Hybrid genetic algorithms and case-based reasoning systems

Authors:
Hyunchul Ahn;Kyoung-jae Kim;Ingoo Han
Affiliations:
Graduate School of Management, Korea Advanced Institute of Science and Technology, Seoul, Korea;Department of Information Systems, Dongguk University, Seoul, Korea;Graduate School of Management, Korea Advanced Institute of Science and Technology, Seoul, Korea
Venue:
CIS'04 Proceedings of the First international conference on Computational and Information Science
Year:
2004

Citing 6
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Abstract

Case-based reasoning (CBR) has been applied to various problem-solving areas for a long time because it is suitable to complex and unstructured problems. However, the design of appropriate case retrieval mechanisms to improve the performance of CBR is still a challenging issue. In this paper, we encode the feature weighting and instance selection within the same genetic algorithm (GA) and suggest simultaneous optimization model of feature weighting and instance selection. This study applies the novel model to corporate bankruptcy prediction. Experimental results show that the proposed model outperforms other CBR models.