weka.classifiers.bayes
Class AODEsr

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

public class AODEsr
extends Classifier
implements OptionHandler, WeightedInstancesHandler, UpdateableClassifier, TechnicalInformationHandler

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: 1.4 $
Author:
Fei Zheng, Janice Boughton
See Also:
Serialized Form

Constructor Summary
AODEsr()
           
 
Method Summary
 void buildClassifier(Instances instances)
          Generates the classifier.
 java.lang.String criticalValueTipText()
          Returns the tip text for this property
 double[] distributionForInstance(Instance instance)
          Calculates the class membership probabilities for the given test instance.
 java.lang.String frequencyLimitTipText()
          Returns the tip text for this property
 Capabilities getCapabilities()
          Returns default capabilities of the classifier.
 int getCriticalValue()
          Gets the critical value.
 int getFrequencyLimit()
          Gets the frequency limit.
 double getMestWeight()
          Gets the weight used in m-estimate
 java.lang.String[] getOptions()
          Gets the current settings of the classifier.
 java.lang.String getRevision()
          Returns the revision string.
 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.
 boolean getUseLaplace()
          Gets if laplace correction is being used.
 java.lang.String globalInfo()
          Returns a string describing this classifier
 double LaplaceEstimate(double frequency, double total, double numValues)
          Returns the probability estimate, using laplace correction
 java.util.Enumeration listOptions()
          Returns an enumeration describing the available options
static void main(java.lang.String[] argv)
          Main method for testing this class.
 double MEstimate(double frequency, double total, double numValues)
          Returns the probability estimate, using m-estimate
 java.lang.String mestWeightTipText()
          Returns the tip text for this property
 double NBconditionalProb(Instance instance, int classVal)
          Calculates the probability of the specified class for the given test instance, using naive Bayes.
 void setCriticalValue(int c)
          Sets the critical value
 void setFrequencyLimit(int f)
          Sets the frequency limit
 void setMestWeight(double w)
          Sets the weight for m-estimate
 void setOptions(java.lang.String[] options)
          Parses a given list of options.
 void setUseLaplace(boolean value)
          Sets if laplace correction is to be used.
 java.lang.String toString()
          Returns a description of the classifier.
 void updateClassifier(Instance instance)
          Updates the classifier with the given instance.
 java.lang.String useLaplaceTipText()
          Returns the tip text for this property
 
Methods inherited from class weka.classifiers.Classifier
classifyInstance, debugTipText, forName, getDebug, makeCopies, makeCopy, setDebug
 
Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, wait, wait, wait
 

Constructor Detail

AODEsr

public AODEsr()
Method Detail

globalInfo

public java.lang.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:
Capabilities

buildClassifier

public void buildClassifier(Instances instances)
                     throws java.lang.Exception
Generates the classifier.

Specified by:
buildClassifier in class Classifier
Parameters:
instances - set of instances serving as training data
Throws:
java.lang.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:
java.lang.Exception - if the instance could not be incorporated in the model.

distributionForInstance

public double[] distributionForInstance(Instance instance)
                                 throws java.lang.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:
java.lang.Exception - if there is a problem generating the prediction

NBconditionalProb

public double NBconditionalProb(Instance instance,
                                int classVal)
                         throws java.lang.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:
java.lang.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 java.util.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(java.lang.String[] options)
                throws java.lang.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:
java.lang.Exception - if an option is not supported

getOptions

public java.lang.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 java.lang.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 java.lang.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 java.lang.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 java.lang.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 java.lang.String toString()
Returns a description of the classifier.

Overrides:
toString in class java.lang.Object
Returns:
a description of the classifier as a string.

getRevision

public java.lang.String getRevision()
Returns the revision string.

Specified by:
getRevision in interface RevisionHandler
Returns:
the revision

main

public static void main(java.lang.String[] argv)
Main method for testing this class.

Parameters:
argv - the options