基于核函数的混合C均值聚类算法  

Hybrid C-means Clustering Algorithm Based on the Kernel Function

作　　者：周巧萍[1] 潘晋孝[1] 杨明[1] 

机构地区：[1]中北大学理学院数学系,山西太原030051

出　　处：《模糊系统与数学》2008年第6期148-151,共4页Fuzzy Systems and Mathematics

基　　金：山西省自然科学基金资助项目(20051042);山西省研究生创新项目(20061024)

摘　　要：提出了一种基于核函数的混合C均值聚类算法。首先利用模糊C均值聚类算法和另一种类型的可能性C均值聚类算法的优点,设计出一种混合C均值聚类算法。然而鉴于该算法存在的不足,本文将Mercer核函数引入到该算法中,仿真实验结果证实了该方法的可行性和有效性。A hybrid C-means clustering algorithm based on the kernel function was presented in this paper. Firstly, the advantages of fuzzy C-means clustering algorithm and another possibilistic C-means clustering algorithm were utilized to design a new hybrid C-means clustering algorithm accordingly in this paper. And then on account of the lack of the algorithm, this paper would introduce Mercer kernel function into the algorithm, so the clustering was better performed. The results of simulation experiments show the feasibility and effectiveness of the hybrid C-means clustering based on the kernel function.

关 键 词：核函数 混合C均值聚类 可能性C均值聚类 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]