iCub::optimization::ff2LayNNTrain_tansig_purelin Class Reference

Class to deal with training of Feed-Forward 2 layers Neural Network with a tansig function for the hidden nodes and a purelin for the output nodes. More...

#include <neuralNetworks.h>

Inheritance diagram for iCub::optimization::ff2LayNNTrain_tansig_purelin:

Additional Inherited Members
Public Member Functions inherited from iCub::optimization::ff2LayNNTrain
	ff2LayNNTrain ()
	Default constructor.
void	setBounds (const yarp::os::Property &bounds)
	Allow specifying the bounds for training network's parameters.
virtual bool	train (const unsigned int numHiddenNodes, const std::deque< yarp::sig::Vector > &in, const std::deque< yarp::sig::Vector > &out, std::deque< yarp::sig::Vector > &pred, double &error)
	Train the network through optimization.
virtual bool	retrain (const std::deque< yarp::sig::Vector > &in, const std::deque< yarp::sig::Vector > &out, std::deque< yarp::sig::Vector > &pred, double &error)
	Retrain the network through optimization.
virtual	~ff2LayNNTrain ()
	Default destructor.
Public Member Functions inherited from iCub::ctrl::ff2LayNN
	ff2LayNN ()
	Create an empty network.
	ff2LayNN (const yarp::os::Property &options)
	Create and configure the network.
virtual bool	configure (const yarp::os::Property &options)
	Configure/reconfigure the network.
virtual bool	isValid () const
	Return the internal status after a configuration.
virtual yarp::sig::Vector	predict (const yarp::sig::Vector &x) const
	Predict the output given a certain input to the network.
virtual bool	getStructure (yarp::os::Property &options) const
	Retrieve the network structure as a Property object.
virtual bool	printStructure (std::ostream &stream=std::cout) const
	Dump tadily the network structure on the stream.
std::deque< yarp::sig::Vector > &	get_IW ()
	Retrieve first layer weights.
std::deque< yarp::sig::Vector > &	get_LW ()
	Retrieve second layer weights.
yarp::sig::Vector &	get_b1 ()
	Retrieve first layer bias.
yarp::sig::Vector &	get_b2 ()
	Retrieve second layer bias.
virtual yarp::sig::Vector	scaleInputToNetFormat (const yarp::sig::Vector &x) const
	Scale input to be used with the network.
virtual yarp::sig::Vector	scaleInputFromNetFormat (const yarp::sig::Vector &x) const
	Scale back input from the network's format.
virtual yarp::sig::Vector	scaleOutputToNetFormat (const yarp::sig::Vector &x) const
	Scale output to be used with the network.
virtual yarp::sig::Vector	scaleOutputFromNetFormat (const yarp::sig::Vector &x) const
	Scale back output from the network's format.
Public Member Functions inherited from iCub::ctrl::ff2LayNN_tansig_purelin
	ff2LayNN_tansig_purelin ()
	Create an empty network.
	ff2LayNN_tansig_purelin (const yarp::os::Property &options)
	Create and configure the network.
virtual yarp::sig::Vector	hiddenLayerFcn (const yarp::sig::Vector &x) const
	Hidden Layer Function.
virtual yarp::sig::Vector	outputLayerFcn (const yarp::sig::Vector &x) const
	Output Layer Function.
virtual yarp::sig::Vector	hiddenLayerGrad (const yarp::sig::Vector &x) const
	Gradient of the Hidden Layer Function.
virtual yarp::sig::Vector	outputLayerGrad (const yarp::sig::Vector &x) const
	Gradient of the Output Layer Function.
Protected Member Functions inherited from iCub::ctrl::ff2LayNN
void	prepare ()
void	setItem (yarp::os::Property &options, const std::string &tag, const yarp::sig::Vector &item) const
bool	getItem (const yarp::os::Property &options, const std::string &tag, yarp::sig::Vector &item) const
Protected Attributes inherited from iCub::optimization::ff2LayNNTrain
yarp::os::Property	bounds
void *	App
Protected Attributes inherited from iCub::ctrl::ff2LayNN
std::deque< yarp::sig::Vector >	IW
yarp::sig::Vector	b1
std::deque< yarp::sig::Vector >	LW
yarp::sig::Vector	b2
std::deque< minmax >	inMinMaxX
std::deque< minmax >	inMinMaxY
std::deque< minmax >	outMinMaxX
std::deque< minmax >	outMinMaxY
yarp::sig::Vector	inMinX
yarp::sig::Vector	inMinY
yarp::sig::Vector	inRatio
yarp::sig::Vector	outMinX
yarp::sig::Vector	outMinY
yarp::sig::Vector	outRatio
bool	configured

Detailed Description

Class to deal with training of Feed-Forward 2 layers Neural Network with a tansig function for the hidden nodes and a purelin for the output nodes.

Definition at line 113 of file neuralNetworks.h.

---

The documentation for this class was generated from the following file:

• icub-main/src/libraries/optimization/include/iCub/optimization/neuralNetworks.h