摘要
金融机构对于客户的挖掘和分类有利于挖掘潜在客户和做出适当的营销决策。将决策树、逻辑斯蒂回归和贝氏机率分类算法用于挖掘购买股票、美金和期货的客户,同时用其分析被访者对不同金融产品的交叉购买行为,为金融机构的交叉营销提供依据。
It' s benefitting to financial institutions by making appropriate marketing decisions and mining the potential customers through mining and classification of their customers. This article applies "Decision Tree, Logistic regression and Bayesian probability classification algorithm" in mining the customers buying stocks, U. S. Dollars and Futures, Meanwhile, it can also be used to analyze customers' cross-purchasing behavior on different financial products to help financial organizations'cross- marketing activities.
出处
《统计与信息论坛》
CSSCI
2008年第9期85-89,共5页
Journal of Statistics and Information
基金
国家教育部社科研究规划项目《数据挖掘中关联规则的统计及应用》(06JA910003)
关键词
数据挖掘
决策树
聚类分析
data mining
decision tree
cluster analysis