Pseudo-label neighborhood rough set: measures and attribute reductions
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Publication:1726344
DOI10.1016/j.ijar.2018.11.010zbMath1452.68236OpenAlexW2900648357MaRDI QIDQ1726344
Yuhua Qian, Hualong Yu, Shaochen Liang, Xibei Yang, Shang Gao
Publication date: 20 February 2019
Published in: International Journal of Approximate Reasoning (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.ijar.2018.11.010
conditional entropyattribute reductionneighborhood rough setconditional discrimination indexneighborhood decision error ratepseudo-label
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Cites Work
- Unnamed Item
- Unnamed Item
- A fuzzy rough set approach for incremental feature selection on hybrid information systems
- An incremental attribute reduction approach based on knowledge granularity under the attribute generalization
- Information-theoretic measures associated with rough set approximations
- Test cost sensitive multigranulation rough set: model and minimal cost selection
- Quick general reduction algorithms for inconsistent decision tables
- Local multigranulation decision-theoretic rough sets
- Tri-partition neighborhood covering reduction for robust classification
- Quick attribute reduct algorithm for neighborhood rough set model
- Neighborhood based decision-theoretic rough set models
- Neighborhood rough set based heterogeneous feature subset selection
- Gaussian kernel based fuzzy rough sets: model, uncertainty measures and applications
- Positive approximation: an accelerator for attribute reduction in rough set theory
- Local rough set: a solution to rough data analysis in big data
- Generation of rough sets reducts and constructs based on inter-class and intra-class information
- A novel incremental attribute reduction approach for dynamic incomplete decision systems
- Rough set models in multigranulation spaces
- Generalized rough set models determined by multiple neighborhoods generated from a similarity relation
- An efficient accelerator for attribute reduction from incomplete data in rough set framework
- Parallel attribute reduction in dominance-based neighborhood rough set
- Attribute reduction for sequential three-way decisions under dynamic granulation
- Feature selection in mixed data: a method using a novel fuzzy rough set-based information entropy
- Rough Set Approximations in Multi-granulation Fuzzy Approximation Spaces
- Conditional entropy for incomplete decision systems and its application in data mining
- Uncertainty Measures for Multigranulation Approximation Space
- Image Interpolation via Graph-Based Bayesian Label Propagation
- NEIGHBORHOOD SYSTEM BASED ROUGH SET: MODELS AND ATTRIBUTE REDUCTIONS
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