Description Usage Arguments Value Examples
This function evaluates a single fitted model and returns the predicted group memberships of new data.
1 | predictNewClasses(modelFit, method, orig.data, newdata, param = NULL)
|
modelFit |
The fitted model being evaluated |
method |
String of the model to be evaluated |
orig.data |
The orginal data before subsetting training sets. Required to have the 'observed' group membership |
newdata |
The testing data to predict group membership |
param |
Optional alternate parameters being fit to the model |
Returns a list of predicted group membership
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 | 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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