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I'm trying to understand what LDA exactly does when used as a classifier, i've understood how the dimensionality reduction works and i've understood that the classification task is carried out with the application of Bayes' theorem, but i still can't figure out if LDA executes both operation when used as a classification algorithm.

It's correct to say that LDA as a classifier executes by itself dimensionality reduction and then applies Bayes' theorem for classification?

If that makes any difference, i've used LDA in Python from the sklearn library.

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  • $\begingroup$ What do you mean by "both operation"? What does "executes by itself" mean? Are you distinguishing between what is done at training time vs what is done at test time? $\endgroup$
    – D.W.
    Mar 1 '21 at 17:35
  • $\begingroup$ Sorry, i will try to better explain myself; i was wondering exactly what happens in the training phase, in particular if dimensionality reduction is performed even when the alghoritm is used for classification. $\endgroup$
    – francesco
    Mar 1 '21 at 20:52

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