Uses of Interface com.bayesserver.inference.InferenceFactory (bayesserver 11.1 API)

Packages that use InferenceFactory
Package	Description
com.bayesserver.analysis
com.bayesserver.causal
com.bayesserver.inference
com.bayesserver.learning.parameters
com.bayesserver.learning.structure
com.bayesserver.optimization

Uses of InferenceFactory in com.bayesserver.analysis

Methods in com.bayesserver.analysis that return InferenceFactory
Modifier and Type	Method	Description
`InferenceFactory`	ImpactOptions.`getFactory()`	Gets the inference factory which is used to create inference engines during an impact analysis.
`InferenceFactory`	LogLikelihoodAnalysisOptions.`getFactory()`	Gets the inference factory which is used to create inference engines during a Log-Likelihood analysis.
`InferenceFactory`	AssociationOptions.`getInferenceFactory()`	Gets the inference factory used for link strength calculations.
`InferenceFactory`	AutoInsightOptions.`getInferenceFactory()`	Gets the inference factory used for link strength calculations.
`InferenceFactory`	ClusterCountOptions.`getInferenceFactory()`	Gets the factory which is used to create inference engines during the cluster count tests.
`InferenceFactory`	InSampleAnomalyDetectionOptions.`getInferenceFactory()`	Gets the factory which is used to create inference engines during the in-sample anomaly detection process.

Methods in com.bayesserver.analysis with parameters of type InferenceFactory
Modifier and Type	Method	Description
`static AutoInsightOutput`	AutoInsight.`calculate(State target, List<Variable> testVariables, InferenceFactory factory)`	Uses comparison queries to automatically derive insight about a target variable from a trained network.
`static AutoInsightOutput`	AutoInsight.`calculate(State target, List<Variable> testVariables, InferenceFactory factory, Evidence evidence)`	Uses comparison queries to automatically derive insight about a target variable from a trained network.
`static ValueOfInformationOutput`	ValueOfInformation.`calculate(VariableContext hypothesis, List<VariableContext> testVariables, Evidence evidence, InferenceFactory factory, ValueOfInformationOptions options)`	Calculates value of information, which can be used to determine which variables are most likely to reduce the uncertainty of a particular variable.
`static ValueOfInformationOutput`	ValueOfInformation.`calculate(Variable hypothesis, List<Variable> testVariables, Evidence evidence, InferenceFactory factory, ValueOfInformationOptions options)`	Calculates value of information, which can be used to determine which variables are most likely to reduce the uncertainty of a particular variable.
`void`	ImpactOptions.`setFactory(InferenceFactory value)`	Sets the inference factory which is used to create inference engines during an impact analysis.
`void`	LogLikelihoodAnalysisOptions.`setFactory(InferenceFactory value)`	Sets the inference factory which is used to create inference engines during a Log-Likelihood analysis.
`void`	AssociationOptions.`setInferenceFactory(InferenceFactory value)`	Sets the inference factory used for link strength calculations.
`void`	AutoInsightOptions.`setInferenceFactory(InferenceFactory value)`	Sets the inference factory used for link strength calculations.
`void`	ClusterCountOptions.`setInferenceFactory(InferenceFactory value)`	Sets the factory which is used to create inference engines during the cluster count tests.
`void`	InSampleAnomalyDetectionOptions.`setInferenceFactory(InferenceFactory value)`	Sets the factory which is used to create inference engines during the in-sample anomaly detection process.

Constructors in com.bayesserver.analysis with parameters of type InferenceFactory
Constructor	Description
`SensitivityToParameters(Network network, InferenceFactory factory)`	Initializes a new instance of the `SensitivityToParameters` class .

