Attribute reduction based on overlap degree and \(k\)-nearest-neighbor rough sets in decision information systems
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Publication:6188196
DOI10.1016/j.ins.2021.10.063OpenAlexW3213473583MaRDI QIDQ6188196
Meng Hu, De-Gang Chen, Wei-Hua Xu, Eric C. C. Tsang, Yanting Guo
Publication date: 1 February 2024
Published in: Information Sciences (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.ins.2021.10.063
Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05) Computational aspects of data analysis and big data (68T09)
Cites Work
- Unnamed Item
- Neighborhood rough set based heterogeneous feature subset selection
- Variable precision rough set model
- Neighborhood operator systems and approximations
- Attribute reduction based on \(k\)-nearest neighborhood rough sets
- Attribute group for attribute reduction
- Incremental approaches for heterogeneous feature selection in dynamic ordered data
- Local logical disjunction double-quantitative rough sets
- Feature selection using neighborhood entropy-based uncertainty measures for gene expression data classification
- Parallel attribute reduction in dominance-based neighborhood rough set
- Fuzzy sets in a approximate reasoning. I: Inference with possibility distributions
- ROUGH FUZZY SETS AND FUZZY ROUGH SETS*
- Rough sets
- Fuzzy sets
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