smile.base.mlp

Class HiddenLayer

java.lang.Object

smile.base.mlp.Layer

smile.base.mlp.HiddenLayer

All Implemented Interfaces:

java.io.Serializable

public class HiddenLayer
extends Layer

A hidden layer in the neural network.

See Also:

Serialized Form

Field Summary

Fields inherited from class smile.base.mlp.Layer

bias, gradient, n, output, p, update, updateBias, weight

Constructor Summary

Constructors

Constructor and Description
HiddenLayer(int n, int p, ActivationFunction f) Constructor.

Method Summary

Modifier and Type	Method and Description
void	backpropagate(double[] error) Propagates the errors back to a lower layer.
void	f(double[] x) The activation or output function.
java.lang.String	toString()

Methods inherited from class smile.base.mlp.Layer

computeUpdate, getInputSize, getOutputSize, gradient, linear, mle, mse, output, propagate, rectifier, sigmoid, tanh, update

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Detail

HiddenLayer

public HiddenLayer(int n,
                   int p,
                   ActivationFunction f)

Constructor.

Parameters:

n - the number of neurons.

p - the number of input variables (not including bias value).

f - the activation function.

Method Detail

toString

public java.lang.String toString()

Overrides:

toString in class java.lang.Object

f

public void f(double[] x)

Description copied from class: Layer

The activation or output function.

Specified by:

f in class Layer

Parameters:

x - the input and output values.

backpropagate

public void backpropagate(double[] error)

Description copied from class: Layer

Propagates the errors back to a lower layer.

Specified by:

backpropagate in class Layer

Parameters:

error - the gradient vector of lower layer.