C# 클래스 Encog.Neural.Flat.Train.Prop.TrainFlatNetworkManhattan

Train the flat network using Manhattan update rule.

상속: TrainFlatNetworkProp

파일 보기 프로젝트 열기: encog/encog-silverlight-core 1 사용 예제들

공개 메소드들

메소드	설명
InitOthers ( ) : void	Not needed for this training type.
TrainFlatNetworkManhattan ( FlatNetwork network, IMLDataSet training, double theLearningRate ) : System	Construct a trainer for flat networks to use the Manhattan update rule.
UpdateWeight ( double gradients, double lastGradient, int index ) : double	Calculate the amount to change the weight by.

메소드 상세

InitOthers() 공개 메소드

Not needed for this training type.

public InitOthers ( ) : void
리턴	void

TrainFlatNetworkManhattan() 공개 메소드

Construct a trainer for flat networks to use the Manhattan update rule.

public TrainFlatNetworkManhattan ( FlatNetwork network, IMLDataSet training, double theLearningRate ) : System
network	FlatNetwork	The network to train.
training	IMLDataSet	The training data to use.
theLearningRate	double	The learning rate to use.
리턴	System

UpdateWeight() 공개 최종 메소드

Calculate the amount to change the weight by.

public final UpdateWeight ( double gradients, double lastGradient, int index ) : double
gradients	double	The gradients.
lastGradient	double	The last gradients.
index	int	The index to update.
리턴	double