Trains a Meka classifier on an incoming training dataset (from a container) and then evaluates it on the test set (also from a container).
The classifier setup being used in the evaluation is a callable 'Classifier' actor.

Additional information

Flow input/output:
- input: adams.flow.container.WekaTrainTestSetContainer
- output: adams.flow.container.MekaResultContainer

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
- adams.flow.container.MekaResultContainer:
   - Result: result container; meka.core.Result
   - Model: model object; java.lang.Object