A novel covering rough set model based on granular-ball computing for data with label noise
As a novel granular computing model, granular-ball computing (GBC) has a notable advantage of robustness. Inspired by GBC, a granular-ball covering rough set (GBCRS) model whose covering is made up of granular-balls (GBs) is proposed. GBCRS is the first covering rough set that fits the data distribu...
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| Published in | International journal of approximate reasoning Vol. 182; p. 109420 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier Inc
01.07.2025
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0888-613X |
| DOI | 10.1016/j.ijar.2025.109420 |
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| Abstract | As a novel granular computing model, granular-ball computing (GBC) has a notable advantage of robustness. Inspired by GBC, a granular-ball covering rough set (GBCRS) model whose covering is made up of granular-balls (GBs) is proposed. GBCRS is the first covering rough set that fits the data distribution well. Inheriting the robustness of GBC, GBCRS can work in label noise environments. First, the optimization objective function of GBs in GBCRS is given. In order to ensure the quality of generated GBs, this function is subject to three constraints. Second, the GBCRS model is proposed. The purity threshold is used to relax the related notions so that GBCRS can be used in label noise environments. Subsequently, GBCRS is applied to the covering granular reduction and attribute reduction in label noise environments. In covering granular reduction, we propose an intuitive, understandable and anti-noise GBCRS-based granular reduction (GBCRS-GR) algorithm, which also solves the optimization objective function of GBs. Based on GBCRS-GR, a GBCRS-based attribute reduction (GBCRS-AR) algorithm is proposed with the classification ability of the attribute subset as the evaluation. The experiments on UCI datasets illustrate that proposed algorithm is more robust against label noise than the comparison ones.
•Innovative GBCRS is proposed for both granular and attribute reduction to simplify the knowledge base.•GBCRS is the first CRS model that fits the data distribution.•GBCRS not only takes decision attributes into consideration, but also has robustness to the label noise. |
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| AbstractList | As a novel granular computing model, granular-ball computing (GBC) has a notable advantage of robustness. Inspired by GBC, a granular-ball covering rough set (GBCRS) model whose covering is made up of granular-balls (GBs) is proposed. GBCRS is the first covering rough set that fits the data distribution well. Inheriting the robustness of GBC, GBCRS can work in label noise environments. First, the optimization objective function of GBs in GBCRS is given. In order to ensure the quality of generated GBs, this function is subject to three constraints. Second, the GBCRS model is proposed. The purity threshold is used to relax the related notions so that GBCRS can be used in label noise environments. Subsequently, GBCRS is applied to the covering granular reduction and attribute reduction in label noise environments. In covering granular reduction, we propose an intuitive, understandable and anti-noise GBCRS-based granular reduction (GBCRS-GR) algorithm, which also solves the optimization objective function of GBs. Based on GBCRS-GR, a GBCRS-based attribute reduction (GBCRS-AR) algorithm is proposed with the classification ability of the attribute subset as the evaluation. The experiments on UCI datasets illustrate that proposed algorithm is more robust against label noise than the comparison ones.
•Innovative GBCRS is proposed for both granular and attribute reduction to simplify the knowledge base.•GBCRS is the first CRS model that fits the data distribution.•GBCRS not only takes decision attributes into consideration, but also has robustness to the label noise. |
| ArticleNumber | 109420 |
| Author | Gong, Yuanlin Tang, Zhan Hou, Xiang Shao, Yabin Peng, Xiaoli |
