#include <nn_alg.hh>

Inheritance diagram for NNAlgorithm:

Collaboration diagram for NNAlgorithm:

Public Member Functions
	NNAlgorithm ()

	~NNAlgorithm ()

int	needNormalization ()

int	initialize ()

int	iterate ()

float	getProgress () const

int	done () const

Scalar	getValue (const Sample &x) const

Public Member Functions inherited from AlgorithmImpl
	AlgorithmImpl (AlgMetadata const *metadata)

virtual	~AlgorithmImpl ()

void	setParameters (int nparam, AlgParameter const *param)

void	setParameters (const ParamSetType &)

std::string const	getID () const

AlgMetadata const *	getMetadata () const

AlgorithmPtr	getFreshCopy ()

virtual int	supportsModelProjection () const

Model	createModel (const SamplerPtr &samp, CallbackWrapper *func=0)

void	setSampler (const SamplerPtr &samp)

virtual int	finalize ()

virtual int	getConvergence (Scalar *const val) const

Normalizer *	getNormalizer () const

void	setNormalization (const SamplerPtr &samp) const

void	setNormalization (const EnvironmentPtr &env) const

virtual Model	getModel () const

ConfigurationPtr	getConfiguration () const

void	setConfiguration (const ConstConfigurationPtr &)

Public Member Functions inherited from Configurable
virtual	~Configurable ()

Protected Member Functions
virtual void	_getConfiguration (ConfigurationPtr &) const

virtual void	_setConfiguration (const ConstConfigurationPtr &)

Protected Member Functions inherited from AlgorithmImpl
int	dimDomain ()

int	getParameter (std::string const &name, std::string *value)

int	getParameter (std::string const &name, double *value)

int	getParameter (std::string const &name, float *value)

int	getParameter (std::string const &name, int *value)

Protected Attributes
bool	_done

int	_num_layers

int	num_presences

int	num_absences

Network	network

vector< vector< double > >	vector_input

vector< vector< double > >	vector_output

nn_parameter	_nn_parameter

double *	outputs

unsigned long	amount_epoch

float	_progress

int	converged

OccurrencesPtr	absences

OccurrencesPtr	presences

Protected Attributes inherited from AlgorithmImpl
SamplerPtr	_samp

Normalizer *	_normalizerPtr

ParamSetType	_param

Additional Inherited Members
Public Types inherited from AlgorithmImpl
typedef std::map< icstring, std::string >	ParamSetType

Detailed Description

Declaration of Neural Network algorithm class.

Author: Fabr�cio Augusto Rodrigues (fabricio.rodrigues [at] poli . usp .br); Alex Oshika Avilla (alex.avilla [at] poli . usp .br)

Id:: nn_alg.hh 5844 2013-08-22 15:16:12Z rdg

LICENSE INFORMATION

http://www.cria.org.br

This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details:

http://www.gnu.org/copyleft/gpl.html

Definition at line 43 of file nn_alg.hh.

Constructor & Destructor Documentation

NNAlgorithm::NNAlgorithm ( )

Definition at line 210 of file nn_alg.cpp.

References AlgorithmImpl::_normalizerPtr.

NNAlgorithm::~NNAlgorithm ( )

Definition at line 222 of file nn_alg.cpp.

Member Function Documentation

void NNAlgorithm::_getConfiguration ( ConfigurationPtr & config ) const

protectedvirtual

Reimplemented from AlgorithmImpl.

Definition at line 622 of file nn_alg.cpp.

References _done, _nn_parameter, _num_layers, Network::getBias(), Network::getWeight(), nn_parameter::hid, and network.

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void NNAlgorithm::_setConfiguration ( const ConstConfigurationPtr & config )

protectedvirtual

Reimplemented from AlgorithmImpl.

Definition at line 713 of file nn_alg.cpp.

References _done, _nn_parameter, _num_layers, nn_parameter::hid, nn_parameter::learning_rate, network, Network::RandomizeWB(), Network::setBias(), Network::SetData(), and Network::setWeight().

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int NNAlgorithm::done ( ) const

virtual

Use this method to find out if the model has completed (e.g. convergence point has been met.

Note: This method is inherited from the Algorithm class

Returns: Implementation specific but usually 1 for completion.

Reimplemented from AlgorithmImpl.

Definition at line 579 of file nn_alg.cpp.

References _done, Log::debug(), Log::instance(), and NN_LOG_PREFIX.

Referenced by getProgress().

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float NNAlgorithm::getProgress ( ) const

virtual

Return progress so far

Reimplemented from AlgorithmImpl.

Definition at line 560 of file nn_alg.cpp.

References _progress, and done().

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Scalar NNAlgorithm::getValue ( const Sample & x ) const

virtual

This method is used when projecting the model.

Note: This method is inherited from the Algorithm class

Returns

Parameters

x	Pointer to a vector of openModeller Scalar type (currently double). The vector should contain values looked up on the environmental variable layers into which the mode is being projected.

This method is used when projecting the model.

Note: This method is inherited from the Algorithm class

Returns

Parameters

Scalar *x a pointer to a vector of openModeller Scalar type (currently double). The vector should contain values looked up on the environmental variable layers into which the mode is being projected.

Implements AlgorithmImpl.

Definition at line 597 of file nn_alg.cpp.

References _num_layers, Network::GetOutput(), network, and Network::SetInputs().

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