anchor.diff:      
   ## Cross validation
   
  -### Cross validation tutorial
  -
   This is a brief introduction to running an experiment that has a cross validation part. The most important things to learn in this example is, how to set a parameter space dimension which is created dynamically via a nested `BatchTask` and how to use a `FoldDimensionBundle`.
   
  -#### Basic tasks
  +### Basic setup
   
   Assume you have these tasks:
   
  
positive.code:    * *line 20-22*: add the sub-tasks that perform the cross-validation.
     * *line 24-27*: configure the overall batchTask that runs the preprocessing and the cross-validation.
  
  #### Reader 
  
  The following snipped illustrates how to use the _trainingSet_ parameter `files_training_` and `filesRoot` to configure the DKPro Core ASL `XmiReader` component.
  
  
negative.code:    * `crossValidationTask`: this task runs the `featureExtractionTask`, the `trainingTask` and the `validationTask`
     * `batchTask` (modified): this tasks now runs the `preprocessingTask` and the `crossValidationTask`.
  
  ### Cross-validation task
  
  Now, instead of statically setting up the parameter space for the `crossValidationTask`, we set it up dynamically by overriding the `execute()` method. In the following example, we assume that the `preprocessingTask` has produced some `XMI` data, which is the data on which we want to perform the cross-validation. The `featureExtractionTask` requires two parameters, `filesRoot` (the base directory of the data) and `files_training` (the data in the _trainingSet_). The `validationTask`also requires `filesRoot` and it needs `files_validation` (the _testSet_ ) to evaluate the classifier.
  
  