| Author_xml | – sequence: 1 givenname: Xiaoli surname: Peng fullname: Peng, Xiaoli organization: Sichuan University of Arts and Science, Dazhou, Sichuan 635000, China – sequence: 2 givenname: Yuanlin surname: Gong fullname: Gong, Yuanlin organization: Dazhou Vocational and Technical College, Dazhou, Sichuan 635000, China – sequence: 3 givenname: Xiang surname: Hou fullname: Hou, Xiang organization: Sichuan University of Arts and Science, Dazhou, Sichuan 635000, China – sequence: 4 givenname: Zhan surname: Tang fullname: Tang, Zhan email: 93334586@qq.com organization: Sichuan University of Arts and Science, Dazhou, Sichuan 635000, China – sequence: 5 givenname: Yabin surname: Shao fullname: Shao, Yabin organization: School of Science, Chongqing University of Posts and Telecommunications, Chongqing 400065, China |
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| Cites_doi | 10.1109/TFUZZ.2016.2581186 10.1109/TFUZZ.2020.2984198 10.1016/j.knosys.2016.10.010 10.1109/TFUZZ.2017.2718492 10.1016/j.ijar.2011.12.010 10.1109/TKDE.2011.89 10.3724/SP.J.1001.2008.00640 10.1109/TSMC.2018.2882090 10.1109/TCYB.2021.3054742 10.1016/j.knosys.2022.109394 10.1016/j.ijar.2012.03.004 10.1109/TKDE.2007.1044 10.1109/TFUZZ.2020.2975152 10.1109/TFUZZ.2024.3397697 10.1016/j.ins.2021.08.032 10.1109/TFUZZ.2021.3053844 10.1016/j.knosys.2007.07.001 10.1109/TCYB.2020.3022527 10.1016/j.knosys.2019.105269 10.1016/j.fss.2015.05.002 10.1016/j.ins.2007.09.019 10.1109/TKDE.2020.2997039 10.1016/j.ijar.2009.11.001 10.1109/TKDE.2024.3419184 10.1016/j.datak.2009.07.007 10.1109/TNNLS.2023.3325199 10.1016/j.knosys.2020.106594 10.1016/j.ins.2022.08.066 10.1109/TFUZZ.2018.2883023 10.1016/j.ins.2016.05.053 10.1016/j.ins.2012.02.065 10.1016/j.fss.2019.02.005 10.1016/j.ijar.2007.06.014 10.1016/j.eswa.2021.116276 10.1109/TCYB.2021.3054593 10.1016/j.ins.2019.01.010 10.1109/TNNLS.2022.3203381 10.1016/j.knosys.2021.107223 10.1016/j.ijar.2015.11.005 10.1016/j.knosys.2021.106908 10.1016/j.ins.2011.07.038 10.1109/TFUZZ.2021.3081916 10.1016/j.ijar.2023.108949 10.1016/j.ins.2022.07.048 |
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| Keywords | Granular reduction Covering rough set Attribute reduction Label noise Granular-ball |
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| References | Xia, Liu, Ding, Wang, Luo (br0070) 2019; 483 Xia, Wang, Wang, Gao, Ding, Yu, Zhai, Chen (br0090) 2025; 36 Yao, Yao (br0460) 2012; 200 Ma (br0170) 2012; 53 Wang, Hu, Wang, Chen, Qian, Dong (br0140) 2018; 29 Hu, Liu, Yu (br0150) 2008; 21 Ma (br0350) 2016; 294 Sun, Mi, Chen, Liu (br0390) 2021; 215 Ding, Pedrycz, Triguero, Cao, Lin (br0190) 2021; 29 Jiang, Zhan, Chen (br0320) 2019; 27 Peng, Wang, Xia, Wang, Chen (br0010) 2022; 611 Peng, Wang, Xia, Wang, Pu, Qian (br0430) 2022; 252 Yang, Li (br0360) 2010; 51 Zhang, Li, Yan, Lei (br0310) 2011 Ji, Li, Yao, Zhao (br0060) 2023; 160 Yang, Chen, Wang (br0200) 2017; 25 Xia, Lian, Wang, Gao, Hu, Shao (br0400) 2024; 36 Zhu, Wang (br0490) 2007; 19 Hu, Miao, Pedrycz (br0230) 2022; 192 Shao, Wu, Wang, Wang (br0220) 2020; 191 Ma, Mi, Lin, Li (br0410) 2022; 602 Sun, Zhang, Ding, Wang, Xu (br0020) 2024 Sang, Chen, Yang, Li, Xu, Luo (br0300) 2021; 227 Du, Hu, Zhu, Ma (br0450) 2011; 181 Hu, Yu, Xie (br0510) 2008; 19 Xia, Zhang, Li, Wang, Giem, Chen (br0330) 2022; 34 Shao, Leung, Wang, Wu (br0380) 2016; 114 Huang, Guo, Zhou (br0110) 2007 Sun, Yin, Ding, Qian, Xu (br0290) 2022; 30 Ziarko (br0470) 2008; 49 Yang, Yang, Wu, Yu (br0120) 2008; 178 Chen, Zhao, Zhang, Yang, Zhang (br0260) 2012; 24 Guo, Wang, Liu, Pedrycz (br0050) 2022; 52 Ma, Sun (br0160) 2012; 53 Shi, Mi, Li, Liu (br0030) 2021; 51 Li, Huang, Jia, Cai (br0280) 2016; 69 Shao, Mou, Gong (br0080) 2019; 375 Xu, Li (br0420) 2020; 2020 Xia, Dai, Wang, Gao, Giem (br0480) 2024; 35 Sun, Wang, Ding, Xu, Lin (br0210) 2021; 578 Huang, Li (br0250) 2022; 52 Zhang, Wang, Zhan, Dai (br0100) 2022; 30 Zhu, Wang (br0440) 2007 Yang, Hu (br0370) 2016; 367–368 Hu, Tsang, Guo, Chen, Xu (br0500) 2021; 220 Yang, Yu, Yang, Wei (br0130) 2009; 68 Hu, Zhao, Yu (br0270) 2008; 21 Concepción, Nápoles, Grau, Pedrycz (br0040) 2022; 52 Yang, Liu, Xia, Wang, Zhang, Li, Xu (br0340) 2024; 32 Yang, Zhong, Lang, Qian, Dai (br0180) 2020; 28 Yang, Chen, Wang, Wang (br0240) 2018; 26 Yao (10.1016/j.ijar.2025.109420_br0460) 2012; 200 Shao (10.1016/j.ijar.2025.109420_br0080) 2019; 375 Yang (10.1016/j.ijar.2025.109420_br0340) 2024; 32 Hu (10.1016/j.ijar.2025.109420_br0510) 2008; 19 Zhu (10.1016/j.ijar.2025.109420_br0490) 2007; 19 Zhang (10.1016/j.ijar.2025.109420_br0100) 2022; 30 Wang (10.1016/j.ijar.2025.109420_br0140) 2018; 29 Ma (10.1016/j.ijar.2025.109420_br0170) 2012; 53 Huang (10.1016/j.ijar.2025.109420_br0250) 2022; 52 Ma (10.1016/j.ijar.2025.109420_br0410) 2022; 602 Chen (10.1016/j.ijar.2025.109420_br0260) 2012; 24 Yang (10.1016/j.ijar.2025.109420_br0360) 2010; 51 Xu (10.1016/j.ijar.2025.109420_br0420) 2020; 2020 Shi (10.1016/j.ijar.2025.109420_br0030) 2021; 51 Li (10.1016/j.ijar.2025.109420_br0280) 2016; 69 Ma (10.1016/j.ijar.2025.109420_br0160) 2012; 53 Yang (10.1016/j.ijar.2025.109420_br0240) 2018; 26 Shao (10.1016/j.ijar.2025.109420_br0220) 2020; 191 Hu (10.1016/j.ijar.2025.109420_br0270) 2008; 21 Xia (10.1016/j.ijar.2025.109420_br0400) 2024; 36 Ding (10.1016/j.ijar.2025.109420_br0190) 2021; 29 Shao (10.1016/j.ijar.2025.109420_br0380) 2016; 114 Sun (10.1016/j.ijar.2025.109420_br0390) 2021; 215 Zhu (10.1016/j.ijar.2025.109420_br0440) 2007 Yang (10.1016/j.ijar.2025.109420_br0180) 2020; 28 Xia (10.1016/j.ijar.2025.109420_br0070) 2019; 483 Du (10.1016/j.ijar.2025.109420_br0450) 2011; 181 Jiang (10.1016/j.ijar.2025.109420_br0320) 2019; 27 Hu (10.1016/j.ijar.2025.109420_br0500) 2021; 220 Sun (10.1016/j.ijar.2025.109420_br0020) 2024 Sun (10.1016/j.ijar.2025.109420_br0210) 2021; 578 Zhang (10.1016/j.ijar.2025.109420_br0310) 2011 Yang (10.1016/j.ijar.2025.109420_br0120) 2008; 178 Hu (10.1016/j.ijar.2025.109420_br0230) 2022; 192 Yang (10.1016/j.ijar.2025.109420_br0130) 2009; 68 Xia (10.1016/j.ijar.2025.109420_br0330) 2022; 34 Yang (10.1016/j.ijar.2025.109420_br0200) 2017; 25 Sang (10.1016/j.ijar.2025.109420_br0300) 2021; 227 Xia (10.1016/j.ijar.2025.109420_br0480) 2024; 35 Sun (10.1016/j.ijar.2025.109420_br0290) 2022; 30 Huang (10.1016/j.ijar.2025.109420_br0110) 2007 Hu (10.1016/j.ijar.2025.109420_br0150) 2008; 21 Ziarko (10.1016/j.ijar.2025.109420_br0470) 2008; 49 Xia (10.1016/j.ijar.2025.109420_br0090) 2025; 36 Peng (10.1016/j.ijar.2025.109420_br0430) 2022; 252 Ji (10.1016/j.ijar.2025.109420_br0060) 2023; 160 Yang (10.1016/j.ijar.2025.109420_br0370) 2016; 367–368 Peng (10.1016/j.ijar.2025.109420_br0010) 2022; 611 Concepción (10.1016/j.ijar.2025.109420_br0040) 2022; 52 Ma (10.1016/j.ijar.2025.109420_br0350) 2016; 294 Guo (10.1016/j.ijar.2025.109420_br0050) 2022; 52 |
| References_xml | – volume: 51 start-page: 809 year: 2021 end-page: 821 ident: br0030 article-title: Concept-cognitive learning model for incremental concept learning publication-title: IEEE Trans. Syst. Man Cybern. Syst. – volume: 52 start-page: 9722 year: 2022 end-page: 9735 ident: br0250 article-title: Discernibility measures for fuzzy publication-title: IEEE Trans. Cybern. – volume: 114 start-page: 156 year: 2016 end-page: 166 ident: br0380 article-title: Granular reducts of formal fuzzy contexts publication-title: Knowl.-Based Syst. – volume: 200 start-page: 91 year: 2012 end-page: 107 ident: br0460 article-title: Covering based rough set approximations publication-title: Inf. Sci. – volume: 181 start-page: 5457 year: 2011 end-page: 5467 ident: br0450 article-title: Rule learning for classification based on neighborhood covering reduction publication-title: Inf. Sci. – volume: 192 year: 2022 ident: br0230 article-title: Multi granularity based label propagation with active learning for semi-supervised classification publication-title: Expert Syst. Appl. – volume: 375 start-page: 121 year: 2019 end-page: 140 ident: br0080 article-title: On retarded fuzzy functional differential equations and nonabsolute fuzzy integrals publication-title: Fuzzy Sets Syst. – volume: 49 start-page: 272 year: 2008 end-page: 284 ident: br0470 article-title: Probabilistic approach to rough sets publication-title: Int. J. Approx. Reason. – volume: 191 year: 2020 ident: br0220 article-title: Knowledge reduction methods of covering approximate spaces based on concept lattice publication-title: Knowl.