Binary Sand Cat Swarm Optimization Algorithm for Wrapper Feature Selection on Biological Data

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dc.authoridSeyyedabbasi, Amir/0000-0001-5186-4499
dc.authorwosidSeyyedabbasi, Amir/HJH-7387-2023
dc.contributor.authorSeyyedabbasi, Amir
dc.date.accessioned2024-05-19T14:39:24Z
dc.date.available2024-05-19T14:39:24Z
dc.date.issued2023
dc.departmentİstinye Üniversitesien_US
dc.description.abstractIn large datasets, irrelevant, redundant, and noisy attributes are often present. These attributes can have a negative impact on the classification model accuracy. Therefore, feature selection is an effective pre-processing step intended to enhance the classification performance by choosing a small number of relevant or significant features. It is important to note that due to the NP-hard characteristics of feature selection, the search agent can become trapped in the local optima, which is extremely costly in terms of time and complexity. To solve these problems, an efficient and effective global search method is needed. Sand cat swarm optimization (SCSO) is a newly introduced metaheuristic algorithm that solves global optimization algorithms. Nevertheless, the SCSO algorithm is recommended for continuous problems. bSCSO is a binary version of the SCSO algorithm proposed here for the analysis and solution of discrete problems such as wrapper feature selection in biological data. It was evaluated on ten well-known biological datasets to determine the effectiveness of the bSCSO algorithm. Moreover, the proposed algorithm was compared to four recent binary optimization algorithms to determine which algorithm had better efficiency. A number of findings demonstrated the superiority of the proposed approach both in terms of high prediction accuracy and small feature sizes.en_US
dc.identifier.doi10.3390/biomimetics8030310
dc.identifier.issn2313-7673
dc.identifier.issue3en_US
dc.identifier.pmid37504198en_US
dc.identifier.scopus2-s2.0-85166290943en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.urihttps://doi.org10.3390/biomimetics8030310
dc.identifier.urihttps://hdl.handle.net/20.500.12713/4772
dc.identifier.volume8en_US
dc.identifier.wosWOS:001035119000001en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherMdpien_US
dc.relation.ispartofBiomimeticsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.snmz20240519_kaen_US
dc.subjectBinary Sand Cat Swarm Optimizationen_US
dc.subjectMetaheuristic Algorithmen_US
dc.subjectFeature Selectionen_US
dc.subjectBiological Dataen_US
dc.subjectOptimization Problemsen_US
dc.subjectClassificationen_US
dc.titleBinary Sand Cat Swarm Optimization Algorithm for Wrapper Feature Selection on Biological Dataen_US
dc.typeArticleen_US

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