cc.factorie.model

TensorFactorStatistics1

trait TensorFactorStatistics1[N1 <: TensorVar] extends TensorFactor1[N1]

A trait for 1-neighbor Factor whose neighbor has Tensor values, and whose statistics are the outer product of those values. Only "statisticsScore" method is abstract. DotFactorWithStatistics2 is also a subclass of this.

Linear Supertypes
TensorFactor1[N1], Factor1[N1], Factor, Ordered[Factor], Comparable[Factor], AnyRef, Any
Known Subclasses
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Inherited
  1. TensorFactorStatistics1
  2. TensorFactor1
  3. Factor1
  4. Factor
  5. Ordered
  6. Comparable
  7. AnyRef
  8. Any
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Type Members

  1. type NeighborType1 = N1

    Definition Classes
    Factor1
  2. type StatisticsType = Tensor

    Definition Classes
    TensorFactor1Factor

Abstract Value Members

  1. abstract def statisticsScore(t: Tensor): Double

    Definition Classes
    TensorFactor1

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 <(that: Factor): Boolean

    Definition Classes
    Ordered
  5. def <=(that: Factor): Boolean

    Definition Classes
    Ordered
  6. final def ==(arg0: AnyRef): Boolean

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

    Definition Classes
    Any
  8. def >(that: Factor): Boolean

    Definition Classes
    Ordered
  9. def >=(that: Factor): Boolean

    Definition Classes
    Ordered
  10. val _1: N1

    Definition Classes
    TensorFactor1Factor1
  11. var _hashCode: Int

    Definition Classes
    Factor
  12. def addLimitedDiscreteCurrentValues1(): Unit

    Definition Classes
    Factor1
  13. def addLimitedDiscreteValues1(i: Int): Unit

    Definition Classes
    Factor1
  14. final def asInstanceOf[T0]: T0

    Definition Classes
    Any
  15. def assignmentScore(a: variable.Assignment): Double

    The ability to score a Values object is now removed, and this is its closest alternative.

    The ability to score a Values object is now removed, and this is its closest alternative.

    Definition Classes
    Factor1Factor
  16. def assignmentScoreAndStatistics(a: variable.Assignment): (Double, StatisticsType)

    Definition Classes
    Factor
  17. final def assignmentStatistics(a: variable.Assignment): StatisticsType

    Return this Factor's sufficient statistics for the values in the Assignment.

    Return this Factor's sufficient statistics for the values in the Assignment.

    Definition Classes
    Factor1Factor
  18. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  19. def compare(that: Factor): Int

    Return an object that can iterate over all value assignments to the neighbors of this Factor

    Return an object that can iterate over all value assignments to the neighbors of this Factor

    Definition Classes
    Factor → Ordered
  20. def compareTo(that: Factor): Int

    Definition Classes
    Ordered → Comparable
  21. def currentAssignment: Assignment1[N1]

    Return a record of the current values of this Factor's neighbors.

    Return a record of the current values of this Factor's neighbors.

    Definition Classes
    Factor1Factor
  22. def currentScore: Double

    This factor's contribution to the unnormalized log-probability of the current possible world.

    This factor's contribution to the unnormalized log-probability of the current possible world.

    Definition Classes
    Factor1Factor
  23. def currentScoreAndStatistics: (Double, StatisticsType)

    Return the score and statistics of the current neighbor values; this method enables special cases in which it is more efficient to calculate them together.

    Return the score and statistics of the current neighbor values; this method enables special cases in which it is more efficient to calculate them together.

    Definition Classes
    Factor1Factor
  24. final def currentStatistics: N1.Value

    Return this Factor's sufficient statistics of the current values of the Factor's neighbors.

    Return this Factor's sufficient statistics of the current values of the Factor's neighbors.

    Definition Classes
    TensorFactorStatistics1Factor1Factor
  25. final def eq(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  26. def equalityPrerequisite: AnyRef

    In order to two Factors to satisfy "equals", the value returned by this method for each Factor must by "eq".

    In order to two Factors to satisfy "equals", the value returned by this method for each Factor must by "eq". This method is overridden in Family to deal with Factors that are inner classes.

