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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