c

com.cra.figaro.algorithm.factored

ProbQueryVariableElimination

class ProbQueryVariableElimination extends OneTimeProbQuery with ProbabilisticVariableElimination

Variable elimination algorithm that computes the conditional probability of query elements.

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Inherited
  1. ProbQueryVariableElimination
  2. ProbabilisticVariableElimination
  3. VariableElimination
  4. FactoredAlgorithm
  5. OneTimeProbQuery
  6. OneTime
  7. ProbQueryAlgorithm
  8. BaseProbQueryAlgorithm
  9. Algorithm
  10. AnyRef
  11. Any
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Visibility
  1. Public
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Instance Constructors

  1. new ProbQueryVariableElimination(universe: Universe, targets: Element[_]*)(showTiming: Boolean, dependentUniverses: List[(Universe, List[NamedEvidence[_]])], dependentAlgorithm: (Universe, List[NamedEvidence[_]]) ⇒ () ⇒ Double)

Type Members

  1. class NotATargetException [T] extends AlgorithmException
    Definition Classes
    BaseProbQueryAlgorithm

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  4. val active: Boolean
    Attributes
    protected
    Definition Classes
    Algorithm
  5. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  6. def check[T](target: Element[T]): Unit
    Attributes
    protected
    Definition Classes
    BaseProbQueryAlgorithm
  7. def cleanUp(): Unit

    Called when the algorithm is killed.

    Called when the algorithm is killed. By default, does nothing. Can be overridden.

    Definition Classes
    Algorithm
  8. def clone(): AnyRef
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  9. val comparator: Option[(Double, Double) ⇒ Boolean]

    Some variable elimination algorithms, such as computing the most probable explanation, record values of variables as they are eliminated.

    Some variable elimination algorithms, such as computing the most probable explanation, record values of variables as they are eliminated. Such values are stored in a factor that maps values of the other variables to a value of the eliminated variable. This factor is produced by finding the value of the variable that "maximizes" the entry associated with the value in the product factor resulting from eliminating this variable, for some maximization function. The recordingFunction determines which of two entries is greater according to the maximization function. It returns true iff the second entry is greater. The recording function is an option so that variable elimination algorithms that do not use it can ignore it.

    Definition Classes
    VariableElimination
  10. def computeDistribution[T](target: Element[T]): Stream[(Double, T)]

    Computes the normalized distribution over a single target element.

    Computes the normalized distribution over a single target element.

    Definition Classes
    ProbQueryVariableEliminationBaseProbQueryAlgorithm
  11. def computeExpectation[T](target: Element[T], function: (T) ⇒ Double): Double

    Computes the expectation of a given function for single target element.

    Computes the expectation of a given function for single target element.

    Definition Classes
    ProbQueryVariableEliminationBaseProbQueryAlgorithm
  12. def computeProbability[T](target: Element[T], predicate: (T) ⇒ Boolean): Double

    Return an estimate of the probability of the predicate under the marginal probability distribution of the target.

    Return an estimate of the probability of the predicate under the marginal probability distribution of the target.

    Definition Classes
    BaseProbQueryAlgorithm
  13. def computeProjection[T](target: Element[T]): List[(T, Double)]
    Attributes
    protected[com.cra.figaro.algorithm]
    Definition Classes
    BaseProbQueryAlgorithm
  14. val debug: Boolean

    By default, implementations that inherit this trait have no debug information.

    By default, implementations that inherit this trait have no debug information. Override this if you want a debugging option.

    Definition Classes
    VariableElimination
  15. val dependentAlgorithm: (Universe, List[NamedEvidence[_]]) ⇒ () ⇒ Double
  16. val dependentUniverses: List[(Universe, List[NamedEvidence[_]])]
  17. def distribution[T](target: Element[T]): Stream[(Double, T)]

    Return an estimate of the marginal probability distribution over the target that lists each element with its probability.

    Return an estimate of the marginal probability distribution over the target that lists each element with its probability. The result is a lazy stream. It is up to the algorithm how the stream is ordered. Throws NotATargetException if called on a target that is not in the list of targets of the algorithm. Throws AlgorithmInactiveException if the algorithm is inactive.

