An Attribute Reduction Method Using Neighborhood Entropy Measures in Neighborhood Rough Sets [PDF]
Entropy, 2019 Attribute reduction as an important preprocessing step for data mining, and has become a hot research topic in rough set theory. Neighborhood rough set theory can overcome the shortcoming that classical rough set theory may lose some useful information ...
Lin Sun +3 more
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A Neighborhood Rough Sets-Based Attribute Reduction Method Using Lebesgue and Entropy Measures [PDF]
Entropy, 2019 For continuous numerical data sets, neighborhood rough sets-based attribute reduction is an important step for improving classification performance. However, most of the traditional reduction algorithms can only handle finite sets, and yield low accuracy
Lin Sun +3 more
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Cost-sensitive Multigranulation Approximation of Neighborhood Rough Fuzzy Sets [PDF]
Jisuanji kexue, 2023 Multigranulation neighborhood rough sets are a new data processing mode in the theory of neighborhood rough sets,in which the target concept can be characterized by upper/lower approximate boundaries of optimistic and pessimistic,respectively ...
YANG Jie, KUANG Juncheng, WANG Guoyin, LIU Qun
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Feature selection based on neighborhood rough sets and Gini index [PDF]
PeerJ Computer Science, 2023 Neighborhood rough set is considered an essential approach for dealing with incomplete data and inexact knowledge representation, and it has been widely applied in feature selection.
Yuchao Zhang +8 more
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On Covering-Based Rough Intuitionistic Fuzzy Sets
Mathematics, 2022 Intuitionistic Fuzzy Sets (IFSs) and rough sets depending on covering are important theories for dealing with uncertainty and inexact problems. We think the neighborhood of an element is more realistic than any cluster in the processes of classification ...
R. Mareay +3 more
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Journal of Mathematics, 2021 Multigranulation rough set theory is an important tool to deal with the problem of multicriteria information system. The notion of fuzzy β-neighborhood has been used to construct some covering-based multigranulation fuzzy rough set (CMFRS) models through
Zaibin Chang, Lingling Mao
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Constructing three-way classifier with interval granulation neighborhood rough sets based on uncertainty invariance [PDF]
Frontiers in NeuroroboticsThree-way decision with neighborhood rough sets (3WDNRS) is effective in handling uncertain problems involving continuous data through the adjustment of the neighborhood radius. However, it faces two main limitations. Firstly, 3WDNRS relies on individual
Yongqi Wang +5 more
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Adaptive neighborhood rough set model for hybrid data processing: a case study on Parkinson’s disease behavioral analysis [PDF]
Scientific ReportsExtracting knowledge from hybrid data, comprising both categorical and numerical data, poses significant challenges due to the inherent difficulty in preserving information and practical meanings during the conversion process.
Imran Raza +6 more
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Weak Label Feature Selection Method Based on Neighborhood Rough Sets and Relief [PDF]
Jisuanji kexue, 2022 In multi-label learning and classification, existing feature selection algorithms based on neighborhood rough sets will use classification margin of samples as the neighborhood radius.However, when the margin is too large, the classification may be ...
SUN Lin, HUANG Miao-miao, XU Jiu-cheng
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Feature Subset Selection Based on Variable Precision Neighborhood Rough Sets
International Journal of Computational Intelligence Systems, 2021 Rough sets have been widely used in the fields of machine learning and feature selection. However, the classical rough sets have the problems of difficultly dealing with real-value data and weakly fault tolerance.
Yingyue Chen, Yumin Chen
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