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- W206508622 abstract "A projection method for multivariate classification problems is presented, which is based on partial least squares in latent variables (PLS). PLS models the dependency between two multivariate blocks X and Y. For a pattern recognition problem we use a dummy matrix Y which describes the class-membership of the training-set objects. The multivariate characterization of the objects forms the X block. The PLS model describes the X-block with a principal component (PC) like model, where class separation is enhanced. The significance of the class separation is tested by cross-validation. Plotting the score vectors of the PLS model gives a PLS discriminant plot." @default.
- W206508622 created "2016-06-24" @default.
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- W206508622 date "1986-01-01" @default.
- W206508622 modified "2023-10-17" @default.
- W206508622 title "PLS DISCRIMINANT PLOTS" @default.
- W206508622 cites W2166446427 @default.
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- W206508622 doi "https://doi.org/10.1016/b978-0-444-87877-9.50042-x" @default.
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