C# 클래스 Encog.Neural.Rbf.Training.SVDTraining

상속: BasicTraining

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

공개 메소드들

메소드	설명
FlatToMatrix ( double flat, int start, double matrix ) : void	Convert a flat network to a matrix.
Iteration ( ) : void	Perform one iteration.
MatrixToFlat ( double matrix, double flat, int start ) : void	Convert the matrix to flat.
Pause ( ) : TrainingContinuation
Resume ( TrainingContinuation state ) : void
SVDTraining ( RBFNetwork network_0, IMLDataSet training ) : Encog.MathUtil.RBF	Construct the training object.

메소드 상세

FlatToMatrix() 공개 메소드

Convert a flat network to a matrix.

public FlatToMatrix ( double flat, int start, double matrix ) : void
flat	double	The flat network to convert.
start	int	The starting point.
matrix	double	The matrix to convert to.
리턴	void

Iteration() 공개 최종 메소드

Perform one iteration.

public final Iteration ( ) : void
리턴	void

MatrixToFlat() 공개 메소드

Convert the matrix to flat.

public MatrixToFlat ( double matrix, double flat, int start ) : void
matrix	double	The matrix.
flat	double	Flat array.
start	int	WHere to start.
리턴	void

Pause() 공개 메소드

public Pause ( ) : TrainingContinuation
리턴	Encog.Neural.Networks.Training.Propagation.TrainingContinuation

Resume() 공개 메소드

public Resume ( TrainingContinuation state ) : void
state	Encog.Neural.Networks.Training.Propagation.TrainingContinuation
리턴	void

SVDTraining() 공개 메소드

Construct the training object.

public SVDTraining ( RBFNetwork network_0, IMLDataSet training ) : Encog.MathUtil.RBF
network_0	Encog.Neural.RBF.RBFNetwork	The network to train. Must have a single output neuron.
training	IMLDataSet	The training data to use. Must be indexable.
리턴	Encog.MathUtil.RBF