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Non-parametric Density Estimation Based on Label Semantics

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Soft Methods for Handling Variability and Imprecision

Part of the book series: Advances in Soft Computing ((AINSC,volume 48))

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Abstract

We propose a non-parametric density estimator based on label semantics, a framework for computing with words which allows to describe a numerical instance or set of instances in linguistic terms and to condition on a linguistic description. This will be the basis of the proposed density estimator, which is MSE consistent under certain regularity conditions. Experimental results illustrate the potential of the proposal.

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Author information

Authors and Affiliations

  1. Department of Engineering Mathematics, University of Bristol, Bristol, United Kingdom

    Jonathan Lawry

  2. Dept. of Mathematics, Statistics and Computing, University of Cantabria, Santander, Spain

    Inés González-Rodríguez

Authors
  1. Jonathan Lawry
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  2. Inés González-Rodríguez
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Editor information

Editors and Affiliations

  1. Université Paul Sabatier, Toulouse, France

    Didier Dubois  & Henri Prade  & 

  2. Universidad de Oviedo, Spain

    M. Asunción Lubiano  & María Ángeles Gil  & 

  3. Polish Academy of Sciences, Warsaw, Poland

    Przemysław Grzegorzewski

  4. Polish Academy of Sciences,, Warsaw, Poland

    Olgierd Hryniewicz

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© 2008 Springer-Verlag Berlin Heidelberg

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Lawry, J., González-Rodríguez, I. (2008). Non-parametric Density Estimation Based on Label Semantics. In: Dubois, D., Lubiano, M.A., Prade, H., Gil, M.Á., Grzegorzewski, P., Hryniewicz, O. (eds) Soft Methods for Handling Variability and Imprecision. Advances in Soft Computing, vol 48. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85027-4_23

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  • DOI: https://doi.org/10.1007/978-3-540-85027-4_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-85026-7

  • Online ISBN: 978-3-540-85027-4

  • eBook Packages: EngineeringEngineering (R0)

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