Name

adams.flow.transformer.WekaWSOptimizeClassifierMultiSearch

Synopsis

Generates an optimization request using weka.classifiers.meta.MultiSearch, using the Weka web-service.

Additional information

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

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	WekaWSOptimizeClassifierMultiSearch

  
  
• 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
  

  Global actore for the base classifier to use optimize.

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

  
  
• parameters
  

  The search parameters to use for the optimization.

  command-line	-parameter <weka.core.setupgenerator.AbstractParameter> [-parameter ...]
  default

  
  
• evaluation
  

  The type of statistic to evaluate the performance of a setup with.

  command-line	-evaluation <CORRELATION_COEFFICIENT|ROOT_MEAN_SQUARED_ERROR|ROOT_RELATIVE_SQUARED_ERROR|MEAN_ABSOLUTE_ERROR|RELATIVE_ABSOLUTE_ERROR|COMBINED|ACCURACY|KAPPA>
  default	ACCURACY