Name

adams.flow.transformer.WekaClassifying

Synopsis

Uses a serialized model to perform predictions on the data being passed through.
The following order is used to obtain the model (when using AUTO):
1. model file present?
2. source actor present?
3. storage item present?

Additional information

Flow input/output:
- input: weka.core.Instance, adams.data.instance.WekaInstanceContainer
- output: adams.flow.container.WekaPredictionContainer

Container information:
- adams.flow.container.WekaPredictionContainer:
   - Instance: data row used for prediction; weka.core.Instance
   - Classification: predicted value; java.lang.Double
   - Classification label: predicted label; java.lang.String
   - Distribution: class distribution; array of double
   - Range check: range check; java.lang.String
   - Abstention classification: predicted value that made classifier abstain; java.lang.Double
   - Abstention classification label: predicted label that made classifier abstain; java.lang.String
   - Abstention distribution: class distribution that made classifier abstain; array of double
   - Report: report for storing meta-data; adams.data.report.Report

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	WekaClassifying

  
  
• 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

  
  
• modelLoadingType
  

  Determines how to load the model, in case of AUTO, first the model file is checked, then the callable actor and then the storage.

  command-line	-model-loading-type <AUTO|FILE|SOURCE_ACTOR|STORAGE>
  default	AUTO

  
  
• modelFile
  

  The file to load the model from, ignored if pointing to a directory.

  command-line	-model <adams.core.io.PlaceholderFile>
  default	${CWD}

  
  
• modelActor
  

  The callable actor (source) to obtain the model from, ignored if not present.

  command-line	-model-actor <adams.flow.core.CallableActorReference>
  default

  
  
• modelStorage
  

  The storage item to obtain the model from, ignored if not present.

  command-line	-model-storage <adams.flow.control.StorageName>
  default	storage

  
  
• onTheFly
  

  If set to true, the model file is not required to be present at set up time (eg if built on the fly), only at execution time.

  command-line	-on-the-fly <boolean>
  default	false

  
  
• useModelResetVariable
  

  If enabled, chnages to the specified variable are monitored in order to reset the model, eg when a storage model changed.

  command-line	-use-model-reset-variable <boolean>
  default	false

  
  
• modelResetVariable
  

  The variable to monitor for changes in order to reset the model, eg when a storage model changed.

  command-line	-model-reset-variable <adams.core.VariableName>
  default	variable

  
  
• outputInstance
  

  Whether to output weka.core.Instance objects or PredictionContainer objects.

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