Package weka.classifiers.meta

Class Consensus

  • All Implemented Interfaces:
    Serializable, Cloneable, AbstainingClassifier, weka.classifiers.Classifier, weka.core.BatchPredictor, weka.core.CapabilitiesHandler, weka.core.CapabilitiesIgnorer, weka.core.CommandlineRunnable, weka.core.OptionHandler, weka.core.RevisionHandler
    public class Consensus
extends weka.classifiers.MultipleClassifiersCombiner
implements AbstainingClassifier
    Outputs predictions only if the ensemble agrees. In case of agreement, the classifier identified by the 'predictor' index is used for making the actual prediction.

    Valid options are: 

     -B <classifier specification>
  Full class name of classifier to include, followed
  by scheme options. May be specified multiple times.
  (default: "weka.classifiers.rules.ZeroR")
     -output-debug-info
  If set, classifier is run in debug mode and
  may output additional info to the console
     -do-not-check-capabilities
  If set, classifier capabilities are not checked before classifier is built
  (use with caution).
     -num-decimal-places
  The number of decimal places for the output of numbers in the model (default 2).
     -batch-size
  The desired batch size for batch prediction  (default 100).
     Options specific to classifier weka.classifiers.rules.ZeroR:
 
     -output-debug-info
  If set, classifier is run in debug mode and
  may output additional info to the console
     -do-not-check-capabilities
  If set, classifier capabilities are not checked before classifier is built
  (use with caution).
     -num-decimal-places
  The number of decimal places for the output of numbers in the model (default 2).
     -batch-size
  The desired batch size for batch prediction  (default 100).
     -predictor <1-based index>
  The index of the classifier for making the actual predictions.
  (default: 1)
    Author:
    FracPete (fracpete at waikato dot ac dot nz)
    See Also:
    Serialized Form

    • Field Summary

      Fields 
      Modifier and Type Field Description
      protected adams.core.Index m_Predictor
      the index of the classifier to use for making the actual prediction.

      • Fields inherited from class weka.classifiers.MultipleClassifiersCombiner

        m_Classifiers

      • Fields inherited from class weka.classifiers.AbstractClassifier

        BATCH_SIZE_DEFAULT, m_BatchSize, m_Debug, m_DoNotCheckCapabilities, m_numDecimalPlaces, NUM_DECIMAL_PLACES_DEFAULT

    • Constructor Summary

      Constructors 
      Constructor Description
      Consensus()  

    • Method Summary

      All Methods Instance Methods Concrete Methods 
      Modifier and Type Method Description
      void buildClassifier​(weka.core.Instances data)
      Generates a classifier.
      boolean canAbstain()
      Whether abstaining is possible, e.g., used in meta-classifiers.
      double classifyInstance​(weka.core.Instance instance)
      Classifies the given test instance.
      protected boolean consensus​(weka.core.Instance instance)
      Checks whether there is consensus between the classifiers.
      double[] distributionForInstance​(weka.core.Instance instance)
      Predicts the class memberships for a given instance.
      double getAbstentionClassification​(weka.core.Instance inst)
      The prediction that made the classifier abstain.
      double[] getAbstentionDistribution​(weka.core.Instance inst)
      The class distribution that made the classifier abstain.
      String[] getOptions()
      Gets the current settings of Vote.
      adams.core.Index getPredictor()
      Returns the index of the classifier for making the actual predictions.
      String globalInfo()
      Returns a string describing classifier
      Enumeration listOptions()
      Returns an enumeration describing the available options.
      String predictorTipText()
      Returns the tip text for this property.
      void setOptions​(String[] options)
      Parses a given list of options.
      void setPredictor​(adams.core.Index value)
      Sets the index of the classifier for making the actual predictions.

      • Methods inherited from class weka.classifiers.MultipleClassifiersCombiner

        classifiersTipText, getCapabilities, getClassifier, getClassifiers, getClassifierSpec, postExecution, preExecution, setClassifiers

      • Methods inherited from class weka.classifiers.AbstractClassifier

        batchSizeTipText, debugTipText, distributionsForInstances, doNotCheckCapabilitiesTipText, forName, getBatchSize, getDebug, getDoNotCheckCapabilities, getNumDecimalPlaces, getRevision, implementsMoreEfficientBatchPrediction, makeCopies, makeCopy, numDecimalPlacesTipText, run, runClassifier, setBatchSize, setDebug, setDoNotCheckCapabilities, setNumDecimalPlaces

      • Methods inherited from interface weka.classifiers.Classifier

        getCapabilities

    • Field Detail

      • m_Predictor

        protected adams.core.Index m_Predictor
        the index of the classifier to use for making the actual prediction.

