Class

com.github.nearbydelta.deepspark.word

LedgerSGD

Related Doc: package word

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class LedgerSGD extends LedgerBuilder

Algorithm: Stochastic Gradient Descent

Basic Gradient Descent rule with mini-batch training.

Example: 

  1. val algorithm = new StochasticGradientDescent(l2decay = 0.0001)
Linear Supertypes
LedgerBuilder, KryoSerializable, Serializable, Serializable, AnyRef, Any
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Inherited
  1. LedgerSGD
  2. LedgerBuilder
  3. KryoSerializable
  4. Serializable
  5. Serializable
  6. AnyRef
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Visibility
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Instance Constructors

  1. new LedgerSGD()

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  2. new LedgerSGD(rate: Double = 0.03, l2decay: Double = 0.0001, momentum: Double = 0.0001)

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    rate

    the learning rate (Default 0.03)

    l2decay

    L2 regularization factor (Default 0.0001)

    momentum

    Momentum factor for adaptive learning (Default 0.0001)

Type Members

  1. class Updater extends LedgerAlgorithm

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Value Members

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

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    Definition Classes
    AnyRef → Any

  2. final def ##(): Int

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    Definition Classes
    AnyRef → Any

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

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    Definition Classes
    AnyRef → Any

  4. final def asInstanceOf[T0]: T0

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  5. def clone(): AnyRef

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

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

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    Definition Classes
    AnyRef

  7. def equals(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

  8. def finalize(): Unit

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

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

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    Definition Classes
    AnyRef → Any

  10. def getUpdater(model: ListLedger): LedgerAlgorithm

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    Definition Classes
    LedgerSGD → LedgerBuilder

  11. def hashCode(): Int

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    Definition Classes
    AnyRef → Any

  12. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any

  13. var l2decay: Double

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    L2 regularization factor (Default 0.0001)

  14. var momentum: Double

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    Momentum factor for adaptive learning (Default 0.0001)

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

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    Definition Classes
    AnyRef

  16. final def notify(): Unit

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    Definition Classes
    AnyRef

  17. final def notifyAll(): Unit

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    Definition Classes
    AnyRef

  18. var rate: Double

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    the learning rate (Default 0.03)

  19. def read(kryo: Kryo, input: Input): Unit

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    Definition Classes
    LedgerSGD → KryoSerializable

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

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    Definition Classes
    AnyRef

  21. def toString(): String

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    AnyRef → Any

  22. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  25. def write(kryo: Kryo, output: Output): Unit

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    Definition Classes
    LedgerSGD → KryoSerializable

Inherited from LedgerBuilder

Inherited from KryoSerializable

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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