Rough set theory-based group incremental approach to feature selection

DOI10.1016/j.ins.2024.120733MaRDI QIDQ6556445

Jie Zhao, Dai-Yang Wu, Jia-ming Liang, Wenhong Wei, Yongxin Zhou, Yun Li

Publication date: 17 June 2024

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

zbMATH Keywords

data miningrough set theorymachine learningfeature selectionattribute reduction

Mathematics Subject Classification ID

Biology and other natural sciences (92-XX) Computer science (68-XX)

Cites Work

• Rudiments of rough sets
• A novel incremental attribute reduction approach for dynamic incomplete decision systems
• Incremental fuzzy rough sets based feature subset selection using fuzzy min-max neural network preprocessing
• An incremental attribute reduction method for dynamic data mining
• Discernibility matrix based incremental feature selection on fused decision tables
• Converse approximation and rule extraction from decision tables in rough set theory
• NEC: a nested equivalence class-based dependency calculation approach for fast feature selection using rough set theory
• Rough sets
• Novel variable precision fuzzy rough sets and three-way decision model with three strategies
• Incremental feature selection approach to interval-valued fuzzy decision information systems based on \(\lambda\)-fuzzy similarity self-information
• A bi-variable precision rough set model and its application to attribute reduction
• Incremental feature selection with fuzzy rough sets for dynamic data sets

Related Items (1)

Covering rough set models, fuzzy rough set models and soft rough set models induced by covering similarity

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