IGLib  1.7.2
The IGLib base library EXTENDED - with other lilbraries and applications.
 All Classes Namespaces Files Functions Variables Typedefs Enumerations Enumerator Properties Events Macros
IG.Neural.NeuralNetworks Class Reference

Static Public Member Functions

static INeuralApproximator TrainNetwork (SampledDataSet trainingData, SampledDataSet verificationData)
 Training neural network in Aforge of NeuronDotNet More...
 
static INeuralApproximator Example3D (int inputLength, int outputLength, ref SampledDataSet trainingData, int nnType)
 
static void Approximate (INeuralApproximator Approximator, SampledDataSet verificationData, ref SampledDataSet approximationData)
 Approximate data More...
 
static SampledDataSet GenerateSguareSet (int numTrainingSet)
 
static SampledDataSet CopyFromCordinates3D (IVector[][] functionCoordinates)
 Copy data from NeuralTrainingSet to vector table More...
 
static IVector[][] CopyToCoordinates3D (int xNumSteps, int yNumSteps, SampledDataSet trainingData)
 

Properties

int MaxEpoch [get, set]
 
int EpochBundle [get, set]
 
double RMS [get, set]
 
double LearningRate [get, set]
 
double Momentum [get, set]
 
int HiddenNeuron1L [get, set]
 
int HiddenNeuron2L [get, set]
 
double InputSafetyFactor [get, set]
 
double OutputSafetyFactor [get, set]
 
bool BreakTraining [get, set]
 

Static Private Member Functions

static void CalculateError (IBoundingBox bounds, IVector[] exactOutputValues, IVector[] approximatedOutputValues, ref double maxError, ref double averageError)
 

Static Private Attributes

static int _maxEpoch
 
static int _epochBundle
 
static double _rms
 
static double _learningRate
 
static double _momentum
 
static int _hiddenNeuron1L
 
static int _hiddenNeuron2L
 
static double _inputSafetyFactor
 
static double _outputSafetyFactor
 
static bool _breakTraining = false
 

Member Function Documentation

static INeuralApproximator IG.Neural.NeuralNetworks.TrainNetwork ( SampledDataSet  trainingData,
SampledDataSet  verificationData 
)
inlinestatic

Training neural network in Aforge of NeuronDotNet

Parameters
inputLengthNumber of input parameters.
outputLengthNumber of output parameters.
trainingData
nnType1-NeuronDotNet; 2-Aforge
Returns

References IG.Num.NeuralApproximatorBase.EpochsInBundle, IG.Num.NeuralApproximatorBase.InputBoundsSafetyFactor, IG.Num.SampledDataSet.InputLength, IG.Num.NeuralApproximatorBase.InputLength, IG.Num.NeuralApproximatorBase.InputNeuronsRange, IG.Num.NeuralApproximatorBase.LearningRate, IG.Num.SampledDataSet.Length, IG.Num.VectorApproximatorBase.Lock, IG.Num.NeuralApproximatorBase.MaxEpochs, IG.Num.NeuralApproximatorBase.Momentum, IG.Num.NeuralApproximatorBase.MultipleNetworks, IG.Num.NeuralApproximatorBase.OutputBoundsSafetyFactor, IG.Num.SampledDataSet.OutputLength, IG.Num.NeuralApproximatorBase.OutputLength, IG.Num.NeuralApproximatorBase.OutputLevel, IG.Num.NeuralApproximatorBase.OutputNeuronsRange, IG.Num.IBoundingBox.Reset(), IG.Num.NeuralApproximatorBase.SaveConvergenceRms, IG.Num.NeuralApproximatorBase.SetHiddenLayers(), IG.Num.NeuralApproximatorBase.SetTrainingAndVerificationData(), IG.Num.NeuralApproximatorBase.SigmoidAlphaValue, IG.Lib.StopWatch1.Start(), IG.Lib.StopWatch1.Stop(), IG.Lib.StopWatch1.Time, IG.Num.NeuralApproximatorBase.ToleranceRms, IG.Num.NeuralApproximatorBase.ToString(), IG.Num.NeuralApproximatorBase.TrainingData, IG.Num.NeuralApproximatorBase.TrainNetwork(), and IG.Num.IBoundingBox.UpdateAll().

Referenced by IG.Neural.Applications.DemoNeuralOld.backgroundWorker1D_DoWork(), IG.Neural.Forms.NeuralDemo1D.backgroundWorker1D_DoWork(), IG.Neural.Forms.NeuralControl2D.backgroundWorker2D_DoWork(), IG.Neural.Applications.DemoNeuralOld.backgroundWorker2D_DoWork(), and IG.Neural.Forms.Old.FormNeural1DOld.btStart_Click().

static INeuralApproximator IG.Neural.NeuralNetworks.Example3D ( int  inputLength,
int  outputLength,
ref SampledDataSet  trainingData,
int  nnType 
)
inlinestatic
static void IG.Neural.NeuralNetworks.Approximate ( INeuralApproximator  Approximator,
SampledDataSet  verificationData,
ref SampledDataSet  approximationData 
)
inlinestatic
static void IG.Neural.NeuralNetworks.CalculateError ( IBoundingBox  bounds,
IVector[]  exactOutputValues,
IVector[]  approximatedOutputValues,
ref double  maxError,
ref double  averageError 
)
inlinestaticprivate
static SampledDataSet IG.Neural.NeuralNetworks.GenerateSguareSet ( int  numTrainingSet)
inlinestatic
static SampledDataSet IG.Neural.NeuralNetworks.CopyFromCordinates3D ( IVector  functionCoordinates[][])
inlinestatic

Copy data from NeuralTrainingSet to vector table

Parameters
functionCoordinates
Returns

References IG.Num.SampledDataSet.AddElement().

static IVector [][] IG.Neural.NeuralNetworks.CopyToCoordinates3D ( int  xNumSteps,
int  yNumSteps,
SampledDataSet  trainingData 
)
inlinestatic

Member Data Documentation

int IG.Neural.NeuralNetworks._maxEpoch
staticprivate
int IG.Neural.NeuralNetworks._epochBundle
staticprivate
double IG.Neural.NeuralNetworks._rms
staticprivate
double IG.Neural.NeuralNetworks._learningRate
staticprivate
double IG.Neural.NeuralNetworks._momentum
staticprivate
int IG.Neural.NeuralNetworks._hiddenNeuron1L
staticprivate
int IG.Neural.NeuralNetworks._hiddenNeuron2L
staticprivate
double IG.Neural.NeuralNetworks._inputSafetyFactor
staticprivate
double IG.Neural.NeuralNetworks._outputSafetyFactor
staticprivate
bool IG.Neural.NeuralNetworks._breakTraining = false
staticprivate

Property Documentation


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