• 홈
• FANNCSharp
• Float
• NeuralNet

C# 클래스 FANNCSharp.Float.NeuralNet

파일 보기 프로젝트 열기: joelself/FannCSharp 1 사용 예제들

Private Properties

프로퍼티	타입	설명
InternalCallback	int
NeuralNet	System

공개 메소드들

메소드	설명
CascadetrainOnData ( TrainingData data, uint maxNeurons, uint neuronsBetweenReports, float desiredError ) : void
CascadetrainOnFile ( string filename, uint maxNeurons, uint neuronsBetweenReports, float desiredError ) : void
ClearScalingParams ( ) : bool
DescaleInput ( float input ) : void
DescaleOutput ( float output ) : void
DescaleTrain ( TrainingData data ) : void
DisableSeedRand ( ) : void
Dispose ( ) : void
EnableSeedRand ( ) : void
GetActivationFunction ( int layer, int neuron ) : ActivationFunction
GetActivationSteepness ( int layer, int neuron ) : float
InitWeights ( TrainingData data ) : void
NeuralNet ( NetworkType netType, ICollection layers ) : System
NeuralNet ( NetworkType netType, uint numLayers ) : System
NeuralNet ( NeuralNet other ) : System
NeuralNet ( float connectionRate, ICollection layers ) : System
NeuralNet ( float connectionRate, uint numLayers ) : System
NeuralNet ( string filename ) : System
PrintConnections ( ) : void
PrintError ( ) : void
PrintParameters ( ) : void
RandomizeWeights ( float minWeight, float maxWeight ) : void
ResetErrno ( ) : void
ResetErrstr ( ) : void
ResetMSE ( ) : void
Run ( DataAccessor input ) : float[]
Run ( float input ) : float[]
Save ( string file ) : bool
SaveToFixed ( string file ) : int
ScaleInput ( DataAccessor input ) : void
ScaleOutput ( DataAccessor output ) : void
ScaleTrain ( TrainingData data ) : void
SetActivationFunction ( ActivationFunction function, int layer, int neuron ) : void
SetActivationFunctionLayer ( ActivationFunction function, int layer ) : void
SetActivationSteepness ( float steepness, int layer, int neuron ) : void
SetActivationSteepnessLayer ( float steepness, int layer ) : void
SetCallback ( TrainingCallback callback, Object userData ) : void
SetInputScalingParams ( TrainingData data, float newInputMin, float newInputMax ) : bool
SetOutputScalingParams ( TrainingData data, float newOutputMin, float newOutputMax ) : bool
SetScalingParams ( TrainingData data, float newInputMin, float newInputMax, float newOutputMin, float newOutputMax ) : bool
SetWeight ( uint fromNeuron, uint toNeuron, float weight ) : void
Test ( float input, float desiredOutput ) : float[]
TestData ( TrainingData data ) : float
TestDataParallel ( TrainingData data, uint threadNumb ) : float
TestDataParallel ( TrainingData data, uint threadNumb, List predictedOutputs ) : float
Train ( float input, float desiredOutput ) : void
TrainEpoch ( TrainingData data ) : float
TrainEpochBatchParallel ( TrainingData data, uint threadNumb ) : float
TrainEpochBatchParallel ( TrainingData data, uint threadNumb, List predictedOutputs ) : float
TrainEpochIncrementalMod ( TrainingData data ) : float
TrainEpochIncrementalMod ( TrainingData data, List predictedOutputs ) : float
TrainEpochIrpropmParallel ( TrainingData data, uint threadNumb ) : float
TrainEpochIrpropmParallel ( TrainingData data, uint threadNumb, List predictedOutputs ) : float
TrainEpochQuickpropParallel ( TrainingData data, uint threadNumb ) : float
TrainEpochQuickpropParallel ( TrainingData data, uint threadNumb, List predictedOutputs ) : float
TrainEpochSarpropParallel ( TrainingData data, uint threadNumb ) : float
TrainEpochSarpropParallel ( TrainingData data, uint threadNumb, List predictedOutputs ) : float
TrainOnData ( TrainingData data, uint maxEpochs, uint epochsBetweenReports, float desiredError ) : void
TrainOnFile ( string filename, uint maxEpochs, uint epochsBetweenReports, float desiredError ) : void

비공개 메소드들

메소드	설명
InternalCallback ( global netPtr, global dataPtr, uint max_epochs, uint epochs_between_reports, float desired_error, uint epochs, global user_data ) : int
NeuralNet ( neural_net other ) : System

메소드 상세