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International Conference on Case-Based Reasoning

ICCBR 2007: Case-Based Reasoning Research and Development pp 31–45Cite as

Usages of Generalization in Case-Based Reasoning

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4626))

Abstract

The aim of this paper is to analyze how the generalizations built by a CBR method can be used as local approximations of a concept. From this point of view, these local approximations can take a role similar to the global approximations built by eager learning methods. Thus, we propose that local approximations can be interpreted either as: 1) a symbolic similitude among a set of cases, 2) a partial domain model, or 3) an explanation of the system classification. We illustrate these usages by solving the Predictive Toxicology task.

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Authors and Affiliations

  1. IIIA, Artificial Intelligence Research Institute, CSIC, Spanish Council for Scientific Research, Campus UAB, 08193 Bellaterra, Catalonia, Spain)

    Eva Armengol

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  1. Eva Armengol
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Rosina O. Weber Michael M. Richter

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Armengol, E. (2007). Usages of Generalization in Case-Based Reasoning. In: Weber, R.O., Richter, M.M. (eds) Case-Based Reasoning Research and Development. ICCBR 2007. Lecture Notes in Computer Science(), vol 4626. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74141-1_3

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  • DOI: https://doi.org/10.1007/978-3-540-74141-1_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74138-1

  • Online ISBN: 978-3-540-74141-1

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