Module es.upm.fi.cig.multictbnc

Package es.upm.fi.cig.multictbnc.learning.parameters.bn

Class BNParameterLearningAlgorithm

java.lang.Object

es.upm.fi.cig.multictbnc.learning.parameters.bn.BNParameterLearningAlgorithm

All Implemented Interfaces:

ParameterLearningAlgorithm

Direct Known Subclasses:

BNBayesianEstimation, BNMaximumLikelihoodEstimation

public abstract class BNParameterLearningAlgorithm
extends Object
implements ParameterLearningAlgorithm

Defines methods for parameter learning algorithms of discrete Bayesian networks.

Constructor Summary

Constructors

Constructor	Description
BNParameterLearningAlgorithm()

Method Summary

Modifier and Type	Method	Description
protected abstract BNSufficientStatistics	getSufficientStatisticsNode(DiscreteStateNode node, Dataset dataset)	Returns the sufficient statistics of a DiscreteNode for a given Dataset.
void	learn(Node node, Dataset dataset)	Learns the parameters of a certain node of a PGM.
void	learn(List<? extends Node> nodes, Dataset dataset)	Learns the parameters of a certain PGM.
void	setSufficientStatistics(Node node, Dataset dataset)	Obtains the sufficient statistics of a BN node.
void	setSufficientStatistics(List<? extends Node> nodes, Dataset dataset)	Obtains for each node the number of times it takes a certain state while its parents take a certain instantiation.

Methods inherited from class java.lang.Object

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

Methods inherited from interface es.upm.fi.cig.multictbnc.learning.parameters.ParameterLearningAlgorithm

getIdentifier, getNameMethod, getParametersAlgorithm

Constructor Details

BNParameterLearningAlgorithm

public BNParameterLearningAlgorithm()

Method Details

setSufficientStatistics

public void setSufficientStatistics(List<? extends Node> nodes,
 Dataset dataset)

Obtains for each node the number of times it takes a certain state while its parents take a certain instantiation.

Parameters:

nodes - list of nodes

dataset - dataset from which the sufficient statistics are extracted

learn

public void learn(Node node,
 Dataset dataset)

Description copied from interface: ParameterLearningAlgorithm

Learns the parameters of a certain node of a PGM.

Specified by:

learn in interface ParameterLearningAlgorithm

Parameters:

node - node of the PGM

dataset - dataset used to learn the parameters

learn

public void learn(List<? extends Node> nodes,
 Dataset dataset)

Description copied from interface: ParameterLearningAlgorithm

Learns the parameters of a certain PGM.

Specified by:

learn in interface ParameterLearningAlgorithm

Parameters:

nodes - nodes of the PGM

dataset - dataset used to learn the parameters

setSufficientStatistics

public void setSufficientStatistics(Node node,
 Dataset dataset)

Description copied from interface: ParameterLearningAlgorithm

Obtains the sufficient statistics of a BN node.

Specified by:

setSufficientStatistics in interface ParameterLearningAlgorithm

Parameters:

node - node whose sufficient statistics will be computed

dataset - dataset used to compute the sufficient statistics

getSufficientStatisticsNode

protected abstract BNSufficientStatistics getSufficientStatisticsNode(DiscreteStateNode node,
 Dataset dataset)

Returns the sufficient statistics of a DiscreteNode for a given Dataset.

Parameters:

node - a DiscreteNode

dataset - dataset from which the sufficient statistics are extracted

Returns:

sufficient statistics of the provided node