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A Study on Exploration of the Recommended Model of Decision Tree to Predict a Hard-to-Measure Mesurement in Anthropometric Survey

인체측정조사에서 측정곤란부위 예측을 위한 의사결정나무 추천 모형 탐지에 관한 연구

Choi, J.H.;Kim, S.K.
최종후;김선경

  • Published : 2009.10.31

Abstract

This study aims to explore a recommended model of decision tree to predict a hard-to-measure measurement in anthropometric survey. We carry out an experiment on cross validation study to obtain a recommened model of decision tree. We use three split rules of decision tree, those are CHAID, Exhaustive CHAID, and CART. CART result is the best one in real world data.

Keywords

Decision tree;k-fold cross validation;CHAID;exhaustive CHAID;CART

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