org.encog.ml.genetic

Class MLMethodGeneticAlgorithm

java.lang.Object

org.encog.ml.train.BasicTraining

org.encog.ml.genetic.MLMethodGeneticAlgorithm

All Implemented Interfaces:

MLTrain, MultiThreadable

public class MLMethodGeneticAlgorithm
extends BasicTraining
implements MultiThreadable

Implements a genetic algorithm that allows an MLMethod that is encodable (MLEncodable) to be trained. It works well with both BasicNetwork and FreeformNetwork class, as well as any MLEncodable class. 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 genetic algorithm how well suited a neural network is. If you would like to use genetic algorithms 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.

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
class	MLMethodGeneticAlgorithm.MLMethodGeneticAlgorithmHelper Very simple class that implements a genetic algorithm.

Constructor Summary

Constructors

Constructor and Description
MLMethodGeneticAlgorithm(MethodFactory phenotypeFactory, CalculateScore calculateScore, int populationSize) Construct a method genetic algorithm.

Method Summary

Modifier and Type	Method and Description
boolean	canContinue()
void	finishTraining() Should be called after training has completed and the iteration method will not be called any further.
MLMethodGeneticAlgorithm.MLMethodGeneticAlgorithmHelper	getGenetic()
MLMethod	getMethod() Get the current best machine learning method from the training.
int	getThreadCount()
void	iteration() Perform one training iteration.
TrainingContinuation	pause() Pause the training to continue later.
void	resume(TrainingContinuation state) Resume training.
void	setGenetic(MLMethodGeneticAlgorithm.MLMethodGeneticAlgorithmHelper genetic) Set the genetic helper class.
void	setThreadCount(int numThreads) Set the number of threads to use.

Methods inherited from class org.encog.ml.train.BasicTraining

addStrategy, getError, getImplementationType, getIteration, getStrategies, getTraining, isTrainingDone, iteration, postIteration, preIteration, setError, setIteration, setTraining

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

MLMethodGeneticAlgorithm

public MLMethodGeneticAlgorithm(MethodFactory phenotypeFactory,
                                CalculateScore calculateScore,
                                int populationSize)

Construct a method genetic algorithm.

Parameters:

phenotypeFactory - The phenotype factory.

calculateScore - The score calculation object.

populationSize - The population size.

Method Detail

canContinue

public boolean canContinue()

Specified by:

canContinue in interface MLTrain

Returns:

True if the training can be paused, and later continued.

getGenetic

public MLMethodGeneticAlgorithm.MLMethodGeneticAlgorithmHelper getGenetic()

Returns:

The genetic algorithm implementation.

getMethod

public MLMethod getMethod()

Get the current best machine learning method from the training.

Specified by:

getMethod in interface MLTrain

Returns:

The best machine learning method.

getThreadCount

public int getThreadCount()

Specified by:

getThreadCount in interface MultiThreadable

Returns:

The number of threads to use, 0 to automatically determine based on core count.

iteration

public void iteration()

Perform one training iteration.

Specified by:

iteration in interface MLTrain

pause

public TrainingContinuation pause()

Pause the training to continue later.

Specified by:

pause in interface MLTrain

Returns:

A training continuation object.

resume

public void resume(TrainingContinuation state)

Resume training.

Specified by:

resume in interface MLTrain

Parameters:

state - The training continuation object to use to continue.

finishTraining

public void finishTraining()

Description copied from class: BasicTraining

Should be called after training has completed and the iteration method will not be called any further.

Specified by:

finishTraining in interface MLTrain

Overrides:

finishTraining in class BasicTraining

setGenetic

public void setGenetic(MLMethodGeneticAlgorithm.MLMethodGeneticAlgorithmHelper genetic)

Set the genetic helper class.

Parameters:

genetic - The genetic helper class.

setThreadCount

public void setThreadCount(int numThreads)

Description copied from interface: MultiThreadable

Set the number of threads to use.

Specified by:

setThreadCount in interface MultiThreadable

Parameters:

numThreads - The number of threads to use, or zero to automatically determine based on core count.