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Java Source Code / Java Documentation » Science » weka » weka.classifiers.bayes.net.search.local 
Source Cross Reference  Class Diagram Java Document (Java Doc) 


weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
   weka.classifiers.bayes.net.search.local.HillClimber
      weka.classifiers.bayes.net.search.local.LAGDHillClimber

LAGDHillClimber
public class LAGDHillClimber extends HillClimber (Code)
This Bayes Network learning algorithm uses a Look Ahead Hill Climbing algorithm called LAGD Hill Climbing. Unlike Greedy Hill Climbing it doesn't calculate a best greedy operation (adding, deleting or reversing an arc) but a sequence of nrOfLookAheadSteps operations, which leads to a network structure whose score is most likely higher in comparison to the network obtained by performing a sequence of nrOfLookAheadSteps greedy operations. The search is not restricted by an order on the variables (unlike K2). The difference with B and B2 is that this hill climber also considers arrows part of the naive Bayes structure for deletion.

Valid options are:

 -L <nr of look ahead steps>
 Look Ahead Depth
 -G <nr of good operations>
 Nr of Good Operations
 -P <nr of parents>
 Maximum number of parents
 -R
 Use arc reversal operation.
 (default false)
 -N
 Initial structure is empty (instead of Naive Bayes)
 -mbc
 Applies a Markov Blanket correction to the network structure, 
 after a network structure is learned. This ensures that all 
 nodes in the network are part of the Markov blanket of the 
 classifier node.
 -S [BAYES|MDL|ENTROPY|AIC|CROSS_CLASSIC|CROSS_BAYES]
 Score type (BAYES, BDeu, MDL, ENTROPY and AIC)

author:
   Manuel Neubach
version:
   $Revision: 1.6 $


Field Summary
 intm_nNrOfGoodOperations
    
 intm_nNrOfLookAheadSteps
    
final static  longserialVersionUID
    


Method Summary
protected  OperationgetAntiOperation(Operation oOperation)
    
protected  Operation[]getGoodOperations(BayesNet bayesNet, Instances instances, int nrOfGoodOperations)
    
public  intgetMaxNrOfParents()
     Gets the max number of parents.
public  intgetNrOfGoodOperations()
    
public  intgetNrOfLookAheadSteps()
    
protected  Operation[]getOptimalOperations(BayesNet bayesNet, Instances instances, int nrOfLookAheadSteps, int nrOfGoodOperations)
    
public  String[]getOptions()
     Gets the current settings of the search algorithm.
public  StringglobalInfo()
     This will return a string describing the search algorithm.
public  EnumerationlistOptions()
     Returns an enumeration describing the available options.
protected  voidlookAheadInGoodDirectionsSearch(BayesNet bayesNet, Instances instances, int nrOfLookAheadSteps, int nrOfGoodOperations)
    
public  StringnrOfGoodOperationsTipText()
    
public  StringnrOfLookAheadStepsTipText()
    
protected  voidsearch(BayesNet bayesNet, Instances instances)
    
public  voidsetMaxNrOfParents(int nMaxNrOfParents)
    
public  voidsetNrOfGoodOperations(int nNrOfGoodOperations)
    
public  voidsetNrOfLookAheadSteps(int nNrOfLookAheadSteps)
    
public  voidsetOptions(String[] options)
     Parses a given list of options.

Field Detail
m_nNrOfGoodOperations
int m_nNrOfGoodOperations(Code)
Number of Good Operations per Step *



m_nNrOfLookAheadSteps
int m_nNrOfLookAheadSteps(Code)
Number of Look Ahead Steps *



serialVersionUID
final static long serialVersionUID(Code)
for serialization





Method Detail
getAntiOperation
protected Operation getAntiOperation(Operation oOperation) throws Exception(Code)
getAntiOperation determines the Operation, which is needed to cancel oOperation
Parameters:
  oOperation - Operation to cancel antiOperation to oOperation
throws:
  Exception - if something goes wrong