    Definition Classes
    BaseProbQueryAlgorithm
  18. def doDistribution[T](target: Element[T]): Stream[(Double, T)]
    Attributes
    protected
    Definition Classes
    OneTimeProbQueryBaseProbQueryAlgorithm
  19. def doElimination(allFactors: List[Factor[Double]], targetVariables: Seq[Variable[_]]): Unit
    Attributes
    protected
    Definition Classes
    VariableElimination
  20. def doExpectation[T](target: Element[T], function: (T) ⇒ Double): Double
    Attributes
    protected
    Definition Classes
    OneTimeProbQueryBaseProbQueryAlgorithm
  21. def doKill(): Unit
    Attributes
    protected[com.cra.figaro.algorithm]
    Definition Classes
    OneTimeAlgorithm
  22. def doProbability[T](target: Element[T], predicate: (T) ⇒ Boolean): Double
    Attributes
    protected
    Definition Classes
    OneTimeProbQueryBaseProbQueryAlgorithm
  23. def doProjection[T](target: Element[T]): List[(T, Double)]
    Attributes
    protected
    Definition Classes
    OneTimeProbQueryBaseProbQueryAlgorithm
  24. def doResume(): Unit
    Attributes
    protected[com.cra.figaro.algorithm]
    Definition Classes
    OneTimeAlgorithm
  25. def doStart(): Unit
    Attributes
    protected[com.cra.figaro.algorithm]
    Definition Classes
    OneTimeAlgorithm
  26. def doStop(): Unit
    Attributes
    protected[com.cra.figaro.algorithm]
    Definition Classes
    OneTimeAlgorithm
  27. def eliminateInOrder(order: List[Variable[_]], factors: MultiSet[Factor[Double]], map: FactorMap[Double]): MultiSet[Factor[Double]]
    Attributes
    protected
    Definition Classes
    VariableElimination
  28. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  29. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  30. def expectation[T](target: Element[T])(function: (T) ⇒ Double, c: Any = DummyImplicit): Double

    Return an estimate of the expectation of the function under the marginal probability distribution of the target.

    Return an estimate of the expectation of the function under the marginal probability distribution of the target. Throws NotATargetException if called on a target that is not in the list of targets of the algorithm. Throws AlgorithmInactiveException if the algorithm is inactive.

    Definition Classes
    BaseProbQueryAlgorithm
  31. def expectation[T](target: Element[T], function: (T) ⇒ Double): Double

    Return an estimate of the expectation of the function under the marginal probability distribution of the target.

    Return an estimate of the expectation of the function under the marginal probability distribution of the target. Throws NotATargetException if called on a target that is not in the list of targets of the algorithm. Throws AlgorithmInactiveException if the algorithm is inactive.

    Definition Classes
    BaseProbQueryAlgorithm
  32. def finalize(): Unit
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  33. def finish(factorsAfterElimination: MultiSet[Factor[Double]], eliminationOrder: List[Variable[_]]): Unit

    All implementation of variable elimination must specify what to do after variables have been eliminated.

    All implementation of variable elimination must specify what to do after variables have been eliminated.

    Definition Classes
    ProbQueryVariableEliminationVariableElimination
  34. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
  35. def getFactors(allElements: List[Element[_]], targetElements: List[Element[_]], upper: Boolean = false): List[Factor[Double]]

    All implementations of factored algorithms must specify a way to get the factors from the given universe and dependent universes.

    All implementations of factored algorithms must specify a way to get the factors from the given universe and dependent universes.

    Definition Classes
    ProbabilisticVariableEliminationFactoredAlgorithm
  36. def getNeededElements(starterElements: List[Element[_]], depth: Int, parameterized: Boolean = false): (List[Element[_]], Boolean)

    Get the elements that are needed by the query target variables and the evidence variables.

    Get the elements that are needed by the query target variables and the evidence variables. Also compute the values of those variables to the given depth. Only get factors for elements that are actually used by the target variables. This is more efficient. Also, it avoids problems when values of unused elements have not been computed.

    In addition to getting all the needed elements, it determines if any of the conditioned, constrained, or dependent universe parent elements has * in its range. If any of these elements has * in its range, the lower and upper bounds of factors will be different, so we need to compute both. If they don't, we don't need to compute bounds.

    Definition Classes
    FactoredAlgorithm
  37. def hashCode(): Int
    Definition Classes
    AnyRef → Any
  38. def initialFactorMap(factors: Traversable[Factor[Double]]): FactorMap[Double]
    Attributes
    protected
    Definition Classes
    VariableElimination
  39. def initialize(): Unit

    Called when the algorithm is started before running any steps.

    Called when the algorithm is started before running any steps. By default, does nothing. Can be overridden.

