[R] LDA with previous PCA for dimensionality reduction
Christoph Lehmann
christoph.lehmann at gmx.ch
Wed Nov 24 11:16:57 CET 2004
Dear all, not really a R question but:
If I want to check for the classification accuracy of a LDA with
previous PCA for dimensionality reduction by means of the LOOCV method:
Is it ok to do the PCA on the WHOLE dataset ONCE and then run the LDA
with the CV option set to TRUE (runs LOOCV)
-- OR--
do I need
- to compute for each 'test-bag' (the n-1 observations) a PCA
(my.princomp.1),
- then run the LDA on the test-bag scores (-> my.lda.1)
- then compute the scores of the left-out-observation using
my.princomp.1 (-> my.scores.2)
- and only then use predict.lda(my.lda.1, my.scores.2) on the scores of
the left-out-observation
?
I read some articles, where they choose procedure 1, but I am not sure,
if this is really correct?
many thanks for a hint
Christoph
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