public class RepeatedHillClimber extends HillClimber
-U <integer> Number of runs
-A <seed> Random number seed
-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 [LOO-CV|k-Fold-CV|Cumulative-CV] Score type (LOO-CV,k-Fold-CV,Cumulative-CV)
-Q Use probabilistic or 0/1 scoring. (default probabilistic scoring)
TAGS_CV_TYPEm_bInitAsNaiveBayes, m_bMarkovBlanketClassifier, m_nMaxNrOfParents, m_sInitalBIFFile| Constructor and Description |
|---|
RepeatedHillClimber() |
| Modifier and Type | Method and Description |
|---|---|
java.lang.String[] |
getOptions()
Gets the current settings of the search algorithm.
|
java.lang.String |
getRevision()
Returns the revision string.
|
int |
getRuns()
Returns the number of runs
|
int |
getSeed()
Returns the random seed
|
java.lang.String |
globalInfo()
This will return a string describing the classifier.
|
java.util.Enumeration<Option> |
listOptions()
Returns an enumeration describing the available options.
|
java.lang.String |
runsTipText() |
protected void |
search(BayesNet bayesNet,
Instances instances)
search determines the network structure/graph of the network with the repeated hill climbing.
|
java.lang.String |
seedTipText() |
void |
setOptions(java.lang.String[] options)
Parses a given list of options.
|
void |
setRuns(int nRuns)
Sets the number of runs
|
void |
setSeed(int nSeed)
Sets the random number seed
|
getInitAsNaiveBayes, getMaxNrOfParents, getUseArcReversal, setInitAsNaiveBayes, setMaxNrOfParents, setUseArcReversal, useArcReversalTipTextcalcScore, calcScoreWithExtraParent, calcScoreWithMissingParent, calcScoreWithReversedParent, cumulativeCV, CVTypeTipText, getCVType, getMarkovBlanketClassifier, getUseProb, kFoldCV, leaveOneOutCV, markovBlanketClassifierTipText, setCVType, setMarkovBlanketClassifier, setUseProb, useProbTipTextaddArcMakesSense, buildStructure, doMarkovBlanketCorrection, initAsNaiveBayesTipText, isArc, maxNrOfParentsTipText, reverseArcMakesSense, toStringprotected void search(BayesNet bayesNet, Instances instances) throws java.lang.Exception
search in class HillClimberbayesNet - the network to useinstances - the data to usejava.lang.Exception - if something goes wrongpublic int getRuns()
public void setRuns(int nRuns)
nRuns - The number of runs to setpublic int getSeed()
public void setSeed(int nSeed)
nSeed - The number of the seed to setpublic java.util.Enumeration<Option> listOptions()
listOptions in interface OptionHandlerlistOptions in class HillClimberpublic void setOptions(java.lang.String[] options)
throws java.lang.Exception
-U <integer> Number of runs
-A <seed> Random number seed
-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 [LOO-CV|k-Fold-CV|Cumulative-CV] Score type (LOO-CV,k-Fold-CV,Cumulative-CV)
-Q Use probabilistic or 0/1 scoring. (default probabilistic scoring)
setOptions in interface OptionHandlersetOptions in class HillClimberoptions - the list of options as an array of stringsjava.lang.Exception - if an option is not supportedpublic java.lang.String[] getOptions()
getOptions in interface OptionHandlergetOptions in class HillClimberpublic java.lang.String globalInfo()
globalInfo in class HillClimberpublic java.lang.String runsTipText()
public java.lang.String seedTipText()
public java.lang.String getRevision()
getRevision in interface RevisionHandlergetRevision in class HillClimber