Mining method of credit evaluation model based on gene expression programming
基于基因表达式编程的信用评估模型挖掘方法

A new mining method of credit evaluation model based on Gene Expression Programming(GEP),named GEP-CREDIT,was presented.The GEP-CREDIT model can extract relative attributions and fuse them automatically.Based on these attributions,GEP-CREDIT model can train and build the credit evaluation model.Experiments and performance analysis on Germany credit database were given.The results show that,compared with Nave Bayes algorithm,SVM algorithm,and KNN(K=17)algorithm,the prediction precision is increased by 3%,1.6% and 6.83% respectively by using GEP-CREDIT model.