ml.combust.mleap.core.ann

FeedForwardTopology

object FeedForwardTopology extends Serializable

Factory for some of the frequently-used topologies

Linear Supertypes
Serializable, Serializable, AnyRef, Any
Ordering
  1. Alphabetic
  2. By inheritance
Inherited
  1. FeedForwardTopology
  2. Serializable
  3. Serializable
  4. AnyRef
  5. Any
  1. Hide All
  2. Show all
Learn more about member selection
Visibility
  1. Public
  2. All

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. def apply(layers: Array[Layer]): FeedForwardTopology

    Creates a feed forward topology from the array of layers

    Creates a feed forward topology from the array of layers

    layers

    array of layers

    returns

    feed forward topology

  7. final def asInstanceOf[T0]: T0

    Definition Classes
    Any
  8. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  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. final def getClass(): Class[_]

    Definition Classes
    AnyRef → Any
  13. def hashCode(): Int

    Definition Classes
    AnyRef → Any
  14. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any
  15. def multiLayerPerceptron(layerSizes: Array[Int], softmaxOnTop: Boolean = true): FeedForwardTopology

    Creates a multi-layer perceptron

    Creates a multi-layer perceptron

    layerSizes

    sizes of layers including input and output size

    softmaxOnTop

    whether to use SoftMax or Sigmoid function for an output layer. Softmax is default

    returns

    multilayer perceptron topology

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

    Definition Classes
    AnyRef
  17. final def notify(): Unit

    Definition Classes
    AnyRef
  18. final def notifyAll(): Unit

    Definition Classes
    AnyRef
  19. final def synchronized[T0](arg0: ⇒ T0): T0

    Definition Classes
    AnyRef
  20. def toString(): String

    Definition Classes
    AnyRef → Any
  21. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  22. final def wait(arg0: Long, arg1: Int): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  23. final def wait(arg0: Long): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

Ungrouped