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Credit Scoring studies are very important for any financial house. Both traditional statistical and modern data mining/machine learning tools have been evaluated in the credit scoring problem. But very few of the studies facilitate the comparison of majority of the commonly employed tools in single comprehensive study. All the tools such as LDA (Linear Discriminant Analysis), SVM (Support Vector Machines), Kernel density estimation, LR (Logistic Regression), GP(Genetic Programming), K neighborhood, which are available in SAS enterprise miner 6.2.
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