution can be realized as an embedding in a pseudo-metric space with the possibility values determined by the distance from distinguished elements in that space. Determining support based on similarity captures the fundamental characteristics of possibilistic analysis: optimistic and independent evaluation of the alternatives. The similarity semantics distinguishes possibility from classical approaches to classification and diagnosis problems based on probabilistic techniques.
| Original language | English |
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| Pages | 735-740 |
| Number of pages | 6 |
| DOIs | |
| State | Published - 2000 |
| Event | FUZZ-IEEE 2000: 9th IEEE International Conference on Fuzzy Systems - San Antonio, TX, USA Duration: May 7 2000 → May 10 2000 |
Conference
| Conference | FUZZ-IEEE 2000: 9th IEEE International Conference on Fuzzy Systems |
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| City | San Antonio, TX, USA |
| Period | 5/7/00 → 5/10/00 |
ASJC Scopus Subject Areas
- Software
- Theoretical Computer Science
- Artificial Intelligence
- Applied Mathematics
Keywords
- Computer science
- Heart
- Histograms
- Independent component analysis
- Information analysis
- Information theory
- Pattern analysis
- Pattern recognition
- Possibility theory
- Set theory
Disciplines
- Computer Sciences
- Engineering
- Mathematics
- Physical Sciences and Mathematics