Computer Engineering and Applications ›› 2011, Vol. 47 ›› Issue (8): 135-137.

• 数据库、信号与信息处理 • Previous Articles     Next Articles

Study of clustering using improved Parzen window on high-dimension dataset

CHAI Yi1,LI Jie1,TANG Jing2   

  1. 1.College of Automation,Chongqing University,Chongqing 400030,China
    2.Lan-Cheng-Yu Oil Transportation Division,PetroChina Pipeline Company,Chengdu 610036,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2011-03-11 Published:2011-03-11

改进Parzen窗解决高维数据聚类的方法研究

柴 毅1,利 节1,唐 婧2   

  1. 1.重庆大学 自动化学院,重庆 400030
    2.中国石油管道公司 兰成渝输油分公司,成都 610036

Abstract: Due to the realistic meaning of clustering on high-dimension dataset,excellent result can be acquired when clustering dataset using traditional Parzen window on low-dimension.With the higher dimension,the efficiency decreases quickly.Through many simulate experiments,the weighting function is gained.The high-dimension dataset is shadowed on lower-dimensional space,and clustered,then shadowed back to higher-dimensional space.The result matrix is optimized,and the better clustering effect is gained.

Key words: high-dimensional dataset, Parzen window, clustering

摘要: 由于高维数据聚类的现实意义日益增强,而Parzen窗估计法仅对低维数据集聚类能获得良好的结果,随着维数增加,效率降低,因此对Parzen窗进行加权改进,通过多次仿真实验确定加权函数,将高维数据投射至低维空间,对其聚类,逐步投向高维空间,对结果矩阵进行优化处理,得到更为优良的聚类效果。

关键词: 高维数据, Parzen窗, 聚类