한국데이터정보과학회:학술대회논문집
- 한국데이터정보과학회 2003년도 추계학술대회
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- Pages.215-228
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- 2003
Exploration of CHAID Algorithm by Sampling Proportion
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Park, Hee-Chang
(Department of Statistics, Changwon National University) ;
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Cho, Kwang-Hyun
(Department of Statistics, Changwon National University)
- 발행 : 2003.10.30
초록
Decision tree algorithms are used extensively for data mining in many domains such as retail target marketing, fraud dection, data reduction and variable screening, interaction effect identification, category merging and discretizing continuous variable, etc. CHAID(Chi-square Automatic Interaction Detector), is an exploratory method used to study the relationship between a dependent variable and a series of predictor variables. CHAID modeling selects a set of predictors and their interactions that optimally predict the dependent measure. In this paper we explore CHAID algorithm in view of accuracy and speed by sampling proportion.