C# 클래스 Encog.Engine.Network.Train.Prop.TrainFlatNetworkResilient

Train a flat network using RPROP.
상속: TrainFlatNetworkProp
파일 보기 프로젝트 열기: encog/encog-silverlight-core 1 사용 예제들

공개 메소드들

메소드 설명
TrainFlatNetworkResilient ( FlatNetwork flat, IEngineDataSet trainingSet ) : Encog.Engine.Data

Tran a network using RPROP.
TrainFlatNetworkResilient ( FlatNetwork network, IEngineDataSet training, double zeroTolerance, double initialUpdate, double maxStep ) : Encog.Engine.Data

Construct a resilient trainer for flat networks.
UpdateWeight ( double gradients, double lastGradient, int index ) : double

Calculate the amount to change the weight by.

비공개 메소드들

메소드 설명
Sign ( double value ) : int

Determine the sign of the value.

메소드 상세

TrainFlatNetworkResilient() 공개 메소드

Tran a network using RPROP.
public TrainFlatNetworkResilient ( FlatNetwork flat, IEngineDataSet trainingSet ) : Encog.Engine.Data
flat Encog.Engine.Network.Flat.FlatNetwork The network to train.
trainingSet IEngineDataSet The training data to use.
리턴 Encog.Engine.Data

TrainFlatNetworkResilient() 공개 메소드

Construct a resilient trainer for flat networks.
public TrainFlatNetworkResilient ( FlatNetwork network, IEngineDataSet training, double zeroTolerance, double initialUpdate, double maxStep ) : Encog.Engine.Data
network Encog.Engine.Network.Flat.FlatNetwork The network to train.
training IEngineDataSet The training data to use.
zeroTolerance double How close a number should be to zero to be counted as zero.
initialUpdate double The initial update value.
maxStep double The maximum step value.
리턴 Encog.Engine.Data

UpdateWeight() 공개 메소드

Calculate the amount to change the weight by.
public 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