-Based Syst. – volume: 26 start-page: 1257 year: 2018 end-page: 1273 ident: br0240 article-title: Incremental perspective for feature selection based on fuzzy rough sets publication-title: IEEE Trans. Fuzzy Syst. – volume: 30 start-page: 1197 year: 2022 end-page: 1211 ident: br0290 article-title: Feature selection with missing labels using multilabel fuzzy neighborhood rough sets and maximum relevance minimum redundancy publication-title: IEEE Trans. Fuzzy Syst. – volume: 52 start-page: 2994 year: 2022 end-page: 3005 ident: br0040 article-title: Fuzzy-rough cognitive networks: theoretical analysis and simpler models publication-title: IEEE Trans. Cybern. – volume: 32 start-page: 4376 year: 2024 end-page: 4387 ident: br0340 article-title: 3WC-GBNRS++: a novel three-way classifier with granular-ball neighborhood rough sets based on uncertainty publication-title: IEEE Trans. Fuzzy Syst. – volume: 2020 year: 2020 ident: br0420 article-title: The relationship between the unicost set covering problem and the attribute reduction problem in rough set theory publication-title: Math. Probl. Eng. – volume: 25 start-page: 825 year: 2017 end-page: 838 ident: br0200 article-title: Active sample selection based incremental algorithm for attribute reduction with rough sets publication-title: IEEE Trans. Fuzzy Syst. – volume: 367–368 start-page: 463 year: 2016 end-page: 486 ident: br0370 article-title: A fuzzy covering-based rough set model and its generalization over fuzzy lattice publication-title: Inf. Sci. – volume: 178 start-page: 1219 year: 2008 end-page: 1234 ident: br0120 article-title: Dominance-based rough set approach and knowledge reductions in incomplete ordered information system publication-title: Inf. Sci. – volume: 294 start-page: 1 year: 2016 end-page: 17 ident: br0350 article-title: Two fuzzy covering rough set models and their generalizations over fuzzy lattices publication-title: Fuzzy Sets Syst. – volume: 611 start-page: 504 year: 2022 end-page: 521 ident: br0010 article-title: VPGB: a granular-ball based model for attribute reduction and classification with label noise publication-title: Inf. Sci. – start-page: 124 year: 2007 end-page: 128 ident: br0110 article-title: Approximation reduction based on similarity relation publication-title: Fourth International Conference on Fuzzy Systems and Knowledge Discovery, vol. 3 – volume: 53 start-page: 608 year: 2012 end-page: 619 ident: br0160 article-title: Probabilistic rough set over two universes and rough entropy publication-title: Int. J. Approx. Reason. – volume: 578 start-page: 887 year: 2021 end-page: 912 ident: br0210 article-title: Feature selection using Fisher score and multilabel neighborhood rough sets for multilabel classification publication-title: Inf. Sci. – volume: 52 start-page: 9101 year: 2022 end-page: 9110 ident: br0050 article-title: Trend-based granular representation of time series and its application in clustering publication-title: IEEE Trans. Cybern. – volume: 30 start-page: 2360 year: 2022 end-page: 2374 ident: br0100 article-title: Fuzzy measures and Choquet integrals based on fuzzy covering rough sets publication-title: IEEE Trans. Fuzzy Syst. – volume: 24 start-page: 2080 year: 2012 end-page: 2093 ident: br0260 article-title: Sample pair selection for attribute reduction with rough set publication-title: IEEE Trans. Knowl. Data Eng. – volume: 227 year: 2021 ident: br0300 article-title: Feature selection for dynamic interval-valued ordered data based on fuzzy dominance neighborhood rough set publication-title: Knowl.-Based Syst. – start-page: 3746 year: 2007 end-page: 3751 ident: br0440 article-title: Properties of the third type of covering-based rough sets publication-title: International Conference on Machine Learning and Cybernetics, vol. 7 – volume: 220 year: 2021 ident: br0500 article-title: A novel approach to attribute reduction based on weighted neighborhood rough sets publication-title: Knowl.