Transfer Object (DTO) for neural network training limits. More...

Inheritance diagram for IG.Num.NeuralTrainingLimitsDto:

Collaboration diagram for IG.Num.NeuralTrainingLimitsDto:

Public Member Functions
override NeuralTrainingLimits	CreateObject ()
	Creates and returns a new object of the corresponding type. More...

Public Attributes
double	LearningRateMin
	Minimum limit for learning rate. More...

double	LearningRateMax
	Maximum limit for learning rate. More...

int	LearningRateNum
	Number of learning rates. More...

double	MomentumMin
	Minimum limit for momentum. More...

double	MomentumMax
	Maximum limit for momentum. More...

int	MomentumNum
	Number of momentums. More...

double	AlphaMin
	Minimum limit for alpha value. More...

double	AlphaMax
	Maximum limit for alpha value. More...

int	AlphaNum
	Number of alpha values. More...

double	InputSafetyFactorMin
	Minimum limit for input safety factor value. More...

double	InputSafetyFactorMax
	Maximum limit for input safety factor value. More...

int	InputSafetyFactorNum
	Number of input safety factor values. More...

double	OutputSafetyFactorMin
	Minimum limit for output safety factor value. More...

double	OutputSafetyFactorMax
	Maximum limit for output safety factor value. More...

int	OutputSafetyFactorNum
	Number of output safety factor values. More...

int	MaxEpochs
	Maximum number of epochs performed in training. More...

int	EpochBundle
	Number of epochs in boundle. More...

bool	EnableRangeTolerance
	Flag for enabling toelrance that represent a percentage of the output range. More...

VectorDtoBase	ToleranceRms
	Tolerance over RMS error of outputs over training points. Training will continue until error becomes below tolerance or until maximal number of epochs is reached. If less or equal than 0 then this tolerance is not taken into account. More...

VectorDtoBase	ToleranceRmsRelativeToRange
	Relative tolerances on RMS errors of outputs over training points, relative to the correspoinding ranges of output data. More...

double	ToleranceRmsRelativeToRangeScalar = NeuralTrainingParameters.DefaultToleranceRmsRelativeToRangeScalar
	Scalar through which all components of the Relative tolerances on RMS errors of outputs can be set to the same value. More...

VectorDtoBase	ToleranceMax
	Tolerance on maximal error of outputs over training points. Training will continue until error becomes below tolerance or until maximal number of epochs is reached. If less or equal than 0 then this tolerance is not taken into account. More...

VectorDtoBase	ToleranceMaxRelativeToRange
	Relative tolerances on max. abs. errors of outputs over training points, relative to the correspoinding ranges of output data. More...

double	ToleranceMaxRelativeToRangeScalar = NeuralTrainingParameters.DefaultToleranceMaxRelativeToRangeScalar
	Scalar through which all components of the Relative tolerances on max. abs. errors of outputs can be set to the same value. More...

int	InputLenght
	Number of input neurons. More...

int	OutputLength
	Number of output neurons. More...

bool	EnableArchitectureTest
	Flag for enabling test in architecture of ANN. More...

int	NumHiddenLayersNum
	Number of hidden layers in neural network. More...

int	NumHiddenNeuronsFirstMin
	Minimum number of hidden neurons in first hidden layer. More...

int	NumHiddenNeuronsFirstMax
	Maximum number of hidden neurons in first hidden layer. More...

int	NumHiddenNeuronsFirstNum
	Number of numbers of hidden neurons in first hidden layer. More...

int[]	NumHiddenNeuronsFirstValues
	Values for number of hidden neurons in the first hidden layer. More...

int	NumHiddenNeuronsSecondMin
	Minimum number of hidden neurons in second hidden layer. More...

int	NumHiddenNeuronsSecondMax
	Maximum number of hidden neurons in second hidden layer. More...

int	NumHiddenNeuronsSecondNum
	Number of numbers of hidden neurons in second hidden layer. More...

int[]	NumHiddenNeuronsSecondValues
	Values for number of hidden neurons in the second hidden layer. More...

int	NumHiddenNeuronsThirdMin
	Minimum number of hidden neurons in third hidden layer. More...

int	NumHiddenNeuronsThirdMax
	Maximum number of hidden neurons in third hidden layer. More...

int	NumHiddenNeuronsThirdNum
	Number of numbers of hidden neurons in third hidden layer. More...

int[]	NumHiddenNeuronsThirdValues
	Values for number of hidden neurons in the third hidden layer. More...

Protected Member Functions
override void	CopyFromPlain (NeuralTrainingLimits trainingLimits)
	Copies the specified training limits to the current DTO. More...

override void	CopyToPlain (ref NeuralTrainingLimits trainingLimits)
	Copies contents of the current DTO to the specified training limits object. More...

