Class WekaTrainTestSetClustererEvaluator

  • All Implemented Interfaces:
    AdditionalInformationHandler, CleanUpHandler, Destroyable, GlobalInfoSupporter, LoggingLevelHandler, LoggingSupporter, OptionHandler, QuickInfoSupporter, ShallowCopySupporter<Actor>, SizeOfHandler, Stoppable, StoppableWithFeedback, VariablesInspectionHandler, VariableChangeListener, Actor, ErrorHandler, InputConsumer, OutputProducer, Serializable, Comparable

    public class WekaTrainTestSetClustererEvaluator
    extends AbstractCallableWekaClustererEvaluator
    Trains a clusterer on an incoming training dataset (from a container) and then evaluates it on the test set (also from a container).
    The clusterer setup being used in the evaluation is a callable 'Clusterer' actor.
    If a class attribute is set, a classes-to-clusters evaluation is performed automatically

    - accepts:
    - generates:

    Container information:
    - adams.flow.container.WekaTrainTestSetContainer: Train, Test, Seed, FoldNumber, FoldCount
    - adams.flow.container.WekaClusterEvaluationContainer: Evaluation, Model, Log-likelohood

    -logging-level <OFF|SEVERE|WARNING|INFO|CONFIG|FINE|FINER|FINEST> (property: loggingLevel)
        The logging level for outputting errors and debugging output.
        default: WARNING
    -name <java.lang.String> (property: name)
        The name of the actor.
        default: WekaTrainTestSetClustererEvaluator
    -annotation <adams.core.base.BaseText> (property: annotations)
        The annotations to attach to this actor.
    -skip <boolean> (property: skip)
        If set to true, transformation is skipped and the input token is just forwarded 
        as it is.
        default: false
    -stop-flow-on-error <boolean> (property: stopFlowOnError)
        If set to true, the flow gets stopped in case this actor encounters an error;
         useful for critical actors.
        default: false
    -clusterer <adams.flow.core.CallableActorReference> (property: clusterer)
        The callable clusterer actor to train and evaluate on the test data.
        default: WekaClustererSetup
    -output-model <boolean> (property: outputModel)
        If enabled, the clusterer model is output as well.
        default: false
    fracpete (fracpete at waikato dot ac dot nz)
    See Also:
    Serialized Form
    • Field Detail

      • m_OutputModel

        protected boolean m_OutputModel
        whether to output the model as well.
    • Constructor Detail

      • WekaTrainTestSetClustererEvaluator

        public WekaTrainTestSetClustererEvaluator()
    • Method Detail

      • setOutputModel

        public void setOutputModel​(boolean value)
        Sets whether to output the clusterer model as well.
        value - true if to output model
      • getOutputModel

        public boolean getOutputModel()
        Returns whether to output the clusterer model as well.
        true if model is output
      • outputModelTipText

        public String outputModelTipText()
        Returns the tip text for this property.
        tip text for this property suitable for displaying in the GUI or for listing the options.
      • accepts

        public Class[] accepts()
        Returns the class that the consumer accepts.
      • generates

        public Class[] generates()
        Returns the class of objects that it generates.
        String.class or weka.classifiers.Evaluation.class
      • doExecute

        protected String doExecute()
        Executes the flow item.
        Specified by:
        doExecute in class AbstractActor
        null if everything is fine, otherwise error message