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java.lang.Objectweka.classifiers.bayes.net.search.SearchAlgorithm
weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
weka.classifiers.bayes.net.search.global.SimulatedAnnealing
public class SimulatedAnnealing
This Bayes Network learning algorithm uses the general purpose search method of simulated annealing to find a well scoring network structure.
For more information see:
R.R. Bouckaert (1995). Bayesian Belief Networks: from Construction to Inference. Utrecht, Netherlands.
@phdthesis{Bouckaert1995,
address = {Utrecht, Netherlands},
author = {R.R. Bouckaert},
institution = {University of Utrecht},
title = {Bayesian Belief Networks: from Construction to Inference},
year = {1995}
}
Valid options are:
-A <float> Start temperature
-U <integer> Number of runs
-D <float> Delta temperature
-R <seed> Random number seed
-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)
| Field Summary |
|---|
| Fields inherited from class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm |
|---|
TAGS_CV_TYPE |
| Constructor Summary | |
|---|---|
SimulatedAnnealing()
|
|
| Method Summary | |
|---|---|
java.lang.String |
deltaTipText()
|
double |
getDelta()
|
java.lang.String[] |
getOptions()
Gets the current settings of the search algorithm. |
java.lang.String |
getRevision()
Returns the revision string. |
int |
getRuns()
|
int |
getSeed()
|
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. |
double |
getTStart()
|
java.lang.String |
globalInfo()
This will return a string describing the classifier. |
java.util.Enumeration |
listOptions()
Returns an enumeration describing the available options. |
java.lang.String |
runsTipText()
|
void |
search(BayesNet bayesNet,
Instances instances)
|
java.lang.String |
seedTipText()
|
void |
setDelta(double fDelta)
Sets the m_fDelta. |
void |
setOptions(java.lang.String[] options)
Parses a given list of options. |
void |
setRuns(int nRuns)
Sets the m_nRuns. |
void |
setSeed(int nSeed)
Sets the random number seed |
void |
setTStart(double fTStart)
Sets the m_fTStart. |
java.lang.String |
TStartTipText()
|
| Methods inherited from class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm |
|---|
calcScore, calcScoreWithExtraParent, calcScoreWithMissingParent, calcScoreWithReversedParent, cumulativeCV, CVTypeTipText, getCVType, getMarkovBlanketClassifier, getUseProb, kFoldCV, leaveOneOutCV, markovBlanketClassifierTipText, setCVType, setMarkovBlanketClassifier, setUseProb, useProbTipText |
| Methods inherited from class weka.classifiers.bayes.net.search.SearchAlgorithm |
|---|
buildStructure, initAsNaiveBayesTipText, maxNrOfParentsTipText, toString |
| Methods inherited from class java.lang.Object |
|---|
equals, getClass, hashCode, notify, notifyAll, wait, wait, wait |
| Constructor Detail |
|---|
public SimulatedAnnealing()
| Method Detail |
|---|
public TechnicalInformation getTechnicalInformation()
getTechnicalInformation in interface TechnicalInformationHandler
public void search(BayesNet bayesNet,
Instances instances)
throws java.lang.Exception
bayesNet - the bayes net to useinstances - the data to use
java.lang.Exception - if something goes wrongpublic double getDelta()
public double getTStart()
public int getRuns()
public void setDelta(double fDelta)
fDelta - The m_fDelta to setpublic void setTStart(double fTStart)
fTStart - The m_fTStart to setpublic void setRuns(int nRuns)
nRuns - The m_nRuns to setpublic int getSeed()
public void setSeed(int nSeed)
nSeed - The number of the seed to setpublic java.util.Enumeration listOptions()
listOptions in interface OptionHandlerlistOptions in class GlobalScoreSearchAlgorithm
public void setOptions(java.lang.String[] options)
throws java.lang.Exception
-A <float> Start temperature
-U <integer> Number of runs
-D <float> Delta temperature
-R <seed> Random number seed
-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 GlobalScoreSearchAlgorithmoptions - 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 GlobalScoreSearchAlgorithmpublic java.lang.String globalInfo()
globalInfo in class GlobalScoreSearchAlgorithmpublic java.lang.String TStartTipText()
public java.lang.String runsTipText()
public java.lang.String deltaTipText()
public java.lang.String seedTipText()
public java.lang.String getRevision()
getRevision in interface RevisionHandlergetRevision in class GlobalScoreSearchAlgorithm
|
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