Semi-supervised feature selection via fuzzy C-means clustering and simulated annealing optimization
Abstract Feature selection is a critical step in machine learning, as it helps minimize redundant features, thereby enhancing model performance and interpretability. In practice, partially labeled datasets are common. When some data labels are unavailable, semi-supervised feature selection has becom...
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| Principais autores: | , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Springer
2026-02-01
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| coleção: | Journal of King Saud University: Computer and Information Sciences |
| Assuntos: | |
| Acesso em linha: | https://doi.org/10.1007/s44443-026-00502-2 |
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