OneLayerFFNN Class Reference

simple one layer neural network with configurable activation function More...

#include <onelayerffnn.h>

Inherits FeedForwardNN.

Inheritance diagram for OneLayerFFNN:

[legend]Collaboration diagram for OneLayerFFNN:

[legend]List of all members.

Public Member Functions
	OneLayerFFNN (double eps, double factor_bias=0.1)
	Uses linear activation function.
	OneLayerFFNN (double eps, double factor_bias, ActivationFunction actfun, ActivationFunction dactfun)
virtual	~OneLayerFFNN ()
virtual void	init (unsigned int inputDim, unsigned int outputDim, double unit_map=0.0, RandGen *randGen=0)
	initialisation of the network with the given number of input and output units
virtual const matrix::Matrix	process (const matrix::Matrix &input)
	passive processing of the input
virtual const matrix::Matrix	learn (const matrix::Matrix &input, const matrix::Matrix &nom_output, double learnRateFactor=1)
	performs learning and returns the network output before learning
virtual unsigned int	getInputDim () const
	returns the number of input neurons
virtual unsigned int	getOutputDim () const
	returns the number of output neurons
virtual const matrix::Matrix &	getWeights () const
virtual const matrix::Matrix &	getBias () const
virtual void	damp (double damping)
	damps the weights and the biases by multiplying (1-damping)
bool	store (FILE *f) const
	stores the layer binary into file stream
bool	restore (FILE *f)
	restores the layer binary from file stream
virtual paramkey	getName () const
	return the name of the object
virtual paramval	getParam (const paramkey key) const
virtual bool	setParam (const paramkey key, paramval val)
virtual paramlist	getParamList () const
	The list of all parameters with there value as allocated lists.

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Detailed Description

simple one layer neural network with configurable activation function

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Constructor & Destructor Documentation

OneLayerFFNN	(	double	eps,
		double	factor_bias = 0.1
	)			[inline]

Uses linear activation function.

Parameters:

	eps	learning rate
	factor_bias	learning rate factor for bias learning

OneLayerFFNN	(	double	eps,
		double	factor_bias,
		ActivationFunction	actfun,
		ActivationFunction	dactfun
	)			[inline]

Parameters:

	eps	learning rate
	factor_bias	learning rate factor for bias learning
	actfun	callback activation function (see FeedForwardNN)
	dactfun	callback for first derivative of the activation function

virtual ~OneLayerFFNN

(

)

[inline, virtual]

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Member Function Documentation

virtual void damp

(

double

damping

)

[inline, virtual]

damps the weights and the biases by multiplying (1-damping)

Implements FeedForwardNN.

virtual const matrix::Matrix& getBias

(

)

const [inline, virtual]

virtual unsigned int getInputDim

(

)

const [inline, virtual]

returns the number of input neurons

Implements AbstractModel.

virtual paramkey getName

(

)

const [inline, virtual]

return the name of the object

Reimplemented from Configurable.

virtual unsigned int getOutputDim

(

)

const [inline, virtual]

returns the number of output neurons

Implements AbstractModel.

virtual paramval getParam

(

const paramkey

key

)

const [inline, virtual]

virtual paramlist getParamList

(

)

const [inline, virtual]

The list of all parameters with there value as allocated lists.

Note that these are only parameters that are managed manually (with setParam, getParam)

See also:

getAllParamNames()

Returns:

list of key-value pairs

Reimplemented from Configurable.

virtual const matrix::Matrix& getWeights

(

)

const [inline, virtual]

void init	(	unsigned int	inputDim,
		unsigned int	outputDim,
		double	unit_map = 0.0,
		RandGen *	randGen = 0
	)			[virtual]

initialisation of the network with the given number of input and output units

Implements AbstractModel.

const Matrix learn	(	const matrix::Matrix &	input,
		const matrix::Matrix &	nom_output,
		double	learnRateFactor = 1
	)			[virtual]

performs learning and returns the network output before learning

Implements AbstractModel.

const Matrix process

(

const matrix::Matrix &

input

)

[virtual]

passive processing of the input

Implements AbstractModel.

bool restore

(

FILE *

f

)

[virtual]

restores the layer binary from file stream

Implements Storeable.

virtual bool setParam	(	const paramkey	key,
		paramval	val
	)			[inline, virtual]

bool store

(

FILE *

f

)

const [virtual]

stores the layer binary into file stream

Implements Storeable.

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

• onelayerffnn.h
• onelayerffnn.cpp

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