C# 클래스 Encog.Neural.Flat.FlatNetwork

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

공개 메소드들

메소드	설명
CalculateError ( IMLDataSet data ) : double	Calculate the error for this neural network. The error is calculated using root-mean-square(RMS).
ClearConnectionLimit ( ) : void	Clear any connection limits.
ClearContext ( ) : void	Clear any context neurons.
Clone ( ) : Object	Clone the network.
CloneFlatNetwork ( FlatNetwork result ) : void	Clone into the flat network passed in.
Compute ( double input, double output ) : void	Calculate the output for the given input.
DecodeNetwork ( double data ) : void	Decode the specified data into the weights of the neural network. This method performs the opposite of encodeNetwork.
EncodeNetwork ( ) : double[]	Encode the neural network to an array of doubles. This includes the network weights. To read this into a neural network, use the decodeNetwork method.
FlatNetwork ( ) : System	Default constructor.
FlatNetwork ( FlatLayer layers ) : System	Create a flat network from an array of layers.
FlatNetwork ( int input, int hidden1, int hidden2, int output, bool tanh ) : System	Construct a flat neural network.
HasSameActivationFunction ( ) : Type	Neural networks with only one type of activation function offer certain optimization options. This method determines if only a single activation function is used.
Init ( FlatLayer layers ) : void	Construct a flat network.
Randomize ( ) : void	Perform a simple randomization of the weights of the neural network between -1 and 1.
Randomize ( double hi, double lo ) : void	Perform a simple randomization of the weights of the neural network between the specified hi and lo.

보호된 메소드들

메소드	설명
ComputeLayer ( int currentLayer ) : void	Calculate a layer.

메소드 상세

CalculateError() 공개 메소드

Calculate the error for this neural network. The error is calculated using root-mean-square(RMS).

public CalculateError ( IMLDataSet data ) : double
data	IMLDataSet	The training set.
리턴	double

ClearConnectionLimit() 공개 메소드

Clear any connection limits.

public ClearConnectionLimit ( ) : void
리턴	void

ClearContext() 공개 메소드

Clear any context neurons.

public ClearContext ( ) : void
리턴	void

Clone() 공개 메소드

Clone the network.

public Clone ( ) : Object
리턴	Object

CloneFlatNetwork() 공개 메소드

Clone into the flat network passed in.

public CloneFlatNetwork ( FlatNetwork result ) : void
result	FlatNetwork	The network to copy into.
리턴	void

Compute() 공개 메소드

Calculate the output for the given input.

public Compute ( double input, double output ) : void
input	double	The input.
output	double	Output will be placed here.
리턴	void

ComputeLayer() 보호된 메소드

Calculate a layer.

protected ComputeLayer ( int currentLayer ) : void
currentLayer	int	The layer to calculate.
리턴	void

DecodeNetwork() 공개 메소드

Decode the specified data into the weights of the neural network. This method performs the opposite of encodeNetwork.

public DecodeNetwork ( double data ) : void
data	double	The data to be decoded.
리턴	void

EncodeNetwork() 공개 메소드

Encode the neural network to an array of doubles. This includes the network weights. To read this into a neural network, use the decodeNetwork method.

public EncodeNetwork ( ) : double[]
리턴	double[]

FlatNetwork() 공개 메소드

Default constructor.

public FlatNetwork ( ) : System
리턴	System

FlatNetwork() 공개 메소드

Create a flat network from an array of layers.

public FlatNetwork ( FlatLayer layers ) : System
layers	FlatLayer	The layers.
리턴	System

FlatNetwork() 공개 메소드

Construct a flat neural network.

public FlatNetwork ( int input, int hidden1, int hidden2, int output, bool tanh ) : System
input	int	Neurons in the input layer.
hidden1	int
hidden2	int
output	int	Neurons in the output layer.
tanh	bool	True if this is a tanh activation, false for sigmoid.
리턴	System

HasSameActivationFunction() 공개 메소드

Neural networks with only one type of activation function offer certain optimization options. This method determines if only a single activation function is used.

public HasSameActivationFunction ( ) : Type
리턴	System.Type

Init() 공개 메소드

Construct a flat network.

public Init ( FlatLayer layers ) : void
layers	FlatLayer	The layers of the network to create.
리턴	void

Randomize() 공개 메소드

Perform a simple randomization of the weights of the neural network between -1 and 1.

public Randomize ( ) : void
리턴	void

Randomize() 공개 메소드

Perform a simple randomization of the weights of the neural network between the specified hi and lo.

public Randomize ( double hi, double lo ) : void
hi	double	The network high.
lo	double	The network low.
리턴	void