#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
Protected Member Functions
virtual void	_getConfiguration (ConfigurationPtr &) const
virtual void	_setConfiguration (const ConstConfigurationPtr &)
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

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 [protected, virtual]

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 ) [protected, virtual]

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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