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From: saswss@hotellng.unx.sas.com (Warren Sarle)
Subject: Re: A question about PCA
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Date: Wed, 5 Jul 1995 23:43:50 GMT
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In article <3tep9n$5a3@bmsr14.usc.edu>, saglam@bmsr14.usc.edu (Mehmet Akif Saglam) writes:
|> Does anybody know if principal component analysis can be
|> used for supervised learning ?

Principal component analysis cannot be used directly for supervised
learning. However, it is often used for feature extraction as a
preliminary to supervised learning. There is also a supervised analog
of principal component analysis called "principal components of
instrumental variables" or "maximum redundancy analysis"; see:

   Fortier, J.J. (1966), "Simultaneous Linear Prediction,"
   Psychometrika, 31, 369-381.

   Rao, C.R. (1964), "The Use and Interpretation of Principal
   Component Analysis in Applied Research," Sankya A, 26, 329-358.

   van den Wollenberg, A.L. (1977), "Redundancy Analysis--An
   Alternative to Canonical Correlation Analysis," Psychometrika,
   42, 207-219.

-- 

Warren S. Sarle       SAS Institute Inc.   The opinions expressed here
saswss@unx.sas.com    SAS Campus Drive     are mine and not necessarily
(919) 677-8000        Cary, NC 27513, USA  those of SAS Institute.
