lda_from_pls: LDA/QDA classification from PLS model

In khliland/plsVarSel: Variable Selection in Partial Least Squares

LDA/QDA classification from PLS model

Description

For each number of components LDA/QDA models are created from the scores of the supplied PLS model and classifications are performed.

Usage

lda_from_pls(model, grouping, newdata, ncomp)

Arguments

model	pls model fitted with the pls package
grouping	vector of grouping labels
newdata	predictors in the same format as in the pls model
ncomp	maximum number of PLS components

Value

matrix of classifications

See Also

VIP (SR/sMC/LW/RC), filterPLSR, shaving, stpls, truncation, bve_pls, ga_pls, ipw_pls, mcuve_pls, rep_pls, spa_pls, lda_from_pls, lda_from_pls_cv, setDA.

Examples

data(mayonnaise, package = "pls")
mayonnaise <- within(mayonnaise, {dummy <- model.matrix(~y-1,data.frame(y=factor(oil.type)))})
pls <- plsr(dummy ~ NIR, ncomp = 10, data = mayonnaise, subset = train)
with(mayonnaise, {
 classes <- lda_from_pls(pls, oil.type[train], NIR[!train,], 10)
 colSums(oil.type[!train] == classes) # Number of correctly classified out of 42
})

khliland/plsVarSel documentation built on June 14, 2025, 8:57 a.m.