Memetic micro-Genetic Algorithms for Cancer Data Classification

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

Intelligent Systems with Applications

Elsevier

Lugar: Ámsterdam; Año: 2023 vol. 17

2667-3053

Fast and precise medical diagnosis of human cancer is crucial for treatment decisions. Gene selection consists of identifying a set of informative genes from microarray data to allow high predictive accuracy in human cancer classification. This task is a combinatorial search problem, and optimisation methods can be applied for its resolution. In this paper, two memetic micro-genetic algorithms (M$mu$V1 and M$mu$V2) with different hybridisation approaches are proposed for feature selection of cancer microarray data. Seven gene expression datasets are used for experimentation. The comparison with stochastic state-of-the-art optimisation techniques concludes that problem-dependent local search methods combined with micro-genetic algorithms improve feature selection of cancer microarray data.