The KIPS Transactions:PartD (정보처리학회논문지D)

Korea Information Processing Society (한국정보처리학회)
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A Study of the Integration of Individual Classification Model in Data Mining for the Credit Evaluation

신용평가를 위한 데이터마이닝 분류모형의 통합모형에 관한 연구

  • 김갑식 (대구산업정보대학 인터넷비즈니스과)
  • Published : 2005.04.01
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Abstract

This study presents an integrated data mining model for the credit evaluation of the customers of a capital company. Based on customer information and financing processes in capital market, we derived individual models from multi-layered perceptrons(MLP), multivariate discrimination analysis(MDA), and decision tree. Further, the results from the existing models were compared with the results from the integrated model using genetic algorithm. The integrated model presented by this study turned out to be superior to the existing models. This study contributes not only to verifying the existing individual models but also to overcoming the limitations of the existing approaches.

본 연구는 금융기관에서의 고객신용평가를 위한 최적의 데이터마이닝 모형을 제안한다. 이를 위해 할부금융시장에서의 고객정보 및 할부진행 과정에 대한 세부 내역을 바탕으로 다계층 퍼셉트론(Multi-Layered Perceptrons:MLP)과 다변량 판별분석(Multivariate Discrimination Analysis : MDA), 그리고 의사결정나무(Decision Tree)를 적용하여 각각의 개별모형을 도출하고 이론 유전자 알고리즘을 이용하여 통합한 최종 모형을 구해 그 결과론 각 단일모형과 비교${\cdot}$분석하였다. 그 견과 유전자 알고리즘을 통해 결합한 통합모형의 성능이 가장 우수한 것으로 나타났다. 이에 본 연구는 기존에 진행되었던 개변모형에 대한 검증은 물론, 단순히 여러 개의 모형을 비교${\cdot}$분석하여 우월한 모형을 평가하는 기존 방법론 상의 한계를 극복하기 위해 각각의 개별모형을 유전자 알고리즘을 통해 통합모형으로 구축하는 하나의 방법론을 제시하였다는데 그 의의가 있다.

Keywords

References

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