Package adams.flow.transformer

Class WekaAttributeSelection

  • All Implemented Interfaces:
    AdditionalInformationHandler, CleanUpHandler, Destroyable, GlobalInfoSupporter, LoggingLevelHandler, LoggingSupporter, OptionHandler, QuickInfoSupporter, Randomizable, ShallowCopySupporter<Actor>, SizeOfHandler, Stoppable, StoppableWithFeedback, VariablesInspectionHandler, VariableChangeListener, Actor, ErrorHandler, InputConsumer, OutputProducer, Serializable, Comparable
    public class WekaAttributeSelection
extends AbstractTransformer
implements Randomizable
    Performs attribute selection on the incoming data.
    In case of input in form of a class adams.flow.container.WekaTrainTestSetContainer object, the train and test sets stored in the container are being used.
    NB: In case of cross-validation no reduced or transformed data can get generated!

    Input/output:
    - accepts:
       weka.core.Instances
       adams.flow.container.WekaTrainTestSetContainer
    - generates:
       adams.flow.container.WekaAttributeSelectionContainer


    Container information:
    - adams.flow.container.WekaTrainTestSetContainer: Train, Test, Seed, FoldNumber, FoldCount, Train original indices, Test original indices
    - adams.flow.container.WekaAttributeSelectionContainer: Train, Reduced, Transformed, Test, Test reduced, Test transformed, Evaluation, Statistics, Selected attributes, Seed, FoldCount 

    -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: WekaAttributeSelection
 
    -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
 
    -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
 
    -evaluator <weka.attributeSelection.ASEvaluation> (property: evaluator)
    The evaluation method to use.
    default: weka.attributeSelection.CfsSubsetEval -P 1 -E 1
 
    -search <weka.attributeSelection.ASSearch> (property: search)
    The search method to use.
    default: weka.attributeSelection.BestFirst -D 1 -N 5
 
    -seed <long> (property: seed)
    The seed value for cross-validation (used for randomization).
    default: 1
 
    -folds <int> (property: folds)
    The number of folds to use in the cross-validation; no cross-validation 
    is performed if folds < 2.
    default: 10
    minimum: -1
    Author:
    fracpete (fracpete at waikato dot ac dot nz)
    See Also:
    Serialized Form

    • Field Detail

      • m_Evaluator

        protected weka.attributeSelection.ASEvaluation m_Evaluator
        the evaluation.

      • m_Search

        protected weka.attributeSelection.ASSearch m_Search
        the search method.

      • m_Folds

        protected int m_Folds
        the number of folds.

      • m_Seed

        protected long m_Seed
        the seed value.

    • Constructor Detail

      • WekaAttributeSelection

        public WekaAttributeSelection()

    • Method Detail

      • setEvaluator

        public void setEvaluator​(weka.attributeSelection.ASEvaluation value)
        Sets the evaluation method to use.
        Parameters:
        value - the evaluation method

      • getEvaluator

        public weka.attributeSelection.ASEvaluation getEvaluator()
        Returns the evaluation method in use.
        Returns:
        the evaluation method

      • evaluatorTipText

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

      • setSearch

        public void setSearch​(weka.attributeSelection.ASSearch value)
        Sets the evaluation method to use.
        Parameters:
        value - the evaluation method

      • getSearch

        public weka.attributeSelection.ASSearch getSearch()
        Returns the evaluation method in use.
        Returns:
        the evaluation method

      • searchTipText

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

      • setFolds

        public void setFolds​(int value)
        Sets the number of folds.
        Parameters:
        value - the folds

      • getFolds

        public int getFolds()
        Returns the number of folds.
        Returns:
        the folds

      • foldsTipText

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

      • setSeed

        public void setSeed​(long value)
        Sets the seed value.
        Specified by:
        setSeed in interface Randomizable
        Parameters:
        value - the seed

      • getSeed

        public long getSeed()
        Returns the seed value.
        Specified by:
        getSeed in interface Randomizable
        Returns:
        the seed

      • seedTipText

        public String seedTipText()
        Returns the tip text for this property.
        Specified by:
        seedTipText in interface Randomizable
        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.core.Instances.class, adams.flow.container.WekaTrainTestSetContainer.class

      • generates

        public Class[] generates()
        Returns the class of objects that it generates.
        Specified by:
        generates in interface OutputProducer
        Returns:
        adams.flow.container.WekaAttributeSelectionContainer.class

      • doExecute

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