A Hybrid Support Vector Machine Ensemble Model for Credit Scoring

@inproceedings{Ghodselahi2011AHS,
  title={A Hybrid Support Vector Machine Ensemble Model for Credit Scoring},
  author={Ahmad Ghodselahi},
  year={2011}
}
  • Ahmad Ghodselahi
  • Published 2011
Credit risk is the most challenging risk to which financial institution are exposed. Credit scoring is the main analytical technique for credit risk assessment. In this paper a hybrid model for credit scoring is designed which applies ensemble learning for credit granting decisions. The hybrid model combines clustering and classification techniques. Ten Support Vector Machine (SVM) classifiers are utilized as the members of ensemble model. Since even a small improvement in credit scoring… CONTINUE READING
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