C# Класс Encog.Neural.Flat.FlatNetwork

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Открытые методы

Метод	Описание
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.

Защищенные методы

Метод	Описание
ComputeLayer ( int currentLayer ) : void	Calculate a layer.

Описание методов

CalculateError() публичный Метод

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.
Результат	double

ClearConnectionLimit() публичный Метод

Clear any connection limits.

public ClearConnectionLimit ( ) : void
Результат	void

ClearContext() публичный Метод

Clear any context neurons.

public ClearContext ( ) : void
Результат	void

Clone() публичный Метод

Clone the network.

public Clone ( ) : Object
Результат	Object

CloneFlatNetwork() публичный Метод

Clone into the flat network passed in.

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

Compute() публичный Метод

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.
Результат	void

ComputeLayer() защищенный Метод

Calculate a layer.

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

DecodeNetwork() публичный Метод

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.
Результат	void

EncodeNetwork() публичный Метод

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[]
Результат	double[]

FlatNetwork() публичный Метод

Default constructor.

public FlatNetwork ( ) : System
Результат	System

FlatNetwork() публичный Метод

Create a flat network from an array of layers.

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

FlatNetwork() публичный Метод

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.
Результат	System

HasSameActivationFunction() публичный Метод

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
Результат	System.Type

Init() публичный Метод

Construct a flat network.

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

Randomize() публичный Метод

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

public Randomize ( ) : void
Результат	void

Randomize() публичный Метод

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.
Результат	void