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数据挖掘中聚类算法比较研究 被引量:12

Comparison of Clustering Methods in Data Mining
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摘要 聚类算法是数据挖掘中的核心技术 ,虽然聚类算法已被广泛深入的研究 ,但其应用在数据挖掘领域时间不长 ,其间产生了许多不同的适用于数据挖掘的聚类算法 ,但这些算法仅适用于特定的问题及用户 .为了更好的使用这些算法 ,综合提出了评价聚类算法好坏的 5个标准 ,基于这 5个标准 ,对数据挖掘中近几年提出的常用聚类方法作了比较分析 ,以利于人们更容易。 Clustering method is the core technology in data mining.Clustering method has been studied very deeply,but the time it is used in the field of data mining is not very long.During which occurred many different clustering methods that suit data mining,however these methods are only suited to special problems and users.In order to use these methods better,the paper puts forwad five standards according to which we can evaluate these clustering methods.We compared and analyzed these clustering methods on the basis of these standards to facilitate finding a clustering mothod that suits a particular problem.
出处 《鞍山钢铁学院学报》 2001年第5期364-367,371,共5页 Journal of Anshan Institute of Iron and Steel Technology
关键词 聚类算法 数据挖掘 聚类方法 快速 用户 领域 使用 核心技术 问题 适用 data mining clustering method database
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参考文献9

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