Probability Error in Bayes Optimal Classifier with Intuitionistic Fuzzy Observations

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5627)


The paper considers the problem of classification error in pattern recognition. This model of classification is primarily based on the Bayes rule and secondarily on the notion of intuitionistic fuzzy sets. A probability of misclassifications is derived for a classifier under the assumption that the features are class-conditionally statistically independent, and we have intuitionistic fuzzy information on object features instead of exact information. Additionally, a probability of the intuitionistic fuzzy event is represented by the real number. Numerical example concludes the work.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

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

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