Hybrid Genetic Algorithm for Classifier Ensemble Selection 


Vol. 14,  No. 5, pp. 369-376, Oct.  2007
10.3745/KIPSTB.2007.14.5.369


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  Abstract

This paper proposes a hybrid genetic algorithm (HGA) for the classifier ensemble selection. HGA is added a local search operation for increasing the fine-turning of local area. This paper apply hybrid and simple genetic algorithms (SGA) to the classifier ensemble selection problem in order to show the superiority of HGA.And this paper propose two methods (SSO: Sequential Search Operations, CSO: Combinational Search Operations) of local search operation of hybrid genetic algorithm. Experimental results show that the HGA has better searching capability than SGA. The experiments show that the CSO considering the correlation among classifiers is better than the SSO.

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[IEEE Style]

Y. W. Kim and I. S. Oh, "Hybrid Genetic Algorithm for Classifier Ensemble Selection," The KIPS Transactions:PartB , vol. 14, no. 5, pp. 369-376, 2007. DOI: 10.3745/KIPSTB.2007.14.5.369.

[ACM Style]

Young Won Kim and Il Seok Oh. 2007. Hybrid Genetic Algorithm for Classifier Ensemble Selection. The KIPS Transactions:PartB , 14, 5, (2007), 369-376. DOI: 10.3745/KIPSTB.2007.14.5.369.

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