摘要
数据挖掘是信息产业界近年来非常热门的研究方向,聚类分析是数据挖掘中的核心技术,而层次聚类算法是众多聚类算法中应用最为广泛的一种,但该方法经常会遇到合并或分裂点选择的问题,一旦一组对象被合并或者分裂,下一步的处理将在新生成的簇上进行,已做的处理不能被撤销,聚类之间也不能交换对象。若在某一步没有很好地选择合并或分裂,可能导致低质量的聚类结果。因此提出了一种改进的层次聚类算法——网状聚类算法,实验结果表明该算法具有更高的准确率。
Data mining is a very popular research direction in the IT industry recently,clustering analysis is the core technology of data mining,and hierarchical clustering algorithm is the most widely used one.But the method often encounter merging or split point selection problem.Once a set of objects is merged or split,the next processing will be performed on the newly created cluster,the processing has been done can not be undone,and the object can not be exchanged between the clusters.If a step does not choose to merge or split very well,that may lead to lower quality clustering results.The author presented an improved hierarchical clustering algorithm,called mesh clustering algorithm,and the experimental results show that the algorithm has a higher accuracy rate.
出处
《计算机科学》
CSCD
北大核心
2015年第S1期510-512,共3页
Computer Science
关键词
层次聚类
实验
网状聚类
Hierarchical clustering,Experiment,Mesh clustering
