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Feature Selection using Salp Swarm Algorithm for Real Biomedical Datasets


Hadeel Tariq Ibrahim, Wamidh Jalil Mazher, Osman N. Ucan1 ,Oguz Bayat


Vol. 17  No. 12  pp. 13-20


The main objective of this paper is to develop a new powerful heuristic optimization algorithm to be used in feature selection. Here, the use of Salp Swarm Algorithm in feature selection (SSA-FS) is proposed for the first time in literature. SSA-FS has been compared with Particle Swarm Optimization and Differential Evolution performance with criteria of accuracy and runtime. In this paper, real datasets obtained from Iraqi hospitals for breast, bladder and colon cancers and synthetic datasets for evaluation. We have found that SSA-FS has been achieved the highest accuracies with less runtime in comparison with other selected algorithms for both real and synthetic datasets.


Feature selection, Salp Swarm Algorithm, Particle Swarm Optimization, Differential Evolution