Application of a Prediction Model Based on Clustering Balance Algorithm in Consumer Credit Default Prediction
In order to improve the prediction accuracy of current consumer credit default predic-tion models,a new type of consumer credit default prediction model will be constructed based on cluste-ring balance algorithm.In the performance comparison experiment of the clustering balance algorithm,it is found that the Mean absolute error of the algorithm is 0.00095,which is significantly lower than the Mean absolute error of the convergence of the other two algorithms.Subsequently,performance a-nalysis was conducted on the credit default prediction model,and the results showed that the prediction accuracy of the consumer credit default prediction model proposed in the study was 92.4％,far superior to similar prediction models.The above results indicate that the prediction accuracy of the consumer credit default prediction model proposed in the study is superior to traditional prediction models,and has practical value.
万方数据
维普
