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基于熵权法加权的模糊C均值聚类算法研究
引用本文:王国伟,闫丽,姚玉霞. 基于熵权法加权的模糊C均值聚类算法研究[J]. 计算机与农业, 2010, 0(8): 148-150,153
作者姓名:王国伟  闫丽  姚玉霞
作者单位:吉林农业大学信息技术学院,长春130118
基金项目:国家“863”高科技计划项目(编号2006AA10A309、2006AA10Z245); 国家成果转化资金项目(编号2006GB2B100068)
摘    要:针对模糊C均值聚类算法不能区分数据各属性之间的不平衡性,提出了一种基于熵权法加权的模糊C均值聚类算法。该算法首先应用熵权法计算各属性的权重系数,然后对标准化之后的原始数据进行加权,最后应用模糊C均值聚类算法对加权之后的数据进行聚类。实验表明,该算法聚类准确率要明显高于未加权的模糊C均值聚类算法。

关 键 词:熵权法  模糊C均值  模糊聚类分析  权重系数

Research on Weighted Fuzzy C-means Clustering Algorithm Based on Entropy Weight Method
WANG Guowei,YAN Li,YAO Yuxia. Research on Weighted Fuzzy C-means Clustering Algorithm Based on Entropy Weight Method[J]. Computer and Agriculture, 2010, 0(8): 148-150,153
Authors:WANG Guowei  YAN Li  YAO Yuxia
Affiliation:(College of Information and Technology Science Jilin Agricultural University,Changchun 130118)
Abstract:For the fuzzy C-means clustering algorithm cannot differentiate the imbalance between the various properties,this paper proposed the fuzzy C-means clustering algorithm based on entropy weight weighted.First,the algorithm applied entropy weight method to calculate the weight coefficient of each attribute;and then,the standardized raw data are weighted;finally fuzzy C-means clustering algorithm was applied to cluster the weighted data.Experiment results showed that the accuracy of this clustering algorithm was significantly higher than unweighted fuzzy C-means clustering algorithm.
Keywords:entropy weight method  fuzzy C-means clustering  fuzzy clustering analysis  weight coefficient
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