An efficient accelerator for attribute reduction from incomplete data in rough set framework

DOI10.1016/j.patcog.2011.02.020zbMath1218.68152OpenAlexW2004068299MaRDI QIDQ2275964

Witold Pedrycz, J. Y. Liang, Yuhua Qian, Chuangyin Dang

Publication date: 10 August 2011

Published in: Pattern Recognition (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.patcog.2011.02.020

zbMATH Keywords

rough set theorygranular computingfeature selectionincomplete information systemspositive approximation

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Pattern recognition, speech recognition (68T10)

Related Items (37)

Fuzzy-rough feature selection accelerator ⋮ Positive macroscopic approximation for fast attribute reduction ⋮ Local rough set: a solution to rough data analysis in big data ⋮ Attribute Reduction on Distributed Incomplete Decision Information System ⋮ Uncertainty and reduction of variable precision multigranulation fuzzy rough sets based on three-way decisions ⋮ A relative decision entropy-based feature selection approach ⋮ A fast heuristic attribute reduction approach to ordered decision systems ⋮ Approximate Reduction for the Interval-Valued Decision Table ⋮ Semi-supervised feature selection for partially labeled mixed-type data based on multi-criteria measure approach ⋮ Constructive and axiomatic approaches to hesitant fuzzy rough set ⋮ Multi-granularity Attribute Reduction ⋮ Incremental rough reduction with stable attribute group ⋮ A unified incremental updating framework of attribute reduction for two-dimensionally time-evolving data ⋮ Matrix representation of the conditional entropy for incremental feature selection on multi-source data ⋮ Knowledge reduction based on divide and conquer method in rough set theory ⋮ Multi-granulation dual hesitant fuzzy rough sets ⋮ Pseudo-label neighborhood rough set: measures and attribute reductions ⋮ Core set analysis in inconsistent decision tables ⋮ Test cost sensitive multigranulation rough set: model and minimal cost selection ⋮ Quick attribute reduction in inconsistent decision tables ⋮ Intuitionistic fuzzy multigranulation rough sets ⋮ Quick general reduction algorithms for inconsistent decision tables ⋮ On measurements of covering rough sets based on granules and evidence theory ⋮ Dominance-based rough set approach to incomplete ordered information systems ⋮ Efficient attribute reduction from the viewpoint of discernibility ⋮ Hierarchy on multigranulation structures: a knowledge distance approach ⋮ Bidirectional heuristic attribute reduction based on conflict region ⋮ Communication between information systems with covering based rough sets ⋮ Attribute group for attribute reduction ⋮ Hierarchical description of uncertain information ⋮ Attribute reduction in ordered decision tables via evidence theory ⋮ Pseudolabel decision-theoretic rough set ⋮ Accelerator for supervised neighborhood based attribute reduction ⋮ Three-way decision on information tables ⋮ Random sampling accelerator for attribute reduction ⋮ Multi-granulation hesitant fuzzy rough sets and corresponding applications ⋮ Updating attribute reduction in incomplete decision systems with the variation of attribute set

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