Artificial Intelligence White Papers
Credit Scoring With a Data Mining Approach Based on Support Vector Machines
Overview The credit card industry has been growing rapidly recently, and thus huge numbers of consumers' credit data are collected by the credit department of the bank. The credit scoring manager often evaluates the consumer's credit with intuitive experience. However, with the support of the credit classification model, the manager can accurately evaluate the applicant's credit score. Support Vector Machine (SVM) classification is currently an active research area and successfully solves classification problems in many domains. This study used three strategies to construct the hybrid SVM-based credit scoring models to evaluate the applicant's credit score from the applicant's input features. Two credit datasets in UCI database are selected as the experimental data to demonstrate the accuracy of the SVM classifier.
| Publisher | Reed Elsevier | File Format | |
|---|---|---|---|
| Date Published | March 2007 | ||
| Format | White Papers | ||
| Topics | |||
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