提出一种新的基于随机抽样的网格聚类算法。
A new grid clustering method based on the random sampling is proposed in the dissertation.
一种新的抽样方法是把数据挖掘技术中的分类、聚类及离群点挖掘等应用到审计风险管理中去。
A new sampling method is proposed, which USES the latest technologies of database. It applies classification rule mining, clustering rule and outlier mining to the management of Audit Risk.
随后，在分析BIRCH算法不足的基础上，提出了一种基于抽样的聚类算法。
Next, based on the analysis of deficiency of BIRCH algorithm, we propose a new clustering algorithm based on sampling.
一种新的抽样方法是把数据挖掘技术中的分类、聚类及离群点挖掘等应用到审计风险管理中去。
It applies classification rule mining, clustering rule and outlier mining to the management of Audit Risk.
根据抽样指标的观测值，选择某种度量样品之间的指标相似度的度量方法，并以此为聚类依据；
According to the observations of a sample of indicators, a measure of samples to choose between the targets of the similarity measurement method and use it as the basis for clustering;
根据抽样指标的观测值，选择某种度量样品之间的指标相似度的度量方法，并以此为聚类依据；
According to the observations of a sample of indicators, a measure of samples to choose between the targets of the similarity measurement method and use it as the basis for clustering;
应用推荐