Uses of InferenceFactory in com.bayesserver.causal

Classes in com.bayesserver.causal that implement InferenceFactory
Modifier and Type	Class	Description
`class`	`BackdoorInferenceFactory`	Uses the factory design pattern to create inference related objects for the Backdoor adjustment algorithm.
`class`	`DisjunctiveCauseInferenceFactory`	Uses the factory design pattern to create inference related objects for the Disjunctive cause algorithm.
`class`	`FrontDoorInferenceFactory`	Uses the factory design pattern to create inference related objects for the Front-door adjustment algorithm.

Methods in com.bayesserver.causal that return InferenceFactory
Modifier and Type	Method	Description
`InferenceFactory`	CausalQueryOptionsBase.`getCausalInferenceFactory()`	Factory that can create inference engines, used by estimation (adjustment) algorithms to perform queries on the Bayesian network.
`InferenceFactory`	AbductionOptions.`getInferenceFactory()`	Used to create an inference engine, to determine the values for the characterstic variables.

Methods in com.bayesserver.causal with parameters of type InferenceFactory
Modifier and Type	Method	Description
`static EffectsAnalysisOutput`	EffectsAnalysis.`calculate(Variable treatment, Variable outcome, CausalEffectKind effect, Evidence fixedEvidence, InferenceFactory factory, EffectsAnalysisOptions options)`	Calculate the causal effect on a target, varying for different treatment values.
`void`	CausalQueryOptionsBase.`setCausalInferenceFactory(InferenceFactory value)`	Factory that can create inference engines, used by estimation (adjustment) algorithms to perform queries on the Bayesian network.
`void`	AbductionOptions.`setInferenceFactory(InferenceFactory value)`	Used to create an inference engine, to determine the values for the characterstic variables.

Constructors in com.bayesserver.causal with parameters of type InferenceFactory
Constructor	Description
`CausalInferenceBase(Network network, InferenceFactory factory)`	Initializes a new instance of the `CausalInferenceBase` class.

Uses of InferenceFactory in com.bayesserver.inference

Classes in com.bayesserver.inference that implement InferenceFactory
Modifier and Type	Class	Description
`class`	`LikelihoodSamplingInferenceFactory`	Uses the factory design pattern to create inference related objects for the Likelihood Sampling algorithm.
`class`	`LoopyBeliefInferenceFactory`	Uses the factory design pattern to create inference related objects for the Loopy Belief algorithm.
`class`	`RelevanceTreeInferenceFactory`	Uses the factory design pattern to create inference related objects for the Relevance Tree algorithm.
`class`	`VariableEliminationInferenceFactory`	Uses the factory design pattern to create inference related objects for the Variable elimination algorithm.

Methods in com.bayesserver.inference that return InferenceFactory
Modifier and Type	Method	Description
`InferenceFactory`	LikelihoodSamplingQueryOptions.`getCausalInferenceFactory()`	Factory that can create inference engines, used by estimation (adjustment) algorithms to perform queries on the Bayesian network.
`InferenceFactory`	LoopyBeliefQueryOptions.`getCausalInferenceFactory()`	Factory that can create inference engines, used by estimation (adjustment) algorithms to perform queries on the Bayesian network.
`InferenceFactory`	QueryOptions.`getCausalInferenceFactory()`	Factory that can create inference engines, used by estimation (adjustment) algorithms to perform queries on the Bayesian network.
`InferenceFactory`	RelevanceTreeQueryOptions.`getCausalInferenceFactory()`	Factory that can create inference engines, used by estimation (adjustment) algorithms to perform queries on the Bayesian network.
`InferenceFactory`	TreeQueryOptions.`getCausalInferenceFactory()`	Factory that can create inference engines, used by estimation (adjustment) algorithms to perform queries on the Bayesian network.
`InferenceFactory`	VariableEliminationQueryOptions.`getCausalInferenceFactory()`	Factory that can create inference engines, used by estimation (adjustment) algorithms to perform queries on the Bayesian network.

