|
||||||||||
| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD | |||||||||
java.lang.Objectweka.classifiers.Classifier
weka.classifiers.bayes.AODEsr
public class AODEsr
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.
@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)
| 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 |
|---|
public AODEsr()
| Method Detail |
|---|
public java.lang.String globalInfo()
public TechnicalInformation getTechnicalInformation()
getTechnicalInformation in interface TechnicalInformationHandlerpublic Capabilities getCapabilities()
getCapabilities in interface CapabilitiesHandlergetCapabilities in class ClassifierCapabilities
public void buildClassifier(Instances instances)
throws java.lang.Exception
buildClassifier in class Classifierinstances - set of instances serving as training data
java.lang.Exception - if the classifier has not been generated
successfullypublic void updateClassifier(Instance instance)
updateClassifier in interface UpdateableClassifierinstance - the new training instance to include in the model
java.lang.Exception - if the instance could not be incorporated in
the model.
public double[] distributionForInstance(Instance instance)
throws java.lang.Exception
distributionForInstance in class Classifierinstance - the instance to be classified
java.lang.Exception - if there is a problem generating the prediction
public double NBconditionalProb(Instance instance,
int classVal)
throws java.lang.Exception
instance - the instance to be classifiedclassVal - the class for which to calculate the probability
java.lang.Exception - if there is a problem generating the prediction
public double MEstimate(double frequency,
double total,
double numValues)
frequency - frequency of value of interesttotal - count of all valuesnumValues - number of different values
public double LaplaceEstimate(double frequency,
double total,
double numValues)
frequency - frequency of value of interesttotal - count of all valuesnumValues - number of different values
public java.util.Enumeration listOptions()
listOptions in interface OptionHandlerlistOptions in class Classifier
public void setOptions(java.lang.String[] options)
throws java.lang.Exception
-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)
setOptions in interface OptionHandlersetOptions in class Classifieroptions - the list of options as an array of strings
java.lang.Exception - if an option is not supportedpublic java.lang.String[] getOptions()
getOptions in interface OptionHandlergetOptions in class Classifierpublic java.lang.String mestWeightTipText()
public void setMestWeight(double w)
w - the weightpublic double getMestWeight()
public java.lang.String useLaplaceTipText()
public boolean getUseLaplace()
public void setUseLaplace(boolean value)
value - Value to assign to m_Laplace.public java.lang.String frequencyLimitTipText()
public void setFrequencyLimit(int f)
f - the frequency limitpublic int getFrequencyLimit()
public java.lang.String criticalValueTipText()
public void setCriticalValue(int c)
c - the critical valuepublic int getCriticalValue()
public java.lang.String toString()
toString in class java.lang.Objectpublic java.lang.String getRevision()
getRevision in interface RevisionHandlergetRevision in class Classifierpublic static void main(java.lang.String[] argv)
argv - the options
|
||||||||||
| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD | |||||||||