C# Class Encog.Neural.Networks.Prune.PruneIncremental

This class is used to help determine the optimal configuration for the hidden layers of a neural network. It can accept a pattern, which specifies the type of neural network to create, and a list of the maximum and minimum hidden layer neurons. It will then attempt to train the neural network at all configurations and see which hidden neuron counts work the best.

Inheritance: Encog.Engine.Concurrency.Job.ConcurrentJob

Afficher le fichier Open project: encog/encog-silverlight-core Class Usage Examples

Méthodes publiques

Méthode	Description
AddHiddenLayer ( int min, int max ) : void
LoadWorkload ( ) : int	Load all workloads, calculate how many networks we will examine.
NetworkToString ( BasicNetwork network ) : String	Format the network as a human readable string that lists the hidden layers.
PerformJobUnit ( JobUnitContext context ) : void	Evaluate one network.
Process ( ) : void	Begin process and find a good network.
PruneIncremental ( INeuralDataSet training, INeuralNetworkPattern pattern, int iterations, IStatusReportable report ) : log4net
RequestNextTask ( ) : Object	Request the next task, the next network to try.

Private Methods

Méthode	Description
GenerateNetwork ( ) : BasicNetwork
IncreaseHiddenCounts ( ) : bool

Method Details

AddHiddenLayer() public méthode

public AddHiddenLayer ( int min, int max ) : void
min	int
max	int
Résultat	void

LoadWorkload() public méthode

Load all workloads, calculate how many networks we will examine.

public LoadWorkload ( ) : int
Résultat	int

NetworkToString() public static méthode

Format the network as a human readable string that lists the hidden layers.

public static NetworkToString ( BasicNetwork network ) : String
network	BasicNetwork	The network to format.
Résultat	String

PerformJobUnit() public méthode

Evaluate one network.

public PerformJobUnit ( JobUnitContext context ) : void
context	Encog.Engine.Concurrency.Job.JobUnitContext	The job context.
Résultat	void

Process() public méthode

Begin process and find a good network.

public Process ( ) : void
Résultat	void

PruneIncremental() public méthode

public PruneIncremental ( INeuralDataSet training, INeuralNetworkPattern pattern, int iterations, IStatusReportable report ) : log4net
training	INeuralDataSet
pattern	INeuralNetworkPattern
iterations	int
report	IStatusReportable
Résultat	log4net

RequestNextTask() public méthode

Request the next task, the next network to try.

public RequestNextTask ( ) : Object
Résultat	Object