Journal of Shandong University(Engineering Science) ›› 2024, Vol. 54 ›› Issue (1): 33-44.doi: 10.6040/j.issn.1672-3961.0.2022.310

• Machine Learning & Data Mining • Previous Articles    

Attribute reduction algorithm of numerical information system based on weighted neighborhood entropy

CHEN Baoguo1, DENG Ming1 *, CHEN Jinlin2   

  1. 1. School of Computer Science, Huainan Normal University, Huainan 232038, Anhui, China;
    2. College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, Jiangsu, China
  • Published:2024-02-01

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  • TP18
[1] 周涛,陆惠玲,任海玲,等.基于粗糙集的属性约简算法综述[J]. 电子学报, 2021, 49(7):1439-1449. ZHOU Tao, LU Huiling, REN Hailing, et al. Survey on attribute reduction algorithm of rough set[J]. Acta Electronica Sinica, 2021, 49(7):1439-1449.
[2] GAO Can, ZHOU Jie, MIAO Duoqian, et al. Granular-conditional-entropy-based attribute reduction for partially labeled data with proxy labels[J]. Information Sciences, 2021, 580:111-128.
[3] ZHANG Qinli, CHEN Yiying, ZHANG Gangqiang, et al. New uncertainty measurement for categorical data based on fuzzy information structures: an application in attribute reduction[J]. Information Sciences, 2021, 580:541-577.
[4] 李明,甘秀娜,王月波. 基于集成学习的决策粗糙集特定类属性约简算法[J]. 计算机应用与软件, 2021, 38(6):262-270. LI Ming, GAN Xiuna, WANG Yuebo. Class-specific attribute reduction algorithm for decision-theoretic rough sets based on ensemble learning[J]. Computer Applications and Software, 2021, 38(6):262-270.
[5] 姚晟,李初宴,陈悦. 基于非平衡数据下不完备混合型信息系统的属性约简[J]. 计算机应用研究, 2021, 38(5):1331-1335. YAO Sheng, LI Chuyan, CHEN Yue. Attribute reduction of incomplete hybrid information system based on unbalanced data[J]. Application Research of Computers, 2021, 38(5):1331-1335.
[6] HU Qinghua, YU Daren, LIU Jingfu, et al. Neighborhood rough set based heterogeneous feature subset selection[J]. Information Sciences, 2008, 178(18):3577-3594.
[7] FAN Xiaodong, ZHAO Weida, WANG Changzhong, et al. Attribute reduction based on max-decision neighborhood rough set model[J]. Knowledge-Based Systems, 2018, 151(1):16-23.
[8] SHU Wenhao, QIAN Wenbin, XIE Yonghong. Incremental feature selection for dynamic hybrid data using neighborhood rough set[J]. Knowledge-Based Systems, 2020, 194:105516.
[9] WANG Changzhong, SHI Yunpeng, FAN Xiaodong, et al. Attribute reduction based on k-nearest neighborhood rough sets[J]. International Journal of Approximate Reasoning, 2019, 106:18-31.
[10] CHEN Hongmei, LI Tianrui, FAN Xin, et al. Feature selection for imbalanced data based on neighborhood rough sets[J]. Information Sciences, 2019, 483:1-20.
[11] HU M, TSANG E C C, GUO Y T, et al. A novel approach to attribute reduction based on weighted neighborhood rough sets[J]. Knowledge-Based Systems, 2021, 220:106908.
[12] WANG Changzhong, HUANG Yang, SHAO Mingwen, et al. Feature selection based on neighborhood self-information[J]. IEEE Transactions on Cybernetics, 2020, 50(9):4031-4042.
[13] 孙林,赵婧,徐久成,等. 基于邻域粗糙集和帝王蝶优化的特征选择算法[J]. 计算机应用, 2022, 42(5):1355-1366. SUN Lin, ZHAO Jing, XU Jiucheng, et al. Feature selection algorithm based on neighborhood rough set and monarch butterfly optimization[J]. Journal of Computer Applications, 2022, 42(5): 1355-1366.
[14] 熊菊霞,吴尽昭,王秋红.邻域互信息熵的混合型数据决策代价属性约简[J]. 小型微型计算机系统, 2021, 42(8):1584-1590. XIONG Juxia, WU Jinzhao, WANG Qiuhong. Decision cost attribute reduction of hybrid data based on neighborhood mutual information entropy[J]. Journal of Chinese Computer Systems, 2021, 42(8):1584-1590.
[15] 陈曦,刘晶. 基于邻域关系的知识粒度增量式属性约简算法[J]. 微电子学与计算机, 2020, 37(10):1-6. CHEN Xi, LIU Jing. Knowledge granularity incremental attribute reduction algorithm based on neighborhood relation[J]. Microelectronics & Computer, 2020, 37(10):1-6.
[16] YANG Xiaoling, CHEN Hongmei, LI Tianrui, et al. Neighborhood rough sets with distance metric learning for feature selection[J]. Knowledge-Based Systems, 2021, 224:107076.
[17] WAN Jihong, CHEN Hongmei, YUAN Zhong, et al. A novel hybrid feature selection method considering feature interaction in neighborhood rough set[J]. Knowledge-Based Systems, 2021, 227:107167.
[18] SUN Lin, WANG Tianxiang, DING Weiping, et al. Feature selection using fisher score and multilabel neighborhood rough sets for multilabel classification[J]. Information Sciences, 2021, 578:887-912.
[19] 张雨新,孙达明,李飞. 基于粒化单调的不完备混合型数据增量式属性约简算法[J]. 计算机应用与软件, 2021, 38(3):279-286. ZHANG Yuxin, SUN Daming, LI Fei. Incremental attribute reduction algorithm for incomplete mixed data based on granulation monotony[J]. Computer Applications and Software, 2021, 38(3):279-286.
[20] 蔡艳婧,程实,王强. 不完备混合决策粗糙集特定类多目标属性约简[J]. 计算机工程与设计, 2020, 41(11):3063-3071. CAI Yanjing, CHENG Shi, WANG Qiang. Class-specific multi-objective attribute reduction for incomplete mixed decision-theoretic rough set[J]. Computer Engineering and Design, 2020, 41(11):3063-3071.
[21] 李小南,赵璐,易黄建. 基于加权信息熵的直觉模糊信息系统的三支决策[J]. 控制与决策, 2022, 37(10):2705-2713. LI Xiaonan, ZHAO Lu, YI Huangjian. Three-way decision of intuitionistic fuzzy information systems based on the weighted information entropy[J]. Control and Decision, 2022, 37(10):2705-2713.
[22] 徐怡,李宝峰,李策. 基于权重分布的多粒度粗糙集模型[J]. 模糊系统与数学, 2020, 34(6):55-67. XU Yi, LI Baofeng, LI Ce. Multi-granulation rough set model based on weight distribution[J]. Fuzzy Systems and Mathematics, 2020, 34(6):55-67.
[23] VLUYMANS S, PARTHALAIN N M, CORNELIS C, et al. Weight selection strategies for ordered weighted average based fuzzy rough sets[J]. Information Sciences, 2019, 501:155-171.
[24] HU Qinghua, ZHANG Lei, ZHANG David, et al. Measuring relevance between discrete and continuous features based on neighborhood mutual information[J]. Expert Systems with Applications, 2011, 38:10737-10750.
[25] DEMIAR J, SCHUURMANS D. Statistical comparisons of classifiers over multiple data sets[J]. Journal of Machine Learning Research, 2006, 7(1):1-30.
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