cc.factorie.optimize

ParallelBatchTrainer

class ParallelBatchTrainer extends Trainer with FastLogging

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FastLogging, Logging, Trainer, AnyRef, Any
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  1. ParallelBatchTrainer
  2. FastLogging
  3. Logging
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Instance Constructors

  1. new ParallelBatchTrainer(weightsSet: WeightsSet, optimizer: GradientOptimizer = ..., nThreads: Int = ...)

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

    Definition Classes
    AnyRef

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

    Definition Classes
    Any

  6. final def asInstanceOf[T0]: T0

    Definition Classes
    Any

  7. def clone(): AnyRef

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

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

    Definition Classes
    AnyRef

  9. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any

  10. def finalize(): Unit

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

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

    Definition Classes
    AnyRef → Any

  12. val gradientAccumulator: SynchronizedWeightsMapAccumulator

  13. def hashCode(): Int

    Definition Classes
    AnyRef → Any

  14. def isConverged: Boolean

    Would more training help?

    Would more training help?

    Definition Classes
    ParallelBatchTrainer → Trainer

  15. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

  16. val logger: Logger

    Definition Classes
    FastLogging → Logging

  17. val nThreads: Int

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

    Definition Classes
    AnyRef

  19. final def notify(): Unit

    Definition Classes
    AnyRef

  20. final def notifyAll(): Unit

    Definition Classes
    AnyRef

  21. val optimizer: GradientOptimizer

  22. def processExamples(examples: Iterable[Example]): Unit

    Process the examples once.

    Process the examples once.

    examples

    Examples to be processed

    Definition Classes
    ParallelBatchTrainer → Trainer

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

    Definition Classes
    AnyRef

  24. def toString(): String

    Definition Classes
    AnyRef → Any

  25. def trainFromExamples(examples: Iterable[Example]): Unit

    Repeatedly process the examples until training has converged.

    Repeatedly process the examples until training has converged.

    Definition Classes
    Trainer

  26. val valueAccumulator: SynchronizedDoubleAccumulator

  27. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  30. val weightsSet: WeightsSet

Inherited from FastLogging

Inherited from Logging

Inherited from Trainer

Inherited from AnyRef

Inherited from Any

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