-Based Syst. – start-page: 166 year: 2011 end-page: 171 ident: br0310 article-title: Neighborhood rough sets based matrix approach for calculation of the approximations publication-title: International Conference on Rough Sets and Knowledge Technology, vol. 6954 – volume: 160 year: 2023 ident: br0060 article-title: Attribute reduction based on fusion information entropy publication-title: Int. J. Approx. Reason. – volume: 19 start-page: 1131 year: 2007 end-page: 1144 ident: br0490 article-title: On three types of covering-based rough sets publication-title: IEEE Trans. Knowl. Data Eng. – volume: 19 start-page: 640 year: 2008 end-page: 649 ident: br0510 article-title: Numerical attribute reduction based on neighborhood granulation and rough approximation publication-title: J. Softw. – volume: 29 start-page: 1395 year: 2021 end-page: 1408 ident: br0190 article-title: Multigranulation supertrust model for attribute reduction publication-title: IEEE Trans. Fuzzy Syst. – volume: 252 year: 2022 ident: br0430 article-title: FNC: a fast neighborhood calculation framework publication-title: Knowl.-Based Syst. – volume: 21 start-page: 732 year: 2008 end-page: 738 ident: br0270 article-title: Efficient symbolic and numerical attribute reduction with neighborhood rough sets publication-title: Pattern Recognit. Artif. Intell. – volume: 28 start-page: 3133 year: 2020 end-page: 3144 ident: br0180 article-title: Granular matrix: a new approach for granular structure reduction and redundancy evaluation publication-title: IEEE Trans. Fuzzy Syst. – volume: 34 start-page: 1231 year: 2022 end-page: 1242 ident: br0330 article-title: GBNRS: a novel rough set algorithm for fast adaptive attribute reduction in classification publication-title: IEEE Trans. Knowl. Data Eng. – volume: 36 start-page: 6293 year: 2024 end-page: 6304 ident: br0400 article-title: Granular-ball fuzzy set and its implement in svm publication-title: IEEE Trans. Knowl. Data Eng. – volume: 483 start-page: 136 year: 2019 end-page: 152 ident: br0070 article-title: Granular ball computing classifiers for efficient, scalable and robust learning publication-title: Inf. Sci. – volume: 21 start-page: 294 year: 2008 end-page: 304 ident: br0150 article-title: Mixed feature selection based on granulation and approximation publication-title: Knowl.-Based Syst. – volume: 53 start-page: 901 year: 2012 end-page: 911 ident: br0170 article-title: On some types of neighborhood-related covering rough sets publication-title: Int. J. Approx. Reason. – volume: 215 year: 2021 ident: br0390 article-title: A new fuzzy multi-attribute group decision-making method with generalized maximal consistent block and its application in emergency management publication-title: Knowl.-Based Syst. – volume: 51 start-page: 335 year: 2010 end-page: 345 ident: br0360 article-title: Reduction about approximation spaces of covering generalized rough sets publication-title: Int. J. Approx. Reason. – volume: 36 start-page: 1719 year: 2025 end-page: 1733 ident: br0090 article-title: GBRS: a unified granular-ball learning model of Pawlak rough set and neighborhood rough set publication-title: IEEE Trans. Neural Netw. Learn. Syst. – start-page: 1 year: 2024 end-page: 17 ident: br0020 article-title: Fcpfs: fuzzy granular ball clustering-based partial multilabel feature selection with fuzzy mutual information publication-title: IEEE Trans. Emerg. Top. Comput. Intell. – volume: 68 start-page: 1331 year: 2009 end-page: 1347 ident: br0130 article-title: Dominance-based rough set approach to incomplete interval-valued information system publication-title: Data Knowl. Eng. – volume: 602 start-page: 1524 year: 2022 end-page: 1540 ident: br0410 article-title: Boundary region-based variable precision covering rough set models publication-title: Inf. Sci. – volume: 27 start-page: 1558 year: 2019 end-page: 1572 ident: br0320 article-title: Covering-based variable precision (I; T)-fuzzy rough sets with applications to multi-attribute decision-making publication-title: IEEE Trans. Fuzzy Syst. – volume: 29 start-page: 2986 year: 2018 end-page: 2999 ident: br0140 article-title: Feature selection based on neighborhood discrimination index publication-title: IEEE Trans. Neural Netw. Learn. Syst. – volume: 35 start-page: 5319 year: 2024 end-page: 5331 ident: br0480 article-title: An efficient and adaptive granular-ball generation method in classification problem publication-title: IEEE Trans. Neural Netw. Learn. Syst. – volume: 69 start-page: 