Personal Credit Assessment Based on KPCA and SVM

Personal credit assessment is carried out by setting up a mathematical model to count, calculate and analyze the personal credit data. At present personal credit assessment has already became a kind of worldwide industry. In this paper we combine kernel principal component analysis and support vector machine to propose a new mathematical model based on KPCA and SVM. We extract personal credit data using KPCA, then use them to train SVM. Experiments show that the new method put forward in this paper is superior to other methods in assessing precision and assessing efficiency.