All Known Implementing Classes:

BackdoorQueryOptions, CausalQueryOptionsBase, DisjunctiveCauseQueryOptions, FrontDoorQueryOptions, LikelihoodSamplingQueryOptions, LoopyBeliefQueryOptions, RelevanceTreeQueryOptions, TreeQueryOptions, VariableEliminationQueryOptions
```
public interface QueryOptions
```
Options that govern the calculations performed by Inference.query(com.bayesserver.inference.QueryOptions, com.bayesserver.inference.QueryOutput).

Method Summary

All Methods Instance Methods Abstract Methods
Modifier and Type	Method	Description
`Cancellation`	`getCancellation()`	Allows cancellation of a query.
`CausalEffectKind`	`getCausalEffectKind()`	Gets the kind of effect to calculate.
`InferenceFactory`	`getCausalInferenceFactory()`	Factory that can create inference engines, used by estimation (adjustment) algorithms to perform queries on the Bayesian network.
`boolean`	`getConflict()`	Gets a value indicating whether the conflict measure should be calculated in a call to `Inference.query(com.bayesserver.inference.QueryOptions, com.bayesserver.inference.QueryOutput)`.
`DecisionAlgorithm`	`getDecisionAlgorithm()`	Gets the algorithm to use when a network contains Decision nodes.
`InconsistentEvidenceMode`	`getInconsistentEvidenceMode()`	Determines when an `InconsistentEvidenceException` is raised.
`boolean`	`getLogLikelihood()`	Gets a value indicating whether the log-likelihood of a case should be calculated in a call to `Inference.query(com.bayesserver.inference.QueryOptions, com.bayesserver.inference.QueryOutput)`.
`PropagationMethod`	`getPropagation()`	Gets the propagation method to be used during inference.
`QueryEvidenceMode`	`getQueryEvidenceMode()`	Determines whether evidence is retracted for each query.
`Integer`	`getTerminalTime()`	Gets the terminal time, which is the time at which any terminal nodes in a Dynamic Bayesian Network connect to temporal nodes.
`void`	`setCancellation(Cancellation value)`	Allows cancellation of a query.
`void`	`setCausalEffectKind(CausalEffectKind value)`	Sets the kind of effect to calculate.
`void`	`setCausalInferenceFactory(InferenceFactory value)`	Factory that can create inference engines, used by estimation (adjustment) algorithms to perform queries on the Bayesian network.
`void`	`setConflict(boolean value)`	Sets a value indicating whether the conflict measure should be calculated in a call to `Inference.query(com.bayesserver.inference.QueryOptions, com.bayesserver.inference.QueryOutput)`.
`void`	`setDecisionAlgorithm(DecisionAlgorithm value)`	Sets the algorithm to use when a network contains Decision nodes.
`void`	`setInconsistentEvidenceMode(InconsistentEvidenceMode value)`	Determines when an `InconsistentEvidenceException` is raised.
`void`	`setLogLikelihood(boolean value)`	Sets a value indicating whether the log-likelihood of a case should be calculated in a call to `Inference.query(com.bayesserver.inference.QueryOptions, com.bayesserver.inference.QueryOutput)`.
`void`	`setPropagation(PropagationMethod value)`	Sets the propagation method to be used during inference.
`void`	`setQueryEvidenceMode(QueryEvidenceMode value)`	Determines whether evidence is retracted for each query.
`void`	`setTerminalTime(Integer value)`	Sets the terminal time, which is the time at which any terminal nodes in a Dynamic Bayesian Network connect to temporal nodes.

- Method Detail
  - getLogLikelihood
```
boolean getLogLikelihood()
```
    Gets a value indicating whether the log-likelihood of a case should be calculated in a call to Inference.query(com.bayesserver.inference.QueryOptions, com.bayesserver.inference.QueryOutput). If calculated the result can be obtained from QueryOutput.getLogLikelihood().
    This should only be requested if required.
    
    The natural log (base e) is calculated.
    
    Returns:
    
    true if the log-likelihood should be calculated; otherwise, false. Defaults to false.
  - setLogLikelihood
```
void setLogLikelihood(boolean value)
```
    Sets a value indicating whether the log-likelihood of a case should be calculated in a call to Inference.query(com.bayesserver.inference.QueryOptions, com.bayesserver.inference.QueryOutput). If calculated the result can be obtained from QueryOutput.getLogLikelihood().
    This should only be requested if required.
    
    The natural log (base e) is calculated.
    
