基于粗集和SVM的客户抵押贷款违约评估

redit risk is the primary source of risk to financial institutions. Support Vector Machine (SVM) is a new machine learning method based on the idea of VC dimension and Statistical Learning Theory (SLT). It is a good classifier to solve binary classification problem and the learning results possess stronger robustness. We use grid-search method adjusts these penalty parameters to achieve better generalization performances in our application. In this paper the attribute reduction of Rough Set has been applied as preprocessor so that we can delete redundant attributes，then default prediction model of the housing mortgage loan is established by using SVM.Classification performance is better than other classification algorithm.