On 12.10.2023 16:25, Fernando Archuby wrote:
Hi.
I have successfully performed the discriminant analysis with the lda
function, I can classify new individuals with the predict function, but I
cannot figure out how the lda results translate into the classification
decision. That is, I don't realize how the classification equation for new
individuals is constructed from the lda output. I want to understand it but
also, I need to communicate it and provide a mechanism for other colleagues
to make classifications with their data.
Thank you very much,
Fernando
Do you want to know the principles of the theory behind LDA? That is
available in lots of textbooks.
Do you want the implementation detials of MASS::lda()?
That is hard. It is based (but does not follow in all details) on a
paper by Nils Hjort from Norway.
A former student of mine, Swetlana Herbrandt, has analysed and reverse
engineered the code and wrote down the theory in a German thesis. The
implementation uses some nice tricks to get numerically rather stable
results that are typically not mentioned in any textbook.
Do you really want to do prediction with LDA?
I typically look at classificatuion performance of LDA as a reference to
compare better and more modern techniques with.
I think you should ask some trained local statistician for advise on
both, the LDA theory and for prediction in general.
Best,
Uwe Ligges
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