Name

adams.flow.transformer.MekaWSTrainClassifier

Synopsis

Trains a classifier on a dataset and makes the model available, using the Meka web-service.

Additional information

Flow input/output:
- input: weka.core.Instances
- output: nz.ac.waikato.adams.webservice.meka.TrainClassifier

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

  
  
• name
  

  The name of the actor.

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

  
  
• 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

  
  
• 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

  
  
• classifier
  

  Classifier to use for training

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

  
  
• modelName
  

  name

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