Name

adams.flow.transformer.WekaClassifierOptimizer

Synopsis

Evaluates a classifier optimizer on an incoming dataset. The best setup (untrained) found is then forwarded.
At the moment, only GridSearch and MultiSearch are supported as optimizers.

Additional information

Flow input/output:
- input: weka.core.Instances
- output: weka.classifiers.Classifier

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	WekaClassifierOptimizer

  
  
• 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

  
  
• optimizer
  

  The classifier optimizer to use, eg, GridSearch or MultiSearch.

  command-line

  -optimizer <weka.classifiers.Classifier>

  default

  weka.classifiers.meta.GridSearch -E CC -y-property kernel.gamma -y-min -3.0 -y-max 3.0 -y-step 1.0 -y-base 10.0 -y-expression pow(BASE,I) -x-property C -x-min -3.0 -x-max 3.0 -x-step 1.0 -x-base 10.0 -x-expression pow(BASE,I) -sample-size 100.0 -traversal ROW-WISE -log-file \"/var/lib/jenkins/jobs/ADAMS Applications/workspace/adams-spectral-app/target/actorstmp\" -num-slots 1 -S 1 -W weka.classifiers.functions.SMOreg -- -C 1.0 -N 0 -I \"weka.classifiers.functions.supportVector.RegSMOImproved -T 0.001 -V -P 1.0E-12 -L 0.001 -W 1\" -K \"weka.classifiers.functions.supportVector.RBFKernel -G 0.01 -C 250007\"