摘要
信用卡公司是一个服务性的金融企业,如何提高在服务过程中的服务质量,改进服务方法,使公司的决策更为准确及时,是信用卡公司追求的一个目标。本文介绍了神经网络方法及数据挖掘技术在信用卡公司对用户评分中的应用,对比分析了几种个人信用评分模型建模方法的特点,建立了一种决策树-神经网络个人信用评分模型,并针对该模型提出了一种近邻聚类算法,该算法在信用评分应用中可以得到较理想的结果。
A credit company is an enterprise to offer services to customers, it is a target for credit companies how to improve the quality of services and how to enrich the ways of services, and how to make decision more correctly and just in time, This paper describes the requirement of the credit card company for data mining and neural network technology which apply for personal credit scoring. Contrasted and analyzed some of personal credit scoring model, and constructed a decision-neural network personal credit scoring model. At last, it gives a Vicinage-Extended Clustering algorithm, and analyzed its usability and utility.
出处
《微计算机信息》
北大核心
2006年第09X期229-231,共3页
Control & Automation
关键词
信用评分
神经网络
分类
聚类
决策树
Credit Scoring,Neural Network,Classification,Clustering,Decision Tree
