Contains Parameters that define neural network architecture and trainig limits, together with achieved results after training such as various error norms. More...

Inheritance diagram for IG.Num.NeuralTrainingTable:

Collaboration diagram for IG.Num.NeuralTrainingTable:

Public Member Functions
void	UpdateTrainingTableDimensionns ()
	Updates the list of dimensions of the table of training results (contained in the list TrainingParameters). More...

int	GetIndex (int[] indices)
	Returns the index of the element in the onedimensional list that corresponds to the specified indices of the multidimensional table of elements. More...

void	GetIndices (int oneDimensionalIndex, ref int[] tableIndices)
	Calculates and stores the multidimensional indices of an element of the multidimensional table of training parameters amd results. More...

Static Public Member Functions
static void	SaveJson (NeuralTrainingTable trainingResults, string filePath)
	Saves (serializes) the specified training results object to the specified JSON file. File is owerwritten if it exists. More...

static void	SaveJson (NeuralTrainingTable trainingResults, string filePath, bool append)
	Saves (serializes) the specified training results object to the specified JSON file. More...

static void	LoadJson (string filePath, ref NeuralTrainingTable trainingResultsRestored)
	Restores (deserializes) a training results object from the specified file in JSON format. More...

Public Attributes
NeuralTrainingLimits	_trainingLimits = null

List< NeuralTrainingParameters >	_trainingParameters = null

Properties
object	Lock `[get]`
	This object's central lock object to be used by other object. Do not use this object for locking in class' methods, for this you should use InternalLock. More...

NeuralTrainingLimits	TrainingLimits `[get, set]`
	Contains Parameters that define neural network architecture limits and trainig parameter limits. More...

List< NeuralTrainingParameters >	TrainingParameters `[get, set]`
	Contains Parameters that define neural network architecture and trainig procedure, together with achieved results after training such as various error norms. More...

List< int >	TrainingTableDimensions `[get, private set]`
	List of dimensions of the table of training results. More...

NeuralTrainingParameters this[params int[]	indices `[get]`
	Gets the element of the training table specified by the indices. More...

Properties inherited from IG.Lib.ILockable
object	Lock `[get]`

Private Attributes
object	_mainLock = new object()

List< int >	_trainingTableDimensions

Detailed Description

Contains Parameters that define neural network architecture and trainig limits, together with achieved results after training such as various error norms.

Not thread safe!

This class is used for storing parameters and limits of neural networks and restoring them at a later time, in order to repeat training under similar condition or simply to analyse performance of neural networks.

$A Igor Jul10 Aug12; Tako78 Aug12;

Member Function Documentation

void IG.Num.NeuralTrainingTable.UpdateTrainingTableDimensionns ( )

inline

Updates the list of dimensions of the table of training results (contained in the list TrainingParameters).

References IG.Num.NeuralTrainingLimits.IterateThroughMultidimensionalTable().

int IG.Num.NeuralTrainingTable.GetIndex ( int[] indices )

inline

Returns the index of the element in the onedimensional list that corresponds to the specified indices of the multidimensional table of elements.

Parameters

indices Indices of the element in the multidimensional table of training results.

Returns: One dimensional index that corresponds to the specified multidimensional indices of the element of the multidimensional table of training results.

References IG.Lib.Util.GetIndex().

void IG.Num.NeuralTrainingTable.GetIndices	(	int	oneDimensionalIndex,
		ref int[]	tableIndices
	)

inline

Calculates and stores the multidimensional indices of an element of the multidimensional table of training parameters amd results.

Parameters

oneDimensionalIndex	One dimensional index that defines the position of the element in the list of elements.
tableIndices	Variable where multidimensional indices of the element are stored.

References IG.Lib.Util.GetIndices().

static void IG.Num.NeuralTrainingTable.SaveJson	(	NeuralTrainingTable	trainingResults,
		string	filePath
	)

inlinestatic

Saves (serializes) the specified training results object to the specified JSON file. File is owerwritten if it exists.

Parameters

trainingResults	Object that is saved to a file.
filePath	Path to the file into which object is is saved.

static void IG.Num.NeuralTrainingTable.SaveJson	(	NeuralTrainingTable	trainingResults,
		string	filePath,
		bool	append
	)

inlinestatic

Saves (serializes) the specified training results object to the specified JSON file.

Parameters

trainingResults	Object that is saved to a file.
filePath	Path to the file into which object is is saved.
append	Specifies whether serialized data is appended at the end of the file in the case that the file already exists.

static void IG.Num.NeuralTrainingTable.LoadJson	(	string	filePath,
		ref NeuralTrainingTable	trainingResultsRestored
	)

inlinestatic

Restores (deserializes) a training results object from the specified file in JSON format.

Parameters

filePath	File from which object data is restored.
trainingResultsRestored	Object that is restored by deserialization.

Member Data Documentation

object IG.Num.NeuralTrainingTable._mainLock = new object()

private

NeuralTrainingLimits IG.Num.NeuralTrainingTable._trainingLimits = null

List<NeuralTrainingParameters> IG.Num.NeuralTrainingTable._trainingParameters = null

List<int> IG.Num.NeuralTrainingTable._trainingTableDimensions

private

Property Documentation

object IG.Num.NeuralTrainingTable.Lock

get

This object's central lock object to be used by other object. Do not use this object for locking in class' methods, for this you should use InternalLock.

NeuralTrainingLimits IG.Num.NeuralTrainingTable.TrainingLimits

getset

Contains Parameters that define neural network architecture limits and trainig parameter limits.

Referenced by IG.Num.NeuralTrainingTableDto.CopyFromPlain().

List<NeuralTrainingParameters> IG.Num.NeuralTrainingTable.TrainingParameters

getset

Contains Parameters that define neural network architecture and trainig procedure, together with achieved results after training such as various error norms.

Referenced by IG.Num.NeuralTrainingTableDto.CopyFromPlain(), and IG.Num.TestTrainingParametersComparers.Test().

List<int> IG.Num.NeuralTrainingTable.TrainingTableDimensions

getprivate set

List of dimensions of the table of training results.

NeuralTrainingParameters this[params int[] IG.Num.NeuralTrainingTable.indices

get

Gets the element of the training table specified by the indices.

Parameters

indices Indices of the element in the table of training parameters.

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

igbase/numeric/approximation/neural/NeuralTrainingParameters.cs

Public Member Functions

Static Public Member Functions

Public Attributes

Properties

Private Attributes

Detailed Description

Member Function Documentation

Member Data Documentation

Property Documentation