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Consistent Matrix: A Feature Selection Framework for Large-Scale Datasets

文献类型：期刊论文

作者Yang, Tian1; Li, Yuan-Jiang1; Qian, Yuhua2; Wang, Fei-Yue3
刊名IEEE TRANSACTIONS ON FUZZY SYSTEMS
出版日期2023-11-01
卷号31期号:11页码:4024-4038
ISSN号1063-6706
关键词Consistent matrix feature selection fuzzy arithmetic covering fuzzy rough sets granular computing
DOI10.1109/TFUZZ.2023.3275635
通讯作者Wang, Fei-Yue(feiyue.wang@ia.ac.cn)
英文摘要Large-scale data processing based on limited computing resources has always been a difficult problem in data mining, where feature selection is often used as an effective data compressing mechanism. For granular computing of Big Data, discernibility matrix and dependency degree are the most representative methods for matrix-based and feature-importance-degree-based feature selection, respectively. However, their temporal and space complexities are high and often lead to poor performance. In this article, a novel feature selection framework for large-scale data processing with linear complexities was proposed for the first time. First, a much more concise fuzzy granule set, called fuzzy arithmetic covering, was introduced to reduce computational costs. Then, a new matrix-based feature selection framework, namely consistent matrix, was proposed for general rough set models. As a result, a heuristic attribute reduction algorithm, i.e., HARCM, was designed accordingly. Compared with six state-of-the-art algorithms for feature selection, the average running time of the newly proposed algorithm was reduced up to 2913 times, with a comparable or even better classification performance.
WOS关键词ROUGH FUZZY-SETS ; ATTRIBUTE REDUCTION ; APPROXIMATION SPACES ; MUTUAL INFORMATION ; DYNAMIC-SYSTEMS ; MAX-DEPENDENCY ; ALGORITHM ; UNCERTAINTY ; REDUNDANCY ; RELEVANCE
资助项目National Natural Science Foundation of China[11201490] ; National Natural Science Foundation of China[61976089] ; National Natural Science Foundation of China[72071207] ; Natural Science Foundation of Hunan Province[2021JJ20037] ; Training Program for Excellent Young Innovators of Changsha[kq1905031] ; National Key Research and Development Program of China[2021ZD0112400] ; Key Program of the National Natural Science Foundation of China[62136005]
WOS研究方向Computer Science ; Engineering
语种英语
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号WOS:001097110800022
资助机构National Natural Science Foundation of China ; Natural Science Foundation of Hunan Province ; Training Program for Excellent Young Innovators of Changsha ; National Key Research and Development Program of China ; Key Program of the National Natural Science Foundation of China
源URL[http://ir.ia.ac.cn/handle/173211/55198]  
专题多模态人工智能系统全国重点实验室
通讯作者Wang, Fei-Yue
作者单位1.Hunan Normal Univ, Hunan Prov Key Lab Intelligent Comp & Language Inf, Changsha 410081, Peoples R China
2.Shanxi Univ, Inst Big Data Sci & Ind, Taiyuan 030006, Peoples R China
3.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100080, Peoples R China
推荐引用方式
GB/T 7714		 Yang, Tian,Li, Yuan-Jiang,Qian, Yuhua,et al. Consistent Matrix: A Feature Selection Framework for Large-Scale Datasets[J]. IEEE TRANSACTIONS ON FUZZY SYSTEMS,2023,31(11):4024-4038.
APA Yang, Tian,Li, Yuan-Jiang,Qian, Yuhua,&Wang, Fei-Yue.(2023).Consistent Matrix: A Feature Selection Framework for Large-Scale Datasets.IEEE TRANSACTIONS ON FUZZY SYSTEMS,31(11),4024-4038.
MLA Yang, Tian,et al."Consistent Matrix: A Feature Selection Framework for Large-Scale Datasets".IEEE TRANSACTIONS ON FUZZY SYSTEMS 31.11(2023):4024-4038.

入库方式： OAI收割

来源：自动化研究所

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