Package smile.base.mlp

Enum Class OutputFunction

java.lang.Object

java.lang.Enum<OutputFunction>

smile.base.mlp.OutputFunction

All Implemented Interfaces:

Serializable, Comparable<OutputFunction>, Constable

public enum OutputFunction
extends Enum<OutputFunction>

The output function of neural networks.

Nested Class Summary

Nested classes/interfaces inherited from class java.lang.Enum

Enum.EnumDesc<E extends Enum<E>>

Enum Constant Summary

Enum Constants

Enum Constant	Description
LINEAR	Linear/Identity function.
SIGMOID	Logistic sigmoid function: sigmoid(v)=1/(1+exp(-v)).
SOFTMAX	Softmax for multi-class cross entropy objection function.

Method Summary

Modifier and Type	Method	Description
abstract void	f(double[] x)	The output function.
abstract void	g(Cost cost, double[] g, double[] y)	The gradient function.
static OutputFunction	valueOf(String name)	Returns the enum constant of this class with the specified name.
static OutputFunction[]	values()	Returns an array containing the constants of this enum class, in the order they are declared.

Methods inherited from class java.lang.Enum

clone, compareTo, describeConstable, equals, finalize, getDeclaringClass, hashCode, name, ordinal, toString, valueOf

Methods inherited from class java.lang.Object

getClass, notify, notifyAll, wait, wait, wait

Enum Constant Details

LINEAR

public static final OutputFunction LINEAR

Linear/Identity function.

SIGMOID

public static final OutputFunction SIGMOID

Logistic sigmoid function: sigmoid(v)=1/(1+exp(-v)). For multi-class classification, each unit in output layer corresponds to a class. For binary classification and cross entropy error function, there is only one output unit whose value can be regarded as posteriori probability.

SOFTMAX

public static final OutputFunction SOFTMAX

Softmax for multi-class cross entropy objection function. The values of units in output layer can be regarded as posteriori probabilities of each class.

Method Details

values

public static OutputFunction[] values()

Returns an array containing the constants of this enum class, in the order they are declared.

Returns:

an array containing the constants of this enum class, in the order they are declared

valueOf

public static OutputFunction valueOf(String name)

Returns the enum constant of this class with the specified name. The string must match exactly an identifier used to declare an enum constant in this class. (Extraneous whitespace characters are not permitted.)

Parameters:

name - the name of the enum constant to be returned.

Returns:

the enum constant with the specified name

Throws:

IllegalArgumentException - if this enum class has no constant with the specified name

NullPointerException - if the argument is null

f

public abstract void f(double[] x)

The output function.

Parameters:

x - the input vector.

g

public abstract void g(Cost cost,
 double[] g,
 double[] y)

The gradient function.

Parameters:

cost - the cost function of neural network.

g - the gradient vector. On input, it holds target - output. On output, it is the gradient.

y - the output vector.