期刊
DECISION SUPPORT SYSTEMS
卷 44, 期 4, 页码 1016-1030出版社
ELSEVIER
DOI: 10.1016/j.dss.2007.12.001
关键词
data mining; classification; mathematical programming; multiple criteria decision making; multi-criteria convex quadric programming (MCQP)
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 Multicriteria Convex Quadric Programming (MCQP) model is highly efficient (computing time complexity O(n(1.5-2))) and scalable to massive problems (size of O(10(9))) 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. (c) 2007 Elsevier B.V. All rights reserved.
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