1 year: 2016 end-page: 17 ident: br0280 article-title: Neighborhood based decision-theoretic rough set models publication-title: Int. J. Approx. Reason. – volume: 25 start-page: 825 issue: 4 year: 2017 ident: 10.1016/j.ijar.2025.109420_br0200 article-title: Active sample selection based incremental algorithm for attribute reduction with rough sets publication-title: IEEE Trans. Fuzzy Syst. doi: 10.1109/TFUZZ.2016.2581186 – start-page: 1 year: 2024 ident: 10.1016/j.ijar.2025.109420_br0020 article-title: Fcpfs: fuzzy granular ball clustering-based partial multilabel feature selection with fuzzy mutual information publication-title: IEEE Trans. Emerg. Top. Comput. Intell. – volume: 28 start-page: 3133 issue: 12 year: 2020 ident: 10.1016/j.ijar.2025.109420_br0180 article-title: Granular matrix: a new approach for granular structure reduction and redundancy evaluation publication-title: IEEE Trans. Fuzzy Syst. doi: 10.1109/TFUZZ.2020.2984198 – volume: 114 start-page: 156 year: 2016 ident: 10.1016/j.ijar.2025.109420_br0380 article-title: Granular reducts of formal fuzzy contexts publication-title: Knowl.-Based Syst. doi: 10.1016/j.knosys.2016.10.010 – volume: 2020 year: 2020 ident: 10.1016/j.ijar.2025.109420_br0420 article-title: The relationship between the unicost set covering problem and the attribute reduction problem in rough set theory publication-title: Math. Probl. Eng. – volume: 26 start-page: 1257 issue: 3 year: 2018 ident: 10.1016/j.ijar.2025.109420_br0240 article-title: Incremental perspective for feature selection based on fuzzy rough sets publication-title: IEEE Trans. Fuzzy Syst. doi: 10.1109/TFUZZ.2017.2718492 – volume: 53 start-page: 608 issue: 4 year: 2012 ident: 10.1016/j.ijar.2025.109420_br0160 article-title: Probabilistic rough set over two universes and rough entropy publication-title: Int. J. Approx. Reason. doi: 10.1016/j.ijar.2011.12.010 – volume: 24 start-page: 2080 issue: 11 year: 2012 ident: 10.1016/j.ijar.2025.109420_br0260 article-title: Sample pair selection for attribute reduction with rough set publication-title: IEEE Trans. Knowl. Data Eng. doi: 10.1109/TKDE.2011.89 – volume: 19 start-page: 640 issue: 3 year: 2008 ident: 10.1016/j.ijar.2025.109420_br0510 article-title: Numerical attribute reduction based on neighborhood granulation and rough approximation publication-title: J. Softw. doi: 10.3724/SP.J.1001.2008.00640 – volume: 51 start-page: 809 issue: 2 year: 2021 ident: 10.1016/j.ijar.2025.109420_br0030 article-title: Concept-cognitive learning model for incremental concept learning publication-title: IEEE Trans. Syst. Man Cybern. Syst. doi: 10.1109/TSMC.2018.2882090 – volume: 29 start-page: 2986 issue: 7 year: 2018 ident: 10.1016/j.ijar.2025.109420_br0140 article-title: Feature selection based on neighborhood discrimination index publication-title: IEEE Trans. Neural Netw. Learn. Syst. – volume: 52 start-page: 9722 issue: 9 year: 2022 ident: 10.1016/j.ijar.2025.109420_br0250 article-title: Discernibility measures for fuzzy β covering and their application publication-title: IEEE Trans. Cybern. doi: 10.1109/TCYB.2021.3054742 – volume: 252 year: 2022 ident: 10.1016/j.ijar.2025.109420_br0430 article-title: FNC: a fast neighborhood calculation framework publication-title: Knowl.-Based Syst. doi: 10.1016/j.knosys.2022.109394 – volume: 53 start-page: 901 issue: 6 year: 2012 ident: 10.1016/j.ijar.2025.109420_br0170 article-title: On some types of neighborhood-related covering rough sets publication-title: Int. J. Approx. Reason. doi: 10.1016/j.ijar.2012.03.004 – volume: 19 start-page: 1131 issue: 8 year: 2007 ident: 10.1016/j.ijar.2025.109420_br0490 article-title: On three types of covering-based rough sets publication-title: IEEE Trans. Knowl. Data Eng. doi: 10.1109/TKDE.2007.1044 – volume: 29 start-page: 1395 issue: 6 year: 2021 ident: 10.1016/j.ijar.2025.109420_br0190 article-title: Multigranulation supertrust model for attribute reduction publication-title: IEEE Trans. Fuzzy Syst. doi: 10.1109/TFUZZ.2020.2975152 – volume: 32 start-page: 4376 issue: 8 year: 2024 ident: 10.1016/j.ijar.2025.109420_br0340 article-title: 3WC-GBNRS++: a novel three-way classifier with granular-ball neighborhood