NeuralNet_2L

scalation.modeling.neuralnet.NeuralNet_2L
See theNeuralNet_2L companion class
object NeuralNet_2L extends Scaling

The NeuralNet_2L companion object provides factory methods for creating two-layer (no hidden layer) neural networks. Note, 'scale' is defined in Scaling.

Attributes

Companion
class
Graph
Supertypes
trait Scaling
class Object
trait Matchable
class Any
Self type

Members list

Inherited
  • Not inherited
  • Scaling
Visibility
  • public
  • protected

Value members

Concrete methods

def apply(xy: MatrixD, fname: Array[String], hparam: HyperParameter, f: AFF)(col: Int): NeuralNet_2L

Create a NeuralNet_2L with automatic rescaling from a combined data matrix.

Create a NeuralNet_2L with automatic rescaling from a combined data matrix.

Value parameters

col

the first designated response column (defaults to the last column)

f

the activation function family for layers 1->2 (input to output)

fname

the feature/variable names (defaults to null)

hparam

the hyper-parameters (defaults to Optimizer.hp)

xy

the combined input and output matrix

Attributes

def perceptron(x: MatrixD, y_: VectorD, fname: Array[String], hparam: HyperParameter, f: AFF): NeuralNet_2L

Create a NeuralNet_2L with automatic rescaling from a data matrix and response vector. As the number of output nodes is one in this case, it is effectively a perceptron.

Create a NeuralNet_2L with automatic rescaling from a data matrix and response vector. As the number of output nodes is one in this case, it is effectively a perceptron.

Value parameters

f

the activation function family for layers 1->2 (input to output)

fname

the feature/variable names (defaults to null)

hparam

the hyper-parameters (defaults to Optimizer.hp)

x

the input/data m-by-n matrix

y_

the output/response m-vector

Attributes

def rescale(x: MatrixD, y: MatrixD, fname: Array[String], hparam: HyperParameter, f: AFF): NeuralNet_2L

Create a NeuralNet_2L with automatic rescaling from a data matrix and response matrix.

Create a NeuralNet_2L with automatic rescaling from a data matrix and response matrix.

Value parameters

f

the activation function family for layers 1->2 (input to output)

fname

the feature/variable names (defaults to null)

hparam

the hyper-parameters (defaults to Optimizer.hp)

x

the input/data m-by-n matrix

y

the output/response m-by-ny matrix

Attributes

Inherited methods

def setScale(scale_: Boolean): Unit

Set the scale flag to the given value.

Set the scale flag to the given value.

Value parameters

scale_

the new value for the scale flag

Attributes

Inherited from:
Scaling

Inherited fields

protected var scale: Boolean

The 'scale' flag indicated whether the data is to be rescaled/normalized

The 'scale' flag indicated whether the data is to be rescaled/normalized

Attributes

Inherited from:
Scaling