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A credit scoring model of a capital company's customers using genetic algorithm based ntegration of multiple classifiers

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2005, 10(6), pp.279-286
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science

김갑식 1

1경북전략산업기획단 정책기획실 책임연구원

Candidate

ABSTRACT

The objective of this study is to suggest a credit scoring model of a capital company's customers by integration of multiple classifiers using genetic algorithm. For this purpose, an integrated model is derived in two phases. In first phase, three types of classifiers - MLP (Multi-Layered Perceptron), RBF (Radial Basis Function) and linear models - are trained, in which each type has three ones respectively so htat we have nine classifiers totally. In second phase, genetic algorithm is applied twice for integration of classifiers. That is, after htree models are derived from each group, a final one is from these three, In result, our suggested model shows a superior accuracy to any single ones.

Citation status

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