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Hybrid Genetic Algorithms for Feature Selection and Classification Performance Comparisons  

오일석 (전북대학교 전자정보공학부)
이진선 (우석대학교 컴퓨터공학)
문병로 (서울대학교 컴퓨터공학부)
Publication Information
Journal of KIISE:Software and Applications / v.31, no.8, 2004 , pp. 1113-1120 More about this Journal
Abstract
This paper proposes a novel hybrid genetic algorithm for the feature selection. Local search operations are devised and embedded in hybrid GAs to fine-tune the search. The operations are parameterized in terms of the fine-tuning power, and their effectiveness and timing requirement are analyzed and compared. Experimentations performed with various standard datasets revealed that the proposed hybrid GA is superior to a simple GA and sequential search algorithms.
Keywords
feature selection; hybrid genetic algorithm; sequential search algorithm; local search operation;
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