Local attribute reductions for decision tables

DOI10.1016/j.ins.2017.09.007zbMath1436.68351OpenAlexW2753804762MaRDI QIDQ781011

Jiyang Zou, Zheng Hua, Guilong Liu

Publication date: 16 July 2020

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2017.09.007

zbMATH Keywords

discernibility matrixreduction algorithmequivalence relationattribute reductiondecision table

Mathematics Subject Classification ID

Reasoning under uncertainty in the context of artificial intelligence (68T37) Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20)

Related Items

Attribute Reduction Algorithms for Relation Systems on Two Universal Sets ⋮ Boundary Region Reduction for Relation Systems ⋮ Topological reduction approaches for relation decision systems ⋮ Cost-sensitive three-way class-specific attribute reduction ⋮ Min-max attribute-object bireducts: on unifying models of reducts in rough set theory ⋮ Three-way class-specific attribute reducts from the information viewpoint ⋮ Quantitative three-way class-specific attribute reducts based on region preservations

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• An incremental attribute reduction approach based on knowledge granularity under the attribute generalization
• A novel method for attribute reduction of covering decision systems
• Variable-precision dominance-based rough set approach and attribute reduction
• Degrees of conditional (in)dependence: A framework for approximate Bayesian networks and examples related to the rough set-based feature selection
• Variable precision rough set model
• Approaches to knowledge reduction based on variable precision rough set model.
• A novel attribute reduction approach for multi-label data based on rough set theory
• Attribute reduction in ordered decision tables via evidence theory
• Parallel attribute reduction in dominance-based neighborhood rough set
• The investigation of the Bayesian rough set model
• Attribute reduction based on evidence theory in incomplete decision systems
• Dynamic programming approach to optimization of approximate decision rules
• Stable rule extraction and decision making in rough non-deterministic information analysis
• Matrix Approaches for Variable Precision Rough Approximations
• Rough sets
• Approaches to knowledge reductions in inconsistent systems
• Relationships Between Length and Coverage of Decision Rules