Use of Dempster-Shafer theory to combine classifiers which use different class boundaries.

Autor: M.R. Ahmadzadeh, M. Petrou
Zdroj: Pattern Analysis & Applications; Mar2003, Vol. 6 Issue 1, p41-46, 6p
Abstrakt: Abstract In this paper we present the Dempster-Shafer theory as a framework within which the results of a Bayesian network classifier and a fuzzy logic-based classifier are combined to produce a better final classification. We deal with the case when the two original classifiers use different classes for the outcome. The problem of different classes is solved by using a superset of finer classes which can be combined to produce classes according to either of the two classifiers. Within the Dempster-Shafer formalism not only can the problem of different number of classes be solved, but the relative reliability of the classifiers can also be considered. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index
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