Package weka.classifiers.meta

Class WeightedInstancesHandlerWrapper

  • All Implemented Interfaces:
    java.io.Serializable, java.lang.Cloneable, Classifier, BatchPredictor, CapabilitiesHandler, CapabilitiesIgnorer, CommandlineRunnable, OptionHandler, Randomizable, RevisionHandler, WeightedInstancesHandler
    public class WeightedInstancesHandlerWrapper
extends RandomizableSingleClassifierEnhancer
implements WeightedInstancesHandler
    Generic wrapper around any classifier to enable weighted instances support.
    Uses resampling with weights if the base classifier is not implementing the weka.core.WeightedInstancesHandler interface and there are instance weights other 1.0 present. By default, the training data is passed through to the base classifier if it can handle instance weights. However, it is possible to force the use of resampling with weights as well.

    Valid options are: 

     -force-resample-with-weights
  Forces resampling of weights, regardless of whether
  base classifier handles instance weights
     -S <num>
  Random number seed.
  (default 1)
     -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).
     -num-decimal-places
  The number of decimal places for the output of numbers in the model (default 2).
     
 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).
    Version:
    $Revision: 12226 $
    Author:
    FracPete (fracpete at waikato dot ac dot nz)
    See Also:
    Serialized Form

    • Field Detail

      • FORCE_RESAMPLE_WITH_WEIGHTS

        public static final java.lang.String FORCE_RESAMPLE_WITH_WEIGHTS
        command-line option for resampling with weights.
        See Also:
        Constant Field Values

    • Constructor Detail

      • WeightedInstancesHandlerWrapper

        public WeightedInstancesHandlerWrapper()

    • Method Detail

      • globalInfo

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

      • setOptions

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

      • getForceResampleWithWeights

        public boolean getForceResampleWithWeights()
        Gets the size of each subSpace, as a percentage of the training set size.
        Returns:
        the subSpace size, as a percentage.

      • setForceResampleWithWeights

        public void setForceResampleWithWeights​(boolean value)
        Sets the size of each subSpace, as a percentage of the training set size.
        Parameters:
        value - the subSpace size, as a percentage.

      • forceResampleWithWeightsTipText

        public java.lang.String forceResampleWithWeightsTipText()
        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​(Instances data)
                     throws java.lang.Exception
        builds the classifier.
        Specified by:
        buildClassifier in interface Classifier
        Parameters:
        data - the training data to be used for generating the classifier.
        Throws:
        java.lang.Exception - if the classifier could not be built successfully

      • distributionForInstance

        public double[] distributionForInstance​(Instance instance)
                                 throws java.lang.Exception
        Calculates the class membership probabilities for the given test instance.
        Specified by:
        distributionForInstance in interface Classifier
        Overrides:
        distributionForInstance in class AbstractClassifier
        Parameters:
        instance - the instance to be classified
        Returns:
        preedicted class probability distribution
        Throws:
        java.lang.Exception - if distribution can't be computed successfully

      • classifyInstance

        public double classifyInstance​(Instance instance)
                        throws java.lang.Exception
        Classifies the given test instance.
        Specified by:
        classifyInstance in interface Classifier
        Overrides:
        classifyInstance in class 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:
        java.lang.Exception - if an error occurred during the prediction

      • toString

        public java.lang.String toString()
        Returns a string description of the model.
        Overrides:
        toString in class java.lang.Object
        Returns:
        the model

      • main

        public static void main​(java.lang.String[] args)
        Main method for testing this class.
        Parameters:
        args - the options