Computer Engineering and Applications ›› 2008, Vol. 44 ›› Issue (6): 182-183.

• 数据库与信息处理 • Previous Articles     Next Articles

Weighted fuzzy C-means for mixed feature variables

XIE Xin-xi,WANG Shi-tong   

  1. School of Information and Technology,Jiangnan University,Wuxi,Jiangsu 214122,China
  • Received:2007-06-13 Revised:2007-09-07 Online:2008-02-21 Published:2008-02-21
  • Contact: XIE Xin-xi

带特征权重的混合特征模糊C均值算法

谢信喜,王士同   

  1. 江南大学 信息工程学院,江苏 无锡 214122
  • 通讯作者: 谢信喜

Abstract: Hathaway has proposed the Fuzzy C-Means Algorithm (FCM) for fuzzy data.For symbolic data El-Sonbaty and Ismail have proposed Fuzzy Symbolic C-Means Algorithm(FSCM) which has been improved by Miin-Shen Yang et al.The proposed Fuzzy Clustering Algorithms For Mixed Feature Variables (MVFCM) that is more available and more practical than FSCM.Base on the MVFCM,this paper gives Weightd MVFCM (WMVFCM),and it is tested through experiment that WMVFCM is more available than MVFCM for mixed feature dataset.

摘要: 针对模糊数据,Hathaway提出了模糊C均值算法(FCM);针对符号数据,El-Sonbaty 和Ismail提出了符号数据模糊C均值算法(FSCM);Miin-Shen Yang等人对FSCM进行了改进,提出了混合特征的模糊C均值算法(MVFCM),MVFCM比FSCM更有效更具有实用性。在MVFCM的基础上,给出了带特征权重的混合特征的模糊C均值算法(WMVFCM),并通过实验比较,说明WMVFCM比MVFCM更有效。