Nothing
dat.discr <- create.discr.matrix(
create.corr.matrix(
create.random.matrix(nvar = 50,
nsamp = 100,
st.dev = 1,
perturb = 0.2)),
D = 10
)
vars <- dat.discr$discr.mat
groups <- dat.discr$classes
fits <- fs.stability(vars,
groups,
method = c("plsda", "rf"),
f = 10,
k = 3,
k.folds = 10,
verbose = 'none')
newdata <- create.discr.matrix(
create.corr.matrix(
create.random.matrix(nvar = 50,
nsamp = 100,
st.dev = 1,
perturb = 0.2)),
D = 10
)$discr.mat
orig.df <- data.frame(vars, groups)
# see what the PLSDA predicts for the new data
# NOTE, newdata does not require a .classes column
predictNewClasses(fits, "plsda", orig.df, newdata)
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