Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
553943 | Decision Support Systems | 2008 | 15 Pages |
Abstract
Speed and scalability are two essential issues in data mining and knowledge discovery. This paper proposed a mathematical programming model that addresses these two issues and applied the model to Credit Classification Problems. The proposed Multi-criteria Convex Quadric Programming (MCQP) model is highly efficient (computing time complexity O(n1.5–2)) and scalable to massive problems (size of O(109)) because it only needs to solve linear equations to find the global optimal solution. Kernel functions were introduced to the model to solve nonlinear problems. In addition, the theoretical relationship between the proposed MCQP model and SVM was discussed.
Related Topics
Physical Sciences and Engineering
Computer Science
Information Systems
Authors
Yi Peng, Gang Kou, Yong Shi, Zhengxin Chen,