C# Class Accord.Neuro.Learning.DeepNeuralNetworkLearning

Deep Neural Network learning algorithm.

Inheritance: ISupervisedLearning

Afficher le fichier Open project: accord-net/framework Class Usage Examples

Méthodes publiques

Méthode	Description
ComputeError ( double inputs, double outputs ) : double	Computes the reconstruction error for a given set of input values.
DeepNeuralNetworkLearning ( DeepBeliefNetwork network ) : System	Creates a new DeepBeliefNetworkLearning algorithm.
GetLayerInput ( double input ) : double[][]	Gets the learning data needed to train the currently selected layer. The return of this function should then be passed to RunEpoch(double[][], double[][]) to actually run a learning epoch.
GetLayerInput ( double batches ) : double[][][]	Gets the learning data needed to train the currently selected layer. The return of this function should then be passed to RunEpoch(double[][], double[][]) to actually run a learning epoch.
Run ( double input, double output ) : double	Runs a single learning iteration.
RunEpoch ( double input, double output ) : double	Runs a single batch epoch of the learning algorithm.

Private Methods

Méthode	Description
createAlgorithms ( ) : void

Method Details

ComputeError() public méthode

Computes the reconstruction error for a given set of input values.

public ComputeError ( double inputs, double outputs ) : double
inputs	double	The input values.
outputs	double	The corresponding output values.
Résultat	double

DeepNeuralNetworkLearning() public méthode

Creates a new DeepBeliefNetworkLearning algorithm.

public DeepNeuralNetworkLearning ( DeepBeliefNetwork network ) : System
network	Accord.Neuro.Networks.DeepBeliefNetwork	The network to be trained.
Résultat	System

GetLayerInput() public méthode

Gets the learning data needed to train the currently selected layer. The return of this function should then be passed to RunEpoch(double[][], double[][]) to actually run a learning epoch.

public GetLayerInput ( double input ) : double[][]
input	double	The batch of input data.
Résultat	double[][]

GetLayerInput() public méthode

Gets the learning data needed to train the currently selected layer. The return of this function should then be passed to RunEpoch(double[][], double[][]) to actually run a learning epoch.

public GetLayerInput ( double batches ) : double[][][]
batches	double	The mini-batches of input data.
Résultat	double[][][]

Run() public méthode

Runs a single learning iteration.

public Run ( double input, double output ) : double
input	double	A single input vector.
output	double	The corresponding output vector.
Résultat	double

RunEpoch() public méthode

Runs a single batch epoch of the learning algorithm.

public RunEpoch ( double input, double output ) : double
input	double	Array of input vectors.
output	double	Array of corresponding output vectors.
Résultat	double