A Hybrid Particle Swarm Optimization Algorithm with Dynamic Adjustment of Inertia Weight Based on a New Feature Selection Method to Optimize SVM Parameters

Support vector machine (SVM) is a widely used and effective classifier. Its efficiency and accuracy mainly depend on the exceptional feature subset and optimal parameters. In this paper, a new feature selection method and an improved particle swarm optimization algorithm are proposed to improve the...

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Detalles Bibliográficos
Autores principales: Wang, Jing, Wang, Xingyi, Li, Xiongfei, Yi, Jiacong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10047894/
https://www.ncbi.nlm.nih.gov/pubmed/36981419
http://dx.doi.org/10.3390/e25030531

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10047894/
https://www.ncbi.nlm.nih.gov/pubmed/36981419
http://dx.doi.org/10.3390/e25030531

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