I applied PLSDA on my data using 10 components and then assessed the performance using the perf () function with 5-fold cross validation repeated 10 times as a trial. The plot of performance is shown below.
I have a question that why the overall error rate and the BER differed so much, especially when they were measured by the max.dist? The results on overall error rate seem to indicate 10 to be the optimal number of component, while the BER from centroid.dist and mahanobis.dist seem to indicate 4. Which number should I choose for the number of component of my PLSDA model? Also can I set the distance parameter in the plsda () function?