Mandatory Parameters

• readers (DimensionBundle)
  • readerTrain (name of the reader for the training data)
  • readerTrainParams (further parameters for the training data reader)
  • readerTest (name of the reader for the test data) not necessary for Crossvalidation
  • readerTestParams (further parameters for the test data reader) not necessary for Crossvalidation
• dataWriter (a writer to produce the input for the classification framework, e.g. Weka)
• classificationArguments (the classification algorithm and a list of arguments to parametrize it)
• featureSet (the names of the feature extractors to use)
• pipelineParameters (further parameters necessary to configure the feature extractors)

Optional Parameters with default values

• multiLabel: false (if true, you need to set threshold)
• threshold: 0 needs to be set when multiLabel is true
• featureSelection (DimensionBundle)
  • attributeEvaluator
  • featureSearcher (only for single-label)
  • labelTransformationMethod (only for multi-label)
  • numLabelsToKeep (only for multi-label)
  • applySelection
• isRegressionExperiment: false
• isPairClassification: false
• isUnitClassification: false