getGoodOperations
protected Operation[] getGoodOperations(BayesNet bayesNet, Instances instances, int nrOfGoodOperations) throws Exception(Code)
getGoodOperations determines the nrOfGoodOperations best Operations, which are considered for the calculation of an optimal operationsequence
Parameters:
  bayesNet - Bayes network to apply operation on
Parameters:
  instances - data set to learn from
Parameters:
  nrOfGoodOperations - number of good operations to consider good operations to consider
throws:
  Exception - if something goes wrong



getMaxNrOfParents
public int getMaxNrOfParents()(Code)
Gets the max number of parents. the max number of parents



getNrOfGoodOperations
public int getNrOfGoodOperations()(Code)
Gets the number of "good operations" the number of "good operations"



getNrOfLookAheadSteps
public int getNrOfLookAheadSteps()(Code)
Gets the number of look-ahead steps the number of look-ahead step



getOptimalOperations
protected Operation[] getOptimalOperations(BayesNet bayesNet, Instances instances, int nrOfLookAheadSteps, int nrOfGoodOperations) throws Exception(Code)
getOptimalOperations determines an optimal operationsequence in respect of the parameters nrOfLookAheadSteps and nrOfGoodOperations
Parameters:
  bayesNet - Bayes network to apply operation on
Parameters:
  instances - data set to learn from
Parameters:
  nrOfLookAheadSteps - number of lood ahead steps to use
Parameters:
  nrOfGoodOperations - number of good operations to consider optimal sequence of operations in respect to nrOfLookAheadSteps and nrOfGoodOperations
throws:
  Exception - if something goes wrong



getOptions
public String[] getOptions()(Code)
Gets the current settings of the search algorithm. an array of strings suitable for passing to setOptions



globalInfo
public String globalInfo()(Code)
This will return a string describing the search algorithm. The string.



listOptions
public Enumeration listOptions()(Code)
Returns an enumeration describing the available options. an enumeration of all the available options.



lookAheadInGoodDirectionsSearch
protected void lookAheadInGoodDirectionsSearch(BayesNet bayesNet, Instances instances, int nrOfLookAheadSteps, int nrOfGoodOperations) throws Exception(Code)
lookAheadInGoodDirectionsSearch determines the network structure/graph of the network with best score according to LAGD Hill Climbing
Parameters:
  bayesNet - the network
Parameters:
  instances - the data to use
Parameters:
  nrOfLookAheadSteps -
Parameters:
  nrOfGoodOperations -
throws:
  Exception - if something goes wrong



nrOfGoodOperationsTipText
public String nrOfGoodOperationsTipText()(Code)
a string to describe the Number of Good Operations option.



nrOfLookAheadStepsTipText
public String nrOfLookAheadStepsTipText()(Code)
a string to describe the Number of Look Ahead Steps option.



search
protected void search(BayesNet bayesNet, Instances instances) throws Exception(Code)
search determines the network structure/graph of the network
Parameters:
  bayesNet - the network
Parameters:
  instances - the data to use
throws:
  Exception - if something goes wrong



setMaxNrOfParents
public void setMaxNrOfParents(int nMaxNrOfParents)(Code)
Sets the max number of parents
Parameters:
  nMaxNrOfParents - the max number of parents



setNrOfGoodOperations
public void setNrOfGoodOperations(int nNrOfGoodOperations)(Code)
Sets the number of "good operations"
Parameters:
  nNrOfGoodOperations - the number of "good operations"



setNrOfLookAheadSteps
public void setNrOfLookAheadSteps(int nNrOfLookAheadSteps)(Code)
Sets the number of look-ahead steps
Parameters:
  nNrOfLookAheadSteps - the number of look-ahead steps



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

Valid options are:

 -L <nr of look ahead steps>
 Look Ahead Depth
 -G <nr of good operations>
 Nr of Good Operations
 -P <nr of parents>
 Maximum number of parents
 -R
 Use arc reversal operation.
 (default false)
 -N
 Initial structure is empty (instead of Naive Bayes)
 -mbc
 Applies a Markov Blanket correction to the network structure, 
 after a network structure is learned. This ensures that all 
 nodes in the network are part of the Markov blanket of the 
 classifier node.
 -S [BAYES|MDL|ENTROPY|AIC|CROSS_CLASSIC|CROSS_BAYES]
 Score type (BAYES, BDeu, MDL, ENTROPY and AIC)

