南京航空航天大学学报（英文版）2006，Vol.23Issue(3)：208-213,6.
联合模糊c-均值聚类模型
ALLIED FUZZY c-MEANS CLUSTERING MODEL
武小红 1周建江2
作者信息
- 1. 南京航空航天大学信息科学与技术学院,南京,210016,中国
- 2. 江苏大学电气信息工程学院,镇江,212013,中国
- 折叠
摘要
Abstract
A novel model of fuzzy clustering, i.e. an allied fuzzy c-means (AFCM) model is proposed based on the combination of advantages of fuzzy c-means (FCM) and possibilistic c-means (PCM) clustering. PCM is sensitive to initializations and often generates coincident clusters. AFCM overcomes this shortcoming and it is an extension of PCM. Membership and typicality values can be simultaneously produced in AFCM. Experimental results show that noise data can be well processed, coincident clusters are avoided and clustering accuracy is better.关键词
模糊c-均值聚类/可能性c-均值聚类/联合模糊c-均值聚类Key words
fuzzy c-means clustering/possibilistic c-means clustering/allied fuzzy c-means clustering分类
信息技术与安全科学引用本文复制引用
武小红,周建江..联合模糊c-均值聚类模型[J].南京航空航天大学学报（英文版）,2006,23(3):208-213,6.
