基于密度聚类分析的相关算法研究

王桂芝

【期刊名称】《电脑知识与技术》

【年(卷),期】2013(000)030

【摘要】Cluster analysis is an important method of data mining. This paper describes the basic concepts of the density-based clustering analysis and the ideas of classic algorithms, and a new clustering algorithm based on boundary objects is proposed. The algorithm first classify the boundary objects, and form each cluster boundary curves, and then cluster the other object using the method of the sum of the angle. As the next step of boundary detection algorithm, the new algorithm ensures the integrity of da-ta processing, and provides a new idea for cluster analysis.%聚类分析是数据挖掘的重要方法。该文阐述了基于密度聚类分析的基本概念及其经典的算法思想，并提出了一种基于边界对象进行聚类的新算法。该算法首先对边界对象分类，形成各个聚类的边界曲线，然后采用夹角和法对其它对象进行聚类。作为聚类边界检测算法的后续步骤，新算法保证了数据处理的完整性，为聚类分析方法提供了新思路。

【总页数】3页(6714-6716)

【关键词】聚类;ε-邻域;核心对象;聚类边界;夹角和

【作者】王桂芝

【作者单位】河南牧业经济学院计算机应用系，河南郑州450044

【正文语种】中文