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. © Springer-Verlag Berlin Heidelberg 2007.
Cite
CITATION STYLE
Armengol, E. (2007). Usages of generalization in case-based reasoning. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4626 LNAI, pp. 31–45). Springer Verlag. https://doi.org/10.1007/978-3-540-74141-1_3
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