Module es.upm.fi.cig.multictbnc

Package es.upm.fi.cig.multictbnc.learning.structure.constraintlearning.PC

Class MarkovBlanketCTPC

java.lang.Object

es.upm.fi.cig.multictbnc.learning.structure.constraintlearning.PC.CTPC

es.upm.fi.cig.multictbnc.learning.structure.constraintlearning.PC.MarkovBlanketCTPC

All Implemented Interfaces:

StructureLearningAlgorithm

Direct Known Subclasses:

OnlineMarkovBlanketCTPC

public class MarkovBlanketCTPC
extends CTPC

Implementation of the MB-CTPC algorithm.

Constructor Summary

Constructors

Constructor	Description
MarkovBlanketCTPC(double sigTimeTransitionHypothesis, double sigStateToStateTransitionHypothesis)	Initialises the MB-CTPC algorithm by providing the significances to be used.

Method Summary

Modifier and Type	Method	Description
void	learn(PGM<? extends Node> pgm)	Learns the structure of a certain PGM.

Methods inherited from class es.upm.fi.cig.multictbnc.learning.structure.constraintlearning.PC.CTPC

addSepSetAndNodeAsParents, addSepSetAsParents, buildCompleteStructure, getIdentifier, getIdxFeatureVariables, getIdxParentsNode, getParametersAlgorithm, learn, learn, learnParentSetNode, retrieveParametersAndSuffStatistics, testNullStateToStateTransitionHypForGivenSepSet, testNullTimeToTransitionHypForGivenSepSet

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Details

MarkovBlanketCTPC

public MarkovBlanketCTPC(double sigTimeTransitionHypothesis,
 double sigStateToStateTransitionHypothesis)

Initialises the MB-CTPC algorithm by providing the significances to be used.

Parameters:

sigTimeTransitionHypothesis - significance level used for the null time to transition hypothesis

sigStateToStateTransitionHypothesis - significance level used for the null state-to-state transition hypothesis

Method Details

learn

public void learn(PGM<? extends Node> pgm)

Description copied from interface: StructureLearningAlgorithm

Learns the structure of a certain PGM.

Specified by:

learn in interface StructureLearningAlgorithm

Overrides:

learn in class CTPC

Parameters:

pgm - a probabilistic graphical model