Package | Description |
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com.bayesserver.causal | |
com.bayesserver.inference |
Modifier and Type | Class and Description |
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class |
BackdoorInference
Estimates the causal effect, using the 'Backdoor Adjustment' formula to avoid confounding bias.
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class |
CausalInferenceBase
Base class for Causal inference engines used by internal algorithms.
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class |
DisjunctiveCauseInference
Estimates the causal effect, using the 'Disjunctive Cause Criterion' adjustment formula to avoid confounding bias.
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class |
FrontDoorInference
Estimates the causal effect, using the 'Front-door Adjustment' formula to avoid confounding bias.
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Modifier and Type | Method and Description |
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Inference |
BackdoorInferenceFactory.createInferenceEngine(Network network)
Creates an instance of an inference algorithm, with the [network] as it's target.
|
Inference |
DisjunctiveCauseInferenceFactory.createInferenceEngine(Network network)
Creates an instance of an inference algorithm, with the [network] as it's target.
|
Inference |
FrontDoorInferenceFactory.createInferenceEngine(Network network)
Creates an instance of an inference algorithm, with the [network] as it's target.
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Modifier and Type | Class and Description |
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class |
LikelihoodSamplingInference
An approximate probabilistic inference algorithm for Bayesian networks and Dynamic Bayesian networks, based on Likelihood Sampling.
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class |
LoopyBeliefInference
An approximate but deterministic probabilistic inference algorithm for Bayesian networks and Dynamic Bayesian networks based on Loopy Belief Propagation.
|
class |
RelevanceTreeInference
An exact probabilistic inference algorithm for Bayesian networks and Dynamic Bayesian networks, that can compute multiple distributions more efficiently than the
VariableEliminationInference algorithm. |
class |
VariableEliminationInference
An exact inference algorithm for Bayesian networks and Dynamic Bayesian networks, loosely based on the Variable Elimination algorithm.
|
Modifier and Type | Method and Description |
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Inference |
InferenceFactory.createInferenceEngine(Network network)
Creates an instance of an inference algorithm, with the [network] as it's target.
|
Inference |
LikelihoodSamplingInferenceFactory.createInferenceEngine(Network network)
Creates an instance of an inference algorithm, with the [network] as it's target.
|
Inference |
LoopyBeliefInferenceFactory.createInferenceEngine(Network network)
Creates an instance of an inference algorithm, with the [network] as it's target.
|
Inference |
RelevanceTreeInferenceFactory.createInferenceEngine(Network network)
Uses the factory design pattern to create inference related objects for the Relevance Tree algorithm.
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Inference |
VariableEliminationInferenceFactory.createInferenceEngine(Network network)
Uses the factory design pattern to create inference related objects for the Variable elimination algorithm.
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Inference |
QueryLifecycleBegin.getInference()
The current inference engine.
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Inference |
QueryLifecycleBeginBase.getInference()
The current inference engine.
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Inference |
QueryLifecycleEnd.getInference()
The current inference engine.
|
Inference |
QueryLifecycleEndBase.getInference()
The current inference engine.
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Constructor and Description |
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QueryLifecycleBeginBase(Inference inference,
QueryOptions queryOptions)
For internal use.
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QueryLifecycleEndBase(Inference inference,
QueryOptions queryOptions,
QueryOutput queryOutput)
For internal use.
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