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The jack-knife with a stepwise discriminant algorithm-a warning to BMDP usesr

 

作者: A. P. White,   W. Z. Liu,  

 

期刊: Journal of Applied Statistics  (Taylor Available online 1993)
卷期: Volume 20, issue 1  

页码: 187-190

 

ISSN:0266-4763

 

年代: 1993

 

DOI:10.1080/02664769300000015

 

出版商: Carfax Publishing Company

 

数据来源: Taylor

 

摘要:

Program 7M in the BMDP statistical package carries out Fisher's linear discriminant analysis and offers a number of options including stepwise variable selection and jack-knife cross-validation. If these two options are used in combination, then a difficulty arises. A Monte Carlo demonstration was performed to demonstrate the problem. The results showed that the classification performance of the stepwise technique under jack-knife appeared to improve when pure noise variables were added to the data set. After studying the manual, it was hypothesized that this phenomenon was due to the stepwise variable selection phase of the procedure being conducted before the jack-knife, rather than being subject to it. This was verified by a second Monte Carlo experiment which compared the jack-knife in BMDP with a complete jack-knife, in which the variable selection phase of the procedure was also subject to the jack-knife.

 

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