    Definition Classes
    Factor
  27. def equals(other: Any): Boolean

    Definition Classes
    Factor → AnyRef → Any
  28. def factorName: String

    Definition Classes
    Factor
  29. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  30. final def getClass(): Class[_]

    Definition Classes
    AnyRef → Any
  31. def hasLimitedDiscreteValues1: Boolean

    Definition Classes
    Factor1
  32. def hashCode(): Int

    Definition Classes
    Factor → AnyRef → Any
  33. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any
  34. def limitedDiscreteValues1: SparseBinaryTensor1

    Definition Classes
    Factor1
  35. final def ne(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  36. final def notify(): Unit

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

    Definition Classes
    AnyRef
  38. def numVariables: Int

    The number of variables neighboring this factor.

    The number of variables neighboring this factor.

    Definition Classes
    Factor1Factor
  39. final def score(v1: N1.Value): Double

    Definition Classes
    TensorFactor1Factor1
  40. def scoreAndStatistics(v1: N1.Value): (Double, Tensor)

    Definition Classes
    TensorFactor1Factor1
  41. final def statistics(v1: N1.Value): N1.Value

    Definition Classes
    TensorFactorStatistics1TensorFactor1Factor1
  42. final def statisticsAreValues: Boolean

    True iff the statistics are the values (without transformation), e.

    True iff the statistics are the values (without transformation), e.g. valuesStatistics simply returns its argument.

    Definition Classes
    TensorFactorStatistics1Factor
  43. final def synchronized[T0](arg0: ⇒ T0): T0

    Definition Classes
    AnyRef
  44. def toString(): String

    Definition Classes
    Factor → AnyRef → Any
  45. def touches(variable: variable.Var): Boolean

    Does this Factor have the given variable among its neighbors?

    Does this Factor have the given variable among its neighbors?

    Definition Classes
    Factor
  46. def touchesAny(variables: Iterable[variable.Var]): Boolean

    Does this Factor have any of the given variables among its neighbors?

    Does this Factor have any of the given variables among its neighbors?

    Definition Classes
    Factor
  47. def valuesScore(tensor: Tensor): Double

    Return the score for Factors whose values can be represented as a Tensor, otherwise throw an Error.

    Return the score for Factors whose values can be represented as a Tensor, otherwise throw an Error. For Factors/Family in which the Statistics are the values, this method simply calls statisticsScore(Tensor).

    Definition Classes
    Factor
  48. def valuesScore1: la.Tensor1

    Return a Tensor1 containing the scores for each possible value of neighbor _1, which must be a DiscreteVar.

    Return a Tensor1 containing the scores for each possible value of neighbor _1, which must be a DiscreteVar. Note that the returned Tensor may be sparse if this factor is set up for limited values iteration. If _1 is not a DiscreteVar then throws an Error.

    Definition Classes
    Factor1
  49. def valuesScoreAndStatistics(t: Tensor): (Double, Tensor)

    Definition Classes
    Factor
  50. final def valuesStatistics(tensor: Tensor): Tensor

    Given a Tensor representation of the values, return a Tensor representation of the statistics.

    Given a Tensor representation of the values, return a Tensor representation of the statistics. We assume that if the values have Tensor representation that the StatisticsType does also. Note that (e.g. in BP) the Tensor may represent not just a single value for each neighbor, but a distribution over values

    Definition Classes
    TensorFactorStatistics1Factor
  51. def variable(i: Int): variable.Var

    The Nth neighboring variable of this factor.

    The Nth neighboring variable of this factor.

    Definition Classes
    Factor1Factor
  52. def variables: IndexedSeq[N1]

    Returns the collection of variables neighboring this factor.

    Returns the collection of variables neighboring this factor.

    Definition Classes
    Factor1Factor
  53. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  54. final def wait(arg0: Long, arg1: Int): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  55. final def wait(arg0: Long): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from TensorFactor1[N1]

Inherited from Factor1[N1]

Inherited from Factor

Inherited from Ordered[Factor]

Inherited from Comparable[Factor]

Inherited from AnyRef

Inherited from Any

Ungrouped