epic.framework

ModelObjective

class ModelObjective[Datum] extends BatchDiffFunction[DenseVector[Double]] with SafeLogging

The objective function for training a epic.framework.Model. Selects a batch, creates an epic.framework.Inference object using the model, computes expected counts using the inference, and then turns them into the objective value.

Linear Supertypes
SafeLogging, BatchDiffFunction[DenseVector[Double]], (DenseVector[Double], IndexedSeq[Int]) ⇒ Double, DiffFunction[DenseVector[Double]], StochasticDiffFunction[DenseVector[Double]], (DenseVector[Double]) ⇒ Double, AnyRef, Any
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Inherited
  1. ModelObjective
  2. SafeLogging
  3. BatchDiffFunction
  4. Function2
  5. DiffFunction
  6. StochasticDiffFunction
  7. Function1
  8. AnyRef
  9. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new ModelObjective(model: Model[Datum], data: IndexedSeq[Datum], numThreads: Int = 1)

  2. new ModelObjective(model: Model[Datum], batchSelector: (IndexedSeq[Int]) ⇒ GenTraversable[Datum], fullRange: IndexedSeq[Int])

Type Members

  1. type Builder = Model.Inference

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. def andThen[A](g: (Double) ⇒ A): (DenseVector[Double]) ⇒ A

    Definition Classes
    Function1
    Annotations
    @unspecialized()

  5. def apply(x: DenseVector[Double], batch: IndexedSeq[Int]): Double

    Definition Classes
    BatchDiffFunction → Function2

  6. final def apply(x: DenseVector[Double]): Double

    Definition Classes
    StochasticDiffFunction → Function1

  7. final def asInstanceOf[T0]: T0

    Definition Classes
    Any

  8. def cached(implicit copy: CanCopy[DenseVector[Double]]): DiffFunction[DenseVector[Double]]

    Definition Classes
    BatchDiffFunction → DiffFunction

  9. def calculate(x: DenseVector[Double], batch: IndexedSeq[Int]): (Double, DenseVector[Double])

    Definition Classes
    ModelObjective → BatchDiffFunction

  10. def calculate(x: DenseVector[Double]): (Double, DenseVector[Double])

    Definition Classes
    BatchDiffFunction → StochasticDiffFunction

  11. def clone(): AnyRef

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

  12. def compose[A](g: (A) ⇒ DenseVector[Double]): (A) ⇒ Double

    Definition Classes
    Function1
    Annotations
    @unspecialized()

  13. def curried: (DenseVector[Double]) ⇒ (IndexedSeq[Int]) ⇒ Double

    Definition Classes
    Function2
    Annotations
    @unspecialized()

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

    Definition Classes
    AnyRef

  15. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any

  16. def finalize(): Unit

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

  17. val fullRange: IndexedSeq[Int]

    Definition Classes
    ModelObjective → BatchDiffFunction

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

    Definition Classes
    AnyRef → Any

  19. def gradientAt(x: DenseVector[Double]): DenseVector[Double]

    Definition Classes
    BatchDiffFunction → StochasticDiffFunction

  20. def gradientAt(x: DenseVector[Double], batch: IndexedSeq[Int]): DenseVector[Double]

    Definition Classes
    BatchDiffFunction

  21. def groupItems(groupSize: Int): BatchDiffFunction[DenseVector[Double]]

    Definition Classes
    BatchDiffFunction

  22. def hashCode(): Int

    Definition Classes
    AnyRef → Any

  23. def initialWeightVector(randomize: Boolean): DenseVector[Double]

  24. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

  25. def logger: Logger

    Definition Classes
    SafeLogging

  26. val model: Model[Datum]

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

    Definition Classes
    AnyRef

  28. var nextSave: Long

  29. final def notify(): Unit

    Definition Classes
    AnyRef

  30. final def notifyAll(): Unit

    Definition Classes
    AnyRef

  31. def select(batch: IndexedSeq[Int]): GenTraversable[Datum]

    Attributes
    protected

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

    Definition Classes
    AnyRef

  33. def throughLens[U](implicit l: Isomorphism[DenseVector[Double], U]): DiffFunction[U]

    Definition Classes
    StochasticDiffFunction

  34. var timeSinceLastWrite: Long

  35. def toString(): String

    Definition Classes
    Function2 → AnyRef → Any

  36. def tupled: ((DenseVector[Double], IndexedSeq[Int])) ⇒ Double

    Definition Classes
    Function2
    Annotations
    @unspecialized()

  37. def valueAt(x: DenseVector[Double]): Double

    Definition Classes
    BatchDiffFunction → StochasticDiffFunction

  38. def valueAt(x: DenseVector[Double], batch: IndexedSeq[Int]): Double

    Definition Classes
    BatchDiffFunction

  39. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  42. def withRandomBatches(size: Int): StochasticDiffFunction[DenseVector[Double]]

    Definition Classes
    BatchDiffFunction

  43. def withScanningBatches(size: Int): StochasticDiffFunction[DenseVector[Double]]

    Definition Classes
    BatchDiffFunction

Inherited from SafeLogging

Inherited from BatchDiffFunction[DenseVector[Double]]

Inherited from (DenseVector[Double], IndexedSeq[Int]) ⇒ Double

Inherited from DiffFunction[DenseVector[Double]]

Inherited from StochasticDiffFunction[DenseVector[Double]]

Inherited from (DenseVector[Double]) ⇒ Double

Inherited from AnyRef

Inherited from Any

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