关键词: 个人信用风险评估, 数据挖掘, 决策树, Choquet模糊积分, Sugeno模糊积分

Abstract:

In order to improve the level of assessment of the credit risk of commercial bank credit management system based on data mining, the model of multiple decision trees by Choquet fuzzy integral fusion (MTCFF) was applied to the system. The basic idea was to mine the classified customer data by decision tree, form the different decision trees and rules according to different pruning degree, and detect unclassified customer data by different decision tree rules, and then nonlinearly combine the results from multiple decision trees by Choquet fuzzy integral to get the best decision. Using the German of the UCI dataset, the experimental results show that fusion of Choquet fuzzy integral is superior to the single decision tree in terms of classification accuracy, and it is also superior to other linear fusion methods. Choquet fuzzy integral is superior to Sugeno fuzzy integral.

Key words: individual credit risk evaluation, data mining, decision tree, Choquet fuzzy integral, Sugeno fuzzy integral