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Opposition-based sine cosine optimizer utilizing refraction learning and variable neighborhood search for feature selection
This paper proposes new improved binary versions of the Sine Cosine Algorithm (SCA) for the Feature Selection (FS) problem. FS is an essential machine learning and data mining task of choosing a subset of highly discriminating features from noisy, irrelevant, high-dimensional, and redundant features...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer US
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9547101/ https://www.ncbi.nlm.nih.gov/pubmed/36247211 http://dx.doi.org/10.1007/s10489-022-04201-z |