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CCIA
2005
Springer

Comparison of Strategies Based on Evolutionary Computation for the Design of Similarity Functions

8 years 9 months ago
Comparison of Strategies Based on Evolutionary Computation for the Design of Similarity Functions
One of the main keys in case-based reasoning system is the retrieval phase, where the most similar cases are retrieved by means of a similarity function. According to the problem, the similarity function must be selected and adapted depending on the characteristics and properties of the problem’s domain. The goal of this article is to present a platform called BRAIN, which incorporates strategies based on different evolutionary approaches to design similarity functions ad hoc for a domain to be used in a case-based reasoning system. The strategies are based on Genetic Programming and Grammar Evolution approaches. Both are applied to different data sets to study the influence of their characteristic in the accuracy rate and in the execution time. Keywords. Reasoning Models, Machine Learning, Similarity Function, Case Base Reasoning, Genetic Programmming, Grammar Evolution
Albert Fornells-Herrera, J. Camps Dausà, El
Added 26 Jun 2010
Updated 26 Jun 2010
Type Conference
Year 2005
Where CCIA
Authors Albert Fornells-Herrera, J. Camps Dausà, Elisabet Golobardes i Ribé, Josep Maria Garrell i Guiu
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