    Definition Classes
    Algorithm
  40. def isActive: Boolean
    Definition Classes
    Algorithm
  41. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  42. def kill(): Unit

    Kill the algorithm so that it is inactive.

    Kill the algorithm so that it is inactive. It will no longer be able to provide answers.Throws AlgorithmInactiveException if the algorithm is not active.

    Definition Classes
    Algorithm
  43. def mean(target: Element[Double]): Double

    Return the mean of the probability density function for the given continuous element.

    Return the mean of the probability density function for the given continuous element.

    Definition Classes
    BaseProbQueryAlgorithm
  44. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  45. final def notify(): Unit
    Definition Classes
    AnyRef
  46. final def notifyAll(): Unit
    Definition Classes
    AnyRef
  47. def posteriorElement[T](target: Element[T], universe: Universe = Universe.universe): Element[T]

    Return an element representing the posterior probability distribution of the given element.

    Return an element representing the posterior probability distribution of the given element.

    Definition Classes
    ProbQueryAlgorithm
  48. def probability[T](target: Element[T], value: T): Double

    Return an estimate of the probability that the target produces the value.

    Return an estimate of the probability that the target produces the value. Throws NotATargetException if called on a target that is not in the list of targets of the algorithm. Throws AlgorithmInactiveException if the algorithm is inactive.

    Definition Classes
    BaseProbQueryAlgorithm
  49. def probability[T](target: Element[T])(predicate: (T) ⇒ Boolean, c: Any = DummyImplicit): Double

    Return an estimate of the probability of the predicate under the marginal probability distribution of the target.

    Return an estimate of the probability of the predicate under the marginal probability distribution of the target. Throws NotATargetException if called on a target that is not in the list of targets of the algorithm. Throws AlgorithmInactiveException if the algorithm is inactive.

    Definition Classes
    BaseProbQueryAlgorithm
  50. def probability[T](target: Element[T], predicate: (T) ⇒ Boolean): Double

    Return an estimate of the probability of the predicate under the marginal probability distribution of the target.

    Return an estimate of the probability of the predicate under the marginal probability distribution of the target. Throws NotATargetException if called on a target that is not in the list of targets of the algorithm. Throws AlgorithmInactiveException if the algorithm is inactive.

    Definition Classes
    BaseProbQueryAlgorithm
  51. lazy val queryTargets: List[Element[_]]
  52. val recordingFactors: List[Factor[_]]
    Attributes
    protected
    Definition Classes
    VariableElimination
  53. def resume(): Unit

    Resume the computation of the algorithm, if it has been stopped.

    Resume the computation of the algorithm, if it has been stopped. Throws AlgorithmInactiveException if the algorithm is not active.

    Definition Classes
    Algorithm
  54. def run(): Unit

    Run the algorithm, performing its computation to completion.

    Run the algorithm, performing its computation to completion.

    Definition Classes
    VariableEliminationOneTime
  55. val semiring: SumProductSemiring
  56. val showTiming: Boolean
  57. def start(): Unit

    Start the algorithm and make it active.

    Start the algorithm and make it active. After it returns, the algorithm must be ready to provide answers. Throws AlgorithmActiveException if the algorithm is already active.

    Definition Classes
    Algorithm
  58. def starterElements: List[Element[_]]

    Elements towards which queries are directed.

    Elements towards which queries are directed. By default, these are the target elements. This is overridden by DecisionVariableElimination, where it also includes utility variables.

    Definition Classes
    VariableElimination
  59. def stop(): Unit

    Stop the algorithm from computing.

    Stop the algorithm from computing. The algorithm is still ready to provide answers after it returns. Throws AlgorithmInactiveException if the algorithm is not active.

    Definition Classes
    Algorithm
  60. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  61. val targetElements: List[Element[_]]
  62. val targetFactors: Map[Element[_], Factor[Double]]
    Attributes
    protected[com.cra.figaro]
    Definition Classes
    VariableElimination
  63. def toString(): String
    Definition Classes
    AnyRef → Any
  64. val universe: Universe
  65. def variance(target: Element[Double]): Double

    Return the variance of the probability density function for the given continuous element.

    Return the variance of the probability density function for the given continuous element.

    Definition Classes
    BaseProbQueryAlgorithm
  66. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  67. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  68. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from VariableElimination[Double]

Inherited from FactoredAlgorithm[Double]

Inherited from OneTimeProbQuery

Inherited from OneTime

Inherited from ProbQueryAlgorithm

Inherited from Algorithm

Inherited from AnyRef

Inherited from Any

Ungrouped