    Parameters:
    
    value - true if the log-likelihood should be calculated; otherwise, false. Defaults to false.
  - getPropagation
```
PropagationMethod getPropagation()
```
    Gets the propagation method to be used during inference. Default is PropagationMethod.SUM.
  - setPropagation
```
void setPropagation(PropagationMethod value)
```
    Sets the propagation method to be used during inference. Default is PropagationMethod.SUM.
  - getDecisionAlgorithm
```
DecisionAlgorithm getDecisionAlgorithm()
```
    Gets the algorithm to use when a network contains Decision nodes.
  - setDecisionAlgorithm
```
void setDecisionAlgorithm(DecisionAlgorithm value)
```
    Sets the algorithm to use when a network contains Decision nodes.
  - getConflict
```
boolean getConflict()
```
    Gets a value indicating whether the conflict measure should be calculated in a call to Inference.query(com.bayesserver.inference.QueryOptions, com.bayesserver.inference.QueryOutput). If calculated the result can be obtained from QueryOutput.getConflict().
    Conflict is a measure that detects evidence that is conflicting or rare. The greater the conflict value above zero, the more likely the evidence is in conflict, or rare.
    
    Conflict = log((P(e1)P(e2)...P(ei)) / P(e)), where P(e1), P(e2) etc... are the likelihoods of each variable considered in isolation, and P(e) is the likelihood of the all the evidence together.
  - setConflict
```
void setConflict(boolean value)
```
    Sets a value indicating whether the conflict measure should be calculated in a call to Inference.query(com.bayesserver.inference.QueryOptions, com.bayesserver.inference.QueryOutput). If calculated the result can be obtained from QueryOutput.getConflict().
    Conflict is a measure that detects evidence that is conflicting or rare. The greater the conflict value above zero, the more likely the evidence is in conflict, or rare.
    
    Conflict = log((P(e1)P(e2)...P(ei)) / P(e)), where P(e1), P(e2) etc... are the likelihoods of each variable considered in isolation, and P(e) is the likelihood of the all the evidence together.
  - getQueryEvidenceMode
```
QueryEvidenceMode getQueryEvidenceMode()
```
    Determines whether evidence is retracted for each query. See QueryEvidenceMode for more information.
  - setQueryEvidenceMode
```
void setQueryEvidenceMode(QueryEvidenceMode value)
```
    Determines whether evidence is retracted for each query. See QueryEvidenceMode for more information.
  - getInconsistentEvidenceMode
```
InconsistentEvidenceMode getInconsistentEvidenceMode()
```
    Determines when an InconsistentEvidenceException is raised.
  - setInconsistentEvidenceMode
```
void setInconsistentEvidenceMode(InconsistentEvidenceMode value)
```
    Determines when an InconsistentEvidenceException is raised.
  - getCancellation
```
Cancellation getCancellation()
```
    Allows cancellation of a query. When cancelled, a CancellationException will be raised.
    If Cancellation.getCancel() has been set to true, it should be reset to false, before a subsequent query.
  - setCancellation
```
void setCancellation(Cancellation value)
```
    Allows cancellation of a query. When cancelled, a CancellationException will be raised.
    If Cancellation.getCancel() has been set to true, it should be reset to false, before a subsequent query.
  - getTerminalTime
```
Integer getTerminalTime()
```
    Gets the terminal time, which is the time at which any terminal nodes in a Dynamic Bayesian Network connect to temporal nodes.
  - setTerminalTime
```
void setTerminalTime(Integer value)
```
    Sets the terminal time, which is the time at which any terminal nodes in a Dynamic Bayesian Network connect to temporal nodes.
  - getCausalEffectKind
```
CausalEffectKind getCausalEffectKind()
```
    Gets the kind of effect to calculate. e.g. Total/Direct. Not all algorithms support direct effect calculations.
  - setCausalEffectKind
```
void setCausalEffectKind(CausalEffectKind value)
```
    Sets the kind of effect to calculate. e.g. Total/Direct. Not all algorithms support direct effect calculations.
  - getCausalInferenceFactory
```
InferenceFactory getCausalInferenceFactory()
```
    Factory that can create inference engines, used by estimation (adjustment) algorithms to perform queries on the Bayesian network.
  - setCausalInferenceFactory
```
void setCausalInferenceFactory(InferenceFactory value)
```
    Factory that can create inference engines, used by estimation (adjustment) algorithms to perform queries on the Bayesian network.

Interface QueryOptions

Method Summary

Method Detail

getLogLikelihood

setLogLikelihood

getPropagation

setPropagation

getDecisionAlgorithm

setDecisionAlgorithm

getConflict

setConflict

getQueryEvidenceMode

setQueryEvidenceMode

getInconsistentEvidenceMode

setInconsistentEvidenceMode

getCancellation

setCancellation

getTerminalTime

setTerminalTime

getCausalEffectKind

setCausalEffectKind

getCausalInferenceFactory

setCausalInferenceFactory