한국데이터정보과학회:학술대회논문집
- 한국데이터정보과학회 2004년도 춘계학술대회
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- Pages.39-50
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- 2004
CHAID Algorithm by Cube-based Proportional Sampling
- Park, Hee-Chang (Department of Statistics, Changwon National University) ;
- Cho, Kwang-Hyun (Department of Statistics, Changwon National University)
- 발행 : 2004.04.30
초록
The decision tree approach is most useful in classification problems and to divide the search space into rectangular regions. Decision tree algorithms are used extensively for data mining in many domains such as retail target marketing, fraud dection, data reduction and variable screening, category merging, etc. CHAID(Chi-square Automatic Interaction Detector) uses the chi-squired statistic to determine splitting and is an exploratory method used to study the relationship between a dependent variable and a series of predictor variables. In this paper we propose CHAID algorithm by cube-based proportional sampling and explore CHAID algorithm in view of accuracy and speed by the number of variables.