C# 클래스 Encog.Engine.Network.Flat.ActivationFunctions

The activation functions used by the flat networks.

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공개 프로퍼티들

프로퍼티	타입	설명
PARAM_NAMES	String[][]

공개 메소드들

메소드	설명
CalculateActivation ( int type, double x, double paras, int xOffset, int xLength, int paramOffset ) : void	Calculate an activation.
CalculateActivationBIPOLAR ( double x, double paras, int xOffset, int xLength, int paramOffset ) : void	Calculate the bipolar activation.
CalculateActivationCOMPETITIVE ( double x, double paras, int xOffset, int xLength, int paramOffset ) : void	Calculate the competitive activation.
CalculateActivationDerivative ( int type, double x, double paras, int paramOffset ) : double	Calculate the derivative of the activation. It is assumed that the value x, which is passed to this method, was the output from this activation. This prevents this method from having to recalculate the activation, just to recalculate the derivative.
CalculateActivationDerivativeBIPOLAR ( double x, double paras, int paramOffset ) : double	Calculate the derivative for bipolar activation. It is assumed that the value x, which is passed to this method, was the output from this activation. This prevents this method from having to recalculate the activation, just to recalculate the derivative.
CalculateActivationDerivativeCOMPETITIVE ( double x, double paras, int paramOffset ) : double	Calculate the derivative for competitive activation. It is assumed that the value x, which is passed to this method, was the output from this activation. This prevents this method from having to recalculate the activation, just to recalculate the derivative.
CalculateActivationDerivativeGAUSSIAN ( double x, double paras, int paramOffset ) : double	Calculate the derivative for gaussian activation. It is assumed that the value x, which is passed to this method, was the output from this activation. This prevents this method from having to recalculate the activation, just to recalculate the derivative.
CalculateActivationDerivativeLINEAR ( double x, double paras, int paramOffset ) : double	Calculate the derivative for linear activation. It is assumed that the value x, which is passed to this method, was the output from this activation. This prevents this method from having to recalculate the activation, just to recalculate the derivative.
CalculateActivationDerivativeLOG ( double x, double paras, int paramOffset ) : double	Calculate the derivative for log activation. It is assumed that the value x, which is passed to this method, was the output from this activation. This prevents this method from having to recalculate the activation, just to recalculate the derivative.
CalculateActivationDerivativeRAMP ( double x, double paras, int paramOffset ) : double	Calculate the derivative for ramp activation. It is assumed that the value x, which is passed to this method, was the output from this activation. This prevents this method from having to recalculate the activation, just to recalculate the derivative.
CalculateActivationDerivativeSIGMOID ( double x, double paras, int paramOffset ) : double	Calculate the derivative for sigmoid activation. It is assumed that the value x, which is passed to this method, was the output from this activation. This prevents this method from having to recalculate the activation, just to recalculate the derivative.
CalculateActivationDerivativeSIN ( double x, double paras, int paramOffset ) : double	Calculate the derivative for sin activation. It is assumed that the value x, which is passed to this method, was the output from this activation. This prevents this method from having to recalculate the activation, just to recalculate the derivative.
CalculateActivationDerivativeSOFTMAX ( double x, double paras, int paramOffset ) : double	Calculate the derivative for softmax activation. It is assumed that the value x, which is passed to this method, was the output from this activation. This prevents this method from having to recalculate the activation, just to recalculate the derivative.
CalculateActivationDerivativeSTEP ( double x, double paras, int paramOffset ) : double	Calculate the derivative for step activation. It is assumed that the value x, which is passed to this method, was the output from this activation. This prevents this method from having to recalculate the activation, just to recalculate the derivative.
CalculateActivationDerivativeTANH ( double x, double paras, int paramOffset ) : double	Calculate the derivative for tanh activation. It is assumed that the value x, which is passed to this method, was the output from this activation. This prevents this method from having to recalculate the activation, just to recalculate the derivative.
CalculateActivationGAUSSIAN ( double x, double paras, int xOffset, int xLength, int paramOffset ) : void	Calculate the gaussian activation.
CalculateActivationLINEAR ( double x, double paras, int xOffset, int xLength, int paramOffset ) : void	Calculate the linear activation.
CalculateActivationLOG ( double x, double paras, int xOffset, int xLength, int paramOffset ) : void	Calculate the log activation.
CalculateActivationRAMP ( double x, double paras, int xOffset, int xLength, int paramOffset ) : void	Calculate the ramp activation.
CalculateActivationSIGMOID ( double x, double paras, int xOffset, int xLength, int paramOffset ) : void	Calculate the sigmoid activation.
CalculateActivationSIN ( double x, double paras, int xOffset, int xLength, int paramOffset ) : void	Calculate the sin activation.
CalculateActivationSOFTMAX ( double x, double paras, int xOffset, int xLength, int paramOffset ) : void	Calculate the softmax activation.
CalculateActivationSTEP ( double x, double paras, int xOffset, int xLength, int paramOffset ) : void	Calculate the step activation.
CalculateActivationTANH ( double x, double paras, int xOffset, int xLength, int paramOffset ) : void	Calculate the tanh activation.
CopyParams ( double source, double target, int index ) : int	Copy parameters. Accounts for variable sized parameters.
GetParams ( int index ) : String[]	Get the parameter names for an activation function.

