Class AODEsr

java.lang.Object
weka.classifiers.Classifier
weka.classifiers.bayes.AODEsr
All Implemented Interfaces:
Serializable, Cloneable, UpdateableClassifier, CapabilitiesHandler, OptionHandler, RevisionHandler, TechnicalInformationHandler, WeightedInstancesHandler

AODEsr augments AODE with Subsumption Resolution.AODEsr detects specializations between two attribute values at classification time and deletes the generalization attribute value.
For more information, see:
Fei Zheng, Geoffrey I. Webb: Efficient Lazy Elimination for Averaged-One Dependence Estimators. In: Proceedings of the Twenty-third International Conference on Machine Learning (ICML 2006), 1113-1120, 2006.

BibTeX:

 @inproceedings{Zheng2006,
    author = {Fei Zheng and Geoffrey I. Webb},
    booktitle = {Proceedings of the Twenty-third International Conference on Machine  Learning (ICML 2006)},
    pages = {1113-1120},
    publisher = {ACM Press},
    title = {Efficient Lazy Elimination for Averaged-One Dependence Estimators},
    year = {2006},
    ISBN = {1-59593-383-2}
 }
 

Valid options are:

 -D
  Output debugging information
 
 -C
  Impose a critcal value for specialization-generalization relationship
  (default is 50)
 -F
  Impose a frequency limit for superParents
  (default is 1)
 -L
  Using Laplace estimation
  (default is m-esimation (m=1))
 -M
  Weight value for m-estimation
  (default is 1.0)
Version:
$Revision: 5516 $
Author:
Fei Zheng, Janice Boughton
See Also:
  • Constructor Details

    • AODEsr

      public AODEsr()
  • Method Details

    • globalInfo

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

      public TechnicalInformation getTechnicalInformation()
      Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
      Specified by:
      getTechnicalInformation in interface TechnicalInformationHandler
      Returns:
      the technical information about this class
    • getCapabilities

      public Capabilities getCapabilities()
      Returns default capabilities of the classifier.
      Specified by:
      getCapabilities in interface CapabilitiesHandler
      Overrides:
      getCapabilities in class Classifier
      Returns:
      the capabilities of this classifier
      See Also:
    • buildClassifier

      public void buildClassifier(Instances instances) throws Exception
      Generates the classifier.
      Specified by:
      buildClassifier in class Classifier
      Parameters:
      instances - set of instances serving as training data
      Throws:
      Exception - if the classifier has not been generated successfully
    • updateClassifier

      public void updateClassifier(Instance instance)
      Updates the classifier with the given instance.
      Specified by:
      updateClassifier in interface UpdateableClassifier
      Parameters:
      instance - the new training instance to include in the model
      Throws:
      Exception - if the instance could not be incorporated in the model.
    • distributionForInstance

      public double[] distributionForInstance(Instance instance) throws Exception
      Calculates the class membership probabilities for the given test instance.
      Overrides:
      distributionForInstance in class Classifier
      Parameters:
      instance - the instance to be classified
      Returns:
      predicted class probability distribution
      Throws:
      Exception - if there is a problem generating the prediction
    • NBconditionalProb

      public double NBconditionalProb(Instance instance, int classVal) throws Exception
      Calculates the probability of the specified class for the given test instance, using naive Bayes.
      Parameters:
      instance - the instance to be classified
      classVal - the class for which to calculate the probability
      Returns:
      predicted class probability
      Throws:
      Exception - if there is a problem generating the prediction
    • MEstimate

      public double MEstimate(double frequency, double total, double numValues)
      Returns the probability estimate, using m-estimate
      Parameters:
      frequency - frequency of value of interest
      total - count of all values
      numValues - number of different values
      Returns:
      the probability estimate
    • LaplaceEstimate

      public double LaplaceEstimate(double frequency, double total, double numValues)
      Returns the probability estimate, using laplace correction
      Parameters:
      frequency - frequency of value of interest
      total - count of all values
      numValues - number of different values
      Returns:
      the probability estimate
    • listOptions

      public Enumeration listOptions()
      Returns an enumeration describing the available options
      Specified by:
      listOptions in interface OptionHandler
      Overrides:
      listOptions in class Classifier
      Returns:
      an enumeration of all the available options
    • setOptions

      public void setOptions(String[] options) throws Exception
      Parses a given list of options.

      Valid options are:

       -D
        Output debugging information
       
       -C
        Impose a critcal value for specialization-generalization relationship
        (default is 50)
       -F
        Impose a frequency limit for superParents
        (default is 1)
       -L
        Using Laplace estimation
        (default is m-esimation (m=1))
       -M
        Weight value for m-estimation
        (default is 1.0)
      Specified by:
      setOptions in interface OptionHandler
      Overrides:
      setOptions in class Classifier
      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 settings of the classifier.
      Specified by:
      getOptions in interface OptionHandler
      Overrides:
      getOptions in class Classifier
      Returns:
      an array of strings suitable for passing to setOptions
    • mestWeightTipText

      public String mestWeightTipText()
      Returns the tip text for this property
      Returns:
      tip text for this property suitable for displaying in the explorer/experimenter gui
    • setMestWeight

      public void setMestWeight(double w)
      Sets the weight for m-estimate
      Parameters:
      w - the weight
    • getMestWeight

      public double getMestWeight()
      Gets the weight used in m-estimate
      Returns:
      the weight for m-estimation
    • useLaplaceTipText

      public String useLaplaceTipText()
      Returns the tip text for this property
      Returns:
      tip text for this property suitable for displaying in the explorer/experimenter gui
    • getUseLaplace

      public boolean getUseLaplace()
      Gets if laplace correction is being used.
      Returns:
      Value of m_Laplace.
    • setUseLaplace

      public void setUseLaplace(boolean value)
      Sets if laplace correction is to be used.
      Parameters:
      value - Value to assign to m_Laplace.
    • frequencyLimitTipText

      public String frequencyLimitTipText()
      Returns the tip text for this property
      Returns:
      tip text for this property suitable for displaying in the explorer/experimenter gui
    • setFrequencyLimit

      public void setFrequencyLimit(int f)
      Sets the frequency limit
      Parameters:
      f - the frequency limit
    • getFrequencyLimit

      public int getFrequencyLimit()
      Gets the frequency limit.
      Returns:
      the frequency limit
    • criticalValueTipText

      public String criticalValueTipText()
      Returns the tip text for this property
      Returns:
      tip text for this property suitable for displaying in the explorer/experimenter gui
    • setCriticalValue

      public void setCriticalValue(int c)
      Sets the critical value
      Parameters:
      c - the critical value
    • getCriticalValue

      public int getCriticalValue()
      Gets the critical value.
      Returns:
      the critical value
    • toString

      public String toString()
      Returns a description of the classifier.
      Overrides:
      toString in class Object
      Returns:
      a description of the classifier as a string.
    • getRevision

      public String getRevision()
      Returns the revision string.
      Specified by:
      getRevision in interface RevisionHandler
      Overrides:
      getRevision in class Classifier
      Returns:
      the revision
    • main

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