基于分类树和支持向量机的个人信用评估方法

Personal Credit Scoring Based on Classification Tree And Support Vector Machines

通过对分类树和支持向量机这两种方法在个人信用评估领域的适用性分析,提出了一种将分类树和支持向量机结合起来处理个人信用评估的新方法.用该方法处理含有混合数据的个人信用评估实例,结果表明,该方法有效地提高了整个模型的训练精度和测试精度.

Firstly, the paper analyzed the adaptation of the classification tree and support vector machine applied to personal credit scoring. It then set up a synthetic approach which combines the above two methods together for credit scoring. Finally it used this method to deal with an example of the personal credit scoring with mixed data, and the result shows the approach improves training precision and test precision of the whole model effectively.