Journal of the Korean Data and Information Science Society

The Korean Data and Information Science Society (한국데이터정보과학회)
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Classification for intraclass correlation pattern by principal component analysis

  • Chung, Hie-Choon (Department of Healthcare Management, Gwangju University) ;
  • Han, Chien-Pai (Department of mathematics, University of Texas at Arlington)
  • Received : 2010.04.02
  • Accepted : 2010.05.23
  • Published : 2010.05.31
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Abstract

In discriminant analysis, we consider an intraclass correlation pattern by principal component analysis. We assume that the two populations are equally likely and the costs of misclassification are equal. In this situation, we consider two procedures, i.e., the test and proportion procedures, for selecting the principal components in classifica-tion. We compare the regular classification method and the proposed two procedures. We consider two methods for estimating error rate, i.e., the leave-one-out method and the bootstrap method.

Keywords

References

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