Alleviating the problem of financing difficulty and high cost is the key to realizing the sustainable development of family farms and ranches,and constructing a credit rating system for family farms and ranches is the basis to solving the problem.Aiming at the problems of multiple sample data indicators,complex noise,non-linearity and even high-dimensionality in the credit risk assessment of family farms and ranches,500 family farms and ranches in 12 cities in Inner Mongolia Autonomous Region are taken as the credit evaluation objects.The XGBoost algorithm,random forest algorithm and fuzzy integral model are combined to construct an improved random forest-fuzzy integral model,which is used to provide credit ratings to family farms and ranches.The analysis results show that the accuracy,precision,recall and Fl score of the improved random forest-fuzzy integral model are higher for the credit rating of family farms and ranches.
XGBoostrandom forestfuzzy integralcredit ratingfamily farms and ranches
维普
万方数据
