Name

adams.flow.transformer.WekaModelReader

Synopsis

Actor for loading a model (classifier or clusterer).

Additional information

Flow input/output:
- input: java.lang.String, java.io.File
- output: adams.flow.container.WekaModelContainer

Container information:
- adams.flow.container.WekaModelContainer:
   - Model: model object; java.lang.Object
   - Header: dataset header; weka.core.Instances
   - Dataset: full dataset; weka.core.Instances

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	WekaModelReader

  
  
• 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

  
  
• outputOnlyModel
  

  If enabled, only the model will be output instead of a model container.

  command-line	-output-only-model <boolean>
  default	false

  
  
• makeThreadSafe
  

  If enabled, the classifier model gets wrapped in a weka.classifiers.meta.ThreadSafeClassifierWrapper meta-classifier.

  command-line	-make-thread-safe <boolean>
  default	false