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计算机系统应用英文版:2010,19(12):246-250
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Chameleon聚类算法的Weka实现
(1.重庆大学 计算机学院 重庆 400044;2.重庆大学 城市建设与环境工程学院 重庆400045)
Study of Chameleon Clustering Algorithm and Implementation in Weka
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Received:March 28, 2010    Revised:April 26, 2010
中文摘要: 为了克服Weka系统在聚类算法方面的不足,在Weka的开源环境下进行了二次开发,扩充了聚类算法。介绍了Chameleon算法的基本原理和构建步骤,给出算法的具体描述,并将Chameleon算法嵌入Weka平台,充分利用了其中的类和可视化功能。对实现的系统进行了实验和测试,并对嵌入的算法和原有聚类算法k-means进行了对比分析。实验结果表明,Chameleon算法可获得更好的聚类效果。
中文关键词: Chameleon  聚类分析  互连度  近似度  Weka
Abstract:To overcome the Weka’s weakness in clustering algorithms, the clustering algorithm was developed based on the Weka open source environment. An introduction is made on the basic principle and construction steps of the Chameleon algorithm which was described concretely and embedded into Weka platform whose inner class and visualization function were exploited adequately. The newly built Weka system was tested by comparing the embedded and the already existed K-means algorithm. The result shows that Chameleon algorithm acquires better clustering effect.
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基金项目:国家科技重大专项(2008ZX07315-001)
引用文本:
刘文凤,卿晓霞.Chameleon聚类算法的Weka实现.计算机系统应用,2010,19(12):246-250
.Study of Chameleon Clustering Algorithm and Implementation in Weka.COMPUTER SYSTEMS APPLICATIONS,2010,19(12):246-250