Classification when a priori evidence is ambiguous

Ronald P. S. Mahler

doi:10.1117/12.181027

29 July 1994 Classification when a priori evidence is ambiguous

Ronald P. S. Mahler

Proceedings Volume 2234, Automatic Object Recognition IV; (1994) https://doi.org/10.1117/12.181027
Event: SPIE's International Symposium on Optical Engineering and Photonics in Aerospace Sensing, 1994, Orlando, FL, United States

Abstract

This paper describes conditioned Dempster-Shafer (CDS) theory, a probabilistic calculus for dealing with possibly non-Bayesian evidence when underlying a priori knowledge is possibly non-Bayesian. The Dempster-Shafer composition operator can be `conditioned' to reflect the influence of any kind of a priori knowledge which can be modeled as a Dempster-Shafer belief measure. CDS is firmly grounded in probability theory via the theory of random sets. It is also a generalization of the Bayesian theory of evidence to the case when both evidence and a priori knowledge are ambiguous.

Citation Download Citation

Ronald P. S. Mahler "Classification when a priori evidence is ambiguous", Proc. SPIE 2234, Automatic Object Recognition IV, (29 July 1994); https://doi.org/10.1117/12.181027

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