Selection of Fuzzy-Valued Loss Function in Two Stage Binary Classifier

Conference paper
Part of the Advances in Soft Computing book series (AINSC, volume 30)


In this paper, a model to deal with Bayesian hierarchical classifier, in which consequences of decision are fuzzy-valued, is introduced. The model is based on the notion of fuzzy random variable and also on a subjective ranking method for fuzzy number defined by Campos and González. The Bayesian hierarchical classifier is based on a decision-tree scheme for given tree skeleton and features to be used in each inertial nodes. The influence of selection of fuzzy-valued loss function on classification result is given. Finally, an example illustrating this case of Bayesian analysis is considered.


Loss Function Fuzzy Number Recognition Algorithm Decision Region Fuzzy Random Variable 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  1. 1.Chair of Systems and Computer NetworksWroclaw University of TechnologyWroclawPoland

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