Two Methods of Combining Classifiers, Which are Based on Decision Templates and Theory of Evidence, in a Dispersed Decision-Making System

Abstract

Issues that are related to decision making that is based on dispersed knowledge are discussed in the paper. The main aim of the paper is to compare the results obtained using two different methods of conflict analysis in a dispersed decision-making system. The conflict analysis methods, used in the article, are discussed in the paper of Kuncheva et al. [5] and in the paper of Rogova [16]. These methods are used if the individual classifiers generate vectors that represent the probability distributions over different decision. Both methods belong to the class-indifferent group, i.e. methods that use all of decision profile matrices to calculate the support for each class. Also, both methods require training. These methods were used in a dispersed decision-making system which was proposed in the paper [12].