#include <Backpropagation.h>

Public Member Functions
	Backpropagation (double learningRate_, double momentumTerm_, double targetErrorLevel_, int maximumEpochs_)
	Initialize the Backpropagation object with necessary constants. More...

	Backpropagation ()
	Initialize empty Backpropagation object. More...

	Backpropagation (std::ifstream *input)
	Loads a Backpropagation object using an input stream. More...

void	store (std::ofstream *output)
	Stores a Backpropagation 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	learningRate
	The rate of learning, set by constructor. More...

double	momentumTerm
	The term of momentum, set by constructor. 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
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...

virtual void	resetNetworkVectors (net::NeuralNet *network)
	Resets the Backpropagation object's neural network specific vectors using a neural network (NN is needed because the number of layers, neurons, and weights are needed). More...

Additional Inherited Members
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

A classic SGDTrainer.

Constructor & Destructor Documentation

Backpropagation::Backpropagation	(	double	learningRate_,
		double	momentumTerm_,
		double	targetErrorLevel_,
		int	maximumEpochs_
	)

Initialize the Backpropagation object with necessary constants.

Parameters

learningRate_	controls how much the neural network is modified each learning iteration
momentumTerm_	allows a network to escape a local max
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

Backpropagation::Backpropagation ( )

Initialize empty Backpropagation object.

Backpropagation::Backpropagation ( std::ifstream * input )

explicit

Loads a Backpropagation object using an input stream.

Parameters

input a pointer to the input stream that contains a stored Backpropagation model

Member Function Documentation

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

protectedvirtual

Implements net::SGDTrainer.

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

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

virtual

Stores a Backpropagation object using specified ofstream.

Parameters

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

Implements net::Trainer.

Member Data Documentation

double net::Backpropagation::learningRate

The rate of learning, set by constructor.

double net::Backpropagation::momentumTerm

The term of momentum, set by constructor.

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

/home/truell20/Documents/Fido/Fido/include/Backpropagation.h
/home/truell20/Documents/Fido/Fido/src/Backpropagation.cpp

Public Member Functions

Public Attributes

Protected Member Functions

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation