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Neuroevolution based multi-objective algorithm for gene selection and microarray classification
2022
Proceedings of the Genetic and Evolutionary Computation Conference Companion
Microarrays allow the expression level analysis of thousands of genes simultaneously; thus, it is a common technique used for cancer detection and diagnosis. However, existing microarray datasets have huge data dimension and class imbalance, therefore, it is important to find relevant genes that accurately set classes apart and allow building more reliable classification models. A multi-objective algorithm is proposed to evolve artificial neural networks' topology and connection weights for
doi:10.1145/3520304.3529058
fatcat:asvafy6lobcfhmlw7v7txlkzlm