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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 |
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Fields inherited from class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm |
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TAGS_CV_TYPE |
Constructor Summary | |
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SimulatedAnnealing()
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Method Summary | |
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java.lang.String |
deltaTipText()
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double |
getDelta()
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java.lang.String[] |
getOptions()
Gets the current settings of the search algorithm. |
int |
getRuns()
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int |
getSeed()
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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()
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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()
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void |
search(BayesNet bayesNet,
Instances instances)
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java.lang.String |
seedTipText()
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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()
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Methods inherited from class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm |
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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 |
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buildStructure, initAsNaiveBayesTipText, maxNrOfParentsTipText, toString |
Methods inherited from class java.lang.Object |
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equals, getClass, hashCode, notify, notifyAll, wait, wait, wait |
Constructor Detail |
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public SimulatedAnnealing()
Method Detail |
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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 OptionHandler
listOptions
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 OptionHandler
setOptions
in class GlobalScoreSearchAlgorithm
options
- 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 OptionHandler
getOptions
in class GlobalScoreSearchAlgorithm
public java.lang.String globalInfo()
globalInfo
in class GlobalScoreSearchAlgorithm
public java.lang.String TStartTipText()
public java.lang.String runsTipText()
public java.lang.String deltaTipText()
public java.lang.String seedTipText()
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