breeze.inference.bp

Factor

trait Factor extends inference.Factor[Factor]

A Factor knows about a set of variables and can score any assignment to those sets of variables. By default, we assume all assignments are valid/scoreable.

You can make some assignments invalid by overriding foreachAssignment. This is useful for sparse structures

Linear Supertypes
inference.Factor[Factor], AnyRef, Any
Known Subclasses
ProductFactor
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Abstract Value Members

  1. abstract def logApply(assignments: Array[Int]): Double

  2. abstract def variables: IndexedSeq[Variable[_]]

Concrete Value Members

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

    Definition Classes
    AnyRef

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

    Definition Classes
    Any

  3. final def ##(): Int

    Definition Classes
    AnyRef → Any

  4. def *(f: Factor): ProductFactor

    Pointwise multiplication

    Pointwise multiplication

    Definition Classes
    Factor → Factor

  5. def /(f: Factor): ProductFactor

    Pointwise division

    Pointwise division

    Definition Classes
    Factor → Factor

  6. final def ==(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  7. final def ==(arg0: Any): Boolean

    Definition Classes
    Any

  8. final def _updateBeliefs(beliefs: IndexedSeq[DenseVector[Double]]): (IndexedSeq[DenseVector[Double]], Double)

    Attributes
    protected[breeze.inference]

  9. def apply(assignments: Array[Int]): Double

  10. final def asInstanceOf[T0]: T0

    Definition Classes
    Any

  11. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws()

  12. final def eq(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  13. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any

  14. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws()

  15. def foreachAssignment(f: (Array[Int]) ⇒ Any): Unit

  16. final def getClass(): Class[_]

    Definition Classes
    AnyRef → Any

  17. def hashCode(): Int

    Definition Classes
    AnyRef → Any

  18. def isConvergedTo(f: Factor, diff: Double): Boolean

    Definition Classes
    Factor → Factor

  19. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

  20. lazy val logPartition: Double

    May be infinite

    May be infinite

    Definition Classes
    Factor → Factor

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

    Definition Classes
    AnyRef

  22. final def notify(): Unit

    Definition Classes
    AnyRef

  23. final def notifyAll(): Unit

    Definition Classes
    AnyRef

  24. def size: Int

  25. final def synchronized[T0](arg0: ⇒ T0): T0

    Definition Classes
    AnyRef

  26. def toString(): String

    Definition Classes
    AnyRef → Any

  27. def updateBeliefs(beliefs: IndexedSeq[DenseVector[Double]]): (IndexedSeq[DenseVector[Double]], Double)

    Return partition function estimate and new normalized beliefs by sending messages to all variables.

    Return partition function estimate and new normalized beliefs by sending messages to all variables. This is actually the EP update, but whatever.

    You might be able to override this, for example, visit fewer assignments if structure permits.

    beliefs

    current beliefs from all other factors.

    returns

    Attributes
    protected

  28. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws()

  29. final def wait(arg0: Long, arg1: Int): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws()

  30. final def wait(arg0: Long): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws()

Inherited from inference.Factor[Factor]

Inherited from AnyRef

Inherited from Any

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