com.bayesserver.learning.structure

Class HierarchicalStructuralLearning

java.lang.Object

com.bayesserver.learning.structure.HierarchicalStructuralLearning

All Implemented Interfaces:

StructuralLearning

public final class HierarchicalStructuralLearning
extends Object
implements StructuralLearning

A structural learning algorithm for Bayesian networks that groups subsets of nodes into a hierarchy.

Constructor Summary

Constructors

Constructor and Description
HierarchicalStructuralLearning()

Method Summary

Modifier and Type	Method and Description
StructuralLearningOutput	learn(EvidenceReaderCommandFactory evidenceReaderCommandFactory, List<Node> nodes, StructuralLearningOptions options) Learn the structure (links) of a Bayesian network.
StructuralLearningOutput	learn(EvidenceReaderCommand evidenceReaderCommand, List<Node> nodes, StructuralLearningOptions options) Learn the structure (links) of a Bayesian network.

Methods inherited from class java.lang.Object

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

Constructor Detail

HierarchicalStructuralLearning

public HierarchicalStructuralLearning()

Method Detail

learn

public StructuralLearningOutput learn(EvidenceReaderCommand evidenceReaderCommand,
                                      List<Node> nodes,
                                      StructuralLearningOptions options)

Learn the structure (links) of a Bayesian network.

Specified by:

learn in interface StructuralLearning

Parameters:

evidenceReaderCommand - Can create a reader which iterates round the data used to learn the network.

nodes - The nodes to be considered for links.

options - Options for the structural learning algorithm.

Returns:

The output generated by the structural learning algorithm.

learn

public StructuralLearningOutput learn(EvidenceReaderCommandFactory evidenceReaderCommandFactory,
                                      List<Node> nodes,
                                      StructuralLearningOptions options)

Learn the structure (links) of a Bayesian network.

Parameters:

evidenceReaderCommandFactory - Creates new evidence reader commands, which may be partitioned for use in cross validation.

nodes - The nodes to be considered for links.

options - Options for the structural learning algorithm.

Returns:

The output generated by the structural learning algorithm.