I have a metabolomics dataset with 2 observations from each participant, under different conditions. I used splsda() to perform sPLS-DA and had trouble getting the model to converge, so I used the options near.zero.var=TRUE and had to set the tolerance to 0.2. When I use perf() with option AUC=TRUE, I get the error mesage:
Error in cut.default(cases, thresholds) : ‘breaks’ are not unique
If I use AUC=FALSE, then perf() completes without errors. However, I want to report the AUC.
When I stratify the observations by condition, so that each participant has only 1 observation, there is no problem with the AUC. So although the sample size is relatively small (N=21), I don’t think that’s the issue.
Many thanks for any assistance.