山西大学学报（自然科学版）2024，Vol.47Issue(1)：30-39,10.DOI:10.13451/j.sxu.ns.2023140
基于簇中心预选策略的三支决策密度峰值聚类算法
Three-way Decision-based Density Peak Clustering Algorithm with Clustering Centers Preselection
摘要
Abstract
Aiming at the uncertainty problem that the CFSFDP(clustering by fast search and find of density peaks)algorithm cannot automatically select the clustering center,in this paper,we propose a three-way decision-based density peak clustering algorithm with clustering centers preselection(TDPC)by incorporating the three-way decision theory.Firstly,the statistical characteristics of density and distance are used to divide the data objects into core region,boundary region and trivial region.The qualified cluster cen-ters are assigned to the core region,and the suspected cluster centers that are difficult to determine are placed in the boundary region.Then the defined k-reachable region and discriminant criterion are used to analyze the suspected cluster centers,and the actual clus-ter centers are subsequently selected.The proposed algorithm can effectively solve the problem of automatic determination of cluster centers in density peak clustering algorithm.The proposed algorithm is evaluated on two synthetic datasets and four UCI(University of California,lrvine)public datasets.Comparing to the CFSFDP algorithm and the DBSCAN(Density-Based Spatial Clustering of Applications with Noise)algorithm,TDPC demonstrated clustering performance that is on par with or superior to the optimal algo-rithm across various clustering evaluation indexes,including silhouette coefficient,DB(Davies-Bouldin)index,adjusted mutual in-formation,adjusted rand index,FM(Fowlkes-Mallows)index,homogeneity,and completeness.These results indicate that TDPC outperforms the comparison algorithms in terms of comprehensive clustering performance,and highlight its good clustering feasibili-ty and effectiveness.关键词
聚类算法/聚类中心/边界域/三支聚类/密度聚类/k-可达域Key words
clustering algorithm/clustering center/boundary region/three-way clustering/density clustering/k-reachable region分类
信息技术与安全科学引用本文复制引用
罗舒文,万仁霞,苗夺谦..基于簇中心预选策略的三支决策密度峰值聚类算法[J].山西大学学报（自然科学版）,2024,47(1):30-39,10.基金项目
国家自然科学基金(61662001) （61662001）
中央高校基本科研业务费专项资金(FWNX04) （FWNX04）
宁夏自然科学基金(2021AAC03203) （2021AAC03203）