    • Constructor Detail

      • Consensus

        public Consensus()

    • Method Detail

      • globalInfo

        public String globalInfo()
        Returns a string describing classifier
        Returns:
        a description suitable for displaying in the explorer/experimenter gui

      • listOptions

        public Enumeration listOptions()
        Returns an enumeration describing the available options.
        Specified by:
        listOptions in interface weka.core.OptionHandler
        Overrides:
        listOptions in class weka.classifiers.MultipleClassifiersCombiner
        Returns:
        an enumeration of all the available options.

      • getOptions

        public String[] getOptions()
        Gets the current settings of Vote.
        Specified by:
        getOptions in interface weka.core.OptionHandler
        Overrides:
        getOptions in class weka.classifiers.MultipleClassifiersCombiner
        Returns:
        an array of strings suitable for passing to setOptions()

      • setOptions

        public void setOptions​(String[] options)
                throws Exception
        Parses a given list of options.
        Specified by:
        setOptions in interface weka.core.OptionHandler
        Overrides:
        setOptions in class weka.classifiers.MultipleClassifiersCombiner
        Parameters:
        options - the list of options as an array of strings
        Throws:
        Exception - if an option is not supported

      • setPredictor

        public void setPredictor​(adams.core.Index value)
        Sets the index of the classifier for making the actual predictions.
        Parameters:
        value - the index (1-based)

      • getPredictor

        public adams.core.Index getPredictor()
        Returns the index of the classifier for making the actual predictions.
        Returns:
        the index (1-based)

      • predictorTipText

        public String predictorTipText()
        Returns the tip text for this property.
        Returns:
        tip text for this property suitable for displaying in the explorer/experimenter gui

      • buildClassifier

        public void buildClassifier​(weka.core.Instances data)
                     throws Exception
        Generates a classifier.
        Specified by:
        buildClassifier in interface weka.classifiers.Classifier
        Parameters:
        data - set of instances serving as training data
        Throws:
        Exception - if the classifier has not been generated successfully

      • consensus

        protected boolean consensus​(weka.core.Instance instance)
                     throws Exception
        Checks whether there is consensus between the classifiers.
        Parameters:
        instance - the instance to check
        Returns:
        true if consensus
        Throws:
        Exception - if classification fails

      • classifyInstance

        public double classifyInstance​(weka.core.Instance instance)
                        throws Exception
        Classifies the given test instance. The instance has to belong to a dataset when it's being classified.
        Specified by:
        classifyInstance in interface weka.classifiers.Classifier
        Overrides:
        classifyInstance in class weka.classifiers.AbstractClassifier
        Parameters:
        instance - the instance to be classified
        Returns:
        the predicted most likely class for the instance or Utils.missingValue() if no prediction is made
        Throws:
        Exception - if an error occurred during the prediction

      • distributionForInstance

        public double[] distributionForInstance​(weka.core.Instance instance)
                                 throws Exception
        Predicts the class memberships for a given instance. If an instance is unclassified, the returned array elements must be all zero. If the class is numeric, the array must consist of only one element, which contains the predicted value.
        Specified by:
        distributionForInstance in interface weka.classifiers.Classifier
        Overrides:
        distributionForInstance in class weka.classifiers.AbstractClassifier
        Parameters:
        instance - the instance to be classified
        Returns:
        an array containing the estimated membership probabilities of the test instance in each class or the numeric prediction
        Throws:
        Exception - if distribution could not be computed successfully

      • canAbstain

        public boolean canAbstain()
        Whether abstaining is possible, e.g., used in meta-classifiers.
        Specified by:
        canAbstain in interface AbstainingClassifier
        Returns:
        true if abstaining is possible

      • getAbstentionClassification

        public double getAbstentionClassification​(weka.core.Instance inst)
                                   throws Exception
        The prediction that made the classifier abstain.
        Specified by:
        getAbstentionClassification in interface AbstainingClassifier
        Parameters:
        inst - the instance to get the prediction for
        Returns:
        the prediction
        Throws:
        Exception - if fails to make prediction

      • getAbstentionDistribution

        public double[] getAbstentionDistribution​(weka.core.Instance inst)
                                   throws Exception
        The class distribution that made the classifier abstain.
        Specified by:
        getAbstentionDistribution in interface AbstainingClassifier
        Parameters:
        inst - the instance to get the prediction for
        Returns:
        the class distribution
        Throws:
        Exception - if fails to make prediction