In order to improve the performance of support vector machine (SVM) applications in the field of credit risk evaluation, an adaptive Lq SVM model with Gauss kernel (ALqG-SVM) is proposed to evaluate credit risks. The ...In order to improve the performance of support vector machine (SVM) applications in the field of credit risk evaluation, an adaptive Lq SVM model with Gauss kernel (ALqG-SVM) is proposed to evaluate credit risks. The non-adaptive penalty of the object function is extended to (0, 2] to increase classification accuracy. To further improve the generalization performance of the proposed model, the Gauss kernel is introduced, thus the non-linear classification problem can be linearly separated in higher dimensional feature space. Two UCI credit datasets and a real life credit dataset from a US major commercial bank are used to check the efficiency of this model. Compared with other popular methods, satisfactory results are obtained through a novel method in the area of credit risk evaluation. So the new model is an excellent choice.展开更多
In this article, the risk process perturbed by diffusion under interest force is considered, the continuity and twice continuous differentiability for Фδ（u,w） are discussed,the Feller expression and the integro-di...In this article, the risk process perturbed by diffusion under interest force is considered, the continuity and twice continuous differentiability for Фδ（u,w） are discussed,the Feller expression and the integro-differential equation satisfied by Фδ （u ,w） are derived. Finally, the decomposition of Фδ（u,w） is discussed, and some properties of each decomposed part of Фδ（u,w） are obtained. The results can be reduced to some ones in Gerber and Landry＇s,Tsai and Willmot＇s, and Wang＇s works by letting parameter δ and （or） a be zero.展开更多
基金The National Natural Science Foundation of China (No.70531040)the National Basic Research Program of China (973 Program) (No.2004CB720103)
文摘In order to improve the performance of support vector machine (SVM) applications in the field of credit risk evaluation, an adaptive Lq SVM model with Gauss kernel (ALqG-SVM) is proposed to evaluate credit risks. The non-adaptive penalty of the object function is extended to (0, 2] to increase classification accuracy. To further improve the generalization performance of the proposed model, the Gauss kernel is introduced, thus the non-linear classification problem can be linearly separated in higher dimensional feature space. Two UCI credit datasets and a real life credit dataset from a US major commercial bank are used to check the efficiency of this model. Compared with other popular methods, satisfactory results are obtained through a novel method in the area of credit risk evaluation. So the new model is an excellent choice.
文摘In this article, the risk process perturbed by diffusion under interest force is considered, the continuity and twice continuous differentiability for Фδ（u,w） are discussed,the Feller expression and the integro-differential equation satisfied by Фδ （u ,w） are derived. Finally, the decomposition of Фδ（u,w） is discussed, and some properties of each decomposed part of Фδ（u,w） are obtained. The results can be reduced to some ones in Gerber and Landry＇s,Tsai and Willmot＇s, and Wang＇s works by letting parameter δ and （or） a be zero.
