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 | American English |
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Journal | Ninth IEEE International Conference of Fuzzy Systems |
DOIs | |
State | Published - Jan 1 2000 |
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