支持向量机在银行贷款客户分类中的应用研究

随着客户关系管理系统的不断发展和应用，使用先进的算法进行客户分析变得越来越重要。尤其是象银行这种以客 户为导向的行业，客户分析是十分必要的。当前，支持向量机方法作为一种统计学习理论的分类方法已经发展的比较成熟而 且成功应用到了很多领域。文章解决的主要问题是对银行的客户数据根据其属性对客户进行分类，为银行的客户关系管理系 统提供一种可靠的分类方法。文中主要介绍了银行的客户分类学习的过程和结果，如，客户数据清洗，数据预处理，SVM 进 行数据分类，多类分类处理，客户属性选择等问题。
关键词：客户关系管理；支持向量机；数据挖掘；客户分类;属性选择
Abstract：With the development and application of the customer relationship management, it become more important to analyze the customer using advanced data mining algorithms. And recently Support Vector Machine, a statistical theory method, has been successfully developed and applied to many areas. Support Vector Machine is chose as the data mining method in the analytical Customer Relationship Management system. The main problems are the customer classification, potential customers finding based on bank credit customer data which is mainly about the properties of the customers. The customer data preprocess and data
classification process by using Support Vector Machines, and some results are presented in detail.
Keywords: CRM (customer relationship management); SVM (support vector machine); DM (data mining); customer classification; attribute selection