BECAS
ROJAS matias Gabriel
artículos
Título:
Memetic micro-Genetic Algorithms for Cancer Data Classification
Autor/es:
MATIAS GABRIEL ROJAS; ANA CAROLINA OLIVERA; JESSICA ANDREA CARBALLIDO; PABLO JAVIER VIDAL
Revista:
Intelligent Systems with Applications
Editorial:
Elsevier
Referencias:
Lugar: √Āmsterdam; Año: 2023 vol. 17
ISSN:
2667-3053
Resumen:
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.