Generates train/test pairs like during a cross-validation run. It is possible to generate pairs for leave-one-out cross-validation (LOOCV) as well.
It is essential that a class attribute is set. In case of a nominal class attribute, the data gets stratified automatically.
Each of the pairs gets forwarded as a container. The training set can be accessed in the container with 'Train' and the test set with 'Test'.

Additional information

Flow input/output:
- input: weka.core.Instances
- output: adams.flow.container.WekaTrainTestSetContainer

Container information:
- adams.flow.container.WekaTrainTestSetContainer:
   - Train: training set; weka.core.Instances
   - Test: test set; weka.core.Instances
   - Seed: seed value; java.lang.Long
   - FoldNumber: current fold (1-based); java.lang.Integer
   - FoldCount: total number of folds; java.lang.Integer
   - Train original indices: original indices (0-based, train); array of int
   - Test original indices: original indices (0-based, test); array of int