takes in predited weights and true labels and determines performance characterisitcs
1 2 | perf.sPLSDA(object, validation = c("Mfold", "loo"), M = 5, iter = 10,
threads = 4, progressBar = TRUE)
|
object |
sPLSDA model object |
M |
Number of folds in the cross-validation |
iter |
number of times to repeat the cross-validation |
threads |
number of cores to use to parrallel the CV |
progressBar |
display progress bar or not (TRUE/FALSE) |
valdation |
type of cross-validation; Mfold "Mfold" or LOOCV "loo" |
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