Variable Selection for data reduction and discriminant anlaysis
There are some pointers to packages for variable selection in the task view for Chemometrics and Computational Physics at http://cran.r-project.org/web/views/ChemPhys.html
On Sun, 21 Sep 2008, Gareth Campbell wrote:
Hello all, I'm dealing with geochemical analyses of some rocks. If I use the full composition (31 elements or variables), I can get reasonable separation of my 6 sources. Then when I go onto do LDA with the 6 groups, I get excellent separation. I feel like I should be reducing the variables to thos that are providing the most discrimination between the groups as this is important information for me. I struggle to interpret the PCA plot in a way that helps me (due to the large number of elements). So I'm trying to do some sort of step-wise variable selection. I would love to hear from someone (possibly a geochemist or similar) who does this regularly to determine the best course of action in R to do this. Thanks very much -- Gareth Campbell PhD Candidate The University of Auckland P +649 815 3670 M +6421 256 3511 E gareth.campbell at esr.cri.nz gcam032 at gmail.com [[alternative HTML version deleted]]
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