Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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Dynamic Decision Tree for Data Mining

데이터마이닝을 위한 동적 결정나무

  • Choi, Byong-Su (Department of Multimedia Engineering, Hansung University) ;
  • Cha, Woon-Ock (Department of Multimedia Engineering, Hansung University)
  • 최병수 (한성대학교 멀티미디어공학과) ;
  • 차운옥 (한성대학교 멀티미디어공학과)
  • Received : 20090900
  • Accepted : 20091000
  • Published : 2009.11.30
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Abstract

Decision tree is a typical tool for data classification. This tool is implemented in DAVIS (Huh and Song, 2002). All the visualization tools and statistical clustering tools implemented in DAVIS can communicate with the decision tree. This paper presents methods to apply data visualization techniques to the decision tree using a real data set.

결정나무는 데이터마이닝에서 데이터를 분류하는 기법으로 가장 많이 사용되고 있으며, 데이터 탐색 소프트웨어 DAVIS에서는 동적 기능을 사용하여 데이터 시각화를 하는 것이 가능하다. 본 논문에서는 동적 데이터 분석의 기본 원리와 이를 결정나무에 적용하는 방법을 소개하고, 생성되는 동적 결정나무의 효율성과 유용성을 실제 데이터를 사용하여 분석한다.

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References

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