군집분석 기법과 단계별 회귀모델을 결합한 예측 방법

A Prediction Method Combining Clustering Method and Stepwise Regression

  • 정일교 (포항공과대학교 산업공학과) ;
  • 전치혁 (포항공과대학교 산업공학과)
  • Chong Il-gyo (Division of Mechanical and Industrial Engineering, POSTECH) ;
  • Jun Chi-Hyuck (Division of Mechanical and Industrial Engineering, POSTECH)
  • 발행 : 2002.05.01

초록

A regression model is used in predicting the response variable given predictor variables However, in case of large number of predictor variables, a regression model has some problems such as multicollinearity, interpretation of the functional relationship between the response and predictors and prediction accuracy. A clustering method and stepwise regression could be used to reduce the amount of data by grouping predictors having similar properties and by selecting the subset of predictors. respectively. This paper proposes a prediction method combining clustering method and stepwise regression. The proposed method fits a global model and local models and predicts responses given new observations by using both models. The paper also compares the performance of proposed method with stepwise regression via a real data of ample obtained in a steel process.

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