Name

adams.flow.transformer.WekaStreamEvaluator

Synopsis

Evaluates an incremental classifier on a data stream using prequential evaluation (first evaluate, then train).

Additional information

Flow input/output:
- input: weka.core.Instance
- output: adams.flow.container.WekaEvaluationContainer

Container information:
- adams.flow.container.WekaEvaluationContainer:
   - Evaluation: evaluation object; weka.classifiers.Evaluation
   - Model: model object; java.lang.Object
   - Prediction output: prediction output text; java.lang.String
   - Original indices: original indices (0-based); array of int
   - Test data: data used for testing; 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	WekaStreamEvaluator

  
  
• 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

  
  
• output
  

  The class for generating prediction output; if 'Null' is used, then an Evaluation object is forwarded instead of a String.

  command-line	-output <weka.classifiers.evaluation.output.prediction.AbstractOutput>
  default	weka.classifiers.evaluation.output.prediction.Null

  
  
• alwaysUseContainer
  

  If enabled, always outputs an evaluation container.

  command-line	-always-use-container <boolean>
  default	false

  
  
• classifier
  

  The callable source with the incremental classifier to evaluate.

  command-line	-classifier <adams.flow.core.CallableActorReference>
  default	WekaClassifierSetup

  
  
• discardPredictions
  

  If enabled, the collection of predictions during evaluation is suppressed, wich will conserve memory.

  command-line	-no-predictions <boolean>
  default	false

  
  
• interval
  

  The interval (number of instance objects processed) after which to output evaluation or buffer.

  command-line	-interval <int>
  default	100
  minimum	1