C# Class Accord.Neuro.Layers.StochasticLayer

Inheritance: ActivationLayer

Méthodes publiques

Méthode	Description
Compute ( double input ) : double[]	Compute output vector of the layer.
CopyReversedWeightsFrom ( StochasticLayer layer ) : void	Copy the weights of another layer in reversed order. This can be used to update visible layers from hidden layers and vice-versa.
Generate ( double input ) : double[]	Compute probability vector of the layer.
StochasticLayer ( IStochasticFunction function, int neuronsCount, int inputsCount ) : Accord.Neuro.ActivationFunctions	Initializes a new instance of the StochasticLayer class.
StochasticLayer ( int neuronsCount, int inputsCount ) : Accord.Neuro.ActivationFunctions	Initializes a new instance of the StochasticLayer class.

Compute output vector of the layer.

public Compute ( double input ) : double[]
input	double	Input vector.
Résultat	double[]

Copy the weights of another layer in reversed order. This can be used to update visible layers from hidden layers and vice-versa.

public CopyReversedWeightsFrom ( StochasticLayer layer ) : void
layer	StochasticLayer	The layer to copy the weights from.
Résultat	void

Compute probability vector of the layer.

public Generate ( double input ) : double[]
input	double	Input vector.
Résultat	double[]

Initializes a new instance of the StochasticLayer class.

public StochasticLayer ( IStochasticFunction function, int neuronsCount, int inputsCount ) : Accord.Neuro.ActivationFunctions
function	IStochasticFunction	The activation function for the neurons in the layer.
neuronsCount	int	The neurons count.
inputsCount	int	The inputs count.
Résultat	Accord.Neuro.ActivationFunctions

Initializes a new instance of the StochasticLayer class.

public StochasticLayer ( int neuronsCount, int inputsCount ) : Accord.Neuro.ActivationFunctions
neuronsCount	int	Layer's neurons count.
inputsCount	int	Layer's inputs count.
Résultat	Accord.Neuro.ActivationFunctions