org.apache.ignite.ml.util.genetic

Class GeneticAlgorithm

java.lang.Object

org.apache.ignite.ml.util.genetic.GeneticAlgorithm

public class GeneticAlgorithm
extends Object

This class is an entry point to use Genetic Algorithm to solve optimization problem.

Constructor Summary

Constructors

Constructor and Description
GeneticAlgorithm(List<Double[]> paramSet)

Method Summary

Modifier and Type	Method and Description
double[]	getTheBestSolution() Returns the best chromosome's genes presented as double array.
void	run() The main method for genetic algorithm.
void	runParallel(LearningEnvironment environment) The main method for genetic algorithm.
GeneticAlgorithm	withAmountOfEliteChromosomes(int amountOfEliteChromosomes)
GeneticAlgorithm	withAmountOfGenerations(int amountOfGenerations)
GeneticAlgorithm	withCrossingoverProbability(double crossingoverProbability)
GeneticAlgorithm	withCrossoverStgy(CrossoverStrategy crossoverStgy)
GeneticAlgorithm	withFitnessFunction(Function<Chromosome,Double> fitnessFunction) Sets the custom fitness function.
GeneticAlgorithm	withMutationOperator(BiFunction<Integer,Double,Double> mutationOperator)
GeneticAlgorithm	withMutationProbability(double mutationProbability)
GeneticAlgorithm	withPopulationSize(int populationSize)
GeneticAlgorithm	withSelectionStgy(SelectionStrategy selectionStgy)

Methods inherited from class java.lang.Object

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

Constructor Detail

GeneticAlgorithm

public GeneticAlgorithm(List<Double[]> paramSet)

Parameters:

paramSet - The list of sets of parameter's values.

Method Detail

run

public void run()

The main method for genetic algorithm.

runParallel

public void runParallel(LearningEnvironment environment)

The main method for genetic algorithm.

Parameters:

environment - The environment.

withFitnessFunction

public GeneticAlgorithm withFitnessFunction(Function<Chromosome,Double> fitnessFunction)

Sets the custom fitness function.

Parameters:

fitnessFunction - Fitness function.

getTheBestSolution

public double[] getTheBestSolution()

Returns the best chromosome's genes presented as double array.

withAmountOfEliteChromosomes

public GeneticAlgorithm withAmountOfEliteChromosomes(int amountOfEliteChromosomes)

Parameters:

amountOfEliteChromosomes - Amount of elite chromosomes.

withAmountOfGenerations

public GeneticAlgorithm withAmountOfGenerations(int amountOfGenerations)

Parameters:

amountOfGenerations - Amount of generations.

withMutationOperator

public GeneticAlgorithm withMutationOperator(BiFunction<Integer,Double,Double> mutationOperator)

Parameters:

mutationOperator - Mutation operator.

withPopulationSize

public GeneticAlgorithm withPopulationSize(int populationSize)

Parameters:

populationSize - Population size.

withCrossingoverProbability

public GeneticAlgorithm withCrossingoverProbability(double crossingoverProbability)

Parameters:

crossingoverProbability - Crossingover probability.

withMutationProbability

public GeneticAlgorithm withMutationProbability(double mutationProbability)

Parameters:

mutationProbability - Mutation probability.

withCrossoverStgy

public GeneticAlgorithm withCrossoverStgy(CrossoverStrategy crossoverStgy)

Parameters:

crossoverStgy - Crossover strategy.

withSelectionStgy

public GeneticAlgorithm withSelectionStgy(SelectionStrategy selectionStgy)

Parameters:

selectionStgy - Selection strategy.