Towards scalable fuzzy-rough feature selection

DOI10.1016/j.ins.2015.06.025zbMath1390.68534OpenAlexW2151257102MaRDI QIDQ1750063

Xianqiang Yang

Publication date: 17 May 2018

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

Full work available at URL: https://doi.org/10.1016/j.ins.2015.06.025

zbMATH Keywords

nearest neighborsfeature selectionfuzzy-rough setsfeature grouping

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items (9)

NEC: a nested equivalence class-based dependency calculation approach for fast feature selection using rough set theory ⋮ Recent fuzzy generalisations of rough sets theory: a systematic review and methodological critique of the literature ⋮ Noise-aware and correlation analysis-based for fuzzy-rough feature selection ⋮ A graph approach for fuzzy-rough feature selection ⋮ An extension of rough fuzzy set ⋮ Feature selection based on composition of rough sets induced by feature granulation ⋮ Min-max attribute-object bireducts: on unifying models of reducts in rough set theory ⋮ Discernibility matrix based incremental feature selection on fused decision tables ⋮ Incremental fuzzy rough sets based feature subset selection using fuzzy min-max neural network preprocessing

Uses Software

• UCI-ml

Cites Work

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• Finding rough and fuzzy-rough set reducts with SAT
• Attribute selection with fuzzy decision reducts
• Upper and lower images of a fuzzy set induced by a fuzzy relation: Applications to fuzzy inference and diagnosis
• A comparative study of fuzzy rough sets
• Fuzzy similarity-based nearest-neighbour classification as alternatives to their fuzzy-rough parallels
• 10.1162/153244303322753616

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