基于最佳分裂点的客户分类变化挖掘方法  

Change Mining Method of Customer Classification Based on the Best Splitting Point

作　　者：朱慧云[1] 陈森发[1] 曹杰[2] 张丽杰[2] 

机构地区：[1]东南大学经济管理学院,江苏南京210096 [2]南京信息工程大学经济管理学院,江苏南京210044

出　　处：《信息与控制》2012年第6期668-674,共7页Information and Control

基　　金：国家自然科学青年基金资助项目(60804047)

摘　　要：针对当前客户分类变化挖掘方法的不足,提出了一种基于最佳分裂点的客户分类变化挖掘方法.根据分类规则的特点,调整了变化类型的定义,并在定义的基础上扩充了变化度量和变化程度测量的方法.为了不影响决策树中每个节点的最佳分裂点的寻找,在变化度量中提出了一个量化属性的属性值匹配度量方法.实证分析的结果表明,所提方法可以有效地识别2个不同时期的数据集的客户分类变化模式.Based on the best splitting point, a change mining methods of customer classification is proposed, which conquers the shortcomings of the existing change mining methods. In terms of the features of classification rule, the new definition of change types is proposed, based on which the metric of change and degree of change measures are redefined. In order not to affect the search for the best splitting point of each node in the decision tree, an extended measure of value match of quantitative attribute is designed to analyze the change measures between patterns. Empirical evaluation shows that the methodology is very effective to recognize the change of customer classification from two different datasets.

关 键 词：数据挖掘 变化分析 变化挖掘 决策树 零售业 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]