Artificial Neural Networks - Multi-Layer Perceptrons. More...

#include "ml.hpp"

Inheritance diagram for cv::ml::ANN_MLP_ANNEAL:

Public Member Functions
virtual double	getAnnealCoolingRatio () const =0

virtual double	getAnnealFinalT () const =0

virtual double	getAnnealInitialT () const =0

virtual int	getAnnealItePerStep () const =0

virtual void	setAnnealCoolingRatio (double val)=0

virtual void	setAnnealEnergyRNG (const RNG &rng)=0
	Set/initialize anneal RNG. More...

virtual void	setAnnealFinalT (double val)=0

virtual void	setAnnealInitialT (double val)=0

virtual void	setAnnealItePerStep (int val)=0

Public Member Functions inherited from cv::ml::ANN_MLP
double	getAnnealCoolingRatio () const

double	getAnnealFinalT () const

double	getAnnealInitialT () const

int	getAnnealItePerStep () const

virtual double	getBackpropMomentumScale () const =0

virtual double	getBackpropWeightScale () const =0

virtual cv::Mat	getLayerSizes () const =0

virtual double	getRpropDW0 () const =0

virtual double	getRpropDWMax () const =0

virtual double	getRpropDWMin () const =0

virtual double	getRpropDWMinus () const =0

virtual double	getRpropDWPlus () const =0

virtual TermCriteria	getTermCriteria () const =0

virtual int	getTrainMethod () const =0

virtual Mat	getWeights (int layerIdx) const =0

virtual void	setActivationFunction (int type, double param1=0, double param2=0)=0

void	setAnnealCoolingRatio (double val)

void	setAnnealEnergyRNG (const RNG &rng)
	Set/initialize anneal RNG. More...

void	setAnnealFinalT (double val)

void	setAnnealInitialT (double val)

void	setAnnealItePerStep (int val)

virtual void	setBackpropMomentumScale (double val)=0

virtual void	setBackpropWeightScale (double val)=0

virtual void	setLayerSizes (InputArray _layer_sizes)=0

virtual void	setRpropDW0 (double val)=0

virtual void	setRpropDWMax (double val)=0

virtual void	setRpropDWMin (double val)=0

virtual void	setRpropDWMinus (double val)=0

virtual void	setRpropDWPlus (double val)=0

virtual void	setTermCriteria (TermCriteria val)=0

virtual void	setTrainMethod (int method, double param1=0, double param2=0)=0

Public Member Functions inherited from cv::ml::StatModel
virtual float	calcError (const Ptr< TrainData > &data, bool test, OutputArray resp) const
	Computes error on the training or test dataset. More...

virtual bool	empty () const CV_OVERRIDE
	Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read. More...

virtual int	getVarCount () const =0
	Returns the number of variables in training samples. More...

virtual bool	isClassifier () const =0
	Returns true if the model is classifier. More...

virtual bool	isTrained () const =0
	Returns true if the model is trained. More...

virtual float	predict (InputArray samples, OutputArray results=noArray(), int flags=0) const =0
	Predicts response(s) for the provided sample(s) More...

virtual bool	train (const Ptr< TrainData > &trainData, int flags=0)
	Trains the statistical model. More...

virtual bool	train (InputArray samples, int layout, InputArray responses)
	Trains the statistical model. More...

Public Member Functions inherited from cv::Algorithm
	Algorithm ()

virtual	~Algorithm ()

virtual void	clear ()
	Clears the algorithm state. More...

virtual String	getDefaultName () const

virtual void	read (const FileNode &fn)
	Reads algorithm parameters from a file storage. More...

virtual void	save (const String &filename) const

virtual void	write (FileStorage &fs) const
	Stores algorithm parameters in a file storage. More...

void	write (const Ptr< FileStorage > &fs, const String &name=String()) const
	simplified API for language bindings This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts. More...

Additional Inherited Members
Public Types inherited from cv::ml::ANN_MLP
enum	ActivationFunctions { IDENTITY = 0, SIGMOID_SYM = 1, GAUSSIAN = 2, RELU = 3, LEAKYRELU = 4 }

enum	TrainFlags { UPDATE_WEIGHTS = 1, NO_INPUT_SCALE = 2, NO_OUTPUT_SCALE = 4 }

enum	TrainingMethods { BACKPROP =0, RPROP = 1, ANNEAL = 2 }

Public Types inherited from cv::ml::StatModel
enum	Flags { UPDATE_MODEL = 1, RAW_OUTPUT =1, COMPRESSED_INPUT =2, PREPROCESSED_INPUT =4 }

Static Public Member Functions inherited from cv::ml::ANN_MLP
static Ptr< ANN_MLP >	create ()
	Creates empty model. More...

static Ptr< ANN_MLP >	load (const String &filepath)
	Loads and creates a serialized ANN from a file. More...

