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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국자료분석학회 Journal of The Korean Data Analysis Society Journal of The Korean Data Analysis Society 제4권 제4호
- 발행연도
- 2002.1
- 수록면
- 361 - 372 (12page)
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초록· 키워드
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This article examines three biased methods used for predictive modelling: ridge regression, principal component regression and partial least squares regression. A Monte Carlo study is performed to compare the prediction ability of these methods along with ordinary least squares. 48 different situations are considered and the root mean squared error of prediction is computed by using leave-one-out cross-validation for the comparison. Performance of the four methods are compared in detail.
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