Class WekaTrainClusterer

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

    public class WekaTrainClusterer
    extends AbstractTransformer
    implements JobRunnerSupporter
    Trains a clusterer based on the incoming dataset and output the built clusterer alongside the training header (in a model container).
    Incremental training is performed, if the input are weka.core.Instance objects and the clusterer implements weka.clusterers.UpdateableClusterer.

    - accepts:
    - generates:

    Container information:
    - adams.flow.container.WekaModelContainer: Model, Header, Dataset

    -logging-level <OFF|SEVERE|WARNING|INFO|CONFIG|FINE|FINER|FINEST> (property: loggingLevel)
        The logging level for outputting errors and debugging output.
        default: WARNING
        min-user-mode: Expert
    -name <java.lang.String> (property: name)
        The name of the actor.
        default: WekaTrainClusterer
    -annotation <adams.core.base.BaseAnnotation> (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 execution at this level gets stopped in case this
        actor encounters an error; the error gets propagated; useful for critical
        default: false
        min-user-mode: Expert
    -silent <boolean> (property: silent)
        If enabled, then no errors are output in the console; Note: the enclosing
        actor handler must have this enabled as well.
        default: false
        min-user-mode: Expert
    -clusterer <adams.flow.core.CallableActorReference> (property: clusterer)
        The Weka clusterer to build on the input data.
        default: WekaClustererSetup
    -post-processor <adams.flow.transformer.wekaclusterer.AbstractClustererPostProcessor> (property: postProcessor)
        The post-processor to use on model containers.
        default: adams.flow.transformer.wekaclusterer.PassThrough
    -prefer-jobrunner <boolean> (property: preferJobRunner)
        If enabled, tries to offload the processing onto a adams.flow.standalone.JobRunnerInstance;
         applies only to batch training.
        default: false
    fracpete (fracpete at waikato dot ac dot nz)
    See Also:
    Serialized Form
    • Field Detail


        public static final String BACKUP_INCREMENTALCLUSTERER
        the key for storing the current incremental clusterer in the backup.
        See Also:
        Constant Field Values
      • m_ActualClusterer

        protected weka.clusterers.Clusterer m_ActualClusterer
        the weka clusterer.
      • m_IncrementalClusterer

        protected weka.clusterers.Clusterer m_IncrementalClusterer
        the clusterer used when training incrementally.
      • m_PreferJobRunner

        protected boolean m_PreferJobRunner
        whether to offload training into a JobRunnerInstance.
      • m_JobRunnerInstance

        protected transient JobRunnerInstance m_JobRunnerInstance
        the JobRunnerInstance to use.
    • Constructor Detail

      • WekaTrainClusterer

        public WekaTrainClusterer()