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Communication Dans Un Congrès Année : 2009

A memetic algorithm for gene selection and molecular classification of cancer

Résumé

Choosing a small subset of genes that enables a good classification of diseases on the basis of microarray data is a difficult optimization problem. This paper presents a memetic algorithm, called MAGS, to deal with gene selection for supervised classification of microarray data. MAGS is based on an embedded approach for attribute selection where a classifier tightly interacts with the selection process. The strength of MAGS relies on the synergy created by combining a problem specific crossover operator and a dedicated local search procedure, both being guided by relevant information from a SVM classifier. Computational experiments on 8 well-known microarray datasets show that our memetic algorithm is very competitive compared with some recently published studies.

Dates et versions

hal-03255430 , version 1 (09-06-2021)

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Béatrice Duval, Jin-Kao Hao, Jose-Crispin Hernandez. A memetic algorithm for gene selection and molecular classification of cancer. 11th Annual conference on Genetic and evolutionary computation, 2009, Montréal, Canada. pp.201 - 208, ⟨10.1145/1569901.1569930⟩. ⟨hal-03255430⟩

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