Interval-Valued Fuzzy Observations in Bayes Classifier

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5788)


The paper considers the problem of pattern recognition based on Bayes rule. In this model of classification, we use interval-valued fuzzy observations. The paper focuses on the probability of error on certain assumptions. A probability of misclassifications is derived for a classifier under the assumption that the features are class-conditionally statistically independent, and we have interval-valued fuzzy information on object features instead of exact information. Additionally, a probability of the interval-valued fuzzy event is represented by the real number as upper and lower probability. Numerical example concludes the work.


Bayes rule probability of error interval-valued fuzzy observations 


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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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