kr.ac.kaist.ir.deep.train

StandardRAEType

class StandardRAEType extends TreeType

Input Operation : VectorTree as Input & Recursive Auto-Encoder Training (no output type)

Example: 

  1. var make = new RAEType(error = CrossEntropyErr)
            var corruptedIn = make corrupted in
            var out = make onewayTrip (net, corruptedIn)
Note

This implementation designed as a replica of the standard RAE (RAE + normalization) in this paper

,

We recommend that you should not apply this method to non-AutoEncoder tasks

Linear Supertypes
TreeType, ManipulationType[BinaryTree, Null], Serializable, Serializable, AnyRef, Any
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Inherited
  1. StandardRAEType
  2. TreeType
  3. ManipulationType
  4. Serializable
  5. Serializable
  6. AnyRef
  7. Any
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Instance Constructors

  1. new StandardRAEType(corrupt: Corruption = NoCorruption, error: Objective = SquaredErr)

    corrupt

    Corruption that supervises how to corrupt the input matrix. (Default : kr.ac.kaist.ir.deep.train.NoCorruption)

    error

    An objective function (Default: kr.ac.kaist.ir.deep.fn.SquaredErr)

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. final def asInstanceOf[T0]: T0

    Definition Classes
    Any

  5. def clone(): AnyRef

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

  6. val corrupt: Corruption

    Corruption that supervises how to corrupt the input matrix.

    Corruption that supervises how to corrupt the input matrix. (Default : kr.ac.kaist.ir.deep.train.NoCorruption)

    Definition Classes
    StandardRAEType → ManipulationType

  7. def corrupted(x: BinaryTree): BinaryTree

    Corrupt input

    Corrupt input

    x

    input to be corrupted

    returns

    corrupted input

    Definition Classes
    TreeType → ManipulationType

  8. def different(x: Null, y: Null): Boolean

    Check whether given two are same or not.

    Check whether given two are same or not.

    x

    Out-type object

    y

    Out-type object

    returns

    True if they are different.

    Definition Classes
    ManipulationType

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

    Definition Classes
    AnyRef

  10. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any

  11. val error: Objective

    An objective function (Default: kr.ac.kaist.ir.deep.fn.SquaredErr)

    An objective function (Default: kr.ac.kaist.ir.deep.fn.SquaredErr)

    Definition Classes
    StandardRAEType → ManipulationType

  12. def finalize(): Unit

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

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

    Definition Classes
    AnyRef → Any

  14. def hashCode(): Int

    Definition Classes
    AnyRef → Any

  15. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

  16. def lossOf(net: Network)(pair: (BinaryTree, Null)): Scalar

    Apply given input and compute the error

    Apply given input and compute the error

    net

    A network that gets input

    pair

    (Input, Real output) for error computation.

    returns

    error of this network

    Definition Classes
    StandardRAEType → ManipulationType

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

    Definition Classes
    AnyRef

  18. val normalizeLayer: NormalizeOperation

    Normalization layer

  19. final def notify(): Unit

    Definition Classes
    AnyRef

  20. final def notifyAll(): Unit

    Definition Classes
    AnyRef

  21. def onewayTrip(net: Network, x: BinaryTree): ScalarMatrix

    Apply given single input as one-way forward trip.

    Apply given single input as one-way forward trip.

    net

    A network that gets input

    x

    input to be computed

    returns

    output of the network.

    Definition Classes
    TreeType → ManipulationType

  22. def roundTrip(net: Network, in: BinaryTree, real: Null): Unit

    Apply & Back-prop given single input

    Apply & Back-prop given single input

    net

    A network that gets input

    in

    Input for error computation.

    real

    Real Output for error computation.

    Definition Classes
    StandardRAEType → ManipulationType

  23. def stringOf(net: Network, pair: (BinaryTree, Null)): String

    Make validation output

    Make validation output

    net

    A network that gets input

    returns

    input as string

    Definition Classes
    StandardRAEType → ManipulationType

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

    Definition Classes
    AnyRef

  25. def toString(): String

    Definition Classes
    AnyRef → Any

  26. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from TreeType

Inherited from ManipulationType[BinaryTree, Null]

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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