Uses of Interface com.bayesserver.data.EvidenceReaderCommand (bayesserver 11.0 API)

Packages that use EvidenceReaderCommand
Package	Description
com.bayesserver.analysis
com.bayesserver.data
com.bayesserver.learning.parameters
com.bayesserver.learning.structure

Uses of EvidenceReaderCommand in com.bayesserver.analysis

Methods in com.bayesserver.analysis that return EvidenceReaderCommand
Modifier and Type	Method	Description
`EvidenceReaderCommand`	ClusterCountActions.`createEvidenceReaderCommand(Network networkCopy, DataPartitioning partitioning)`	A user supplied function to create an evidence reader command based on a copy of the original network.

Methods in com.bayesserver.analysis with parameters of type EvidenceReaderCommand
Modifier and Type	Method	Description
`void`	ClusterCountActions.`learn(Network networkCopy, EvidenceReaderCommand evidenceReaderCommand)`	A user supplied function to learn the paramters of a copy of the original network based on a training partition of the data.
`void`	InSampleAnomalyDetectionActions.`learn(Network networkCopy, EvidenceReaderCommand evidenceReaderCommand)`	A user supplied function to learn the paramters of a copy of the original network based on a training partition of the data.

Uses of EvidenceReaderCommand in com.bayesserver.data

Classes in com.bayesserver.data that implement EvidenceReaderCommand
Modifier and Type	Class	Description
`class`	`DefaultEvidenceReaderCommand`	Creates instances of `EvidenceReader` on demand.

Methods in com.bayesserver.data that return EvidenceReaderCommand
Modifier and Type	Method	Description
`EvidenceReaderCommand`	DataTableEvidenceReaderCommandFactory.`create(Network network)`	Create an evidence reader command, based on a specific network which may be a copy of the original.
`EvidenceReaderCommand`	EvidenceReaderCommandFactory.`create(Network network)`	Create an evidence reader command, based on a specific network which may be a copy of the original.
`EvidenceReaderCommand`	DataTableEvidenceReaderCommandFactory.`createPartitioned(Network network, DataPartitioning dataPartitioning, int partitionCount)`	Create an evidence reader command on a partition, based on a specific network which may be a copy of the original.
`EvidenceReaderCommand`	EvidenceReaderCommandFactory.`createPartitioned(Network network, DataPartitioning dataPartitioning, int partitionCount)`	Create an evidence reader command on a partition, based on a specific network which may be a copy of the original.

Uses of EvidenceReaderCommand in com.bayesserver.learning.parameters

Methods in com.bayesserver.learning.parameters with parameters of type EvidenceReaderCommand
Modifier and Type	Method	Description
`ParameterLearningOutput`	ParameterLearning.`learn(EvidenceReaderCommand readerCommand, ParameterLearningOptions options)`	Learns the parameters of a Bayesian network or Dynamic Bayesian network, from data.
`ParameterLearningOutput`	ParameterLearning.`learn(EvidenceReaderCommand readerCommand, List<DistributionSpecification> distributionSpecifications, ParameterLearningOptions options)`	Learns the parameters of a Bayesian network or Dynamic Bayesian network, from data.

Uses of EvidenceReaderCommand in com.bayesserver.learning.structure

Methods in com.bayesserver.learning.structure with parameters of type EvidenceReaderCommand
Modifier and Type	Method	Description
`static FeatureSelectionOutput`	FeatureSelection.`detect(List<Variable> variables, EvidenceReaderCommand evidenceReaderCommand, Variable target, FeatureSelectionOptions options)`	Determines which variables are likely to be good features (predictors) of a target variable.
`StructuralLearningOutput`	ChowLiuStructuralLearning.`learn(EvidenceReaderCommand evidenceReaderCommand, List<Node> nodes, StructuralLearningOptions options)`	Learn the structure (links) of a Bayesian network.
`StructuralLearningOutput`	ClusteringStructuralLearning.`learn(EvidenceReaderCommand evidenceReaderCommand, List<Node> nodes, StructuralLearningOptions options)`	Learn the structure (links) of a Bayesian network.
`StructuralLearningOutput`	HierarchicalStructuralLearning.`learn(EvidenceReaderCommand evidenceReaderCommand, List<Node> nodes, StructuralLearningOptions options)`	Learn the structure (links) of a Bayesian network.
`StructuralLearningOutput`	PCStructuralLearning.`learn(EvidenceReaderCommand evidenceReaderCommand, List<Node> nodes, StructuralLearningOptions options)`	Learn the structure (links) of a Bayesian network.
`StructuralLearningOutput`	SearchStructuralLearning.`learn(EvidenceReaderCommand evidenceReaderCommand, List<Node> nodes, StructuralLearningOptions options)`	Learn the structure (links) of a Bayesian network.
`StructuralLearningOutput`	StructuralLearning.`learn(EvidenceReaderCommand evidenceReaderCommand, List<Node> nodes, StructuralLearningOptions options)`	Learn the structure (links) of a Bayesian network.
`StructuralLearningOutput`	TANStructuralLearning.`learn(EvidenceReaderCommand evidenceReaderCommand, List<Node> nodes, StructuralLearningOptions options)`	Learn the structure (links) of a Bayesian network.