epic.framework

Model

trait Model[Datum] extends AnyRef

A Model represents a class for turning weight vectors into epic.framework.Inferences. It's main job is to hook up with a epic.framework.ModelObjective and mediate computation of ExpectedCounts and conversion to the objective that's needed for optimization.

Datum

the kind of

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Model[Datum]
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Type Members

  1. abstract type ExpectedCounts >: Null <: framework.ExpectedCounts[ExpectedCounts]

  2. abstract type Inference <: framework.Inference[Datum] { ... /* 2 definitions in type refinement */ }

  3. abstract type Marginal <: framework.Marginal

  4. abstract type Scorer

Abstract Value Members

  1. abstract def accumulateCounts(s: Scorer, d: Datum, m: Marginal, accum: ExpectedCounts, scale: Double): Unit

  2. abstract def emptyCounts: ExpectedCounts

  3. abstract def expectedCountsToObjective(ecounts: ExpectedCounts): (Double, DenseVector[Double])

  4. abstract def featureIndex: Index[Feature]

    Models have features, and this defines the mapping from indices in the weight vector to features.

    Models have features, and this defines the mapping from indices in the weight vector to features.

    returns

  5. abstract def inferenceFromWeights(weights: DenseVector[Double]): Inference

  6. abstract def initialValueForFeature(f: Feature): Double

Concrete Value Members

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

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

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  3. final def ##(): Int

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

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

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  6. final def accumulateCounts(inf: Inference, d: Datum, accum: ExpectedCounts, scale: Double): Unit

  7. final def asInstanceOf[T0]: T0

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  8. def cacheFeatureWeights(weights: DenseVector[Double], suffix: String = ""): Unit

    Caches the weights using the cache broker.

  9. def clone(): AnyRef

    Attributes
    protected[java.lang]
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    @throws( ... )
  10. final def eq(arg0: AnyRef): Boolean

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  11. def equals(arg0: Any): Boolean

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  12. final def expectedCounts(inf: Inference, d: Datum, scale: Double = 1.0): ExpectedCounts

  13. def finalize(): Unit

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

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  15. def hashCode(): Int

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  16. final def isInstanceOf[T0]: Boolean

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

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  18. final def notify(): Unit

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  19. final def notifyAll(): Unit

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  20. def numFeatures: Int

  21. def readCachedFeatureWeights(suffix: String = ""): Option[DenseVector[Double]]

    just saves feature weights to disk as a serialized counter.

    just saves feature weights to disk as a serialized counter. The file is prefix.ser.gz

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

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  23. def toString(): String

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  24. final def wait(): Unit

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

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

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    @throws( ... )
  27. def weightsCacheName: String

    Attributes
    protected

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