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An Algorithm for Identifying Fuzzy Measures with Ordinal Information

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Soft Methods in Probability, Statistics and Data Analysis

Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 16))

Abstract

Consider a decision problem in which the preferences of the decision maker can be modelled through the Choquet integral [2] with respect to a fuzzy measure [10]. This means that he follows some behavioural rules while making decision (see [1], [9]). Next step consists in obtaining such a measure. The problem of identifying fuzzy measures from learning data has always been a difficult problem occurring in the practical use of fuzzy measures [5], [6].

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References

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Author information

Authors and Affiliations

  1. Departamento de Estadística, I.O. y D.M., Calvo Sotelo s/n, 33007, Oviedo, Spain

    Pedro Miranda

  2. Université Pierre et Marie Curie- LIP6, 8, rue du Capitaine Scott, 75015, Paris, France

    Michel Grabisch

Authors
  1. Pedro Miranda
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  2. Michel Grabisch
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Editor information

Editors and Affiliations

  1. Systems Research Institute, Polish Academy of Sciences, ul. Newelska 6, 01-447, Warsaw, Poland

    Przemysław Grzegorzewski  & Olgierd Hryniewicz  & 

  2. Facultad de Ciencias, Departamento de Estadística e I.O. y D.M., Universidad de Oviedo, C/Calvo Sotelo, s/n, 33007, Oviedo, Spain

    María Ángeles Gil

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© 2002 Springer-Verlag Berlin Heidelberg

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Miranda, P., Grabisch, M. (2002). An Algorithm for Identifying Fuzzy Measures with Ordinal Information. In: Grzegorzewski, P., Hryniewicz, O., Gil, M.Á. (eds) Soft Methods in Probability, Statistics and Data Analysis. Advances in Intelligent and Soft Computing, vol 16. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1773-7_33

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  • DOI: https://doi.org/10.1007/978-3-7908-1773-7_33

  • Publisher Name: Physica, Heidelberg

  • Print ISBN: 978-3-7908-1526-9

  • Online ISBN: 978-3-7908-1773-7

  • eBook Packages: Springer Book Archive

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