郑州大学学报（理学版）2025，Vol.57Issue(6)：16-23,8.DOI:10.13705/j.issn.1671-6841.2024108
基于粒球邻域粗糙集的三支高斯混合聚类
Three-way Gaussian Mixture Clustering Based on Granular Ball Neighborhood Rough Sets
摘要
Abstract
In order to solve the problem of redundant information in affecting the clustering effect of three-way Gaussian mixture models in high-dimensional datasets,the theory of granular ball neighborhood rough sets was integrated into the model,and a three-way Gaussian mixture clustering model based on granular ball neighborhood rough sets was proposed.Firstly,k-means clustering was used to generate a set of granular balls that meet the purity requirements,and attribute reduction was performed with the in-variant constraint of the positive region produced by the granular balls to extract key attributes.Secondly,the three-way Gaussian mixture model was used to cluster the reduced data,dividing the objects into the core region or the boundary region of the clusters.Comparative experimental results on 7 UCI public data-sets demonstrated that the proposed model not only inherited the superior clustering performance of the three-way Gaussian mixture model with higher accuracy,silhouette coefficient,and lower Davies-Bouldin index,but also provided a more accurate depiction of the cluster boundaries.Furthermore,as a result of reducing attributes in high-dimensional space,the proposed model achieved lower time complexity.关键词
高维数据/三支高斯混合模型/聚类/粒球邻域粗糙集/正域/属性约简Key words
high-dimensional data/three-way Gaussian mixture model/clustering/granular ball neigh-borhood rough set/positive region/attribute reduction分类
信息技术与安全科学引用本文复制引用
邵春梅,万仁霞,苗夺谦,赵杰..基于粒球邻域粗糙集的三支高斯混合聚类[J].郑州大学学报（理学版）,2025,57(6):16-23,8.基金项目
国家自然科学基金项目(62066001) （62066001）
宁夏科技领军人才项目(2022GKLRLX08) （2022GKLRLX08）
宁夏自然科学基金项目(2021AAC03203) （2021AAC03203）
