Name

adams.flow.transformer.WekaRepeatedCrossValidationEvaluator

Synopsis

Performs repeated cross-validation a classifier on an incoming dataset. The classifier setup being used in the evaluation is a callable 'Classifier' actor.

Additional information

Flow input/output:
- input: weka.core.Instances
- 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	WekaRepeatedCrossValidationEvaluator

  
  
• 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

  
  
• classifier
  

  The callable classifier actor to cross-validate on the input data.

  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

  
  
• runs
  

  The number of cross-validation runs to perform.

  command-line	-runs <int>
  default	10
  minimum	1

  
  
• folds
  

  The number of folds to use in the cross-validation; use -1 for leave-one-out cross-validation (LOOCV); overrides the value defined by the fold generator scheme.

  command-line	-folds <int>
  default	10
  minimum	-1

  
  
• numThreads
  

  The number of threads to use for parallel execution; > 0: specific number of cores to use (capped by actual number of cores available, 1 = sequential execution); = 0: number of cores; < 0: number of free cores (eg -2 means 2 free cores; minimum of one core is used); overrides the value defined by the fold generator scheme.

  command-line	-num-threads <int>
  default	1

  
  
• generator
  

  The scheme to use for generating the folds; the actor options take precedence over the scheme's ones.

  command-line	-generator <weka.classifiers.CrossValidationFoldGenerator>
  default	weka.classifiers.DefaultCrossValidationFoldGenerator