| 一种基于k prototype的多层次聚类改进算法 |
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| 引用本文： | 李士进,朱跃龙,刘净.一种基于k prototype的多层次聚类改进算法[J].河海大学学报(自然科学版),2007,35(3):342-347. |
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| 作者姓名： | 李士进 朱跃龙 刘净 |
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| 作者单位： | 河海大学计算机及信息工程学院,江苏,南京,210098 |
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| 基金项目： | 引进国际先进农业科技计划(948计划)
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河海大学校科研和教改项目 |
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| 摘 要： | 针对k-prototype算法在处理复杂的数据集时,常出现一些纯度不高的簇,影响了聚类质量的问题,提出一种基于k-prototype的多层次聚类改进算法,利用属性自动选择的方法将一些纯度不高的簇进行再聚类,以提高聚类质量.以UCI标准测试数据集进行实验,实验结果表明,该改进算法能够明显提高混合型数据集的聚类质量,并且在数据约简方面有良好表现.
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| 关 键 词： | 聚类 混合数据 多层次聚类 k-prototype聚类 |
| 文章编号： | 1000-1980（2007）03-0342-06 |
| 修稿时间： | 2006-09-19 |
An improved multi-level clustering algorithm based on k-prototype |
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| LI Shi-jin,ZHU Yue-long,LIU Jing.An improved multi-level clustering algorithm based on k-prototype[J].Journal of Hohai University (Natural Sciences ),2007,35(3):342-347. |
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| Authors: | LI Shi-jin ZHU Yue-long LIU Jing |
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| Institution: | College of Computer and Information Engineering, Hohai University, Nanjing 210098, China |
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| Abstract: | When k-prototype algorithm was employed to process complex data sets, some clusters with low-purity always occurred.An improved multi-level clustering algorithm based on k-prototype was proposed to tackle the above problem.In order to improve the quality of clustering,re-clustering was performed on those clusters with low-purity through automatic selection of attributes.Experimental results on data set from UCI machine learning repository show that the present algorithm can improve the clustering quality evidently,and it is also suitable for data abstraction. |
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| Keywords: | clustering mixed data multi-level clustering k-prototype clustering |
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