C# 클래스 Encog.Neural.Networks.Training.Anneal.NeuralSimulatedAnnealing

This class implements a simulated annealing training algorithm for neural networks. It is based on the generic SimulatedAnnealing class. It is used in the same manner as any other training class that implements the Train interface. There are essentially two ways you can make use of this class. Either way, you will need a score object. The score object tells the simulated annealing algorithm how well suited a neural network is. If you would like to use simulated annealing with a training set you should make use TrainingSetScore class. This score object uses a training set to score your neural network. If you would like to be more abstract, and not use a training set, you can create your own implementation of the CalculateScore method. This class can then score the networks any way that you like.
상속: Encog.ML.Train.BasicTraining
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공개 메소드들

메소드 설명
Iteration ( ) : void

Perform one iteration of simulated annealing.

NeuralSimulatedAnnealing ( BasicNetwork network, ICalculateScore calculateScore, double startTemp, double stopTemp, int cycles ) : Encog.ML

Construct a simulated annleaing trainer for a feedforward neural network.

Pause ( ) : TrainingContinuation
PutArray ( double array ) : void

Convert an array of doubles to the current best network.

Randomize ( ) : void

Randomize the weights and bias values. This function does most of the work of the class. Each call to this class will randomize the data according to the current temperature. The higher the temperature the more randomness.

Resume ( TrainingContinuation state ) : void

메소드 상세

Iteration() 공개 최종 메소드

Perform one iteration of simulated annealing.
public final Iteration ( ) : void
리턴 void

NeuralSimulatedAnnealing() 공개 메소드

Construct a simulated annleaing trainer for a feedforward neural network.
public NeuralSimulatedAnnealing ( BasicNetwork network, ICalculateScore calculateScore, double startTemp, double stopTemp, int cycles ) : Encog.ML
network BasicNetwork The neural network to be trained.
calculateScore ICalculateScore Used to calculate the score for a neural network.
startTemp double The starting temperature.
stopTemp double The ending temperature.
cycles int The number of cycles in a training iteration.
리턴 Encog.ML

Pause() 공개 메소드

public Pause ( ) : TrainingContinuation
리턴 Encog.Neural.Networks.Training.Propagation.TrainingContinuation

PutArray() 공개 메소드

Convert an array of doubles to the current best network.
public PutArray ( double array ) : void
array double An array.
리턴 void

Randomize() 공개 메소드

Randomize the weights and bias values. This function does most of the work of the class. Each call to this class will randomize the data according to the current temperature. The higher the temperature the more randomness.
public Randomize ( ) : void
리턴 void

Resume() 공개 메소드

public Resume ( TrainingContinuation state ) : void
state Encog.Neural.Networks.Training.Propagation.TrainingContinuation
리턴 void