JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2023, Vol. 58 ›› Issue (5): 26-35.doi: 10.6040/j.issn.1671-9352.4.2022.1581

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Attribute reduction algorithm based on discreteness of the universe

LIU Changshun1, LIU Yan1, SONG Jingjing1*, XU Taihua1,2   

  1. 1. School of Computer, Jiangsu University of Science and Technology, Zhenjiang 212100, Jiangsu, China;
    2. Key Laboratory of Oceanographic Big Data Mining &
    Application of Zhejiang Province, Zhejiang Ocean University, Zhoushan 316022, Zhejiang, China
  • Published:2023-05-15

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Abstract: A fitness function based on the dispersion of the universe was proposed. Under the forward greedy searching strategy, the fitness function was employed to evaluate the importance of conditional attributes and then used to derive the reduct of the neighborhood rough set. The proposed algorithm was compared with three state-of-the-art attribute reduction algorithms and validated on 12 UCI datasets. Experimental results showed that compared with the other three algorithms, the proposed algorithm exhibited better in time consumption and stability without reducing the classification effect.

Key words: attribute reduction, conditional attribute, fitness function, neighborhood rough set

CLC Number: 

  • TP181
[1] PAWLAK Z. Rough sets[J]. International Journal of Computer & Information Sciences, 1982, 11(5):341-356.
[2] 钱进,汤大伟,洪承鑫.多粒度层次序贯三支决策模型研究[J].山东大学学报(理学版),2022,57(9):33-45. QIAN Jin, TANG Dawei, HONG Chengxin. Research on multi-granularity hierarchical sequential three-way decision model[J]. Journal of Shandong University(Natural Science), 2022, 57(9):33-45.
[3] 张文娟,李进金,林艺东. 基于图的悲观多粒度粗糙集粒度约简[J].山东大学学报(理学版),2021,56(1):60-67. ZHANG Wenjuan, LI Jinjin, LIN Yidong. Graph-based granularity reduction in pessimistic multi-granulation rough set[J]. Journal of Shangdong University(Natural Science), 2021, 56(1):60-67.
[4] 万青,马盈仓,魏玲. 基于多粒度的多源数据知识获取[J].山东大学学报(理学版),2020,55(1):41-50. WAN Qing, MAYingcang, WEI Ling. Knowledge acquisition of multi-source data based on multigranularity[J]. Journal of Shangdong University(Natural Science), 2020, 55(1):41-50.
[5] SONG Jingjing, TSANG E C C, CHEN Degang, et al. Minimal decision cost reduct in fuzzy decision-theoretic rough set model[J]. Knowledge-Based Systems, 2017, 126:104-112.
[6] 李智远,杨习贝,徐苏平,等.邻域决策一致性的属性约简方法研究[J].河南师范大学学报(自然科学版),2017,45(5):68-73. LI Zhiyuan, YANG Xibei, XU Suping, et al. Attribute reduction approach to neighborhood decision agreement[J]. Journal of Henan Normal University(Natural Science Edition), 2017, 45(5):68-73.
[7] LIU Yong, HUANG Wenliang, JIANG Yunliang, et al. Quick attribute reduct algorithm for neighborhood rough set model[J]. Information Sciences, 2014, 271(1):65-81.
[8] CHEN Hongmei, LI Tianrui, CAI Yong, et al. Parallel attribute reduction in dominance-based neighborhood rough set[J]. Information Sciences, 2016, 373(1):351-368.
[9] WANG Changzhong, SHAO Mingwen, HE Qiang, et al. Feature subset selection based on fuzzy neighborhood rough sets[J]. Knowledge-Based Systems, 2016, 111(1):173-179.
[10] YAO Yiyu, ZHAO Yan. Discernibility matrix simplification for constructing attribute reducts[J]. Information Sciences, 2009, 179(7):867-882.
[11] YANG Xibei, QI Yunsong, SONG Xiaoning, et al. Test cost sensitive multigranulation rough set: model and minimal cost selection[J]. Information Sciences, 2013, 250:184-199.
[12] 胡清华,于达仁,谢宗霞.基于邻域粒化和粗糙逼近的数值属性约简[J].软件学报,2008,19(3):640-649. HU Qinghua, YU Daren, XIE Zongxia. Numerical attribute reduction based on neighborhood granulation and rough approximation[J]. Journal of Software, 2008, 19(3):640-649.
[13] 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(9):10737-10750.
[14] WANG Yibo, CHEN Xiangjian, DONG Kai. Attribute reduction via local conditional entropy[J]. International Journal of Machine Learning and Cybernetics, 2019, 10(12):3619-3634.
[15] 周艳红,张贤勇,莫智文.粒化单调的条件邻域熵及其相关属性约简[J].计算机研究与发展,2018,55(11):2395-2405. ZHOU Yanhong, ZHANG Xianyong, MO Zhiwen. Conditional neighborhood entropy with granulation monotonicity relevant attribute reduction[J]. Journal of Computer Research and Development, 2018, 55(11):2395-2405.
[16] 王念,彭政红,崔莉.EasiFFRA: 一种基于邻域粗糙集的属性快速约简算法[J].计算机研究与发展,2019,56(12):2578-2588. WANG Nian, PENG Zhenghong, CUI Li. EasiFFRA: a fast feature reduction algorithm based on neighborhood rough set[J]. Journal of Computer Research and Development, 2019, 56(12):2578-2588.
[17] YANG Xibei, YAO Yiyu. Ensemble selector for attribute reduction[J]. Applied Soft Computing, 2018, 70:1-11.
[18] GAO Yuan, CHEN Xiangjian, YANG Xibei, et al. Ensemble-based neighborhood attribute reduction: a multigranularity view[J]. Complexity, 2019, 2019:1-17.
[19] YAO Yiyu, ZHAO Yan, WANG Jue. On reduct construction algorithms[M] //Transactions on Computational Science II. Berlin: Springer, 2008: 100-117.
[20] 巴婧,陈妍,杨习贝.快速求解粒球粗糙集约简的属性划分方法[J].南京理工大学学报,2021,45(4):394-400. BA Jing, CHEN Yan, YANG Xibei. Attribute partition strategy for quick searching reducts based on granular ball rough sets[J]. Journal of Nanjing University of Science and Technology, 2021, 45(4):394-400.
[21] IORIO C, ARIA M, D'AMBROSIO A, et al. Informative trees by visual pruning[J]. Expert Systems with Applications, 2019, 127:228-240.
[22] WANG Rui, LI Wei, LI Rui, et al. Automatic blur type classification via ensemble SVM[J]. Signal Processing: Image Communication, 2019, 71:24-35.
[23] YU Hualong, MU Chaoxu, SUN Changyin, et al. Support vector machine-based optimized decision threshold adjustment strategy for classifying imbalanced data[J]. Knowledge-Based Systems, 2015, 76:67-78.
[24] YU Hualong, SUN Changyin, YANG Xibei, et al. Fuzzy support vector machine with relative density information for classi-fying imbalanced data[J]. IEEE Transactions on Fuzzy Systems, 2019, 27(12):2353-2367.
[25] ZHANG Shichao, LI Xuelong, ZONG Ming, et al. Efficient kNN classification with different numbers of nearest neighbors[J]. IEEE Transactions on Neural Networks and Learning Systems, 2017, 29(5):1774-1785.
[26] HU Qinghua, LIU Jinfu, YU Daren. Stability analysis on rough set based feature evaluation[C] //International Conference on Rough Sets and Knowledge Technology. Berlin: Springer, 2008: 88-96.
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