rough sets based on uncertainty publication-title: IEEE Trans. Fuzzy Syst. doi: 10.1109/TFUZZ.2024.3397697 – volume: 578 start-page: 887 year: 2021 ident: 10.1016/j.ijar.2025.109420_br0210 article-title: Feature selection using Fisher score and multilabel neighborhood rough sets for multilabel classification publication-title: Inf. Sci. doi: 10.1016/j.ins.2021.08.032 – volume: 30 start-page: 1197 issue: 5 year: 2022 ident: 10.1016/j.ijar.2025.109420_br0290 article-title: Feature selection with missing labels using multilabel fuzzy neighborhood rough sets and maximum relevance minimum redundancy publication-title: IEEE Trans. Fuzzy Syst. doi: 10.1109/TFUZZ.2021.3053844 – volume: 21 start-page: 294 issue: 4 year: 2008 ident: 10.1016/j.ijar.2025.109420_br0150 article-title: Mixed feature selection based on granulation and approximation publication-title: Knowl.-Based Syst. doi: 10.1016/j.knosys.2007.07.001 – volume: 52 start-page: 2994 issue: 5 year: 2022 ident: 10.1016/j.ijar.2025.109420_br0040 article-title: Fuzzy-rough cognitive networks: theoretical analysis and simpler models publication-title: IEEE Trans. Cybern. doi: 10.1109/TCYB.2020.3022527 – volume: 191 year: 2020 ident: 10.1016/j.ijar.2025.109420_br0220 article-title: Knowledge reduction methods of covering approximate spaces based on concept lattice publication-title: Knowl.-Based Syst. doi: 10.1016/j.knosys.2019.105269 – volume: 294 start-page: 1 year: 2016 ident: 10.1016/j.ijar.2025.109420_br0350 article-title: Two fuzzy covering rough set models and their generalizations over fuzzy lattices publication-title: Fuzzy Sets Syst. doi: 10.1016/j.fss.2015.05.002 – volume: 178 start-page: 1219 issue: 4 year: 2008 ident: 10.1016/j.ijar.2025.109420_br0120 article-title: Dominance-based rough set approach and knowledge reductions in incomplete ordered information system publication-title: Inf. Sci. doi: 10.1016/j.ins.2007.09.019 – volume: 34 start-page: 1231 issue: 3 year: 2022 ident: 10.1016/j.ijar.2025.109420_br0330 article-title: GBNRS: a novel rough set algorithm for fast adaptive attribute reduction in classification publication-title: IEEE Trans. Knowl. Data Eng. doi: 10.1109/TKDE.2020.2997039 – volume: 51 start-page: 335 issue: 3 year: 2010 ident: 10.1016/j.ijar.2025.109420_br0360 article-title: Reduction about approximation spaces of covering generalized rough sets publication-title: Int. J. Approx. Reason. doi: 10.1016/j.ijar.2009.11.001 – volume: 36 start-page: 6293 issue: 11 year: 2024 ident: 10.1016/j.ijar.2025.109420_br0400 article-title: Granular-ball fuzzy set and its implement in svm publication-title: IEEE Trans. Knowl. Data Eng. doi: 10.1109/TKDE.2024.3419184 – volume: 68 start-page: 1331 issue: 11 year: 2009 ident: 10.1016/j.ijar.2025.109420_br0130 article-title: Dominance-based rough set approach to incomplete interval-valued information system publication-title: Data Knowl. Eng. doi: 10.1016/j.datak.2009.07.007 – volume: 36 start-page: 1719 issue: 1 year: 2025 ident: 10.1016/j.ijar.2025.109420_br0090 article-title: GBRS: a unified granular-ball learning model of Pawlak rough set and neighborhood rough set publication-title: IEEE Trans. Neural Netw. Learn. Syst. doi: 10.1109/TNNLS.2023.3325199 – volume: 215 year: 2021 ident: 10.1016/j.ijar.2025.109420_br0390 article-title: A new fuzzy multi-attribute group decision-making method with generalized maximal consistent block and its application in emergency management publication-title: Knowl.-Based Syst. doi: 10.1016/j.knosys.2020.106594 – start-page: 166 year: 2011 ident: 10.1016/j.ijar.2025.109420_br0310 article-title: Neighborhood rough sets based matrix approach for calculation of the approximations – volume: 611 start-page: 504 year: 2022 ident: 10.1016/j.ijar.2025.109420_br0010 article-title: VPGB: a granular-ball based model for attribute reduction and classification with label noise publication-title: Inf. Sci. doi: 10.1016/j.ins.2022.08.066 – start-page: 124 year: 2007 ident: 10.1016/j.ijar.2025.109420_br0110 article-title: Approximation reduction based on similarity relation – volume: 27 start-page: 1558 issue: 8 year: 2019 ident: 10.1016/j.ijar.2025.109420_br0320 article-title: Covering-based