Memetic micro-Genetic Algorithms for Cancer Data Classification

MATÍAS GABRIEL ROJAS; ANA CAROLINA OLIVERA; JESSICA ANDREA CARBALLIDO; PABLO JAVIER VIDAL

Intelligent Systems with Applications

Elsevier

Año: 2023 vol. 17 p. 200173 - 200173

2667-3053

Fast and precise medical diagnosis of human cancer is crucial for treatment decisions. Geneselection consists of identifying a set of informative genes from microarray data to allow highpredictive accuracy in human cancer classification. This task is a combinatorial search prob-lem, and optimisation methods can be applied for its resolution. In this paper, two memeticmicro-genetic algorithms (MμV1 and MμV2) with different hybridisation approaches areproposed for feature selection of cancer microarray data. Seven gene expression datasets areused for experimentation. The comparison with stochastic state-of-the-art optimisation tech-niques concludes that problem-dependent local search methods combined with micro-geneticalgorithms improve feature selection of cancer microarray data.