摘要
在传统层次聚类基础上,提出并实现了一种基于距离的增量式聚类算法,并应用于粮食智能决策支持系统中.算法在保持层次聚类优点的基础上,利用原有的聚类结果提高聚类速度,并可以根据用户需要在聚类精度和聚类速度两方面选取一个适当的平衡点,有效地提高聚类分析的效率.
In this paper an incremental distance cluster arithmetic based on traditional level cluster arithmetic is proposed and realized. It has been used in the Grain Enterprise Intelligent Decision-Support System, which holds the benefit of level cluster , makes use of old cluster result to increase the cluster speed and can control cluster quality and speed according to need of customers to efficiency of cluster analysis.
出处
《湖南工程学院学报（自然科学版）》
2005年第3期41-44,共4页
Journal of Hunan Institute of Engineering(Natural Science Edition)
基金
国家自然科学基金资助项目(60073039
60273080)
关键词
增量聚类
层次聚类
决策支持系统
数据挖掘
incremental cluster
level cluster
decision-support system
data mining
