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Soft Methods in Probability, Statistics and Data Analysis pp 116–125Cite as

A New Calculus for Linguistic Prototypes in Data Analysis

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

Abstract

A random set semantics for imprecise concepts is introduced. It is then demonstrated how label descriptions of data sets can be learnt in this framework. These descriptions take the form of linguistic prototypes representing amalgams of elements. The potential of this approach for classification and query evaluation is then investigated.

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References

  1. Duda R., Hart P.: Pattern Classification and Scene Analysis, Wiley, New York (1973).

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  3. Lawry, J.: Label Prototypes for Modelling with Words, Proceedings of The North American Fuzzy Information Processing Society 2001 Conference, (2001).

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Author information

Authors and Affiliations

  1. Department of Engineering Mathematics, University of Bristol, Bristol, UK

    Jonathan Lawry

Authors
  1. Jonathan Lawry
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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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Lawry, J. (2002). A New Calculus for Linguistic Prototypes in Data Analysis. 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_9

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  • DOI: https://doi.org/10.1007/978-3-7908-1773-7_9

  • 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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