###
DOI:
Journal of Software:2004.15(6):858-868

基于划分的模糊聚类算法
张敏,于剑
(北京交通大学,计算机与信息技术学院,北京,100044)
Fuzzy Partitional Clustering Algorithms
ZHANG Min,YU Jian
()
Abstract
Chart / table
Reference
Similar Articles
Article :Browse 4920   Download 8210
Received:June 01, 2004    
> 中文摘要: 在众多聚类算法中,基于划分的模糊聚类算法是模式识别中最常用的算法类型之一.至今,文献中仍不断有关于基于划分的模糊聚类算法的研究成果出现.为了能更为系统和深入地了解这些聚类算法及其性质,本文从改变度量方式、改变约束条件、在目标函数中引入熵以及考虑对聚类中心进行约束等几个方面,对在C-均值算法的基础上得到的基于划分的模糊聚类算法作了综述和评价,对各典型算法的优缺点进行了实验比较分析.指出标准FCM算法被广泛应用的原因之一是它对数据的比例变化具有鲁棒性,而其他类似的算法对这种比例变化却很敏感,并以极大熵方法为例进行了比较实验.最后总结了基于划分的模糊聚类算法普遍存在的问题及其发展前景.
中文关键词: 划分聚类  C均值  权重指数    隶属度函数
Abstract:Fuzzy partitional clustering algorithms are widely used in pattern recognition field. Until now, more and more research results on them have been developed in the literature. In order to study these algorithms systematically and deeply, they are reviewed in this paper based on c-means algorithm, from metrics, entropy, and constraints on membership function or cluster centers. Moreover, the advantages and disadvantages of the typical fuzzy partitional algorithms are discussed. It is pointed out that the standard FCM algorithm is robust to the scaling transformation of dataset, while others are sensitive to such transformation. Such conclusion is experimentally verified when implementing the standard FCM and the maximum entropy clustering algorithm. Finally, the problems existing in these algorithms and the prospects of the fuzzy partitional algorithms are discussed.
文章编号:     中图分类号:    文献标志码:
基金项目:Supported by the National Natural Science Foundation of China under Grant No.60303014(国家自然科学基金);the Scientific Key Project of Ministry of Education of China under Grant No.02031(教育部科学技术研究重点项目) Supported by the National Natural Science Foundation of China under Grant No.60303014(国家自然科学基金);the Scientific Key Project of Ministry of Education of China under Grant No.02031(教育部科学技术研究重点项目)
Foundation items:
Reference text:

张敏,于剑.基于划分的模糊聚类算法.软件学报,2004,15(6):858-868

ZHANG Min,YU Jian.Fuzzy Partitional Clustering Algorithms.Journal of Software,2004,15(6):858-868