비공개 메소드들

메소드	설명
ActivationFunctions ( ) : Encog.Engine	Private constructor.

메소드 상세

CalculateActivation() 공개 정적인 메소드

Calculate an activation.

public static CalculateActivation ( int type, double x, double paras, int xOffset, int xLength, int paramOffset ) : void
type	int	The type of activation.
x	double	The input and output array. Input values are provided and thearray is modified to reflect the output.
paras	double
xOffset	int	The offset into X for where we are calculating.
xLength	int	The length of the array we are calculating.
paramOffset	int	The parameter offset.
리턴	void

CalculateActivationBIPOLAR() 공개 정적인 메소드

Calculate the bipolar activation.

public static CalculateActivationBIPOLAR ( double x, double paras, int xOffset, int xLength, int paramOffset ) : void
x	double	The input and output array. Input values are provided and thearray is modified to reflect the output.
paras	double
xOffset	int	The offset into X for where we are calculating.
xLength	int	The length of the array we are calculating.
paramOffset	int	The parameter offset.
리턴	void

CalculateActivationCOMPETITIVE() 공개 정적인 메소드

Calculate the competitive activation.

public static CalculateActivationCOMPETITIVE ( double x, double paras, int xOffset, int xLength, int paramOffset ) : void
x	double	The input and output array. Input values are provided and thearray is modified to reflect the output.
paras	double
xOffset	int	The offset into X for where we are calculating.
xLength	int	The length of the array we are calculating.
paramOffset	int	The parameter offset.
리턴	void

CalculateActivationDerivative() 공개 정적인 메소드

Calculate the derivative of the activation. It is assumed that the value x, which is passed to this method, was the output from this activation. This prevents this method from having to recalculate the activation, just to recalculate the derivative.

public static CalculateActivationDerivative ( int type, double x, double paras, int paramOffset ) : double
type	int	The type of activation.
x	double	The activation to calculate for.
paras	double
paramOffset	int	The offset the parameters begin at.
리턴	double

CalculateActivationDerivativeBIPOLAR() 공개 정적인 메소드

Calculate the derivative for bipolar activation. It is assumed that the value x, which is passed to this method, was the output from this activation. This prevents this method from having to recalculate the activation, just to recalculate the derivative.

public static CalculateActivationDerivativeBIPOLAR ( double x, double paras, int paramOffset ) : double
x	double	The activation to calculate for.
paras	double
paramOffset	int	The offset the parameters begin at.
리턴	double

CalculateActivationDerivativeCOMPETITIVE() 공개 정적인 메소드

Calculate the derivative for competitive activation. It is assumed that the value x, which is passed to this method, was the output from this activation. This prevents this method from having to recalculate the activation, just to recalculate the derivative.

public static CalculateActivationDerivativeCOMPETITIVE ( double x, double paras, int paramOffset ) : double
x	double	The activation to calculate for.
paras	double
paramOffset	int	The offset the parameters begin at.
리턴	double

CalculateActivationDerivativeGAUSSIAN() 공개 정적인 메소드

Calculate the derivative for gaussian activation. It is assumed that the value x, which is passed to this method, was the output from this activation. This prevents this method from having to recalculate the activation, just to recalculate the derivative.

