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山东大学学报 (工学版) ›› 2022, Vol. 52 ›› Issue (2): 57-66.doi: 10.6040/j.issn.1672-3961.0.2021.317

• • 上一篇    

自适应图正则的单步子空间聚类

程业超,刘惊雷*   

  1. 烟台大学计算机与控制工程学院, 山东 烟台 264005
  • 发布日期:2022-04-20
  • 作者简介:程业超(1997— ),男,山东泰安人,硕士研究生,主要研究方向为子空间聚类的建模与优化. E-mail:ytdxcyc@163.com. *通信作者简介:刘惊雷(1970— ),男,山西临猗人,教授,博士,硕士生导师,主要研究方向为人工智能和理论计算机科学. E-mail:jinglei_liu@sina.com
  • 基金资助:
    国家自然科学基金资助项目(61572419,62072391);山东省自然科学基金资助项目(ZR2020MF148)

One-step subspace clustering with adaptive graph regularization

CHENG Yechao, LIU Jinglei*   

  1. School of Computer and Control Engineering, Yantai University, Yantai 264005, Shandong, China
  • Published:2022-04-20

摘要: 针对子空间聚类算法中相似性学习和谱聚类相互分离的问题,提出自适应图正则的单步子空间聚类(one-step subspace clustering with adaptive graph regularization, OSCAGR)算法。利用Frobenius范数鼓励分组效应,根据局部连通性为每个数据点分配自适应的最优邻域学习系数矩阵;考虑全局结构和局部结构,保证数据空间中相近的点拥有较大的表示系数;通过量化范数将子空间聚类两个独立的阶段整合到一个统一的优化框架中。试验结果表明,OSCAGR算法在UCI数据集和3个图像数据集上比其他对比方法的精度高1%~7%,OSCAGR算法的聚类正确率和归一化互信息优于其他对比方法。

关键词: 子空间聚类, 谱聚类, 单步, 自适应图正则, 量化范数

中图分类号: 

  • TP181
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