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Probability Error in Global Optimal Hierarchical Classifier with Intuitionistic Fuzzy Observations

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Hybrid Artificial Intelligence Systems (HAIS 2009)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5572))

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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, we consider the global optimal hierarchical classifier.

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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

Authors
  1. Robert Burduk
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Editors and Affiliations

  1. Grupo de Investigación GICAP, Área de Lenguajes Higher Polytechnic School, Universidad de Burgos, Burgos, Spain

    Emilio Corchado

  2. Department of Computer Science, University of Vermont, 33 Colchester Avenue, Burlington, VT, USA

    Xindong Wu

  3. Computer and Information Science, Helsinki University of Technology, P.O. Box 5400, 02015 HUT, Finland

    Erkki Oja

  4. Grupo de Investigación GICAP, Área de Lenguajes y Sistemas Informáticos, Departamento de Ingeniería Civil, Escuela Politécnica Superior, Universidad de Burgos, Campus Vena, Francisco de Vitoria, 09006, Burgos, Spain

    Álvaro Herrero  & Bruno Baruque  & 

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© 2009 Springer-Verlag Berlin Heidelberg

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Burduk, R. (2009). Probability Error in Global Optimal Hierarchical Classifier with Intuitionistic Fuzzy Observations. In: Corchado, E., Wu, X., Oja, E., Herrero, Á., Baruque, B. (eds) Hybrid Artificial Intelligence Systems. HAIS 2009. Lecture Notes in Computer Science(), vol 5572. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02319-4_64

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  • DOI: https://doi.org/10.1007/978-3-642-02319-4_64

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02318-7

  • Online ISBN: 978-3-642-02319-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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