I need some information to clarify some concept about PLS, LDA. LDA is able to decompose the independent variable to maximize the classes separation. the approach used is to develop a PCA on the product between the in-class covariance matrix and between-class covariance matrix. on the latent variables identified is applied a Bayesian algorithm to develop a classification model.

PLS has a similar ability. PLS develop a PCA on the independent variables and in parallel with the dependent ones. and then? i don't understand the process.

Could anyone to help me to confirm my LDA concepts and to understnd the PLS process? Thank you!



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