Class/Object

regressors

NeuralNetworkRegressor

Related Docs: object NeuralNetworkRegressor | package regressors

Permalink

class NeuralNetworkRegressor extends Regressor

Neural network regressor

Linear Supertypes
Regressor, AnyRef, Any
Ordering
  1. Alphabetic
  2. By Inheritance
Inherited
  1. NeuralNetworkRegressor
  2. Regressor
  3. AnyRef
  4. Any
  1. Hide All
  2. Show All
Visibility
  1. Public
  2. All

Instance Constructors

  1. new NeuralNetworkRegressor(json: JsValue)

    Permalink

  2. new NeuralNetworkRegressor(alpha: Double = NeuralNetworkRegressor.alpha, alphaHalflife: Int = ..., alphaDecay: String = NeuralNetworkRegressor.alphaDecay, regularization: Double = ..., activation: String = NeuralNetworkRegressor.activation, batchSize: Int = NeuralNetworkRegressor.batchSize, layers: List[Int] = NeuralNetworkRegressor.layers)

    Permalink

    alpha

    Learning rate

    alphaHalflife

    Learning rate decay after this number of training steps

    alphaDecay

    Type of learning rate decay

    regularization

    Regularization parameter

    activation

    Activation function

    batchSize

    Number of (randomized) training instances to use for each training step

    layers

    Structure of the network as a list of number of neurons in each layer

Value Members

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

    Permalink
    Definition Classes
    AnyRef → Any

  2. final def ##(): Int

    Permalink
    Definition Classes
    AnyRef → Any

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

    Permalink
    Definition Classes
    AnyRef → Any

  4. val W: IndexedSeq[DenseMatrix[Double]]

    Permalink

  5. var alphaEvolution: ListBuffer[(Double, Double)]

    Permalink

  6. final def asInstanceOf[T0]: T0

    Permalink
    Definition Classes
    Any

  7. val b: IndexedSeq[DenseVector[Double]]

    Permalink

  8. def clone(): AnyRef

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

  9. def diagnostics(): Map[String, List[(Double, Double)]]

    Permalink

    Provides meta-information on the regressor

    Provides meta-information on the regressor

    returns

    Map object of metric names and metric values

    Definition Classes
    NeuralNetworkRegressor → Regressor

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

    Permalink
    Definition Classes
    AnyRef

  11. def equals(arg0: Any): Boolean

    Permalink
    Definition Classes
    AnyRef → Any

  12. def finalize(): Unit

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

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

    Permalink
    Definition Classes
    AnyRef → Any

  14. def hashCode(): Int

    Permalink
    Definition Classes
    AnyRef → Any

  15. final def isInstanceOf[T0]: Boolean

    Permalink
    Definition Classes
    Any

  16. var lossEvolution: ListBuffer[(Double, Double)]

    Permalink

  17. val name: String

    Permalink

    The name of the regressor

    The name of the regressor

    Definition Classes
    NeuralNetworkRegressor → Regressor

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

    Permalink
    Definition Classes
    AnyRef

  19. final def notify(): Unit

    Permalink
    Definition Classes
    AnyRef

  20. final def notifyAll(): Unit

    Permalink
    Definition Classes
    AnyRef

  21. def predict(listX: List[List[Double]]): List[Double]

    Permalink

    Applies the trained regressor to a dataset

    Applies the trained regressor to a dataset

    returns

    List of predictions

    Definition Classes
    NeuralNetworkRegressor → Regressor

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

    Permalink
    Definition Classes
    AnyRef

  23. def toString(): String

    Permalink
    Definition Classes
    AnyRef → Any

  24. def train(listX: List[List[Double]], listy: List[Double]): Unit

    Permalink

    Performs the training of the regressor

    Performs the training of the regressor

    Definition Classes
    NeuralNetworkRegressor → Regressor

  25. final def wait(): Unit

    Permalink
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Permalink
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Permalink
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from Regressor

Inherited from AnyRef

Inherited from Any

Ungrouped