Methods in com.bayesserver.inference with parameters of type InferenceFactory
Modifier and Type	Method	Description
`void`	LikelihoodSamplingQueryOptions.`setCausalInferenceFactory(InferenceFactory value)`	Factory that can create inference engines, used by estimation (adjustment) algorithms to perform queries on the Bayesian network.
`void`	LoopyBeliefQueryOptions.`setCausalInferenceFactory(InferenceFactory value)`	Factory that can create inference engines, used by estimation (adjustment) algorithms to perform queries on the Bayesian network.
`void`	QueryOptions.`setCausalInferenceFactory(InferenceFactory value)`	Factory that can create inference engines, used by estimation (adjustment) algorithms to perform queries on the Bayesian network.
`void`	RelevanceTreeQueryOptions.`setCausalInferenceFactory(InferenceFactory value)`	Factory that can create inference engines, used by estimation (adjustment) algorithms to perform queries on the Bayesian network.
`void`	TreeQueryOptions.`setCausalInferenceFactory(InferenceFactory value)`	Factory that can create inference engines, used by estimation (adjustment) algorithms to perform queries on the Bayesian network.
`void`	VariableEliminationQueryOptions.`setCausalInferenceFactory(InferenceFactory value)`	Factory that can create inference engines, used by estimation (adjustment) algorithms to perform queries on the Bayesian network.

Uses of InferenceFactory in com.bayesserver.learning.parameters

Methods in com.bayesserver.learning.parameters with parameters of type InferenceFactory
Modifier and Type	Method	Description
`static void`	ParameterLearning.`learnDistributedMapper(EvidencePartition<DistributedMapperContext> partition, NameValuesReader configuration, NameValuesWriter output, InferenceFactory factory)`	This method should be called during distributed parameter learning on a distributed partition.

Constructors in com.bayesserver.learning.parameters with parameters of type InferenceFactory
Constructor	Description
`OnlineLearning(Network network, InferenceFactory factory)`	Initializes a new instance of the `OnlineLearning` class.
`ParameterLearning(Network network, InferenceFactory factory)`	Initializes a new instance of the `ParameterLearning` class.

Uses of InferenceFactory in com.bayesserver.learning.structure

Methods in com.bayesserver.learning.structure that return InferenceFactory
Modifier and Type	Method	Description
`InferenceFactory`	ClusteringStructuralLearningOptions.`getInferenceFactory()`	Gets the inference factory used during scoring.
`InferenceFactory`	HierarchicalStructuralLearningOptions.`getInferenceFactory()`	Gets the inference factory used during scoring.
`InferenceFactory`	SearchStructuralLearningOptions.`getInferenceFactory()`	Gets the inference factory used during scoring.

Methods in com.bayesserver.learning.structure with parameters of type InferenceFactory
Modifier and Type	Method	Description
`void`	ClusteringStructuralLearningOptions.`setInferenceFactory(InferenceFactory value)`	Sets the inference factory used during scoring.
`void`	HierarchicalStructuralLearningOptions.`setInferenceFactory(InferenceFactory value)`	Sets the inference factory used during scoring.
`void`	SearchStructuralLearningOptions.`setInferenceFactory(InferenceFactory value)`	Sets the inference factory used during scoring.

Uses of InferenceFactory in com.bayesserver.optimization

Methods in com.bayesserver.optimization that return InferenceFactory
Modifier and Type	Method	Description
`InferenceFactory`	GeneticOptionsBase.`getInferenceFactory()`	Used to create one or more inference engines, used by the algorithm to determine the fitness of possible solutions.
`InferenceFactory`	OptimizerOptions.`getInferenceFactory()`	Creates one or more inference engines used by the optimization algorithm.

Methods in com.bayesserver.optimization with parameters of type InferenceFactory
Modifier and Type	Method	Description
`void`	GeneticOptionsBase.`setInferenceFactory(InferenceFactory value)`	Used to create one or more inference engines, used by the algorithm to determine the fitness of possible solutions.
`void`	OptimizerOptions.`setInferenceFactory(InferenceFactory value)`	Creates one or more inference engines used by the optimization algorithm.