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Orthogonal support vector machine for credit scoring
2013
Engineering applications of artificial intelligence
The most commonly used techniques for credit scoring is logistic regression, and more recent research has proposed that the support vector machine is a more effective method. However, both logistic regression and support vector machine suffers from curse of dimension. In this paper, we introduce a new way to address this problem which is defined as orthogonal dimension reduction. We discuss the related properties of this method in detail and test it against other common statistical
doi:10.1016/j.engappai.2012.10.005
fatcat:2ftey756lfdw5jrtlrsllpreii