Showing content from https://cran.r-project.org/web/packages/sitar/../rmarkdown/../TPLSr/vignettes/TPLS_example2.R below:
## ---- include = FALSE--------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----setup-------------------------------------------------------------------- library(TPLSr) attach(TPLSdat) ## ----------------------------------------------------------------------------- ACCstorage <- rep(NA, 3) for (i in 1:3) { # primary cross-validation fold test = subj==i; train = !test # perform nested cross-validation within training data cvmdl = TPLS_cv(X[train,],Y[train],subj[train]) cvstats = evalTuningParam(cvmdl,"Pearson",X[train,],Y[train],1:25,seq(0,1,0.05),run[train]) # fit T-PLS model using all training data based on best tuning parameter mdl = TPLS(X[train,],Y[train]) # predict the testing subject score = TPLSpredict(mdl,cvstats$compval_best,cvstats$threshval_best,X[test,]) prediction = 1*(score > 0.5) # assess performance of prediction ACCstorage[i] = mean(prediction==Y[test]) } mean(ACCstorage) # out-of-sample CV performance
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