【摘要】 本文提出一种新的聚类方法。这一方法首先找出一个初始类,然后建立一个关于样本点和特征变化区间的二部图模型,并利用这一模型对初始类进行进一步的划分。重复这一步骤直到全部样本点被合理分类为止。这个方法可以利用关系数据库运算实现,而且不要求预先指定类数。对例子进行了试算并得到了合理的结果。更多还原

【Abstract】 In this paper,a new clustering merhod is presented. According to this method, an initial class is found first, then set up a model of bipa-rtite graph relevant to sample points and feature changing intervals, and divide the primary class further with the bipartite model.This procedure is repeated until one gets the reasonable classes for all points. This method can be implemented by the calculation of the relational data base, and it is not necessary to fix numbers of classes in advance.We have got a good result from trial calculation of an example for earthquake forecast.更多还原