lda_from_pls_cv {plsVarSel}

Cross-validated 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. This use of cross-validation has limitations. Handle with care!

Usage

lda_from_pls_cv(model, X, y, ncomp, Y.add = NULL)

Arguments

model

pls model fitted with the pls package

X

predictors in the same format as in the pls model

y

vector of grouping labels

ncomp

maximum number of PLS components

Y.add

additional responses

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 = 8, data = mayonnaise, subset = train, 
            validation = "CV", segments = 40, segment.type = "consecutive")
with(mayonnaise, {
 classes <- lda_from_pls_cv(pls, NIR[train,], oil.type[train], 8)
 colSums(oil.type[train] == classes) # Number of correctly classified out of 120
})