Protected Member Functions inherited from IG.Lib.SerializationDto< NeuralTrainingLimits >
	SerializationDto ()

Additional Inherited Members
Static Public Member Functions inherited from IG.Lib.SerializationDto< NeuralTrainingLimits >
static ObjectType	CopyToObjectReturned< DtoType, ObjectType > (DtoType dto, ObjectType obj)
	Replacement for CopyToObject for cases where object can not be passed by reference. The returned object must be assigned to object (property, list element, etc.) to which object state is copied. More...

static void	CopyToObject< DtoType, ObjectType > (DtoType dto, ref ObjectType obj)
	Copies object state form the specified DTO (data transfer object) to the specified object. More...

static DtoType	CopyFromObjectReturned< DtoType, ObjectType > (ObjectType obj, DtoType dto)
	Replacement for CopyFromObject for cases where object can not be passed by reference. The returned object must be assigned to object (property, list element, etc.) to which object state is copied. More...

static void	CopyFromObject< DtoType, ObjectType > (ObjectType obj, ref DtoType dto)
	Copies object state form the specified object to the corresponding DTO (data transfer object). More...

static ObjectType[]	CopyArrayToObjectReturned< DtoType, ObjectType > (DtoType[] tabDto, ObjectType[] tabObj)
	Replacement for CopyArrayToObject for cases where object can not be passed by reference. The returned object must be assigned to object (property, list element, etc.) to which data is copied. More...

static void	CopyArrayToObject< DtoType, ObjectType > (DtoType[] tabDto, ref ObjectType[] tabObj)
	Copies array of DTOs (Data Transfer Objects) to an array of appropriate objects. More...

static DtoType[]	CopyArrayFromObjectReturned< DtoType, ObjectType > (ObjectType[] tabObj, DtoType[] tabDto)
	Replacement for CopyArrayFromObject for cases where object can not be passed by reference. The returned object must be assigned to object (property, list element, etc.) to which data is copied. More...

static void	CopyArrayFromObject< DtoType, ObjectType > (ObjectType[] tabObj, ref DtoType[] tabDto)
	Copies array of objects to an array of DTOs. More...

static List< ObjectType >	CopyListToObjectReturned< DtoType, ObjectType > (DtoType[] tabDto, List< ObjectType > listObj)
	Replacement for CopyListToObject for cases where object can not be passed by reference. The returned object must be assigned to object (property, list element, etc.) to which data is copied. More...

static void	CopyListToObject< DtoType, ObjectType > (DtoType[] tabDto, ref List< ObjectType > listObj)
	Copies array of DTOs (Data Transfer Objects) to a list of appropriate objects. More...

static DtoType[]	CopyListFromObjectReturned< DtoType, ObjectType > (List< ObjectType > tabObj, DtoType[] tabDto)
	Replacement for CopyArrayFromObject for cases where object can not be passed by reference. The returned object must be assigned to object (property, list element, etc.) to which data is copied. More...

static void	CopyListFromObject< DtoType, ObjectType > (List< ObjectType > tabObj, ref DtoType[] tabDto)
	Copies array of objects to a list of DTOs. More...

Detailed Description

Transfer Object (DTO) for neural network training limits.

$A Igor Jul10 Aug12; Tako78 Aug12;

Member Function Documentation

override NeuralTrainingLimits IG.Num.NeuralTrainingLimitsDto.CreateObject ( )

inline

Creates and returns a new object of the corresponding type.

override void IG.Num.NeuralTrainingLimitsDto.CopyFromPlain ( NeuralTrainingLimits trainingLimits )

inlineprotected

Copies the specified training limits to the current DTO.

Parameters

trainingLimits Object that is copied to the current DTO.

override void IG.Num.NeuralTrainingLimitsDto.CopyToPlain ( ref NeuralTrainingLimits trainingLimits )

inlineprotected

Copies contents of the current DTO to the specified training limits object.

Parameters

trainingLimits Object that the current DTO content is copied to.

Member Data Documentation

double IG.Num.NeuralTrainingLimitsDto.LearningRateMin

Minimum limit for learning rate.

double IG.Num.NeuralTrainingLimitsDto.LearningRateMax

Maximum limit for learning rate.

int IG.Num.NeuralTrainingLimitsDto.LearningRateNum

Number of learning rates.

double IG.Num.NeuralTrainingLimitsDto.MomentumMin

Minimum limit for momentum.

double IG.Num.NeuralTrainingLimitsDto.MomentumMax

Maximum limit for momentum.

int IG.Num.NeuralTrainingLimitsDto.MomentumNum

Number of momentums.

double IG.Num.NeuralTrainingLimitsDto.AlphaMin

Minimum limit for alpha value.

double IG.Num.NeuralTrainingLimitsDto.AlphaMax

Maximum limit for alpha value.

int IG.Num.NeuralTrainingLimitsDto.AlphaNum

Number of alpha values.

double IG.Num.NeuralTrainingLimitsDto.InputSafetyFactorMin

Minimum limit for input safety factor value.

double IG.Num.NeuralTrainingLimitsDto.InputSafetyFactorMax

Maximum limit for input safety factor value.

int IG.Num.NeuralTrainingLimitsDto.InputSafetyFactorNum

Number of input safety factor values.

double IG.Num.NeuralTrainingLimitsDto.OutputSafetyFactorMin

Minimum limit for output safety factor value.

double IG.Num.NeuralTrainingLimitsDto.OutputSafetyFactorMax

Maximum limit for output safety factor value.

int IG.Num.NeuralTrainingLimitsDto.OutputSafetyFactorNum

Number of output safety factor values.

int IG.Num.NeuralTrainingLimitsDto.MaxEpochs

Maximum number of epochs performed in training.

int IG.Num.NeuralTrainingLimitsDto.EpochBundle

Number of epochs in boundle.

bool IG.Num.NeuralTrainingLimitsDto.EnableRangeTolerance

Flag for enabling toelrance that represent a percentage of the output range.

