C# Class Accord.Neuro.Learning.DeepBeliefNetworkLearning

Deep Belief Network learning algorithm.
Inheritance: IUnsupervisedLearning
Afficher le fichier Open project: accord-net/framework Class Usage Examples

Méthodes publiques

Méthode Description
ComputeError ( double inputs ) : double

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

DeepBeliefNetworkLearning ( DeepBeliefNetwork network ) : System

Creates a new DeepBeliefNetworkLearning algorithm.

GetLayerAlgorithm ( int layerIndex ) : IUnsupervisedLearning

Gets the unsupervised learning algorithm allocated for the given layer.

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[][]) 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[][]) to actually run a learning epoch.

Run ( double input ) : double

Runs a single learning iteration.

RunEpoch ( double input ) : 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
inputs double The input values.
Résultat double

DeepBeliefNetworkLearning() public méthode

Creates a new DeepBeliefNetworkLearning algorithm.
public DeepBeliefNetworkLearning ( DeepBeliefNetwork network ) : System
network Accord.Neuro.Networks.DeepBeliefNetwork The network to be trained.
Résultat System

GetLayerAlgorithm() public méthode

Gets the unsupervised learning algorithm allocated for the given layer.
public GetLayerAlgorithm ( int layerIndex ) : IUnsupervisedLearning
layerIndex int The index of the layer to get the algorithm for.
Résultat IUnsupervisedLearning

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[][]) 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[][]) 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
input double A single input vector.
Résultat double

RunEpoch() public méthode

Runs a single batch epoch of the learning algorithm.
public RunEpoch ( double input ) : double
input double Array of input vectors.
Résultat double