대한산업공학회지 (Journal of Korean Institute of Industrial Engineers)

  • 제40권4호
  • /
  • Pages.375-381
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  • 2014
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  • 1225-0988(pISSN)
  • /
  • 2234-6457(eISSN)
대한산업공학회 (Korean Institute of Industrial Engineers)
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의사결정나무 모델에서의 중요 룰 선택기법

Rule Selection Method in Decision Tree Models

  • 손지은 (고려대학교 산업경영공학과) ;
  • 김성범 (고려대학교 산업경영공학과)
  • Son, Jieun (School of Industrial Management Engineering, Korea University) ;
  • Kim, Seoung Bum (School of Industrial Management Engineering, Korea University)
  • 투고 : 2013.12.04
  • 심사 : 2014.04.29
  • 발행 : 2014.08.15
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초록

Data mining is a process of discovering useful patterns or information from large amount of data. Decision tree is one of the data mining algorithms that can be used for both classification and prediction and has been widely used for various applications because of its flexibility and interpretability. Decision trees for classification generally generate a number of rules that belong to one of the predefined category and some rules may belong to the same category. In this case, it is necessary to determine the significance of each rule so as to provide the priority of the rule with users. The purpose of this paper is to propose a rule selection method in classification tree models that accommodate the umber of observation, accuracy, and effectiveness in each rule. Our experiments demonstrate that the proposed method produce better performance compared to other existing rule selection methods.

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참고문헌

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