Class WekaStreamEvaluator

  • 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 WekaStreamEvaluator
    extends AbstractCallableWekaClassifierEvaluator
    Evaluates an incremental classifier on a data stream using prequential evaluation (first evaluate, then train).

    - accepts:
    - generates:

    Container information:
    - adams.flow.container.WekaEvaluationContainer: Evaluation, Model, Prediction output

    -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: WekaStreamEvaluator
    -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 gets stopped in case this actor encounters an error;
         useful for critical actors.
        default: false
    -silent <boolean> (property: silent)
        If enabled, then no errors are output in the console.
        default: false
    -output <weka.classifiers.evaluation.output.prediction.AbstractOutput> (property: output)
        The class for generating prediction output; if 'Null' is used, then an Evaluation 
        object is forwarded instead of a String.
        default: weka.classifiers.evaluation.output.prediction.Null
    -always-use-container <boolean> (property: alwaysUseContainer)
        If enabled, always outputs an evaluation container.
        default: false
    -classifier <adams.flow.core.CallableActorReference> (property: classifier)
        The callable source with the incremental classifier to evaluate.
        default: WekaClassifierSetup
    -no-predictions <boolean> (property: discardPredictions)
        If enabled, the collection of predictions during evaluation is suppressed,
         wich will conserve memory.
        default: false
    -interval <int> (property: interval)
        The interval (number of instance objects processed) after which to output 
        evaluation or buffer.
        default: 100
        minimum: 1
    fracpete (fracpete at waikato dot ac dot nz)
    See Also:
    Serialized Form