Package weka.classifiers.meta

Class ThresholdedBinaryClassification

  • All Implemented Interfaces:
    Serializable, Cloneable, weka.classifiers.Classifier, weka.core.BatchPredictor, weka.core.CapabilitiesHandler, weka.core.CapabilitiesIgnorer, weka.core.CommandlineRunnable, ModelOutputHandler, weka.core.OptionHandler, weka.core.RevisionHandler
    public class ThresholdedBinaryClassification
extends weka.classifiers.SingleClassifierEnhancer
implements ModelOutputHandler
    Meta classifier for binary classification problems that allows to specify a minimum probability threshold for one of the labels. If this label achieves at least this probability then this label gets chosen, otherwise the other one.

    Valid options are: 

     -label <value>
  The index of the label to check.
  (default: first)
     -min-probability <value>
  The minimum probability for the label (0-1).
  (default: 0.5)
     -suppress-model-output
  If enabled, suppresses any large model output.
     -W
  Full name of base classifier.
  (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).
     
 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).
    Version:
    $Revision$
    Author:
    FracPete (fracpete at waikato dot ac dot nz)
    See Also:
    Serialized Form

    • Field Detail

      • m_ActualLabel

        protected int m_ActualLabel
        the index of the label to check.

      • m_OtherLabel

        protected int m_OtherLabel
        the index of the other label.

      • m_MinProbability

        protected double m_MinProbability
        the minimum probability for the label.

      • m_SuppressModelOutput

        protected boolean m_SuppressModelOutput
        whether to suppress the model output.

    • Constructor Detail

      • ThresholdedBinaryClassification

        public ThresholdedBinaryClassification()

    • Method Detail

      • globalInfo

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

      • getDefaultLabel

        protected WekaLabelIndex getDefaultLabel()
        Returns the default label index.
        Returns:
        the default

      • setLabel

        public void setLabel​(WekaLabelIndex value)
        Sets the label index to use.
        Parameters:
        value - the label index

      • getLabel

        public WekaLabelIndex getLabel()
        Returns the label index.
        Returns:
        the label index

      • labelTipText

        public String labelTipText()
        Returns the tip text for this property.
        Returns:
        tip text for this property suitable for displaying in the gui

      • getDefaultMinProbability

        protected double getDefaultMinProbability()
        Returns the default minimum probability.
        Returns:
        the default

      • setMinProbability

        public void setMinProbability​(double value)
        Sets the minimum probability for the selected label.
        Parameters:
        value - the probability

      • getMinProbability

        public double getMinProbability()
        Returns the minimum probability for the selected label.
        Returns:
        the probability

      • minProbabilityTipText

        public String minProbabilityTipText()
        Returns the tip text for this property.
        Returns:
        tip text for this property suitable for displaying in the gui

      • setSuppressModelOutput

        public void setSuppressModelOutput​(boolean value)
        Sets whether to output the model with the toString() method or not.
        Specified by:
        setSuppressModelOutput in interface ModelOutputHandler
        Parameters:
        value - true if to suppress model output

      • getSuppressModelOutput

        public boolean getSuppressModelOutput()
        Returns whether to output the model with the toString() method or not.
        Specified by:
        getSuppressModelOutput in interface ModelOutputHandler
        Returns:
        the label index

      • suppressModelOutputTipText

        public String suppressModelOutputTipText()
        Returns the tip text for this property.
        Specified by:
        suppressModelOutputTipText in interface ModelOutputHandler
        Returns:
        tip text for this property suitable for displaying in the 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.SingleClassifierEnhancer
        Returns:
        an enumeration of all the available options.

      • setOptions

        public void setOptions​(String[] options)
                throws Exception
        Sets the OptionHandler's options using the given list. All options will be set (or reset) during this call (i.e. incremental setting of options is not possible).
        Specified by:
        setOptions in interface weka.core.OptionHandler
        Overrides:
        setOptions in class weka.classifiers.SingleClassifierEnhancer
        Parameters:
        options - the list of options as an array of strings
        Throws:
        Exception - if an option is not supported

      • getOptions

        public String[] getOptions()
        Gets the current option settings for the OptionHandler.
        Specified by:
        getOptions in interface weka.core.OptionHandler
        Overrides:
        getOptions in class weka.classifiers.SingleClassifierEnhancer
        Returns:
        the list of current option settings as an array of strings

      • getCapabilities

        public weka.core.Capabilities getCapabilities()
        Returns the ensemble's capabilities.
        Specified by:
        getCapabilities in interface weka.core.CapabilitiesHandler
        Specified by:
        getCapabilities in interface weka.classifiers.Classifier
        Overrides:
        getCapabilities in class weka.classifiers.SingleClassifierEnhancer
        Returns:
        the capabilities

      • buildClassifier

        public void buildClassifier​(weka.core.Instances data)
                     throws Exception
        Builds the classifier with the training data.
        Specified by:
        buildClassifier in interface weka.classifiers.Classifier
        Parameters:
        data - the training data
        Throws:
        Exception

      • distributionForInstance

        public double[] distributionForInstance​(weka.core.Instance instance)
                                 throws Exception
        Returns the class distribution for the instance.
        Specified by:
        distributionForInstance in interface weka.classifiers.Classifier
        Overrides:
        distributionForInstance in class weka.classifiers.AbstractClassifier
        Parameters:
        instance - the instance to make the prediction for
        Returns:
        the class distribution
        Throws:
        Exception - if classification fails

      • toString

        public String toString()
        Returns the classifier's model.
        Overrides:
        toString in class Object
        Returns:
        the model