Package adams.flow.transformer

Class WekaTestSetEvaluator

  • 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 WekaTestSetEvaluator
extends AbstractWekaClassifierEvaluator
implements JobRunnerSupporter
    Evaluates a trained classifier (obtained from input) on the dataset obtained from the callable actor.

    Input/output:
    - accepts:
       weka.classifiers.Classifier
       adams.flow.container.WekaModelContainer
    - generates:
       adams.flow.container.WekaEvaluationContainer


    Container information:
    - adams.flow.container.WekaModelContainer: Model, Header, Dataset
    - adams.flow.container.WekaEvaluationContainer: Evaluation, Model, Prediction output, Original indices, Test data 

    -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: WekaTestSetEvaluator
 
    -annotation <adams.core.base.BaseAnnotation> (property: annotations)
    The annotations to attach to this actor.
    default:
 
    -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
    actors.
    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
 
    -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
 
    -testset <adams.flow.core.CallableActorReference> (property: testset)
    The callable actor to use for obtaining the test set.
    default: Testset
 
    -no-predictions <boolean> (property: discardPredictions)
    If enabled, the collection of predictions during evaluation is suppressed,
     which will conserve memory.
    default: false
 
    -prefer-jobrunner <boolean> (property: preferJobRunner)
    If enabled, tries to offload the processing onto a adams.flow.standalone.JobRunnerInstance;
     applies only to training.
    default: false
    Author:
    fracpete (fracpete at waikato dot ac dot nz)
    See Also:
    Serialized Form

    • Field Detail

      • m_DiscardPredictions

        protected boolean m_DiscardPredictions
        whether to discard predictions.

      • 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

      • WekaTestSetEvaluator

        public WekaTestSetEvaluator()

    • Method Detail

      • setTestset

        public void setTestset​(CallableActorReference value)
        Sets the name of the callable classifier to use.
        Parameters:
        value - the name

      • getTestset

        public CallableActorReference getTestset()
        Returns the name of the callable classifier in use.
        Returns:
        the name

      • testsetTipText

        public String testsetTipText()
        Returns the tip text for this property.
        Returns:
        tip text for this property suitable for displaying in the GUI or for listing the options.

      • setDiscardPredictions

        public void setDiscardPredictions​(boolean value)
        Sets whether to discard the predictions instead of collecting them for future use, in order to conserve memory.
        Parameters:
        value - true if to discard predictions

      • getDiscardPredictions

        public boolean getDiscardPredictions()
        Returns whether to discard the predictions in order to preserve memory.
        Returns:
        true if predictions discarded

      • discardPredictionsTipText

        public String discardPredictionsTipText()
        Returns the tip text for this property.
        Returns:
        tip text for this property suitable for displaying in the GUI or for listing the options.

      • setPreferJobRunner

        public void setPreferJobRunner​(boolean value)
        Sets whether to offload processing to a JobRunner instance if available.
        Specified by:
        setPreferJobRunner in interface JobRunnerSupporter
        Parameters:
        value - if true try to find/use a JobRunner instance

      • getPreferJobRunner

        public boolean getPreferJobRunner()
        Returns whether to offload processing to a JobRunner instance if available.
        Specified by:
        getPreferJobRunner in interface JobRunnerSupporter
        Returns:
        if true try to find/use a JobRunner instance

      • preferJobRunnerTipText

        public String preferJobRunnerTipText()
        Returns the tip text for this property.
        Specified by:
        preferJobRunnerTipText in interface JobRunnerSupporter
        Returns:
        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.
        Specified by:
        accepts in interface InputConsumer
        Returns:
        weka.classifiers.Classifier.class, adams.flow.container.WekaModelContainer.class

      • doExecute

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