This case study will use the exact same methodology as the sPLS-DA SRBCT Case Study. However, prior to model construction, the class labels (srbct$class) will be randomly permuted. The proportions of each class will be maintained, but the instances they are associated with will be different. This is done to exemplify a case where the distinction between the provided classes is minimal and/or the data are quite noisy.
The R script used for all the analysis in this case study is available here.
Note that seed is not set in this script, so re-running the code will result in slightly different outputs (i.e. values and plots) from those shown here.