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

doi:10.1109/TFUZZ.2023.3275635

	Consistent Matrix: A Feature Selection Framework for Large-Scale Datasets
	Yang, Tian 1; Li, Yuan-Jiang 1; Qian, Yuhua 2; Wang, Fei-Yue3
发表期刊	IEEE TRANSACTIONS ON FUZZY SYSTEMS
ISSN	1063-6706
	2023-11-01
卷号	31 期号:11 页码:4024-4038
通讯作者	Wang, Fei-Yue(feiyue.wang@ia.ac.cn)
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.
关键词	Consistent matrix feature selection fuzzy arithmetic covering fuzzy rough sets granular computing
DOI	10.1109/TFUZZ.2023.3275635
关键词[WOS]	ROUGH FUZZY-SETS ; ATTRIBUTE REDUCTION ; APPROXIMATION SPACES ; MUTUAL INFORMATION ; DYNAMIC-SYSTEMS ; MAX-DEPENDENCY ; ALGORITHM ; UNCERTAINTY ; REDUNDANCY ; RELEVANCE
收录类别	SCI
语种	英语
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]
项目资助者	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
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS记录号	WOS:001097110800022
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：2[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/55199
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
通讯作者单位	中国科学院自动化研究所
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.