public static CalculateActivationDerivativeGAUSSIAN ( double x, double paras, int paramOffset ) : double
x	double	The activation to calculate for.
paras	double
paramOffset	int	The offset the parameters begin at.
리턴	double

CalculateActivationDerivativeLINEAR() 공개 정적인 메소드

Calculate the derivative for linear activation. It is assumed that the value x, which is passed to this method, was the output from this activation. This prevents this method from having to recalculate the activation, just to recalculate the derivative.

public static CalculateActivationDerivativeLINEAR ( double x, double paras, int paramOffset ) : double
x	double	The activation to calculate for.
paras	double
paramOffset	int	The offset the parameters begin at.
리턴	double

CalculateActivationDerivativeLOG() 공개 정적인 메소드

Calculate the derivative for log activation. It is assumed that the value x, which is passed to this method, was the output from this activation. This prevents this method from having to recalculate the activation, just to recalculate the derivative.

public static CalculateActivationDerivativeLOG ( double x, double paras, int paramOffset ) : double
x	double	The activation to calculate for.
paras	double
paramOffset	int	The offset the parameters begin at.
리턴	double

CalculateActivationDerivativeRAMP() 공개 정적인 메소드

Calculate the derivative for ramp activation. It is assumed that the value x, which is passed to this method, was the output from this activation. This prevents this method from having to recalculate the activation, just to recalculate the derivative.

public static CalculateActivationDerivativeRAMP ( double x, double paras, int paramOffset ) : double
x	double	The activation to calculate for.
paras	double
paramOffset	int	The offset the parameters begin at.
리턴	double

CalculateActivationDerivativeSIGMOID() 공개 정적인 메소드

Calculate the derivative for sigmoid activation. It is assumed that the value x, which is passed to this method, was the output from this activation. This prevents this method from having to recalculate the activation, just to recalculate the derivative.

public static CalculateActivationDerivativeSIGMOID ( double x, double paras, int paramOffset ) : double
x	double	The activation to calculate for.
paras	double
paramOffset	int	The offset the parameters begin at.
리턴	double

CalculateActivationDerivativeSIN() 공개 정적인 메소드

Calculate the derivative for sin activation. It is assumed that the value x, which is passed to this method, was the output from this activation. This prevents this method from having to recalculate the activation, just to recalculate the derivative.

public static CalculateActivationDerivativeSIN ( double x, double paras, int paramOffset ) : double
x	double	The activation to calculate for.
paras	double
paramOffset	int	The offset the parameters begin at.
리턴	double

CalculateActivationDerivativeSOFTMAX() 공개 정적인 메소드

Calculate the derivative for softmax activation. It is assumed that the value x, which is passed to this method, was the output from this activation. This prevents this method from having to recalculate the activation, just to recalculate the derivative.

public static CalculateActivationDerivativeSOFTMAX ( double x, double paras, int paramOffset ) : double
x	double	The activation to calculate for.
paras	double
paramOffset	int	The offset the parameters begin at.
리턴	double

CalculateActivationDerivativeSTEP() 공개 정적인 메소드

Calculate the derivative for step activation. It is assumed that the value x, which is passed to this method, was the output from this activation. This prevents this method from having to recalculate the activation, just to recalculate the derivative.

public static CalculateActivationDerivativeSTEP ( double x, double paras, int paramOffset ) : double
x	double	The activation to calculate for.
paras	double
paramOffset	int	The offset the parameters begin at.
리턴	double

CalculateActivationDerivativeTANH() 공개 정적인 메소드

Calculate the derivative for tanh activation. It is assumed that the value x, which is passed to this method, was the output from this activation. This prevents this method from having to recalculate the activation, just to recalculate the derivative.

public static CalculateActivationDerivativeTANH ( double x, double paras, int paramOffset ) : double
x	double	The activation to calculate for.
paras	double
paramOffset	int	The offset the parameters begin at.
리턴	double

CalculateActivationGAUSSIAN() 공개 정적인 메소드

Calculate the gaussian activation.

public static CalculateActivationGAUSSIAN ( double x, double paras, int xOffset, int xLength, int paramOffset ) : void
x	double	The input and output array. Input values are provided and thearray is modified to reflect the output.
paras	double
xOffset	int	The offset into X for where we are calculating.
xLength	int	The length of the array we are calculating.
paramOffset	int	The parameter offset.
리턴	void

