On the independence requirement in Dempster-Shafer theory for combining classifiers providing statistical evidence |
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Authors: | Hakan Altınçay |
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Affiliation: | (1) Department of Computer Engineering, Eastern Mediterranean University Gazi Mağusa, Northern Cyprus, via Mersin 10, Turkey |
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Abstract: | In classifier combination, the relative values of beliefs assigned to different hypotheses are more important than accurate estimation of the combined belief function representing the joint observation space. Because of this, the independence requirement in Dempster’s rule should be examined from classifier combination point of view. In this study, it is investigated whether there is a set of dependent classifiers which provides a better combined accuracy than independent classifiers when Dempster’s rule of combination is used. The analysis carried out for three different representations of statistical evidence has shown that the combination of dependent classifiers using Dempster’s rule may provide much better combined accuracies compared to independent classifiers. |
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Keywords: | Dempster’ s combination rule Dempster-Shafer theory Independent classifiers Dependent classifiers Classifier combination Pattern classification |
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