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

被引：0
|
作者：
Herrera, A. Fornells [1 ]
Dausa, J. Camps [1 ]
Golobardes i Ribe, E. [1 ]
Garrell i Guiu, J. M. [1 ]
机构：
[1] Univ Ramon Llull, Researching Grp Intelligence Syst Engn & Arquitec, Barcelona 08022, Spain
来源：
ARTIFICIAL INTELLIGENCE RESEARCH AND DEVELOPMENT | 2005年 / 131卷
关键词：
Reasoning Models; Machine Learning; Similarity Function; Case Base Reasoning; Genetic Programmming; Grammar Evolution;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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
引用
收藏
页码：231 / 238
页数：8
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