Name

adams.flow.transformer.PrepareFileBasedDataset

Synopsis

Processes the incoming files and generates a dataset container.

Additional information

Flow input/output:
- input: java.lang.String[]
- output: adams.flow.container.FileBasedDatasetContainer

Container information:
- adams.flow.container.FileBasedDatasetContainer:
   - Train: training files; java.lang.String[]
   - Test: test files (optional); java.lang.String[]
   - Validation: validation files (optional); java.lang.String[]
   - Negative: negative files (optional); java.lang.String[]

See also

• adams.flow.control.SetContainerValue
• adams.flow.transformer.GenerateFileBasedDataset

Options

• loggingLevel
  

  The logging level for outputting errors and debugging output.

  command-line	-logging-level <OFF|SEVERE|WARNING|INFO|CONFIG|FINE|FINER|FINEST>
  default	WARNING
  min-user-mode	Expert

  
  
• name
  

  The name of the actor.

  command-line	-name <java.lang.String>
  default	PrepareFileBasedDataset

  
  
• annotations
  

  The annotations to attach to this actor.

  command-line	-annotation <adams.core.base.BaseAnnotation>
  default

  
  
• skip
  

  If set to true, transformation is skipped and the input token is just forwarded as it is.

  command-line	-skip <boolean>
  default	false

  
  
• stopFlowOnError
  

  If set to true, the flow execution at this level gets stopped in case this actor encounters an error; the error gets propagated; useful for critical actors.

  command-line	-stop-flow-on-error <boolean>
  default	false
  min-user-mode	Expert

  
  
• silent
  

  If enabled, then no errors are output in the console; Note: the enclosing actor handler must have this enabled as well.

  command-line	-silent <boolean>
  default	false
  min-user-mode	Expert

  
  
• outputArray
  

  If enabled, outputs the containers as array rather than one-by-one.

  command-line	-output-array <boolean>
  default	false

  
  
• preparation
  

  The preparation scheme to apply to the files.

  command-line	-preparation <adams.flow.transformer.preparefilebaseddataset.AbstractFileBasedDatasetPreparation>
  default	adams.flow.transformer.preparefilebaseddataset.TrainTestSplit