Use this function when you do not want to squash the net. For example, using this activation function with a network that has no hidden layers makes a perceptron model. Also, it is common to use this activation function on the output layer for regression problems. More...

#include <GActivation.h>

Inheritance diagram for GClasses::GActivationIdentity:

Public Member Functions
virtual double	center ()
	Returns 0.0. More...

virtual GActivationFunction *	clone ()
	See the comment for GActivationFunction::clone. More...

virtual double	derivative (double x)
	Returns 1.0. More...

virtual double	derivativeOfNet (double net, double activation)
	Returns 1.0. More...

virtual double	halfRange ()
	Returns 10000. More...

virtual double	identityBias ()
	Returns 0.0. More...

virtual double	identityDiag ()
	Returns 1.0. More...

virtual double	inverse (double y)
	Returns y. More...

virtual const char *	name () const
	Returns the name of this activation function. More...

virtual double	squash (double x)
	Returns x. More...

Public Member Functions inherited from GClasses::GActivationFunction
	GActivationFunction ()

virtual	~GActivationFunction ()

GDomNode *	serialize (GDom *pDoc) const
	Serialize this object. More...

Additional Inherited Members
Static Public Member Functions inherited from GClasses::GActivationFunction
static GActivationFunction *	deserialize (GDomNode *pNode)
	Deserialize this object. More...

Detailed Description

Use this function when you do not want to squash the net. For example, using this activation function with a network that has no hidden layers makes a perceptron model. Also, it is common to use this activation function on the output layer for regression problems.