| 一种基于信息熵与K均值迭代模型的模糊聚类算法 |
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| 引用本文： | 吴春旭,吴镝,蒋宁.一种基于信息熵与K均值迭代模型的模糊聚类算法[J].中国管理科学,2008(Z1). |
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| 作者姓名： | 吴春旭 吴镝 蒋宁 |
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| 作者单位： | 中国科学技术大学管理学院; |
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| 摘 要： | 本文提出了基于信息熵和K均值算法混合迭代模糊聚类的细分模型,解决了模糊聚类的原型初始化参数问题。将信息熵和K均值算法引入模糊聚类中进行分析,并结合测试样本数据进行实际分析,与传统方法相比,取得了较好的效果。
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| 关 键 词： | 客户细分 模糊聚类 信息熵 K均值算法 |
One Fuzzy Clustering Algorithm Based on Iterative model of Information Entropy and K-means |
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| WU Chun-xu,WU Di,JIANG Ning.One Fuzzy Clustering Algorithm Based on Iterative model of Information Entropy and K-means[J].Chinese Journal of Management Science,2008(Z1). |
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| Authors: | WU Chun-xu WU Di JIANG Ning |
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| Institution: | WU Chun-xu,WU Di,JIANG Ning (School of Management,University of Science , Technology of China,Hefei 230052,China) |
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| Abstract: | The sub-cluster model based on the fuzzy clustering algorithm based on iterative model of entropy and Kmeans, solves the issue of the fuzzy cluster initialization parameters.Information entropy and K-means algorithm in the introduction of fuzzy clustering analysis,combined with the test sample analysis of the actual data,compared with traditional methods,and achieved good results. |
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| Keywords: | customer segmentation fuzzy clustering information entropy K-means algorithm |
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