takes in predited weights and true labels and determines performance characterisitcs
1 2 3 4 5 | tuned.sPLSDA(X.train, Y.train, keepXgrid, ncomp, X.test = X.test,
Y.test = Y.test, filter = filter, topranked = topranked,
validation = validation, M = M, iter = iter, threads = threads,
progressBar = progressBar, optimal = optimal,
errorMethod = errorMethod)
|
keepXgrid |
sequence of integers (# of variables to select per component) |
ncomp |
number of components |
M |
Number of folds in the cross-validation |
X |
nxp dataset |
Y |
vector of phenotype labels with names(Y) == rownames(X) |
validatoin |
"Mfold" or "loo" |
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