Static Public Member Functions inherited from cv::ml::StatModel
template<typename _Tp >
static Ptr< _Tp >	train (const Ptr< TrainData > &data, int flags=0)
	Create and train model with default parameters. More...

Static Public Member Functions inherited from cv::Algorithm
template<typename _Tp >
static Ptr< _Tp >	load (const String &filename, const String &objname=String())
	Loads algorithm from the file. More...

template<typename _Tp >
static Ptr< _Tp >	loadFromString (const String &strModel, const String &objname=String())
	Loads algorithm from a String. More...

template<typename _Tp >
static Ptr< _Tp >	read (const FileNode &fn)
	Reads algorithm from the file node. More...

Protected Member Functions inherited from cv::Algorithm
void	writeFormat (FileStorage &fs) const

Detailed Description

Artificial Neural Networks - Multi-Layer Perceptrons.

See also: Neural Networks

Member Function Documentation

§ getAnnealCoolingRatio()

virtual double cv::ml::ANN_MLP_ANNEAL::getAnnealCoolingRatio ( ) const

pure virtual

Python:
	retval	=	cv.ml_ANN_MLP_ANNEAL.getAnnealCoolingRatio(		)

ANNEAL: Update cooling ratio. It must be >0 and less than 1. Default value is 0.95.

See also: setAnnealCoolingRatio

§ getAnnealFinalT()

virtual double cv::ml::ANN_MLP_ANNEAL::getAnnealFinalT ( ) const

pure virtual

Python:
	retval	=	cv.ml_ANN_MLP_ANNEAL.getAnnealFinalT(		)

ANNEAL: Update final temperature. It must be >=0 and less than initialT. Default value is 0.1.

See also: setAnnealFinalT

§ getAnnealInitialT()

virtual double cv::ml::ANN_MLP_ANNEAL::getAnnealInitialT ( ) const

pure virtual

Python:
	retval	=	cv.ml_ANN_MLP_ANNEAL.getAnnealInitialT(		)

See also: setAnnealInitialT

§ getAnnealItePerStep()

virtual int cv::ml::ANN_MLP_ANNEAL::getAnnealItePerStep ( ) const

pure virtual

Python:
	retval	=	cv.ml_ANN_MLP_ANNEAL.getAnnealItePerStep(		)

ANNEAL: Update iteration per step. It must be >0 . Default value is 10.

See also: setAnnealItePerStep

§ setAnnealCoolingRatio()

virtual void cv::ml::ANN_MLP_ANNEAL::setAnnealCoolingRatio ( double val )

pure virtual

Python:
	None	=	cv.ml_ANN_MLP_ANNEAL.setAnnealCoolingRatio(	val	)

See also: getAnnealCoolingRatio

§ setAnnealEnergyRNG()

virtual void cv::ml::ANN_MLP_ANNEAL::setAnnealEnergyRNG ( const RNG & rng )

pure virtual

Set/initialize anneal RNG.

§ setAnnealFinalT()

virtual void cv::ml::ANN_MLP_ANNEAL::setAnnealFinalT ( double val )

pure virtual

Python:
	None	=	cv.ml_ANN_MLP_ANNEAL.setAnnealFinalT(	val	)

See also: getAnnealFinalT

§ setAnnealInitialT()

virtual void cv::ml::ANN_MLP_ANNEAL::setAnnealInitialT ( double val )

pure virtual

Python:
	None	=	cv.ml_ANN_MLP_ANNEAL.setAnnealInitialT(	val	)

See also: getAnnealInitialT

§ setAnnealItePerStep()

virtual void cv::ml::ANN_MLP_ANNEAL::setAnnealItePerStep ( int val )

pure virtual

Python:
	None	=	cv.ml_ANN_MLP_ANNEAL.setAnnealItePerStep(	val	)

See also: getAnnealItePerStep

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

ml/include/opencv2/ml.hpp

Public Member Functions

Additional Inherited Members

Detailed Description

Member Function Documentation

§ getAnnealCoolingRatio()

§ getAnnealFinalT()

§ getAnnealInitialT()

§ getAnnealItePerStep()

§ setAnnealCoolingRatio()

§ setAnnealEnergyRNG()

§ setAnnealFinalT()

§ setAnnealInitialT()

§ setAnnealItePerStep()