ml.combust.mleap.core.ann

FeedForwardModel

class FeedForwardModel extends TopologyModel

Model of Feed Forward Neural Network. Implements forward, gradient computation and can return weights in vector format.

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TopologyModel, Serializable, Serializable, AnyRef, Any
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  1. FeedForwardModel
  2. TopologyModel
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  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
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  6. final def asInstanceOf[T0]: T0

    Definition Classes
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  7. def clone(): AnyRef

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

  8. def computeGradient(data: DenseMatrix[Double], target: DenseMatrix[Double], cumGradient: Vector, realBatchSize: Int): Double

    Computes gradient for the network

    Computes gradient for the network

    data

    input data

    target

    target output

    cumGradient

    cumulative gradient

    returns

    error

    Definition Classes
    FeedForwardModel → TopologyModel

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

    Definition Classes
    AnyRef

  10. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any

  11. def finalize(): Unit

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

  12. def forward(data: DenseMatrix[Double]): Array[DenseMatrix[Double]]

    Forward propagation

    Forward propagation

    data

    input data

    returns

    array of outputs for each of the layers

    Definition Classes
    FeedForwardModel → TopologyModel

  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. val layerModels: Array[LayerModel]

    Array of layer models

    Array of layer models

    Definition Classes
    FeedForwardModel → TopologyModel

  17. val layers: Array[Layer]

    Array of layers

    Array of layers

    Definition Classes
    FeedForwardModel → TopologyModel

  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. def predict(data: Vector): Vector

    Prediction of the model

    Prediction of the model

    data

    input data

    returns

    prediction

    Definition Classes
    FeedForwardModel → TopologyModel

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

    Definition Classes
    AnyRef

  23. def toString(): String

    Definition Classes
    AnyRef → Any

  24. val topology: FeedForwardTopology

    network topology

  25. final def wait(): Unit

    Definition Classes
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    Annotations
    @throws( ... )

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

    Definition Classes
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    @throws( ... )

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

    Definition Classes
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    @throws( ... )

  28. val weights: Vector

    network weights

    network weights

    Definition Classes
    FeedForwardModel → TopologyModel

Inherited from TopologyModel

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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