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

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

Abstract

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.

Keywords

Loss Function Fuzzy Number Recognition Algorithm Decision Region Fuzzy Random Variable 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Robert Burduk
    • 1
  1. 1.Chair of Systems and Computer NetworksWroclaw University of TechnologyWroclawPoland

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