%0 Journal Article
%T Possibility Fuzzy Clustering Approach with Weighted Features<br>一种基于加权特征的可能模糊聚类方法*
%A LUO Jian-jun
%A GUAN Tao
%A FENG Bo-qin
%A <br>罗建军
%A 管涛
%A 冯博琴
%J 计算机应用研究
%D 2006
%I 
%X Based on the different weights of features of objects, this paper presents two weighted feature-based improved possibilistic fuzzy clustering models separately with a probable weighted feature constraint and a possibilistic one respectively. The possibilistic model extends the PCM and enlarges its applications. Experimental results show that this model can reasonably cluster data in terms of different probable weights or possibilistic weights, which extends the applications of improved PCM, furthermore, the clustering results have an advantage over PCM.
%K Possibility Fuzzy Clustering
%K Weighted Feature
%K Piobable Constraint
%K Possibility Constraint<br>可能模糊聚类
%K 加权特征
%K 概率约束
%K 可能性约束
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=FC3E0C08D560F030&yid=37904DC365DD7266&vid=EA389574707BDED3&iid=B31275AF3241DB2D&sid=286FB2D22CF8D013&eid=318E4CC20AED4940&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=6