Trait

com.cra.figaro.algorithm.factored.gibbs

Cached

Related Doc: package gibbs

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trait Cached extends SimpleBlockSampler

Caches factors according to assignments of values in the Markov blanket, which avoids recomputing the same factors repeatedly Takes advantage of the fact in Gibbs sampling, nearby samples tend to be highly correlated

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  1. Cached
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Value Members

  1. final def !=(arg0: Any): Boolean

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  2. final def ##(): Int

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    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any
  4. val adjacentFactors: List[Factor[Double]]

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    Definition Classes
    BlockSampler
  5. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any
  6. val block: Block

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    Definition Classes
    BlockSampler
  7. val blockInfo: BlockInfo

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    The pair containing the variables to sample and adjacent factors.

    The pair containing the variables to sample and adjacent factors.

    Definition Classes
    BlockSampler
  8. lazy val cache: Map[List[Int], Factor[Double]]

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  9. def clone(): AnyRef

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    Attributes
    protected[java.lang]
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    Annotations
    @throws( ... )
  10. def computeSamplingFactor(currentSamples: Map[Variable[_], Int]): Factor[Double]

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    Definition Classes
    SimpleBlockSampler
  11. final def eq(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef
  12. def equals(arg0: Any): Boolean

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  13. def finalize(): Unit

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    protected[java.lang]
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    @throws( classOf[java.lang.Throwable] )
  14. final def getClass(): Class[_]

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  15. def getSamplingFactor(currentSamples: Map[Variable[_], Int]): Factor[Double]

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    Get the factor from which to sample this block Returns a non-logarithmic factor

    Get the factor from which to sample this block Returns a non-logarithmic factor

    Definition Classes
    CachedSimpleBlockSamplerBlockSampler
  16. def hashCode(): Int

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    Definition Classes
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  17. val indexMap: Map[Variable[_], Int]

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    Definition Classes
    SimpleBlockSampler
  18. val indices: Indices

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    Definition Classes
    SimpleBlockSampler
  19. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any
  20. lazy val markovBlanket: List[Variable[_]]

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  21. lazy val maxSize: Int

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  22. final def ne(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef
  23. def normalizeFactor(factor: Factor[Double]): Factor[Double]

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    Normalize a factor so its weights sum to 1 Takes a logarithmic factor and returns a non-logarithmic factor

    Normalize a factor so its weights sum to 1 Takes a logarithmic factor and returns a non-logarithmic factor

    Definition Classes
    SimpleBlockSampler
  24. final def notify(): Unit

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    Definition Classes
    AnyRef
  25. final def notifyAll(): Unit

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    Definition Classes
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  26. def sample(currentSamples: Map[Variable[_], Int]): Unit

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    Sample this block once

    Sample this block once

    Definition Classes
    BlockSampler
  27. def sampleFactor(factor: Factor[Double]): List[Int]

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    Select a set of indices in the factor according to the weights in the factor Works on a non-logarithmic factor

    Select a set of indices in the factor according to the weights in the factor Works on a non-logarithmic factor

    Definition Classes
    BlockSampler
  28. val semiring: LogSumProductSemiring

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    Definition Classes
    SimpleBlockSampler
  29. final def synchronized[T0](arg0: ⇒ T0): T0

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    Definition Classes
    AnyRef
  30. def toString(): String

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  31. final def wait(): Unit

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    @throws( ... )
  32. final def wait(arg0: Long, arg1: Int): Unit

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    @throws( ... )
  33. final def wait(arg0: Long): Unit

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Inherited from SimpleBlockSampler

Inherited from BlockSampler

Inherited from AnyRef

Inherited from Any

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