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International Workshop on Machine Learning and Data Mining in Pattern Recognition

MLDM 2001: Machine Learning and Data Mining in Pattern Recognition pp 35–51Cite as

Are Case-Based Reasoning and Dissimilarity-Based Classification Two Sides of the Same Coin?

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2123))

Abstract

Case-Based Reasoning is used when generalized knowledge is lacking. The method works on a set of cases formerly processed and stored in the case base. A new case is interpreted based on its similarity to cases in the case base. The closest case with its associated result is selected and presented as output of the system. Recently, Dissimilarity-based Classification has been introduced due to the curse of dimensionality of feature spaces and the problem arising when trying to make image features explicitly. The approach classifies samples based on their dissimilarity value to all training samples. In this paper, we are reviewing the basic properties of these two approaches. We show the similarity of Dissimilarity based Classification to Case-Based Reasoning. Finally, we conclude that Dissimilarity based Classification is a variant of Case-Based Reasoning and that most of the open problems in Dissimilarity-based Classification are research topics of Case-Based Reasoning.

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Author information

Authors and Affiliations

  1. Institute of Computer Vision and applied Computer Sciences, Arno-Nitzsche-Str. 45, 04277, Leipzig

    Petra Perner

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  1. Petra Perner
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Editors and Affiliations

  1. Institute of Computer Vision and Applied Computer Sciences, Arno-Nitzsche-Str. 45, 04277, Leipzig, Germany

    Petra Perner

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Perner, P. (2001). Are Case-Based Reasoning and Dissimilarity-Based Classification Two Sides of the Same Coin?. In: Perner, P. (eds) Machine Learning and Data Mining in Pattern Recognition. MLDM 2001. Lecture Notes in Computer Science(), vol 2123. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44596-X_4

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  • DOI: https://doi.org/10.1007/3-540-44596-X_4

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42359-1

  • Online ISBN: 978-3-540-44596-8

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