VectorDtoBase IG.Num.NeuralTrainingLimitsDto.ToleranceRms

Tolerance over RMS error of outputs over training points. Training will continue until error becomes below tolerance or until maximal number of epochs is reached. If less or equal than 0 then this tolerance is not taken into account.

$A Tako78 Jul12;; Igor Jul12;

VectorDtoBase IG.Num.NeuralTrainingLimitsDto.ToleranceRmsRelativeToRange

Relative tolerances on RMS errors of outputs over training points, relative to the correspoinding ranges of output data.

See also: NeuralApproximatorBase.ToleranceRmsRelativeToRange

double IG.Num.NeuralTrainingLimitsDto.ToleranceRmsRelativeToRangeScalar = NeuralTrainingParameters.DefaultToleranceRmsRelativeToRangeScalar

Scalar through which all components of the Relative tolerances on RMS errors of outputs can be set to the same value.

See also: NeuralApproximatorBase.ToleranceRmsRelativeToRangeScalar

VectorDtoBase IG.Num.NeuralTrainingLimitsDto.ToleranceMax

Tolerance on maximal error of outputs over training points. Training will continue until error becomes below tolerance or until maximal number of epochs is reached. If less or equal than 0 then this tolerance is not taken into account.

$A Tako78 Jul12;

VectorDtoBase IG.Num.NeuralTrainingLimitsDto.ToleranceMaxRelativeToRange

Relative tolerances on max. abs. errors of outputs over training points, relative to the correspoinding ranges of output data.

See also: NeuralApproximatorBase.ToleranceMaxRelativeToRange

double IG.Num.NeuralTrainingLimitsDto.ToleranceMaxRelativeToRangeScalar = NeuralTrainingParameters.DefaultToleranceMaxRelativeToRangeScalar

Scalar through which all components of the Relative tolerances on max. abs. errors of outputs can be set to the same value.

See also: NeuralApproximatorBase.ToleranceMaxRelativeToRangeScalar

int IG.Num.NeuralTrainingLimitsDto.InputLenght

Number of input neurons.

int IG.Num.NeuralTrainingLimitsDto.OutputLength

Number of output neurons.

bool IG.Num.NeuralTrainingLimitsDto.EnableArchitectureTest

Flag for enabling test in architecture of ANN.

int IG.Num.NeuralTrainingLimitsDto.NumHiddenLayersNum

Number of hidden layers in neural network.

int IG.Num.NeuralTrainingLimitsDto.NumHiddenNeuronsFirstMin

Minimum number of hidden neurons in first hidden layer.

int IG.Num.NeuralTrainingLimitsDto.NumHiddenNeuronsFirstMax

Maximum number of hidden neurons in first hidden layer.

int IG.Num.NeuralTrainingLimitsDto.NumHiddenNeuronsFirstNum

Number of numbers of hidden neurons in first hidden layer.

int [] IG.Num.NeuralTrainingLimitsDto.NumHiddenNeuronsFirstValues

Values for number of hidden neurons in the first hidden layer.

int IG.Num.NeuralTrainingLimitsDto.NumHiddenNeuronsSecondMin

Minimum number of hidden neurons in second hidden layer.

int IG.Num.NeuralTrainingLimitsDto.NumHiddenNeuronsSecondMax

Maximum number of hidden neurons in second hidden layer.

int IG.Num.NeuralTrainingLimitsDto.NumHiddenNeuronsSecondNum

Number of numbers of hidden neurons in second hidden layer.

int [] IG.Num.NeuralTrainingLimitsDto.NumHiddenNeuronsSecondValues

Values for number of hidden neurons in the second hidden layer.

int IG.Num.NeuralTrainingLimitsDto.NumHiddenNeuronsThirdMin

Minimum number of hidden neurons in third hidden layer.

int IG.Num.NeuralTrainingLimitsDto.NumHiddenNeuronsThirdMax

Maximum number of hidden neurons in third hidden layer.

int IG.Num.NeuralTrainingLimitsDto.NumHiddenNeuronsThirdNum

Number of numbers of hidden neurons in third hidden layer.

int [] IG.Num.NeuralTrainingLimitsDto.NumHiddenNeuronsThirdValues

Values for number of hidden neurons in the third hidden layer.

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

igbase/numeric/approximation/neural/SerializationDtoNeural.cs

Public Member Functions

Public Attributes

Protected Member Functions

Additional Inherited Members

Detailed Description

Member Function Documentation

Member Data Documentation