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International Conference Image Analysis and Recognition

ICIAR 2009: Image Analysis and Recognition pp 359–368Cite as

Probability Error in Bayes Optimal Classifier with Intuitionistic Fuzzy Observations

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5627))

Abstract

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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Author information

Authors and Affiliations

  1. Chair of Systems and Computer Networks, Wroclaw University of Technology, Wybrzeze Wyspianskiego 27, 50-370, Wroclaw, Poland

    Robert Burduk

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  1. Robert Burduk
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Editor information

Editors and Affiliations

  1. Department of Electrical and Computer Engineering, University of Waterloo, N2L 3G1, Waterloo, Ontario, Canada

    Mohamed Kamel

  2. Faculty of Engineering, Institute of Biomedical Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal

    Aurélio Campilho

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Burduk, R. (2009). Probability Error in Bayes Optimal Classifier with Intuitionistic Fuzzy Observations. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2009. Lecture Notes in Computer Science, vol 5627. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02611-9_36

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  • DOI: https://doi.org/10.1007/978-3-642-02611-9_36

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02610-2

  • Online ISBN: 978-3-642-02611-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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