CalculateActivationLINEAR() 공개 정적인 메소드

Calculate the linear activation.

public static CalculateActivationLINEAR ( double x, double paras, int xOffset, int xLength, int paramOffset ) : void
x	double	The input and output array. Input values are provided and thearray is modified to reflect the output.
paras	double
xOffset	int	The offset into X for where we are calculating.
xLength	int	The length of the array we are calculating.
paramOffset	int	The parameter offset.
리턴	void

CalculateActivationLOG() 공개 정적인 메소드

Calculate the log activation.

public static CalculateActivationLOG ( double x, double paras, int xOffset, int xLength, int paramOffset ) : void
x	double	The input and output array. Input values are provided and thearray is modified to reflect the output.
paras	double
xOffset	int	The offset into X for where we are calculating.
xLength	int	The length of the array we are calculating.
paramOffset	int	The parameter offset.
리턴	void

CalculateActivationRAMP() 공개 정적인 메소드

Calculate the ramp activation.

public static CalculateActivationRAMP ( double x, double paras, int xOffset, int xLength, int paramOffset ) : void
x	double	The input and output array. Input values are provided and thearray is modified to reflect the output.
paras	double
xOffset	int	The offset into X for where we are calculating.
xLength	int	The length of the array we are calculating.
paramOffset	int	The parameter offset.
리턴	void

CalculateActivationSIGMOID() 공개 정적인 메소드

Calculate the sigmoid activation.

public static CalculateActivationSIGMOID ( double x, double paras, int xOffset, int xLength, int paramOffset ) : void
x	double	The input and output array. Input values are provided and thearray is modified to reflect the output.
paras	double
xOffset	int	The offset into X for where we are calculating.
xLength	int	The length of the array we are calculating.
paramOffset	int	The parameter offset.
리턴	void

CalculateActivationSIN() 공개 정적인 메소드

Calculate the sin activation.

public static CalculateActivationSIN ( double x, double paras, int xOffset, int xLength, int paramOffset ) : void
x	double	The input and output array. Input values are provided and thearray is modified to reflect the output.
paras	double
xOffset	int	The offset into X for where we are calculating.
xLength	int	The length of the array we are calculating.
paramOffset	int	The parameter offset.
리턴	void

CalculateActivationSOFTMAX() 공개 정적인 메소드

Calculate the softmax activation.

public static CalculateActivationSOFTMAX ( double x, double paras, int xOffset, int xLength, int paramOffset ) : void
x	double	The input and output array. Input values are provided and thearray is modified to reflect the output.
paras	double
xOffset	int	The offset into X for where we are calculating.
xLength	int	The length of the array we are calculating.
paramOffset	int	The parameter offset.
리턴	void

CalculateActivationSTEP() 공개 정적인 메소드

Calculate the step activation.

public static CalculateActivationSTEP ( double x, double paras, int xOffset, int xLength, int paramOffset ) : void
x	double	The input and output array. Input values are provided and thearray is modified to reflect the output.
paras	double
xOffset	int	The offset into X for where we are calculating.
xLength	int	The length of the array we are calculating.
paramOffset	int	The parameter offset.
리턴	void

CalculateActivationTANH() 공개 정적인 메소드

Calculate the tanh activation.

public static CalculateActivationTANH ( double x, double paras, int xOffset, int xLength, int paramOffset ) : void
x	double	The input and output array. Input values are provided and thearray is modified to reflect the output.
paras	double
xOffset	int	The offset into X for where we are calculating.
xLength	int	The length of the array we are calculating.
paramOffset	int	The parameter offset.
리턴	void

CopyParams() 공개 정적인 메소드

Copy parameters. Accounts for variable sized parameters.

public static CopyParams ( double source, double target, int index ) : int
source	double	The source.
target	double	The target.
index	int	The index.
리턴	int

GetParams() 공개 정적인 메소드

Get the parameter names for an activation function.

public static GetParams ( int index ) : String[]
index	int	The activation function.
리턴	String[]

프로퍼티 상세

PARAM_NAMES 공개적으로 정적으로 프로퍼티

The names of all of the params.

public static String[][] PARAM_NAMES
리턴	String[][]