Package com.bayesserver.learning.structure

Interface Summary

Interface	Description
LinkOutput	Contains information about a link returned from a structural learning algorithm.
StructuralLearning	Defines methods for learning the structure (links) of a Bayesian network.
StructuralLearningOptions	Options governing a structural learning algorithm.
StructuralLearningOutput	Contains information returned from a structural learning algorithm.
StructuralLearningProgress	Interface to provide progress information during structural learning.
StructuralLearningProgressInfo	Interface to provide progress information during structural learning.

Class Summary

Class	Description
ChowLiuLinkOutput	Contains information about a new link learnt using the com.bayesserver.learning.structure.chowliu.ChowLiuStructuralLearning algorithm.
ChowLiuStructuralLearning	A structural learning algorithm for Bayesian networks based on the Chow-Liu algorithm.
ChowLiuStructuralLearningOptions	Options for structural learning with the com.bayesserver.learning.structure.chowliu.ChowLiuStructuralLearning class.
ChowLiuStructuralLearningOutput	Contains information returned from the com.bayesserver.learning.structure.chowliu.ChowLiuStructuralLearning algorithm.
ChowLiuStructuralLearningProgressInfo	Progress information returned from the Chow-Liu structural learning algorithm.
ClusteringLinkOutput	Contains information about a new link learnt using the com.bayesserver.learning.structure.clustering.ClusteringStructuralLearning algorithm.
ClusteringStructuralLearning	A structural learning algorithm for a cluster model (a.k.a mixture model).
ClusteringStructuralLearningOptions	Options for structural learning with the com.bayesserver.learning.structure.clustering.ClusteringStructuralLearning class.
ClusteringStructuralLearningOutput	Contains information returned from the com.bayesserver.learning.structure.clustering.ClusteringStructuralLearning algorithm.
ClusteringStructuralLearningProgressInfo	Progress information returned from the Clustering structural learning algorithm.
FeatureSelection	Contains methods to determine which variables are likely to be good features (predictors) or not.
FeatureSelectionOptions	Options governing the tests carried out to determine whether variables are likely to be features (predictors) of a target variable.
FeatureSelectionOutput	Contains information returned by FeatureSelection.detect(java.util.List<com.bayesserver.Variable>, com.bayesserver.data.EvidenceReaderCommand, com.bayesserver.Variable, com.bayesserver.learning.structure.FeatureSelectionOptions) about feature selection tests.
FeatureSelectionTest	Contains information about a test carried out between a variable and a target to determine whether the variable is likely to be a feature or not.
HierarchicalLinkOutput	Contains information about a new link learnt using the com.bayesserver.learning.structure.hierarchical.HierarchicalStructuralLearning algorithm.
HierarchicalStructuralLearning	A structural learning algorithm for Bayesian networks that groups subsets of nodes into a hierarchy.
HierarchicalStructuralLearningOptions	Options for structural learning with the com.bayesserver.learning.structure.hierarchical.HierarchicalStructuralLearning class.
HierarchicalStructuralLearningOutput	Contains information returned from the com.bayesserver.learning.structure.hierarchical.HierarchicalStructuralLearning algorithm.
HierarchicalStructuralLearningProgressInfo	Progress information returned from the Hierarchical structural learning algorithm.
IndependenceOptions	Options governing independence and conditional independence tests.
LinkConstraint	Defines a constraint on a link between two nodes during structural learning.
LinkConstraintCollection	A collection of link constraints.
PCLinkOutput	Contains information about a new link learnt using the com.bayesserver.learning.structure.pc.PCStructuralLearning algorithm.
PCStructuralLearning	A structural learning algorithm for Bayesian networks based on the PC algorithm.
PCStructuralLearningOptions	Options for structural learning with the com.bayesserver.learning.structure.pc.PCStructuralLearning class.
PCStructuralLearningOutput	Contains information returned from the com.bayesserver.learning.structure.pc.PCStructuralLearning algorithm.
PCStructuralLearningProgressInfo	Progress information returned from the PC structural learning algorithm.
SearchLinkOutput	Contains information about a new link learnt using the com.bayesserver.learning.structure.search.SearchStructuralLearning algorithm.
SearchStructuralLearning	A structural learning algorithm for Bayesian networks based on Search and Score.
SearchStructuralLearningOptions	Options for structural learning with the com.bayesserver.learning.structure.search.SearchStructuralLearning class.
SearchStructuralLearningOutput	Contains information returned from the com.bayesserver.learning.structure.search.SearchStructuralLearning algorithm.
SearchStructuralLearningProgressInfo	Progress information returned from the Search based structural learning algorithm.
TANLinkOutput	Contains information about a new link learnt using the com.bayesserver.learning.structure.tan.TANStructuralLearning algorithm.
TANStructuralLearning	A structural learning algorithm for Bayesian networks based on the Tree augmented naive Bayes (TAN) algorithm.
TANStructuralLearningOptions	Options for structural learning with the com.bayesserver.learning.structure.tan.TANStructuralLearning class.
TANStructuralLearningOutput	Contains information returned from the com.bayesserver.learning.structure.tan.TANStructuralLearning algorithm.
TANStructuralLearningProgressInfo	Progress information returned from the TAN structural learning algorithm.

Enum Summary

Enum	Description
LinkConstraintFailureMode	Determines the action taken if a link constraint cannot be honoured.
LinkConstraintMethod	Determines how a link is constrained.
ScoreMethod	The scoring mechanism used to evaluate different Bayesian network structures during a search.