C# Class Accord.Neuro.Networks.DeepBeliefNetwork

Inheritance: ActivationNetwork

Show file Open project: accord-net/framework Class Usage Examples

Public Methods

Method	Description
Compute ( double input ) : double[]	Computes the network's outputs for a given input.
Compute ( double input, int layerIndex ) : double[]	Computes the network's outputs for a given input.
CreateGaussianBernoulli ( int inputsCount ) : DeepBeliefNetwork	Creates a Gaussian-Bernoulli network.
CreateMixedNetwork ( IStochasticFunction visible, IStochasticFunction hidden, int inputsCount ) : DeepBeliefNetwork	Creates a Mixed-Bernoulli network.
DeepBeliefNetwork ( IStochasticFunction function, int inputsCount ) : System	Creates a new DeepBeliefNetwork.
DeepBeliefNetwork ( int inputsCount ) : System	Creates a new DeepBeliefNetwork.
GenerateInput ( double output ) : double[]	Samples an input vector from the network given an output vector.
GenerateOutput ( double input ) : double[]	Samples an output vector from the network given an input vector.
GenerateOutput ( double input, int layerIndex ) : double[]	Samples an output vector from the network given an input vector.
Load ( Stream stream ) : DeepBeliefNetwork	Loads a network from a stream.
Load ( string path ) : DeepBeliefNetwork	Loads a network from a file.
Pop ( ) : void	Removes the last layer from the network.
Push ( RestrictedBoltzmannMachine network ) : void	Stacks a new Boltzmann Machine at the end of this network.
Push ( int neurons ) : void	Inserts a new layer at the end of this network.
Push ( int neurons, IStochasticFunction function ) : void	Inserts a new layer at the end of this network.
Push ( int neurons, IStochasticFunction visibleFunction, IStochasticFunction hiddenFunction ) : void	Inserts a new layer at the end of this network.
Reconstruct ( double output ) : double[]	Reconstructs a input vector for a given output.
Reconstruct ( double output, int layerIndex ) : double[]	Reconstructs a input vector using the output vector of a given layer.
Save ( Stream stream ) : void	Saves the network to a stream.
Save ( string path ) : void	Saves the network to a stream.
UpdateVisibleWeights ( ) : void	Updates the weights of the visible layers by copying the reverse of the weights in the hidden layers.

Method Details

Compute() public method

Computes the network's outputs for a given input.

public Compute ( double input ) : double[]
input	double	The input vector.
return	double[]

Compute() public method

Computes the network's outputs for a given input.

public Compute ( double input, int layerIndex ) : double[]
input	double	The input vector.
layerIndex	int	The index of the layer.
return	double[]

CreateGaussianBernoulli() public static method

Creates a Gaussian-Bernoulli network.

public static CreateGaussianBernoulli ( int inputsCount ) : DeepBeliefNetwork
inputsCount	int	The number of inputs for the network.
return	DeepBeliefNetwork

CreateMixedNetwork() public static method

Creates a Mixed-Bernoulli network.

public static CreateMixedNetwork ( IStochasticFunction visible, IStochasticFunction hidden, int inputsCount ) : DeepBeliefNetwork
visible	IStochasticFunction	The to be used in the first visible layer.
hidden	IStochasticFunction	The to be used in all other layers.
inputsCount	int	The number of inputs for the network.
return	DeepBeliefNetwork

DeepBeliefNetwork() public method

Creates a new DeepBeliefNetwork.

public DeepBeliefNetwork ( IStochasticFunction function, int inputsCount ) : System
function	IStochasticFunction	The activation function to be used in the network neurons.
inputsCount	int	The number of inputs for the network.
return	System

DeepBeliefNetwork() public method

Creates a new DeepBeliefNetwork.

public DeepBeliefNetwork ( int inputsCount ) : System
inputsCount	int	The number of inputs for the network.
return	System

GenerateInput() public method

Samples an input vector from the network given an output vector.

public GenerateInput ( double output ) : double[]
output	double	An output vector.
return	double[]

GenerateOutput() public method

Samples an output vector from the network given an input vector.

public GenerateOutput ( double input ) : double[]
input	double	An input vector.
return	double[]

GenerateOutput() public method

Samples an output vector from the network given an input vector.

public GenerateOutput ( double input, int layerIndex ) : double[]
input	double	An input vector.
layerIndex	int	The index of the layer.
return	double[]

Load() public static method

Loads a network from a stream.

public static Load ( Stream stream ) : DeepBeliefNetwork
stream	Stream	The network from which the machine is to be deserialized.
return	DeepBeliefNetwork

Load() public static method

Loads a network from a file.

public static Load ( string path ) : DeepBeliefNetwork
path	string	The path to the file from which the network is to be deserialized.
return	DeepBeliefNetwork

Pop() public method

Removes the last layer from the network.

public Pop ( ) : void
return	void

Push() public method

Stacks a new Boltzmann Machine at the end of this network.

public Push ( RestrictedBoltzmannMachine network ) : void
network	RestrictedBoltzmannMachine	The machine to be added to the network.
return	void

Push() public method

Inserts a new layer at the end of this network.

public Push ( int neurons ) : void
neurons	int	The number of neurons in the new layer.
return	void

Push() public method

Inserts a new layer at the end of this network.

public Push ( int neurons, IStochasticFunction function ) : void
neurons	int	The number of neurons in the new layer.
function	IStochasticFunction	The activation function which should be used by the neurons.
return	void

Push() public method

Inserts a new layer at the end of this network.

public Push ( int neurons, IStochasticFunction visibleFunction, IStochasticFunction hiddenFunction ) : void
neurons	int	The number of neurons in the layer.
visibleFunction	IStochasticFunction	The activation function which should be used by the visible neurons.
hiddenFunction	IStochasticFunction	The activation function which should be used by the hidden neurons.
return	void

Reconstruct() public method

Reconstructs a input vector for a given output.

public Reconstruct ( double output ) : double[]
output	double	The output vector.
return	double[]

Reconstruct() public method

Reconstructs a input vector using the output vector of a given layer.

public Reconstruct ( double output, int layerIndex ) : double[]
output	double	The output vector.
layerIndex	int	The index of the layer.
return	double[]

Save() public method

Saves the network to a stream.

public Save ( Stream stream ) : void
stream	Stream	The stream to which the network is to be serialized.
return	void

Save() public method

Saves the network to a stream.

public Save ( string path ) : void
path	string	The file path to which the network is to be serialized.
return	void

UpdateVisibleWeights() public method

Updates the weights of the visible layers by copying the reverse of the weights in the hidden layers.

public UpdateVisibleWeights ( ) : void
return	void