Parameters:
  options - the list of options as an array of strings
throws:
  Exception - if an option is not supported



Fields inherited from weka.classifiers.bayes.net.search.local.HillClimber
Cache m_Cache(Code)(Java Doc)
boolean m_bUseArcReversal(Code)(Java Doc)
final static long serialVersionUID(Code)(Java Doc)

Methods inherited from weka.classifiers.bayes.net.search.local.HillClimber
void applyArcAddition(BayesNet bayesNet, int iHead, int iTail, Instances instances)(Code)(Java Doc)
void applyArcDeletion(BayesNet bayesNet, int iHead, int iTail, Instances instances)(Code)(Java Doc)
Operation findBestArcToAdd(BayesNet bayesNet, Instances instances, Operation oBestOperation)(Code)(Java Doc)
Operation findBestArcToDelete(BayesNet bayesNet, Instances instances, Operation oBestOperation)(Code)(Java Doc)
Operation findBestArcToReverse(BayesNet bayesNet, Instances instances, Operation oBestOperation)(Code)(Java Doc)
public boolean getInitAsNaiveBayes()(Code)(Java Doc)
public int getMaxNrOfParents()(Code)(Java Doc)
Operation getOptimalOperation(BayesNet bayesNet, Instances instances) throws Exception(Code)(Java Doc)
public String[] getOptions()(Code)(Java Doc)
public boolean getUseArcReversal()(Code)(Java Doc)
public String globalInfo()(Code)(Java Doc)
void initCache(BayesNet bayesNet, Instances instances) throws Exception(Code)(Java Doc)
boolean isNotTabu(Operation oOperation)(Code)(Java Doc)
public Enumeration listOptions()(Code)(Java Doc)
void performOperation(BayesNet bayesNet, Instances instances, Operation oOperation) throws Exception(Code)(Java Doc)
protected void search(BayesNet bayesNet, Instances instances) throws Exception(Code)(Java Doc)
public void setInitAsNaiveBayes(boolean bInitAsNaiveBayes)(Code)(Java Doc)
public void setMaxNrOfParents(int nMaxNrOfParents)(Code)(Java Doc)
public void setOptions(String[] options) throws Exception(Code)(Java Doc)
public void setUseArcReversal(boolean bUseArcReversal)(Code)(Java Doc)
void updateCache(int iAttributeHead, int nNrOfAtts, ParentSet parentSet)(Code)(Java Doc)
public String useArcReversalTipText()(Code)(Java Doc)

Fields inherited from weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
final public static Tag[] TAGS_SCORE_TYPE(Code)(Java Doc)
BayesNet m_BayesNet(Code)(Java Doc)
double m_fAlpha(Code)(Java Doc)
int m_nScoreType(Code)(Java Doc)
final static long serialVersionUID(Code)(Java Doc)

Methods inherited from weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
public void buildStructure(BayesNet bayesNet, Instances instances) throws Exception(Code)(Java Doc)
public double calcNodeScore(int nNode)(Code)(Java Doc)
protected double calcScoreOfCounts(int[] nCounts, int nCardinality, int numValues, Instances instances)(Code)(Java Doc)
protected double calcScoreOfCounts2(int[][] nCounts, int nCardinality, int numValues, Instances instances)(Code)(Java Doc)
public double calcScoreWithExtraParent(int nNode, int nCandidateParent)(Code)(Java Doc)
public double calcScoreWithMissingParent(int nNode, int nCandidateParent)(Code)(Java Doc)
public boolean getMarkovBlanketClassifier()(Code)(Java Doc)
public String[] getOptions()(Code)(Java Doc)
public SelectedTag getScoreType()(Code)(Java Doc)
public String globalInfo()(Code)(Java Doc)
public Enumeration listOptions()(Code)(Java Doc)
public double logScore(int nType)(Code)(Java Doc)
public String markovBlanketClassifierTipText()(Code)(Java Doc)
public String scoreTypeTipText()(Code)(Java Doc)
public void setMarkovBlanketClassifier(boolean bMarkovBlanketClassifier)(Code)(Java Doc)
public void setOptions(String[] options) throws Exception(Code)(Java Doc)
public void setScoreType(SelectedTag newScoreType)(Code)(Java Doc)

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