Multi-feature weighting neighborhood density clustering

doi:10.1007/s00521-019-04467-4

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 机器人理论与应用

	Multi-feature weighting neighborhood density clustering
	Xu, Shuliang 1; Feng, Lin 2; Liu, Shenglan 2; Zhou, Jian 1; Qiao, Hong3,4
发表期刊	NEURAL COMPUTING & APPLICATIONS
ISSN	0941-0643
	2020-07-01
卷号	32 期号:13 页码:9545-9565
通讯作者	Feng, Lin(fenglin@dlut.edu.cn)
摘要	Clustering is an important data mining method to discover knowledge and patterns. Feature weighting is widely applied in high-dimensional data mining. In this paper, a multi-feature weighting neighborhood density clustering algorithm is proposed. It uses different dimension reduction algorithms to generate different features, and then, the weights of the features are determined by the discrimination ability. For the clustering algorithm, the center points can be selected by the upper approximation set and lower approximation set. At last, the final clustering result is from the fusion of multiple clustering results. The proposed algorithms and comparison algorithms are executed on the synthetic and real-world data sets. The test results show that the proposed algorithm outperforms the comparison algorithms on the most experimental data sets. The experimental results prove that the proposed algorithm is effective for data clustering.
关键词	Clustering analysis Multi-feature Neighborhood density Rough set Granular computing
DOI	10.1007/s00521-019-04467-4
关键词[WOS]	SUBSPACE ; ALGORITHM
收录类别	SCI
语种	英语
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence
WOS记录号	WOS:000544784200045
出版者	SPRINGER LONDON LTD
引用统计	被引频次：3[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/173211/40008
专题	多模态人工智能系统全国重点实验室_机器人理论与应用
通讯作者	Feng, Lin
作者单位	1.Dalian Univ Technol, Fac Elect Informat & Elect Engn, Dalian, Peoples R China 2.Dalian Univ Technol, Sch Innovat & Entrepreneurship, Dalian, Peoples R China 3.Chinese Acad Sci, Inst Automat, Beijing, Peoples R China 4.State Key Lab Management & Control Complex Syst, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Xu, Shuliang,Feng, Lin,Liu, Shenglan,et al. Multi-feature weighting neighborhood density clustering[J]. NEURAL COMPUTING & APPLICATIONS,2020,32(13):9545-9565.
APA	Xu, Shuliang,Feng, Lin,Liu, Shenglan,Zhou, Jian,&Qiao, Hong.(2020).Multi-feature weighting neighborhood density clustering.NEURAL COMPUTING & APPLICATIONS,32(13),9545-9565.
MLA	Xu, Shuliang,et al."Multi-feature weighting neighborhood density clustering".NEURAL COMPUTING & APPLICATIONS 32.13(2020):9545-9565.