An adaptive learning rate Trainer (Zeiler). More...

#include <Adadelta.h>

Public Member Functions
	Adadelta (double rho_, double targetErrorLevel_, int maximumEpochs_)
	Initialize an Adadelta object with necessary constants. More...

void	store (std::ofstream *output)
	Stores an Adadelta object using specified ofstream. More...

bool	initFromStream (std::ifstream *in)

Public Member Functions inherited from net::SGDTrainer
	SGDTrainer ()
	Initialize empty Backpropagation object. More...

	SGDTrainer (double targetErrorLevel_, int maximumEpochs_)
	Initialize the object with necessary constants. More...

double	train (net::NeuralNet *network, const std::vector< std::vector< double > > &input, const std::vector< std::vector< double > > &correctOutput)
	Trains a neural network on a training set until the target error level is reached. More...

double	trainEpocs (double numberOfEpochs, net::NeuralNet *network, const std::vector< std::vector< double > > &input, const std::vector< std::vector< double > > &correctOutput)
	Trains a neural network on a training set for a specified number of epochs. More...

void	store (std::ofstream *out)
	Stores a Trainer object using specified stream. More...

bool	initFromStream (std::ifstream *in)

Public Member Functions inherited from net::Trainer
std::vector< std::vector < std::vector< std::vector < double > > > >	getGradients ()

std::vector< std::vector < std::vector< std::vector < double > > > >	getWeightChanges ()

std::vector< std::vector < std::vector< double > > >	getInitialWeights ()

std::vector< std::vector < std::vector< double > > >	getFinalWeights ()

Public Attributes
double	rho
	the decay rate of the system, set by constructor More...

double	epsilon
	a very small number used for root mean square calculations More...

Public Attributes inherited from net::SGDTrainer
double	targetErrorLevel
	The target error level, set by constructor. More...

int	maximumEpochs
	The maximum number of iterations, set by constructor. More...

Protected Member Functions
void	resetNetworkVectors (net::NeuralNet *network)
	Resets the Adadelta object's accumulation vectors. More...

double	getChangeInWeight (double weight, int layerIndex, int neuronIndex, int weightIndex)

Protected Member Functions inherited from net::SGDTrainer
double	trainOnDataPoint (net::NeuralNet *network, const std::vector< double > &input, const std::vector< double > &correctOutput)
	Gets the output of the neural network, calculates the error of each neuron, and edits the weights of the neurons to reduce error. More...

Protected Attributes
std::vector< std::vector < std::vector< double > > >	accumulatedGradients

std::vector< std::vector < std::vector< double > > >	accumulatedUpdates

Protected Attributes inherited from net::Trainer
std::vector< std::vector < std::vector< std::vector < double > > > >	gradients

std::vector< std::vector < std::vector< std::vector < double > > > >	weightChanges

std::vector< std::vector < std::vector< double > > >	initialWeights

std::vector< std::vector < std::vector< double > > >	finalWeights

Detailed Description

An adaptive learning rate Trainer (Zeiler).

Constructor & Destructor Documentation

Initialize an Adadelta object with necessary constants.

Parameters

rho_	decay level of the trainer. Between 0 and 1.
targetErrorLevel_	at this error level, a net will be considered trained
maximumEpochs_	after this number of training iterations (one pass through all of the data points), a net will stop being trained no matter what

double Adadelta::getChangeInWeight	(	double	weight,
		int	layerIndex,
		int	neuronIndex,
		int	weightIndex
	)

protectedvirtual

bool Adadelta::initFromStream ( std::ifstream * in )

void Adadelta::resetNetworkVectors ( net::NeuralNet * network )

protectedvirtual

Resets the Adadelta object's accumulation vectors.

Reimplemented from net::SGDTrainer.

void Adadelta::store ( std::ofstream * output )

virtual

Stores an Adadelta object using specified ofstream.

Parameters

output pointer to the output stream which the neural network will be written to

std::vector< std::vector< std::vector<double> > > net::Adadelta::accumulatedGradients

protected

std::vector< std::vector< std::vector<double> > > net::Adadelta::accumulatedUpdates

protected

double net::Adadelta::epsilon

a very small number used for root mean square calculations

double net::Adadelta::rho

the decay rate of the system, set by constructor

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