variable precision (I; T)-fuzzy rough sets with applications to multi-attribute decision-making publication-title: IEEE Trans. Fuzzy Syst. doi: 10.1109/TFUZZ.2018.2883023 – volume: 367–368 start-page: 463 year: 2016 ident: 10.1016/j.ijar.2025.109420_br0370 article-title: A fuzzy covering-based rough set model and its generalization over fuzzy lattice publication-title: Inf. Sci. doi: 10.1016/j.ins.2016.05.053 – volume: 200 start-page: 91 year: 2012 ident: 10.1016/j.ijar.2025.109420_br0460 article-title: Covering based rough set approximations publication-title: Inf. Sci. doi: 10.1016/j.ins.2012.02.065 – volume: 375 start-page: 121 year: 2019 ident: 10.1016/j.ijar.2025.109420_br0080 article-title: On retarded fuzzy functional differential equations and nonabsolute fuzzy integrals publication-title: Fuzzy Sets Syst. doi: 10.1016/j.fss.2019.02.005 – volume: 21 start-page: 732 issue: 6 year: 2008 ident: 10.1016/j.ijar.2025.109420_br0270 article-title: Efficient symbolic and numerical attribute reduction with neighborhood rough sets publication-title: Pattern Recognit. Artif. Intell. – volume: 49 start-page: 272 issue: 2 year: 2008 ident: 10.1016/j.ijar.2025.109420_br0470 article-title: Probabilistic approach to rough sets publication-title: Int. J. Approx. Reason. doi: 10.1016/j.ijar.2007.06.014 – volume: 192 year: 2022 ident: 10.1016/j.ijar.2025.109420_br0230 article-title: Multi granularity based label propagation with active learning for semi-supervised classification publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2021.116276 – volume: 52 start-page: 9101 issue: 9 year: 2022 ident: 10.1016/j.ijar.2025.109420_br0050 article-title: Trend-based granular representation of time series and its application in clustering publication-title: IEEE Trans. Cybern. doi: 10.1109/TCYB.2021.3054593 – volume: 483 start-page: 136 year: 2019 ident: 10.1016/j.ijar.2025.109420_br0070 article-title: Granular ball computing classifiers for efficient, scalable and robust learning publication-title: Inf. Sci. doi: 10.1016/j.ins.2019.01.010 – volume: 35 start-page: 5319 issue: 4 year: 2024 ident: 10.1016/j.ijar.2025.109420_br0480 article-title: An efficient and adaptive granular-ball generation method in classification problem publication-title: IEEE Trans. Neural Netw. Learn. Syst. doi: 10.1109/TNNLS.2022.3203381 – volume: 227 year: 2021 ident: 10.1016/j.ijar.2025.109420_br0300 article-title: Feature selection for dynamic interval-valued ordered data based on fuzzy dominance neighborhood rough set publication-title: Knowl.-Based Syst. doi: 10.1016/j.knosys.2021.107223 – volume: 69 start-page: 1 year: 2016 ident: 10.1016/j.ijar.2025.109420_br0280 article-title: Neighborhood based decision-theoretic rough set models publication-title: Int. J. Approx. Reason. doi: 10.1016/j.ijar.2015.11.005 – volume: 220 year: 2021 ident: 10.1016/j.ijar.2025.109420_br0500 article-title: A novel approach to attribute reduction based on weighted neighborhood rough sets publication-title: Knowl.-Based Syst. doi: 10.1016/j.knosys.2021.106908 – start-page: 3746 year: 2007 ident: 10.1016/j.ijar.2025.109420_br0440 article-title: Properties of the third type of covering-based rough sets – volume: 181 start-page: 5457 issue: 24 year: 2011 ident: 10.1016/j.ijar.2025.109420_br0450 article-title: Rule learning for classification based on neighborhood covering reduction publication-title: Inf. Sci. doi: 10.1016/j.ins.2011.07.038 – volume: 30 start-page: 2360 issue: 7 year: 2022 ident: 10.1016/j.ijar.2025.109420_br0100 article-title: Fuzzy measures and Choquet integrals based on fuzzy covering rough sets publication-title: IEEE Trans. Fuzzy Syst. doi: 10.1109/TFUZZ.2021.3081916 – volume: 160 year: 2023 ident: 10.1016/j.ijar.2025.109420_br0060 article-title: Attribute reduction based on fusion information entropy publication-title: Int. J. Approx. Reason. doi: 10.1016/j.ijar.2023.108949 – volume: 602 start-page: 1524 year: 2022 ident: 10.1016/j.ijar.2025.109420_br0410 article-title: Boundary region-based variable precision covering rough set models publication-title: Inf. Sci. doi: 10.1016/j.ins.2022.07.048 |
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