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Flexible Control of Case-Based Prediction in the Framework of Possibility Theory

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Advances in Case-Based Reasoning (EWCBR 2000)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1898))

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Abstract

The “similar problem-similar solution” hypothesis underlying case-based reasoning is modelled in the framework of possibility theory and fuzzy sets. Thus, case-based prediction can be realized in the form of fuzzy set-based approximate reasoning. The inference process makes use of fuzzy rules. It is controlled by means of modifier functions acting on such rules and related similarity measures. Our approach also allows for the incorporation of domain-specific (expert) knowledge concerning the typicality (or exceptionality) of the cases at hand. It thus favors a view of case-based reasoning according to which the user interacts closely with the system in order to control the generalization beyond observed data. Our method is compared to instance-based learning and kernel-based density estimation. Loosely speaking, it adopts basic principles of these approaches and supplements them with the capability of combining knowledge and data in a flexible way.

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Author information

Authors and Affiliations

  1. Institut de Recherche en Informatique de Toulouse, Université Paul Sabatier, France

    Didier Dubois, Eyke Hüllermeier & Henri Prade

Authors
  1. Didier Dubois
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  2. Eyke Hüllermeier
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  3. Henri Prade
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Editor information

Editors and Affiliations

  1. Centre for Scientific and Technological Research (ITC-irst), Istituto Trention di Cultura, via Sommarive 18, 38050, Povo (Trento), Italy

    Enrico Blanzieri

  2. DISTA, University of Eastern Piedmont “Amedeo Avogadro”, C.so Borsalino 54, 15100, Alessandria, Italy

    Luigi Portinale

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© 2000 Springer-Verlag Berlin Heidelberg

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Dubois, D., Hüllermeier, E., Prade, H. (2000). Flexible Control of Case-Based Prediction in the Framework of Possibility Theory. In: Blanzieri, E., Portinale, L. (eds) Advances in Case-Based Reasoning. EWCBR 2000. Lecture Notes in Computer Science, vol 1898. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44527-7_7

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  • DOI: https://doi.org/10.1007/3-540-44527-7_7

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-67933-2

  • Online ISBN: 978-3-540-44527-2

  • eBook Packages: Springer Book Archive

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