SMpeaks-A semi-supervised clustering algorithm based on density peaks

doi:10.1117/12.2652790

	SMpeaks-A semi-supervised clustering algorithm based on density peaks
	Duan, Huiyu; Chen, Chen; Wang, Jikui
	2022
会议名称	6th International Workshop on Advanced Algorithms and Control Engineering, IWAACE 2022
会议录名称	Proceedings of SPIE - The International Society for Optical Engineering
卷号	12350
会议日期	July 8, 2022 - July 10, 2022
会议地点	Qingdao, China
会议录编者/会议主办者	Academic Exchange Information Center (AEIC)
出版者	SPIE
摘要	Clustering by fast search and find of Density Peaks (referred to as DP) was introduced by Alex Rodriguez and Alessandro Laio. DP algorithm is based on the idea that cluster centers are characterized by a higher density than their neighbors and by a relatively large distance from points with higher densities. This algorithm can discover clusters regardless of their shapes and the dimensions of the space containing them. However, it cannot effectively detect clusters with different sizes and densities of arbitrary shapes, especially the same cluster with multiple peaks. Moreover, the DP algorithm needs to select the centers of the clusters by using a decision graph manually. Despite a highly improved performance in semi-supervised clustering, to address this problem, we propose a semi-supervised framework for DP, namely SMpeaks, by integrating pairwise must-link and cannot-link constraints to guide the clustering procedure. We tested the SMpeaks algorithm on complex data sets having clusters with arbitrary shapes, different sizes, and densities. The experimental results have demonstrated that this algorithm is more effective in finding clusters of complex shapes and different densities than DP. © 2022 SPIE.
关键词	Clustering algorithms Machine learning Arbitrary shape Cluster centers Clusterings Density Different densities Different sizes Fast search Multiple-peak Semi-supervised clustering algorithms Semi-supervised learning
DOI	10.1117/12.2652790
收录类别	EI
语种	英语
EI入藏号	20224613130291
EI主题词	Data mining
EI分类号	723.2 Data Processing and Image Processing ; 723.4 Artificial Intelligence ; 903.1 Information Sources and Analysis
原始文献类型	Conference article (CA)
文献类型	会议论文
条目标识符	http://ir.lzufe.edu.cn/handle/39EH0E1M/33111
专题	信息工程与人工智能学院信息中心
作者单位	School of Information Engineering, Lanzhou University of Finance and Economics, Lanzhou; 730020, China
推荐引用方式 GB/T 7714	Duan, Huiyu,Chen, Chen,Wang, Jikui. SMpeaks-A semi-supervised clustering algorithm based on density peaks[C]//Academic Exchange Information Center (AEIC):SPIE,2022.