摘要
在决策树理论的指导下,通过信息增益的应用和公式的构造获取属性重要程度评价值,结合决策树挖掘得到个人住房贷款风险评估模型。经过对该模型进行测试和评价,得出它们预测准确率较高的结论,实现了能够从真正意义上帮助银行信贷人员进行信贷分析并为信贷决策提供支持的模型。同时,该方法对其它评价模型的构造也有一定借鉴意义。
Based on the theories of decision tree, this paper gets the importance assessment value among attributes through applying information gain and constructing formula. Combined with decision tree mining, this paper gets credit risk assessment for individual housing loan, which has highly predictive accuracy when it has been tested and evaluated. This model can be used to help employees of banks to analyze housing loan and can help loan department to make correct credit decision. Meanwhile, the methods using in this paper can be referred to construct other assessment models.
出处
《计算机工程》
EI
CAS
CSCD
北大核心
2006年第13期263-265,271,共4页
Computer Engineering
关键词
数据挖掘
决策树
个人住房贷款
信用风险评估
Data mining
Decision tree
Individual housing loan
Credit risk assessment
